ISSN 2185-159X

erd

International Journal ofEnvironmental and Rural Development

Volume 12 Number 2

December 2021

International Society of Environmental and Rural Development

IJERD – International Journal of Environmental and Rural Development

erdInternational Journal ofEnvironmental and Rural Development
Official Journal of the International Society of Environmental and Rural Development(Accessible from J-Stage, EBSCO, Google Scholar, CABI International, etc.)

Aims and Scope:
The International Journal of Environmental and Rural Development, IJERD, is an interdisciplinary journal
concerning environmental and rural development research in the education for sustainable development, ESD.
The IJERD is devoted to publishing peer-reviewed research article, review article and technical report in thefields of environmental and rural development, such as education for sustainable rural development, ruraldevelopment, environmental management or agricultural systems. Every article or report in IJERD must be
accepted by at least 2 reviewers and an editorial member.
The aims of IJERD are to publish the latest research development and achievements, to strengthen
education systems, to promote cooperation in environmental and rural development and to contribute to theprogress in sustainable development. The editorial board of this journal covers a variety of scientificdisciplines.
Thematic Areas:
The following areas are envisioned in IJERD.
Education for Sustainable Rural Development:
Environmental Education, Food and Agricultural Education, Participatory Approach, Capacity Building,Community Empowerment, Agricultural Extension, etc.
Rural Development:
Marketing, Partnership, Value Added Product, Community Development, Access to Technology,
Cultural Preservation, etc.
Environmental Management:
Bio-Diversity, Soil Degradation and Land Conservation, Water Quality Conservation, Deforestation andSustainable Forest Management, Environmental Management, etc.
Agricultural Systems:
Organic Farming, Conservation Tillage, Mechanization, Irrigation and Drainage, Nutrient and Pest
Management, Cattle Breeding, Agro-Forestry, Indigenous Technology, etc.
Infrastructural Systems:
Water Resource Development, Land Reclamation, Road Construction, etc.
Editorial Board:
Editor in Chief:
Prof. Dr. Machito Mihara, Tokyo University of Agriculture, Japan /Institute of Environmental Rehabilitation and Conservation, Japan
Managing Editors:
Dr. Narong Touch, Tokyo University of Agriculture, Japan
Dr. Shinobu Terauchi, Institute of Environmental Rehabilitation and Conservation, Japan
Dr. Jeeranuch Sakkhamduang, Institute of Environmental Rehabilitation and Conservation,
Southeast Asia Office / Association of Environmental and Rural Development, Thailand
Editorial Advisory Board:
Prof. Dr. Mom Seng, Royal University of Agriculture, Cambodia
Dr. Insa Kuhling, University of Applied Sciences, Germany
Dr. Carlos Onan Tovar Mendoza, Honduras Embassy in Japan, HondurasProf. Dr. Noureddin Driouech, Mediterranean Agronomic Institute of Bari, Italy
Prof. Dr. Kiichiro Hayashi, Nagoya University, Japan
Prof. Dr. Kingshuk Roy, Nihon University, Japan
Dr. Yuri Yamazaki, Tokyo University of Agriculture, Japan
Prof. Dr. Merites M. Buot, University of the Philippines Los Baños, Laguna, Philippines /UP Open University, Philippines
Prof. Dr. Salvador Catello, University of the Philippines, Philippines
Prof. Tomas Reyes, Jr. Bohol Island State University, Philippines

IJERD – International Journal of Environmental and Rural Development

Dr. Julian Torillo, Jr. Bohol Island State University, Philippines
Dr. Venkatachalam Anbumozhi, International Centre for Trade and Sustainable Development,
Switzerland
Dr. Anchasa Pramuanjaroenkij, Kasetsart University, Thailand
Prof. Dr. Rajendra P. Shrestha, Asian Institute of Technology, Thailand
Dr. Somsak Srisontisuk, Khon Kaen University, Thailand
Dr. Vidhaya Trelo-Ges, Khon Kaen University, Thailand
Prof. Dr. Vo Quang Minh, Cantho University, Vietnam
Editorial Section in ISERD Secretariat:
Dr. Shinobu Terauchi and Dr. Takashi Ueno
Research Center, Institute of Environmental Rehabilitation and Conservation (ERECON)
2987-1 Onoji Machida-Shi, Tokyo 195-0064, Japan
Tel/Fax: +81-42736-8972
E-mail: iserd.secretariat@gmail.com
Webpage: www.iserd.net
Collaborated with

Association of Environmental and Rural Development (AERD)
93/64 Moo.3, Sinsab Village 2, Bungyeetho Sub-district, Thanyaburi District,Pathum Thani 12130, Thailand
Tel/Fax: +66-2957-8064
E-mail: iserd.secretariat@gmail.com
Webpage: www.iserd.net
Publisher of International Journal of Environmental and Rural Development:
Research Center, Institute of Environmental Rehabilitation and Conservation
2987-1 Onoji Machida-Shi, Tokyo 195-0064, Japan
Tel/Fax: +81-42736-8972
E-mail: hq-erecon@nifty.com
Webpage: www.erecon.jp

IJERD – International Journal of Environmental and Rural Development (2021) 12-2

Contents
The Application of Intervention Mapping in Developing a Parental Behavior Modification Programfor Pesticide Exposure Prevention Among Children in Agricultural Areas for a Sub-District Health
Promotion Hospital, Thailand
Satinee Siriwat, Apiradee Wangkahard,
Sriwipa Chuangchaiya and Chakkrit Ponrachom

1

Rice Varietal Assessment for Climate Change Adaptation from a Socioeconomic Point of View:
A Study in Myittha Township, Myanmar
Shwe Mar Than, Yin Nyein Aye and Yin Yin Thant

7

Soil Organic Carbon Stabilization on Forested and Deforested Red-yellow Soil under Different
Temperature Conditions
Arostegui, Keiji and Machito Mihara

13

Assessment of Some Promising Lines of Rice (Oryza sativa L.) for Salt Tolerance using
Microsatellite Markers Associated with the saltol QTL
Moe Kyaw Thu, Aung Naing Oo, Nyo Mar Htwe,
Ohn Mar Lynn and Khin Thida Myint

18

Evaluation of School Gardens as a Method of Scaling up Sustainable Agriculture Technologies
Gracie Pekarcik and David Ader

24

Factors Driving the Effectiveness of Community Fisheries Management Resulted from
Fisheries Policy Reforms
Kaing Khim, Hori Mina, Kang Kroesna and So Nam

34

Status of Cassava Production and Distribution Channels in Cambodia: Prospects for Sustainable
Production
Ito Kasumi, Nakatani Aya, Baba Tamon, Nomura Hisako,
Than Tha and Srean Pao

41

Contracting and Negotiation Attributes: A Case of Sunflower Seed Crop in Central Tanzania
Rubasha Matiku Mujama and Tomohiro Uchiyama

49

Possibility of Value Addition on Traditional Rice Liquor in Cambodia
Mitsuru Hamano, Takashi Kuroda, Chim Chay, Boratana Ung
and Kasumi Ito

56

Farmers` Perception on Contract Farming: A Case of Sunflower Seed Crop in Central Tanzania
Rubasha Matiku Mujama and Tomohiro Uchiyama

65

Factors Affecting the Teaching Attitude of High School Agriculture Teachers in the Philippines
Jennica Amielle M. Mora, Hiroki Inaizumi andNina N. Shimoguchi

71

Spatial Analysis of Yield Gaps Variability of Black Gram Based on GIS and Geostatistics
Htay Htay Oo and Khin Mar Oo

77

Effect of Farmers’ Attitude and Behavior in Farm Succession in the Philippines
Eliza C. Aquino, Hiroki Inaizumi, Nina N. Shimoguchi and
Satoshi Suzuki

83

The Challenges of Agribusiness Training on Livestock Farmers in Namibia
Norah Lydia Ngatjizeko, Hiroki Inaizumi andNina N. Shimoguchi

90i

IJERD – International Journal of Environmental and Rural Development (2021) 12-2

Visitor Perception and Economic Value Estimation of Mekarsari Fruit Garden as Agritourism
Destination in Indonesia
Ramadhina P. Indraswari, Kenji Okubo andNina N. Shimoguchi

98

The Effects of the Application of Compost and Chemical Fertilizer on the Growth and Yield of Rice(Oryza sativa L.)
Theingi Win, Swe Swe Mar, Kyi Kyi Shwe, Win Yu Hlaing,
Hsu Myat Thwin, Kyaw Ngwe and Toru Sakai

104

Production and Utilization of Crop Residues in Cambodia: Rice Straw, Corn Stalk, and Cassava Stem
Dyna Theng, Lytour Lor, Chhengven Chhoem,
Kanhara Sambath, Pisey Vong, Sorkunthika Srour,
Vathana Chamroeun, Davith Eang, Makara Lay,
Rajiv Pradhan and Gerald Hitzler

110

Water Harvesting Potential and its Maximization by the Application of Clayey Dressing
in Qargha Reservoir Watershed, Kabul, Afghanistan
Shafiqullah Rahmani, Ihsanullah Akramzoi and
Machito Mihara

116

Relationship between NDVI and Canopy Cover Sensed by Small UAV under Different Ground
Resolution
Ke Zhang, Hiromu Okazawa, Yuri Yamazaki,
Kiichiro Hayashi and Osamu Tsuji

122

Establishment of Optimized Manufacturing Conditions for Cooked Rice -Part IEquilibrium Moisture Content and Latent Heat of Vaporization of Cooked Rice
Yoshiki Muramatsu, Masanori Hashiguchi, Dahai Mi,
Sokly Sorm, Eiichiro Sakaguchi and Shotaro Kawakami

129

Establishment of Optimized Manufacturing Conditions for Cooked Rice -Part IIMoisture Transfer Kinetics of Cooked Rice when Drying and Soaking in Water
Yoshiki Muramatsu, Masanori Hashiguchi, Dahai Mi,
Sokly Sorm, Eiichiro Sakaguchi and Shotaro Kawakami

135

Bamboo Charcoal as a Lactic Acid Bacteria Carrier for Phosphate Removal
Takahiko Nakamura and Narong Touch

142

Contribution of Sustainability Rice Cultivation Practice for Farmers according to SRP Standard:
A Case Study of Ubon Ratchathani Province, Thailand
Narat Rattanacharoen and Ryuichi Yamada

148

Organic Agriculture Certification on Thai Agricultural Standard in Upper Northeast Thailand
Jiraphon Choeichit, Chuleemas Boonthai Iwai,
Sanitpim Simmatun and Waraphon Wongsiriwan

155

Application of APEX Model in Evaluating Streamflow and Sediment Yield in Stung Chinit
Catchment
Nareth Nut, Manuel R. Reyes, Gilbert Sigua, Machito Mihara,
Sakdanuphol Chan and taingaun sourn160

Effects of Chemical Extraction Methods on Physicochemical Properties of Shrimp Chitosan
Socheath Tong, Borarin Buntong, Laikong Sophal,
Sokmean Vann and Antonio Acedo Jr.

170

Evaluation of Organic Rice Contract Farming Model in Cambodia
Chanmony Sok, Tomohiro Uchiyama and Nina N. Shimoguchi

176

ii

IJERD – International Journal of Environmental and Rural Development (2021) 12-2

The Distance Learning Model on Cross-Cultural Agriculture: A Case Study of Thai and American
4-H clubSineenuch Khrutmuang Sanserm, Bumpen Keowan,
Benchamas Yooprasert, Nareerut Seerasarn andPonsaran Saranrom

182

A Case Study on Postharvest Handling Practices of Mango Fruits in Selected Areas of Myanmar
Than Than Soe, Nyein Nyein Htwe and May Thu Hlaing

189

Evaluation of Water Quality and Vegetable Production in Cheung Ek Lake, Cambodia
Oum Somara and Machito Mihara

194

Impacts of Land Use-Land Cover Changes on Streamflow and Water Balance of Stung Sangkae
Catchment using SWAT
Nareth Nut, Machito Mihara, Jaehak Jeong, Bunthan Ngo,
Sakdanuphol Chan, Gilbert Sigua and Manuel R. Reyes

201

The Possibility of Producing and Distributing Healthy Cassava Seeds in Cambodia
Tamon Baba, Hisako Nomura, Pao Srean, Tha Than andKasumi Ito

209

The Current Status of Cassava Producers and Healthy Cassava Seed Production and Distribution Trial
in Vietnam
Nien Chau Nguyen, Tamon Baba, Hisako Nomura andKasumi Ito

215

Measurement of Postharvest Losses of Sesame (Sesamum indicum L.) from Harvesting to Storageat Farm Level
Hnin Thida Nyo, Nyein Nyein Htwe and Kyaw Kyaw Win

223

iii

IJERD – International Journal of Environmental and Rural Development (2021) 12-2

Research article
erd

The Application of Intervention Mapping in Developing a
Parental Behavior Modification Program for Pesticide
Exposure Prevention Among Children in Agricultural Areas
for a Sub-District Health Promotion Hospital, Thailand
SATINEE SIRIWAT
Faculty of Public Health, Kasetsart University Chalermphrakiat Sakon Nakhon Province
Campus, Sakon Nakhon, Thailand

APIRADEE WANGKAHARD
Faculty of Public Health, Kasetsart University Chalermphrakiat Sakon Nakhon Province
Campus, Sakon Nakhon, Thailand

SRIWIPA CHUANGCHAIYA
Faculty of Public Health, Kasetsart University Chalermphrakiat Sakon Nakhon Province
Campus, Sakon Nakhon, Thailand

CHAKKRIT PONRACHOM*
Faculty of Education, Kasetsart University, Bangkok, Thailand
Email: ponrachom@hotmail.com
Received 30 December 2020

Accepted 9 July 2021(*Corresponding Author)

Abstract Child health problems in agricultural areas of Thailand are still a problem and must
be addressed urgently. This study used a research and development (R&D) design consistingof two phases. Phase 1 aimed to understand parental behavior regarding pesticide exposure
among children in agricultural areas. Data were collected by key informants with purposive
sampling that used focus group discussion (8 informants/group) from 5 groups of parents of
1-3 years old children living in agricultural areas in Sakon Nakhon Province, totaling 40
people. Data were collected by multiple parent focus group in Sakon Nakhon Province. Data
collected was then analyzed using content analysis. Phase 2 aimed to develop and study thequality of a parental behavior modification program for pesticide exposure prevention amongchildren in agricultural areas. The results in phase 1 were used as input factors to develop theforeside program by the Intervention Mapping ( IM) . The developed program was then tests
and reviewed by nine experts. Data were analyzed with mean and standard deviation. We
found that parent’s behavior in preventing pesticide exposure in their children was influenced
by a least three factors, namely: attitudes toward pesticide exposure in their children, social
norms and perceived behavioral control about pesticides exposure in their children. This
meets the basic structure of Theory of Planned Behavior. The second phase involved
developing a parental behavior modification program for pesticide exposure prevention inchildren in agricultural areas for a Sub-District Health Promotion Hospital. The componentsof the developed program were:1) background and significance; 2) objective; 3) organization;4) role of involved people; 5) guidelines for organizing four learning activities for the parent
behavior modification program; 6) monitoring and evaluation and 7) program management.
The results of the program’s quality assessment found that the overall quality of the programis in a very good level. When considered each aspect, it was found that all aspects; accuracy
standard, utility standard, appropriateness standard, feasibility standard and generalizability
standard were in very good quality as well. The findings of this study suggest that thedeveloped program should be implemented with parents who had desirable pesticide
exposure prevention behaviors.
Keywords theory of planned behavior, pesticide exposure, prevention behavior,
health program modification, intervention mapping (IM)Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2021) 12-2

INTRODUCTION
44.36 percent of land in Thailand is agricultural. The Northeast of the country has the mostagricultural land, up to 63.86 percent of the entire country (OAE, 2020). Pesticides are used inagricultural societies for pest, insect and disease control (U.S. EPA, 2015). In 2011-2017, Thailand
imported more than one hundred thousand tons of pesticides (OAE, 2020). While pesticides arewidely used in agriculture society and households, the exposure to pesticides in large quantities
affects human health and the environment (Snelder et al., 2008). Symptoms of pesticide exposure
can include skin irritation, nausea, vomiting, loss of appetite, cough, runny nose, etc. When ingested,organophosphate and carbamate pesticides will inhibit the activity of choline esterase in red blood
cells, which can result in both acute and chronic health problems (Suarez-Lopez et al., 2012).
Especially, in children, very sensitive to chemicals more than adults because of ages, development,
behavior and hygiene that may lead to a greater risk of exposure to environmental contaminants thanadults (WHO, 2019; Curwin et al, 2007). Children living in agricultural societies are exposed topesticides at a much higher rate than those living in other areas (Panuwet et al., 2008; Petchuay etal., 2006; Lu et al., 2000). They may be at high risk from exposure to pesticides both from agriculturalactivities and farmer families (Suarez-Lopez et al., 2012). Young children (1-3 years old) living inan agricultural areas are likely to have play activities on the ground in contact with the soil, bothindoors and outdoors. This puts them greatly at risk of being exposed to agricultural pesticides(Curwin et al, 2007; U.S. EPA, 2008). Studies on pesticide exposure in 1-3 years old children living
in agricultural areas in Sakon Nakhon Province found pesticides on children’ hands skin up to 60
percent of the children surveyed (Siriwat et al., 2019). This is consistent with the annual report ofcases of pesticide poisoning in 2014-2016 of the Department of Disease Control, Ministry of Public
Health, which found that Sakon Nakhon Province is the top 10 provinces of the country with highest
number of cases of chemical poisoning and residues by pesticides on health symptoms may include
contact dermatitis, nausea, sweating, diaphoresis, lacrimation, diarrhea, salivation and headache inchildren under the age of 5 years.
Although various departments involved in managing diseases from poisoning and pesticides inchildren have been looking for solutions, previous studies show that the problem is not truly solved( Siriwat et al., 2019) . One reason may due to pesticide prevention behavior in the individual orparents. There are multiple factors, mostly related to parent's internal issue and external factors in
the environment, consisting of physical environment and social environment. However, whenanalyzing the causal factors leading to real and sustainable behavior change, causal factors fromindividuals seem more important as external factors are constantly changing due to a dynamic
society. Therefore, finding causal factors of pesticide prevention behavior in children’ patients ( asopposed to factors unique to the individual) might result in the design of behavior change program
for the target group that is sustainable.
After reviewing the literature of effective and efficient parental behavior modification programsin the prevention of pesticides exposure in children living in agricultural areas, we found that there
is no such program in Thailand that focuses on solving the problem using an individual model.
Meanwhile, Intervention Mapping (IM), a model that integrates theory and empirical evidence forplanning and designing health promotion and health education (Bartholomew et al., 2006), has beensuccessfully applied in many countries (Voogt, et al., 2014; Kwak et al., 2006; Tortelo et al., 2005).
IM as an alternative way for health educators and health promoters to plan and design health behavior
development leading to effective health promotion and health education program. The research team
aimed to apply IM as a basis for planning, designing and building a high quality and practical parental
behavior modification program in the prevention of pesticides exposure among children living in
agricultural areas to result in the prevention of pesticide exposure among children living in
agricultural areas.
OBJECTIVEⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2021) 12-2

This study, therefore, aims to develop and study the quality of a parental behavior modification
program for pesticide exposure prevention among children in agricultural areas for a Sub-District
Health Promotion Hospital in Sakon Nakhon Province, Thailand.
METHODOLOGY
Research Design
This research was conducted as a research and development (R&D) by dividing into two phases.
Phase 1 was the search for the internal causal factors of parents with children aged 1-3 years inagricultural areas. The research results were input and applied as data in Phase 2 for the development
and study of the quality of the developed program by applying IM as a base for development because
IM is a systematic process in developing a program design that promotes health and health education.
More importantly, its application based on the concept and the theory integrated with empirical datafor designing health promotion and health education program used for planning before implementing
with a blueprint., as follows:
Phase 1 began with the implementation of Step 1 of IM: conduct a needs assessment or problem
analysis using a qualitative research process with focus group discussion. A group of key informants
included 40 parents of 1-3 years old children who were selected by purposive sampling (Palys, 2008)
with the following criteria: 1) parents of 1-3 years old children living in agricultural areas in Sakon
Nakhon Province for more than 1 year, 2) parents who were taking care of their children closely andliving in the same house, 3) residential area was within 50 meters radius away from the agriculturalareas, and 4) being voluntary participants in the study by signing a consent form for human research
ethics. Together, there were 5 groups of informants from 5 agricultural areas in Sakon Nakhon
Province, grouped into 8 people each, resulting in 40 informants.
Phase 2 was conducted with the process of Step 2 - 6 of IM, including; Step 2: create matricesof change objectives based on the determinants of behavior, Step 3: Select theory-based intervention
methods and practical strategies, Step 4: translate methods and strategies into an organized program,
Step 5: Plan for adoption, implementation, and sustainability of the program, and Step 6: Generate
an evaluation plan. The program was drafted by the research team and quality was evaluated by nine
experts ( 3 experts of behavioral research scientist, 3 experts of environmental health researchscientist, and 3 experts of children health).
Research Instruments
There are two separate instruments used in phase1 and phase 2 detailed as follows:
Phase 1: For the range of questions used in group discussion, the researchers applied a semistructured interview based upon a review of the literature regarding parent behavior and causal
factors for the prevention of pesticide exposure among 1-3 years old children ( Adgate and Sexton,
2001). The interview guideline consisted of an open-ended questionnaire for informants to freely
express their opinions and own feelings freely. Accuracy and comprehensiveness of the content aswell as appropriateness of the question were reviewed by three experts.
Phase 2: The program quality assessment form assessed standards of accuracy, utility,
appropriateness, feasibility and generalizability, as well as an overview of the program. The rating
scale had five quality levels: very good, good, moderate, fair and needs improvement (Best, 1977).
Ethical Approval
Ethical approval was obtained from the Human Research Ethics Committee, Kasetsart University,
Bangkok, Thailand. (COA No. COA62/046 approved dated 2019/December/2).
Data AnalysisⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2021) 12-2

Phase 1, content analysis with a three-stage process of data reduction, data display, and drawing
conclusions/ verification (Miles et al., 2018). Phase 2, means, and standard deviation.
RESULTS AND DISCUSSION
Phase 1 Participants’ characteristics. The majority of participants were female (95.0%), ages ranging
from 20 to 60 years ( Mean = 40.7) , with educational levels ranging from elementary school todiploma level, All the informants worked as cantaloupe melon, chili, potato and tomato farmers. The
relationship with children aged 1 - 3 years, mothers (52.5%). The important research findings are as
follows: parents still had unwanted pesticide prevention behavior for children in agricultural areas
reflected in three areas of parents' individual behavior:
1) Unpreventable exposure: Parents were aware that children living in the agricultural areas often
cannot avoid being exposed to pesticides. Even though children might not be taken to agriculturalareas where chemicals are applied, chemicals still might get to their bodies by unavoidable touchingfrom someone else. This parental internal factors made parents sometimes unable to take care of theirchildren to prevent pesticide exposure, even when they wanted to do so.
2) Everyone must accept the condition: Parents recognized that people who influences them areparents of other 1-3year old children living in the same community, village or agricultural areas,
Most of their child care is no different. Parents often had expectations and decision making which
followed their reference group.
3) Difficulty of parental duty: Parents believed it is difficult to control or take action for very young
children in their care, even to prevent or reduce pesticide exposure. Particularly when parents weretaking care of their children alone, they believed that they were unable to perform demanding
pesticide prevention for their children.
In Phase 2, the research team applied the results of Phase 1 as input to develop a program, byfollowing the Step 2-6 of IM.
Parental behavior modification program in the prevention of pesticide exposure in children
living in agricultural areas was a program for Sub-District Health Promotion Hospital as it is a
department close to farmers and children aged 1-3 years. The research team focused on the practicaland integration principles in designing this program with the following elements of the program.
1) Background and significance: Principles of parental health behavior modification to care andprotect 1-3 years old children from pesticides in agricultural areas.
2) Objective: Modify the internal behavior of the parents based on the findings, including (1)attitudes toward pesticide exposure in their children, (2) social norms and (3) perceived behavioral
control about pesticides exposure in their children, in order to achieve desirable parental behavior inpreventing exposure to pesticides in children aged 1 - 3 years.
3) Organization: Sub-District Health Promotion Hospital that operates the program in the future,and the District Public Health Office that controls, monitors and directs the effective use of the
program.
4) Role of involved people: (1) Director of Sub-District Health Promotion Hospital who supports
and drives the implementation of the program, (2) program users who are the Public Health Officer
of Sub-District Health Promotion Hospital and Village Health Volunteer (VHV), and who are also
responsible for studying the program, and (3) parents of 1-3 years old children who are responsible
for participating in the program and implementing the program for their children in a concretemanner.
5) Guidelines for four learning activities for the parent behavior modification program:
Learning Activity 1 - It can be prevented with understanding; Learning Activity 2 - Everyone cantake good care of their children; Learning Activity 3 - Believe that you can do it; and, Learning
Activity 4 - Visit and follow up “Can it be done?”. The four learning activities took six hours tocomplete, divided into three learning activities integrated and organized by Public Health Officers
over 4.5 hours and another learning activity organized by VHVs for 1.5 hours.

Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2021) 12-2

6) Monitoring and evaluation: The program was conducted in three phases with objective
questionnaires, including the phase before using the program, the phrase right after using the
program, and the follow-up phase 3 months the program.
7) Program management: District Public Health Office must have at least one responsible person
for monitoring and evaluating the overall program. There was also the program server to implement
the program by adapting it to the context of the organization, report the results of the program usage
to the management team and then also delivery suggestions to improve and develop the program
after completing it.
Quality assessment tools placed the overall quality of the program is the “very good” range.
Each standard, individually, also fell in the “very good” quality range (Table 1).
Table 1 Number and percentage of program quality from the improvement
Program quality
Accuracy standard
Utility standard
Appropriateness standard
Feasibility standard
Generalizability standard
Overall program quality

Mean
4.56
4.89
4.22
4.56
4.22
4.67

SD.
.527
.333
.972
.527
.441
.500

Interpretation
Very good
Very good
Very good
Very good
Very good
Very good* 9 experts were evaluated the quality of program.

Parental behavior in the prevention of pesticide exposure among 1-3 years old children living
in agricultural areas did not meet the desirable level due to at least three important individual causal
factors. This could be explained by the Theory of Planned Behavior (TPB) (Ajzen, 1991), whichholds that human behavior is guided by three beliefs, including behavioral beliefs, normative beliefs
and control beliefs. Each belief influenced various variables, including attitude toward behavior,social norms and perceived behavioral control, respectively, which also affected behavioral intention
leading to behavior as a result. The developed program applied IM as a model development inplanning and designing this program, because IM was a model for integrating theory and empiricalevidence for the design of health promotion and health education (Bartholomew et al., 2006). The
design was essential to rely on behavioral science theory together with empirical evidence for codesign (Kok, et al., 2004). The results of this research applied the findings from Phase 1 as an input
for the design and development by applying all 6 steps of IM until the program achieved a very goodlevel of quality that was also practical and possible to be integrated into the Sub-District Health
Promotion Hospital.
CONCLUSION
This study described a parental behavior modification program for pesticide exposure prevention
among children in agricultural areas for a Sub-District Health Promotion Hospital with theapplication of IM. The program was able to reach a “very good” quality level. This study suggeststhat public health agencies in agricultural areas where pesticide exposure is a problem might placesuch program into practice by integrating with the routine work of those agencies in such a way thatthey fit sustainably into the life context of local people and society.
ACKNOWLEDGEMENTS
This research is sponsored by Health System Research Institute ( HSRI) , Thailand. Appreciation ismade to the Executive Director of Health System Research Institute; Sakon Nakhon Provincial Public
Health Officers; Muang district, Tao Ngoi district and Phanna Nikhom district Public Health Office,who provided assistance and support for conducting the research. We would also like to thank all of
the participants in this research who gave great attention to this work in order to help develop theircommunity.
Ⓒ ISERD

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Panuwet, P., Prapamontol, T., Chantara, S., Thavornyuthikarn, P., Montesano, M.A., Whitehead, R.D. andBarr, D.B. 2008. Concentrations of urinary pesticide metabolites in small-scale farmers in Chiang Mai
Province, Thailand. Sci. Total Environ., 407 (1), 655-668.
Petchuay, C., Visuthismajarn, P., Vitayavirasak, B., Hore, P. and Robson, M. 2006. Biological monitoring oforganophosphate pesticide in preschool children in an agricultural community in Thailand. Int. J. Occup.
Environ. Health, 12 (2), 133-141.
Siriwat, S., Ong-artborirak, P., Nganchamung, T., Robson, M.G. and Siriwong, W. 2019. Exposure ofchlorpyrifos in toddlers living in an agricultural area in Sakon Nakhon Province, North-East Thailand.
J. Health Res., 33 (2), 151-161.
Snelder, D.J., Masipiquena, M.D. and Snoo, G.R. 2008. Risk assessment of pesticide usage by smallholder
farmers in the Cagayan Valley (Philippines). Crop Prot, 27 (3), 747-762.
Suarez-Lopez, J.R., Jacobs Jr, D.R., Himes, J.H., Alexander, B., Lazovich, D.A. and Gunnar, M. 2012. Lower
acetylcholinesterase activity among children living with flower plantation workers. Environ. Res., 114 (3)53-59.
Tortelo, S.R., Markham, C.M., Parcel, G.S., Peters, R.J., Escobar-Chaves, S.L., Basen-Engquist, K. and Lewis,
H.L. 2005. Using intervention mapping to adapt an effective HIV, sexually transmitted disease, andpregnancy prevention program for high-risk minority youth. Health Promot. Pract., 6 (3), 286-298.
U.S. EPA. 2008. Child-specific exposure factors handbook. U.S. Environmental Protection Agency, Policy
and Approved for Publication, Washington D.C., USA.
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U.S. Environmental Protection Agency, Washington D.C., USA.
Voogt, C.V., Poelen, E.A., Kleinjan, M., Lemmers, L.A. and Engles, R.C. 2014. The development of a webbased brief alcohol intervention in reducing heavy drinking among college students, An intervention
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social_determinants/sdh_definitionen/Ⓒ ISERD

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Research article
erd

Rice Varietal Assessment for Climate Change Adaptationfrom a Socioeconomic Point of View: A Study in Myittha
Township, Myanmar
SHWE MAR THAN*
Department of Participatory Knowledge Management, Advanced Center for Agricultural
Research and Education, Yezin Agricultural University, Myanmar
Email: dr.shwemarthan@yau.edu.mm

YIN NYEIN AYE
Department of Participatory Knowledge Management, Advanced Center for Agricultural
Research and Education, Yezin Agricultural University, Myanmar

YIN THANT
Department of Participatory Knowledge Management, Advanced Center for Agricultural
Research and Education, Yezin Agricultural University, Myanmar
Received 31 December 2020

Accepted 9 July 2021(*Corresponding Author)

Abstract Myanmar is the second most vulnerable country in the world to the effects ofclimate change, with agriculture highly vulnerable. This study was conducted to determine
farmers’ knowledge on how to respond to the impacts of climate change, to identify climateresilient adaptation technologies in rice farming, to also identify the desired characteristics ofchosen rice varieties, and to estimate the cost and benefits for different rice production
systems for the chosen varieties. The study was carried out in Myittha Township, a major
rice-growing area in the middle of Myanmar. Most of the rice areas are irrigated. Primarydata were collected by conducting a socio-economic survey. Descriptive analysis and costbenefit analysis were applied. More than 95 percent of the farmers adopted an adaptation
strategy of using quality seeds. A change to the time of sowing, was favored by only 27% of
respondents. About 41% of farmers grew Manaw Thukha rice variety, followed in popularity
by Ayeyar Min (33.62%), and Shwe Manaw (20.49%) varieties. The traits of rice variety
most desired were high yield and high marketability. The farmers practiced two different
methods of rice establishment: direct seeding and transplanting, and grew in both monsoon
and summer seasons. In monsoon, direct-seeded Ayeyarmin achieved the highest BCR (1.75)
whereas the Manaw Thukha variety yielded the highest BCR in summer (1.70). The study
area is an irrigated rice-growing area and has not yet suffered much from climate change
impacts on rice production. This is despite a trend to scarcity of rainfall, which implies that
improved irrigation facilities will comprise an essential adaptation strategy.
Keywords farmers’ perception, knowledge, climate change adaptation, rice variety,irrigation facilities

INTRODUCTION
In many empirical studies, climate change is manifest in various forms, such as changes intemperature and rainfall patterns, more frequent extreme climate events (e.g. floods, typhoons,droughts, storms, etc.), unusual timing of seasons, and sea level rise (Apata et al., 2009; Deressa etal., 2011; Mertz et al., 2009; Smit et al., 1996; Thomas et al., 2007; Vedwan and Rhoades, 2001).
Climate change adaptation is one policy option to reduce the negative consequences of the climatechange. Adaptation to climate change is a critical issue for many developing economies. The issue
is particularly important to agriculture, as this sector which relies substantially on climate-sensitive
resources, is highly vulnerable to climate change. Rice remains the staple food in Myanmar, andMyanmar is the world’s sixth-largest rice producing country. Rice is the country’s most importantⒸ ISERD

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crop and is grown on over 8 million hectares, or more than half of the arable land. Rice is also themost important crop for millions of small farmers who grow it on millions of hectares throughout theregion, and to the many landless workers who derive income from working on these farms. Empiricalstudies assessing the rice varieties best suited for climate change adaptation are limited in the
Myanmar context.

Fig. 1 Climate change scenario maps for Myittha Township with RCP 4.5 scenario
Previously, monsoon began in mid-May and ended in mid-October whereas it now begins at theend of May and ends at the end of September. That is, the monsoon season has shortened by about
40 days (Aung, 2019). A longer pre- and post-monsoon period has been observed, and may result in
extreme weather such as thunder, lightning, hailstorms and thunder showers. To reflect probableclimate change impacts on the study area, the climate change scenario maps were developed for
rainfall patterns for a Representative Concentration Pathway (RCP) 4.5 scenario (Fig. 1). A RCP 4.5
is a scenario that stabilizes radiative forcing at 4.5 W m−2 in the year 2100 without ever exceedingthat value (Thomson et al., 2011). These scenario maps convinced the continuation of climate change
in future.
OBJECTIVESThis paper makes a general investigation of a rice variety to determine its suitability for climatechange adaptation from a socioeconomic point of view. However, the specific objectives of the study
are as follows:- to determine farmers’ knowledge of responses to the impacts of climate change on agriculture,- to explore location-specific climate resilient adaptation technologies in rice farming,- to determine the desired characteristics of any rice varieties chosen, and- to estimate cost and benefits of different rice production systems for the chosen varieties
METHODOLOGY
Selection of the Study Area
Myittha Township, which is located in Kyaukse District, Mandalay Region, central Myanmar, wasselected as the study area. It is situated at 21◦ 25̍ North, and 96◦ 8̍ East. It is a major rice growing areaand most of the rice grown is irrigated. The survey was conducted in Yit Kan, Yakhaing Gyi, Ku
Phyu and Ngar Su villages in 2018. The total number of respondents was 122. Data collection was
carried out using a simple random sampling method and by the use of a structured interview schedule.
For data analysis, descriptive analysis and cost and benefit analysis were calculated using
Microsoft office excel and the software, STATA (Version 14). Mean, minimum, maximum, standard
deviation, frequency and percentage values were applied to reveal the indigenous knowledge of
farmers on how to respond climate change impacts, the preferences of farmers of traits for suitable
rice varieties, and any climate adaptation strategies practiced by farmers in the study area.
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Enterprise Budget
The following equations were used to do enterprise budgeting and to estimate the benefit-cost ratio;
Costs for cash and non-cash material inputs, hired labor, family labor and interest on cash, were
calculated to obtain the total production cost.
Return above variable cash cost
= Total gross benefit – Total variable cash cost
Gross margin= Total gross benefit – Total variable cost
Benefit Cost Ratio (BCR)= Total gross benefit / Total variable cost
Return per unit cash cost
= Total gross benefit / Total cash cost ×100
RESULTS AND DISCUSSION
Characteristics of the Farmers in the Study Area
The average age of the respondents in the study area was 51.69 years. The youngest age was 19 years
and the oldest age was 80 years. The range of farming experience was from 0 to 53 years with anaverage of 24.75 years. Average length of schooling of respondents was 4.66 years, with a range
from 0 (illiterate) to 20 years (tertiary qualifications). Respondents had an average 5.69 acres oflowland farming area. Land ownership ranged from 0 (landless) to 50 acres. The average uplandfarming area possessed by the respondents was 2.44 acres. The minimum and maximum uplandownership areas were from 0 to 15 acres. Farmers also had 0.39 acres of orchard area on average. In
general, the respondents can be described as elderly with low (primary) formal education but withhigh levels of farming experience.
Table 1 Demographic information of respondents in the study area
Item

Unit

Average

SD

Age

Year

51.69 (19-80)

12.18

Farming ExperienceYear24.75 (0-53)

12.29

Education (Schooling years)Year

4.66 (0-20)

3.10

Ownership of Lowland

Acre

5.69 (1-50)

5.92

Ownership of UplandAcre

2.44 (0-15)

3.70

Ownership of Orchard

Acre

0.39 (0-8)

1.25*Values in parentheses represent range.

Indigenous Knowledge of Farmers to Respond Climate Change Impacts
Seventeen agricultural practices, based on farmers’ indigenous knowledge of climate change
adaptation, were identified in the survey. More than one quarter of respondents (25.41%) havechanged varieties grown and another 25 percent have changed crops, for example, by now growing
summer rice instead of sesame. Changed cropping systems and crop management practices werepracticed by 17.22% of farmers. Other indigenous responses to climate change impacts were throughchanging sowing time (6.56%), growing varieties of shorter duration (5.74%), using chemical inputs
differently (4.92%), applying FYM (3.28%), using better quality seeds (3.28%), using undergroundwater (2.46%), practicing the line sowing method (2.46%), changing cropping patterns (1.64%),
using irrigation water (1.64%), growing more marketable varieties (1.64%), practicing crop rotation(0.82%), growing low-cost crops (0.82%), changing seeds yearly (0.82%) and the willingness toadopt organic farming (0.82%) (Fig. 2). In the study area, it can be assumed that farmers are awareof climate change and are actively adapting to changes.

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Climate Resilient Adaptation Technologies
Adapting to climate change requires that the correct measures, utilizing appropriate adjustments andchanges, are made to reduce negative effects.

Fig. 2 Indigenous knowledge of farmers to respond climate change impacts (n=122)
Table 2 Climate change adaptation strategies practiced by farmers
in Myittha Township (n=122)
No.

Adaptation Strategies

Frequency

Percent (%)

1

Using quality seeds

115

95

2

Using fertilizers

108

89

3

Using Farm Yard Manure (FYM)

98

81

4

Changing crop types

98

81

5

Changing varieties

96

79

6

Practicing crop rotation

92

76

7

Changing cultural practices

91

75

8

Using traditional varieties

43

36

9

Using underground water

38

31

10

Changing sowing time

33

27

Table 2 ranks ten climate adaptation strategies, practiced by farmers in the study area. Almost
all respondents (95%) used quality seeds. Most were using fertilizers (89%), using farm yard manure(FYM) (81%), changing crop type (81%), changing variety (79%) and practicing crop rotation (76%)
followed by using traditional varieties (36%), making use of underground water (31%) and changes
to sowing time (27%). Results show almost all respondents were using quality seeds as a climatechange adaptation strategy. This reflects that seed is the basic and most vital input of agriculture.
Without high quality seed, other inputs and better technologies remain worthless.
Desired Characters of the Rice VarietiesⒸ ISERD

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Rice variety traits and characteristics such as high yield, market price, eating quality, seed quality,
pest and disease resistance, good milling recovery and resistance to climate change were found to bewhat respondents prioritized. Most farmers (76.47%) desired high yielding varieties with high market
price, whereas good eating quality, good quality seeds were the desired characteristics sought by
46.93%, 44.16% and 41.05% of farmers respectively. Fewer farmers (22%), (12.31%) and (10.95%)
prioritized pest and disease resistance, good milling recovery and resistance to climate change (Fig.
3). From this it can be assumed most farmers in the study area have not suffered severely from theimpacts of climate change to this point.

Fig. 3 Farmers' preference on rice variety traits (n=122)
Cost and Benefit Analysis of Rice Varieties
Cost and benefit analysis of selected rice varieties in both summer and monsoon was made and theresults are presented in Table 3. Farmers practiced two different rice establishment methods:
transplanting and direct seeding and grew throughout both seasons. Only the Manaw Thukha rice
variety was grown, using both methods, in summer, with other varieties not grown in summer using
only direct seeding. The Manaw Thukha rice variety exhibited a higher Benefit Cost (BC) ratio (1.70)
when transplanted compared to the direct seeding method (1.64), in summer. Also in summer, GW1
gave the highest BC ratio (2.16) of all rice varieties grown after transplanting. GW1 is a Chinese
hybrid rice, and although it showed the highest BC ratio, few farmers grew it. It is a newly introduced
variety whose plant characteristics and yield potential are not well known. In monsoon season, theShwe Manaw variety gave the highest BC ratio (1.65) of all rice varieties using transplantation, and
the Ayeyar Min variety gave the highest BC ratio (1.75) when the direct seeding method was used.
Table 3 Cost and benefit analysis of selected rice varieties by establishment methodsⒸ ISERD

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CONCLUSION
According to the survey results, farmers in the study area appear to have a good knowledge, anddeveloped local strategies to adapt to the effects of climate change, evidenced by practices such as
using quality seeds, using fertilizers, employing FYM and changing crop types in their efforts to copewith the impacts of climate change. Switching to high yielding varieties is mostly favored. During
monsoon, direct seeding methods yielded higher BC ratios for all varieties. In summer, farmers did
not practice direct seeding method much because they are able to irrigate to manage their nursery.
Thus, irrigation facilities become essential infrastructure for successful climate change adaptation
strategies.
ACKNOWLEDGEMENTS
We would like to gratefully acknowledge the Japan International Cooperation Agency (JICA) for
their technical and financial support, not only for the Project of Capacity Development of Yezin
Agricultural University, but also for financial support for this study. We also would like to thankYezin Agricultural University for giving us an opportunity to do research. Special thanks toGovernment officials and staff from the Department of Agriculture (Myittha Township) and thefarmers in the study area for their keen cooperation, support and participation throughout the study.
REFERENCES
Apata, T.G., Samuel, K.D. and Adeola, A.O. 2009. Analysis of climate change perception and adaptation
among arable food crop farmers in South Western Nigeria. International Association of Agricultural
Economists, 2009 Conference, Beijing, China.
Aung, M.M. 2019. Preparing for next disaster. Retrieved from https://www.mmtimes.com/news/ preparingnext-disaster.html
Deressa, T.T., Hassan, R.M. and Ringler, C. 2011. Perception of and adaptation to climate change by farmers
in the Nile basin of Ethiopia. Journal of Agricultural Science, Retrieved from https://doi.org/10.1017/
S0021859610000687
Francisco, H., Nabangchang, O., Bui, D.T. and Yusuf, A.A. 2008. Climate change: Impacts, adaptation, andpolicy in Southeast Asia. Proceedings of EEPSEA Conference on 13-15 February 2008, Bali, Indonesia,
Retrieved from https://www.mmtimes.com/news/preparing-next-disaster.html
IPCC. 2001. Climate change 2001: The scientific basic contribution of working group I to the third assessment
report. The Intergovernmental Panel on Climate Change, Retrieved from http://www.ipcc.ch/ipccreports/tar/wg1/518.htm
IPCC. 2007. IPCC fourth assessment report: Climate change 2007. Retrieved from http://www.ipcc.ch/publications_and_data/publications_and_data_reports.shtml
Mertz, O., Mbow, C., Reenberg, A. and Diouf, A. 2009. Farmers’ perceptions of climate change andagricultural adaptation strategies in rural Sahel. Environmental Management, 43, 804-816, Retrieved fromhttps://doi.org/10.1007/s00267-008-9197-0
Smit, B., McNabb, D. and Smithers, J. 1996. Agricultural adaptation to climatic variation. Retrieved fromhttps://link. springer.com/article/10.1007/BF00140511
Thomas, D.S.G. 2007. Adaptation to climate change and variability: Farmer responses to intra-seasonal
precipitation trends in South Africa. Retrieved from https://link.springer.com/article/10.1007/s10584-0069205-4
Thomson, A.M., Calvin, K.V., Smith, S.J., Kyle, G.P., Volke, A., Patel, P., Delgado-Arias, S., Bond-Lamberty,
B., Wise, M.A., Clarke, L.E. and Edmonds, J.A. 2011. RCP 4.5: A pathway for stabilization of radiative
forcing by 2100. Climatic Change 109, 77, Retrieved from https://doi.org/10. 1007/s10584-011-0151-4
Vedwan, N. and Rhoades, R.E. 2001. Climate change in the Western Himalayas of India: A study of local
perception and response. Retrieved from https://www.researchgate.net/publication/250221587Ⓒ ISERD

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Research article
erd

Soil Organic Carbon Stabilization on Forested andDeforested Red-yellow Soil under Different Temperature
Conditions
KEIJI AROSTEGUIGraduate School of Agriculture, Tokyo University of Agriculture, Tokyo, Japan
Email: karostegui@cientifica.edu.pe

MACHITO MIHARA*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Email: m-mihara@nodai.ac.jp
Received 5 January 2021

Accepted 16 July 2021(*Corresponding Author)

Abstract Soil organic carbon (SOC) has an important role as a key indicator for soil healthdue to its contributions on mitigation and adaptation to climate change. Tropical areas coverwith Red-yellow soil (Udults) such as Amazon represents the highest amount of soil carbon
sources in the earth. Although it is affected by human impacts due to deforestation, it isimportant to maintain and increase SOC of tropical Red-yellow soil toward an optimal level
for meeting challenges such as mitigating climate change effects. The aim of this study is toanalyze the stabilization of soil organic carbon from Red-yellow soil under different
temperatures conditions. A detailed comparison was made between forested and deforested
conditions of Red-yellow soil. In order to analyze the temperature sensitivity, each treatment
was kept under 25ºC and 35ºC, and the soil respiration ratio (SRR) was measured as well as
SOC content by spectrophotometry method. Lastly, a treatment of biochar at 5% was added
as part of stabilization mechanisms of carbon. The experimental results showed that there
were significant differences in SOC content between forested conditions in contrast to
deforested conditions, where 7.25 mg C/g was found in forest conditions while deforested
conditions was 5.68 mg C/g. Although it was not found significant change in SOC under
different temperature, SRR increased at 39% from 8.87 μL CO2/h/g to 11.90 μL CO2/h/g withtemperature changes from 25ºC to 35ºC. Additionally, biochar application contributes toincrease the value of SOC at more than 2.66 mg C/g in all treatments, however, it did not
make a significant difference in SRR by temperature changes. Thus, biochar works as carbon
sources to maintain and increase SOC content, but stabilization effects on Soil Respiration
Ratio (SRR) should be observed in long term.
Keywords soil organic carbon, soil respiration rate, temperature sensitive, biochar

INTRODUCTION
The SOC represents between 50% to 58% of the soil organic matter content, which has an importantfunction of storing nutrients for plants, improving soil structural stability to enhance soil fertility andproviding mechanism to mitigate climate change effects. Turnover of SOC in terrestrial ecosystems
is dynamic and human impacts can turn SOC into either a net sink or a net source of greenhousegases (GHG) to the atmosphere (Trivedi et al., 2018).
The impact of climate change on SOC stocks is variable according to the soil type and location,
however temperature changes and increasing frequency of extreme drought events are probably
leading to increased loss of SOC. Although significant scientific progress has been achieved related
to understanding of SOC dynamic, mechanism of protection and stabilization of SOC stocks in shortterm and at different conditions still face complicated challenges impeding effectives conservation
strategies (Pribyl, 2010).
The Red-yellow soil (Udults), mainly located in Amazon area, has an important role in global
carbon changes, making this area as a considerable interest to quantify emissions when deforestationⒸ ISERD

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converts these forests into pasture or other land uses (de Oliveira Marques et al., 2017). Maintaining
carbon stocks in Red-yellow soils of tropical forests such as Amazon area has increasingly becomea justification for governments to take measures of reforesting rather than allowing them to be
deforested. Nevertheless, deforestation has accelerated the process of forest fragmentation in
Amazon area, resulting in changes in carbon stocks in biomass and soil (Barros and Fearnside, 2016).
The enhance of soil microbe’s activity is stimulated by increasing of environment temperature,causing a higher release of microbial CO2 (Lloyd and Taylor, 1994), leading to soil C losses, higher
soil respiration rate and a positive contribution to global warming. In the short-term, increasing oftemperature results in a significant increase of microbial activity and decomposition rates. It has beenshown that decomposition of SOC increases with temperature, with the greatest proportional
increases being observed at low temperatures. It is a fundamental issue to estimate the extent to whichrising temperatures could destabilize SOC and make it available to decomposing microorganisms.
The proportion of SOC stored in the world’s soils is still argued and how it is vulnerable to theimpacts of warming of this century (Crowther et al., 2016).
Therefore, modeling approaches that consider changes in carbon availability and microbialactivity may be needed to improve understanding under different conditions on Red-yellow soil.
Forested and deforested conditions of soils have a significant effect on SOC that must be connectedwith respiration rate, decomposition and possible conservation strategies on Amazon area.
OBJETIVE
The present study aimed to analyze the quantity and stabilization of soil organic carbon from Redyellow soil, under different temperatures (25ºC and 35ºC) and conditions (forested and deforested).
Such study is important to provide information about potential carbon emissions and climate change
effects.
METHODOLOGY
Soil Sample Source and Preparation
The current investigation involved sampling and analyzing two sites of Red-yellow soil to measure
SOC and SRR. The sites were selected from Miyako Island, which is located in Okinawa Prefecture,south of Japan. The soil sample was collected from a deforested and forested area with four samples
each site as repetitions (Carter and Gregorich, 2008). Air-dried soil at 1,000 g were sieve and weighed
into a labeled tray followed by adding 5% (w/w) of biochar as a biochar treatment. Samples were
kept at approximate a field capacity moisture condition. Each treatment was divided into soil atambient conditions (25ºC) and warm conditions (35ºC), and by conditions (Forested and Deforested)
and biochar rate (0% and 5%).
Soil Organic Carbon Determination
Each one of the treatments and repetitions were analyzed by Spectrophotometric Procedure ofOrganic Carbon Contents of Soil (Wallinga et al., 1992). The soil at 50 mg were weight precisely,
and it was transferred carefully to a dry 100 mL volumetric flask. 10.0 mL of 0.333 M potassium
dichromate solution (K2Cr2O7) was added to each flask. 16.0 mL of concentrated sulphuric acid wereadded following by putting the flasks in a boiling water bath for 45 min. The samples were cooled in
the sink made up to the volume with distilled water. The samples were centrifuged for 10 min at
3,000 rpm.
For the preparation of standard series, 100 mL flasks containing sodium oxalate (Na2C2O4) withvolumes of 0, 25.0, 50.0, 75.0 and 100.0 mL were used as standard into the volumetric flask. Thesestandard series worked as 0, 5, 10, 15 and 20 mmol Cr+3 per litter of solution of standard series. The
absorbance was measured in a 1 cm cuvette at a wavelength of 590 nm within 2 hours after oxidation.
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SOC percentage were calculated by multiplying the Cr+3 concentrations found by 0.2250/w, where“w” is the weight of the air-dry soil sampled.
Soil Respiration Rate Determination
Air-dried soil at 10 g were weighted from each treatment into a 450 mL glass bottle followed byadding 3 mL of distilled water. The soil and water were mixed in the bottles then covered withperforated films to reduced evaporation. The SRR was determined by using the infrared gas analyzer
at time zero and measure again at the end of 1 h incubation (Sparda et al. 2016). The soil respiration
rate (SRR, μL CO2/h/g air-dried soil) was calculated as:
𝑆𝑅𝑅 = (𝐶𝑂2𝑓 − 𝐶𝑂2𝑖 ) ∗ 𝑉 ∗

1000
𝑆

(1)

Where CO2i and CO2f are the initial and final CO2 concentrations (ppm) of the 1 h incubation,
respectively, and V is the space volume of the bottle with the soil sample (450 mL). The amount ofsoil (S) was 10.0 g. Four repetition were measured for each one of the treatments.
Statistical Analysis
The comparison of the average of each one of the treatments were analyzed through Shapiro-Wilk
Normality and Levene Homogeneity test. The one-way ANOVA test were performed to determine
if there are differences through variance analysis. Then, Tukey test was applied to determine thedifferences between treatments. In addition, a Box-Cox transformation was performed to fit the
ANOVA test. All the tests were performed using RStudio (version 1.2.5042) for statistical analysesof the data. Analyses were performed at the significant level of P≤0.05.
RESULTS AND DISCUSSION
Mean values and standard deviation of Soil Organic Carbon (mg/g) and Soil Respiration Rate(μLCO2/h/g) of treatments at Forested and Deforested condition, biochar rates and temperature, areshown in Table 1. The amount of organic carbon obtained in this study indicated significant
differences (P<0.05) between treatments (Forested vs Deforested). In previous studies, the amountof Soil Organic Carbon has been analyzed at Forested and Deforested conditions (Fujisaki et al.,2017), where the values on Forested condition were found higher that Deforested condition. The
theoretical basis for this is as follows. The forest keeps equilibrium between incomes and outcomesof carbon while deforestation cuts incomes and increase outcomes in the short term.
Table 1 Soil Organic Carbon (SOC) content and Soil Respiration Rate (SRR) ofdifferent conditions, biochar rate and temperature
Condition

Biochar0%

Forested
5%0%
Deforested
5%

Tº
25º
35º
25º
35º
25º
35º
25º
35º

SOC (mg/g)
7.24 ± 0.04 a
7.61 ± 0.43 a
10.27 ± 0.39 b
10.97 ± 0.37 b
5.68 ± 0.46 c
6.6 ± 0.44 cd
4.99 ± 0.09 c
5.52 ± 0.53 c

SRR (μL CO2/h/g)
8.87 ± 0.20 a
12.14 ± 0.20 b
8.53 ± 0.04 a
11.9 ± 0.13 b
6.57 ± 0.02 c
4.93 ± 0.13 d5.51 ± 0.09 d
4.88 ± 0.24 d

The letters indicate the significant different of result among the treatments at 95% of confidence level.

On the other hand, the addition of biochar at 5% rate on soil showed a considerable different on
SOC rather than 0% treatment. Biochar is composed by high values of organic matter which includes
organic carbon (Oladele and Adetunji, 2020). The biochar increased values of SOC in ForestedⒸ ISERD

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conditions at 5% rate in contrast of 0%, however, there were not differences found on Deforested at
5% in contrast of 0%. Temperature changes did not show significant difference between treatments
in short term. Liu et al. (2021) described the degradation of organic carbon in long-term by microbes
at warm conditions as a reduction in the amount of SOC, this explain the non-significant change inthe values of SOC by temperature in short-term.

Fig. 1 Soil Organic Carbon content and Soil Respiration Rate of each treatment
It can be seen in Fig. 1 that the Soil Respiration Rate was altered by temperature in the shortterm. In Forested conditions, values of SRR reached 12 μL CO2/h/g in contrast to values lower than
9 μL CO2/h/g (39% higher in warm conditions). The increased of temperature in soil reflects a
considerable change in microbial activity in the short-term, which means an increase of CO2 released.
Although biochar addition shows a considerable increase of SOC, there is not stabilization of SRR
under warm conditions. Xu et al. (2019) describe the activation and stabilization of carbon by biocharin the middle-term, which not only increase carbon but also reduce the release of it.
Deforested conditions showed values of SRR lower in comparison with Forested. It is clear due
to the low amount of carbon in the Red-yellow soil and the relation with microbial activity. The SRR
reached values of 6.57 μL CO2/h/g and the lowest 4.93 μL CO2/h/g with significant differences (25%lower than Forested conditions). Effect of temperature on Deforested conditions showed an increasedin SRR values, but in the same way, biochar did not have a significant effect. Biochar application
has affected the SOC but the effects on SRR stabilization in the short-term is depending bytemperature and the microbial activity (Xu et al., 2019).
CONCLUSIONS
It is demonstrated that Deforested condition reduces significantly the amount of organic carbon in
the soil. Although Red-yellow soil has a low organic carbon content, this reduction can be recoveredby biochar addition. The loss of carbon by microbial activity increases by the effect of temperature
which has an important role through Soil Respiration Rate. The Forested conditions of Red-yellow
soil showed an increase of microbial activity due to the high carbon content, thus, the changes on
respiration are easily affected by weather such as temperature conditions. This process of organiccarbon degradation is not stabilized by biochar addition in the short-term. Finally, biochar works as
carbon sources to maintain and increase SOC content, but stabilization effect on Soil Respiration
Ratio (SRR) should be observed in long term under warm and ambient conditions as part of thestabilization process.
REFERENCESⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2021) 12-2

Barros, H. and Fearnside, P. 2016. Soil carbon stock changes due to edge effects in central Amazon forest
fragments. Forest Ecology and Management, 379, 30-36.
Carter, M. and Gregorich, E. 2008. Soil sampling and methods of analysis. 2nd ed., Canadian Society of Soil
Science, 33-37, Pinawa, Manitoba.
Crowther, T., Todd-Brown, K., Rowe, C., Wieder, W., Carey, J. and Machmuller, M. 2016. Quantifying global
soil carbon losses in response to warming. Nature, 540 (7631), 104-108.
De Oliveira Marques, J., Luizão, F., Teixeira, W., Nogueira, E., Fearnside, P. and Sarrazin, M. 2017. Soil
carbon stocks under Amazonian Forest: Distribution in the soil fractions and vulnerability to emission.
Open Journal of Forestry, 7, 121-142.
Fujisaki, K., Perrin, A., Garric, B., Balesdent, J. and Brossard, M. 2017. Soil organic carbon changes after
deforestation and agrosystem establishment in Amazonia: An assessment by diachronic approach.
Agriculture, Ecosystems & Environment, 245, 63-73.
Liu, X., Pold, G., Domeignoz-Horta, L., Geyer, K., Caris, H., Nicolson, H., Kemner, K., Frey, S., Melillo, J.
and DeAngelis, K. 2021. Soil aggregate-mediated microbial responses to long-term warming. Soil Biology
and Biochemistry, 152, 108055.
Lloyd, J. and Taylor, J. 1994. On the temperature dependence of soil respiration. Funct, Ecology, 315-323.
Oladele, S. and Adetunji, A.T. 2021. Agro-residue biochar and N fertilizer addition mitigates CO2-C emission
and stabilized soil organic carbon pools in a rain-fed agricultural cropland. International Soil and Water
Conservation Research, 9 (1), 76-86.
Pribyl, W. 2010. A critical review of the conventional SOC to SOM conversion factor, Geoderma, 156 (3-4),
75-83.
Sparda, A., Miller, R., Anderson, G. and Hsieh, Y. 2016. Real-time soil CO2 respiration rate determinationand the comparison between the infrared gas analyzer and microrespirometer (MicroRes®) methods.
Communications in Soil Science and Plant Analysis, 48 (2), 214-221.
Trivedi, P., Singh, B. and Singh, B. 2018. Soil carbon storage. Academic Press an imprint of Elsevier, 1,
London.
Walinga, I., Kithome, M., Novozamsky, I., Houba, V. and van der Lee, J. 1992. Spectrophotometricdetermination of organic carbon in soil. Communications in Soil Science and Plant Analysis, 23 (15-16),
1935-1944.
Xu, W., Yuan, W., Cui, L., Ma, M. and Zhang, F. 2019. Responses of soil organic carbon decomposition towarming depend on the natural warming gradient. Geoderma, 343, 10-18.

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Research article
erd

Assessment of Some Promising Lines of Rice (Oryza sativa
L.) for Salt Tolerance using Microsatellite Markers
Associated with the saltol QTL
MOE KYAW THU*
Department of Agricultural Biotechnology, Yezin Agricultural University Myanmar
Email: dr.moekyawthu@yau.edu.mm

AUNG NAING OO
Department of Soil and Water Science, Yezin Agricultural University, Myanmar

NYO MAR HTWE
Advanced Center for Agariculturla Research and Education, Yezin Agricultural University

OHN MAR LYNN
Department of Agricultural Biotechnology, Yezin Agricultural University Myanmar

KHIN THIDA MYINT
Department of Horticulture, Yezin Agricultural University, Myanmar
Received 30 December 2020

Accepted 19 July 2021(*Corresponding Author)

Abstract Rice is one of the most important staple food crops in the world that grownextensively under irrigation. Salinity is an important physical factor influencing rice (Oryza
sativa L.) production. To assess this limiting factor, YAU developed 100 breeding lines ofrice. After screening at seedling and vegetative stages at different salinity levels (0.2, 6.0, and
8.0 dS m-1), seven rice lines were selected as moderately saline-tolerant genotypes. Theseseven lines (V1: YAU- 1211-14-1-1; V2: YAU1201-90-2-4; V3: YAU-1211-18-1-1; V4:
YAU1211-195-1-1; V5: YAU-1201-26-1-1; V6: YAU1201-26-1-3; and V7: YAU-1211-821-1) along with three local control varieties (Yatanatoe, Superhnankaut and Theehtatyin), one
salt tolerance check (Pokkali) and one susceptible check (IR 29) were used in this study.
Seven Saltol QTL associated SSR markers (RM5, RM9, RM140, RM472, RM493, RM1287
and RM3412) were used to check the usefulness of microsatellite (SSR) markers associatedwith Saltol QTL. The number of alleles on the SSR markers ranged from 2 for RM140 to 4
for RM3412. Polymorphic information content (PIC) value varied from 0.00 for RM140 to
0.62 for RM3412, with an average of 0.36. The SSR marker, RM3412, was found to besuperior for analysis as an indicator of genetic diversity in this study. Cluster analysis of therice genotypes based on SSR data divided the genotypes into three groups, each of which
include Yatanatoe, Theehtatyn, Superhnankaut and susceptible check IR29 (cluster 1), V1,V2 and V3 (cluster 2), V4, V5, V6, V7 including salt tolerance genotypes Pokkali (cluster 3),
respectively. Of the seven lines, four SSR markers (RM5, RM493, RM1287 and RM3412)
could discriminate Pokkali (saltol) from the IR29 (susceptible) genotype. Two specific alleles
were found by RM5 (170) and RM493 (220) for Pokkali. At locus RM140, almost all
genotypes possessed the same allele as Pokkali (260) except Theehtatyin and IR29 (nullallele). RM1285 indicated four YAU rice lines (V4, V5, V6 and V7) as salt tolerance lines.
The study revealed V4: YAU1211-195-1-1 as a tolerance genotype. The RM5, RM493,
RM1287 and RM3412 markers were able to discriminate the tolerant genotypes and hence
could be useful for marker-assisted selection of Saltol QTL.
Keyword promising rice lines, Saltol QTL, SSR marker

INTRODUCTIONⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2021) 12-2

Rice (Oryza sativa) is the staple food of half of the population of the world. Identifying a rice cropthat resists saline incursions due to climate change is prevalent among farmer’s requirements. Soilsalinization has become a serious problem all over the world and around 20% of the world's
cultivated land is affected (Sumner, 2000). In Myanmar, soil salinization is found in both coastal andinland regions, and about 3% of the total rice sown area is affected by salinity (DOA, 2012). Coastal
salinity is often due to seawater intrusion/ infiltration during floods, resulting in salt accumulation in
the topsoil in the summer season. It occurs commonly in Ayeyarwady, Yangon, Yakhaing andTaninthari regions. Inland salinity is common in dry zone areas of central Myanmar such as the
Mandalay, Magway and Sagaing regions. Rice productivity is quite low due to this salinization, withlimited water resources, and low soil fertility in these inland areas of Myanmar (Oo et al., 2017). Sweand Ando (2017) have pointed out that salinity is becoming a prominent abiotic problem, withdeclining rice production in the central dry zone and which has had little attention paid to it. An
improvement in rice breeding programs which offers rice varieties suitable for these changing
conditions is important.
There are many salt tolerant rice varieties providing an opportunity to improve crop salt-stress
tolerance through genetic means. Some attempts based on highly tolerant traditional rice cultivars i.e.
Pokkali and Nona-Bokra have been made to these develop salt-tolerant genotypes (Akbar et al., 1985;
Gregorio and Senadhira, 1993). DNA based molecular markers have been used extensively to assess
the genetic diversity in most crop species (Mohammadi-Nejad et al., 2008). Currently, simple
sequence repeats (SSRs) or microsatellite markers have been used to study genetic diversity,
phylogenetic relationships, classification, evolutionary processes and quantitative trait loci in many
crops. This technique has been used effectively to map QTLs associated with salt tolerance (Lang etal., 2000 and 2001; Singh et al., 2007). A major QTL located on chromosome 1 has been identified
for salt tolerance using F8 recombinant inbred lines (RILs) of Pokkali/ IR29 cross (Gregorio et al.,1997). Therefore, it could be stated that Pokkali represents the most widely used salt tolerant parent
by rice breeders. Our group have developed hundreds of rice breeding lines to transfer salt tolerance
gene of Pokkali to local height yielding varieties.
OBJECTIBESThe present study intended to (i) evaluate salt tolerant rice breeding lines at different growth stages;
seedling and vegetative, and (ii) test the usefulness of microsatellite (SSR) markers associated with
Saltol QTL to identify promising YAU rice lines.
MATERIALS AND METHODS
Evaluation of Selected Improved Rice Lines at Vegetative Stage
This experiment was conducted as a two-factor factorial in a randomized complete block design,with three replications at vegetative stage. Seven promising lines out of YAU 100 improved line
were formerly selected by conducting farmer participatory variety selection based on their preferenceof eating quality and visual assessment in the field. The seven rice selected lines with Pokkali(tolerant check) and IR29 (susceptible check), were grown at three different levels of salinity (0.2,
6.0, and 8.0 dS m-1). Salinity tolerance was rated using a modified standard evaluation system (SES)
rating the visual symptoms of salt toxicity (Gregorio et al., 1997) as shown in Table 1. Following
Gregorio et al. (1997), who modified the method for the screening of rice genotypes at vegetative
stage, the wall of plastic pot was drilled with 3-4 mm diameter holes 2 cm apart, with the topmost
circle of holes at least 3 cm below the rim of the plastic pot. Cotton cloth was used to line the plastic
pots. The pots were filled with fertilized soil, and then placed in the plastic tray filled with ordinary
tap water, which served as a water bath. Four to five pre-germinated seeds of the tested varieties wereplaced on the soil surface of each pot. Two weeks after seeding, seedlings were thinned to one per
pot and the water level was raised to a level about 1 cm above soil. When the seedlings were 25 days
old, all water was siphoned out. Then salinized water, at the different EC saturations, was introduced.
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IJERD – International Journal of Environmental and Rural Development (2021) 12-2

The water level was maintained on a daily basis and the plants protected from any pests and diseases.
Scoring was started at two weeks after salinization by using a modified standard evaluation system
to rate the visual symptoms of salt toxicity (Gregorio et al., 1997) with results presented in Table 1.
Plant height (cm) and the number of tillers per hill were recorded at 6 weeks after salinization.
Table 1 Modified Standard Evaluation Score (SES) of visual salt injury at seedling andvegetative stages
Score
Observation
1
Normal growth, no leaf symptoms
3
Nearly normal growth, but leaf tips of few leaves whitish and rolled
5
Growth severely retarded, most leave rolled
7Complete cessation of growth, most leaves dry, some plant dying
9
Almost all plant dead or dying
Source; Gregorio et al., 1997

Tolerance
Highly tolerant
Tolerant
Moderately tolerant
Susceptible
Highly susceptible

Microsatellite (SSR) Analysis
A total of twelve genotypes including seven YAU promising rice line (V1: YAU- 1211-14-1-1; V2:
YAU1201-90-2-4; V3: YAU-1211-18-1-1; V4: YAU1211-195-1-1; V5: YAU-1201-26-1-1; V6:
YAU1201-26-1-3; and V7: YAU-1211-82-1-1) and three local control varieties (Yatanatoe,
Superhnankaut and Theehtatyin), one susceptible check (IR29) and one tolerance check (Pokkali)
were used to extract total genomic DNA. A modified CTAB method was used to extract DNA fromthe plants’ young leaves. The relative purity and concentration of extracted DNA was estimated with
NanoDrop ND-1000 (NanoDrop Technologies, Inc., Wilmington, DE, USA). The final concentrationof each DNA sample was adjusted to 50 ng/µl.
Seven Saltol QTL associated SSR markers (RM5, RM9, RM140, RM472, RM493, RM1287
and RM3412) were used to check the usefulness of microsatellite (SSR) markers associated with
Saltol QTL in the identification of promising YAU rice lines (Mohammadi-Nejad et al., 2008).
GoTaq®Colorless Master Mix M713 was used according to the manufacturer’s procedure for PCR
amplification. The PCR reaction was a 10 μl volume using a Boeco Thermal Cycler TC-SQ (Boeco
Germany). The PCR profile; 5 min of denaturation at 94°C, 35 cycles were performed for 1 min at
94°C, 45 s at 55°C, 1 min at 72°C, and a final extension step of 5 min at 72°C. PCR amplified
products were separated in 2% agarose gel at 100 V for 1 h in 1 x TBE buffe. RedSafe™ Nucleic
Acid Staining Solution (20,000x) was used to stain DNA in the agarose gel. The resulting DNA
bands were scored as base pairs using grid lines in photoshop, comparing 100 bp DNA ladder bands.
Data Analysis
The data collected were analyzed statistically using Analysis of Variance (ANOVA) techniques, andrice lines means were compared by least significant different (LSD) method at a 5% probability level.
All statistical analyses were done using Statistix 8.0 software and Excel program (2010).
The variability at each locus was measured in terms of the number of alleles, major allele
frequency (MAF), and polymorphic information content (PIC) using PowerMarker 3.25 (Liu andMuse, 2005). The UPGMA algorithm of MEGA6 software embedded in PowerMarker was used toconstruct an unrooted neighbour-joining tree of each accession based on the shared allele distances(Tamura et al., 2007).
RESULTS AND DISCUSSION
Evaluation of Selected Improved Rice Lines at the Vegetative Stage
The sight evaluation scores (SES), showed a variation in response to salt stress among the rice lines.
SES increased with an increase in stress level, indicating greater susceptibility at higher stress levelⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2021) 12-2

(Table 2). All seven improved rice lines at vegetative stage grew strongly and showed uniform green
colour in non-salinized conditions (0.2 dS m-1 ). In salinized conditions (6.0 and 8.0 dS m-1 ), the ricelines showed significant differences for salt tolerance at the vegetative stage, with scores ranging
from score 1 (highly tolerant) to score 9 (highly susceptible) (Table 2). The seven rice lines selected
showed a high degree of tolerance and moderate tolerance, respectively, under increasing salinity
levels (6.0 and 8.0 dS m-1).
The reactions of the selected improved rice lines in terms of plant height and number of tillers
per hill, under three different salinity levels at the vegetative stage, are showed in Table 3. The plantheights are significantly different among the rice lines in the non-salinized condition (0.2 dS m-1). In
contrast, these parameters were not significantly different among the rice lines in the two salinizedconditions. Similarly, the number of tillers per hill was not significantly different among the ricelines in all conditions.
Table 2 Reactions of improved rice lines at vegetative stage to salinity at three different levels
measured by Standard Evaluation Score (SES)
Improved rice lines
YAU-1211-14-1-1
YAU-1201-90-2-4
YAU-1211-118-1-1
YAU-1211-195-1-1
YAU-1201-26-1-1
YAU-1201-26-1-3
YAU-1211-82-1-1
PokkaliIR29

0.2 dS m-1
Highly tolerantHighly tolerantHighly tolerantHighly tolerantHighly tolerantHighly tolerantHighly tolerantHighly tolerantHighly tolerant

Reaction to salinity at 6 weeks after salinization
6.0 dS m-1
8.0 dS m-1
Tolerant
Moderately tolerant
Tolerant
Moderately tolerant
Tolerant
Moderately tolerant
Tolerant
Moderately tolerant
Tolerant
Moderately tolerant
Tolerant
Moderately tolerant
Tolerant
Moderately tolerant
Tolerant
Tolerant
Highly susceptible
Highly susceptible

Table 3 Reactions of selected improved rice lines at the vegetative stage to salinity at threedifferent levels measured by plant height and number of tillers per hill
Plant height (cm)Number of tillers per hill
0.2 dS m-1
6.0 dS m-1
8.0 dS m-1
0.2 dS m-1
6.0 dS m-1
8.0 dS m-1
YAU-1211-14-1-1
39.0 bcd
32.7
26.3
4.7
4.0
3.0
YAU-1201-90-2-4
37.3 de
32.3
25.7
4.3
4.0
3.3
YAU-1211-118-1-1
42.0 ab
32.7
23.7
4.3
3.7
3.3
YAU-1211-195-1-1
39.7 bcd
33.3
24.0
4.0
3.7
3.3
YAU-1201-26-1-1
44.7 a
32.0
26.7
5.0
4.3
4.0
YAU-1201-26-1-3
38.0 cde
35.7
22.7
4.0
3.3
3.3
YAU-1211-82-1-1
40.7 bc
34.0
27.3
4.3
3.7
4.0
Pokkali
35.3 ef
36.3
25.0
4.3
3.3
3.3
IR29
33.0 f
31.7
24.0
3.7
3.7
3.3
F-test
**
ns
ns
ns
ns
ns
C.V %
4.6
5.5
9.2
15.2
18.6
19.4
Values in the same column followed by the same letter are not significantly different at the 5% level by the LSD test, (**)
significantly different at P≤0.01, ns − not significant
Improved rice lines

Microsatellite (SSR) Analysis
The number of alleles of the SSR markers ranged from 2 for RM140 to 4 for RM3412. Polymorphic
information content (PIC) values varied from 0.00 for RM140 to 0.62 for RM3412, with an averageof 0.36 (Table 4). The measure, or value of the PIC, is determined by the ability of a marker toestablish polymorphism in the population depends on the number of alleles detected and on theirdistribution frequency (Botstein et al., 1980). The PIC value of the marker is defined as the expected
fraction of informative offspring from the type of pedigree (Hildebrand, et al. 1992). In this regard,
SSR marker, RM3412, was found to be superior for discrimination of potential breeding lines in thisstudy.

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Cluster analysis of the rice genotypes based on SSR data, separated the genotypes into threegroups, each of which had Yatanatoe, Theehtatyn, Superhnankaut and susceptible check IR29
(cluster 1), V1, V2 and V3 (cluster 2), V4, V5, V6, V7, including salt tolerance genotypes Pokkali(cluster 3), respectively (Figure 1). Out of the seven varieties, four SSR markers (RM5, RM493,
RM1287 and RM3412) were able to discriminate Pokkali (Saltol) from IR29 (susceptible) genotype.
Two specific alleles were found by RM5 (170) and RM493 (220) for Pokkali. At locus RM140,
almost all genotypes possessed the same allele as Pokkali (260), except for Theehtatyin and IR29
(null allele). Null alleles were likely to be encountered in populations with a large size, with unusuallyhigh mutation rates in the flanking regions, and those that have diverged from the population fromwhich the cloned allele state was drawn and the primers designed (Chapuis and Estoup, 2007).
Theehtatyin and IR29 would exhibit mutations in this locus, RM140. RM1285 was an indicator thatfour YAU rice lines (V4, V5, V6 and V7) are salt tolerant lines. These results, in combination,
revealed V4: YAU1211-195-1-1 as saline tolerant genotypes. The RM5, RM493, RM1287 andRM3412 markers were able to discriminate for tolerant genotypes and hence could be useful formarker-assisted selection of Saltol QTL.
Table 4 Number of alleles and polymorphism information content (PIC) values of
SSR markers for 12 rice genotypes
Marker
RM5
RM9
RM140
RM472
RM493
RM1287
RM3412Frequency ofmajor allele
0.92
0.44
1.00
0.83
0.50
0.56
0.42

No. of allele
2
3
1
2
3
3
4

PIC
0.14
0.57
0.00
0.24
0.48
0.49
0.62

Amplicon size
range (bp)150-170
100-170260
320-350
220-250
125-160
200-260

Fig. 1 Dendrogram of 12 rice genotypes based on 7 polymorphic SSR markers
derived from the Shared allele distance with neighbor joint method
CONCLUSION
In conclusion, in this study seven YAU improved rice lines were observed for relative salt tolerance
in terms of agronomic parameters such as tiller numbers, panicle numbers and grain yield. Results
show that four rice breeding lines; V4, V5, V6, V7 have the potential to be developed for future
improvement as salt tolerant rice varieties. Furthermore, the result highlights the usefulness of SSR
markers associated with saltol QTL for the screening of rice breeding lines. The RM5, RM493,
RM1287 and RM3412 markers may be useful for marker-assisted selection.
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ACKNOWLEDGEMENTS
The authors would like to thank the JICA (Japan International Cooperation Agency) for theirfinancial support for this project and the capacity development they have fostered at Yezin
Agricultural University.
REFERENCES
Akbar, M., Khush, G.S. and Hillerislambers, D. 1985. Genetics of salt tolerance in rice. In Rice Genetics,
Proceeding of the International Rice Genetics Symposium, IRRI, 399-409, Los Baños Laguna, Philippines.
Botstein, D., White, R.L., Skalnick, M.H. and Davies, R.W. 1980. Construction of a genetic linkage map in
man using restriction fragment length polymorphism. Am. J. Hum. Genet., 32, 314-331.
Chapuis, M.P. and Estoup, A. 2007. Microsatellite null alleles and estimation of population differentiation.
Mol. Biol. Evol., 24 (3), 621-631, Retrieved from https://doi.org/10.1093/molbev/msl191
DOA (Department of Agriculture). 2012. Annual report paper, Agricultural Extension Section.
Garland, S.H., Lewin, L., Abedinia, M., Henry, R. and Blakeney, A. 1999. The use of microsatellite
polymorphisms for the identification of Australian breeding lines of rice (Oryza sativa L). Euphytica, 108,
53-63.
Gregorio, G.B. and Senadhira, D. 1993. Genetic analysis of salinity tolerance in rice (Oryza sativa L.). Theor.
Appl. Genet., 86, 333-338.
Gregorio, G.B., Senadhira, D. and Mendoza, R.D. 1997. Screening rice for salinity tolerance. IRRI Discussion
Paper Series, 22, International Rice Research Institute, Los Baños, Laguna, Philippines.
Hildebrand, C.E., Torney, D.C. and Wagner, R.P. 1992. Informativeness of polymorphic DNA markers. Los
Alamos Science, 20, 100-102.
Lang, N.T., Yanagihara, S. and Buu, B.C. 2000. Quantitative trait loci for salt tolerance in rice via molecularmarkers. Omonrice, 8, 37-48.
Lang, N.T., Zhikang, L. and Bui, C.B. 2001. Microsatellite markers linked to salt tolerance in rice. Omonrice,
9, 9-21.
Liu, K. and Muse, S.V. 2005. Power marker: An integrated analysis environment for genetic marker analysis.
Bioinformatics, 21, 2128-2129.
McCouch, S.R., Chen, X., Panaud, O., Temnykh, S., Xu, Y., Cho, Y., Huang, N., Ishii, T. and Blair, M. 1997.
Microsatellite marker development, mapping and applications in rice genetics and breeding. Plant Mol.
Biol., 35, 89-99.
Mohammadi-Nejad, G., Arzani, A., Rezai, A.M., Singh, R.K. and Gregorio, G.B. 2008. Assessment of rice
genotypes for salt tolerance using microsatellite markers associated with the saltol QTL. African Journalof Biotechnology, 7 (6), 730-736.
Oo, A.N., Ando, K., Khaung, T. and Khaing, M.T. 2017. Food security and socio-economic impacts of soil
salinization in the central dry zone of Myanmar, A case study. Journal of Agroforestry and Environment,
11 (1 & 2), 149-154.
Singh, R.K., Gregorio, G.B. and Jain, R.K. 2007. QTL mapping for salinity tolerance in rice. Physiol, Mol.
Biol. Plants, 13, 87-99.
Sumner, M.E. 2000. Handbook of soil science. CRC Press, Boca Raton.
Swe, K.L. and Ando, K. 2017. Rice production in salt affected areas of central dry zone, Myanmar. The
Proceedings of 10th Agricultural Research Conference of Yezin Agricultural University, Nay Pyi Taw,
Myanmar.
Tamura, K., Dudley, J., Nei, M. and Kumar, S. 2007. MEGA4: Molecular evolutionary genetics analysis(MEGA) software version 4.0. Mol. Biol. Evol., 24, 1596-1599.
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microsatellite DNA polymorphism in land races and cultivars of rice. Mol. Gen. Genet., 245, 187-194.

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Research article
erd

Evaluation of School Gardens as a Method of Scaling Up
Sustainable Agriculture Technologies
GRACIE PEKARCIK*
University of Tennessee, Knoxville, USA
Email: gpekarci@vols.utk.edu

DAVID ADER
University of Tennesse, Knoxville, USA
Received 31 December 2020

Accepted 1 August 2021(*Corresponding Author)

Abstract Current research on school gardens is primarily focused on improving student
nutrition. Less examined is their potential to be agents of knowledge transfer to the wider
community. This paper seeks to determine the potential of school gardens as a pathway toscaling agricultural innovations. Literature is reviewed for best practices andrecommendations conducive to scaling up agricultural technologies using school gardens.
Findings indicated that school gardens have the potential to play a key role in scalingsustainable intensification (SI) technologies. They provide opportunities for knowledgetransfer through teacher-student-parent communication. Best practices for scaling throughschool gardens comprised: including parents in the learning process and upkeep of school
gardens; collaboration and commitment among all stakeholders; establishment of hands-on,
research-based agricultural curriculum in schools; financial assistance from government or
outside organization for startup and upkeep; and establishment of home gardens alongsideschool gardens. Primary barriers to scaling included: focusing on the ‘what’ and not the‘how’; social mores and the relationship between parent/child; capacity building for andinvolvement of school heads, teachers, and parents; lack of social, human, and/or economic
capital; and unintegrated commitment and partnership among stakeholders. Identified bestpractices and barriers are then applied to a case study analysis of a USAID-funded project inCambodia: Scaling Suitable Sustainable Technologies (S3-Cambodia) project. S3-Cambodia
targets youth as an entry point to extend target SI technologies to farm families. The project
engages students in experiential learning opportunities by establishing “green labs” atsecondary schools. S3-Cambodia is found to already be implementing many of the bestpractices listed above. Suggestions are made to increase parent involvement in the project
and to increase awareness of the challenges that come with a transnational project.
Keywords adoption, scaling, school garden, knowledge transfer, agriculture

INTRODUCTION
School gardens are a well-known tool to develop agricultural education curriculum and food systemknowledge within primary and secondary schools worldwide. Current research on school gardens is
primarily focused on improving student nutrition and increasing vegetable consumption (Ratcliffe etal., 2011; Schreinemachers et al., 2019; Leuven et al., 2018; FAO, 2004; Ferguson et al., 2019). Less
examined is their potential to be agents of food system reskilling and knowledge transfer to the wider
community (Cramer et al., 2019). Yet, students have significant potential to be agents of change intheir homes and communities. Using knowledge gained through school garden education, students
can serve as credible sources of information to their parents on best agriculture practices (Okiror etal., 2011).
School gardens provide a pathway to evaluate new technologies without personal risk. Often,
implementation and scaling up of new technologies and innovations is met with apprehension due tofear of the economic, social, and health risks that come with crop failure (Shilomboleni and De Plaen,
2019; Westermann et al., 2019). Understanding the process of and barriers to scaling are not newlyⒸ ISERD

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developed streams of social science research. Feder and Umali (1993) in their literature review ofagricultural innovation adoption during the prior decade detail risk, information availability, credit,
and farm size as major factors influencing farmer adoption of new technologies. This understandingof risk severely limits ability to scale new agricultural technologies which seek to improve
livelihoods and combat impacts of climate change. Often, scaling is described as either ‘scaling up’or ‘scaling out’. ‘Scaling up’ can be likened to the act of increasing, often in terms of number, speed,size, etc. On the other hand, ‘scaling out’ refers to the act of expansion, such as the spread of aparticular technology to new geographical locations (Wigboldus et al., 2016). This paper will
combine the distinction into the phrase ‘scaling up’ which covers the expansion, replication, andadaption of successful technologies, practices, or innovations to reach a greater number of people(Finn, 2012).
Understanding the role of risk in agriculture adoption and scaling is of particular relevance forsustainable intensification (SI) technologies. SI is a method of agricultural production which seeks
to balance environmental, economic, and social factors of farming. Zurek et al. (2015) definesustainable intensification as, “production of more food on the same piece of land while reducing thenegative environmental impacts and at the same time increasing the contributions to natural capitaland flow of environmental services” (p. 24). This has been further expanded to include social issues,
economics, and the human condition as non-environmental factors for a balanced application of SI
processes (Musumba et al., 2017). Barriers to the adoption of SI technologies include, but aren’t
limited to, demographic variables, farm-location characteristics, fiscal capital, information accessand human capital, and the occurrence of climate shocks. Often, these barriers vary based upon timeand location. For example, Kassie et al (2015) finds the primary barriers of SI adoption in easternand southern Africa to be, “social capital and networks, quality of extension services, reliance on
government support during crop failure, incidence of pests and diseases, resource constraints, tenure
security, education, and market access” (p. 400).
This paper seeks to determine the potential of school gardens as a pathway to scaling agricultural
innovations, particularly SI technologies. Specifically, it will assess if school gardens are able to limit
barriers to adoption such as risk and information availability. Literature is reviewed for best practices
and recommendations conducive to scaling up agricultural technologies using school gardens.
Identified challenges and suggestions are then applied to a case study analysis of a USAID-funded
project on scaling of SI technologies in Cambodia.
OBJECTIVE
Objectives of research are as follows:- to identify current and historical literature regarding scaling and adoption of agricultural innovation- to determine the impact of school gardens as a method of scaling up agricultural technologies.
METHODOLOGYThis paper reviewed theoretical and empirical literature on school gardens with a focus on scaling ofagricultural technologies and innovations. Literature was found using key word searching throughusing the University of Tennessee libraries database and Google Scholar (Google Inc., Mountain
View, CA, USA). Key words included: ‘adoption’, ‘scaling’, ‘agriculture’, ‘school garden’,‘knowledge’, ‘transfer’, ‘education’, and ‘sustainable intensification’. Themes and key activities
were then drawn from the literature to determine best practices of scaling successful school garden
programs. Research gaps and challenges to school garden implementation were determined for eachpiece of literature and used to determine key barriers to scaling.
Findings were then applied to a case study analysis of the Scaling Suitable Sustainable
Technologies (S3-Cambodia) project. S3-Cambodia is a 3-year project funded by the USAID
Sustainable Intensification Innovation lab to examine pathways for scaling. S3-Cambodia will
advance the capacity and roles of scaling agents in technology diffusion through applied research,technical assistance, curricula development and organizational strengthening. This process will
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demonstrate the potential for and provide critical information on scaling technology through local,
national, and regional networks.
Previous research in Cambodia has identified, evaluated, and promoted SI technologies that
addressed gaps within the production systems. These innovations promote the diversification andresilience of smallholder systems by introducing new sources of income and nutrition during seasonal“food gaps,” across different agricultural spaces and serving different functions in livelihood
strategies. S3-Cambodia will pursue diffusion and adoption of technologies for different user groups.
Cambodian youth serve as an entry point to extend target technologies to farm families throughexperiential learning opportunities in schools by establishing “green labs”. Students will receive a
combination of hands-on training in SI practices and STEM-based instruction in SI principles. Thispreparation will culminate in the establishment of student home gardens featuring SI technologies.
The process of technology evaluation and diffusion will be supported by applied, participatory
research on the agronomic and nutritional qualities and marketing potential. In order to improve therate of success of S3, it is important to identify previous work in scaling through school gardens andthe lessons learned from attempts.
RESULTS AND DISCUSSION
Current and Past Studies regarding Scaling and Adoption of Agricultural Innovation
Based on extensive review of literature on school gardens in various world regions, a list of bestpractices to assure scaling of agricultural technologies was developed. Additionally, primary barriers
to scaling up through school gardens were identified (Table 1).
Inclusion of parents in the learning process and upkeep of school gardens was found to be a key
component in assuring a successful and scalable school garden. Active parent involvement increased
the likelihood of knowledge transfer from students to parents. Schreinemachers et al. (2017) in theirassessment of a pilot school garden program in Bhutan highlighted the positive impact of the
program’s inclusion of parental involvement throughout the learning process. Parents were involved
through land preparation, crop care, material provision, and student advising. Additionally, teachers
took the time to visit parents at home and encouraged the use of home gardens. The authors determine
the impact to be that parents were highly accepting of the school garden and families increased theirknowledge about sustainable agriculture and nutritious food. Along the same lines, Schreinemachers
et al. (2019) in their study on school gardens in Burkina Faso involved parents through contributions
in determining garden vegetables choice, volunteer garden upkeep, land preparation, and fencing.
The authors determined the impact of parental involvement to be that children’s knowledge about
agriculture, food, and nutrition improved. However, the scope of the study did not directly assesschanges in attitudes and behavior of children, teachers, or parents. The authors specifically describe
the need for such a component to be included in future study design. Furthermore, barriers to scaling
arise if parents are uninterested are unable to commit the necessary time and energy for school garden
involvement. This is especially true if a teacher spearheading the school garden effort leaves theschool. Ferguson et al. (2019) acknowledge that highly motivated parents/schools are necessary tokeep school gardens going on their own if the project leader leaves.
Inclusion of parents in the learning process was directly tied to another identified best practicefor scaling – the establishment of home gardens alongside school gardens. The utilization of homegardens to test methods and technologies learned by children in school settings allows for streamlined
transfer of knowledge and practices to the parents. This in turn increases usage of new agricultural
technologies on a larger scale within households and communities. Calub et al. (2019) in their
School-Plus-Home Gardens Project (S+HGP) in the Philippines found that through this methodology,
the school gardens became learning laboratories; a place where both students and parents learned
about appropriate technologies and practices relevant to sustainable intensification, organic
agriculture, edible landscaping, climate change, and the interconnection of food and nutrition.
Likewise, Okiror et al.’s (2011) study on school gardens in eight Ugandan schools shows how homegardens allow for the transfer of knowledge from student to parent. The authors find that studentsⒸ ISERD

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were able to effectively pass along their new agricultural knowledge to their parents despite potential
barriers such as language constraints, timidness, and social mores. This was accomplished byproviding visible examples of agricultural techniques to parents through their home gardens, showing
income earned from sale of grown vegetables, and increasing the amount of food eaten at thehousehold level. The likelihood of adoption of these new agricultural practices by parents was
improved when inputs (seeds, chemicals, etc.) were provided for home garden projects. Conversely,
barriers to scaling arose if parents lacked inputs, household land size was small, or there was a poor
relationship between parent and child. Social mores of respect between parent and child could limit
youth’s confidence or ability to share knowledge with their elder. This phenomenon was found to bea key barrier to scaling in Uganda.
In continuation, child to parent transfer of knowledge is evident in the United Nations University
flagship project, network of Regional Centres of Expertise (RCE) on Education for Sustainable
Development (ESD) in Cambodia entitled ‘RCE Greater Phnom Penh’ (GPP). Tabucanon and
Mihara (2016) look specifically at the GPP project entitled, ‘Promoting Sustainable Agriculture at
Kampong Cham Province in Cambodia.’ The authors find evidence of transfer of learning throughschool gardens by incorporating sustainable agriculture and ESD into school curriculum. They
highlight that because most students were children of farmers, they were easily able to discuss andtest learned SI concepts/practices at home using home gardens/fields. The school gardens,
compounded with home garden practice, resulted in increased adoption of sustainable agriculture
practices among farming communities in the region. Similarly, Ran et al. (2013) highlight the‘Promoting ESD through Food, Agriculture and Environment Education in Elementary Schools andRural Communities in Cambodia’ project under GPP. While they also acknowledge the positive
outcome of ESD to be transfer of knowledge, they also highlight lack of resources as a key barrier toscaling of sustainable agriculture. Many schools in the project lacked adequate buildings, desks,
chairs, books, and materials for learning. Additionally, many students are unable to spend necessary
time in school due to commitments on their home farms or financial strain forcing them to seek
additional employment. Lack of social, human, and/or economic capital can severely impact theability of a school garden program to contribute to scaling of sustainable technologies.
The implementation of ESD into curricula in Cambodia detailed by Tabucanon and Mihara(2016) and Ran et al. (2013) highlights another identified best practice of scaling: the establishmentof hands-on, research-based agricultural curriculum in schools. FAO (2004)’s concept note regarding
school gardens calls for the, “integration of school gardening into the curriculum to ensure adequate
time is available for school gardening and related teaching activities without compromising the restof the curriculum” (p. 1). ESD serves as a great example as it is a “holistic and transformational
education which addresses learning content and outcomes, pedagogy and the learning environment”(UNESCO, 2019). ESD incorporates SI learning, promotes exploratory learning, and seeks
collaborative decision-making learning outcomes. However, ESD is not the only pathway tointegrating hands-on, research-based curriculum into schools. Sprague (2016) in her study ofopportunities for and barriers to scaling school gardens using the case study of the Edible Schoolyard
Pittsburgh project notes the importance that school gardens offer, “dynamic learning experiences via
experiential and inquiry-based learning” (p. 18). Remarks from the author’s surveys of garden
educators and parents both centered around the advantages of experimental learning. In fact, someparents indicated that they had actually sent their child to the particular school because of the school
garden curriculum and desired an increased focus on, “outdoor classroom, experimental, inquirybased learning” (Sprague, 2016, p. 97).
Ferguson et al. (2019) focused on the utilization of action research and inquiry-based learningin the classroom, the garden, and through farmer visits. They highlighted this curriculum approachas a key factor of success for their program scaling agroecology through education in Chiapas,
Mexico. Likewise, The Southeast Asian Regional Center for Graduate Study and Research inAgriculture (SEARCA) (2017) also used participatory action research through their discussion of aschool and home gardens project in the Philippines. Through the project, “one hundred and twentyfive (125) lesson plans integrating the concepts of nutrition, organic agriculture, climate change
mitigation and adaptation, and solid waste management were prepared by Grade 4 and Grade 7
Science, Mathematics, English, Edukasyong Pantahanan at Pangkabuhayan (EPP) (HomeⒸ ISERD

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Economics) and Technology and Livelihood Education (TLE) teachers” (p. 2). This resulted insignificant sustainable agriculture and nutrition knowledge increase among students and theirfamilies. However, important to note is that creating well-established experiential school garden
curriculum is a long and tedious process that requires collaboration and patience (SEARCA, 2020).
Building a successful school garden curriculum and then teaching said curriculum is only
possible through collaboration and commitment among all stakeholders. Stakeholders include, but
are not limited to, teachers, parents, students, school leadership, local government, policymakers,
local community members, and research organizations. Without all school garden stakeholders
working together, barriers to scaling become paramount. For example, Tabucanon and Mihara (2016)use a multi-stakeholder networking approach in their study and impress upon readers that it produces,“awareness-raising and learning among farmers, curriculum transformation in schools, andimplementing the notion of sustainable livelihood” (p. 4). SEARCA (2020) also highlight thenecessity of stakeholder collaborations in their briefing of the ‘International Conference on School
Gardens: Leveraging the Multifunctionality of School Gardens.’ The editors describe lack ofpartnership and leadership between academia, local government, policymakers, schools, parents, andteachers as a key barrier to school garden start-up and maintenance.
Sprague (2016) proclaims that collaboration and commitment among school administrators,
teachers, parents, garden coordinators, and community volunteers is necessary for the scaling of an
instructional school garden. She introduces the necessity of a reliable system to track levels of
stakeholder commitment, capacity, and confidence – dubbed the 3Cs. The 3C approach uses aframework that provides a 3C score that serves as, “a measurement of readiness for change or
improvement of a given stakeholder group, arrived at and agreed upon by the stakeholder group”(p.131). Sprague claims this framework serves as a research roadmap with realistic, actionable
timelines that do not cause stakeholders to overextend themselves, creating a balanced, scalable
school garden system. Similarly, Rositsa and Hernandez (2018), in their comparative case study
analysis of three locations for scaling up agricultural technologies, find coalition building between
participants, government, and market institutions to be essential for scaling up of innovations. An
example of appropriate stakeholder collaboration is seen in SEARCA (2017)’s project report onhome and school gardens in the Philippines. The project provided support to the school gardens
through partnership with local government and other stakeholders. Local Government Units (LGU)
were created to support households in establishing home gardens in pilot schools. This was done tosustain necessary resource inputs and services as well as mainstream the project into LGU
development programs.
Concerning resource inputs for school gardens, another best practice of scaling centered aroundthe provision of financial assistance from the government or outside organization for startup andupkeep of school gardens. Many school gardens struggle to maintain the necessary amount of
economic capital to run their programs effectively. For example, in 2012, 4-H, a youth centeredagricultural program from the US, began a club in rural Ghana that encouraged students to planthybrid maize seeds donated by DuPont Pioneer. While Pioneer provided the startup costs, the project
failed in 2015. Pioneer only provided one round of seeds and additional seeds and inputs (pesticides,
herbicides, fertilizers) were simply too expensive for farmers and schools to purchase on their own.
The project would have required substantial subsidies in order to be sustainable long-term (Butler,2014). In Giliberti (2018)’s study on the barriers to adoption and scaling of school gardens he findsthat over 50% of agricultural educators surveyed viewed lack of finances as a key barrier to adoption.
He suggests the offering of monetary incentives in order to increases rates of school garden adoption.
FAO (2004) provides a guideline for minimum budgetary provisions for a national school garden
program including start-up costs, teacher preparation and planning costs, and physical input costs.
If fiscal concerns for a school garden program are diminished, more time and attention is able
to be given to focus on adequate methods for development and scaling. A key barrier found inliterature was focusing too much on the ‘what’ and not the ‘how’ of a school garden program (i.e.,
scaling is not ‘one size fits all’). Trying to implement the school garden curriculum without
considering social, political, economic, geographic, etc. factors will result in substantial gaps insuccess (Wigboldus et al., 2016; Glover et al., 2019). Not one of the studies or projects examined forthis review used the exact same methodology. Each school garden was situated in a uniqueⒸ ISERD

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geographical, cultural, social, and economic setting that required different tools to address barriers
to scaling. To use the same methods of school garden implementation and maintenance in Pittsburgh
as in Ghana would make the scaling of agricultural technologies immensely challenging, if not
impossible.
Further, a key barrier to scaling was found to be poor capacity building for and involvement ofschool heads and teachers. At SEARCA’s ‘International Conference on School Gardens: Leveraging
the Multifunctionality of School Gardens’, capacity building was a key discussion point with overall
issues/challenges section including, “capacity building for school heads, teachers, and parents as partof social and technical preparation to school gardens” (SEARCA, 2020, p. 68). This was often
founded in lack of adequate training for teachers and administration working with school gardens.
DeMarco (1997) found in his study on factors affecting elementary school teachers’ adoption ofschool gardens into curriculum that teachers’ education and knowledge on gardening principals was
essential for implementation. However, their knowledge was found to be considerably lacking. In his
survey of 236 teachers in the United States, only 18 (8%) indicated that, “their training was sufficient
to successfully handle school gardening with their students and no further training was necessary”
and 217 (92%) stated they felt additional training was needed. Undertaken 21 years after DeMarco’s
study, Giliberti (2018)’s study on adoption of school gardens by Agricultural Science teachers in
Alabama found almost identical teacher concerns. He found that perceptions of planning, time,
incentives, and teaching were key barriers to scaling. If teachers did not feel they had adequate school
garden knowledge and training, strategic planning resources, monetary incentive, and/or time outsideof the traditional classroom setting, then school gardens were far less likely to be implemented.
Capacity is also a key barrier to scaling outside of the United States as we see in Okiror et al.
(2011)’s study on transfer of knowledge from school gardens in Uganda. They find lack of practicalskills among teachers and administration support to be key barriers to scaling of school garden
knowledge. Limiting factors were listed as: administrative conflicts between teachers and headteacher, negative actions of the school management committee (SMC), inadequate agricultural skills
among teachers, and ineffective teachers. Conversely, enabling factors were listed as: teamwork
among teachers, supportive school administration, assistance from extension workers, andavailability of skilled teachers. Unfortunately, many teachers and administrators in the Global Southlack the educational resources and training desired for school garden instruction (Okiror et al., 2020;
Ferguson et al., 2019; Tabucanon and Mihara (2016); Comia et al., 2018; Calub et al., 2019;
SEARCA, 2017; Schreinemachers et al., 2017; Schrienemachers et al., 2019).
Table 1 Best practices and primary barriers to scaling through school gardens••••

Best Practices
Including parents in the learning
process and upkeep of school
gardens
Establishment of home gardens
alongside school gardens
Establishment of hands-on, researchbased agricultural curriculum inschools
Collaboration and commitment
among all stakeholders

•
•
•
•
•

Primary Barriers
Focusing on the ‘what’ and not the ‘how’ (i.e.,
scaling is not ‘one size fits all’)Social mores and the relationship between
parent/child
Poor capacity building for and involvement ofschool heads, teachers, and parents
Lack of social, human, and/or economic capital
Unintegrated commitment and partnershipamong stakeholders

As such, it is essential to provide capacity building opportunities to educators to assure effective
scaling of agricultural technologies through school gardens.
It is of note that a limitation to our review was that while the intended focus was to highlightscaling of agricultural technologies, much literature on school gardens focused on nutrition and foodsecurity. While these are important benefits of school gardens, we found literature regarding theknowledge transfer of school gardens to the lacking. However, we were able to pull out the bestpractices that lead to scaling potential to highlight as tools for future use as well as barriers that would
limit a school garden’s ability to be used for scaling of agricultural technologies.
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Case Study: S3 Cambodia
School gardens have the potential to play a key role in scaling sustainable intensification (SI)technologies. They provide opportunities for knowledge transfer through teacher-student-parent
communication. We can apply best practices and address key challenges through analyzing S3Cambodia. S3-Cambodia seeks to target youth as an entry point to extend target SI technologies tofarm families. The project will engage students in experiential learning opportunities by establishing“green labs” at six pilot secondary schools. Students will receive a combination of hands-on training
in SI practices and STEM-based instruction in SI principles from Cambodian teachers trained on this
topic (Figs. 1, 2). This preparation will culminate in the establishment of student home gardens
featuring SI technologies learned in the schools (Fig. 3).
In order to apply best practices and avoid the barriers to scaling S3 will incorporate the findings
from the literature. For example, home gardens will be implemented alongside school gardens as a
key project activity. It will be done to increase learning and to allow school communities to evaluate
new practices before applying them at the field or farm scale. Additionally, hands-on, research-based
agricultural curriculum will be developed and applied in the pilot secondary schools. As part of its
youth development strategy, the project will work hand-in-hand with the Cambodian Ministry of
Education, Youth, and Sport (MOEYS) to develop new 4-H style1 curriculum and adapt existing
curriculum to provide agricultural-based STEM instruction that can be scaled nationally.
Additionally, S3-Cambodia implements the best practice of providing financial assistance to theschools for the startup and upkeep of the school gardens. As a USAID funded project with additional
leveraged funds, S3-Cambodia is able to provide the necessary monies to establish green labs,
trainings, and necessary inputs. To assure green lab infrastructure and curriculum will be maintained
after project close, the project will provide training, supplies, curriculum, and government support toCambodian educators.
Furthermore, S3-Cambodia will assure collaboration and commitment among stakeholders
through adhering to its detailed capacity building plan. This plan includes collaboration andmentorship with project counterparts (CE-SAIN, RUA, UBB 2 ), a train-the-trainer program, anddirect engagement with end-users. However, it is necessary to be aware of the challenges that may
be faced with collaboration of a transnational project funded and directed from the United States but
taking place in Cambodia. For example, the COVID-19 pandemic, though unprecedented, hasresulted in the stunting of first year project activities because of school closures and travel delays.
This was only exacerbated by extreme flooding events in Cambodia during October, 20203.
Thankfully, because the project is solely focused on Cambodia and particular regions therein,
it is not likely to be hindered by the barrier of focusing on the ‘what’ and not the ‘how’. S3Cambodia is very context-specific and leverages knowledge from past projects (i.e., 2015-2020
WAgN-Cambodia project4) and national partners (CE-SAIN, RUA, UBB).
However, not finalized in the project implementation is parental involvement. As the project
moves forward, acknowledging how to incorporate parents into implementation of school gardens
should be a key goal. This will be necessary in order to overcome potential barriers such as social
mores and the relationship between parent/child. For example, this could be done through welcoming
parents to visit the school demonstration plots once a week to view how the SI technologies areworking and gain a first-hand understanding of what their children are doing at school, encouraging
parent volunteers to help in the green labs, or having parents provide their farms for field visits. Such
activities will add to the potential for successful transferring of SI technology knowledge from childto parent.

1 https://4-h.org/about/what-is-4-h/
2 Center of Excellence on Sustainable Agricultural Intensification and Nutrition (CE SAIN), Royal University ofAgriculture (RUA), University of Battambang (UBB)
3 https://reliefweb.int/disaster/fl-2020-000212-khm
4 https://smithcenter.tennessee.edu/women-in-agriculture-network-wagn-cambodia-gender-and-ecologically-sensitive-

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Fig. 1 Students trimming trees in the wild food plant nursery

Fig. 2 Students propagating wild food plants

Fig. 3 Farmer planting grafted vegetables using conservation agriculture techniquesⒸ ISERD

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CONCLUSION
School gardens serve as a useful tool worldwide to enhance student agriculture education and foodsystems knowledge. This paper addressed a key gap in research on school gardens by reviewing
literature to assess their potential to serve as agents of knowledge transfer. While much of current
research focuses on nutrition and vegetable consumption, there is literature supporting school
gardens’ ability to play a key role in scaling agricultural, specifically SI, technologies. Best practices
and barriers were identified for scaling through school gardens. The best practices provided plausible
opportunities for knowledge transfer through teacher-student-parent communication; the barriers
limited these opportunities. S3-Cambodia has strong potential to successfully transfer knowledge of
SI technologies from the green labs to the home farm. The project utilizes a significant amount of
the best practices identified in literature and has measures in place to avoid the barriers. If parental
involvement is increased, project scaling objectives are likely to be met.
ACKNOWLEDGEMENTS
This study was partially supported by the USAID Bureau for Food Security and the Feed the Future
Innovation Lab for Collaborative Research on Sustainable Intensification managed by the Kansas
State University and was led by the University of Tennessee Institute of Agriculture (USAID Federal
Award No.: AID-OAA-L-14-00006; Subaward No.: 5587-UT-KSU-6056). The contents of thismanuscript are the responsibility of The University of Tennessee and do not necessarily reflect theviews of USAID or the United States Government.
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Research article
erd

Factors Driving the Effectiveness of Community Fisheries
Management Resulted from Fisheries Policy Reforms
KAING KHIM*
Fisheries Administration and Royal University of Agriculture, Phnom Penh, Cambodia
Email: kaingkhim@online.com.kh or kaingkhim8@gmail.com

HORI MINA
Kochi University, Japan.

KANG KROESNARoyal University of Agriculture, Phnom Penh, Cambodia

SO NAM
Inland Fisheries Research and Development Institute, Phnom Penh, Cambodia Mekong River
Commission of Lao PDR
Received 11 January 2021

Accepted 2 August 2021(*Corresponding Author)

Abstract The fisheries policy reforms on co-management in Cambodia have been
implemented for almost two decades, starting its first reform in 2000 and its second reformin 2012. These reforms had promoted the organization of 516 Community Fisheries (CFis)around the country. After two decades of the CFis operation, it is noteworthy to identify thedriving factors that brought the functionality and effective operation of the CFi on comanagement of the fisheries resources in Cambodia. The study aims to identify the different
driving factors that led to the functionality and effective operation of the CFis comanagement of the fisheries resources development and sustainability resulting in the
improvement of food security and socio-economic status of the CFi members. To identify
those factors, the study purposely selected 16 CFis among the 516 CFis and randomlyinterviewed 527 CFi members from these CFis. To support the quantitative information fromthe interviews, the study conducted 16 Focus Group Discussion (FGD) in the 16 selected
CFis for validation and qualitative information. The results show that there are two key main
factors influencing the functionality and effective operation of the CFis. First, according to
96% of the CFis members respondents and all FGDs respond, the legal framework that
supports the process of CFi establishment and co-management of the fisheries resources havegiven them the legal rights and opportunity to use and sustain the fisheries resources. The
legal frameworks supporting the CFis establishment includes the Royal Decree on the
Establishment of CFi, the Sub-decree on CFi Management, and the amendments of Fisheries
Law immediately after the reforms and the declaration on CFi Guideline. The second factor
according to 93% of the total respondents and all 16 FGDs is the benefit of being a memberof the CFi. Being a CFi member and small-scale fisher, they were given more access to thefishing ground, harvesting more fish for consumption and income that improve their socioeconomic status, recognition of their value in participating in a co-management concept ofgovernance, capacity building and working together as one and trusting each other. Asidefrom these influencing factors, challenges and lessons learnt were also documented for abrighter future of CFi co-management. These include the actions on the amendment of CFi
legal framework particularly on the CFi economic creation and financial support for afunctional and effective CFi co-management. This should include the expansion of CFi rights
and roles on economic activities and benefits of being CFi member, which needs to be clearly
defined in the Fisheries Law and CFi sub-decree amendment followed by the developmentof the CFi Guideline. The government, development partners and the private sector shouldⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2021) 12-2

financially and technically support the CFis to function and operate effectively in comanaging the fisheries resources development and sustainability.
Keywords fisheries policy reform, community fisheries (CFi), CFi legal framework,
benefits of CFi membership, fisheries management

INTRODUCTION
Cambodia is endowed with rich natural fisheries resources in both freshwater fisheries from the
Mekong Region and Tonle Sap Lake system, and the marine fisheries from the coastal region. Fishis one of the most important foods and necessities of life for a rice-fish-eating population, andpotentially an important contributor to improve food security and nutritional status of the population.
Therefore, the management of the fisheries resources is an important responsibility that requires
development and improvement overtime according to its context, demands and needs that will occur.
As the situation became unfavorable for subsistence farmers-fishers to get equal benefits from thenatural fisheries resources, the government decided to reform the fisheries management in October2000 by cancelling 56% of the fishing lots and providing to the public/fishers for communal use.
Finally, in 2012 the government cancelled all remaining fishing lots (industry/large fishing scale) in
the Great Lake as part of the deep reform of the government to sustain the fisheries resources andimprove the socio-economic development of the communities in the rural areas. To support thisreform, the government supports the small-scale fishers to organize Community Fisheries (CFi) to
implement fisheries co-management with the government to develop and sustain the fisheries
resources.
As a result of the fisheries policy reforms for almost two decades, the government was able toestablish 516 CFi around the country. Witnessing the impacts of the reforms, it raises the questionof what factors have driven the functionality and the effective operation of the CFi co-managementthat can be learned to improve CFi legal framework for the sustainability of the fisheries resource
management in Cambodia.
Table 1 List of CFi target study by province and region
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16

CFi Name
CFi Kaoh Kaev
CFi Kanlaeng Pe
CFi Roha Suong
CFi Phneat Koh Pongsath
CFi Chong Khneas
CFi Samaki Kampong Kou
CFi Samaki Akphyrak Stung Kombot
CFi Beung Krapet
CFi Rokakoy
CFi Chroy Check
CFi Boeung Chulen
CFi Put Sar Cham Pei
CFi Kok Thlok
CFi Trapeang Ropov
CFi Trapeang Sangke
CFi Tumnub Rolok

Province

RegionKampong Chhnang
Battambang
Bantheay Meanchey
Siem Reap

Tonle Sap Great
Lake

Kampong Thom
Tboung Khmom
Kampong Cham
KandalMekongTakeo
KampotPreah Sihanouk

METHODOLOGYⒸ ISERD

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Sixteen (16) CFis were purposely selected from the three regions (Tonle Sap, Mekong and Coastal
region) based on the geographical fisheries ecosystem in Cambodia. The CFIs were organized andestablished in these three regions after the implementation of the fisheries reforms as shown in Figure
1 and table 1. A total of 527 CFi members (169 women, 32%) as respondents was randomly selectedin the 16 CFi members’ list. Primary data was collected through a face-to-face interview with the
527 respondents using a structured questionnaire that was conducted in 2018. The 16 Focus Group
Discussion (FGD) from the 16 CFis was conducted in 2020 providing qualitative information to
support the quantitative data from individual interviews. The 16 FGDs were facilitated with the CFi
Committee (CFiC) members to get their views and perceptions about the factors driving CFi
functionality, effective operation and identifying the strengths, weaknesses, opportunities and threatsof each CFi using SWOT analysis. FGD data is mainly on qualitative analysis to substantiate thequantitative analysis with the multiple responses of CFi members on key indicators to understand theeffects and causes of factors driving the functionality and effective operation of CFi management
after the fisheries reforms in Cambodia.

Fig. 1 Study sites location
Table 2 Factors driving CFi functionality and effectiveness CFi management-

Factor*CFi legal framework’s support
CFi membership’s benefits
Financial and technical support
Collaboration and support and from local authorities
Collaboration and support from technical agencies
Collaboration and support from DP
CFiC ability and capacity
Participation of CFi members
Others (people willingness, support and work together…)

Frequency

Percent

505
488
475
466
443
433
339
321
303

96
93
90
88
84
82
64
61
57

* Multiple responses

RESULTS AND DISCUSSION
There were several key factors driving the functionality and effective operation of CFi comanagement reported by the 527 representatives of CFi members and 16 CFi Committees aspresented in Table 2. The factor with the highest percentage 96% of the total respondents is theprovision of CFi legal framework to the community fisheries. The second important factor mentionedⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2021) 12-2

with a total percentage of 93% of the CFi members respondents and all 16 Focus Group Discussion
from CFi Committee is the benefits that they received being a member of the CFis. Moreover, otherfactors presented in Table 2 below are same important parameters that interlinked with the otherfactors that contributed to the functionality and effective operation of CFi co- management of thefisheries as a whole.
The results of the 16 Focus Group Discussion with CFi Committee members expressed theirviews that CFi legal framework and CFi members’ benefit are the most key necessary factors driving
the functionality and effective operation of CFi in their co-management of the fisheries resources.
While the other factors are of equal importance contributing to the functionality and effective
operation of CFi co-management of fisheries resources. The study explored the reasons for these two
factors as presented in Tables 3-4 below.
Table 3 Reason of CFi legal framework driven factor the CFi effective management-

Reason*Legal guidance for CFi establishment
Official and legal recognition of CFi
Legal guidance for CFi function and management
Official support from the government and development partners
Fisher’s rights and responsibility in the natural fisheries resourcesmanagement
Increased support and collaboration more than before CFi
establishment
Others (CFi empowerment, commitment and resource ownership)

Frequency

Percent

521
518
502
467
436

99
97
95
89
83

328

62

311

59

* Multiple responses

Table 3 presented the reasons why CFi legal framework is an effective driver for the CFi
operation and co-management. Around 99% of all CFi member respondents and all CFiC Focus
Group Discussion expressed that the legal framework had guided them to establish their CFi
organization, this includes the Royal Decree on the Establishment of the Community Fisheries (NorSor/Ror Kor Tor/0505/240, 2005) for them to work closely with the government in managing anddeveloping the fisheries resources. According to 97% of the CFi member respondents, the legal
framework had been an instrument for them to be recognized by other stakeholders including
development partners as an official and legal entity that co-managing the development of the fisheries
resources. Around 95% of the CFi member respondents mentioned that the legal framework hadprovided a clear roles and responsibilities to the CFs including their mandates to function effectively
in co-managing with the government the development and sustainability of the fisheries resource
sustainability. The role and responsibility of the CFi are clearly indicated in the Sub-decree on CFi
management (No. 25 OrNor Kror. BorKor, 2007). These three top reasons are inter-related and themain provision of the official and legal recognition of the Community Fisheries organization in theform of co-management approach that are financially and technically supported by the governmentand development partners according to 89% of CFi member respondents. Based on these legal
frameworks the CFis were provided and promoted fisher groups’ tenure rights, user rights, and rights
to protect and co-manage their natural fisheries resources to develop and sustain in an effective way.
The CFis legal recognition is also indicated in the amended Fisheries Law of 2006 as a result of thefirst fisheries reform in 2000, which never before in the history of fisheries resources managementin the country. In article 59 of Chapter 11 on Community Fisheries of the Fisheries Law, stated that“all Cambodian citizens have the rights to form Community Fisheries in their own areas on a
voluntary basis to take part in the sustainable management, conservation, development and use of
the fishery resource”. Therefore, the legal framework is an important legislation and key factor at thegrass-root level and people can officially and legally form their Community Fisheries organizationthat legally provides their rights and responsibility in protecting and co-managing their naturalⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2021) 12-2

fisheries resources in an effective way. Moreover, this local community fisheries organizations havereceived substantial support and cooperation with the local authorities from all levels, development
partners and private sector more than before when they do not have their CFi organization. Finally,
the respondents also mentioned that the legal framework has empowered them socially andeconomically including mainstreaming of gender and fisheries resources ownership.
Table 4 shows the reasons why being a CFi membership benefits is a driving factor for thefunctionality and effective operation of the CFi in a co-management approach. According to 97% of
the total CFi member respondents the benefits of being a CFi member is about building trust among
each other, among villagers with other villagers, among fishers with other fishers, in particular forsmall-scale/family and poor fisher families. Another reason is the unification among the community
fishers and working as a group and organizations and recognizing equity and rights to their fisheries
resources, especially for the family scale fishers in the CFi fishing areas. According to 89% of theCFi member respondents after becoming members of the CFi they were provided more access to theCFi fishing ground that was previously fishing lots.
Table 4 Reason of CFi membership benefits driven factor the CFi effective management-

Reason*Building trust to each other (villagers and villagers) as united
Being recognized as group work (work together)
Equal rights for fishing by family scale
Can do fishing (more access to fishing ground) more than
beforeTheir membership and participation being recognized andvalued (resources ownership)
Gaining knowledge on fisheries resource protection andmanagement
Building empowerment and capacity (from meeting,workshop…)
Voices and demands can be addressed
Received more support for social welfare and poverty
alleviation
Others (more safety than before, no stolen, no violence…)

Frequency

Percent

518
502
480
467

97
95
91
89

436

83

388

74

353

67

321
313

61
59

301

57

* Multiple responses

Other benefits of being a CFi members include; the official recognition and value from otherstakeholders, the CFi builds trust and foster cooperation among the community which improve socialand economic development within the community, the CFi members gain knowledge on how toprotect and manage their natural fisheries resources in the effective and sustainable way, empoweredand built capacity of individual member and fisher group through participating in meetings,
workshops and trainings as well as other events taken place in the CFis area, the government andother stakeholders heard their voices and demands, and noted and addressed, being member , theyreceive more support for social welfare and help to alleviate their family poverty, and finally theirliving conditions have improved including security, violence, gender, and child labor were taken
into high consideration in the CFi.
However, there are still challenges that the CFis are facing as presented in Table 5, these include
generation of income or finance that will support the CFi operation especially the co-management
activities for the development of the fisheries resources. The CFi respondents expressed that the CFi
legal framework should have a section that articulates the possible sources of income for CFi in orderto generate their own income or finance in a collective way to effectively function and operate theiractivities for the conservation of the fisheries resources and help their CFi members on their social
welfare and poverty alleviation. Another challenge that was ranked high is the limited benefits ofsome CFi members regarding their rights for fishing in the CFi fishing areas because outsiders couldⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2021) 12-2

still encroach and fish in CFi fishing areas. They suggested that the CFi legal framework should
consider defining the differences between the fishing rights of the CFi members and outsiders thensupport the implementation of control and surveillance of these outsiders. They further suggest thatCFi members should have all the rights in doing fishing freely in the CFi fishing area, while non-CFi
members and outsiders should pay fishing fee according to the legal fishing gears used, which need
to be defined clearly and effectively applied based on the CFi by-law and regulation. Other key
challenges are also important areas for improvement, which require actions accordingly.
Table 5 Key challenges facing the CFi effective management-

Key challenges**
Lacking of CFi self-financial support and generation
Still limited benefits for being CFi members regarding with rights for fishing,
everyone can do small-scale fishing in CFi area
Limited financial support for CFi operation and functioning from the state anddevelopment partners
5 years of CFi Area Agreement is short, which could not enough to produce
tangible imparts of CFi development and management
Poor enforcement of CFi by-laws and internal rules by members and nonmembers in CFi villages
Poor implementation of CFi Area Management Plan due to budget lacked
CFi Committee (CFi leader team) capacity is still limited, leading to take poor
rules and responsibilities, and affectively poor CFi function and management
Still limitation support from local authorities
Limitation of technical support and follow up by technical agencies
Local people’s awareness on CFi legislation/legal framework is still limited

Ranking
1
2
3
4
5
6
7
8
9
10

** Results of FGD

CONCLUSION
Community Fisheries is a voluntary fisher organization in Cambodia, which is officially establishedand legally recognized by the state with the provision of suitable legal framework, which never before
in the history of fisheries management in Cambodia. It is a prime objective and achievement of theGovernments’ fisheries reforms, in 2000 and in 2012, to ensure that the local fisher communities andsmall-scale fishers can obtain access to the fisheries resources for food, livelihood and poverty
alleviation. The achievements and results produced after the fisheries reforms are due to the supportof the legal framework for CFi that was provided at the right time and direction. Through these CFi
legal frameworks, the small-scale and poor fishers are receiving benefits and rights to share theirroles and responsibilities for the co-management of their natural fisheries resources for development
and sustainability. These are the most important factors that guide and drive the functionality andeffective operation of the CFis. However, there are still key areas that are facing challenges for the
CFis to be more functional and effective in co-management of the fisheries resources in the long run,which included the improvement of CFi legal framework. The CFi respondents recommended theimprovement of the legal framework to consider the provision of guiding the CFi to generate income
to self-finance their activities, suitable fisheries related livelihoods, and harvesting their resources.
Finally, the CFis recommended to define clearly the rights of the CFi members and nonmembers/outsiders in fishing in the CFi fishing areas. They suggest that they should be given higher
benefits for being a CFi members as well as CFi committee members as prime incentives for their
participation and efforts to actively protect and co-manage the natural fisheries resources
development in an effective and sustainable manner.
ACKNOWLEDGEMENTⒸ ISERD

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It is gratefully acknowledged the useful financial support from FAO HQ Rome for undertaking theimportant study and assessment on the impacts of CFi management for securing small-scale fisheries
in Cambodia. The study was a participative approach, undertaken by active staff of the Community
Fisheries Development Department (CFDD) of the Fisheries Administration (FiA) of the Royal
Government of Cambodia, are gratefully acknowledged and appreciated.
REFERENCESCBNRM Learning Institute. 2009. Trend, problems faced and innovation: Community based natural resourcesmanagement in Cambodia. Cambodia.
CFDD/FiA. 2017. The effectiveness of community fisheries management in Cambodia. Cambodia.
FiA. 2008. The compilation of legal instruments related to community fisheries in the Kingdom of Cambodia.
Fisheries Administration, Cambodia.
FiA. 2019. The strategic planning framework for fisheries 2010-2019: Background information. Fisheries
Administration, Volume 2, Cambodia.
FiA and FAO. 2013. Participatory assessment of community fisheries in Cambodia. Fisheries Administration,
Cambodia.
FiA and FAO. 2018. Community fisheries of Cambodia: Harbingers of the voluntary guidelines for securing
sustainable small-scale fisheries in the context of food security and poverty eradication. Analysis from a
Participatory Assessment, Fisheries Administration and FAO, Cambodia.
FiA, IDRC and CBNRM. 2006. Key factors affected the achievement in Community Fisheries Management.
In Nao, T. and Pol, S., History of Fisheries Management in the Kingdom of Cambodia, Cambodia.
Ngor, P., Suy, S., Heng, K., Thor, S. and Thownsley, P. 2010. Pilot participatory policy impact assessment:
Fisheries policy related to Community Fisheries development. Cambodia.

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Research article
erd

Status of Cassava Production and Distribution Channels in
Cambodia: Prospects for Sustainable Production
ITO KASUMI*International Center for Research and Education in Agriculture,
Nagoya University, Nagoya, Japan
Email: kasumito@agr.nagoya-u.ac.jp

NAKATANI AYA
Graduate School of Bioagricultural Sciences, Nagoya University, Aichi, Japan

BABA TAMON
College of Letters, Ritsumeikan University, Kyoto, JapanNOMURA HISAKO
Faculty of Agriculture, Kyushu University, Fukuoka, Japan

THAN THA
Faculty of Agriculture and Food Processing, National University of Battambang,
Battambang, Cambodia

SREAN PAO
Faculty of Agriculture and Food Processing, National University of Battambang,
Battambang, Cambodia
Received 21 January 2021

Accepted 2 August 2021(*Corresponding Author)

Abstract Cassava is expected to become a major industrial crop in Cambodia, but moststudies on its cultivation only discuss the potential for improving its production scale,productivity, and suitable cultivation techniques, including ways to protect the crop from
diseases and pests. However, sustainability of its cultivation as the country’s main industrial
crop cannot be achieved only by introducing agronomically suitable cultivation methods. The
cultivation must be economically viable, socially beneficial, and environmentally
sustainable. Therefore, this study aims to identify and analyze the characteristics of cassava
cultivators and their business activities, the current distribution channel and the challenges
and prospects for sustainable cassava cultivation in Cambodia. Semi-structured interviews of
24 cassava cultivators were conducted in two major cassava-growing provinces in
Cambodia—Battambang and Pailin—to understand the series of production events, including
the way they sell their produce. In addition, owners of six consolidating points that collectand process cassava root to sell domestically or for export were interviewed about their sales
partners and destinations to identify the distribution channel. As a result, three different
distribution types, from producers to collecting points, were identified, and their selection
criteria appeared to be the distance between the producers and the collection points. The direct
and indirect destination of the produce from the collecting points was identified as Thailand.
The identified distribution channel, including collection points, comprised only cassava
cultivators and exporters to Thailand, and no production specialization was observed. Thisreveals that building an efficient and viable distribution mechanism and strategy by utilizing
the existing system will be one of the most important challenges in making cassava
cultivation a major industrial crop and thus expanding the revenue source for the country.
Keywords cassava, distribution channel, small farmers, CambodiaⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2021) 12-2

INTRODUCTION
Cassava (Manihot esculenta Crantz) is an important food crop cultivated in more than 90 countries,
mainly in the tropical and subtropical latitudes in Latin America, Africa, and Asia. Cassava products
are consumed by 770 million people worldwide. In Cambodia, cassava is one of the most important
cash crops for farmers, even though it is consumed less as human and animal food. The market
demand for dried cassava chips has increased because of ethanol production and starch processing
in China, which is the largest buyer of the produce (RGC, 2020). Cambodia is located between
Thailand and Vietnam, which are the two main suppliers of cassava to the Chinese market. However,these two countries have limited cassava cultivation area because of their governments’policies. Thissituation provides an opportunity for Cambodia to become a major producer of the crop in the region.
Cassava cultivation in Cambodia has been increasing rapidly since 2010, and it has become thecountry’s largest crop, exceeding rice, which is the country’s staple food (Fig. 1). In 2020, over 13
million tons of fresh cassava that is more than that of Vietnam were harvested (FAO, 2021). Cassava
has been exported indirectly to China as a raw material through Thailand and Vietnam, therefore, thecountry is unknown in the market and is recognized as a marginal supplier despite being 3 rd in theregional and 7th in the global production of the crop (FAO, 2021). Recently, cassava is envisioned to
be a strategic crop for the country in line with the Cambodia Industrial Development Policy 20152025 (RGC, 2015). Furthermore, the government of Cambodia has prepared a National Policy on
Cassava 2020-2025 to transform the country into a cultivation and processing hub of the crop by
improving the cultivation, processing, and exporting mechanisms (RGC, 2020).
The development must be economically viable, socially beneficial and environmentally
sustainable, and it must be beneficial for both commercial and individual producers because cassava
cultivation is an important source of income for small-scale producers in Cambodia. To establish
such a system, it is essential to identify current status and challenges from both socio-economic andagronomic points of view. However, the majority of existing studies have focused on the potentialof cassava cultivation in Cambodia from an agronomic point of view, including cultivation methods(Sopheap et al., 2012; Ou et al., 2016), occurrence of insect pests and diseases (Wang et al., 2015;
Uke et al., 2018), management of insect pests and diseases (Smith et al., 2018), and land suitability(Teamhy et al., 2017). Although a limited number of studies have reported on cultivators’ perception(Sopheap et al., 2011, Chanda et al., 2016) and their profit (Sopheak, 2017), little is known about
locally existing sales and distribution mechanism that will contribute to maintain or improve theeconomic viability of cassava cultivation in Cambodia.
（1,000 t）
14,000Study area
12,000Laos

Battambang

Production

10,000
8,000

Th

6,000

d
an
ail

PailinRice
4,000

Tonle sap lake

Road # 5
m
na
et
Vi

2,000

Cassava

Main production area

Year

2015

Phnom Penh

2018

2009

2012

2003

2006

1997

2000

1991

1994

1985

1988

1976

1979
1982

1967

1970
1973

1961
1964

0

Study area

（FAO 2021）

Fig. 1 Cassava production in Cambodia

Fig. 2 Study area

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IJERD – International Journal of Environmental and Rural Development (2021) 12-2

OBJECTIVE
This study aims to identify and analyze the characteristics of cassava cultivators and their businessactivities, the distribution channel, and the challenges and prospects for its sustainable production in
Cambodia.
METHODOLOGYThis study selected two major cassava producing provinces in Cambodia—Battambang and Pailin—as the study area (MAFF, 2018). These two provinces are located in the north-western part of thecountry, and both border on Thailand, the third largest cassava producing country in the world (Fig.
2). Semi-structured interviews of 24 cassava producers in the study area were conducted tounderstand their cultivation methods, annual schedule, and sales destination. Additionally, ownersof six collection and processing points (known as silos in Cambodia) that collect cassava roots, makedried chips, and sell domestically or export them were interviewed about their customers and saledestinations to identify the distribution channel. The collection and processing points were locatedmostly in Pailin, along the National Road No. 57 near the country’s border with Thailand. This survey
sampled six major points to conduct the interviews. The field surveys were conducted between July
2017 and February 2018.
RESULTS AND DISCUSSIONInterviewees and Characteristics of their Households
Table 1 shows the numbers of producers interviewed for this study as well as their valid responses
for analysis. Cassava cultivators in Battambang were younger, had been living there for longer time,and had longer experience of agriculture than those in Pailin. By contrast, cultivators in Pailin hadlarger cultivation area, more experience in terms of cassava cultivation, and a larger variety ofagricultural produce. The Pailin province was invaded by the Khmer Rouge because of its extensive
gem deposits and former leaders of the Pol Pot regime continued in the area even long after the war.
Additionally, the province was extensively mined during the war, and demining activities continue.
Therefore, it is inferred that migration from the other provinces and agricultural production became
active very recently, and that these situations influenced cassava cultivation.
Table 1 Interviewees
Battambang
Summary of producers*(n=18)
Age (year)
35.0
Length of stay（year）
23.1
Agri experience (year)
18.4
Cassava experience (time)
2.3
Cassava area（ha)5.3
Other Agri products (ha)10.6

Table 2 Scale of production
Pailin
(n=6)
50.8
11.3
9.8
4.0
12.5
18.5

Cassava* Own land* #of
(ha)
(ha)
HHs
Small (< 5ha)
2.55
5.76
14
Medium (5ha < 10 ha)
5.50
11.22
5
Large (> 10ha)
21.50
17.33
5
* average
Created by authors according to the results of the survey
Area* average

Created by authors according to the results of the survey

To analyze the characteristics of cassava cultivators, the interviewees valid answers weredivided into three groups according to the size of their cassava plantations. Those with less than 5haof cassava plantations were categorized as small-scale (58.3%), 5ha or more but less than 10ha as
medium-scale (20.8%), and 10 ha or more as large-scale (20.8%) (Table 2). Even though the largescale cultivators owned larger farmlands, their cassava plantations were even larger than their own
lands. This indicated that large-scale producers were renting farmland to produce cassava. Smalland medium-scale producers were using about half their own farmland to cultivate cassava. However,the small- and medium-scale cassava cultivators grew slightly more varieties of crops than theirⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2021) 12-2

large-scale counterparts (Fig. 3). These results imply that unlike the others, large-scale producers
focus more on cassava cultivation than other crops. However, almost half of the small- and mediumscale producers were not cultivating rice, an important staple food in Cambodia; therefore, they may
be part-time farmers who have income generating activities other than agriculture that make themcapable of buying rice (Fig. 4).
(# of items)

(HH)

3.5
3.0

10
3.2

8

2.5
2.3

2.0

With rice

9

Without rice

6

2.2

1.5

4

1.0

5

0.0

>5ha

5ha -9ha

3

3

2

0.5

2

2

5-9ha

10ha<

0

10h<

<5ha

（area）

Fig. 3 Other agricultural production（area）

Fig. 4 Rice production of cassava producers

Production Status
Annual schedule and cultivation methods were compiled as Fig. 5 according to the results ofinterview. Cultivators in the study area plant cassava stems at the beginning of the rainy season, andall of them used stem cuttings from the previous crop as usual. For most cassava varieties, the stems
can be stored vertically in the shade for up to two months before planting (IAEA 2018). Some
producers also bought stem cuttings from neighbors and sellers for planting and replanting. The
cassava is harvested after 9–12 months, generally after the onset of the dry season. Most cultivators
prepare their land for the next cultivation in February and March, immediately after the harvest.
Rainy season

Mar Apr May Jun

Aug Sep Oct Nov Dec Jan Feb Mar
Replant

Reasons：lack of water
pests/diseases
Source ： buy fromneighbors

Ship

Production
methods

Seedling ： Last production
neighbors, sellers
Varieties： Unknown
Planting ： Vertical
Density ： 5,174 stems/ha

Jul

Dry

HV

Plant

Bed

Plow

Procedure

Dry

Period： 9-12 months
Parts ： Tubas, stems
Form ： Row, driedConsume： No

Fig. 5 Annual production schedule and methods
Distribution from Producers to Collection and Processing Points
This study identified (Table 3) three different types of cassava distribution: (1) harvested, transported,and sold to collection points directly by producer; (2) harvested, transported and sold to collection
points exclusively by middleman; and (3) harvested by producers, but transported and sold bymiddlemen. Cultivators adopting Type 1 need to own or rent all necessary machines and equipment
for planting, harvesting, and transportation, such as power tillers, harvesters, and trucks.
By contrast, those adopting Type 2 do not need any machinery or equipment except those forland preparation and planting. Cultivators adopting Type 3 need to own or rent machines andequipment for both planting and harvesting but not for transportation. The results discussed in theprevious section show that most cassava cultivators are also growing several other crops. These
cultivators have some machinery available to them that can also be used in cassava cultivation.
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Middlemen who harvest or transport the cassava roots are mostly large-scale cultivators in theneighborhood. According to Table 3, the majority of cultivators are categorized as Type 3, however,there is no clear relationship between their production scale and the distribution type. At the sametime, the producer’s location (province) seems to have an effect on the distribution type. Most
cultivators (six out of five) in Pailin belong to Type 2, whereas only one of 18 cultivators in
Battambang belong to this type. On the contrary, most producers (14 out of 18) in Battambang belong
to Type 3.
Table 3 Flows from cultivators to collection points and selling price(1) Producer only
BTB (%)PL (%)
Production scale< 5ha
1 (100.0)
2 (40.0)
5-9 ha0
1 (20.0)> 10ha0
2 (40.0)
sub-total
1 (100.0)
5 (100.0)
Total number (%)
6 (25.0)
BTB: Battambang province, PL: Pailin province“-“indicates no respondents for the category(2) Middleman only
BTB (%)PL(%)(3) Combination
BTB (%)PL (%)

2 (66.6)
1 (33.3)03 (100.0)

8 (57.1)
3 (21.4)
3 (21.4)
14 (100.0)0000
3 (12.5)

Total (%)

1 (100.0)
14 (58.3)
0
5 (16.7)05 (25.0)
1 (100.0)
24 (100.0)
15 (62.5)
24 (100.0)
Created by authors based on the results

The number of cultivators and the selling price of cassava roots according to distribution types
and location (province) are shown in Table 4, and the selling prices according to production scaleand location are shown in Table 5. In these tables, cassava roots are categorized as fresh and dried,
and the numbers of cultivators and sales are analyzed according to the province and distribution type.
The dried cassava roots are generally made by chopping them into small bits and drying them in thesun. Drying reduces the weight by two thirds, making it easier to transport even though chopping isheavy work and requires a large space for drying.
Table 4 shows that five out of six producers in Pailin sell their cassava as fresh roots, whereas
majority of producers (14 out of 24 producers) in Battambang sell their cassava as dried roots. Thisdifference might also have influenced the selection of distribution type. Table 6 shows theinformation about the collection and processing points surveyed, where both producers andmiddlemen were selling their cassava roots. Five out of six points were in Pailin, which is closer tothe border with Thailand than Battambang. It is inferred that producers in Battambang were trying
to avoid heavy and costly work such as harvesting and transporting the cassava, and either depended
more on middleman or dried the roots so that they could transport them in one lot. It is also inferredthat proximity to the collection points and ease of transportation allows cultivators in Pailin to savethe effort of drying the roots and they do everything themselves as mentioned in Type 1. Although it
is difficult to analyze the selling price according to the distribution type owing to lack of data forsome categories, the price of fresh roots in Pailin is slightly higher than that in Battambang. It is
assumed that the selling price reflects the transportation fee from the collection points to the next
destination, which is mostly Thailand.
Table 4 Distribution types from producers to collection point and selling price(1) Producer only
(2) Middlemen only
price
HHs
price
HHs
Fresh roots
177.485 (38.5)
135.443 (23.0)BTB
0 (0.00)
176.67
3 (42.9)
PL
177.485 (83.3)
0 (0.00)
Dried roots
440.001 (6.7)0 (0.00)
BTB 440.00
1 (6.7)0 (0.0)PL
0 (0.0)0 (0.0)
BTB: Battambang province, PL: Pailin province“-“indicates no respondents for the category.

Ⓒ ISERD45(3) Combination
Total
price
HHs
price
HHs
192.255 (38.5) 182.97
13 (100.0)
184.254 (57.1) 181.00
7 (100.0)
224.25
1 (16.7) 185.28
6 (100.0)
492.3614 (93.3) 488.87
15 (100.0)
492.3614 (93.3) 488.87
15 (100.0)
0 (0.0)0(0.0)
Created by authors based on the results

IJERD – International Journal of Environmental and Rural Development (2021) 12-2

An analysis of the production scales and selling prices according to location revealed that the
average selling price at each location is the lowest for middle-scale cultivators and the highest forlarge-scale producers (Table 5). This trend was observed for both fresh and dried roots. However,this survey did not have enough variables to explain the cause.
Table 5 Production scale and selling price by location
Small (< 5ha)
Medium (5<10 ha)
price
HHs
price
HHs
Fresh roots
183.637 (53.8)
166.003 (23.1)
BTB 185.75
4 (57.1)
168.502 (28.6)
PL
180.813 (50.0)
161.001 (16.7)
Dried roots
509.449 (60.0)
429.003 (20.0)
BTB 509.44
9 (60.0)
429.003 (20.0)PL0 (0.0)0 (0.0)
BTB: Battambang province, PL: Pailin province“-“ indicates no respondents for the category.

Large (>10ha)
Total
price
HHs
price
HHs
198.423 (23.1) 182.97
13 (100.0)
187.001 (14.3) 181.00
7 (100.0)
204.132 (33.3) 185.28
6 (100.0)
487.003 (20.0) 488.87
15 (100.0)
487.003 (20.0) 488.87
15 (100.0)
0 (0.0)0(0.0)
Created by authors based on the results

Table 6 Surveyed collection and processing points
Collection point

A

B

C

D

E

F

Location

PL

PL

PL

PL

PL

BTB

Chipping period

Dec-Mar

Nov-Mar-*Nov-Apr-Oct-MarAmount (t/day)

1,820

20〜30

-

50

-

200

Production (ha)6300
15* Collection points that do not do processing activities such as chipping and drying
Average daily quota for chipping workers was 1 ton per person of family.

50

Yard staff

Yard staff

Middlemen

All of them werecassava producers*1 Producers *2 Middlemen

Other countries

Producers

Domestic
consumers

Starch, ethanol andanimal feed factories

Yard staff

Thailand

Yard staff

Other yards

Collection & processing yards

Cassava producers

P*1
M*2

Buyers from Thai

Channels of interviewees
Channels indirectly identified from interviewees

Fig. 6 Distribution channel of cassava root
Destination: From Collection Points to Consumers or Exporters
To study their modes of operation and the destination of collected cassava roots (Table 6), data werecollected from interviews with the owners of six collection and processing points and revealed
several types of operations. Whereas collection points A, B, D, and F were making dried cassava
chips, the other two were not. From these consolidating points with processing facilities, the cassava
chips are sent to other collection and processing points, starch factories, and even directly to ThailandⒸ ISERD

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by trading companies from that country. This type of consolidating point was trading both fresh anddried roots. The fresh roots were either sold to other consolidating points for processing or exported
to Thailand without processing, whereas all the dried roots were directly exported to Thailand. Freshroots exported to Thailand are processed in starch factories across the border. Collection points
without processing facilities such as C and E (Table 6) were only transporting and selling fresh roots
to starch factories which in turn exported them mainly to Thailand. Thus, the characteristics ofcollection and processing points are found to have a relation to the destination of the collected cassava
roots. Interestingly, most collection and processing points are established and operated by large-scalecassava cultivators such as A, C, E, and F in Table 6. In addition to owning large cassava plantations,these cultivators also play the roles of harvesters, middlemen, collectors, processors, transporters,
and traders. They collect cassava roots from small-scale cultivators to fill the gap between the
demand from Thailand and their own production. In sum, this research has found that the cassava
distribution channel in the study area comprised only various types of cassava cultivators and tradersfrom Thailand, and there was no division of labor for efficiency (Fig. 6).
CONCLUSION
This study aimed to identify cassava distribution channels in Cambodia as well as the characteristics
of cultivators and their mode of business operations. The results revealed that the production scaleand characteristics of the producers, such as average age and experience in agriculture, especiallycassava cultivation, are influenced by the historical and geographical characteristics of each province.
This study identified three different types of distribution channels from producers to consolidating
points. The first type is direct distribution wherein all related processes such as planting, harvesting,transporting and selling are handled by the cultivators. In the second type, apart from cultivation,
everything is handled by middlemen. The third type features a combination of both cultivators andmiddlemen. The distribution type also depended on the type of root being traded—fresh or dried—
and the distance from farms to the collection and processing points. Moreover, analysis of selling
price and characteristics of income from cassava cultivation need further study with sufficient
sampling with statistical methods. This study also found that large-scale cassava cultivators, who
also operate root collection and processing points, were playing important roles as collectors,
middlemen, and transporters in the cassava root distribution system of Cambodia. The existing
cassava root distribution mechanism in the country is well-concerned about its benefit to cultivators
including small-scale producers; however, there is more room for improving efficiency such as
introducing division of labor. Thus, building an efficient and viable distribution mechanism andstrategy by utilizing the existing system as its base will be one of the most important challenges formaking cassava a major industrial crop and increasing revenue from its cultivation. The results ofthis study were based on qualitative analysis only due to small number of samples. Further studies
with quantitative analysis on cultivators’ profits, characteristics of sales activities, and distribution
types according to their production scale and location are desirable to find out suitable distribution
mechanism that is efficient and viable as main industrial crop in Cambodia.
ACKNOWLEDGEMENTS
This research was supported by Science and Technology Research Partnership for Sustainable
Development (SATREPS) in collaboration with Japan Science and Technology Agency (JST,JPMJSA1508) and Japan International Cooperation Agency (JICA). We would also like to thankDeutsche Gesellschaft für Internationale Zusammenarbeit for their cooperation.
REFERENCES
Chanda, P., Tara, P. and Schiller, M.J. 2016. Farmer perception on the causes and effects of cassava witches’
broom (CWB) on cassava production in three provinces of Cambodia. International Journal ofEnvironmental and Rural Development, 7 (1), 186-191.
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Food and Agriculture Organization (FAO). 2021. Retrived from http://www.fao.org/faostat/en/#home
IAEA (International Atomic Energy Agency). 2018. Cassava production guidelines for food security andadaptation to climate change in Asia and Africa. Prepared by the Joint FAO/IAEA Division of Nuclear
Techniques in Food and Agriculture.
MAFF (Ministry of Agriculture, Forestry and Fisheries in Cambodia). 2018. Annual reports of the Ministry ofAgriculture, Forestry and Fisheries. Cambodia.
Ou, W., Li, M., Tin, M.A. and Sinath, S. 2016. Current situation of cassava production, constraints andopportunities in Cambodia. Agriculture, Forestry and Fisheries, 5 (3), 64-70.
RGC (Royal Government of Cambodia). 2015. Cambodia industrial development policy 2015-2025. Cambodia.
RGC (Royal Government of Cambodia). 2020. National policy on cassava 2020-2025. Cambodia.
Smith, D., Newby, J., Cu Thi Le Thuy, Yadav, L., Malik, A.I. and Cramb, R. 2018. Smallholder farmer
experience with cassava related pests and diseases and their view on clean/ certified planting materials.
Discussion Paper Number 9, University of Queensland, Australia.
Sopheak, T. 2015. Economic analysis of cassava production in Cambodia. International Journal of Science andResearch, 6 (6), 2403-2406.
Sopheap, U., Patanothai, A. and Aye, T.M. 2011. Farmers’ perception on cassava cultivation in Cambodia.
Khon Kaen Agriculture Journal, 39, 279-294.
Sopheap, U., Patanothai, A. and Aye, T.M. 2012. Unveiling constrains to cassava production in Cambodia: An
analysis from farmers’ yield variations. International Journal of Plant Production, 6 (4), 409-428.
Teamhy, S., Penwadee, C. and Savitri, G. 2017. Potentialn of cassava production as eneergy feedstock in
Cambodia: Assessment of land suitability using GIS approach. Journal of Sustainable Energy andEnvironment, 8, 55-58.
Uke, A., Hoat, T.X., Quan, M.V., Liem, N.V., Ugaki, M. and Natsuaki, K.T. 2018. First report of Sri Lankan
cassava mosaic virus infecting cassava in Vietnam. Plant Dis., 102 (12).
Wang, H.L., Wang, X.W., Cui, X.Y. and Liu, S.S. 2015. First report of Sri Lankan cassava mosaic virus
infecting cassava in Cambodia. Plant Dis., 100 (5), 1029.

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Research article
erd

Contracting and Negotiation Attributes:
A Case of Sunflower Seed Crop in Central Tanzania
RUBASHA MATIKU MUJAMA*
Graduate School of Agriculture, Tokyo University of Agriculture, Japan
Email: matikurubasha85@gmail.com

TOMOHIRO UCHIYAMA
Faculty of International Agriculture and Food Studies,Tokyo University of Agriculture, Japan
Received 31 December 2020

Accepted 9 September 2021(*Corresponding Author)

Abstract In the most developing countries like Tanzania, poor farmers have limited accessto agricultural inputs. One of the proposed solutions is to link farmers with the private sector
through contract farming. In Tanzania, sunflower oil has been preferred as edible cooking oil
for many households since it has a low cholesterol level for human consumption. Moreover,sunflower-contract farming was adopted as part of the new agricultural policy in 2009-2010
cropping season, majoring in providing triangular benefits to the stakeholders, including
sunflower-farmers, private companies, and the Government of Tanzania. Despite thegovernment of Tanzania’s efforts to link the sunflower farmers with the private sector,
contract farming has been facing some challenges in coordination such as pricing, production
services and credit services. The purpose of this study is to investigate the impact of thecontract farming program among sunflower farmers. Specifically, the study aims to: (i)determine the socio-economic characteristics of the sample farmers; (ii) identify private firms
providing contract farming to the sunflower farmers; and (iii) evaluate the relationship of thenegotiation attributes in income growth among sunflower farmers. The field survey was
conducted in March 2020, targeting 40 contracted farmers and 40 non-contracted farmers in
the two regions of Central Tanzania. In relationship of the negotiation attributes the paper
points out the credit access and production services were significant with farmers’ income.
Besides, the results show that there was no statistically significant relationship between
advance pricing and income growth among sunflower farmers. This was because in contract
terms price is not set in advance.
Keywords contract farming, sunflower seed crop, Central Tanzania.

INTRODUCTION
Contract financing has been a promising linkage strategy between smallholders and agribusiness
firms with vested interests in sharing the risks associated with producing of a specific crop.
Consequently, the World Bank also recognizes contract financing as an avenue to create strategic
partnerships between private capitals and smallholders leading to the transfer of modern agricultural
technology, quality inputs, entrepreneurial development of smallholders and market growth (World
Bank, 2008).
Contract farming is not a new phenomenon in Tanzania. It dates back during the colonial era,
where contract farming arrangements were practiced in some of the major cash crops plantations ofsugarcane and tea. Contract arrangements in the Tanzania farming industry fall under the four models
as explained by Eaton and Shepherd (2001); centralized, multipartite, intermediary and the informal
models. For sunflower sector, contract farming among sunflower farmers in Tanzania has beendeveloped widely since 2010 in solving the problems faced by farm households such as poor accessof modern seeds, in-adequate use of farming techniques and provides a secure purchaser for theirproduction (SDC, 2018). Likewise, from the countryside the main motivation of introducingⒸ ISERD

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sunflower contract farming was to reduce the shortage and burden of edible cooking oil importationfrom foreign countries (URT, 2009).
Due to its low cholesterol level, sunflower oil is highly preferred as an edible and safe cooking
oil for many households in the country. The crop accounts for 40% of the total national cooking oil
requirements (URT, 2014). For the countryside, contract farming policy attempted to reduce theburden of importing edible cooking oil from foreign countries by offering opportunities of high yield
varieties together with aim of the income generation to farmers.
Despite the government’s new agricultural policy, sunflower contract farming has faced somechallenges in coordination such as pricing which leads to side-selling, production services such as
delay of paying farmers-produce and credit services which is not provided as agreed in advance.
Additionally, in contract terms, major negotiation attributes between the companies and contract
farmers include pricing, credit access and production services such transport and inputs access.
OBJECTIVE
The study aims to investigate the impact of contract farming program among sunflower farmers.
Specifically, the study aims to (i) determine the socio-economic characteristics of the sample farmers;(ii) identify private firms providing contract farming among the sunflower farmers; and (iii) evaluate
the relationship of the negotiation attributes in income growth among contract sunflower farmers.
The following research hypotheses were formulated and tested: H01: Capital has no significant
influence on income growth among sunflower farmers in Tanzania; H02: Advance pricing has no
significant influence on income growth among sunflower farmers in Tanzania; and H03: Contractor
credit services have no significant influence on income growth among sunflower farmers in Tanzania.
METHODOLOGY
The field study was conducted in Dodoma and Singida regions located in Central Tanzania in March
2020 (Fig. 1). These regions were selected because contract farming has been extended to sunflower
farmers since 2020. Based on the observation, it was found that there were two types of sunflower
seed producers: i) sunflower farmers with contract farming and ii) sunflower farmers without contract farming. Data collected comprised mainly data from the 2018/2019 cropping season,
therefore farmers had to recall on some aspects such as costs of production, yield of different crops
and inputs use.

Study
area

Fig. 1 Study area
Source: Available at https://www.google.com/united-republic-of-Tanzania-map-vectorⒸ ISERD

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Considering this observation, a total of 80 farmers from two types of category farmers wereselected from two regions: Dodoma and Singida regions. Among them, 40 farmers were selectedfrom each category of farmers. A two-stage sample design was used to collect the data. First, twovillages were purposefully selected because of the presence of sunflower contract farming. Then, thecontract farmers were randomly selected from the list of contracted farmers, and non-contract
farmers were randomly selected from the village households list (after removing the contract farmers).
The study adopted a semi-structured questionnaire as an instrument for data collection. Bothqualitative and quantitative methods of data collection were collected. Major information collected
includes socio-economic characteristics of the farmer-respondents such as age, farm size (ha),average cultivated area (ha), education of head of households, objectives of the contract farming
among sunflower farmers, production characteristics such as cost and sales of produce and current
problems and farmers suggestions on sunflower production.
This study employed data analysis techniques, and descriptive statistics, correlation analysis
between variables was used to measure how well the variables are related. Descriptive statistics suchas frequencies means, and cross-tabulation of some critical values were used to compare basic
characteristics of farmers who participated in contract farming and farmers who did not participate.
RESULTS AND DISCUSSION
1) Socio-Economic Characteristics of the Sample Farmers
The the field study showed that the average age for both contract farmers and non-contract farmers
was 48 years (Fig. 2). In terms of gender distribution, the sunflower is a men’s crop where men
constitute (95%) of the contract farmers and (74%) of the non-contract farmers respectively (Fig. 3).
The very low proportion of women contract farmers may indicate contractual arrangements and toolsthat still discriminate against women participation and access. In most Nyanturu societies in Singida
region and Rangi societies in Dodoma region, women still require the approval of men whenborrowing money, which tends to limit women’s participation and access to contract farming.
Considering the education background, the study shows that (82%) of the contract farmers had
attained at least secondary education compared to (67%) of the non-contract farmers (Fig. 4). This
clearly shows that most of the contract farmers had attained a good level of education to enable themto have a better understanding of how contractual arrangements work.

Fig. 2 Age distribution of sampled farmers
Source: Field survey, 2020

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Fig. 3 Gender distribution of sampled farmers
Source: Field survey, 2020

Fig. 4 Education level of sampled farmers
Source: Field survey, 2020

2) Private Firms Providing Contract Farming among Sunflower Farmers
Based on the observations, the major actors in sunflower contract farming were farmers; thecompany; and the Government of Tanzania who closely oversee the progress of the contract farming
program. Initially, the contract farming among sunflower farmers was introduced by eight (8) private
firms. However, major private firms still having contract farming among sunflower farmers include:
Three Sisters Company Limited in Dodoma region and Ikungi Sunflower Edible Cooking Oil
Company in Singida region (Table 1). Additionally, both Three sisters in Dodoma and Ikungi
Sunflower Edible Cooking Oil provide a long-term contract for a period of eight (8) years. However,some farmers did not join the contract in the first instance as they wanted reassurance that thecompany would fulfil its obligations in terms of providing improved seeds and purchasing all
produce before contracting. Farmers subsequently joined the program. Other contract companies did
not continue providing contract farming because of some challenges such as side selling among thecontract farmers, financial constraint, and their contract were short- term such as one-year, two-years,
and three-years of contract (Table 1).

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Table 1 Private firms providing contract farming among sunflower farmers in Tanzania
Private firm

Still having
contract

Region, the company
operates

Number ofvillages

Years of doing
contract

Uncle Millo
Ringo consolidated
Furaha Dodoma
Three Sisters
Ikungi Edible Cooking Oil Ltd
Nyemo Investment
Ring Investment
Kibaigwa Oil Suppliers

No
No
No
Yes
Yes
No
No
No

DodomaDodomaDodomaDodomaSingidaSingidaDodomaDodoma

20
25
11
5
3
28
10
70

3(2010-2013)
2(2010-2012)
2(2010-2012)
8(2011-to date)8(2012-to date)3(2010-2013)
2(2011-2013)
1(2010-2011)

Source: Field survey, 2020

3) Relationship of the Negotiation Attributes in Income among Contract Sunflowers Farmers
To understand the gross income of two category farmers, the economic return analysis was employed.
Gross income was calculated as a gross revenue minus total production cost excluding family laborcost. The study shows that, contract farmers receive higher gross income (1228.9 TZS/ha) after
joining the contract farming compared to the non-contract farming (602.1 TZS/ha) (Table 2). For thegood aspect, this result imply that contract farming has a positive impact on household income.
Table 2 Income comparison of non-contract sunflower farmers andcontract sunflower farmers(Unit of cost: `000TZS/ha)

Item

Non-contract

Contract

farmers

farmers

Difference(b)-(a)(a)(b)

Head of household(n=40)(n=40)

Yield (tons/ha)

1.20

2.41

1.21

Seeds cost

10.6

12.2

1.6

Chemical fertilizer cost

22.7

37.9

15.2

Pesticide cost

1.20

10.8

9.60

Transport cost

40.00

55.5

55.5

Hired labor cost

23.4

27.9

4.5

Total variable cost

57.9

144.8

86.9

Total production cost

98.3

196.9

98.6

Gross Revenues

660.0

1373.7713.7

Gross Income

602.1

1228.9626.8

Gross Profit

561.5

1176.8

615.3

Price

550

570

Additionally, the study adopted the correlation analysis to examine the negotiation attributes inincome growth among the sunflower contract farmers. The correlation between variables was used
to measure how well the variables are related. Table 3 presents the results of the correlation
coefficient analysis, which shows a statistically insignificant weak positive relationship between
capital and income growth among sunflower farmers (r = 0.037, p >0.05). Surprisingly, the results
show that there was no statistically significant relationship between pricing and income among
sunflower farmers (r = 0.23, p >0.05). This was because in contract terms price is not set in advance.
However, contractor credit (r= 0.71) and production services (r= 0.78) among sunflower farmers
show static significant relationship with income growth among sunflower farmers (Table 3)Ⓒ ISERD

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Table 3 Relationship of the negotiation attributes in income growth among contract
sunflower farmers
CapitalPricing

Contractor
creditProduction
services

IncomeCapitalPearson1
correlation
Sig (2 tailed)N
40
Pricing
Pearson
0.32
1
correlation
Sig (2 tailed)
.818
N
40
40
Contractor
Pearson.062.255**
1creditcorrelation
Sig (2 tailed)
.661
.000
N
40
40
40
Production
Pearson.022.615**.345
servicescorrelation
Sig (2 tailed)
.876
.000
.012
N
40
40
40
IncomePearson.037.023.741**.779**
1
correlation
Sig (2 tailed)
.791
.000
.000
.000
N
40
40
40
40
40
Note: **Correlation is significant at the 0.05 level (2-tailed-test); N is the total number of the contract sunflower
farmers; Production services means transport provision during harvesting and inputs provision such as seeds,
pesticides and fertilizers. Source: Field survey, 2020.

CONCLUSION
The study aimed to investigate the impact of contract farming program among sunflower farmers. In
the sunflower sector, only two major private firms still provide contract farming among the sunflower
farmers. Additionally, in relationship of the negotiation attributes the paper points out the credit
access and production services were significant with farmers’ income. Besides, the results show that
there was no statistically significant relationship between advance pricing and income growth among
sunflower farmers. This was because in contract terms price is not set in advance.
In relation to the findings and conclusion, the following were recommended to alleviate theexisting challenges. First, fixed price should set in advance; this can work as an incentive if thesunflower-contract producers feel their work is rewarded. Secondly, there is a definite need for theGovernment of Tanzania to provide proper monitoring to ensure both contract parties adhere to theterms of contract. Finally, non-contract farmers need more education and training for more contract
participation.
ACKNOWLEDGEMENTS
We would like to express our gratitude to Tokyo Nodai Foundation and Tokyo Tamagawa RotaryFoundation for financially supporting this study.
REFERENCES
Abadi, G. and Pannell, D.J. 1999. A conceptual framework of adoption of an agricultural innovation.
Agricultural Economics, 21, 145-154.
Abunga, M., Emelia, A., Samweli, G. and Dadzie, K. 2012. Adoption of modern agricultural production
technologies by farm households in Ghana, What Factors Influence Their Decision? Journal of Biology
Agriculture and Healthcare, 2 (3), 1-13, Retrieved from www.iiste.org/Journals/index.php/JBAH/article/
viewFile/1522/1454
Ari Ilonga. 2008. Oilseed research sub-program. Ilonga Agricultural Research Institute, Kilosa, Tanzania.
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CIMMYT. 1993. The adoption of agricultural technologies: A guide for survey design. Londres, Mexico.
Damiani, M.G. and George, V. 2010. Sunflower production in the Central Corridor of Tanzania.
Eaton, C. and Shepherd, A. 2001. Contract financing: Partnerships for growth. Food and Agriculture
Organization of the United Nations.
Feder, G., Just, R.E. and Zilberman. 1985. Adoption of agricultural innovation in developing countries: A
survey. Economic Development and Cultural Change, 33 (2), 225-298.
Myers, R.L. 2002. Sunflower: A native oilseed with growing markets. Retrieved from www.jefferson
institute.org
Rutatora, D. and Mattee, A. 2001. Major agricultural extension providers in Tanzania. African Study
Monographs, 4, 155-170.
SDC. 2018. The three-year development plan 2014-2017 for Singida District. Singida District Council,
Tanzania.
URT. 2009. Agriculture sector review and public expenditure review. United Republic of Tanzania.
URT. 2014. Agriculture sector review and public expenditure review. United Republic of Tanzania.
WB. 2008. Agriculture for development. World Bank Report, Washington.

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Research article
erd

Possibility of Value Addition on Traditional Rice Liquor in
Cambodia
MITSURU HAMANO
Faculty of Agriculture, Shinshuu University, Nagano, Japan

TAKASHI KURODA
Graduate School of Bioagricultural Sciences (graduated), Nagoya University, Aichi, JapanCHIM CHAY
Faculty of Agro-Industry, Royal University of Agriculture, Phnom Penh, Cambodia

BORATANA UNG
Cambodia and Japan High-quality Agricultural Products, Phnom Penh, Cambodia

KASUMI ITO*
International Center for Research and Education in Agriculture, Nagoya University, Japan
Email: kasumito@agr.nagoya-u.ac.jp
Received 30 December 2020

Accepted 21 September 2021(*Corresponding Author)

Abstract Rice liquor is one of the traditional alcoholic beverages produced by small-scale
farmers in rural areas. However, rice liquor production faced deficits and low profitability
due to low sales price and productivity, frequent production failure, and low quality. It was
hypothesized that improving the quality could increase the product value and the profitabilityof rice liquor production. The key modifications of production techniques to improve rice
liquor quality include sanitary control of the working place, equipment, and raw material, andproduction process and quality management. However, it remains unclear if improving the
product quality may result in value addition on traditional rice liquor in Cambodian markets.
This study aimed to assess the possibility of value addition on the traditional rice liquor in
Cambodian markets. First, consumers had structured interviews with questionnaires to
identify consumption trends and preferences on rice liquor and other alcoholic beverages.
Second, liquor produced with the modified techniques underwent consumer tests on its
quality and sales price in 2009. Finally, quality liquor with the required registration forcommercialization was trialed to identify the possibility of adding value to the products in
Phnom Penh markets from 2010 to 2011. The survey results found that traditional rice liquor
was consumed more in rural areas than the urban areas. More males consumed rice liquor
than females, who mostly consumed medicinal and fruit liquor. A consumer test was
conducted with tasting, observing bottled products, and labeling after a quality check. Both
Cambodians and foreigners' evaluated liquor produced with modified techniques andindicated the possibility of putting a higher price as commercialized products. After
registering for commercialization, the quality rice liquor was trialed for marketing and sales.
These activities attracted several supermarkets, restaurants, and souvenir shops, and a sales
contract was agreed for more than ten times higher than the sales price at the local markets.
These results showed that the traditional rice liquor with value addition might gain market
shares by ensuring product quality and safety.
Keywords value addition, agro processing, rural development, marketing, rice liquor

INTRODUCTION
Value addition to agricultural products is expected to increase farmers' incomes and reduce poverty
in rural areas (Royal Government of Cambodia 2006; Royal Government of Cambodia, 2013). Rice
liquor is one of the traditional alcoholic beverages produced by small-scale farmers in rural areas. ItⒸ ISERD

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contributed to income generation combined with pig farming, which became profitable by using rice
liquor residue that reduces feeding costs. However, rice liquor production faced deficits and low
profitability (Yagura et al., 2010). Main factors of low profitability include low sales price andproductivity and frequent production failures, and many producers recognized the issues of low
quality (Hamano et al., 2020). It was hypothesized that improving quality could increase theprofitability of rice liquor production (Hamano et al., 2020).
The general production methods of traditional alcoholic beverages from rice in Vietnam andLaos have been clarified (Kozaki et al., 2002; Kozaki et al., 2005). Kozaki (2007) also revealed the
production methods of traditional brewed and distilled liquor from rice in Cambodia. Yamamoto andMatsumoto (2011) identified the production methods of starter culture and its raw material for rice
liquor and wine in Cambodia. Hamano et al. (2014) identified the key modifications of production
techniques to improve rice liquor quality, such as sanitary control of working place, equipment, andraw material, and production process and quality management.
However, it remains unclear if improving product quality may result in value addition on
traditional rice liquor in Cambodian markets.
OBJECTIVE
This study aimed to assess the possibility of value addition on the traditional rice liquor in Cambodian
markets.
METHODOLOGYThis study employed a series of action research (Greenwood and Levin, 1998; Popplewell andHayman, 2012) to examine the possibility of value addition on the traditional rice liquor throughinterview surveys on consumption behavior, consumer tests on quality, and marketing and sales trials
in domestic markets of Cambodia.
First, structured interviews were conducted with questionnaires to the consumers to identify the
consumption trends and preferences on the rice liquor and other alcoholic beverages during the Water
Festival and One Province One Product Exhibition (OPOP) in 2008 at the capital city, Phnom Penh
(Fig. 1). Second, rice liquor produced with the modified techniques by rice liquor farmers in Takeo
Province was provided for consumer tests on its quality and sales price during the OPOP in 2009 at
Phnom Penh. In order to set up the trial sales prices, the sales conditions of the local rice liquor andother commercialized alcoholic beverages were clarified by conducting market surveys in Takeo
province and Phnom Penh in advance. Third, the trial marketing and sales of the quality liquor withthe required registration for commercialization were conducted to identify the possibility of adding
value on the products at Phnom Penh markets from mainly 2010 to 2011. Finally, the possibility ofthe value addition on rice liquor was discussed with the necessary conditions.

Fig. 1 Target area
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RESULTS AND DISCUSSION
Trends and preference of consumers: The interview survey was performed with questionnaire on
alcoholic beverage consumption to the Water Festival visitors in Phnom Penh, the capital city of
Cambodia. The interviews were conducted to 111 males and 121 females, and 230 valid answers
were obtained. Most interviewees at 94% came from provinces outside Phnom Penh.
Table 1 shows the alcoholic beverage consumption behavior of the interviewees. The results
indicated that beer is consumed by 73.5% of the interviewees, with rice liquor at 59.6% and herb
liquor at 54.8%. More people drink beer than rice liquor and herb rice liquor processed from the rice
liquor, followed by palm wine at 46.1%, and fruit rice liquor at 33.1%, which are both traditionallyproduced and consumed in Cambodia. On the other hand, the traditional rice liquor, herb rice liquor,
and palm wine were more frequently drunk on a daily (5-7 times/week) or weekly (1-4 times/week)basis than beer. Rice liquor, herb liquor, and palm wine were consumed by 27.4%, 21.4%, and 14.8%,
respectively, more than once per week (both 5-7 times/day and 1-4 times/week), while beer was
consumed by 11.3%. On the other hand, whiskey and wine were consumed a few occasions per year
(1-11 times/year).
Table 1 Consumption of alcoholic beverage by the interviewees

Note: Most interviewee (94%) were from provinces out of Phnom Penh.
*Palm wine and rice wine were brewed alcoholic beverages without distillation like rice liquor.

Table 2 shows the interview results during the One Province and One Product Exhibition in2008 about the rice liquor consumption comparing urban and rural residences. Interviews wereconducted with 393 visitors and obtained 337 valid answers (by 303 male and 34 female) consistedof 202 from Phnom Penh and 135 from other provinces out of Phnom Penh.
The results indicated that both urban and rural people consumed rice liquor since more than
59.9% by Phnom Penh visitors and 66.7% by consumers from other provinces. The weekly (1-2times/week) or daily drinkers (Everyday) shared 13.9% at Phnom Penh and 17.0% at other provinces.
Although rural people tended to consume rice liquor more frequently, people in Phnom Penh also
consume traditional products.
Table 2 Consumption behavior of rice liquor in urban and rural areas
Phnom Penh

Other provinces

Answer%Answer%AnswerTotal%

No drink
Drink

81
121

40.1
59.9

45
90

33.3
66.7

126
211

37.4
62.6

1-5times/year
1-3times/month
1-2times/week
Everyday

68
25
20
8

33.6
12.4
9.9
4.0

48
19
13
10

35.6
14.1
9.6
7.4

116
44
33
18

34.4
13.1
9.8
5.3

Total

202

100.0

135

100.0

337

100.0

The interviewees were asked about their impression of the rice liquor quality (Table 3). Amongthe answers, 116 (34.4%) recognized rice liquor as low quality at a nearly same ratio in Phnom Penh
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and from provinces, while 76 (22.6%) evaluated it as high quality. Among the 116 interviewees who
answered “low quality”, the reasons were described and appearances of keywords were counted. As
a result, “added industrial alcohol” or “other kinds of harmful chemical” was 47 (41.6%), followedby “bad for health” at 23 (20.4%), “unstable quality” at 14 (12.4%), and “no quality control” at 13(11.5%).
Table 3 Impression on traditional rice liquor
quality in urban and rural areas

High quality
Low quality
No idea
No-answer
Total

Phnom Penh
Number
%
41
20.3
70
34.7
79
39.1
12
5.9
202
100.0

Other Provinces
Number
%
35
25.9
46
34.1
43
31.9
11
8.1
135
100.0

Table 4 Factors of low quality
Add industrial
alcohol/chemical
Bad for healthNo standard/ Various
quality
No quality control
Add water
Others
No idea
Total

Frequency

%

47

41.6

23

20.4

14

12.4

13
3
11
2
113

11.5
2.7
9.7
1.8
100.0

*Frequency of key words in the answers to the openended question. 108 out of 116 respondents answeredand 113 key words were counted. No answer by 8
respondents.

Current sales price and its quality: Hamano et al. (2013) identified the modified production
techniques for quality improvements by improving sanitary conditions and quality control throughtrial productions with a selected farmer in a rural area of Takeo province. Consumers recognized theimproved quality and high possibility of commercialization in the trial rice liquor during consumers'
tasting tests, comparing with the farmer's liquor in the One Province and One Product Exhibition in2008. However, people were suspicious about the quality and safety control of the local rice liquor
as shown in Table 3. It indicated that the consumers refused pay high value without the guarantee ofthe products quality and safety under a strict production control.
During the OPOP exhibition in 2009, the quality liquor was provided to the second consumer
test with tasting and observation of the rice liquor products, which have been developed to ensure
the necessary conditions for the commercialization. The rice liquor was produced under strict quality
management, such as ensuring the sanitary condition of raw material, equipment, and production
place, checking and recording the production process, measuring the alcohol degree, and conducting
the sensory tests for checking taste, fragrance, color, and smell. The rice liquor was packaged withsealed glass bottles. Front and back labels were attached to the bottle with the product logo mark andnamed as “Sraa Takeo,” which means rice liquor from Takeo province in Khmer language. The label
included the information on producers, and product information such as alcohol percentage, rawmaterial, and production process with strict sanitary and quality control (Fig. 2).

Checking fermentation
Recording production

Sensually test and alcohol
degree check

Final sensually test andalcohol degree check

Bottling and labelingFig. 2 Quality check during the rice liquor productions
Fig. 3 shows comparison results of retail prices of general rice liquor at local shops between
Phnom Penh and Takeo province. The price setting at Phnom Penh has three price ranges of R2,000– R3,000/L (USD0.5–0.75), while the price at Takeo province has only one price range at R2,000/L.
It seemed that the Phnom Penh market could be more sensitive in differentiating the prices andⒸ ISERD

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quality. However, the prices and the alcoholic degree did not have a significant correlation. It meansthat the traditional rice liquor was not clearly evaluated its quality with price setting.

Fig. 3 Rice liquor price (Riel/L) and alcohol contents
The prices of the trial products for commercialization were also based on the production costand market survey results on alcoholic beverages in Phnom Penh. Table 5 shows the retail prices at
10 shops, including supermarkets and local shops. Local liquor was sold at USD0.5–1.0/L in local
shops and supermarkets. On the other hand, imported whiskey, vodka, and wine were sold at USD5/L
in the lowest price, and USD10–20/L in general. The alcohol contents varied from 20%–40% in thecase of distilled liquor.
Consumer tests on its quality and sales price: For the consumer test, two trial products withdifferent alcohol degree at 25% with a green label and 40% (alc/vol) with a black label, and one local
liquor from the market in Phnom Penh were provided to the OPOP exhibition visitors in 2009 at
Phnom Penh to compare the liquor quality and examine the marketability of the packaged products(Fig. 4). The total number of interviewees was 349, consisting of 332 Cambodians (314 males and
18 females) and 17 foreigners (14 males and 3 females). Among the Cambodians, 86.5% lived in
Phnom Penh, and 13.2% were from other provinces. The eight foreigners included were Japanese,
Americans, and Europeans.
Table 5 Sales of alcoholic beverages in different retailers

Note: Rice liquor (local shops) were distributed with plastic container from local farmers and sold after putting in reused PET bottle without showing any information such as alcoholic contents and raw material.

The results of interviews after the tasting and observations of the products most interviewee
preferred the trial products sharing Sraa Takeo 25% (alc/vol) and 40% (alc/vol) at 50.7% and 40.7%
of total answers respectively (Table 6). The fragrances of two Sraa Takeo products were highly
evaluated that more than 66% of interviewees recognized them as the more preferred aromas, while
only 23.8% preferred the aroma of the local rice liquor (Table 7). The color of Sraa Takeo products,
which were mostly transparent, were preferable for the consumers, while nearly 70% of theⒸ ISERD

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interviewees described the cloudy local liquor as unpreferable, as it usually appeared in general local
rice liquor in Cambodia (Table 8). The prices set per 500-mL bottle, which were USD5 for Sraa
Takeo 25% and USD8 for Sraa Takeo 40%, were recognized as the appropriate price for commercial
products by respectively 56.7% and 53.2% of all interviewees, even though the local rice liquor was
sold at USD0.75/L (Table 9).
Green label:
25% alc/volat USD5.00
Black label:
40% alc/volat USD8.00

Sample of quality rice liquor
products

Samples for tasting

Interviews after tasting andobservation of the products

Fig. 4 Consumer tests during One Province One Product exhibition in 2009
Table 6 Preference of rice liquor
Sraa Takeo 25%
Sraa Takeo 40%
Local rice liquor
Total

Table 7 Evaluation on fragrance of rice liquor

Answers (%)
177 (50.7)
142 (40.7)
30 (8.6)
349 (100.0)

Aromatic
Notaromatic
No idea
Total

Table 8 Evaluation on color of rice liquor

106 (30.4)
242 (69.3)

Sraa
Takeo
25% (%)
321 (92.0)
27 (7.7)

1 (0.3)1 (0.3)1 (0.3)349(100.0)349(100.0)349 (100.0)

Local rice
liquor (%)
Good
Bad
No
idea
Total

Local rice
liquor (%)
83 (23.8)

Sraa Takeo
25% (%)
232 (66.5)

Sraa Takeo
40% (%)
236 (67.6)

266 (76.2)

116 (33.2)

112 (32.1)

0 (0.0)349 (100.0)

1 (0.3)349 (100.0)

1 (0.3)349 (100.0)

Table 9 Evaluation on price setting of trial
rice liquor

Sraa Takeo
40% (%)
314 (90.0)
34 (9.7)

Reasonable
Appropriate
High

Sraa Takeo
25% (%)
2 (0.6)198 (56.7)
149 (42.7)

Sraa Takeo
40% (%)
3 (0.9)186 (53.3)
160 (45.9)

Total

349 (100.0)

349 (100.0)

Questionnaires about the place of drinking rice liquor were answered to be mainly consumed at
the house (Fig. 5), while the other alcoholic beverages were consumed at house and restaurant(Fig. 6). On the other hand, rice liquor was purchased directly from producers at 36.0% and local
markets at 30% (Fig. 7). Other alcoholic beverages were bought from local markets, street stoles,
and at supermarkets (Fig. 8). These results indicated that the traditional rice liquor has not been
introduced to the supermarkets and restaurants, where popularly high valued alcoholic beverages
were served and sold. In other words, high-quality rice liquor could have room to enter those markets.
Trial marketing and sales of the quality rice liquor: Based on the consumers' concerns for
unsafety of the rice liquor especially by the contamination of the industrial alcohol and otherchemical material into the products, it was assumed that the safety control has remained as afundamental issue toward value addition on rice liquor product. Thus, the trial rice liquor was
packaged by glass bottle and sealed cap after completing the commercial registration under the
Ministry of Commerce and manufacturing registration under the Ministry of Industry, Mine, andEnergy with quality test which certify the alcohol degree, appropriate acidity and no contaminationof methyl alcohol.
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Fig. 5 Drinking place of rice liquor

Fig. 6 Drinking place of other alcoholic beverageFig. 7 Buying place of rice liquor

Fig. 8 Buying place of other alcoholic beverage

After the required registrations for commercialization in terms of business (company)
registration, tax, small-medium manufacturing and product test, and trademarks, the Sraa Takeo 25%
and 40% were trialed for marketing and sales from 2010 September. The marketing and promotion
activities targeted around 80 clients including 4 supermarkets and 7 minimarts, 10 souvenir shops,
50 restaurants, 7 hotels in Phnom Penh and Siem Reap (Fig. 9).
These activities resulted to get 35 clients who bought Sraa Takeo 25% and 40% at least one
time and sell at the suggested consumer price consumer price at USD5 for Sraa Takeo 25% and
USD8 for 40% with 500 ml in minimum which were more than 10–16 times higher price than thelocal rice liquor price at the local markets during the 1st year. Then two supermarkets, threerestaurants/bar, six souvenir shops repeated to purchase the products within the first-year sales.

Supermarkets

Restaurants

Bars

Souvenir shops

Fig. 9 Marketing and sales of Sraa Takeo 25% and 40%
Figure 10 shows the first-year results of the sales every 3 months. The average monthly sales
were about 100 bottles in the first 6 months and increased to 200 bottles in the second 6 months. The
main clients were several souvenir and food shops and restaurant in the first 6 months and 2
supermarkets in the second 6 months in Phnom Penh, and a part of sales were accepted by souvenir
shops in Siem Reap, a famous tourism area.
Hamano et al. (2013) has clarified that the rice liquor production techniques can be modified
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cost material and equipment and difficult techniques from other countries. Keeping the sanitarycondition and quality control were the fundamental technical improvements.

Sales amount in 2011
Sraa Takeo 25%

Sraa Takeo 40%

700
600

500
400
300

200
100
0
Oct~Dec

2010

Jan~MarApr~Jun

Jul~Sep

Oct~Dec

2011

Fig. 10 Sales (bottle numbers) of Sraa Takeo
Local markets in general did not have significant differences in the values on the traditional rice
liquor even though the alcoholic percentage was different. Thus, the commercialized markets suchas supermarkets, restaurants and bar, or souvenir shop that sold the high value alcoholic beverages
in the urban areas could be considered as possible markets for value addition.
In order to enter those markets, the rice liquor with improved quality should be developed ascommercialized products with commercial registration including not only business andmanufacturing registration but also obtaining the certification on product safety and quality from theauthorized laboratories. In addition, the products packaging with bottling, sealing, and labeling withnecessary information to indicate the product name, product quality, raw material, and producers.
One year marketing and sales activities to the high value markets in urban areas revealed thatsupermarkets and souvenir shops, and also restaurants and bars have accepted to sell the high-quality
rice liquor at USD5-8 which were 6-10 times higher than the local products. Some of them becomefrequent buyers and continuously purchased. These indicated that there were needs of the traditional
rice liquor by both domestic consumers and international customers. In the following year, thesouvenir shops in the international airports at Phnom Penh and Siem Reap accepted the Sraa Takeo.
The one of the largest chain supermarkets in Cambodia also continuously purchased the Sraa Takeoand extended the sold stores in their distribution system. In December 2020, at the time of writing
this paper, the products have been continuously sold in these retail markets.
These results indicated the high possibility of value addition on the traditional rice liquor in thedomestic markets of Cambodia through the quality improvement and the safety control. However,
the efforts of the marketing and promotion activities or further product development should benecessary for the further market extension and sustainable commercialization.
CONCLUSION
This study was conducted by using action research method to examine the possibility of value
addition through conducting the interview surveys on consumption behavior, market survey on theprice setting of local rice liquor, and impression on quality of the trial products for thecommercialization with tasting and observation. Finally, the sales of the commercialized products
were trialed in the domestic markets. These results indicated the possibility of value addition on the
traditional rice liquor under ensuring not only the high and stable quality but also the product safety
under the appropriate quality control and testing.

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ACKNOWLEDGMENTS
We thank Professor Tetsuo Matsumoto for his supervision and instruction of this study, and Mr.
Mitsuhide Fujimoto and Mr. Iwao Fukaya for their technical supports during the quality
improvement and commercialization of the rice liquor; This study was supported by Grants-in Aid
for Scientific Research (No. 20405045) and Cooperation Bases System (34-G-G0003) from the
Ministry of Education, Culture, Sports, Science and Technology of Japan.
REFERENCES
Greenwood, D.J. and Levin, M. 1998. Introduction to action research: Social research for social change. SAGE
Publication (California), 274.
Hamano, M., Matsumoto, T. and Ito, K. 2013. Technical modifications for the quality improvement of rice
liquor (Sraa Sar) in Cambodia. Tropical and Agriculture Development, 57, 126-137.
Hamano, M., Matsumoto, T. and Ito, K. 2020. Factors causing deficits in traditional rice liquor production inrural areas of Cambodia. International Journal of Environmental and Rural Development, 11, 105-113.
Kozaki, M. 2007. Alcohol beverages and fermented foods of Ratanak Kiri, in Northeast Cambodia, J. Brewing
Soc. Japan, 102, 31-38. (in Japanese)
Kozaki, M., Iino, H., Thuoc, T.L., Ho, P.T. and Seki, T. 2002. Rice wine of south highland of Annamese
Cordillera (Vietnam) -Ruou can and ruou nep-. J. Brewing Soc. Japan, 97, 327-337. (in Japanese)
Kozaki, M., Naitoh, A. and Takayama, T. 2005. Rice wine of northern Laos (1): Fermented mash of rice wineand distilled rice wine of Thai people. J. Brewing Soc. Japan, 100, 796-806. (in Japanese)
Popplewell, R. and Hayman, R. 2012. Where, how and why are action research approaches used byinternational development non-governmental organizations? International NGO Training and ResearchCenter, Briefing Paper, 32.
Royal Government of Cambodia. 2006. National strategic development plan 2006-2010. Royal Governmentof Cambodia (Phnom Penh), 211.
Royal Government of Cambodia. 2013. National strategic development plan 2014-2018. Royal Governmentof Cambodia, Phnom Penh.
Yagura, K., Nishimura, Y., Keo, S. and Matsumoto, T. 2010. Roles and obstacles of agro-processing industries
in rural Cambodia. J. Agr. Develop. Studies, 20, 1-8. (in Japanese with English summary)
Yamamoto, S. and Matsumoto, T. 2011. Rice fermentation starters in Cambodia: Cultural importance andtraditional methods of production. Southeast Asian Studies, 49, 192-213.

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Research article
erd

Farmers` Perception on Contract Farming:
A Case of Sunflower Seed Crop in Central Tanzania
RUBASHA MATIKU MUJAMA*
Graduate school of Agriculture, Tokyo University of Agriculture, Japan
Email: mujamarubasha85@gmail.com

TOMOHIRO UCHIYAMA
Faculty of International Agriculture and Food Studies,Tokyo University of Agriculture, Japan
Received 23 January 2020

Accepted 24 September 2021(*Corresponding Author)

Abstract In most developing countries like Tanzania, poor farmers have limited access toagricultural inputs. In case of sunflower seed, one of the proposed solutions is through use ofcontract farming among the farmers. In the country, sunflower oil has been preferred as ediblecooking oil for many households since it is much safer for human consumption. Despite thegovernment’s new agricultural policy, contract farming has been facing some challenges incoordination such as pricing, trust, arrangement for the delivery of the inputs, procedures forpaying farmers, poor credit (cash) services as agreed of the contract. The study aims toinvestigate the impact of contract farming program among sunflower farmers. Specifically,
the study aims to (i) determine households’ background characteristics; (ii) examine contract
arrangement of sunflower seeds in Tanzania; (iii) discuss the farmers’ perception in termsof trust, and personal relations play for their coordination. The field study was conducted inAugust and September 2019, selecting 80 farmers in two regions in Central Tanzania. Amongthem 40 farmers were sunflower producers with contract farming with Three Sisters
Company Ltd and Ikungi Sunflower Edible Cooking Oil Company for eight (8) years; 40
farmers were sunflower producers without contract farming. Based on the field study,
contract terms and conditions, hereafter called contract design attributes such as mode ofpayment and price setting of farmers’ crop produce can affect farmers’ decisions toparticipate in contract farming, varyingly affecting their expected level of utility fromparticipation. On the other hand, in contract farming, farmers produce quality seeds withhigh cooking oil content. Surprisingly, in contract terms, prices are not set in advance,
contract farmers sell their produce with similar price to the local sunflower seed. Finally,lack of education was the factor for non-contract farmers to participate in contract
farming.
Keywords contract farming, sunflower seed crop, Central Tanzania

INTRODUCTION
Contract Farming (CF) among sunflower farmers in Tanzania has been developed widely since 2010
as an alternative approach to solving the problems faced by farm households and provides a securepurchaser for their production. At the same time, households receive the necessary inputs for theirfarm and advice on necessary farming techniques, while the buyers benefit from assured production
from the contract farming (SDC, 2018). Due to its low level of cholesterol, sunflower oil is highly
preferred as edible and safe cooking oil for many households in the country. The crop accounts 40%of the total national cooking oil requirements (URT, 2014). For the country-side, contract farming
policy attempted to reduce the burden of importing edible cooking oil from foreign countries byoffering opportunities of high yield varieties together with aim of income generation to farmers.
Despite the government’s new agricultural policy, contract farming has been facing some challenges
in coordination such as pricing, trust, arrangement for the delivery of the inputs and procedures forpaying farmers.
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OBJECTIVE
The study aims to investigate the impact of contract farming program among sunflower farmers.
Specifically, the study aims to (i) determine households’ background characteristics; (ii) examine
contract arrangement of sunflower seeds in Tanzania; (iii) discuss the farmers’ perception in termsof trust, and personal relations play for their coordination.
METHODOLOGY
The field study was conducted in Dodoma and Singida regions located in Central Tanzania in Augustand September 2019. Region and district were sampled purposively due to the potentiality inproduction of sunflower seed at the central corridor. In addition, contract farming has been promoted
to sunflower farmers since 2019. These regions are located in semi-arid area characterized byinadequate rainfall. Recently, there had been a tremendous shift of the population in these regions
towards farming sunflower seed crop. The crop is drought tolerant and survives harsh conditions.
The study adopted a semi-structured questionnaire as an instrument for data collection. Bothqualitative and quantitative methods of data collection were applied. Secondary data were obtained
from the two companies providing sunflower contract farming in Central Tanzania, sunflower
farmers, ministry of agriculture and rural development, published reports, books and journals.
Educational status, the level of awareness and willingness of the respondents to participate in contract
farming was collected.
Considering the observation, a sample of 80 farmers were selected from Dodoma and Singida
regions (Fig. 1). Among them, 40 farmers were sunflower producers with contract farming withThree Sisters Company Ltd and Ikungi Sunflower Edible Cooking Oil Company for eight (8) years;
40 farmers were sunflower producers without contract farming. A two-stage sample design was used
to collect the data. First, two villages were purposefully selected because of the presence of sunflower
contract farming. Then, the contract farmers were randomly selected from the list of contracted
farmers, and non-contract farmers were randomly selected from the village households list after
removing the contract farmers.

CentralTanzania

Fig. 1 Map of study area
Source: https://www.google.com/united-republic-of-Tanzania-map-vectorⒸ ISERD

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RESULTS AND DISCUSSION
This study employed data analysis techniques namely descriptive statistics and parametricestimations. Descriptive statistics such as frequencies means, and cross tabulation of some criticalvalues were used to compare basic characteristics of farmers who participated in contract farming
and farmers who did not participate.
1) Households’ Background Characteristics
From the field study it was found that sunflower farmers with contract farming were older (42.3
years) than sunflower farmers with non-contract farming (37.1 years). This implies that the elder
farmers participate in contract farming compared to younger farmers. Moreover, with respect to thefarm size, sunflower producers without contract farming were relatively small (0.82 ha) compared tosunflower farmers with contract farming (2.41 ha) as shown in Table 1.
Considering the education background, contract farmers have reached high school level andcollege level. But, majority of heads of household producing sunflower seed without contract farming
have reached to primary level only (Table 1).
Table 1 Households’ background characteristics
Contract farmers(n=40)
Mean
SD
Characteristics
Age of heads of household (years)
Average cultivated area (ha)Gender of farmers
Male
FemaleFarmers' education
Primary level
Secondary level
High school level
College level
University level

Non-contract farmers(n=40)
Mean
SD

42.30
2.41
Number offarmers

7.06
1.20
Percentage
of farmers

37.10
0.82
Number offarmers6.82
0.40
Percentage
of farmers

32
8

80.0
20.0

12
28

30
70

26
4
1
9
0

65.0
10.0
2.5
22.5
0.0

40
0
0
0
0

100
0
0
0
0

Source: Authors’ computation based on the data collected from field survey, 2019.
Note: (1) SD refers standard deviation (2) Primary level is seven years of schooling (3) Secondary level is four yearsof schooling (4) High school level is two years of schooling (5) College level is two years of schooling (6)University level is three to four years of schooling.

2) Contract Arrangement of Sunflower Seeds in Tanzania
The use of contract farming in the production of sunflower in Central Tanzania began in the 2010/11
crop season. Major actors in sunflower contract farming are the farmers, the company and thegovernment of Tanzania. The contract states the obligation of the company, farmers, and otherfeatures. In the contract, the company obligate itself to deliver improved seeds to farmers usually of
the record-type, buy up all the produce grown from the seeds provided to the farmer. In addition, theprice is not fixed, and the contract firm buy the produce at the farm gate price and sometimes bynegotiations. The cost of the input seeds is deducted at the period of selling of produce after
harvesting.
In the study area, both Three sisters in Dodoma and Ikungi Sunflower Edible Cooking Oilprovide a long-term contract for a period of eight (8) years cropping season. In production, individual
sunflower farmers organize themselves into contract farming and non-contract farming. The contract
company provides inputs such as fertilizers, seeds, and pesticides. The contract is through verticalⒸ ISERD

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coordination and major support institutions in sunflower contract arrangements are Rural Livelihood
Development Corporation (RLDC), Private and Small Medium Sunflower Oil Processors andInternational Agriculture Non-Government Organization (NGOs) as shown in Fig. 2.

Fig. 2 Coordinating production and contract arrangement of sunflower seeds in Tanzania
Source: Field survey, 20193) Farmers’ Perception in Terms of Trust, and Personal Relations Play for their Coordination
To understand the farmers’ perception in terms of personal relations play for their coordination, theGarret ranks were calculated based on the data obtained in the field survey 2019, by using appropriate
Garret Ranking formula. This method provides out the most significant factor which influences the
respondent.
Percent position = 100 (Rij – 0.5)
Njwhere Rij = rank given for the ith variable by jth respondents, Nj = number of variables ranked byjth respondent.
Table 2 Farmers` perception in terms of trust personal relations playfor their coordination
Serial number

Constraint

Garret Score

Rank

1
2
3

Mistrust in the mode of payment
Lack of government monitoring
Price of produce

63.0
58.0
55.0

1
2
3

Source: Field survey, 2019In terms of trust and personal relations, the study noted a prevailing mistrust between the twoparties in the mode of payment on crop produce (63.0 Garret score). Farmers were arguing that; thecost of inputs were inflated to maximize companies` profits. In an interview with one farmer, shesaid; “ After harvesting sunflower I take them to XXX company that I have a contractual agreementwith. But, honestly, I am not satisfied with the costs of inputs, I think they tend to inflate them…”(Interview, 2019). Moreover, contract farmers did not have written signed contract papers. Anotherimportant factor is lack of government monitoring (58.0 Garret score). In the study area farmers
reported that the contracts are not well monitored by the ward and village officers that are responsible
to oversee compliance. Therefore, the absence of proper government control discourages smallⒸ ISERD68

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holder participation in contract farming. In addition, price of produce was reported as anotherchallenge among farmers (55.0 Garret score). In contract farming, farmers produce quality seeds withhigh cooking oil content. Surprisingly, in contract terms, prices are not set in advance, contract
farmers sell their produce with similar price to the local sunflower seed. Based on this finding, noncontract farmers were not willing to participate in contract farming.
CONCLUSION
The study aims to investigate the impact of contract farming program among sunflower farmers. It
was indicated that contract terms and conditions, hereafter called contract design attributes such asmode of payment and price setting of farmers’ crop produce can affect farmers’ decisions toparticipate in contract farming, varyingly affecting their expected level of utility from participation.
In other words, lack of education was the factor for non-contract farmers to participate in contract
farming.
In relation to the findings and conclusion the following were recommended to alleviate theexisting challenges by all stakeholders of this sector. First, there is a definite need for the governmentof Tanzania to monitor and ensure that both parties adhere to the contract terms. In addition, priceshould be set in advance and reflect the quality of the crop. This will increase the willingness offarmers to participate in contract farming.
ACKNOWLEDGEMENTS
We would like to express our gratitude to Tokyo Nodai Foundation and Graduate Research Funding
Program from Tokyo University of Agriculture Research Institute (NRI) for financially supporting
this study.
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Ugulumu, E. and Inanga, E. 2014. Market access and sunflower marketing: Challenges and prospects to small
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Research article
erd

Factors Affecting the Teaching Attitude of High School
Agriculture Teachers in the PhilippinesJENNICA AMIELLE M. MORA
Graduate School of Agriculture, Tokyo University of Agriculture, Tokyo, JapanHIROKI INAIZUMIFaculty of International Agriculture and Food Studies,Tokyo University of Agriculture, Tokyo, Japan

NINA N. SHIMOGUCHI*
Faculty of International Agriculture and Food Studies,Tokyo University of Agriculture, Tokyo, Japan
Email: n3nocon@nodai.ac.jp
Received 20 January 2020

Accepted 24 September 2021(*Corresponding Author)

Abstract The Enhanced Basic Education Act of 2013, also known as K to 12 Program,
primarily aims to bring the Philippine education system at par with international standards
through preparing graduates for college education, employment, or entrepreneurship. The
Philippines has a clearer model with four Senior High School tracks compared to othercountries. As the new program puts focus on student-centered learning, the quality ofagriculture teacher education seems to be left behind. Previous literatures show that majorityof the Teacher Education Institutions (TEIs) still has not aligned their curriculum to the needsof the K to 12 Program while current high school agriculture teachers have insufficient
relevant trainings or seminars that relates to teaching strategies and in-service specialization.
Aside from the effect of TEIs, one of the factors that can affect the quality of teachers is theirteaching attitude. Teaching attitude encompasses complex topics, but this study focused only
on preferences and motivations of high school agriculture teachers as these can be reflectedto the interventions done in concurrent challenges in the Philippine education and agriculture.
This study employed a semi-structured questionnaire for preferences on teaching andteaching agriculture and motivations in teaching. A five-point Likert-type scale revealed thatthe median for both preferences was ‘5’ which means most of the respondents have ‘veryhigh’ preferences. This is despite only one (1) among seven (7) respondents stated that thefirst choice of profession was teaching. Qualitative analysis revealed that respondents
encountered challenges in school facilities, professional development focusing on content
knowledge, and lack of teaching and non-teaching personnel. The recommendation of thisstudy is to focus on improving the holistic skills of high school agriculture teachers not onlyin teaching strategies but in content knowledge as well since these relate to their professional
development.
Keywords teaching attitude, preference and motivation, high school agriculture teachers,
content knowledge

INTRODUCTION
The Enhanced Basic Education Act of 2013, also known as the K to 12 Program, primarily aims tobring the Philippine education system to international standards by preparing graduates for college
education, employment, or entrepreneurship. This initiative entails two additional years of basic
education, called the Senior High School (SHS) Program. The Philippines’ SHS Program has four
tracks with 10 strands which makes it a more detailed model compared to that of Japan and USA(Sarmiento and Orale, 2016).

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The four tracks of the Philippines’ SHS Program are: Academic; Arts and Design; Sports; andTechnical-Vocational-Livelihood (TVL). A school offers a track based on the capability andpotentiality of the community where the school is located. Before the students choose a track, they
are required to take the exploratory components of the Technology and Livelihood Education (TLE)
subject, which includes: Agri-Fishery Arts (AFA), Home Economics (HE), Information andCommunications Technology (ICT), and Industrial Arts (IA). (Perolina, personal communication,
september, 2019)
The K to 12 Program focuses on student-centered learning, as can be seen in the 2019 Voluntary
National Review of the Philippines on the status and implementation of the United Nations’Sustainable Development Goals (SDGs). However, there are still gaps in providing quality education
to the students as the Department of Education (DepEd) identified that the proportion of teachers
teaching in line with their specialization must be increased. According to the Philippine Business for
Education (PBEd), as cited by Montemayor (2018), only 20% of the Teacher Education Institutions(TEIs) have aligned their curriculum to the needs of the K to 12 Program. There have been inadequate
teacher training programs that can help teachers acquire new knowledge and approaches (Alegado,2018). Aside from the effect of TEIs and teacher training, one of the factors that can affect the qualityof teachers is their teaching attitude. Teaching attitude encompasses complex topics. However, thisstudy focused only on the preferences and motivations of high school agriculture teachers (HSATs).
OBJECTIVE
This study aimed to determine the teaching attitude of HSATs in terms of preferences and motivations
since these can be reflected in the interventions done in contemporary challenges of Philippine
education and agriculture.
METHODOLOGYThis study utilized Life History Approach (LHA) through one-on-one interviews. LHA does notfollow a chronological path as it aims for the participants to tell the story of their lives without
obstruction (Bakar and Abdullah, 2008). A total of seven (7) teachers from three (3) public highschools were interviewed from August to October,2020. There were two (2) teachers from School A,
a college preparatory high school and one of the basic education units of University A; two (2)teachers from School B, a science and technology high school; and three (3) teachers from School C,
an agro-industrial high school. These schools were chosen to adhere to the primary function of the K
to 12 Program, which is to prepare the students for college education, employment, andentrepreneurship, respectively. This study employed a semi-structured questionnaire for teaching andteaching agriculture preferences and motivations in teaching. A five-point type Likert scale (1 as very
low preference; 5 as very high preference) was used to determine teaching and teaching agriculture
preferences, while open-ended questions were used to identify the challenges encountered. In
addition, the teachers were asked to rate the extent of how the challenges affect their teaching.
RESULTS AND DISCUSSION
Preferences of High School Agriculture Teachers (HSATs) on ‘Teaching as a First Choice ofProfession’, ‘Teaching’, and ‘Teaching Agriculture’
Table 1 shows the characteristics and preferences of HSATs on teaching, teaching agriculture, andteaching as the first choice of profession. Four (4) out of seven (7) teachers stated that they have very
high preferences for teaching. Teacher A1 stated that teaching was not his first choice since he had
other plans when he was in college. Teacher A1, who graduated from BS in Forestry, has beenteaching in School A as part-time for four (4) years and as full-time for 29 years. During his parttime teaching in School A, he took the offer to teach agriculture; hence, he had to take his secondⒸ ISERD

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degree, BS in Agriculture. He was hired as a full-time teacher before he finished his second degree.
He also took units on education which qualified him to take the Licensure Examination for Teachers(LET). However, at that time, he was the appointed principal of School A. Teacher A1 rated a ‘highpreference’ on teaching stating, “When you are in School A’s system, your position is relatively stable
but then at the same time you need to satisfy the school’s requirements like an advanced degree,
publication… things like that. It is stable, and at the same time, you have professional growth since
you are required. If you do not take further studies, you will be dismissed from teaching.” Moreover,
Teacher A1 rated a ‘very high preference’ in teaching agriculture stating, “Some of our students here
are really alien on agriculture since most of our students here come from private schools. … Thereis a different challenge in high school since you do not just teach them; you also mentor them whichsometimes become an additional effort.” Teacher A1 also stated that he shows the actual conditionof agriculture in the Philippines not to discourage the students but to challenge them.
Teacher A2 stated that teaching was not her first choice of profession. She took the Licensure
Examination for Agricultural Engineer administered by the Professional Regulation Commission(PRC). She tried practicing her expertise in public office for six (6) months, but when she did not
feel any professional growth, she resigned then applied for a position in School A instead. Teacher
A2 originally wanted to teach college students, but her husband, who has the same course and major
as hers, was accepted as a college instructor in University A, where she wanted to teach. She did not
pursue applying for the teaching position at University A since she did not want to be in the sameworking environment with her husband. She also stated, “I thought to myself, I will just teach here
in School A since the topics are somewhat similar.” Teacher A2, who has been in School A for seven(7) years, rated a ‘very high preference’ on teaching but asked to clarify the question, “Is this basedon what I felt before or what I feel now?” which may imply that she may have had a lower preference
during her early years in teaching since it was not her first choice of profession. Teacher A2 also
rated a ‘very high preference’ in teaching agriculture and stated that she wanted to encourage students
to take the same degree as hers or any agriculture-related courses.
Teacher B1, whose major was fish culture in Bachelor of Secondary Education (BSE), teaches
crop production in School B. He stated that teaching was not his first choice of profession. According
to Teacher B1, “I took it because back then, it was the only four-year course offered in our province,
which sounded very professional.” He has a ‘high preference’ for teaching because of the stable
income while a ‘very high preference’ on teaching agriculture because of the suitability of crop
production in the Philippine setting. Teacher B1, a member of a religious organization, also sharedthat he wanted to insist agriculture to students since agriculture existed as early as the bible recorded.
Teacher B2 took BS Agricultural Education and technical courses in cookery and pastry. She
has developed her interest in teaching during her 40 years of experience but stated that teaching was
not her first choice of profession. She shared, “This was what my family could afford back then. It
would have been very expensive had I taken nursing since my siblings and I were simultaneously
studying.” Teacher B2 rated both preferences on teaching and teaching agriculture as ‘very high’because of having a stable income.
Teacher C1 stated that he originally wanted to work overseas on a different job despite
graduating with a degree in BSE. He was underqualified with the work he applied for overseas.
Therefore, he decided to settle in the Philippines and apply for a teaching position in School C. This
was also why he rated ‘high preference’ on both teaching and teaching agriculture.
Among the seven (7) teachers interviewed, Teacher C2, who has the shortest experience inteaching of two (2) years, stated that teaching was his first choice of profession. He stated, “It is the
only course that comes to my mind. It is like being a teacher is the only profession that I want.” Healso rated his preference on teaching as ‘very high preference’ not because of income but because hewanted to impart knowledge to his students. However, he hesitantly answered ‘neutral preference’
when asked about his preference for teaching agriculture. Teacher C2 stated that his interest and preservice specialization was IA, one of the four components of TLE, yet his in-service specialization
was organic agriculture. In addition, there were only a few units for agriculture during the time hewas taking his major courses.
Teacher C3 would have been a priest not until he decided he wanted to get married and have his
own family. He left the seminary and would have taken BS Electrical Engineer, but due to financialⒸ ISERD73

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constraints, he opted to take BSE instead with the reason, “Being a priest and a teacher is almost thesame. The only difference is that one teaches the word of God, the other teaches academic lessons.”
Teacher C3 rated his preferences on both teaching and teaching agriculture as ‘very high,’ statingthat “As of now, maybe I am already in the highest preference because I am already here. I havecome to like what I am teaching.”
Table 1 Characteristics and preferences of high school agriculture teachers on teaching as afirst choice of profession, teaching, and teaching agriculture
Respondent
Teacher A1
Teacher A2Teacher B1
Teacher B2
Teacher C1
Teacher C2Teacher C3

Bachelor’ degree
Forestry;
Agriculture
AgriculturalEngineering
Secondary
Education
Agricultural
Education
Agricultural
Education
Secondary
Education
Secondary
Education

Educational
attainmenta

Teaching as first
choice ofprofession

Teachingb

Teaching
agricultureb

3

No

4

5

2

No

5

5

2*

No

4

5

2; 4

No

5

5

2

No

4

4

1

Yes

5

3

2

No

5

5

Source: Field Survey, 2019a(1) Bachelor’s degree (2) Master’s degree (3) Doctoral degree (4) Technical/vocational degree (*) Units onlyb(1) Very Low Preference (2) Low Preference (3) Neutral Preference (4) High Preference (5) Very High Preference

Challenges Encountered and Interventions Done by the High School Agriculture Teachers(HSATs)Table 2 shows the factors affecting the challenges encountered by the HSATs and the extent of theireffect daily. One (1) teacher and two (2) teachers from Schools B and C, respectively, rated ‘low
extent’ for their problems on school facilities in terms of Information and Communication
Technology (ICT) units and demonstration garden. According to Teacher B1, School B has thebudget to provide the ICT units such as laptops and Liquid Crystal Display televisions (LCD TV)
for their laboratory room. This situation makes it easy for him to teach as his limited teaching time
will not be spent on the preparation of these materials. Regarding Teachers C1 and C3 related school
facilities, specifically demonstration garden and ICT units, School C has enough area for hands-on
farming activities. However, both teachers use their own laptop for everyday teaching, sharing thatit has become a part of their daily routine as teachers. As per Teacher C3, he had to loan money tobuy a laptop which has been a great help to him during the preparation of instructional materials andcomputation of final grades.
On the other hand, Teachers B2 and C2 rated ‘moderate extent’ for their problems with school
facilities regarding their respective demonstration gardens. The garden for School B gets flooded
when typhoons and heavy rains come, while Teacher C2 thinks that the area for the garden is still
small. Typhoons and heavy rains are usually experienced in the Philippines from June to November,and this has been a problem for Teacher B2 for years. To cope with the environmental challenges,
she does not plant leafy vegetables during these months as these can be easily damaged. In contrast
to the previous statement of the other two (2) teachers in School C, Teacher C2 thinks that the school
can still expand the demonstration garden to give the students more areas to experiment on theirclassroom learning.
Teachers A1 and A2 related their problems on school facilities in terms of the quality andavailability of classrooms and laboratories and rated it as ‘high extent.’ School A borrows rooms andⒸ ISERD

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various types of machinery from University A (approx. 5.5 km away) while its laboratory was only
improvised. The improvised laboratory of School A, a four-poster shed with a galvanized iron sheet
for the roof, is where the students conduct food processing. Teachers A1 and A2 shared that it
becomes difficult for them to teach in the improvised laboratory, especially when it is raining, as
their voices need to compete with the sound of rain on the roof. Animal production is also a part ofthe curriculum of School A; however, due to financial constraints, School A would ask the students
for contributions to build cages and buy animals such as chicks and pigs. The students will, later on,
be taught how to dress the chickens and slaughter the pigs, then take them home.
Three (3) out of seven (7) teachers rated ‘moderate extent’ for their problems on content
knowledge. Teacher A2 related content knowledge not only on the topics that she teaches but also
on the teaching strategies. As previously mentioned, Teacher A2 graduated from an engineeringcourse; hence, she assessed that she lacks knowledge on the how-to of teaching. Teacher A2 plansto take education units in University A. Teachers C1 and C3 felt the need for more training or seminarfor the reasons of interest in other fields and difference in pre- and in-service specialization,
respectively. Teacher C1 wanted to know more about food processing as he thinks that learning how
to grow agricultural products is not enough; the students also need to know how to put additional
value to their produce. Meanwhile, Teacher C3’s pre-service specialization was electrical under HE
but is now teaching organic agriculture. He has attended several trainings on organic agriculture
before being assigned to teach it.
Table 2 Factors affecting the challenges encountered by the high school agriculture teachers
and the extent of its effectRespondent
School A
Teacher A1
Teacher A2
School B
Teacher B1
Teacher B2
School C
Teacher C1
Teacher C2Teacher C3Years inteaching
33
7
15
40
12
2
10

School information
Basic education unit ofUniversity A

Under the management of
Department of Education(DepEd)Schoolfacilitiesa

Content
knowledgea

Lack ofpersonnela

3
3

1
2

3
3

1
2

3
1

1
1

1
2
1

2
3
2

1
1
1

Source: Field Survey, 2019a(1) Low Extent (2) Moderate Extent (3) High Extent

Teachers A1 and B2, who have been teaching for more than 30 years, rated ‘low extent’ oncontent knowledge. Teacher A1 thinks that this problem would have been rated ‘high extent’ if hewere a new teacher, while Teacher B2 uses her own experience in farming as a reference in teaching.
The World Bank (2005) as cited by Wongsamun et al. (2012), stated that one of the powerful toolsthat teachers can use in the learning environment of the students are their local or indigenous
knowledge. Conversely, Teachers B1 and C3 rated ‘high extent’ for their problems on content
knowledge. They both felt the need for more training and seminar for different reasons. Teacher B1’s
pre-service specialization was fish culture, yet he teaches crop production in School B, while Teacher
C2 has been teaching in School C for not more than five (5) years. Teacher B1 shared that if thedesignated topic for the day is too difficult for him to teach due to his lack of knowledge, he will opt
not to teach the topic and search for another topic somehow related to it. He also shared that whenever
his students ask questions that are too difficult for him to answer, he gives that question an assignment
for them. As for Teacher C2, he would ask his co-teachers to explain unfamiliar topics to him.
The lack of personnel was rated as ‘low extent’ by two (2) teachers and three (3) teachers in
Schools B and C, respectively. Since Schools B and C are under the DepEd, along with theimplementation of the K to 12 Program is the hiring of non-teaching personnel. The non-teaching
personnel are tasked to do administrative works. Teacher B1, on his initiative, maintains theirⒸ ISERD

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demonstration garden during his free time. Teacher C3 was appointed by their principal to be thecanteen coordinator of School C. He also attends to the repair and maintenance of School C’s
facilities and other things as directed by their principal. Both teachers do not see these works as outof bounds since they think that these come as part of being a teacher.
On the other hand, both Teacher A1 and A2 rated the lack of personnel as ‘high extent.’ School
A is the basic education unit of University A. Therefore, the implementation of K to 12 Program did
not affect the hiring of additional personnel to attend to the changes in the curriculum. Teacher A2needed to take some units/loads from Teacher A1 since the latter was appointed to an administrative
position in School A. Both teachers shared that there is only one non-teaching personnel who can
assist other subject’s laboratories simultaneously. This situation causes a problem for the teachers
since they must prepare class materials instead of doing other activities that can contribute to thebetterment of their teaching performance. To cope with the lack of personnel, Teacher A1 would
have to prepare the materials a day or two before the class.
CONCLUSION
Based on the interviews, only one (1) HSAT preferred teaching as the first choice of profession.
However, most of the interviewed HSATs rated ‘very high preference’ for teaching and teaching
agriculture because of developed preferences, stable income, and passion for becoming an educator.
In general, HSATs from the University A-managed school rated ‘high extent’ on both challenges
encountered in school facilities and lack of personnel while HSATs from the DepEd-managed
schools rated ‘low extent’ on these challenges. Conversely, HSATs from DepEd-managed schools
rated ‘high extent’ on challenges encountered in content knowledge while HSATs from University
A-managed school rated ‘high extent’ and ‘moderate extent.’ Therefore, it can be concluded that
despite these challenges, the developed HSATs preferences and passion for teaching primarily drives
them to ensure that their students learn the fundamentals of agriculture.
In this regard, the study recommends that the DepEd provide more accessible professional
development activities such as lectures, seminars, or training to HSATs in Schools B and C throughpartnering with the nearby agricultural universities. At the same time, University A can further extend
its assistance to School A by lending a kitchen laboratory used by one of its institutes.
For further study, there is a need to determine the life experiences of the HSATs that developed
their preferences on teaching and teaching agriculture. The TEIs can use these life experiences toincrease the number and quality of HSATs.
REFERENCES
Alegado, P.J.E. 2018. The challenges of teacher leadership in the Philippines as experienced and perceived byteachers. International Journal of Education and Research, 6 (6), 291-302.
Bakar, N.A. and Abdullah, M. 2008. The life history approach: Fieldwork experience. Jurnal e-Bangi, 3 (1), 19.
Montemayor, M.T. 2018. Teacher education must be learner-centered. DepEd exec, Retrieved from https://www.pna.gov.ph/articles/1053507
Sarmiento, D.H. and Orale, R.L. 2016. Senior high school curriculum in the Philippines, USA, and Japan.
Journal of Academic Research, 1 (3), 12-23.
United Nations. 2019. The 2019 voluntary national review of the Philippines. Retrieved from https://sustai
nabledevelopment.un.org/content/documents/23366Voluntary_National_Review_2019_Philippines.pdf
Wongsamun, C., Martwanna, N., Taechaprasertwitaya, P. and Charoenkornburi, S. 2012. Integration of local
knowledge into teaching-learning activities of agricultural subjects in primary education. International
Journal of Environmental and Rural Development, 3 (2), 38-42.

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Research article
erd

Spatial Analysis of Yield Gaps Variability of Black Gram

Based on GIS and Geostatistics
HTAY HTAY OO *Yezin Agricultural University, Myanmar
Email: htay.agro96@gmail.com

KHIN MAR OO
Nyein Nyein Htwe and Hla Than, Yezin Agricultural University, Myanmar
Received 25 January 2020

Accepted 24 September 2021(*Corresponding Author)

Abstract Black gram, a pulse, is one of the major export crops in Myanmar. Because of adecline in the maximum possible yield of this crop in farmers’ fields, a yield gap exists
between potential and farmers’ actual yields. Reducing the gap between actual and potential
yields is critical for increasing crop production. This study was carried out to generate yield
gap mapping, and to investigate the reasons responsible for this yield gap in black gramproduction. An annual survey was carried out to determine farmers’ actual yield at Kyee Inn
Village, Pyinmana Township during October 2017 and 2018. Drone photos wereconsolidated and prepared for digitizing and analyzed with Pix4D software. ArcGIS 10.7
software was used to map the spatial distribution of the yield gap of black gram in the selected
area. Yield gaps of black gram with a range of 0.02 t ha-1 to 2.70 t ha-1 in the two consecutive
years were observed. The yield gap between potential and farmers’ actual yields (Yield Gap
I) was greater in 2018 compared to the 2017 season. The gap between the yield obtained
through an organized farm trials and the yield harvested by the farmers (Yield Gap II) was
also larger in 2018 than that for the 2017 crop season. A technology gap for the variety Yezin6 (0.68 t ha-1) was observed in 2018 whereas there were no gaps for Yezin-2 and Yezin-5 in2017 and non for these varieties in the 2018 post-monsoon season. The reasons these large
yield gaps may exist, is probably due to differences in crop management practices used at theexperimental stations and those by farmers. The results of this study should provide useful
information for policymakers, researchers, extension agents, and other stakeholders to
upgrade a location-specific package of practices and increase crop yield by supporting
technological solutions and training for the farmers.
Keywords black gram, yield gap, mapping, spatial, potential yield

INTRODUCTIONIn Myanmar, black gram (Vigna mungo L.) is one of the major exportable pulses and widely sown
as a second crop after monsoon rice. The total sown area of black gram was 0.98 million hectares,
with a production of 1.38 million tons from 2016 to 2018. Depending on the varieties, the averagepotential yield of black gram recorded by the Department of Agricultural Research (DAR) is 2.40 t
ha-1, whereas the average actual yield of black gram is 1.44 t ha -1(MOALI, 2018). Consequently, alarge yield gap exists between the farmers’ actual yield and the potential yield as demonstrated at the
research station.
Expansion of cropland farmed is probably not a sustainable option to increase crop production
so there is a need to increase crop yield on existing cropland, providing sustainable intensification of
the current crop production (Forland, 2015). Presently, spatial and temporal variability of crop yields
exist across regions, even within the same climatic zones due to different levels of knowledge,
different farming practices, technologies, supply chains, and policies in that area (Licker et al., 2010).
This has resulted in a spatial variability of the yield gap in black gram production in Myanmar.
Additionally, farmers were still facing diverse technological gap in cultivation though there wereagricultural modernization in pulse crops.
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Analyzing the yield gap using Geographic Information System (GIS) can provide graphic
information demonstrating the variability of crop yields and possibly allow for the assessment of theunderlying causes of this yield gap, which would then assist in identifying strategies for narrowing
these yield gaps (Tran and Nguyen, 2006). Yield gap analysis can help to develop changes in methodsof crop production to bridge the gaps between the potential yield of crop variety obtained through anorganized farm demonstration during its development in research stations and the yield harvested by
the farmers (Jopir and Bera, 2017). It also provides valuable information for decision makers andresearchers allowing the development of strategies or action plans for minimizing yield gaps andimproving production sustainability.
OBJECTIVE
The objectives of this research were to develop mapping showing the spatial variation of yield gapsof black gram in selected areas to provide information that allows the generation of good production
practices for black gram production.
METHODOLOGY
Study Site
The research was conducted over two consecutive years of post-monsoon season, in 2017 and 2018,
at Kyee Inn Village, Pyinmana Township, Nay Pyi Taw Union Territory, which lies between
1970'66''- 1972'62'' N and 9622'43''- 9625'73'' E (Fig 1.). The total study area was 483 ha. The
major pulse was black gram which is grown as a second crop after the harvest of monsoon rice. The
study area was characterized by low content of organic matter, it has (mostly) low to high levels of
total nitrogen and low to medium ranges of total phosphorus, while the level of the CEC is very low
to low (Moe et al., 2019).

Nay Pyi Taw

Kyee Inn
Village

Sample grid(300 m  300)m)
Sample plot

Pyinmana
TownshipFig. 1 The study area at Kyee Inn Village,
Pyinmana TownshipFig. 2 Sample grids and sample plots
taken in Kyee Inn Village

Source: https://myanmar.unfpa.org/…/union-report- volume-3o-nay-pyi-taw-union-territory-re
www.dop.gov.mm/sites/dop.gov.mm/files/publication _docs/pyinmana_0.pdf

Preparation of Sample Plots and Data Collection
The base-map preparation enabling use of ArcGIS 10.7 software was accomplished by data obtained
from a DJI Phantom 4 drone, with this processed using Litchi software. The photos were consolidated
and processed for digitizing using Pix4D software and incorporated onto the digital base map. The
study area was divided into 300 m × 300 m geographic grids. The 92 sample grids were encompassed
and 78 of these sample grids were under black gram cultivation (Fig 2).
The 70 farmers cultivating the 78 sample plots were selected as respondents and interviews wereconducted to identify variation in average yield and crop management practices in the sample area.
The potential yield (YP- irrigated conditions) of black gram was provided by the Oilseeds and Pulses
Crops Division, Department of Agricultural Research (DAR), Yezin, Nay Pyi Taw. The potential
yield (YW- rainfed conditions) of black gram was obtained from on farm trials conducted byⒸ ISERD

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Department of Agronomy, at Kyee Inn Village, Pyinmana Township in the 2017 and 2018 (Oo et.
al., 2019). The farmers’ actual yield (YA) was recorded from the respondents in the study area for the2017 and 2018 crop seasons.
Preparation for Mapping
The polygon boundary shapefiles and merged polygon shapefiles were created using the ArcGIS
10.7 software. According to yield gap calculation, point shapefiles of Yield gap I and Yield gap II
were prepared for the study area for the two consecutive years. Because of limited number of sample
points, the spatial interpolation was conducted by Kriging, it is a geostatistical interpolation method(Karydas et al., 2009). Maps of the spatial distribution of Yield gap I and Yield gap II was generate
through ArcToolbox (Spatial Analyst > Interpolation > Kriging).
Calculations
Yield gap I is the difference between potential yield (YP- irrigated conditions) and farmers’ actual
yield (YA) and Yield gap II is the difference between water-limited potential yield (YW- rainfed
conditions) and farmers’ actual yield (YA) (Equations 1 and 2).
Yield gap I = Potential yield (YP) – Farmers’ actual yield (YA)

(1)

Yield gap II = Water-limited potential yield (YW) – Farmers’ actual yield (YA)

(2)

The technology gap (YTG) was determined as the difference between the water-limited potential
yield (YW) and the highest farmers’ yield (YHF) (Equation 3). The highest farmers’ yield (YHF) is anempirical concept intended to define the maximum YA achieved. YHF was estimated by calculating
the mean of actual yields above the 90th percentile (Silva et al., 2017).
Technology gap (YTG) = Water-limited Potential yield (YW) – Highest farmers’ yield (YHF)(3)

RESULTS AND DISCUSSION
Survey Result of Yield and Crop Management Practices
In this study area, the farmers’ actual yield (YA) was in the range of 0.08 to 1.97 t ha-1, for the 2017and 2018 post-monsoon seasons (Table 1.). Most of the respondents (85%) do not retain residues of
black gram after harvesting. About 32% of respondents use optimum seeding rate recommended by
DOA. Only 18% of respondents applied urea and compound fertilizers as basally at planting time.
There was no evidence of the application of phosphorus and potash fertilizers for black gramproduction. The most common type of chemical sprayings used by respondents for black gramcultivation were foliar and fungicides and about 12% of respondents follow optimum spraying
frequency (4 times for whole season) recommended by DOA. Seed sowing method was broadcastingso that weeding was not done for black gram cultivation in the study area.
Spatial Analysis on the Variation in Yield Gap I
The potential yield (YP) obtained from the DAR for black gram varieties used in the study area ranged
from 1.75 to 2.78 t ha-1 while the farmers’ actual yield (YA) was in the range of 0.08 to 1.97 t ha-1,
for the 2017 and 2018 post-monsoon seasons (Table 1). The Yield gap I of black gram was recordedwith the range of 0.73 to 2.70 t ha-1 in 2017 and 0.28 to 2.62 t ha-1 in the 2018 post-monsoon season(Table 2). The results indicate that variations of Yield gap I occurred during these two consecutive
years.
A wider Yield gap I of 0.73 to 1.99 t ha-1 and 0.81 to 2.70 t ha-1 was recorded for the varieties
Yezin-2 and Yezin-6, respectively in the 2017 and 2018 post-monsoon seasons (Table 2).

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Table 1 Potential yield and farmers’ actual yield of black gram varieties in Kyee Inn Village,
Pyinmana Township during 2017 and 2018 (post-monsoon seasons)Variety

Potential yield (YP)(t ha-1)

Potential yield (YW)(t ha-1)

Yezin-2
Yezin-5
Yezin-6

2.15
1.75
2.78

0.88
0.73
0.93

Farmers’ actual yield (YA)(t ha-1)
2017
2018
0.43-1.42
0.16-1.47
0.16-1.82
0.16-1.47
0.08-1.97
0.16-0.25

Table 2 Yield gap I and Yield gap II of black gram varieties in Kyee Inn Village, Pyinmana
Township during 2017 and 2018 (post-monsoon seasons)
Yield gap I (t ha-1)
Variety
Yezin-2
Yezin-5
Yezin-6

Yield gap II (t ha-1)

2017

2018

2017

2018

0.73-1.72
0.80-1.59
0.81-2.70

0.68-1.99
0.28-1.59
2.53-2.62

0.21-0.45
0.02-0.57
0.10-0.85

0.23-0.47
0.08-0.32
0.68-0.77

The spatial variations of Yield gap I appears to be higher and range from 1.26 to 1.60 t ha-1 in
2017 whereas most fields displayed a Yield gap I of 0.91 to1.25 t ha-1in 2018 (Fig. 3). The highest
Yield gap I (1.61-1.89 t ha-1) happened in both years, but showed a greater and more scattered patternin 2017 (Fig. 3). These differences may possibly be due to differences in crop and nutrientsmanagement practices between the trial station and the farmer’s fields.
2017

2018

0.84-0.90 t ha
1.26-1.60 t ha

-1

0.91-1.25 t ha

-1

-1

1.61-1.89 t ha

-1

Fig. 3 Spatial variations of Yield gap I of black gram in Kyee Inn Village, Pyinmana Township
Spatial Analysis on Variation of Yield Gap II
The Yield gap II varied from 0.02 to 0.85 t ha-1 in 2017, and 0.08-0.77 t ha-1 in 2018 (Table 2). The
variation in Yield gap II across the fields appears to indicate varied crop management practices
among black gram farmers in the study area. The trial plantings, used as a base comparison, usuallyfollow recommended crop management practices, especially regarding basal and foliar fertilizers
application, weeding, and plant protection measures. However, the potential yield (YW) obtained was
lower than that of some farmers’ actual yield. The Yield gap II ranged from 0.20 to 0.55 t ha-1 in thetwo consecutive years (Fig. 4). The larger proportion of the fields had a Yield gap II of 0.26-0.35 t
ha-1 in 2017 and this gap appear to be larger 0.36-0.45 t ha-1in 2018. The greatest Yield gap II of
0.46-0.55 t ha-1 was observed in the 2018 crop season, and such a gap was not present in the 2017
crop. The slight increase of Yield gap II in the 2018 season may have been due to a steady decreasein farmers’ actual yield during the study period. The study area was characterized by low content oforganic matter, it has (mostly) low to high levels of total nitrogen and low to medium ranges of totalⒸ ISERD

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phosphorus, while the level of the CEC is very low to low (Moe et al., 2019). According to the resultsof interviews, farmers in the study area did not apply of phosphorus and potash fertilizers for black
gram production and thus, the Yield gap II was resulted for two consecutive years.
2017

2018

0.20-0.25 t ha

0.36-0.45 t ha

-1

0.26-0.35 t ha

-1

-1

0.46-0.55 t ha

-1

Fig. 4 Spatial variations of Yield gap II of black gram in Kyee Inn Village, Pyinmana TownshipTechnology Gap of Black Gram in Kyee Inn Village, Pyinmana Township
The technology gap represents the difference between the potential yield (YW) and the highest
farmers’ yield (YHF). The technology gap was not found in the 2017 post-monsoon seasons (Table3). It was observed only by the variety of Yezin-6 (0.68 t ha-1) in 2018. From 2017 to 2018 postmonsoon seasons, the technology gap was not recorded by the variety of Yezin-2 and Yezin-5. The
results indicated that the recommended crop production practices of a black gram would need to
upgrade for increasing crop yield in the study area.
Table 3 Technology gap of black gram varieties in Kyee Inn village, Pyinmana Townshipduring 2017 and 2018 (post-monsoon seasons)Variety
Yezin-2
Yezin-5
Yezin-6

Potential yield(YW)(t ha-1)
0.88
0.73
0.93

Highest farmers’ yield (YHF)(t ha-1)
2017
2018
1.42
1.19
0.91
1.23
1.32
0.25

Technology gap (t ha-1)
2017
-

2018
0.68

CONCLUSION
A crop yield gap was found in most farmers’ fields due to their differences in crop management
practices including residue management, basal and foliar fertilizers applications, weeding and plant
protection measures. Therefore, it is necessary to introduce an appropriate package of production
practices for the study area. Farmers should be encouraged to follow the systematic crop management
practices as much as possible to increase crop production. As expected, the spatial variation of Yield
gaps exists largely due to the differences in the crop management practices used at the experimental
stations and those by farmers. The wide Yield gaps were observed in both years. The reason theselarge yield gaps may exist, is probably due to not applying phosphorus and potash fertilizers to theblack gram. Therefore, the results of the study provide useful information for policy makers,
researchers, extension agents, and other stakeholders to upgrade location-specific information
packages outlining best practice. This study has shown that the use of new technologies such as GIS
and Geostatistics can provide important information for evaluating the status of Yield gap of black
gram in the study area.

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ACKNOWLEDGEMENTS
We would like to gratefully acknowledge the Japan International Cooperation Agency (JICA), who
supervise the Project for Capacity Development of Yezin Agricultural University, and who haveprovided technical and financial support for this study. We are also appreciative for the information
provided by the authorized persons from Department of Agricultura (DOA), Department ofAgricultural Research (DAR) and Department of Agricultural Land Management and Statistics.
Finally, we are very grateful to the farmers in the study area for their keen participation throughout
the study.
REFERENCES
Forland, C. 2015. Spatial quqantification of the gap between farm field and University Trial Maize Yields in
the United States. Master Degree Dissertation of Master of Science in Bioproducts/Biosystems Science
Engineering and Management/ University of Minnesota, USA.
Jopir, O. and Bera, B.K. 2017. A study on analysis of yield gap in pulses of Nadia district of West Bengal.
India, Journal of Applied and Natural Science, 9 (2), 646-652.
Karydas, C.G., Gitas, I.Z., Koutsogiannaki, E., Lydakis-Simantiris, N. and Silleos, G.N. 2009. Evaluation of
spatial interpolation techniques for mapping agricultural topsoil properties in Crete. EARSeLe Proceedings,
8 (1), 26-39.
Licker, R., Johnston, M., Foley, J.A., Barford, C., Kucharik, C.J., Monfreda, C. and Ramankutty, N. 2010.
Mind the gap: How do climate and agricultural management explain the ‘yield gap of croplands aroundthe world? Global Ecology and Biogeography, 19 (6), 769-782.
Ministry of Agriculture, Livestock and Irrigation (MOALI). 2018. Agriculture at a glance. Nay Pyi Taw,
Myanmar.
Moe, N.N., Mar, S.S., Myint, A.K., Toe, K. and Ngwe, K. 2019. The spatial variability of soil chemical
properties in a selected area of Myanmar. International Journal of Environmental and Rural Development,
10 (2), 20-26.
Oo, K.M., Oo, H.H., Htwe, N.N. and Than, H. 2019. Comparative study on pulse production with different
practices: A case study of mungbean and black gram. International Journal of Environmental and Rural
Development, 10 (2), 97-103.
Silva, J.V., Reidsma, P., Laborte, A.G. and Van Ittersum, M.K. 2017. Explaining rice yields and yield gaps inCentral Luzon, Philippines: An application of stochastic frontier analysis and crop modelling. European
Journal of Agronomy, 82, 223-241.
Tran, D.V. and Nguyen, N.V. 2006. The concept and implementation of precision farming and rice integrated
crop management systems for sustainable production in the twenty-first century. International RiceCommission Newsletter, 55, 91-102.

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Research article
erd

Effect of Farmers’ Attitude and Behavior on Farm
Succession in the Philippines
ELIZA C. AQUINO
Graduate School of Agriculture, Tokyo University of Agriculture, Tokyo, JapanHIROKI INAIZUMIFaculty of International Agriculture and Food Studies,Tokyo University of Agriculture, Tokyo, Japan

NINA N. SHIMOGUCHI*
Faculty of International Agriculture and Food Studies,Tokyo University of Agriculture, Tokyo, Japan
Email: n3nocon@nodai.ac.jp

SATOSHI SUZUKI
Division of Teacher, Curator, and Librarian Training Course
Tokyo University of Agriculture, Tokyo, Japan
Received 13 February 2020

Accepted 24 September 2021(*Corresponding Author)

Abstract Two of the major problems worldwide are the decreasing number of new farmers
and aging of existing ones. These problems correlate to the challenges of the increasing
demand on safe food and food production of the growing population. Decreased number of
new farmers can be associated with the perception of new generations towards agriculture as
most of them do not see farming as a lucrative profession. In addition, farming is also known
to be a back-breaking, underrated, and undervalued occupation which leads the current
farmers to think twice about handing-over their farm to their successors. In order to change
the discernment of the society towards farming and to boost the confidence of farmers tobequeath their farm to their children, this paper aimed to understand and interpret farmers’
attitude and behavior towards farm succession. Specifically, this clarified the farmers’ actual
situation on the ground, their attitude and behavior, and their family’s perception about
farming. Organic farmers in Laguna, Philippines, were interviewed and observed. Life
History Approach (focused on analyzing of the farmers’ lives to farm succession) and
Grounded Theory Approach (provided guidelines to identify categories and make links andestablish relationships between categories) were utilized. Results showed that farmers hadvaried perceptions in transferring knowledge and motivations to their successors. Upon being
acknowledged in the society, most of the farmers’ moral were uplifted. They displayed
positive attitude and outlook towards agriculture that were reflected through theirencouraging behavior to engage their children in farming. Their children were also proud of
their farmer-parents. In general, farm succession is one way to ensure agricultural
sustainability. In order to do so, situation of farmers on the real ground must be understood
through proper interpretation of their attitude and behavior that greatly affect farm
succession.
Keywords interpretation, attitude and behavior, farm succession, qualitative, GTA & LHA

INTRODUCTION
Increasing population is synonymous with the significant number of mouths to feed as the fooddemand also increases. This global problem demands agricultural sustainability to make sure that
there will be enough food for all. Agricultural sustainability will not be reached if there are fewer
new farmers and an increasing number of aging farmers.
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According to FAO (2019), the number of farmers decreased from 41.3% of the world’s
population in 1995 to 26.7% in 2016. In the Philippines, it decreased from 44.1% to 27.0% in 1995
and 2016, respectively. In addition, Saliot (2013) stated that the food security of the Philippines is at
risk, as millions of farmers and fishermen are also aging with an average age of 57 years old. In
Japan, one of the greatest factors limiting agricultural sustainability is the shortage of farmers due tothe lack of new farmers and the aging of existing farmers, with an average age of 67 years old(Muramoto et al., 2010).
Decreased number of new farmers may be associated with the low morale of farmers as new
generations do not see farming as a lucrative profession. In addition, farming is also known to be aback-breaking, underrated, and undervalued occupation, which leads the current farmers to think
twice about handing over their farm to their successors. As a parent who endured decades of hardshiptilling their land, living in poverty, and being degraded by society, they naturally want their children
to have better lives.
Understanding and interpreting farmers’ attitudes and behavior can be a possible way tocontinue farm succession. This study will give the researchers, private, and government institutions
the knowledge and understanding of what the farmers need and provide them with the needed
technology or innovation. Moreover, policymakers will also be able to make effective and efficient
policies and programs.
OBJECTIVE
To change the society's discernment towards farming and boost the confidence of farmers to bequeath
their farm to their children, this paper aimed to understand and interpret farmers' attitudes andbehavior towards farm succession. Specifically, this clarified the farmers' actual situation on the
ground, their attitude and behavior, and their family's perception about farming.
METHODOLOGYThis study is a qualitative research based on the interviews and observations of 17 farmers (doing
and did organic farming) and some of their family members in Laguna, Philippines, in August 2017,
March, July-September 2018, and July-September 2019. The farmers were selected using
Historically Structured Inviting (HSI) and purposive sampling, satisfying the appropriate sample andcase requirements. Consent from both parents and children regarding the interviews, observation andthe use of data concerning children below 18 years old were acquired. Furthermore, parents were
present during the interview.
Life History Approach (LHA), Grounded Theory Approach (GTA), and Trajectory Equifinality
Approach (TEA) were utilized. Following Sato et al (2016) TEA, Historically Structured Inviting(HSI) was used as a sampling method, and the Equifinality Points (EFP), and Obligatory Passage
Points (OPP) were set. LHA focused on the analysis of the lives of farmers in relation to farm
succession. Farmers were asked for their lives’ narratives, and these were contextualized, defined,
and explained how specific event affects farmers’ decisions over time (Hagemaster, 1992). As
adopted from Locke (2002) and Glaser (2001), GTA was used in data collection and categorization
as it provided guidelines to identify categories, make links, and establish relationships between
categories. Trajectory Equifinality Models (TEM) were generated to aid the discussion of LHA.
While GTA was used to uncover beliefs and meanings that underlie action and examines topics of
behavior from different angles to gain insight and deeper understanding of farm succession.
RESULTS AND DISCUSSION
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Different factors affect farm successions, such as farm’s profile (e.g., land size, accessibility,commodities grown) and farmer’s profile (e.g., age, educational attainment, farming experiences).
Table 1 shows that most of the farmers are from a farm family, but two of them admitted that even
they are from a farm family, they had zero background in farming when they first engaged inagriculture. In contrast, the 11 farmers assisted and were involved in their family farms and later took
over the farm. The remaining four farmers were motivated to do farming after learning theimportance of farming and organic agriculture (OA). Four out of 11 farmers from a farm-family arestill using their farming knowledge obtained from their farmer-parents, while seven of them utilizes
the information gained through their attendance to trainings. Those farmers that are not from thefarmer-family stated that they got their knowledge on farming from different trainings they attended.
Most of the farmers were motivated to engage, convert, or continue organic agriculture after
attending different trainings provided by their municipalities. It was also noted that 12 out of 17
farmers encourage their children to engage in farming. All of the farmers were motivated and adopted
specific technology or innovation on OA once in their farming career as some of the interviewed
farmers stopped OA, went back to conventional, or stopped farming.
Table 1 Distribution of farmers by family background, source of farming knowledge andexperiences, and engaging children in farming
No. of farmers
n=17• belongs to farm family or non-farm family• that learned their knowledge from family• attended trainings• motivated adopt/modify/ innovations learned• that are engaging their children in farming

From a farmer’s family
without
with farming
farmingexperiences
experiences
11
2
4
7
2
11
2
8
2

From a nonfarmer’sfamily
4
4
4
2

Total
17
4
13
17
12

Source: Field study in July-September 2019

The results showed that farmers had varied perceptions in transferring knowledge andmotivations to their successors. The most common reason that was noted is the safeness of OA tofarmers, consumers, and the environment as the farmer-parents want to make sure that their children
will be safe in doing farming. Some farmers started farming for their family consumption and chose
OA to feed their families with safe food. In time, most of them realized the importance of OA not
just for the farmers and consumers but also for the environment. Some also saw the possible
opportunity that OA can give them in terms of market and income.
Factors Affecting Morale and Confidence of Farmers
Low morale in farming, as it is known to be the underrated and undervalued occupation, especiallyin the Philippines, was noted as one of the factors why the younger generation does not want toengage in farming. In order to boost the confidence of farmers and change how the young generation
perceives farming as a career, farmers’ importance must be acknowledged in the society. In the
research area, it was observed that farmer tends to be motivated by other farmers, they are also
confident if farmers, students, teachers, hobbyist, and other actors in the society asked for their help
in terms of advice and other farming-related activities. They feel that their opinion matters,
motivating them to continue farming and do experiments on their farm. Some of them do OA for
their consumers’ sake. Upon being acknowledged in the society, most of the farmers’ morals were
uplifted. They displayed a positive attitude and outlook towards agriculture that were reflected
through their encouraging behavior to engage their children in farming.
These results responded to the United Nation's Sustainable Development Goals 2, 3, and 12.
Goal number 2 or zero hunger will be reached if yields will be increased and stabilized; goal number
3 or good health and well-being; and goal number 12 or responsible production and consumption
will be attained if current and future farmers will avoid the use of synthetic inputs and consumersⒸ ISERD

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will support them. If current and future organic farmers' morals continue to be boosted, thesesustainable goals will also be achieved.
Family Members’ Perception in Agriculture
Family perception plays a vital role in boosting the confidence of farmers. Their children were alsoproud of their farmer-parents. As per the in-depth interview, transcripts from the family members
were assessed and help in the understanding of the effects of engaging in OA on the farmer’s family.
Based on different transcripts, farmers gained positive change in terms of having a better family
relationship and gaining self-worth as the farmer can decide on his own and share his experiences
and knowledge with others, especially younger generations (Transcript 1 in table 2). Another noted
answer focused on the child’s personal feelings and preferences, as can be seen in Transcript 2 inTable 2. As a 4-year-old son, he requires the attention and affection of his parents, especially his
father that he rarely sees and remembers when his father was still working as a security guard.
Table 2 Transcripts from the farmers’ family members regarding the effect of farming totheir family
Farmers’ family members
Trans. 1- Wife of a farmer

Transcripts“Before, when he was working as a security guard, he usually arrived
very late when children were already sleeping. He was also leaving early
when his children were still sleeping. He does not even have time to talkand say hi to his children. However, now, it is better. He is his own boss,
he manages his own time, and he has time for us. Also, he is free to decide
on matters regarding his farm. He is always with us and can still provide
for the needs of the family. I also feel proud that students and other future
farmers are visiting our farms to learn and to experience farming.”

Trans. 2- Son of a farmer“I like it now. I can always see my Papa. He can play with me now. I
can also help him in his work (by weeding and watering plants)”

Trans. 3- Son of a farmer“I am proud of my mother. I also often do school gardening activities
similar to what she’s doing on our farm. I can confidently tell myclassmates that organic agriculture can be fun and easy if I do what mymom does.”Trans. 4- Daughter of a farmer“I am happy that my mother is doing better now. She also has more time
for us and can help us in school activities.”

Trans. 5- Son of a farmer“Mama is doing better for her customers; she loves farming; even if
her body tells her to stop, she will not.”Trans. 6- Grandson of a farmer“I want to help my Lola (grandmother) in doing activities on the farm,
it is fun, but I saw her getting sick because it is hard, so I keep telling my
Papa that we should help Lola”.

Source: Field study in July-September 2018

Table 2 also shows the interview conducted from a 12-year-old son of a farmer. The grade 6
student is a proud son. During interview, it was observed that the son was shy at first and when ask
about the effect of OA to his mother, he positively, and bravely answered that he is a proud son andkeeps applying what he learns from her mother to his school’s garden (Transcript 3). In addition, adaughter, 10 years old, grade 4 student eagerly answered the effect of OA to her mother (Transcript4), stating that she is happy for her mom. For these children, they value more the time allotted bytheir parents with them greatly matters as both parents are working. In addition to the family timethat leads to better family relationship, proud children also boost the morale and confidence of their
farmer parents.
A transcript from a son, 32 years old and a grandson, age 5 were also distinguished. The son
focused on how he sees his mother as a hardworking farmer to meet her goal to provide safe food forⒸ ISERD

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her consumer (transcript 5). The grandson's answer, on the other hand, was unique as he saw thehardship of farming (transcript 6) but his grandmother still enjoys it.
It can be concluded that based on the transcripts from the farmer’s family members there are
significant effects brought by farming aside from providing the needs for their family, farmers
particularly improved their family relationships. Moreover, farmers’ confidence and morale, wereboosted and these improvements were all connected to the positive outlook and support of theirfamily members.
Life History of Farmers Utilizing Trajectory Equifinality Method
To fully understand and interpret the attitude and behavior of farmers that greatly affect theirdecisions in farm activities, including farm succession, each of their life history was noted andanalyzed with the Trajectory Equifinality Model (TEM) as shown in Fig. 1. TEM is a methodology
for describing life within irreversible time which is composed of Bifurcation Point (BFP),
Equifinality point (EFP) and Trajectory or the life path (Sato, et al.,2013)

Fig. 1 Life history of the farmers using the Trajectory Equifinality Method (TEM) of
selected organic farmers in Laguna, Philippines
For this paper, the bifurcation points are the points in farmers’ lives that can leads to different
path. The equifinality points on the other hand, are the end point or the end-goal of the farmers’ farm
career such as sharing OA to the next generation and engaging them, going back to conventional, or
stopping farming. In addition, the decision points are the turning points on the farmers’ lives (learned
the importance of OA and faced problems) which affects their decision in meeting their equifinality
points. The obligatory passage point (learned OA) is a point which every farmer experienced.
The 17 farmers were grouped based on five categories based on their starting and equifinality
points. The first category has three (3) farmers who were from a family of farmers, two of them withno experience in farming and graduated college with a degree of BS Computer Engineering and a
Bachelor of Arts in English, both worked in private companies and retire early to engage in farming.
The three (3) farmers attended agricultural training at different point of their lives with different
reasons and motivations, learned the importance of OA, engaged in OA, and share OA information
to the next generation and persuading and encouraging younger generations in OA. They havedifferent life paths and choices that lead to different bifurcation points but started and ended with thesame starting and equifinality point.

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On the other hand, the second category comprises seven (7) farmers from the family of farmers,
with experiences in tending crops and livestock, assisting their parent family on their farm sincechildhood. Faced different problems and challenges during their farming life that lead to different
life paths, but at certain point of their lives, each of them learned the importance of OA and decided
to engage in OA and share it with the next generation.
One farmer belonging in this category chose to change his career from being an employee to be
his own boss as he also wants to spend more quality time with his children, as per the interview withhis wife, she stated that “he was preparing and leaving early for work, our children were all still
sleeping, he will be back late at night from work, and our children were already sleeping.” During
his childhood, even when he attended an agricultural high school, his father neglected his ideas to be
implemented on their farm. After attending OA training, he quit his job and started his own organic
farm and executed what he learned from the training and his past experiences. His learnings wereshared to his wife and children and later even to students, and other farmers. He also involves hischildren in farming by allowing them to do simple tasks like watering and weeding. In addition,
being unheard and disregarded during his childhood while helping in his father’s farm, he is now
making sure that his children can try and voice-out their thoughts while assisting him in their farm.
Farmers on the third category are the two farmers who are from a family of farmers, withexperiences in farming, they were doing farming, attended some trainings and learned the importanceof OA. Unfortunately, even though they know the importance of OA, they just decided to stop
farming when they faced problems while doing organic farming. According to the interview, bothhave problems managing their time as they were hired in a full-time job. For them, OA is very
laborious and time consuming, even they are aware of the health benefits of growing and consumingorganic produced, they chose to stop doing it and stated that if there will still be chance for them to
do it after their retirement, if their body can still do the farm activities, they might go back to farming.
Likewise, the fourth category involves a farmer who is also from a family of farmers. The
farmer’s spouse is also a farmer. Both experienced farming during childhood and later in life engagedin farming, they also attended training related to agriculture and learned the importance of OA, they
did OA and conventional, but after trying and experiencing the increased input in terms of labor, theygave up OA and go went to conventional farming. They stated that they tried their best in doing andmanaging OA, but regrettably, OA is not for them as it is too labor-intensive and requires too muchtime on the field.
Four farmers constituted the fifth category. They are the farmers who are from the families of
non-farmer, learned the importance of farming and/ or attended agriculture training, engaged infarming, learned the importance of OA, engaged in OA, and shared OA information to family
members and other actors in the community including the next generation.
These categories gave us a clear picture of the life history of farmers with the aid of TEM. It
also gave us background on how each point of farmer’s life affects their decision making in farm
activities and farm succession in terms of their attitude towards information sharing and engaging
younger generations in farming.
CONCLUSION
Farm succession is one way to ensure agricultural sustainability. Thus, the situation of farmers on
the real ground must be understood through proper interpretation of their attitude and behavior that
greatly affect farm succession. Common factors such as farm’s profile, farmers’ perceptions intransferring knowledge, and motivations related to farm successors are essential. Different farmers
can also be understood through the utilization of TEM. TEM assisted the researchers see eachfarmer's life history and how each point of life affects their decision to continue and hand over theirfarms to their successors.
ACKNOWLEDGEMENTSⒸ ISERD

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The researchers would like to acknowledge the warm and sincere cooperation of the organic farmers
and their families in Laguna, Philippines, and Tokyo University of Agriculture, particularly the
NODAI Research Institute and the NODAI Education Support Association for partial financial
support.
REFERENCES
Food and Agriculture Organization (FAO). 2019. FAOSTAT database. Food and Agriculture Organization of
the United Nations, Retrieved from http://www.fao.org/faostat/en/#country/171
Glaser, B. 2001. The grounded theory perspective: Conceptualization contrasted with description. Mill Valley,
CA, Sociology Press, 232 pp.
Hagemaster, J.N. 1992. Life history: A qualitative method of research. J. Adv. Nursing, 17 (9), 1122-1128,
Retrieved from https://doi.org/10.1111/j.1365-2648.1992.tb02047
Locke, K. 2002. The grounded theory approach to qualitative research. In Drasgow, F. and Schmitt, N. (eds.),
Measuring and Analyzing Behavior in Organizations, Advances in Measurement and Data Analysis, San
Francisco, CA. Jossey-Bass, 17-43.
Muramoto, J., Hidaka, K. and Mineta, T. 2010. Japan: Finding opportunities in the current crisis. In Gliessman,S. (ed.), The Conversion to Sustainable Agriculture: Principles, Process, and Practices, CRC Press, Taylor
and Francis Group, LLC, USA. 273-301.
Saliot, A. 2013. Filipino farmers - a dying breed? IRIN News of the United Nations Office, Retrived fromhttp://www.irinnews.org/feature/2013/02/26/filipino-farmers-dying-breed
Sato, T., Mori, N. and Valsiner, J. 2016. Making of the future: The trajectory equifinality approach in cultural
psychology. Info. Age Pub. Inc. NC, USA. 220.
Sato, T., Yasuda, Y., Kanzaki, M. and Valsiner, J. 2013. From describing to reconstructing life trajectories:
How the TEA (Trajectory Equifinality Approach) explicates context-dependent human phenomena.
Seminars in Aalborg: Inauguration of the Niels Bohr Professorship.

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Research article
erd

The Challenges of Agribusiness Training on Livestock
Farmers in Namibia
NORAH LYDIA NGATJIZEKO
Graduate School of Agriculture, Tokyo University of Agriculture, Tokyo, JapanHIROKI INAIZUMIFaculty of International Agriculture and Food Studies,Tokyo University of Agriculture, Tokyo, Japan

NINA N. SHIMOGUCHI*
Faculty of International Agriculture and Food Studies,Tokyo University of Agriculture, Tokyo, Japan
Email: n3nocon@nodai.ac.jp
Received 13 February 2020

Accepted 24 September 2021(*Corresponding Author)

Abstract Although contributing only less than five percent to GDP, agriculture remains oneof the top employers in Namibia, with livestock production being the top earner. The national
agriculture policy has highlighted the lack of capacity as one of the constraints in the industry.
Both private and public training institutions in Namibia have had numerous training such asrangeland management, farm infrastructure, and animal health, and seldom focus on the
postproduction activities such as markets and marketing. This study aimed to assess thechallenges of agribusiness training in Namibia as identified by livestock farmers. An in-depth
literature review on Namibian agribusiness training looking at national policies that address
agricultural training and farm survey using a structured questionnaire was conducted. The 33
respondents were from three regions of Namibia: Erongo, Omaheke and Otjozondjupa
regions, and three land tenures: communal, commercial, and resettlement farms. Natural
phenomena including drought and lack of water were crucial challenges identified bylivestock farmers. Other challenges such as access to markets, few buyers in the market, andlack of coordination were among the critical agribusiness factors highlighted by most
farmers. Commercial farmers were the main market of communal livestock which areconsidered of low quality. Communal livestock farmers lamented the lack of market options
available. Thus, Namibia needs to implement a training policy that captures aspects oflivestock marketing that integrates various levels of farmers from communal level to thecommercial level.
Keywords agribusiness training, southern communal area, communal farmer,
resettlement farmers

INTRODUCTION
Namibia is a vast, middle-income developing country in Southern Africa. Located between twodeserts, the country is the driest south of the Sahel, characterized by sporadic rainfall and frequent
drought. Despite these factors, agriculture is a major industry in Namibia. Agriculture uses moreland than any other activity (approx. 78% of the country is farmland), and nearly 1.2 million people(roughly 206,000 households) live on farms and/or in rural areas. Agriculture is the second main
source of income for many households in Namibia (Namibia Statistics Agency, 2013) and remains
one of the top employers in the country in both the formal and informal sectors (Namibia Statistics
Agency, 2015). The following characterize agriculture: small scale mixed farming, cattle ranching,small stock farming, commercial crop production and other intensive agriculture (Mendelsohn, 2006).
Cattle ranching is Namibian’s main agricultural production sector, with an estimated value of N$ 900Ⓒ ISERD

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million (approx. 56 million USD), 44.4% of which accounted for weaner exports (Enkono et al.,2013). Livestock production includes cattle, sheep, goats, and pigs.
Despite all these factors, agricultural contribution to GDP has been less than 5% (MAWF,
2017) (Fig 1). Several factors attributed to this include the country’s well-diversified economy andhigh production by other sectors. The specific challenges of agriculture however are the low
agricultural capacity because of aridity and poor soils and the low demand within Namibia andelsewhere for Namibian products due to the lack of market development in most communal areas
and the relatively low value-added through local processing (MAWF, 2015).

Fig. 1 GDP by Primary and Secondary Sectors at Current Prices – Percentage Contribution
Source: Ministry of Agriculture Water and Forestry, 2017

Namibian agriculture is agrarian in nature, with many households depending on their crops
and livestock for part of or all their income and/or nutritional needs. A key distinctive factor of thesector is its dualistic in nature with a highly developed, technology-based, and productive
commercial sector and a subsistence sector characterized by low productivity dependent on manuallabor and use of traditional methods of production often referred to as communal farming (Namibia
Training Authority, 2013). The communal land system is a remnant of the duality applied to land
tenure by the apartheid pre-independence system. Black communities had to stay in small areas, often
away from cities and share resources such as land and water. Traditional livestock rearing in Namibia
is characterized by low productivity due to low calving rates, high mortality, and low off-take rates
for meat and milk (JICA, 2017). Historically commercial farmers benefitted considerable support
from the government through direct assistance – such as subsidies, extension, and veterinary services– and indirectly because of the development of transport, marketing, and other services (Schmokel1985).
At independence, studies found that farmers in the communal areas often lacked adequate
agribusiness skills to make them competitive in modern agriculture (Ministry of Agriculture, Water
and Forestry, 2015).
In its 2013 inaugural report, the Namibian Training Authority (NTA), the country’s regulator
for vocational education and training, developed the agricultural sector skills plan (SSP) to provide
skills the needed by sector (Namibia Training Authority, 2013). This SSP set the blueprint fortraining in agriculture. This SSP focused on the demand for vocationally skilled labor, specificallyon the primary agricultural sector, and excluded occupations of a generic and general nature which
do not relate specifically to the sector. This SSP found that reliable data on qualification and skill
profiles in the agricultural sector remains scarce as most studies and surveys have focused on thecommercial sector (Namibia Training Authority, 2013). This is supported by studies stating thattraining in developing countries often focuses on production without taking cognizance of postproduction activities (Mabeya et al., 2010). Hence, capacity-building exercises also often target
commercial producers and professionals leading to a skills shortage in rural (communal) areas.
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OBJECTIVE
Due to the highlighted factors, the objective of this study is to identify the challenges farmers facegiven the current agribusiness training offered in the country. Further, this study looks at findings
from farmers in all three-land tenures in the country.
METHODOLOGY
Study Area
This study was conducted in three regions within the Southern Communal Area: Erongo, Omaheke,
and Otjozondjupa, where a combination of livestock farming takes place. A veterinary cordon fence
was erected in 1896 under German colonial rule to contain a Rinderpest outbreak, resulting in the
splitting of Namibia into two livestock farming zones: Northern and Southern Communal Areas.
Method of the Study
This study utilized both qualitative and quantitative data. Secondary data was sourced frompublications from line ministries involved in agriculture, which are the Ministry of Agriculture,
Water and Forestry, the Ministry of Land Reform, and the Ministry of Industrialization and Trade,
as well as documents from parastatals (refers to government-owned agencies): Meat-Board of
Namibia, MeatCo (Meat Company) Namibia and the Namibia Statistics Agency. Primary data werecollected from a structured questionnaire administered to livestock farmers from all land tenures (e.g.,communal, commercial, and resettlement farmers) in August 2019. A total of 33 livestock farmers
were surveyed through convenient sampling. The questionnaire aimed to collect farmers' views on
agribusiness training in the country, including what they believed were the challenges in agriculture,training, and livestock markets. It should be noted that this study is essentially a qualitative literature
review, that not only considers findings from the three regions but relies on historical findings andsupporting studies on Agricultural training in Namibia.
RESULTS AND DISCUSSION
Training Access and Content
Prior to the inaugural SSP report in 2013, Namibia conducted baseline surveys on the impact ofextension services in all regions. These surveys tried to address whether impact can be proven andto whom this impact is felt (Ministry of Agriculture, Water and Rural Development, 2003). Thesesurveys looked at advisory services, information, communication, and farmer training, and can beconsidered the most significant for looking at communal areas as extension services address all
farmers. These surveys are also critical for assessing training access in terms of government
extension services which are offered at no cost but vary in frequency and location (distance fromtraining area), and these can be seen as challenges.
The most significant research on training access and content for Namibia in recent years is the
SSP, which aimed at addressing all Technical, Vocational Education and Training (TVET) in the
country by looking at factors affecting training and all the key role players. This SSP was a
consultative process, to match demand and supply of Agricultural Technical and Vocational
Education and Training (ATVET), the skills needed mainly include production side (e.g., anatomy
and physiology, farm production). Farm management, another sub-category of the trainings,
includes business planning and entrepreneurial skills, marketing skills, record keeping andadministration, financial management skills, people management and management as well astransport and stores management (Namibia Training Authority, 2013). These are the skills considered
to scale up farmers entrepreneurship (Schulleri, 2013). According to the TVET studies, the demand
for training is high and diverse but providers are few thus there is a need to prioritize on the trainingⒸ ISERD

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needs. It is important to note that “agribusiness” is rarely explicitly mentioned in most documents,and often “agricultural training” and “marketing” and most other “finance” related terminology are
the terms used to capture these critical skills.
Assessment of ATVET provision found numerous challenges including incapacity of trainers,
limited training institutions, and inadequacy of practical training facilities and equipment. The
government through the NTA has agreed to adopt the Competency Based Education and Training(CBET) approach to vocational training which places a high demand on the ability of the training
provider to provide practical training opportunities wherein trainees can develop practice anddemonstrate competence very few institutions currently can offer.
Farmer-Respondents and Training
Respondent profiling was done in terms of age, gender, education level, occupation sector andmonthly income. Majority of the 33 farmer-respondents were male (72.7%) and were between theages of 50-59 (36.4%), closely followed by 60-69 age group (33.3%). The education level for morethan 50% of farmer-respondents was undergraduate degree and post-graduate degree levels, with30.3% and 27.3 % respectively. Most of the farmer-respondents were full time employees in public
and private sector with 18.2 and 45.4% respectively. Most of the surveyed farmers had over 21 yearsof farming experience, many of whom consider themselves communal farmers. Table 1 shows thedetailed results of the farmer-respondents’ socio-economic profile.
Table 1 Socio-economic profile of farmer-respondents (n=33)
Socio-economic
characteristic
AgeLess than 40 yr. old
41-50 yr. old
51-60 yr. old
61-70 yr. oldAbove 70 yr. old
GenderMale
FemaleFrequency

Percentage

3
6
12
11
1

9.1
18.2
36.4
33.3
3.0

24
6

72.7
27.3

25
8

75.8
24.2

9
10
4
10

27.3
30.3
12.1
30.3

21
5
7

63.6
15.2
21.2

Marital Status
MarriedSingleEducation
Postgraduate
Undergraduate
Diploma
Other
Occupation
Employed
Self-employedPensioner

Socio-economic
characteristic
Annual Income
50,000 N$ and less
50,001-100,000
100,001-300,000
300,001-500,000
500,001-above
Household size
1-5 persons
6-10 persons
11 persons and more
Farming experience
1-5 years
6-10 years
11-15 years
16-20 years
21 years and above
Type of Farming
Communal
Commercial
Resettled

Frequency

Percentage

3
8
7
6
9

9.1
24.2
21.2
18.2
27.3

18
14
1

54.5
42.4
3.0

1
8
4
6
14

3.0
24.2
12.1
18.2
42.4

16
12
5

48.5
36.4
15.2

Source Field Survey, August 2019

Out of the 33 farmers surveyed, 25 had attended some form of training as seen in Table 2, yet
two were aware of training and opted not to attend any, the remaining six were unaware of any
available training and therefore had not attended any. Of the trained farmers, 12 farmer-respondents
attended training identified by the farmers’ organization or ministry involved. The training institution
mostly identified was government extension services provided by the ministry. Government
extension training is offered on an ongoing basis through advice and farmer support services. This
type of training is mostly done in the field by the extension staff and is usually not of a structured
nature and is not standardized (Ministry of Agriculture Water and Rural Development, 2003 andⒸ ISERD

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Namibia Training Authority, 2013). Some attended training with MeatCo which provides training
mainly to livestock farmers. Agribank of Namibia also offers training through its Agri Advisory
Services, which offers various content packages, from financial to rangeland management, howeverthese are often for those in urban areas or those that can attend farm excursions which is notnecessarily available to all farmers. Farmers also attended training with Agrifutura, although they
could not provide the training content, the institution offers training and farm visit (site-led) training
on livestock management; livestock marketing; farm finances; animal health; rangeland and pasturemanagement. Few farmers mentioned attending training provided by Agra ProVision. This isperhaps the costliest of the ATVET institutions in Namibia, its courses are tailormade and includes
mentoring. Their course content ranges across the entire plethora of farming and management. The
SSP has stated that Agra ProVision is one of the few institutions with the capacity to offer adequate
training, its biggest constraint is resources to pay for such services.
Table 2 Awareness and participation to training
Characteristic
Aware of training, attended training
Aware of training, did not attend training
Unaware of training, did not attend

Frequency (n=33)
25
2
6

Source: Field Survey, August 2019

Table 3 Agricultural challenges identified by number and tenurial type of farmers
Challenges identified
Environment-related
Bush Encroachment
Drought
Increase in number of wildlife
Lack of grazing
Water shortages
Livestock technology
Animal health
Quality of livestockMarket-related
Few auctions/uncoordinated auctions
Few buyers/monopolies buyers
High cost of transport
Low market accessNo direct marketing channels
Poor prices
Policy environment
Few regional farmers’ organizations
High interest loans
High land prices
Lack of capacity
Lack of information
Low government support
Permit bureaucracy

Commercial(n=12)

Communal(n=16)

Resettlement
(n=5)

0
1
0
0
0

0
1
1
1
1

1
1
1
1
1

1
1

1
0

1
0

1
1
1
0
1
1

1
1
1
1
1
1

0
0
0
0
0
1

0
1
1
1
1
1
0

1
0
0
1
1
0
0

0
0
0
1
1
0
1

Source: field survey August 2019
Note: 1 implies that farmers agree this is a challenge and 0 implies farmers did not agree that this is a challenge. For
each challenge all farmers from that tenure agreed the factor is a challenge.

Although the available trainings ranged from basic livestock management to range management(Mabeya et al., 2010), it is evident that training is often production-oriented leaving a capacity gap
in post-production activity. Moreover, this study found that livestock farmers, even those receiving
some form of training experienced various challenges (Table 3).
Environment related ChallengesⒸ ISERD

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All farmers identified drought as being a major threat to livestock agriculture in Namibia, theMinistry of Agriculture, Water and Forestry (2015) highlighted this as one of Namibia’s major
agricultural constraints as the country has had a severe drought over consecutive periods since 2013.
This has worsened water shortages, especially in communal areas where farmers share resources
including land and water with each other and the growing amount of wildlife. Farmers in communal
areas are increasingly facing challenges of reducing grazing pastures as more areas are being fenced
off by well to do families, leaving less land available for open grazing (Togarepi et al., 2016).
Livestock grazes on open access commonage pastures and woodlands. The practice of transhumancehas declined in recent years. Farmers also alluded the high cost of land in Namibia.
Livestock Technology
Animal health was identified by all farmers as a common problem which explains why one of themain trainings is on livestock health. Musaba (2011) found that increased technology adoption is
only possible through capacity development, his findings show higher adoption rates for farmers
located closer to extension officials. This clearly shows the importance of extension services and theneed for frequency of training for livestock farmers. The SSP also identified 40 areas of skills
demanded in agriculture through consultation with farmers and other key stakeholders (Namibia
Training Authority, 2013), these skills were ranked from 5 to 1 on importance. Those skills pertaining
to livestock technology ranked between 3 to 5 which is high ranking.
Market Challenges
The low prices, small number of buyers, and few uncoordinated auctions point to livestock market
challenges. The Namibian market is small due to the country’s low population with the only lucrative
markets being in urban areas. Many farmers stressed how difficult it was to make a profit in livestock
farming due to numerous cost constraints including the price of stock feed, high cost of transportation
to markets and few auctions and buyers available in the country. Most farms are located far frommarkets thus prices of farm products are often also high to cover variable costs, including transport.
Similarly, perishables, like meat and meat products require costly cooling or other special storage
facilities, which are not readily available in rural areas. Farmers predominantly sell to a single buyer
or speculator, a situation which has created monopolies within the sector, as one commercial farmer
stated, “Farmers have few options but to sell to a middleman,” conveying that they are often pricetakers.
Policy Environment
One of the key factors that play a major role in livestock market participation by farmers has beenfound to be “business orientation by the smallholder livestock farmers” (Zuwarimwe and Mbaai2015) which highlights a need for capacity in the industry as identified by all the farmer-respondents.
Another common policy problem was the lack of information among or within the agricultural sector.
Agricultural policy decisions are made, without involvement of the primary recipients – the farmers(Kumba, 2003).
CONCLUSION AND RECOMMENDATIONS
Farmer-respondents clearly identified agricultural sector challenges in the country, including theirpersonal farming challenges. Literature review of the SSP also highlighted challenges of the training.
Together these sketch a foundational analysis where the two can be used to further study training
needs and agricultural challenges’ convergence to improve the sector. It was found that the livestock
production, although dominating the Namibian agriculture sector, is faced with a myriad ofchallenges, some, such as drought and climate variability are beyond anyone’s control. However,Ⓒ ISERD

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most of the training offered to farmers by institutions, including government extension, is production
centered, yet the measures to integrate farmers into greater markets are very few. Farmers need to begiven adequate training on how to market their livestock independently. Farmer capacity
development cannot be the sole responsibility of the government; the private sector also needs to be
involved. Farmers need to be equipped with the necessary skills to cope with ever-changing
environments and operate their farms more efficiently. To enhance livestock productivity in ruralcommunities, better farm management practices should be adopted.
ACKNOWLEDGEMENTS
The researchers would like to acknowledge the sincere cooperation of the surveyed livestock farmers
in Namibia, and Tokyo University of Agriculture particularly the NODAI Research Institute and the
NODAI Education Support Association for partial financial support.
REFERENCES
Enkono, S.G., Kalundu, S.K. and Thomas, B. 2013. Analysis of factors influencing cattle off-take rate andmarketing in Ndiyona constituency of Kavango region, Namibia. Journal of Agricultural Extension and
Rural Development, 5 (9), 201-206.
JICA. 2017. The Republic of Namibia Northern crop and livestock development master plan. Final Report,
Volume 1. Windhoek JICA.
Kumba, F. 2003. Farmer participation in agricultural research and extension service in Namibia. Journal ofInternational Agricultural and Extension Education, 10 (3), 47-55, Retrived from 10.5191/jiaee.2003.
10306.
Mabeya, E., Christy, R.D. and Bandama, M. 2010. The current state of agribusiness education and training in
Africa. Joint 3rd African Association of Economists (AAAE) and 48th Agricultural Economists Associationof South Africa (AEASA) Conference, Cape Town, South Africa. September 19-23.
Mendelsohn, J. 2006. Farming systems in Namibia. Windhoek, Namibia, Namibia National Farmers Union.
Ministry of Agriculture, Water and Forestry. 2015. Namibia agriculture policy. Windhoek, Namibia,
Government of the Republic of Namibia.
Ministry of Agriculture, Water and Forestry. 2017. Agricultural statistics bulletin 2010-2015. Windhoek,
Namibia, Government of the Republic of Namibia.
Ministry of Agriculture, Water and Rural Development. 2003. Baseline survey of the impact of agriculturalextension services in the Omaheke Region. Government of the Republic of Namibia.
Musaba, E.C. 2011. Analysis of factors influencing adoption of cattle management technologies by communal
farmers in Northern Namibia. Livestock Research for Rural Development, 22 (6), Retrieved from http://
www.lrrd.org/lrrd22/6/musa22104.htm
Namibia Statistics Agency. 2013. Namibia labour force survey. Windhoek, Namibia, Government of the
Republic of Namibia.
Namibia Statistics Agency. 2015. Namibia census of agriculture: Commercial, leasehold and resettlement
farms 2013/2014. Windhoek, Namibia, Government of the Republic of Namibia.
Namibia Training Authority. 2013. Sector skills plan - Agricultural sector of Namibia (2013 -2017). Final
Report, Government of the Republic of Namibia.
Schulleri, F. 2013. Promotion of technical vocational education and training (TVET) for the agricultural sectorin Africa. Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, Retrieved from https://www.
academia.edu/31791983/Promotion_of_Technical_Vocational_Education_and_Training_TVET_for_the_
Agricultural_Sector_ATVET_in_Africa_A_Review_of_best_Practises_on_ATVET_in_Africa_Case_Stu
dies_of_Ethiopia_Benin_Namibia_and_Sierra_Leone_Final_Report
Schmokel, W.W. 1985. The myth of the white farmer: Commercial agriculture in Namibia 1900-1983. The
International Journal of African Historical Studies, 18 (1), 93-108.
Togarepi, C., Thomas, B. and Kankono, M. 2016. Cattle marketing constraints and opportunities in northcentral communal areas of Namibia, Ohangwena Region. Livestock Research for Rural Development,
Volume 28, Article #132, Retrieved from http://www.lrrd.org/lrrd28/7/toga28132.html
Zuwarimwe, J. and Mbaai, S.M. 2015. Factors influencing smallholder farmers’ decisions to participate inlivestock markets in Namibia. Journal of Development and Agricultural Economics, 7 (7), Retrieved fromⒸ ISERD

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10.5897/ JDAE2014.0562.

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Research article
erd

Visitor Perception and Economic Value Estimation of
Mekarsari Fruit Garden as Agritourism Destination inIndonesia
RAMADHINA P. INDRASWARI
Graduate School of Agriculture, Tokyo University of Agriculture, Japan

KENJI OKUBO*
Faculty of International Agriculture and Food Studies, Tokyo University of Agriculture, Japan
Email: kuboken@nodai.ac.jp

NINA N. SHIMOGUCHI
Faculty of International Agriculture and Food Studies, Tokyo University of Agriculture, Japan
Received 25 February 2020

Accepted 24 September 2021(*Corresponding Author)

Abstract With abundant natural and cultural resources, Indonesia has great potential in the
tourism sector significantly contributing to GDP. To achieve its long-term benefits, there isa need to address tourism development, focusing mainly on how to create various types of
tourism combined with education and the environment, such as agritourism. Mekarsari Fruit
Garden (MFG) is Indonesia’s largest agritourism destination and education, research, andtraining center for horticultural plant germplasm. Although MFG experienced a 70% drastic
decrease in visitors in 2013, visitors started to increase in 2014. However, MFG has notreached the same number of visitors as its peak years. This study aimed to determine visitor
perception and agritourism economic value of MFG in Bogor Regency, West Java, towards
finding sustainable and innovative ways to increase visitors and expand the business.
Specifically, this study aimed to identify visitor characteristics and their perception of MFG
using factor analysis, determine the frequency of visits and economic value using the travel
cost method, and formulate the sustainable development plan for MFG. A questionnaire
survey of 321 visitor-respondents and key-informant interviews of MFG executives were also
conducted. Factor analysis on visitor perception identified three factors: (1) location,
facilities, and agritourism operation characteristics, (2) agritourism attractivenesscharacteristics, and (3) agritourism support characteristics. Moreover, the travel cost method
revealed that MFG had a high economic value amounting to Rp 107 billion per year. As arecommendation, MFG should continue its operations and improve its facilities and services
offered due to prevailing high economic value and the willingness of its visitors to pay more,in addition to its significant role as the preservation and education center of tropicalhorticulture in Indonesia.
Keywords agritourism, factor analysis, travel cost method

INTRODUCTION
As a tropical country with abundant natural and cultural resources, Indonesia has great potential in
the tourism sector, significantly contributing to GDP. World Travel and Tourism Council (2018)
reported that travel and tourism generated Rp 787,100 billion (5.8% of GDP) and created 12.2 million
jobs (10% of total employment) in 2017. The World Tourism Organization (WTO) refers to theeconomic importance of tourism for future growth, employment, and development (WTO, 2003).
The Indonesian tourism sector is one of the sectors with a positive revenue earning, based on thecontribution of foreign tourists and domestic tourists spending generated 58.7% of direct travel andtourism GDP in 2017 compared with 41.3% for foreign visitors (World Travel and Tourism Council,
2018).

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Along with the increasing public interest in tourism, the tourism sector could provide long-term
benefits if the management carried out sustainable and environmentally friendly initiatives (OECD,2020). Therefore, there is a need to address the development of the tourism sector, focusing mainly
on creating various types of tourism combined with education and the environment, such as
agritourism. There are many definitions of agritourism and many agriculture-related tourism that are
similar to agritourism. For example, agritourism is identical to "farm tourism" (Busby and Rendle,
2000; Getz and Carlsen, 2000). Agritourism and rural tourism are not the same. Agritourism may
also be seen as a segment within rural tourism (Roberts and Hall, 2001; Wilson et al., 2001). Rural
tourism, agritourism, and active tourism are directly connected to rural areas (Hegarty andPrzezborska, 2005). Agritourism refers to commercial enterprises offering festivals and educational
events related to agricultural production and processing through tourism. These enterprises attract
visitors onto a farm, ranch, or other agricultural business to entertain and educate the visitors andgenerate income for the farm, ranch, or business owner (McGehee and Kim, 2004; The National
Agricultural Law Center, 2018). Thus, opportunities for agritourism development offer the
tranquility and natural atmosphere of an agricultural area to attract many tourists. Integrating
agriculture (agri-industry) and tourism in a particular undeveloped region's economic development
planning can be considered an alternative (Satriawan, 2005).
Located in Bogor Regency, West Java Province, Mekarsari Fruit Garden (MFG) has been thevenue to cultivate, preserve and showcase Indonesian tropical horticulture since 1995. However,
MFG has experienced a drastic decrease in the number of visitors. From the peak year at 1.6 million
visitors in 2008, the number of visitors has decreased ever since. Due to the global crisis, MFG also
experienced a drastic 70% decrease in visitors in 2012 and 2013. Although the MFG manager had atarget to attract 1 million visitors in 2014, MFG has had around 200,000 visitors per year since 2016
(Mekarsari Fruit Garden, 2018), conveying that this is the most crucial issue to be addressed
immediately.
OBJECTIVESThis study aimed to identify characteristics of visitors and their perception of MFG using factor
analysis, determine the frequency of visits and economic value in MFG using the travel cost method,and formulate the sustainable development plan for MFG.
METHODOLOGYThis study utilized primary data from a questionnaire survey, key-informant interviews, and direct
observation in August 2018, with a preliminary survey in February 2018. There was a total of 321
domestic tourist respondents.
Factor Analysis
Factor Analysis (FA) was utilized to determine visitors’ perception towards MFG. The Travel Cost
Method (TCM) was used to estimate the economic value and development of MFG tourist activities.
Principal Component Analysis (PCA) and FA are statistical techniques applied by researchers when
there is a need to find which variables are related to one another. Variables correlate with each otherbut are independent with other subsets, a combination of variables in the factor. Factors reflect theunderlying process that correlates with variables (Umar, 2009).
Travel Cost Method
Travel Cost Method is used for calculating the economic values of environmental goods or services.
It is mainly applied for determining the economics of recreation. It can also serve as a basis forevaluating how an increase in entrance fees will affect the number of visitors. Willingness to pay fora site visit is thus estimated based on the number of trips they make at the different travel costs. ThisⒸ ISERD

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is called a revealed preference technique because it ‘reveals’the willingness to pay based on the
consumption behavior of visitors (Healy et al., 2013).
Individual TCM is the best tool to estimate the value of the recreational costs incurred by thevisitors to visit the place. Thus, an increase in travel costs is expected to decrease the number of visitsby the visitors. Researchers use this inverse relationship between travel cost and the number of visits
to map/design a travel demand function of the place of interest. Then from the demand function, theconsumer surplus is calculated, representing the recreational value of the place of interest (Alam etal., 2017).
RESULTS AND DISCUSSIONSFA revealed that visitors' perceptions on the facilities are essential to make MFG one of the best
examples of agritourism in Indonesia. The results of FA processing and Promax rotation are shownin Table 1.
Table 1 The result of factor analysis of visitors' perception
Access to location
Security
Tourism object management
Can eat and pick the fruit directly
Educational activities
Farm tour
Facilities and infrastructure
Support local economy
Petting zoo
Location hygiene
Trash canSpend time with family
Experience
Family atmosphereFresh fruit
Quality
Price
Support local agriculture
Convenience
Learn or be taught how fruits is produced
Natural panorama
Souvenir kiosk
ToiletRestaurant
Proportion var
Cumulative var
Sources: Field survey, 2018

Factor 1
0.892
0.859
0.775
0.696
0.670
0.562
0.542
0.533
0.530
0.521
0.463
-0.1930.132-0.136
0.383
0.270
0.304
0.367
0.404
0.458
0.205
0.030
0.404
0.147
0.244
0.244

Factor 2-0.197
0.083
0.121
0.370
0.164
0.190
0.062
0.433
0.253
0.114
0.139
1.028
0.934
0.894
0.720
0.668
0.586
0.519
0.507
0.480
0.468
0.088
-0.707
0.259
0.235
0.479

Factor 3
0.207
0.045
0.093
-0.092
0.176
0.270
0.421
0.035
0.203
0.357
0.416
0.129
-0.1170.211-0.133
0.074
0.110
0.128
0.118
0.086
0.253
0.904
0.659
0.613
0.105
0.584

Average
3.794
3.829
3.838
3.844
3.850
3.838
3.841
3.841
3.841
3.835
3.847
3.885
3.879
3.866
3.860
3.860
3.847
3.860
3.841
3.850
3.879
3.841
3.841
3.835

SD
0.501
0.466
0.480
0.468
0.477
0.473
0.477
0.477
0.477
0.469
0.466
0.496
0.482
0.498
0.450
0.457
0.452
0.464
0.464
0.450
0.507
0.503
0.503
0.488

Factor 1 comprises the visitor's perception of the "Location, Facilities and Agritourism
Operation Characteristics." Factor 1 was the main reason why visitors chose to visit MFG rather thanother tourist attractions. Specifically, "Can eat and pick the fruit directly from the tree" was the main
reason that made MFG distinct from other tourist attractions and the main attraction of MFG. Factor
2 is about "Agritourism Attractive Characteristic." Factor 2 revealed that visitors could enjoy natural
panoramas, spend time with their family and friends, and have a family atmosphere that cannot befound in other tourist attractions. Factor 3 is about "Agritourism Support Characteristics." Factor 3
can be considered the additional factor/reason for traveling to MFG, conveying the importance ofimproving its restaurants or souvenirs kiosk to attract visitors further. Improvements may include
menu development for restaurants related to increasing usage of fresh fruit ingredients, facility
renovation, the introduction of new souvenirs, and branch establishment of restaurants or souvenir
kiosks outside MFG or nearby areas. It would be more effective if these improvements wereInstagram or SNS-worthy.
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The recreation demand model at MFG was carried out to estimate the effect of several socioeconomic variables on the frequency of tourist visits using a zero-truncated Poisson regression model.
Table 2 shows the results of Poisson regression analysis with a p-value of less than 0.05, conveyingthat the opportunity to reject the equation model was minimal and the occurrence of errors was veryminimal. The regression coefficients that influence the frequency of visits (Y) were travel cost (X1),
transportation by bus (D3), and accompany with friends (D4) at 1% level of significance, while
public transportation (D1), accompany by family (D4), and no accompany (D6) at 0.1% level ofsignificance. The zero-truncated Poisson regression analysis results indicated that five variables
influence the chances of the average number of MFG visits.
Table 2 Result of Poisson regression analysis
Coefficients
Constant-0.166
Travel cost
-1.909 x 10-6
Income/month (IDR)-1.193 x 10-8
Transport by public (Yes:1, No:0)
0.840
Transport by car (Yes:1, No:0)-0.167
Transport by bus (Yes:1, No:0)
1.039
With family (Yes:1, No:0)
1.325
With friends (Yes:1, No:0)
1.163
No accompany (Yes:1, No:0)
1.345
Marital status_NM (Yes:1, No:0)-0.139
Smpl
311
Log L
-404.577
Source: Field survey, 2018. Note. Signif codes: 0.001 (**), 0.01 (*)

Z value-0.346-2.456-0.5203.227-1.159
2.143
3.011
2.562
2.832
-1.095

P value
0.729
0.014
0.603
0.001
0.246
0.032
0.003
0.010
0.005
0.273

*
**
*
**
*
**

a. Travel Cost
Based on the results of analysis using Poisson regression, it is known that the probability value of
actual travel costs at the 1% level conveys that the travel costs significantly affect the number ofvisitors. The coefficient value, which has a negative sign (-1.909b×10-6), indicates that the higher
the value of travel costs will further reduce the number of goods consumed. This negative sign result
had similarities with Khoshakhlagh et al. (2013). Therefore, travel cost seemed to be a significant
factor in the decision to carry out recreational activities.
b. Public Transportation
The variable public transportation explains how much the availability of public transportation affects
the frequency of visitor visits. Results showed that the variable had a positive coefficient with 0.1%
level of significance, conveying that the more a person visits MFG by public transportation, thehigher the chances of visiting again in the future.
c. Transportation by Bus
Most visitors (group of friends or family members of more than ten people) come to MFG by bus(public transportation). Bus transportation is considered more effective to bring many visitors orbring visitors who come in a group. Results showed that the variable had a positive coefficient witha 1% level of significance, conveying that the more a person visits MFG in a group using bus
transportation, the higher the chances of visiting again in the future.
d. Accompany with Family
Accompany with family had a positive coefficient with a 0.1% level of significance, conveying thatthe more a person visits MFG with their family, the higher the chances of visiting again in the future.
Results showed that 54% of visitors visited MFG together with their families.
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e. Accompany with Friends
Visiting with friends had a positive coefficient with 1% level of significance, conveying that themore a person visits MFG together with their friends, the higher the chances of visiting again in the
future.
f. No Accompany/Alone
Variables of visiting to MFG alone had a positive coefficient with 0.1% level of significance,
conveying that the more a person visit MFG alone, the higher the chances of visiting again in the
future.
Determination of the total economic value of MFG is based on the surplus consumer value
estimated from the previously formed recreational demand function. Consumer surplus on total visits
per individual can be measured through the formula:𝑁2

𝐶𝑆 = − 2𝑏1(1)

whereas, CS = Consumer Surplus (Rp/person), N = Frequency visits per person, b1 = Coefficientfrom variable travel cost from Table 2.
𝐶𝑆 = −

1−1.909 𝑥 10−6

= 𝑅𝑝 523,834 = $36.421 𝑈𝑆 𝑑𝑜𝑙𝑙𝑎𝑟𝑠(2)

The consumer surplus concept is an indicator of visitors' ability to want to pay more than thecurrent one. Based on the calculation above, the surplus consumer value per individual per year was
Rp 523,834 (USD 36.42, exchange rate on January 2019: 1 USD = 14,382.51 rupiah). Therefore,
consumer surplus in a year (calculated based on 205,108 people in 2017) was Rp 107,442,640,126(USD 7,470,368). This economic value of MFG conveys its high economic value. Therefore, theMFG should continuously carry out the management and operations of its facilities andinfrastructure.
CONCLUSION
This study aimed to determine visitor perception and agritourism economic value of MFG in Bogor
Regency, West Java, towards finding sustainable and innovative ways to increase visitors and expand
the business. Visitor’s perception can be divided into three factors: factor 1 as “Location, Facilities,
and Agritourism Operation Characteristics” was the main reason why visitors choose to visit MFG
rather than other tourist attractions, for example, can eat and pick up the fruit directly from the tree;
factor 2 as “Agritourism Attractive Characteristics,” which attracts visitors to visit MFG (e.g., canenjoy natural panoramas, spend time with their family and friends, and have a family atmospherethat cannot be found in other tourist attractions); and factor 3 as “Agritourism Support Characteristic”
that can be considered as an additional reason for MFG visit, conveying that the improvement ofservices and facilities in the restaurant and souvenir kiosks should be prioritized to attract visitors
further or encourage an increase in frequency visit. Improvements may include menu development
for restaurants related to increasing usage of fresh fruit ingredients, facility renovation, theintroduction of new souvenirs, and branch establishment of restaurants or souvenir kiosks outside
MFG or nearby areas.
Travel costs, public transportation, transportation with bus, accompany with family, accompany
with a friend, and accompany alone significantly influenced the frequency of visits to MFG. Travel
cost method revealed that MFG had a high economic value amounting to Rp 107,442,640,126 (USD
7,470,368, exchange rate on January 2019: 1 USD = 14,382.51 rupiah) per year. Annual consumer
surplus value per individual was estimated at Rp 523,834 (USD 36.421). Therefore, the MFG should
continue its operations and improve on its facilities and services offered due to its high economic
value and the willingness of its visitors to pay more for its facilities services, in addition to its
significant role as the preservation and education center of tropical horticulture (fruits) in Indonesia.
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We acknowledge that our study has a number of limitations because all respondents in our
research are domestic tourists. For future research, it would be better if we could combine opinions
about MFG from foreign tourists with domestic tourists so that MFG can develop better and also be
widely known by all foreign tourists. With the global recognition of MFG, Indonesia's tropical fruits
will be sustainable.
ACKNOWLEDGEMENT
The authors extend sincere appreciation to the Management of Mekarsari Fruit Garden, its visitors,
and other individuals involved for their valuable understanding and cooperation in this research.
Moreover, we also wish to acknowledge the support and fellowship from the Tokyo University ofAgriculture.
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Busby, G. and Rendle, S. 2000. The transition from tourism of farms to farm tourism. Tourism Management,
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Getz, D., and Calsen, J. 2000. Characteristics and goals of family and owner-operated business in the rural
tourism industry and hospitality sectors. Tourism Management, 21 (6), 547-560.
Healy, H., Lorek, S. and Rodríguez-Labajos, B. 2013. Economic valuation. Retrieved from http://www.ejolt.
org/2013/05/economic-valuation/
Hegarty, C. and Przezborska, L. 2005. Rural and agri-tourism as a tool for reorganising rural areas in old andnew member states- a comparison study of Ireland and Poland. International Journal of Tourism Research,
7, 63-77.
Khoshakhlagh, R., Safaeifard, S.V. and Sharifi, S.N.M. 2013. Estimating recreation demand function by using
zero truncated poisson distribution: A case study of Tehran Darband site (Iran). Journal of Empirical
Economics, 1 (1), 11-20.
McGehee, N.G. and Kim, K. 2004. Motivation for agri-tourism entrepreneurship. Journal of Travel Research,
43, 161-170.
Mekarsari Fruit Garden. 2018. Mekarsari fruit garden pamphlet.
Organization for Economic Co-operation and Development. 2020. Tourism 2020: Policies to promotecompetitive and sustainable tourism. Retrieved from https://www.oecd-ilibrary.org/
Roberts, L. and Hall, D. 2001. Rural tourism and recreation: Principles to practice, CABI Publishing:
Wallingford.
Satriawan, IK., 2005. A design of decision support system for the integration model of tourism and agroindustry in the economic development planning of Jembrana Regency. Ph.D. Dissertation, Graduate
School of Bogor Agricultural University, Bogor.
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aglawcenter.org/overview/agritourism/
Umar, H.B. 2009. Principal component analysis (PCA) dan aplikasinya dengan spss. Jurnal Kesehatan
Masyarakat Andalas, 3 (2), 97-101. Retrieved from http://jurnal.fkm.unand.ac.id/index.php/jkma/article/view/68
Wilson, S., Fesenmaier, D.R., Fesenmaier, J. and Van Es, J.C. 2001. Factors for success in rural tourism
development. Journal of Travel Research, 40 (2), 132-138.
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www.world-tourism.org/Ⓒ ISERD

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Research article
erd

The Effects of the Application of Compost and Chemical
Fertilizer on the Growth and Yield of Rice (Oryza sativa L.)
THEINGI WIN*
Dept. of Soil and Water Science, Yezin Agricultural University, Myanmar
Email: theingiwin@yau.edu.mm

SWE SWE MAR
Dept. of Soil and Water Science, Yezin Agricultural University, Myanmar

KYI KYI SHWE
Dept. of Soil and Water Science, Yezin Agricultural University, Myanmar

WIN YU HLAING
Dept. of Soil and Water Science, Yezin Agricultural University, Myanmar

HSU MYAT THWIN
Dept. of Soil and Water Science, Yezin Agricultural University, Myanmar

KYAW NGWE
Dept. of Soil and Water Science, Yezin Agricultural University, Myanmar

TORU SAKAI
Japan International Research Center for Agricultural Sciences, Japan
Received 25 February 2020

Accepted 24 September 2021(*Corresponding Author)

Abstract The addition of compost to the soil can increase the efficiency of chemicalfertilizers, improve plant growth, and sustain the environment. This field experiment was
conducted at Yezin Agricultural University Farm, Yezin, Nay Pyi Taw, during the 2020 wet
season, from July to November, to investigate sustainable rice production along with
optimum farm productivity. The experiment was arranged in a randomized complete block
design (RCBD) with four replications. The treatments were as follows; T1 (control, no
fertilizer), T2 (100-16-66-12 N, P, K, S) kgha-1, T3 (4 ton ha-1 Compost), and T4 (4 ton ha1Compost and 50-8-33-6 N, P, K, S) kgha-1. Urea, Triple superphosphate, Muriate of potash,
and Gypsum were used as sources of N, P, K, and S and the rice variety tested was Sinthukha.
The plant growth characteristics were collected at biweekly intervals and yield and yieldcomponents were recorded at harvest time. Results showed yield and yield components
responded to the application of different treatments. The number of panicles hill-1, the numberof spikelets panicle-1, filled grain percent, and harvest index were superior in T4 than forother treatments. The maximum grain yield (7.93 ton ha-1) was observed in T4, followed by(7.03 ton ha-1) T2 and (6.36 ton ha-1) T3 treatments and the minimum grain yield (5.71 tonha-1) was produced under T1 conditions. According to the results of this study, the applicationof compost reduces the number of unfilled grain per panicle compared to the control.
Therefore, it is necessary to apply organic materials such as compost, which is cheaper thanchemical fertilizers and which promotes the recovery soil nutrients. Application of compost
increases the yield of rice grain from 11 to 39% compared to the control.
Keywords rice, chemical fertilizer, compost, yield

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Rice (Oryza sativa L.) is a main staple food and is consumed by half the world’s population (Chauhan
et al., 2017). Production of rice globally was more than 759.6 Mt in 2017 (FAO, 2018).
Approximately 90% of all rice is produced and consumed annually; in Asia. However, global mean
yields are high compared to the mean yields in Asia. (Haider, 2018). Significantly, there are several
ways to improve rice yields. For example, one important way of improving rice yields, is throughthe proper management of nitrogen (N) fertilizers (Stellacci et al., 2013).
In Myanmar, rice is critical for the economic livelihood and food security of the population(Okamoto, 2004). Throughout Myanmar, resource-poor rural farmers, and landless agriculturallaborers combine to grow rice on small farms which average only 2.3 ha in size (Okamoto, 2004).
Therefore, more efficient ways to produce rice, that are sustainable and have lower input costs are
crucial to the farmers.
In recent times, farmers have mostly relied on costly chemical fertilizers to boost rice yields(Myint et al., 2011). Rice yields are increased initially, but application of chemical fertilizers often
results in soil problems, declining crop yields, and contributes to worsening global environmental
conditions. Therefore, we need to develop and adopt alternative ways that are environmentally
sustainable and maintain soil health, by supplementing or replacing chemical fertilizers. Applicationof organic fertilizer can conserve the amount and quality of organic matter in the soil, and ensure
supply of N, P, K, and essential micronutrients (Timsina and Connor, 2001; Gruhn et al., 2000).
Although having many advantages, organic fertilizer application can deliver lower nutrient content
compared to chemical fertilizers and may result in nutrient deficiencies and subsequently lower yield(Liu et al., 2009). However, combining the application of organic fertilizer and chemical fertilizer
can ameliorate problems caused by the application of chemical fertilizer alone, by neutralizing soil
pH, leading to higher levels of organic carbon and improving macro and micronutrient availability,
physical properties, and microbial activity (Liu et al., 2009). The combined application also increases
the crop yields (Kumar et al., 2014).
OBJECTIVE
The experiment was conducted to determine the effects of the application of compost and chemicalfertilizer on the growth and yield of a rice crop and to determine which treatment best supports
sustainable production along with optimum productivity.
METHODOLOGY
A field experiment was conducted at Yezin Agricultural University Farm, Yezin, Nay Pyi Taw
during the 2020 wet season, from July to November. The Sinthukha rice variety was used for thisexperiment. Four treatments with four replications were set up with a Randomized Complete Block
Design (RCBD). The treatments contained in this experiment were T1 (Control, no fertilizer
application), T2 (100-16-66-12 N, P, K, S kg ha-1), T3 (4 ton ha-1, Compost) and T4 (4 ton ha-1,
Compost and 50-8-33-6 N, P, K, S kg ha-1).
There were 16 plots and each plot size was 25m2 (5m x 5m). Double bunds were constructed 1
m apart between the plots and with 1.5 m between the blocks to prevent water and nutrients flowing
from one plot to another. Twenty-five-day-old seedlings were immediately transplanted with twoplants per hill at a spacing of 20 cm x 20 cm. Compost (4 ton ha -1) was added one week before
sowing to the T3 and T4 plots. Urea, Triple superphosphate, Muriate of potash, and Gypsum wereused as N, P, K, and S sources. Triple superphosphate, Muriate of potash, and Gypsum fertilizers
were applied basally by broadcast method. Urea was applied at three time splits in the basal,
maximum tillering and panicle initiation stages. Regular weed control was undertaken, especially atthe early stages of growth. The plots were irrigated whenever necessary. Soil physicochemical
properties of the experimental site were as follow; sandy loam texture, moderately acid (pH 5.6) soil
with low organic matter (1.28%) which had low level of available nitrogen (51 ppm), medium levels
in both available phosphorus (11.4 ppm) and available potassium (178 ppm).

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Growth parameters such as plant height and the number of tillers hill -1 were recorded from 5
randomly selected hills for each plot, starting 14 days after transplanting (DAT) and at two week
intervals. The grain yield was determined from a central 1 m 2 harvested area in each plot and was
adjusted for 14% moisture content. The yield component parameters were measured by harvesting 5
hills per plot on a random basis.
The harvest index was calculated by using the following formula; Grain harvest index = (Grain
yield)/ (Grain + Straw yield) (Fageria 2011). All the collected data were analyzed using ANOVA
with Statistix 8 software. The differences in treatment means were separated by the Least Significant
Difference (LSD) at a 5 percent probability level.
RESULTS AND DISCUSSION
Plant height was recorded at 2-weeks intervals from 14 DAT to 98 DAT (Fig. 1). Plants exhibit acontinuing increase in height over all treatments from 14 DAT to 84 DAT and the use of compost
with chemical fertilizer (T4) significantly influenced the height of the Sinthukha rice variety at 1%
level. The lowest height (103.25 cm) is observed in the T1. The highest plant height (109.88 cm)
was, as mentioned, in T4, followed by (107.53 cm) in T2. Greatest increases in height were observedwith the T4 treatment of compost with chemical fertilizer. The results are in agreement with thefindings of Masarirambi et al. (2010). They also found that a half dose of chemical and organic
fertilizers significantly increases plant height.

Fig. 1 Plant height (cm) as affected by compost and chemical fertilizer application

Fig. 2 Number of tillers hill-1 as affected by compost and chemical fertilizer application
Tillering, is an important trait for grain production with its correlation to rice yield. The numberof tillers hill-1 counted at various growth stages are illustrated in (Fig. 2). A significant difference inthe number of tillers hill-1 can be seen for all growth stages at the 1% level. The number of tillers hill1
range from 10.05 to 13.85 and the maximum value was in T4 followed by T2, T3, with theserecorded at the 98 DAT. The treatment T1 showed the lowest number of tillers hill-1. Mirza et al.
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(2010) reported that the increased number of tillers hill-1 in rice plants is due to the influence ofdifferent fertilizer combinations. The more balanced nutrition that the plants can get from organic
sources, especially micronutrients, positively affect the number of tillers in plants (Miller, 2007).
The number of productive tillers influences rice productivity rather than the total number oftillers. There were significant differences at the 1% level in the number of panicles hill -1 among thetreatments (Table 1). The highest number of panicles hill-1 (13.70) occurred in T4, followed by T2(12.50), T3 (10.80), and the lowest value was in T1 (9.65). This result parallels Miller, (2007), whofound that a single application of inorganic fertilizers with a high dose is not necessary to produce
effective tillers if supplementation with compost as organic sources is provided, thus helping to
supply essential micronutrients to the plants.
The panicle lengths range from (22.50 cm) to (23.31cm) and there is a significant difference atthe 5% level among the treatments (Table 1). The longest panicle length (23.31cm) was found in T4
which is statically similar to T2 (23.19 cm), while the shortest panicle length (22.50 cm) was in T1.
One of the most important factors that affect the rice yield is the number of spikelets per panicle(Yoshida, 1981). The mean value of the number of spikelets per panicle indicate no significant
difference between treatments (Table. 1). The maximum number of spikelets panicle-1 were produced
from T4 (165.55), whereas the second-highest number of spikelets panicle-1 (161.85) were from T2,
followed by T3 (154.15) and the T1 (149.65) treatments. It was observed that the application oforganic matter as a supplement can produce more effective tillering in comparison to sole applicationof inorganic fertilizers, which also help in providing essential micronutrients to the plants (Miller,
2007; Rakshit et al., 2008). Mirza et al. (2010) also reported similar results in rice. The filled grain %is not significantly different among the treatments (Table 1). The filled grain % range from 70.75 to
83. The highest filled grain % (83) was found in T4, followed by (76.75) the T2. The lowest filled
grain % was in T1. According to the results of this study, the application of compost increases thenumber of filled grain % in comparison to the control.
The maximum number of 1000 grain weight of 22.01g was in T4 treatment, followed bytreatment T2 (21.11 g). There was a significant difference among the treatments at the 5 % level. The
treatments T1 and T3, which has the minimum 1000 grain weight, were statistically similar. These
results are similar to the findings of Kuepper (2003) which showed that the organic fertilizer
improved the 1000 grain weight. The application of inorganic fertilizers, with the addition of organic
manures, shows a positive correlation with 1000 grain weight (Anas et al., 2016).

Fig. 3 Grain yields (ton ha-1) with different compost and chemical fertilizer applications
In Fig. 3, T4 achieved the highest grain yield (7.93 ton ha-1), whereas the lowest grain yield(5.71 ton ha-1) was in T1. The maximum grain yield was followed by T2 (7.03 ton ha-1) and T3 (6.36
ton ha-1) treatments. The combined application of compost and chemical fertilizer increased grain
yield compared to the control by up to 39% while the increase with the use of chemical fertilizer is
23% compared to the control. The application of compost increases yield by 11% compared to thecontrol. An increase in paddy yield with the use of T4 treatment can be seen in this study and this issimilar to that observed by Jagadeeswari and Kumaraswami (2000), and these increases are greaterthan for treatments with compost alone.
The harvest index of rice as affected by the application compost and chemical fertilizer is not
significantly different among the treatments (Table 1). The harvest index ranges from 0.40 to 0.43.
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The maximum harvest index (0.43) was recorded in T4 and the second highest (0.42) was observed
for the T2 treatment. The minimum value (0.40) was found in T1. T4 produced the greatest numberof panicles hill-1, the number of spikelets panicle-1, filled grain percent, and a harvest index superior
to other treatments (Table 1). Muhammad (2008) observed that the plant height, number of tillers
hill-1, spikelet number panicle-1, grain yield, and 1000 grain weight increased due to the applicationof organic and chemical fertilizers by enhancing the availability of nutrients.
Table 1 Effects of compost and chemical fertilizer applications on yield andyield components parameters of rice during wet season, 2020
Treatment

Number ofpanicle hill-1

Number of
spikelet panicle-1

1000 grain
weight (g)Filledgrain (%)

Paniclelength (cm)Harvest
Index

T1
T2
T3
T4
LSD0.05
pr≥F
CV%

9.65 d12.50 b10.80 c13.70 a
0.93
**
4.97

149.65161.85154.15165.55
14.19
ns
5.62

20.48 b21.11 ab20.47 b22.01 a
1.18
*
3.52

70.75
76.75
76.50
83.00
18.46
ns
15.03

22.50 b23.19 a22.96 ab23.31 a
0.58
*
1.58

0.40
0.42
0.41
0.43
0.09
ns
14.12

**p<0.01; *p<0.05; ns: no significant

CONCLUSION
The application of chemical fertilizers combined with composted organic matter increases thenumber of filled grain panicle-1, 1000 grains weight, and rice yield. This combination of compost
along with a half dose of chemical fertilizer provides a suitable integrated fertilizer application for
the farmers in the study area. According to this study, the integrated application of compost andchemical fertilizer is a good way to achieve optimum growth and yields of rice and this also reduces
cost of fertilizers for the farmers when compared to application of chemical fertilizer alone.
ACKNOWLEDGEMENTS
I would like to thank everybody who assisted me in completing this research and also thank the Japan
International Center for Agricultural Sciences (JIRCAS) for their financial support for this paper.
REFERENCES
Anas, M.A.W.M., Iqbal, Y.B. and Silva, C.S.De. 2016. Evaluation of the effects of compost as a substitution
for inorganic fertilizers on yield o rice (bg 94 - i) in Ampara district. Open University Research Sessions,
ISSN 2536-8893.
Chauhan, B.S., Jabran, K. and Mahajan, G. 2017. Rice production worldwide. Springer International, ISBN
978-3-319-47516-5, USA.
Fageria, N.K., Moreira, A. and Coelho, A.M. 2011. Yield and yield components of upland rice as influenced
by nitrogen sources. Journal of Plant Nutrition, 34, 361-370.
Food and Agriculture Organization. 2018. Rice market monitor. Food and Agriculture Organization (FAO) of
the United Nations, Rome, Italy.
Gruhn, P., Goletti, F. and Yudelman, M. 2000. Integrated nutrient management, soil fertility, and sustainableagriculture: Current issues and future challenges. Food, Agriculture, and the Environment Discussion
Paper, 32, International Food Policy Research Institute, Washington, DC, USA.
Haider, I.K. 2018. Appraisal of bio-fertilizers in rice: To supplement inorganic chemical fertilizer. Rice Sci.,
25, 357-362.
Jagadeeswari, P.V. and Kumaraswami, K. 2000. Long term effects of manure fertilizers schedules on the yieldand nutrient uptake by rice crop in a permanent manorial experiment. Journal of the Indian Society of Soil
Science, 48 (4), 833-836.

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Kuepper, G. 2003. Manures for organic rice production, Fundamentals of sustainable agriculture. Appropriate
Technology Transfer for Rural Areas (ATTRA), USA.
Kumar, P., Singh, F., Singh, A.P. and Singh, M. 2014. Integrated nutrient management in rice-pea cropping
system for sustainable productivity. International Journal of Engineering Research & Technology (IJERT),
3, 1093-1095.
Liu, M., Hu, F., Chen, X., Huang, Q., Jiao, J., Zhang, B. and Li, H. 2009. Organic amendments with reduced
chemical fertilizer promote soil microbial development and nutrient availability in a subtropical paddy
field: The influence of quantity, type and application time of organic amendments. Applied Soil Ecology,
42 (2), 166-175.
Masarirambi, M.T., Manyatsi, A.M. and Mhazo, N. 2010. Distribution and utilization of wetlands in Swaziland.
Res. J. Environ. Earth Sci., 2, 147-153.
Miller, H.B. 2007. Poultry litter induces tillering in rice. J. Sustain. Agric., 31, 1-12.
Mirza, H.K.U., Ahamed, N.M., Rahmatullah, N., Akhter, K.N. and Rahman, M.L. 2010. Plant growth
characters and productivity of wetland rice (Oryza sativa L.) as affected by the application of different
manures. Emir, J. Food Agric., 22 (1), 46-58.
Muhammad, I. 2008. Response of wheat growth and yield to various levels of compost and organic manure.
Pak. J. Bot., 40 (5), 2135-2141.
Myint, A.K., Yamakawa, T., Zenmyo, T., Thao, H.T.B. and Sarr, P.S. 2011. Effects of organic-manure
application on growth, grain yield, and nitrogen, phosphorus, and potassium recoveries of rice variety
Manawthuka in paddy soils of differing fertility. Commun, Soil Sci. Plant. Anal. 42, 457-474.
Okamoto, I. 2004. Agricultural marketing reform and rural economy in Myanmar: The successful side ofreform. Paper presented at the Parallel Session II, Reform in Agriculture-Country Experiences from Asia,
GDN the 5th Conference on 28th January 2004, New Delhi, India.
Rakshit, A., Sarkar, N.C. and Debashish, S. 2008. Influence of organic manures on productivity of two varietiesof rice. J. Cent. Eur. Agric., 9 (4), 629-634.
Stellacci, A.M., Cristiano, G., Rubino, P., Lucia, B.D. and Cazzato, E. 2013. Nitrogen uptake, nitrogenpartitioning and N-use efficiency of container- Grown holmoak (Quercus ilex L.) under different nitrogenlevels and dertilizer sources. Journal of Food, Agriculture & Environment, 11 (3 & 4), 132-137.
Timsina, J. and Connor, D.J. 2001. Productivity and management of rice - Wheat cropping systems: Issues andchallenges. Field Crop. Res. 69, 93-132.
Yoshida, S. 1981. Fundamental of rice crop science. International Rice Research Institute, Los Baños, Laguna,Philippines, 269.

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Research article
erd

Production and Utilization of Crop Residues in Cambodia:
Rice Straw, Corn Stalk, and Cassava Stem
DYNA THENG*
Faculty of Agricultural Engineering, Royal University of Agriculture, Phnom Penh, Cambodia
Email: thdyna@rua.edu.kh

LYTOUR LOR
Faculty of Agricultural Engineering, Royal University of Agriculture, Phnom Penh, Cambodia

CHHENGVEN CHHOEM
Faculty of Agricultural Engineering, Royal University of Agriculture, Phnom Penh, Cambodia

KANHARA SAMBATH
Faculty of Agricultural Engineering, Royal University of Agriculture, Phnom Penh, Cambodia

PISEY VONG
Faculty of Agriculture, University of Heng Samrin Thbong Khmum, Thbong Khmum, Cambodia

SORKUNTHIKA SROUR
Swisscontact, Phnom Penh, Cambodia

VATHANA CHAMROEUN
Swisscontact, Phnom Penh, Cambodia

DAVITH EANG
Swisscontact, Phnom Penh, Cambodia

MAKARA LAY
Department of Science and Technology, Linköping University, Sweden

RAJIV PRADHAN
Swisscontact, Phnom Penh, Cambodia

GERALD HITZLER
Center for International Migration and Development (CIM), Germany
Received 21 June 2021

Accepted 24 September 2021(*Corresponding Author)

Abstract Rice is the main staple crop, followed by cassava and corn in Cambodia. Annually,
million tons of these crops are produced with the particularly need is its grain or root. After
harvesting, these crop residues are usually collected for various purposes. Some of them areburned (the easiest option for farmers), which leads to loss nutrients and air andenvironmental pollution. However, it is limited report on these crop wastes production andutilization, and the crop residues management remain a challenge in Cambodia. Therefore,
this study was conducted to assess to what extent that crop residues are available for further
processing in Cambodia manufacture. Two hundred eighty eight key informers, were selectedpurposively to be interviewed through structure-questionnaire interview. The results showedthat the crop residues were produced annually approximately 8.6, 0.9, and 2.9 million ton for
rice, corn and cassava, respectively. The rice straw was collected for supplementary feed tocattle, vegetable mulch-based and mushroom production. The cassava stem was collected fornext year planting and selling to other farmers. In term of quantity, the crop residues
collection was just to meet the household’s utilizations and the remaining are burned. For
better crop waste management and practice, other alternative uses, for instance developmentⒸ ISERD

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of packaging products, construction materials, paper and renewable energy such as biogas
and bio-energy using these residues, will change the open-field option and add value chainsto the farm owners and rural people.
Keywords: crop residues, rice paddy, corn stalk, animal feed, mushroom, packaging products

INTRODUCTION
Agriculture is one of the priorities economic activity in Cambodia, which contributed about 21% toGDP in 2019 with the contribution of crops, animal production, fisheries resources, and forestry
resources were about 58%, 11%, 24%, and 7%, respectively. Rice is regarded as the main staple cropin Cambodia, approximately 3.328 million hectares planted with the average yield 3.338 ton perhectare (totally 10.885 million tons paddy rice produced in 2019) (MAFF, 2020). Rice straw is a
residual by-product of rice at harvest. The total biomass of this residue depends on various factors
including: varieties, soils, nutrient management and weather. The ratio of straw to paddy varies,
ranging from 0.74 to 0.49 (Nguyen, et al., 2016, Nguyen, et al., 2020). At harvest, rice straw is piled
or spread in the field depending on the harvesting methods, using human labor plus stationary
threshers or self-propelled combined harvester. Rice straw that remains in the field after harvest canbe collected, burned, or left to decompose (soil incorporation).
The intensification of rice production and rising labor costs have led to the spread of combine
harvesters in Asian rice fields. Combine harvesters leave loose rice straw on the ground, making its
collection and transportation difficult, laborious, and costly. Farmers choose the quick solution ofburning rice straw to quickly remove the biomass and prepare the field for the next crop. In-fieldburning of rice straw contributes to greenhouse gas emission and poses health and environmental
hazards (Tabil, 2011).
Unlike rice, corn and cassava are industrial crops, planted on approximately 200 thousand and656 thousand hectares, respectively in Cambodia. There are two types of corn: white corn (mainly
for human food) and yellow/red (mainly for animal feed) in term of grain (MAFF, 2020).
Annually, million tons of crops and its biomass are produced, but it is limited report about theresidues. Even though, some amounts of the crop wastes are collected and used for various purposes
and literatures showed that the agricultural waste has complex carbohydrate similar to those of wood
sources, i.e, percentage of cellulose, hemicellulose and lignin (Theng, 2017), but field burning is stillheard a quick solution for farmers to clear the land for next crop. Among several crops in Cambodia,
rice straw, corn stalk and cassava stem are seasonal crop residues with widely available and fast
growth, compared with wood sources.
OBJECTIVE
The study aimed to assess to what extent that crop residues are available for further processing in
Cambodia manufacture.
METHODOLOGY
The results presented in this article are based on quantitative and qualitative methods of primary datacollection. The total of 288 households are dealing with rice, corn and cassava production, utilizationand supply of the crop residues were subjected for the interview. The study was conducted in six
provinces including: Kampong Cham, Kampong Thom, Battambang, Kampong Chhnang, Kampong
Speu, and Takeo (Fig. 1). The data collection instrument was a structure-questionnaire (Sa, 2011).
The samples are purposively selected (Norng et al., 2011). The collected data was analyzed using
SPSS computer software.

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Fig. 1 Map of Cambodia and selected provinces for the data collection
RESULTS AND DISCUSSION
Household Demographic for Agricultural Categories
Table 1 shows the types of agriculture in the study sites. There were 232 (53.2%) rice producer, 36
corn, cassava, and other crops, 15 vegetable growers, 130 cattle producers with 9 cattle farms, and23 mushroom producers. The household scale cattle are cows or water buffaloes raising at home with
the number from 1-13 heads per household (4.22 heads in average) were observed, whereas the farmscale of cattle is raising in a large area of land with more number from 50 to 700 heads (137.77 heads
in average) per farm were investigated.
Table 1 Types of agriculture in the studied areas
Agricultural categories
Rice-Wet season rice
-Dry season rice
Plantation crops (corn, cassava, cashew, bean)
Vegetable
Cattle (farm scale)
Mushroom

Frequency
232
210
122
36
15
130 (9)23

Percentage
53.2
8.3
3.4
29.8
5.3

Crops and Crop Residues Production
Rice, corn, and cassava is grown on 0.1 to 300 ha, 0.1 to 10 ha, and 0.5 to 100 ha per household,respectively (Fig. 2). The wet season rice was grown by 210 farmers on the land size range 0.1-50
ha and dry season rice was grown by 122 farmers on the land size from 0.1 to 300 ha. This study
found that approximately 50% of the farmers grow 3 times a year for both seasonal rice. But, themajority a household owned between 1 and 2 ha and can grow rice only once a year with few cangrow up to 3 times a year depending on irrigation availability and flooding condition. The average
yield paddy was 3-6 ton per hectare of grain depend on variety, location, production time, input andwater supply, and care. It was in range of the average yield 3.338 tons ha-1 (MAFF, 2020). However,there was no investigation and record about rice straw.
Corn and cassava are classified as upland crops, cultivated on smaller area and number offarmers, compared to rice. In this study, the yellow corn variety and cassava are found in KampongⒸ ISERD112

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Cham, Kampong Thom and Battambang Provinces. The average yield of corn grain was 5-10 tons
ha-, higher than the literatures (MAFF, 2020; PPDA, 2012; Net et al., 2013) i.e, about 4.5 tons ha-1,
but in the range compared to Belfield et al. (2013) and the average yield of cassava is 20-30 tons ha1. Corn and cassava can be grown two times per year or diversify together (Net et al., 2013).
According to the key informers, the yield of cassava plant or stem was around 1500 bunch per hectarewith around 3 kg a bunch.

Fig. 2 Land size belong and/or rental by individual household for rice, corn, and cassava
Collection and Utilization of Crop Residues
Fig. 3 showed that about 55%, 0%, and 82% of the respondents collected rice straw, corn stalk, andcassava stem, respectively. The rice straw was collected in quantity ranging from less than 1 ton peryear per household to more than 1000 tons and the cassava stem up to 3-5 tons (Fig. 4).
Approximately 80%, 8%, and 12% of the collected rice straw was used for cattle feed, mulching andmushroom production, respectively (Fig. 5). The quantity of rice straw needed for household cattle
was small, just below 10 tons per year depending on the number of cattle, the available time ofhousehold members to collect green grass, and the available free land for cattle feeding with natural
green grass. Most of the cattle farm used planted grass or natural grass in orchard of coconut, longan,
cashew, and other perennial crops. The more quantity of rice straw was used for mushroom
production as the mushroom can be grown 10 to 13 cycles a year. The quantity from 100 to morethan 1000 tons per year was collected by collectors or service providers using baler machine. The
baler has high collection capacity, make easier to transport the baled rice straw from paddy to cattle
farm, mushroom farm and vegetable garden, but the crop growing farmers experienced that the baled
rice straw is difficult use, heavier and easier to damage when it is wet. The crop-based mulch using
rice straw in vegetable production was commonly in Saang and Koh Thom Districts, bordering with
Prey Kabas District of Takeo Province. Because more farmers live in Saang and Koh Thom selected
vegetables growing than rice and other crops, they purchase more rice straw from other neighboringareas including Prey Kabas, Angkor Borey and Bati Districts for mulching and animal feed, whereas
the other study sites collected and supplied locally. The 45% of respondents did not collect rice straw
selected two means including: burning in the paddy field about 20% (IRRI (2019) reported around 3
million tons generated rice straw was burned) and other 25% was left degradation, those farmers or
paddy allow once growing per year in rainy season. The cassava plant yield is approximately 10
times over the seedlings need, but generally Cambodian farmers reserved the stem at least double
since sometimes experiences of damaged by drought or diseases and required the second planting.
In addition, cassava plantation keeps increasing from year to year in Cambodia about 0.66% (MAFF,
2020). Therefore, the result from this study indicated that around 25% of the cassava stem was used
for seedlings and the remaining was burned.

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Fig. 3 Collection of crop residues by farmers

Fig. 4 Quantity of the collected crop residues

Fig. 5 Proportion of rice straw uses in Cambodia
Cost of Crop Residues
In this study, the rice straw is not value, except Battambang and Takeo Provinces, because thefarmers do not care on selling the rice straw as it is widespread on the paddy with possible to collecteither from their paddy or neighbors’. There is market in Battambang and Takeo provinces, although,Ⓒ ISERD

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the farmer is paid at lower price around 17 USD per hectare when the collectors collected and soldbetween 20 and 50 USD per ton, depending on the location of transportation. The cassava stem costs
around 1 USD/bunch of 3 kg, excluding transportation cost.
CONCLUSIONSThe by-product of rice, corn, and cassava are produced in lots of quantity with limited use seasonallyand annually in Cambodia. The rice straw was used as household cattle feed, mushroom feedstock,and mulch-based vegetable production. Approximately 55% of the rice straw was collected and 45%
was burned or left to natural degradation in the paddy field. In term of economic cost-effective, it isa huge loss of money when the biomass can be value added. Regarding, greenhouse gas emission
through burning the rice straw, it is a high impact as million ton of rice straw is burned every year.
It is similar to corn and cassava crop residues that plenty tons of biomass was produced annually andthe matured corn stalk was only burn and cassava stem was only replanting. According to previous
studies and literatures, the biomass has similar chemical and physical compositions compared towood sources fiber, suitable uses for manufacturing various products such as biodegradable
packaging materials, paper, construction materials, adding to the current uses for animal feed,
mushroom and mulching.
ACKNOWLEDGEMENTS
This study was made possible thanks to the Higher Education Improvement Project (HEIP) IDA
credit no. 6221-KH for financial support. The authors also thanks to key informers in the 6 target
provinces in Cambodia for providing the helpful information.
REFERENCES
Belfield, S.C., Robert, J.M. and Fiona, J.S. 2013. Alternative cropping systems for North-West Cambodia.
International Journal of Environmental and Rural Development, 4 (1), 209-214.
IRRI. 2019. Cambodia scales up rice straw management. News, International Rice Research Institute, Los
Baños, Laguna, Philippines, Retrieved from http://news.irri.org/2019/01/cambodia-scales-up-rice-strawmanagement.html
MAFF. 2020. Annual report of Ministry of Agriculture, Forestry, and Fisheries for 2019-2020 and future
direction 2020-2021. Ministry of Agriculture, Forestry, and Fisheries, Phnom Panh, Cambodia.
Net, N., Ra, T. and Maria, T.S.M. 2013. An analysis of maize value chain in Palin province, Cambodia.
Research Working Paper Series 2013, Mekong Institute, Khon Kaen, Thailand.
Nguyen, H.V., Maguyon-Detras, C.M., Migo, V., Quilloy, R., Balingbing, C., Chivenge, P. and Martin, G.
2020. Rice straw overview: Availability, properties and management practices. In Chivenge, P., Gummert,
B.D.M. and Hung, N.V. (Eds.), Sustainable Rice Straw Management, Springer Open, International Rice
Research Institute, Los Baños, Laguna, Philippines.
Nguyen, H.V., Topno, S., Nguyen, V.C.N., Roder, M., Quilty, J. and Martin, G. 2016. Generating a positiveenergy balance from using rice straw for anaerobic digestion. Energy Report, 2, 117-122.
Norng, C., Chay, C., So, N. and Chou, K. 2011. Small-sized fish paste (prahoc) processing in Cambodia.
International Journal of Environmental and Rural Development, 2 (2), 36-41.
Sa, K. 2011. Organic rice farming systems in Cambodia: Socio-economic impact of smallholder systems in
Takeo. International Journal of Environmental and Rural Development, 2 (1), 115-119.
Tabil, L., Adapa, P. and Kashaninejad, M. 2011. Biomass feedstock preprocessing. Part 2 Densification,
Biofuel’s Engineering Process Technology, 19, 439-464.
Theng, D. 2017. Feasibility of incorporating treated lignin and cellulose nanofiber in fiberboards made fromcorn stalk and rice straw. Doctoral Thesis, University of Girona, Spain.

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Research article
erd

Water Harvesting Potential and its Maximization by the
Application of Clayey Dressing in Qargha Reservoir
Watershed, Kabul, Afghanistan
SHAFIQULLAH RAHMANI
Department of Horticulture, Ghazni University, Ghazni, Afghanistan

IHSANULLAH AKRAMZOI
Department of Horticulture, Ghazni University, Ghazni, Afghanistan

MACHITO MIHARA*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Email: m-mihara@nodai.ac.jp
Received 8 February 2021

Accepted 4 October 2021(*Corresponding Author)

Abstract The unfavorable impacts of climate change are experienced all over the world.
Afghanistan is among the countries that are severely affected by the impacts of climatechange. The adverse effect on water resources constitutes one of the most negative effects.
Currently, water management authorities and researchers look for improved water
management techniques that will reduce the pressure on the already stressed water resources.
Surface runoff harvesting is becoming more popular in regions with an arid-semi-arid climate,such as Afghanistan because of the increasing demand for scarce water resources. Therefore,a study was carried out to analyze the water harvesting potential in Qargha Reservoir
Watershed, and to evaluate the effectiveness of clayey dressing application in maximizing
surface runoff compared to control conditions. Rational method and sorptivity method wereused to estimate the potential surface runoff and clayey dressing (silty clay loam and clayloam) was applied as a conservation strategy. A small area of 2 ha was selected in suitableareas of Qargha Reservoir Watershed. Based on 16 rainfall events, the volume of surface
runoff estimated by the rational method was 509.40 m3, which was larger than the 478.34 m3,
estimated by the sorptivity method. After clayey dressing application, the estimated volume
of surface runoff based on the rational method increased to 1392.36 m3. Furthermore, theestimated volume of surface runoff after clayey dressing calculated with the sorptivity
method increase to 1608.46 m3 based on 16 rainfall events. Proper soil surface treatment suchas application of clayey dressing is highly recommended for achieving sustainable agriculture.
Keywords water harvesting, Qargha Reservoir, clayey dressing application,
silty clay loam, clay loam and sorptivity method

INTRODUCTION
In recent years, the adverse impacts of climate change occur more consistently, and the sector most
severely hit by climate change is agriculture sector. The adverse effect of climate crises on water
resources constitutes one of the most negative effects. Moreover, excessive use of available irrigationwater in the field aggravates the consequences. The most common irrigation method used in the study
area is surface irrigation (flood irrigation). Thus, intensive aridity has altered the yield pattern
negatively (Parvizi and Sepaskhah, 2015). According to Oweis and Hachum, (2006), rain water
harvesting can considerably boost productivity in the drier marginal environments. Water harvestingis among the most promising ways of supplementing the scarce surface water resources in areas tomeet demand (Aladenola and Adeboye, 2010). Maximizing surface runoff can be used to provide
partial water requirement of rain-fed and irrigation based agriculture (Parvizi and Sepaskhah, 2015).
Currently, water management authorities and researchers look for improved water management
techniques that will reduce the pressure on the already stressed water resources. Climate inducedⒸ ISERD

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changes in precipitation, surface runoff, and soil moisture will possibly have intense impacts on
living creatures (Hardy, 2005). Survey conducted by Rahmani and Mihara, (2017) reported that water
shortage was the main problem in the study area farmers face during crop production. Growing
season in Qargha Reservoir Watershed of Paghman District, Kabul Province starts in March and ends
in October; however, in the latter half from June to October, it hardly rains, which causes crop failure
and low productivity. So, collecting and stocking a certain amount of runoff water in the wet season
and using it as irrigation water during the latter half of the growing season can reduce water shortage
problems (Rahmani et al., 2019 and). Wide range of techniques such as soil compaction, gravel
removal, bitumen emulsion and tall oil, less permeable soil, wax and plastic and Sodium dispersantssuch as sodium carbonate and sodium chloride (Yazar et al., 2014, Parvizi et al., 2015, Short and
Lantzke, 2006, Amu-Mensah et al., 2013, Fink et al., 1980 and Frasier et al., 1987) used worldwide
for surface runoff maximization. This study aimed to evaluate the effectiveness of clayey dressing
application in surface runoff maximization compared to control conditions in the laboratory and in
the field.
OBJECTIVE
To analyze the water harvesting potential in Qargha Reservoir Watershed, and to evaluate theeffectiveness of clayey dressing application in maximizing surface runoff compared to control
conditions.
METHODOLOGY

Study Area
The research area lies between longitudes E 68° 49' 44'' and E 68° 40' 54'' and latitudes N 34° 25' 14''and N 34° 40' 19.2''. The research was carried out in Qargha Reservoir Watershed, Paghman District,
Kabul Province, Afghanistan. The total area of Paghman District is 361 km 2, and Qargha Reservoir
catchment area is 40.33 km2. According to Rahmani et al, (2018), average precipitation in thewatershed is around 280 mm annually and average annual temperature is 11.01 oC. Majority of thepeople living in Paghman District is small subsistence farmers with small plots of agricultural land.

Fig. 1 Location map of proposed water harvesting site (Rahmani et al., 2019)
Surface runoff experiments were conducted in the field and laboratory. Sorptivity method andrational method were used to calculate surface runoff. Soil sorptivity experiments were carried out
in the laboratory; several samples from local soil were used in the experiment. The dominant soil
particle size distribution (soil texture) in the study area is loam. Thus, surface runoff was calculatedwith and without clayey dressing application. Clayey dressing application is an economical andenvironmental friendly runoff enhancement technique. Clayey dressing (less permeable soil) was
extracted using sieve sieving and cloth sieving. A clothing was placed on the bucked to remove largerⒸ ISERD

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particles from diluted soil (Rahmani, et al., 2018). Cloth sieving was used for clayey dressing
extraction in the field and soil sieved (clayey dressing) using sieves of 38 μm and 75 μm were usedin the surface runoff experiment in the laboratory. Runoff experiment was conducted in thelaboratory of Land and Water Use Engineering, Tokyo University of Agriculture using runoff plots
with 0.90 m long, 0.052 m wide and 0.035 m deep. Marriott bottle was used to provide constant waterflow rate of 20 cm3 s-1 at constant pressure for a concentrated surface scenario and 8% slope.
The rational runoff coefficient for treated condition was calculated based on the runoff plot
experiment in the laboratory and in the field. The change in rational coefficient was recorded andthen added to rational runoff coefficient for control condition based on ODOT (2014). And then the
average runoff coefficient was calculated. The average runoff coefficient for treated conditions
calculated was 0.41. Total 16 rainfall events observed from 18 November 2017 to 6 May 2018 for
170 days were selected for runoff volume estimation. Additionally, silty clay loam (SiCL) dressing
and clay loam (CL) dressing were used as a surface runoff maximization strategy. For further
information refer to the calculation of surface runoff using sorptivity method and rational method in
Qargha Reservoir Watershed control condition (Rahmani et al., 2019).
RESULTS AND DISCUSSION
Surface Runoff Estimation
The amounts of surface runoff generated under different treatments compared to control in thelaboratory are shown in Table 1. Silty clay loam dressing with 57%, 53% and 47% concentration
increased runoff 1.30 x, 1.28 x and 1.16 x, respectively. While, clay loam dressing with 65%, 60%
and 53% concentration increased runoff 1.43 x 1.41 x and 1.27 x, respectively. The result shows that,the clay dressing application is highly effective in increasing surface runoff, and the influence ofsieve size was not obvious. Shirazi et al., (2010) stated that permeability noticeably decreasing by
the increasing rate of clay in the clay-sand mixture. For instance, application of clayey dressing on
the soil surface is highly recommended as a runoff maximizer. Thus, it is very economical and easy
to use, and extraction does not need expensive and difficult equipment and tools to use. Availability
and generation of extra rainfall runoff water can help to revive agriculture in the study area andcultivate large dry uncultivated lands. Statistical analysis showed that there are significant differences
between control and clayey dressing applied conditions.
Table 1 Surface runoff water under different treatments
Clayeydressing

Dry density(g cm-3)

Treatment Water applied
RunoffInfiltration
Increase from
Runoff (C)(cg g-1)(dm3)(dm3 m-2)(dm3 m-2)
control (x)Control
12.96
9.70 a**
3.20
0.75
46.4
12.96
11.24 b**
1.68
0.87
1.16
SiCL
1.3
52.3
12.96
12.45 b**
0.50
0.96
1.28
56.9
12.96
12.62 b**
0.00
0.97
1.30
Control
12.96
8.68 a**
3.82
0.67
52.1
12.96
11.04 c**
1.55
0.85
1.27
CL
1.5
60.1
12.96
12.20 b**
0.00
0.94
1.41
64.9
12.96
12.38 b**
0.00
0.95
1.42
CL = Clay loam dressing, SiCL = Silty clay loam dressing, **denotes significance difference level at P<0.01

The result of surface runoff experiment conducted in the field showed that, Deh Ponba soil
treated with clayey dressing at 57.7 and 64.9 cg g-1 increased runoff by 1.41 x and 1.42 x, and Doda
Mast soil increased runoff by 1.55x and 1.58x compared to control shown in Table 2. Statisticalanalysis also showed that the result of control and treated conditions had signification differences.
Parvizi and Sepaskhah, (2016), examined the effect of gravel removal, rill construction across toslope and applying of baking soda on surface runoff. According to the results, gravel removal
technique is nearly as effective in the runoff enhancement as rill construction across to slope andbaking soda technique.
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Table 2 Surface runoff estimation in the field
Treatment(cg g-1)

Site

Water applied(dm3)

Runoff(dm3 m-2)

Runoff (C)Control
45.0
27.7 a**0.62
Deh Ponba
SiCL 57.7
45.0
39.2 b**0.87
SiCL 64.9
45.0
39.5 b**0.88
Control
45.0
25.3 a**0.56
Doda Mast
SiCL 57.7
45.0
39.2 b**0.87
SiCL 64.9
45.0
39.5 b**0.88
SiCL = Silty clay loam dressing. **denotes significance difference level at P<0.01

Increase fromcontrol (x)
1.41
1.42
1.55
1.58

Results of runoff volume calculation showed that with clayey dressing application of either silty
clay loam or clay loam, the runoff volume increased from 509.40 m 3 to 1392.36 m3 compared tocontrol conditions, which shows 2.73 x increase in surface runoff. Similarly, the runoff coefficientvalue was increased from 0.15 to 0.41. The results of surface runoff calculated based on sorptivity
method with clayey dressing application showed that surface runoff volume can be increase to1608.46 m3 from 478.34 m3 control condition, which shows 3.36 x increase. Accordingly, bothmethods confirm that clayey dressing application onto the soil surface can effectively increase
surface runoff. The results of surface runoff volume in treated conditions estimated using sorptivity
method is shown in Table 3. For the result of surface runoff calculated using rational and Sorptivity
method in control conditions please refer to Rahmani et al., (2019). Comparison result of rationaland Sorptivity method calculated surface runoff is shown in Table 4.
Table 3 Surface runoff volume estimated using the rational method and sorptivity method
treated conditions
Rainfall
even
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16

P (mm)S

Area (m-2)

C

14.80
12.80
8.00
14.20
11.40
16.80
3.20
15.60
11.20
22.60
6.80
17.40
8.00
10.20
3.80
2.20

6.70
6.00
10.50
8.60
7.30
8.90
10.80
9.20
15.30
11.80
7.90
14.20
9.40
11.10
3.90
8.90

20000
20000
20000
20000
20000
20000
20000
20000
20000
20000
20000
20000
20000
20000
20000
20000

0.41
0.41
0.41
0.41
0.41
0.41
0.41
0.41
0.41
0.41
0.41
0.41
0.41
0.41
0.41
0.41

Total

Qsp
(mm)
9.00
7.70
2.10
7.40
5.70
9.40
0.00
8.30
2.80
12.80
2.10
7.40
2.40
3.40
0.00
0.00

Qsp
(m3)
179.70153.2042.50
147.90114.20188.700.00
165.2056.60
255.5041.60
147.80
48.30
67.10
0.00
0.00
1608.46Qra(m3)
121.36104.9665.60
116.4493.48
137.760.00
127.92
91.84
185.3255.76
142.68
65.60
83.64
0.00
0.00
1392.36

Amu-Mensah et al., (2013), reported that, possibility of water harvesting to can be created insoils with high infiltration rate by less permeable soil application onto the soils surface. In accordancewith the results, it was assumed that the higher effectiveness of clayey dressing in surface runoff
inducement (maximization) and reducing infiltration rate of the soil is due to its characteristic ofclogging and sealing surface which leads to lower infiltration rate and high runoff production. A
study conducted by Rahmani et al., (2018), indicated that, application of less permeable soil (clayey
dressing) on soil surface lower the infiltration rate because of clogging soil pores and cracks. It is tobe concluded that, the increase observed in surface runoff by clayey dressing application compared
to control was due to clogging the soil pores and sealing the surface. Pore clogging and surface
sealing take place when the plug flow radius of the soil suspension was bigger than the radius of soil
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pores. Mihara et al. (1993), also confirm that pore radius smaller than radius of plug flow causes
clogging of soil pores, which leads to increased runoff. Mihara and Yasutomi (1992) also reported
that clayey suspension flow causes pore clogging.
Table 4 Surface runoff volume change after clayey dressing compared to control
Treatment

MethodControl*
Clayey dressing
Control*
Clayey dressing

Sorptivity
methodRational
methodRainfallevents16
16
16
16

Area (m2)
20,00020,00020,00020,000

Runoff (m3) Increase in runoff volume (x)478.3
1,608.5
509.4
1,392.4

3.36 x2.73 xRational method and sorptivity method (control condition) by Rahmani et al.,( 2019).

This idea is confirmed and backed by Mihara and Yasutomi (1993) and Mihara et al., (1992),
which conclude that clay suspension caused pore clogging and surface sealing. According to Robert(1974), infiltration decreases with increased number of suspended solids in the water. Further, hestated that sediment deposition caused surface sealing.
CONCLUSION
Water harvesting is one of the promising ways of supplementing the surface and underground scarcewater resources in areas where existing water supply system is inadequate to meet demand. Water
harvesting can substantially increase rainwater productivity in the drier marginal environments. The
results of both laboratory and field runoff experiment showed that clayey dressing application (lesspermeable soil) was highly effective in maximizing surface runoff and to lower infiltration rate evenin rainfall events with depth and intensity. Thus, the result of surface runoff calculated using rational
method and sorptivity method also indicated that surface runoff can be increased with clayey dressing
application onto the soil surface. The statistical analysis also showed that there were significant
differences between control and soil treated with clayey dressing. So, maximizing surface runoff canbe used to provide water requirement of rain-fed and irrigation based agriculture.
ACKNOWLEDGEMENTS
We would like to convey our sincere gratitude to Faculty of Regional Environment Science, Tokyo
University of Agriculture, for continues support and backing during our study.
REFERENCES
Aladenola, O.O. and Adeboye, O.B. 2010. Assessing the potential for rainwater harvesting. Water Resources
Management, 24 (10), 2129-2137.
Amu-Mensah, F.K., Tahei, Y. and Mitsuhiro, I. 2013. Improving soil surface conditions for enhanced rainwater
harvesting on highly permeable soils. International Journal of Water Resources and Environmental
Engineering, 5 (11), 616-621.
Fink, D.H., Frasie, G.W. and Cooley, K.R. 1980. Water harvesting by wax-treated soil surface, Progress,
problems and potential. Agricultural Management, 3, 125-134.
Frasie, G.W., Dutt, G.R. and Fink, D.H. 1987. Sodium salt treated catchments for water harvesting. American
Society of Agricultural Engineers, 30 (3), 658-664.
Hardy, J.T. 2005. Climate change: Causes, effects and solutions. Wiley, John Wiley and Sons, 77-95. UK.
Keese, C.W. 2006. Sealing ponds and lakes with bentonite. Extension Agricultural Engineer, Texas
Agricultural Extension Service, The Texas A and M University, Texas, 77843.
Mihara, M. and Yasutomi, R. 1992. Structural mechanism in porous medium by soil suspension flow. In
Moldenaers, P. and Keunings, R. (Eds.), Theoretical and Applied Rheology, Proc. XIth International
Congress on Rheology, 653.
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Mihara, M., Yasutomi, R. and Nakamura, Y. 1993. Rheological study on strainer structure of under drain pipes
for slope protection. Proc. International Conference for Agricultural Machinery and Process Engineering,
197-204.
Oweis, T. and Hachum, A. 2006. Water harvesting and supplemental irrigation for improved water productivityof dry farming systems in West Asia and North Africa. Agricultural Water Management, 80, 57-73.
Parvizi, H. and Sepaskhah, A.R. 2016. The effect of physical and chemical treatments on runoff, infiltrationand soil loss. Iran Agricultural Research, 35 (2), 9-18.
Rahmani, S. and Mihara, M. 2017. Current agricultural status and problems faced in Paghman District of Kabul
Province, Afghanistan. International Journal of Environmental and Rural Development, 8 (1), 180-186.
Rahmani, S., Nakajima, T. and Mihara, M. 2018. Development of water harvesting technique in Qargha
Reservoir Watershed of Paghman District, Afghanistan. International Journal of Environmental and Rural
Development IJERD, 9 (1), 142-149.
Rahmani, S., Nakamura, T. and Mihara, M. 2019. Analyzing water harvesting potentials in zoned areas in
Qargha Reservoir Watershed. International Journal of Environmental and Rural Development IJERD, 10(1), 88-94.
Shirazi, S.M., Kazama, H., Salman, F.A., Othman, F. and Akib, S. 2010. Permeability and swellingcharacteristics of bentonite. International Journal of the Physical Sciences, 5 (11), 1647-1659.
Yazar, A., Kuzucu, M., Elik, I.C., Sezen, S.M. and Jacobsen, S.E. 2014. Water harvesting for improved waterproductivity in dry environments of the Mediterranean region case study, Pistachio in Turkey. Journal ofAgronomy and Crop Science, 200, 361-370.

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Research article
erd

Relationship between NDVI and Canopy Cover Sensed by
Small UAV under Different Ground Resolution
KE ZHANG
Graduate School of Agriculture, Tokyo University of Agriculture, Tokyo, Japan

HIROMU OKAZAWA*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Email: h1okazaw@nodai.ac.jp

YURI YAMAZAKI
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan

KIICHIRO HAYASHI
Institute of Materials and Systems for Sustainability, Nagoya University, Nagoya, JapanOSAMU TSUJI
Obihiro University of Agriculture and Veterinary Medicine, Obihiro, Japan
Received 16 January 2021

Accepted 14 October 2021(*Corresponding Author)

Abstract Canopy Cover (CC) is a significant indicator of crop development and estimationof the evapotranspiration volume of crop leaves within crop simulation models. During thelast three decades, monitoring CC for crops using Normalized Difference Vegetation Index(NDVI) obtained from satellite sensors has been studied worldwide. However, a few studies
have estimated the CC of crops using NDVI by UAVs. One of UAV imagery’s crucial
advantages is a high resolution of less than 0.10 m, while the resolution of satellite imagery
is usually larger than 10 m. Now that the UAV has become a popular method in agriculturescience, it is necessary to prove the interchangeability of UAV and satellite imagery ofmonitoring CC. In this study, small UAVs took RGB and multispectral images of theexperimental peanuts field in Hokkaido. Orthomosaic and reflectance map of the field wereconstructed using the UAV imagery and then were obtained CC and NDVI values with GIS
software. CC was calculated as the green canopy area ratio, extracted from the orthomosaic
using a GIS supervised classification tool. CC was compared with NDVI values undervarious resolutions of 0.50 m, 1.0 m, 2.5 m, 5.0 m, and 10 m. The NDVI showed a highly
correlated linear relationship with CC under each ground resolution from 0.10 m to 10 m (R2
led a range of 0.88** to 0.94**). The shapes of NDVI and CC’s regression equations closely
resembled each other, with the slopes of 1.06 to 1.11 and the intercepts of 0.247 to 0.250,
respectively. From the result of ANCOVA, the UAV imagery resolution has no significant
impact on NDVI and CC’s relationship. Although more irrelevant factors, such as soil andmulching seat, got included within one pixel of the images, the regression equations stayed
the same with the increased ground resolution.
Keywords UAV, NDVI, canopy cover, ground resolution

INTRODUCTION
Canopy cover (CC) is a relatively easily measured property that is an indicator of crop growth andan important parameter in crop simulation models, such as the Aqua Crop (FAO, 2012) model. Whensimulating crop development, Aqua Crop model describes the development expansion of the CC
using the percentage area of green canopy cover. According to the Food and Agriculture Organization(FAO), CC is defined as the ratio between the soil surface covered by the green canopy cover over
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the ground surface (FAO, 2012). CC value ranges from 0, when there is bare soil, to 1, where thevegetation canopy fully covered the ground. The crop characteristic decides the maximum value of
CC. Aqua Crop model describes the development of the canopy between generation and the momentmaximum CC is reached through a logistic type equation. Then, at the end of the season, when thesenescence starts, the CC value declines (Steduto et al., 2009). Accurate and efficient CC estimation
would allow improved scheduling and allocation of irrigation water (Bausch, 1995).
On the other hand, during the last three decades, Vegetation indices (VIs) have been extensively
used to trace and monitor vegetation conditions such as health, growth levels, and water or nutrient
stress (Silleo et al., 2006). Previous studies have shown that various spectral calculated from visible
and near-infrared reflectance data are linearly related to the value of CC (Purevdor et al., 1998).
Healthy canopies of green vegetation have a very distinct interaction with certain portions of theelectromagnetic spectrum. In the visible region, chlorophyll causes strong absorption of energy,
primarily for use in photosynthesis. This absorption peaks in the red and blue region s of the visible
spectrum, while the green region is reflected by chlorophyll, thus leading to the green color of mostleaves. This strong contrast between the reflectance of red and near-infrared regions of theelectromagnet spectrum has been used to develop the Normalized Difference Vegetation Index(NDVI), a VI that has been widely used in the agricultural remote sensing field (Silleos et al., 2006).
Region scale NDVI data could be obtained using high-resolution satellite sensors such as NOAAAVHRR, Terra MODIS, Landsat TM. This kind of traditional remote sensing data has been used tomake better crop management, monitor the growing stress, and estimate the yield (Hirata, 2009).
Furthermore, for the last decade, the research methodology and data analysis techniques fromtraditional remote sensing have been used to process aerial images with much higher spatial andtemporal resolutions taken by Unmanned Aerial Vehicles (UAVs). This rapid development of remotesensing and precision agriculture provide aerial imagery with various resolution.
However, a few studies have estimated CC with UAV-obtained NDVI. It is still unclear if UAVbased NDVI has the same linear regression relationship with CC as satellite-based NDVI. To apply
both satellite-sensed and UAV-sensed CC data to crop simulation models such as Aqua Crop, it isnecessary to unravel whether the relationship between NDVI and CC remains the same under
different ground resolutions. Therefore, This paper processed the UAV-sensed data into different
resolutions, and compared the regression relationships between NDVI and CC.
METHODOLOGY
Study Site
This study was conducted in the experimental field of the Obihiro University of Agriculture andVeterinary Medicine located in Obihiro City, Hokkaido, Japan (143.1709-143.1747°N, 42.869842.8671°E; Fig.1). The experimental field has a total area of 3.2 ha (200 m×160 m), separated into
multiple sectors planted with various experimental crops. The peanuts sector inside the experimental
field was selected as the study site to compare NDVI with CC. The peanuts usually have relatively
spreading forms of about 30-50 cm high with long branches that grow close to the ground. This plant
form makes peanut a good objective to study the relationship between NDVI and CC. Previous study
shows that the NDVI tends to perform poor correlation to CC when the Leaf Area Index (LAI) value
is high. In other words, if the leaf density under the vegetation canopy varies, the NDVI value could
be different even though the CC value stays the same (Purevdorj et al., 1998). This kind of variationof LAI is relatively unapparent in peanuts because peanuts tend to grow with a horizonal pattern
rather than a vertical pattern. The peanut field area is 1600m2 (40 m×40 m), with a plant density of
7.7 plant/m2. The surface of the planting area was covered by white mulch sheets made by plastic
films, because insolation was important during the early stage of growth to ensure the basic
vegetation growth of peanuts in low temperature region such as Hokkaido.

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Fig. 1 Location and details of the study site
Investigation and Analyses
The RGB imagery of the experimental field was taken by Phantom 4 Pro (DJI) on 31st July 2019,
and the reflectance imagery was made by a portable multispectral camera “Sequoia” (Parrot), which
was mounted on Inspire 1(DJI) on 1st August 2019. The flight data is shown in Table 1.
Table 1 Flight conditions
Equipment

Date

Phantom 4 Pro
Inspire 1 with Sequoia

31th July
1st August

Camera heightfrom ground (m)
50
40

Speed
(m/s)
4.8
3.0

Overlap (%)
Top
Side
80
80
80
80

Resolution(cm/pixel)
1.3
5.9

NDVI and CC
After obtaining aerial imagery, RGB orthomosaic image and reflectance map of the experimental
field were generated with the photogrammetric software, Pix4D Mapper 4.6.4 (Pix4D). The RGB
orthomosaic image was used to separate the vegetation, soil and mulch films in ArcGIS Pro 2.3.0(Esri), with a supervised image classification tool. The result of classification is shown in Fig.3.
Based on the classified raster, the CC value of the peanuts field was calculated using Eq. 1.
𝐶𝐶 =𝑉𝑒𝑔𝑒𝑡𝑎𝑡𝑖𝑜𝑛
𝑉𝑒𝑔𝑒𝑡𝑎𝑡𝑖𝑜𝑛 + 𝑆𝑜𝑖𝑙 + 𝑀𝑢𝑙𝑐ℎ 𝑓𝑖𝑙𝑚

(1)

Where “Vegetation,” “Soil,” and “Mulch film” mean the number of pixels covered by green
vegetation canopy, soil, and mulch films, respectively. To obtain the CC and NDVI values under
different ground resolutions, we divided the peanut field into squared grids with a side length of 0.5
m, 1.0 m, 2.5 m, 5.0 m, and 10 m. As an example, the 1.0 m grids are shown in Fig.4. Based on thegeoreferenced reflectance map, the NDVI values were calculated by Eq. 2.
𝑁𝐷𝑉𝐼 =(2)

𝑁𝐼𝑅 − 𝑅𝑒𝑑𝑁𝐼𝑅 + 𝑅𝑒𝑑

Where “NIR” and “Red” mean the reflectance volume of the near-infrared region and the redregion. The relationship between NDVI and CC values of each grid’s size was determined using aleast-squares fitting algorithm with python 3.7. An Analysis of Covariance (ANCOVA) was carriedout to testify if there is a significant difference between NDVI and CC relationships under different
ground resolutions. Finally, the accuracy of the regression equation was verified using RMSE.

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Fig. 3 Classification result (Left: RGB orthomosaic image; Right: Classified raster)Fig. 4 Example of squared grid dividing the peanuts field (Grid size: 1.0 m)
RESULTS AND DISCUSSION
Fig. 5a and Fig. 5b show the spatial distribution of NDVI and vegetation cover under the original
resolution of the peanuts field. NDVI tended to be high in the area covered by vegetation and low in
the area covered by soil or mulch films. This is because the vegetation surface has a lower reflectance
rate in the red region and a higher reflectance in the near-infrared region. In contrast, the soil and theplastic mulch films have similar reflectance in both regions. Besides, the mulch film has a lower
NDVI than soil because the PVC material has a relatively higher reflectance of red, and at themeantime, a lower reflectance of near infrared than soil (Corradini et al., 2019). The spatial
distribution of NDVI of the other grid sizes (0.5m, 1.0m, 2.5m, 5.0m, and 10m) showed the sametendency. The NDVI value varied from -0.47 to 0.68 under the original resolution, from -0.37 to 0.61
under 0.5 m grid size, from -0.29 to 0.40 under 1.0 m, grid size, from -0.25 to 0.24 under 2.5 m gridsize, from -0.10 to 0.13 under 5.0 m grid size, and from -0.05 to 0.08 under 10 m grid size. Unlike
the crops or forests with the vertical growth pattern, the maximum NDVI value of peanuts was lessthan 0.7. This is because peanuts have low-height, wide-expanding, and horizontal-trained canopies,
which cause relatively low LAI within the canopies. The CC values varied from 0.00 to 1.00 under
the original resolution, from 0.00 to 1.00 under 0.5 m grid size, from 0.00 to 0.74 under 1.0 m gridsize, from 0.03 to 0.53 under 2.5 m grid size, from 0.14 to 0.42 under 5.0 m grid size, and from 0.19
to 0.35 under 10 m grid size. The range of both NDVI and CC values decreased with grid sizes.

Fig. 5 Spatial distribution of NDVI (a) and vegetation cover (b)Ⓒ ISERD

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Fig. 6a to Fig. 6e show the correlation between NDVI and CC under each grid size. NDVI wasstrongly correlated with CC under the resolution of 0.5m, 1.0m, 2.5m, 5.0m, and10m (R2=0.88**,
0.92**, 0.94**, 0.89**, and 0.93**, respectively). The shape of the linear regression line (y=ax+b)of NDVI and CC closely resembled each other; the slopes (a) such as 1.16, 1.11, 1.09, 1.08, and1.06, respectively, and the intercepts (b) such as 0.25, 0.25, 0.25, 0.25, and 0.25, respectively. The
incept values indicate that a grid with 25 percent of it covered by peanuts canopies has an
approximately NDVI value of 0. The slope values slightly decreased with the increasing grid size,
resulting in the grid’s NDVI values without any vegetation cover varying from 0.5m to 10m (-0.21,-0.22, 0.23, -0.23, and -0.24 respectively). This difference of slopes is considered to be caused by
two kinds of abnormal values of NDVI. One was the abnormally high NDVI value due to relatively
high LAI. The other one was the abnormally low NDVI value caused by the mulch sheets. These twokinds of abnormal NDVI became outliers when the grid size was small, because there were grids that
include only canopies or only plastic. However, they cancelled each out when the grid size was large,
so that the regression line was closer to the ideal state where there were simply vegetation and soil.

Fig. 6 Relationship between NDVI and CC
To testify the significance of each regression equation’s differences, an ANCOVA was
conducted with an Excel data analysis add-in, XLSTAT (ver 2020.5.1, Addinsoft), where CC as thedependent variable, while NDVI and ground resolution as the explanatory variables. The result isshown in Table 2. The p-value of all kinds of grid sizes except for 10.0 m was near 1.000, indicatingthat the grid sizes have no significant effect on NDVI and CC’s relationship.
Table 2 Model parameters of ANCOVA
FactorCoefficientIntercept
NDVI
Ground Resolution-0.5
Ground Resolution-1
Ground Resolution-3
Ground Resolution-5
Ground Resolution-10

24.775115.735-0.021
0.004
0.078
0.000
0.000

Standard
deviation
1.980
0.466
1.983
1.990
2.072
2.214
1.310

Ⓒ ISERD126t

Pr > |t|12.512248.448-0.011
0.002
0.038
0.000
0.000

<0.0001<0.0001
0.991
0.998
0.970
1.000
1.000

IJERD – International Journal of Environmental and Rural Development (2021) 12-2

Therefore, despite the slight difference between the regression equations of the five kinds ofgrid sizes, it is considered that the NDVI value of peanuts remains the same relationship with CC
under different ground resolution. Since the offset effect of two abnormal values of NDVI was mostremarkable at the 10 m grids, the equation derived from the data of 10m grid size was used to predict
CC using NDVI. The RMSE of CC estimation of each grid size from 0.50 m to 10 m was 0.081,
0.089, 0.048, 0.025, 0.020, 0.014, respectively.
CONCLUSION
Herein, we analyzed the relationships between NDVI and CC values of peanuts in the experimental
field using UAV-sensed data under five kinds of ground resolutions. As a result, the NDVI showed ahighly correlated linear relationship with CC under each ground resolution. Slight differences ofslopes and intercepts were found between the regression equations, however this kind of difference
was found not significant due to an ANCOVA. The regression equation of 10 m grid size performeda moderate estimation accuracy of CC with the RMSE less than 0.01. This result demonstrated that
CC estimation tend to keep consistent despite of the change of resolution, suggesting the possibility
that both UAV-sensed and satellite-sensed NDVI could be used to estimate CC for the usage of crop
simulation models such as Aqua Crop.
ACKNOWLEDGEMENTS
We would like to express our gratitude to Dr. Masahiro AKIMOTO (Obihiro University ofAgriculture and Veterinary Medicine) for providing the experimental field. This research was
supported by JSPS KAKENHI (Grant Number 20K06351), the joint usage/research program of theInstitute of Materials and Systems for Sustainability (IMaSS) in Nagoya University, and the strategic
research project founded by Tokyo NODAI.
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Agricultural Water Management,27 (1), 55.
Corradini, F., Bartholomeus, H., Lwanga, E.H., Gertsen, H. and Geissen, V. 2019. Predicting soil microplastic
concentration using vis-NIR spectroscopy. Science of the Total Environment, 650, 922-932.
Eskandari, S., Reza Jaafari, M., Oliva, P., Ghorbanzadeh, O. and Blaschke, T. 2020. Mapping land cover andtree canopy cover in Zagros Forests of Iran: Application of Sentinel-2, google earth, and field data. Remote
Sensing, 12 (12), 1912.
Food and Agriculture Organization (FAO). 2012. Crop yield response to water. FAO Irrigation and Drainage
Paper, FAO, Retrieved from http://www.fao.org/documents/card/en/c/c355da16-217c-555b-acbc-505d87
bade00/
Hirata, Y. 2009. Uses of high spatial resolution satellite data to forest monitoring. Journal of the Japanese Forest
Society, 91 (2), 136-146.
Mulla, D.J. 2013. Twenty five years of remote sensing in precision agriculture: Key advances and remaining
knowledge gaps. Biosystems Engineering, 114 (4), 358-371.
Purevdorj, T.S., Tateishi, R., Ishiyama, T. and Honda, Y. 1998. Relationships between percent vegetation coverand vegetation indices. International Journal of Remote Sensing, 19 (18), 3519-3535.
Recanatesi, F., Giuliani, C. and Ripa, M.N. 2018. Monitoring Mediterranean oak decline in a peri-urban
protected area using the NDVI and Sentinel-2 images: The case study of Castelporziano State natural
reserve. Sustainability, 10 (9), 3308.
Steduto, P., Hsiao, T.C., Raes, D. and Fereres, E. 2009. AquaCrop - The FAO crop model to simulate yield
response to water: I. Concepts and underlying principles. Agronomy Journal, 101 (3), 426-437.
Trout, T.J., Johnson, L.F. and Gartung, J. 2008. Remote sensing of canopy cover in horticultural crops.
HortScience, 43 (2), 333-337.

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Xu, R., Li, C. and Paterson, A.H. 2019. Multispectral imaging and unmanned aerial systems for cotton plant
phenotyping. PloS one, 14 (2), 0205083.
Zhao, D., Huang, L., Li, J. and Qi, J. 2007. A comparative analysis of broadband and narrowband derived
vegetation indices in predicting LAI and CCD of a cotton canopy. ISPRS Journal of Photogrammetry andRemote Sensing, 62 (1), 25-33.

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Research article
erd

Establishment of Optimized Manufacturing Conditions for
Cooked Rice -Part I- Equilibrium Moisture Content and
Latent Heat of Vaporization of Cooked RiceYOSHIKI MURAMATSU*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Email: y-murama@nodai.ac.jp

MASANORI HASHIGUCHI
Keisoku Engineering System Co., Ltd., Tokyo, JapanDAHAI MI
Keisoku Engineering System Co., Ltd., Tokyo, JapanSOKLY SORM
Graduate School of Agriculture, Tokyo University of Agriculture, Tokyo, JapanEIICHIRO SAKAGUCHI
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, JapanSHOTARO KAWAKAMI
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Received 6 November 2020

Accepted 15 October 2021(*Corresponding Author)

Abstract The equilibrium moisture contents of cooked milled rice in the desorption process
were measured at several temperatures (20-60°C) and relative humidity levels (10-86%) bya static method. The equilibrium moisture content of the sample increased with increasing
equilibrium relative humidity at a constant temperature and increased with a decrease intemperature at any given equilibrium relative humidity. The Chen-Clayton equation, which
is a sorption isotherm, was used to express the relationship between the equilibrium moisture
content of the sample, equilibrium relative humidity, and absolute temperature. The latent
heat of vaporization of water for the cooked rice was calculated by using the Chen-Clayton
equation and thermodynamic theory (Clapeyron equation). At a moisture content of 15-30%(d.b.) (d.b.: the amount of water per unit mass of dry matter present in the material), the latent
heat of vaporization of the sample decreased almost exponentially with an increase inmoisture content. For samples at a moisture content above 50% (d.b.), the values of latent
heat of vaporization sufficiently approached that of free water.
Keywords equilibrium moisture content, sorption isotherms, latent heat of vaporization,
Chen-Clayton equation, Clapeyron equation, cooked milled rice

INTRODUCTION
The development of processed food made from rice at production location is expected to lead toregional revitalization and increased income for farmers. A simply processed food made from rice isdried cooked rice or pregelatinized rice. A general manufacturing process of dried cooked rice is asfollows: 1) washing raw rice, 2) soaking the washed rice in water, 3) cooking or steaming the rice(the raw rice starch is changed to pregelatinized starch), 4) separating the rice kernel from the massof cooked rice to a single cooked rice, and 5) drying the cooked rice. The dried cooked rice is usuallyrehydrated with water or hot water and then eaten.
Recently, food that can be kept in case of emergency has been developed and manufactured inJapan to prevent food shortage in the case of natural disasters and infectious diseases. The interest inⒸ ISERD

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dried cooked rice has increased as it can be used in preserved food, portable ration food, andemergency provisions. In addition, dried cooked rice has been used as a material in instant foodproducts, for example, an instant pot dried rice similar to an instant pot noodle; thus, the market ofdried cooked rice products has continued to increase. The data of the drying characteristics,
equilibrium moisture content, latent heat of vaporization for cooked rice, and water absorption(rehydration) characteristics of dried cooked rice are required for optimizing processing operations,designing equipment, and ensuring high quality.
We measured the equilibrium moisture content of the cooked rice, the hot air-drying
characteristics of the cooked rice, and the water absorption characteristics of the dried cooked rice.
This basic information is needed to establish the optimized manufacturing conditions for cooked rice.
The latent heat of vaporization of water for cooked rice was calculated based on the thermodynamic
theory by using the equilibrium moisture content data. The moisture transfer kinetics during thedrying and the water absorption was analyzed based on the drying theory of the first falling rate
period or the first-order reaction rate theory. The equilibrium moisture contents are needed to analyze
the hot air-drying characteristics in addition to examining food preservation. Because the changes inmoisture content occur during the drying and the water absorption process, kinetic analysis to predictthe changes in moisture content are required to optimize the processing conditions. We reported theequilibrium moisture content and the latent heat of vaporization of water in this part I and will report
the moisture transfer kinetics in next part II.
To determine the storage conditions and analyze the drying process, it is necessary to know the
relationship between the equilibrium moisture content (EMC) in the foodstuffs and the equilibrium
relative humidity (ERH) of the drying air or aeration air at a given temperature. This relationship is
described by sorption isotherm equations (Sun and Woods, 1993). Knowledge of the moisturesorption isotherms of foodstuffs is valuable in solving food processing and engineering problems
such as equipment design, drying, and storage processes as well as predicting shelf life (Arogba,
2001). The latent heat of vaporization (LHV) of water in foodstuffs is important for the design ofdrying equipment (Chen, 2006). The LHV is neither constant nor equal to the heat of pure water
evaporation because the LHV is a function of temperature and moisture content, i.e., the LHV varies
throughout the drying process (Rückolda et al., 2003). The LHV can be calculated by using thesorption isotherm equations and Clapeyron thermodynamic theory (Murata et al., 1988; Tagawa etal., 1993). Koide et al. (2016) reported the EMCs for dried cooked rice in the absorption process.
However, little research has been reported on the EMC and LHV for cooked rice.
In this study, the EMCs of cooked rice (short grain rice, japonica) in the desorption process were
measured at several temperatures and relative humidity levels, and the LHV of water for the cookedrice was calculated by using the measured results of EMC and thermodynamic theory.
OBJECTIVE
The objectives of this study were 1) to evaluate the relationship between the EMC, ERH, andtemperature and 2) to estimate the LHV of water by using the thermodynamic theory.
METHODOLOGY
SampleNon-glutinous rough rice (cv. “Hoshinoyume”) was purchased from a Japanese agricultural
cooperative in Tohma, Hokkaido, Japan (JA Tohma) and was stored in a refrigerator at approximately
5°C until the test. The “Hoshinoyume” was widely cultivated in Hokkaido when we conducted thisresearch because this rice had a good eating quality or tasty. This non-glutinous rough rice was firsthulled with a roll-type rice huller (THU35B, Satake Co., Ltd.). Brown rice (800 g) was put into anabrasive-type (stir-type) rice-milling machine (SKM-5B (1), Satake Co., Ltd.) and milled for 5.0 min
to produce milled rice. The degree of milling (or milling yield) was adjusted to be approximately
92%.
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The milled rice was cooked with commercial rice cookers (NP-FB10, Zojirushi Co., Ltd.) in
accordance with the operation manual of the rice cooker. To uniformly gelatinize the rice, the rice
was soaked in tap water at room temperature for 1 h before cooking. The cooking time was 45-60
min and the maximum temperature in the rice cooker was around 104°C. To obtain a single grain of
cooked rice from the mass of cooked rice, the cooked rice was rinsed with tap water for 3 s, and theexcess water was drained. After the rinse, the surface of the cooked rice was wiped with Kimwipes ®
(S-200, Nippon Paper Crecia Co., Ltd.) to remove excess water.
Equilibrium Moisture Content (EMC)
The EMCs of the cooked rice in the desorption process were measured by a static method (Murata
et al., 1988; Tagawa et al., 1993) at three temperatures (20, 40, and 60°C) and ten relative humidity
levels ranging from 10% to 86%. The temperature was controlled with an incubator (IN802, Yamato
Scientific Co., Ltd.). Ten kinds of saturated salt solutions (NaOH, LiCl, CH3COOK, MgCl2, K2CO3,
NaBr, NaNO2, NaNO3, NaCl, KCl) were used to maintain the particular relative humidity in each
vessel. Each saturated salt solution presents different vapor pressure or relative humidity at eachtemperature in a closed container. The relative humidity ranges for each saturated salt solution were
4-7% for NaOH, 10-12% for LiCl, 19-24% for CH3COOK, 29-34% for MgCl2, 42-45% for K2CO3,
49-60% for NaBr, 58-66% for NaNO2, 67-76% for NaNO3, 74-76% for NaCl, and 80-86% for KCl.
The relative humidity data of these saturated salt solutions are shown in the references (Arai et al.,
1976; Tagawa et al., 1993; Tanaka, 1998). Approximately 10 g of the sample was suspended in a 1
L wide-mouth bottle containing a selected saturated salt solution to maintain a constant humidity ata constant temperature. The sample was weighed on a digital balance (ER-182A, A&D Co., Ltd.) atintervals of 2 or 3 days. Equilibrium was considered to be reached when the change in weight wasless than 0.2 mg between two successive measurements. In this method, it took approximately 30
days for a sample to reach the EMC. The EMC of the sample was determined using a forced hot air
oven (DX-600, Yamato Scientific Co., Ltd.) at 135°C for 24 h.
RESULTS AND DISCUSSION
Relationship among the Equilibrium Moisture Content (EMC), Equilibrium Relative
Humidity (ERH), and Temperature in the Desorption Process
The relationship between the EMC and ERH is usually expressed by means of a sorption isotherm.
The moisture desorption isotherms of the sample at three different temperatures are presented in Fig.
1. As shown in Fig. 1, the EMC increased with increasing ERH at a constant temperature andincreased with a decrease in temperature at any given ERH.
Several mathematical descriptions of the sorption data have been developed for different ranges
of ERH in regard to different agricultural products (Chakraverty & Singh, 2014). The Chen-Clayton
equation (Chen & Clayton, 1971), which is a sorption isotherm, closely fit measured EMC data of
the six kinds of grains (Murata et al., 1988; Tagawa et al., 1993). The Chen-Clayton equation is asfollows:

rh = exp − f1T g1 exp ( − f 2T g2 M e )(1)where rh: equilibrium relative humidity (-), T: absolute temperature (K), Me: equilibrium moisture
content (% (d.b.), d.b.: the amount of water per unit mass of dry matter present in the material), and f1,
f2, g1, and g2: parameters.
The measured EMC data of the sample were fitted to Eq. (1) using a nonlinear least squares
method (false position method). The goodness of fit was evaluated by the values of the root meansquared error (RMSE). The values of the parameters in Eq. (1) were: f1 = 50.61, f2 = 2.577×10-7, g1= -0.3675, and g2 = 2.326. The solid lines in Fig. 1 are the results calculated from Eq. (1). As isevident from Fig. 1, the agreement between the experimental and predicted values of Eq. (1) wasⒸ ISERD

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found to be satisfactory (RMSE = 0.022). The relationship between the EMC of the sample in thedesorption process, ERH, and absolute temperature was expressed by Eq. (1).

Fig. 1 Moisture desorption isotherms of the sample at three different temperatures
Latent heat of Vaporization (LHV) of Water
Because Eq. (1) satisfactorily correlated the experimental sorption data of the sample within the rangeof measurement conditions, Eq. (1) was used to calculate the LHV of water for the sample. The LHV
was determined by the same method as Murata et al. (1988) and Tagawa et al. (1993). The Clapeyron
equation for vapor-liquid equilibrium is written as follows:

dpst
hv
=
dT T ( vg − vl )(2)

where pst: the water vapor pressure in the sample (Pa), Δhv: the latent heat of vaporization (J/kg), vg:
the specific volume of water vapor (m3/kg), and vl: the specific volume of liquid water (m3/kg).
To calculate the LHV (Δhv), Eq. (3) was rewritten from Eq. (2).

hv = ( vg − vl )  T 

dpst
dT

(3)

In Eq. (3), the vapor pressure of the moisture in the sample at a given psychrometric condition(pst) was determined from Eqs. (1) and (4).

pst = rh  ps

(4)

Where pst: the water vapor pressure in the sample (Pa) and ps: the saturated vapor pressure (Pa).
The saturated vapor pressure (ps) in Eq. (4) is a function of temperature only. The saturated vapor
pressure (ps) in Eq. (4), along with the specific volume of water vapor (vg) and specific volume ofliquid water (vl) in Eq. (3) were calculated by using the IFC formulation for industrial use (The Japan
Society of Mechanical Engineers, 1980) and the equilibrium relative humidity (rh) in Eq. (4) was
determined by Eq. (1). The values of dpst/dT in Eq. (3) was obtained by differentiating pst in Eq. (4)with respect to the absolute temperature (T).

dpst drhdp=
ps + s rh
dT
dT
dT

(5)

The drh⁄dT value in Eq. (5) was obtained by differentiating rh in Eq. (1) with respect to T as
shown by Eq. (6).

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IJERD – International Journal of Environmental and Rural Development (2021) 12-2drh
= − rh  exp ( − f 2T g2 M e )  ( f1 g1T g1 −1 − f1 f 2 g 2T g1 + g2 −1M e )dT(6)

In addition, the dps/dT value in Eq. (5) was calculated by differentiating ps with respect to T,
where ps was obtained from the IFC formulation (The Japan Society of Mechanical Engineers, 1980).
The LHV isotherms of the sample are shown in Fig. 2, and the LHV values calculated from Eq.
(3) for three temperatures is plotted against the moisture content. Though these isotherms wereobtained by extrapolating the data at moisture contents above 25% (d.b.), they showed that the LHV
decreased as temperature increased. At a moisture content of 15-30% (d.b.), the LHV of the sample
decreased almost exponentially with an increase in moisture content, and at a moisture content above
50% (d.b.), the LHV sufficiently approached that of free water. This tendency of LHV versus
moisture content is in agreement with the results of Murata et al. (1988) and Tagawa et al. (1993) for
grains. The values of LHV for cooked rice were almost the same degree with the grains and beans
reported by Murata et al. (1988) and Tagawa et al. (1993). For the sample with a moisture content
above 50% (d.b.), it seemed reasonable to assume that the LHV of the sample was equal to that offree water. Since the LHV is the amount of energy required to remove water from a solid, the higher
the LHV, the more tightly bound the water is. The LHV was a function of both temperature andmoisture content, i.e., the values varied throughout the drying process. Through the utilization of Eqs.
(1) and (2), the LHV of the sample could be estimated as a function of both temperature and moisture
content. The LHV of water is the amount of energy (enthalpy) that must be added to a liquid
substance, to transform a given quantity of the substance into gas. The energy necessary to add tothe drying process can be estimated based on the values of the LHV. This energy calculation leads
to the optimization of the manufacturing condition for the cooked rice.

Fig. 2 Latent heat of vaporization of water for the sample calculated from Eq. (3)CONCLUSION
The equilibrium moisture contents (EMCs) of the cooked rice in the desorption process were
measured by a static method at three temperatures (20, 40, and 60 °C) and ten relative humidity levels
ranging from 10-86 %. The Chen-Clayton equation was used to express the relationship among the
EMC of the sample in the desorption process, equilibrium relative humidity, and absolutetemperature. Using the measured results of the EMC, the latent heat of vaporization of water in thesample (LHV) was calculated5 by the Clapeyron thermodynamic theory. The values of LHV
decreased almost exponentially with an increase in moisture content from 15-30 % (d.b.) andsufficiently approached that of free water at a moisture content above 50 % (d.b.).
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salt solutions. J. Chem. Eng. of Japan, 9 (4), 328-330.
Arogba, S.S. 2001. Effect of temperature on the moisture sorption isotherm of a biscuit containing processedmango (Mangifera indica) kernel flour. J. Food Eng., 48 (2), 121-125.
Chakraverty, A. and Singh, R.P. 2014. Theory of grain drying. In Postharvest Technology and Food Process
Engineering, CRC Press, 31-74, Florida, USA.
Chen, C. 2006. Obtaining the isosteric sorption heat directly by sorption isotherm equations. J. Food Eng., 74(2), 178-185.
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Koide, S., Orikasa, T., Koide, F., Muramatsu, Y. and Tagawa, A. 2016. Moisture content prediction of driedcooked rice during drying, preservation, and water absorption. J. Japan Assoc. Food Preservation Scientists,
42 (2), 59-64.
Murata, S., Tagawa, A. and Ishibashi, S. 1988. An equation for calculating the latent heat of vaporization ofwater in cereal grains. J. Japanese Soc. Agric. Machinery, 50 (3), 85-93.
Rückolda, S., Isengard, H.D., Hanss, J. and Grobecker, K.H. 2003. The energy of interaction between waterand surfaces of biological reference materials. Food Chem., 82 (1), 51-59.
Sun, D.W. and Woods, J.L. 1993. The moisture content/relative humidity equilibrium relationship of wheat A review. Drying Tech., 11 (7), 1523-1551.
Tagawa, A., Murata, S. and Hayashi, H. 1993. Latent heat of vaporization in buckwheat using the data ofequilibrium moisture content. Trans. ASAE, 36 (1), 113-118.
Tanaka, C. 1998. Thermodynamic properties of foods. Master Thesis, Tokyo University of Agriculture,
Hokkaido.
The Japan Society of Mechanical Engineers. 1980. 1980 SI JSME steam table (4th edition). The Japan Societyof Mechanical Engineers, Tokyo.

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Research article
erd

Establishment of Optimized Manufacturing Conditions for
Cooked Rice -Part II- Moisture Transfer Kinetics of Cooked
Rice when Drying and Soaking in Water
YOSHIKI MURAMATSU*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Email: y-murama@nodai.ac.jp

MASANORI HASHIGUCHI
Keisoku Engineering System Co., Ltd., Tokyo, JapanDAHAI MI
Keisoku Engineering System Co., Ltd., Tokyo, JapanSOKLY SORM
Graduate School of Agriculture, Tokyo University of Agriculture, Tokyo, JapanEIICHIRO SAKAGUCHI
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, JapanSHOTARO KAWAKAMI
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Received 6 November 2020

Accepted 15 October 2021(*Corresponding Author)

Abstract The thin-layer drying characteristics of cooked milled rice during hot air drying
were measured at four temperatures (30, 40, 50, and 60 °C) and at a relative humidity of 40%.
The hot air-drying process of the sample was composed of the first falling rate, and theexponential model was applied to predict the changes in moisture content of the sample ateach temperature. The drying rate constant of the sample increased as temperature increased
and was expressed as an Arrhenius-type equation. The water absorption characteristics ofdried cooked milled rice when soaking in water were examined at four temperatures (70, 80,
90, and 98 °C). The ratios of the changes in moisture content from 8 to 150% (d.b.) wereconverted from the data of changes in moisture content. The first-order reaction rate equation
could be applied to explain the water absorption process of samples. The water absorption
rate constant had a tendency to increase with increasing soaking temperature and was
expressed as a function of soaking temperature by an Arrhenius-type equation.
Keywords cooked milled rice, hot air drying, dried milled rice, water absorption, exponential
model, first-order rate constant

INTRODUCTION
The development of processed food made from rice at production location is expected to lead toregional revitalization and increased income for farmers. A simply processed food made from rice isdried cooked rice or pregelatinized rice. A general manufacturing process of dried cooked rice is asfollows: 1) washing raw rice, 2) soaking the washed rice in water, 3) cooking or steaming the rice(the raw rice starch is changed to pregelatinized starch), 4) separating the rice kernel from the massof cooked rice to a single cooked rice, and 5) drying the cooked rice. The dried cooked rice is usuallyrehydrated with water or hot water and then eaten.
Recently, food that can be kept in case of emergency has been developed and manufactured inJapan to prevent food shortage in the case of natural disasters and infectious diseases. The interest in
dried cooked rice has increased as it can be used in preserved food, portable ration food, andⒸ ISERD

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emergency provisions. In addition, dried cooked rice has been used as a material in instant foodproducts, for example, an instant pot dried rice similar to an instant pot noodle; thus, the market ofdried cooked rice products has continued to increase. The data of the drying characteristics,
equilibrium moisture content, latent heat of vaporization for cooked rice, and water absorption(rehydration) characteristics of dried cooked rice are required for optimizing processing operations,designing equipment, and ensuring high quality.
We measured the equilibrium moisture content of the cooked rice, the hot air-drying
characteristics of the cooked rice, and the water absorption characteristics of the dried cooked rice.
This basic information is needed to establish the optimized manufacturing conditions for cooked rice.
The latent heat of vaporization of water for cooked rice was calculated based on the thermodynamic
theory by using the equilibrium moisture content data. The moisture transfer kinetics during thedrying and the water absorption was analyzed based on the drying theory of the first falling rate
period or the first-order reaction rate theory. We had reported the equilibrium moisture content andthe latent heat of vaporization of water in part I (Muramatsu et al., 2021). The equilibrium moisture
contents are needed to analyze the hot air-drying characteristics in addition to examining foodpreservation. Because the changes in moisture content occur during the drying and the water
absorption process, kinetic analysis to predict the changes in moisture content are required to
optimize the processing conditions. The moisture transfer kinetics was reported in this Part II. The
equilibrium moisture content data reported in Part I was used in the analysis of the moisture transfer
kinetics during drying.
Ramesh and Rao (1996) examined the drying of cooked rice (high amylose variety rice) with avibro-fluidized bed drier. Luangmalawat et al. (2008) reported on the effect of temperature on thedrying characteristics and quality of cooked rice (Jasmin rice: long grain rice, indica rice). Jiao et al.
(2014) used convective hot air, microwave, and combined microwave-hot air drying techniques forthe drying of cooked rice (hybrid indica rice) and evaluated the efficacy of these techniques. Jiao etal. (2014) also investigated the effect of microwave power and air temperature on the drying andrehydration kinetics of dried cooked rice and examined the changes in the color values of the productafter drying. Koide et al. (2016) measured the changes in the moisture content of cooked rice during
hot air drying and changes in the moisture content of dried cooked rice during water adsorption.
Almost all previous papers have reported the drying characteristics of indica rice. Additionally, thedrying characteristics of many kinds of food have been measured, and many mathematical models,
are used to describe the drying process of food. Optimum drying and water absorption models
including the values of parameters, are particularly useful for easily predicting the changes in the
moisture content of materials. Therefore, knowing the optimum model is important for practical use.
In this study, we examined the thin-layer hot air-drying characteristics of cooked milled rice
(short grain rice, japonica) at four different temperatures. In addition, the water absorption(rehydration) characteristics of dried cooked milled rice were also measured at four different
temperatures.
OBJECTIVE
The objectives of this study were 1) to examine the hot air-drying and the water absorption
characteristics at several temperatures, 2) to derive a suitable mathematical drying and water
absorption models to describe changes in moisture content, and 3) to evaluate the relationshipbetween the drying rate constant or the water absorption rate constant and temperature.
METHODOLOGY
SampleNon-glutinous rough rice (cv. “Hoshinoyume”) was purchased from a Japanese agricultural
cooperative in Tohma, Hokkaido, Japan (JA Tohma) and was stored in a refrigerator at approximately
5 °C until the test. The “Hoshinoyume” was widely cultivated in Hokkaido when we conducted thisⒸ ISERD

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research because this rice had a good eating quality or tasty. This non-glutinous rough rice was firsthulled with a roll-type rice huller (THU35B, Satake Co., Ltd.). Brown rice (800 g) was put into anabrasive-type (stir-type) rice-milling machine (SKM-5B (1), Satake Co., Ltd.) and milled for 5.0 min
to produce milled rice. The degree of milling (or milling yield) was adjusted to be approximately
92%.
The milled rice was cooked with commercial rice cookers (NP-FB10, Zojirushi Co., Ltd.) in
accordance with the operation manual of the rice cooker. To uniformly gelatinize the rice, the rice
was soaked in tap water at room temperature for 1 h before cooking. The cooking time was 45-60
min and the maximum temperature in the rice cooker was around 104 °C. To obtain a single grain of
cooked rice from the mass of cooked rice, the cooked rice was rinsed with tap water for 3 s, and theexcess water was drained. After the rinse, the surface of the cooked rice was wiped with Kimwipes ®
(S-200, Nippon Paper Crecia Co., Ltd.) to remove excess water.
Cooked milled rice was used for measuring the drying characteristics. Dried cooked milled rice
was used as a sample for the water absorption test. For the preparation of this dried milled rice,cooked milled rice was dried at a temperature of 40 °C and a drying time of 6 h with a commercial
hot air dryer (LH-103D, Satake Co., Ltd.).
Hot Air Drying Test

Fig. 1 Schematic of the hot air-drying apparatus
The changes in the moisture content of the cooked rice using the hot air-drying method were
measured at four temperatures (30, 40, 50, and 60 °C) and at a relative humidity of 40 %. Fig. 1
shows a schematic of the hot air-drying apparatus used in this study. The apparatus consisted of threeunits: a drying chamber at constant temperature and humidity, a ventilation unit, and a recording unit.
A constant temperature and humidity chamber (IG420, Yamato Scientific Co., Ltd.) was used as thedrying chamber. The drying chamber dimensions were a width of 500 mm, a length of 390 mm, anda height of 600 mm. The temperature and relative humidity in the drying chamber were measured
with a T-type thermocouple and a relative humidity sensor, and recorded with a data logger (GL200,
GRAPHTEC Co., Ltd.). The airflow rate in the chamber was adjusted to 2.0 m/s by a fan (CUDC
12B4, Japan Servo Co., Ltd.) using a DC power source (model 526, Metronix Co., Ltd.). The DC
power source was controlled with a timer (ELT-3, AS ONE Co., Ltd.), and the airflow was stopped
when the sample mass was measured. A grid screen was fitted below the fan to straighten the air
velocity pattern. Changes in mass, i.e., the changes in moisture content, when drying were measured
using a digital balance (EK-300i, A&D Co., Ltd.), and the changes in sample mass wereautomatically recorded on a personal computer. A stainless steel basket with a diameter of 100 mm,
a height of 15 mm, and a 3.0 mm aperture, was utilized as a sample tray.

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The sample (approximately 10 g) was placed on the tray. The drying test was terminated whenthe moisture content of the sample was approximately 15 %, on a dry basis (d.b.). The final moisture
content of the sample was determined using a forced hot air oven (DX-600, Yamato Scientific Co.,
Ltd.) at 135 °C for 24 h. Through the use of measured values of final moisture content, the changes
in mass when drying were converted to the moisture content of the sample.
Measurement of Water Absorption Characteristics
Moisture content changes of the dried cooked rice when soaking in water were measured at fourwater temperatures (70, 80, 90, and 98 °C). Approximately 5 g of sample was put into a sample net
after weighing the sample mass with a digital balance (FX-300, A&D Co., Ltd.), and soaked in awater bath (SH-12, TAITEC Co., Ltd.). The sample net was removed from the water bath at eachpreset soaking time (1.0, 2.0, and 5 min intervals), and the surface of the sample was wiped with
Kimwipes® (S-200, Nippon Paper Crecia Co., Ltd.) to remove residual liquid. The sample was thenreweighed. The increase in sample mass when soaking in water was considered to be an increase in
the moisture content of the sample. The moisture content of the sample after soaking was determinedfrom the values of the initial moisture content of the dried cooked rice and the mass changes datawhen soaking in water.
RESULTS AND DISCUSSION
Hot Air-Drying Characteristics
The moisture content of cooked rice decreased over elapsed time and exhibited a gentle downward
curve from the beginning of the drying process at each temperature. The changes in the moisture
content of the sample at four different temperatures (30-60°C) and at a relative humidity of 40% areshown in Fig. 2. The drying rate (% (d.b.)/h) of the sample was obtained by numerical differentiation(Gregory-Newton forward method) using the moisture content measurements. The drying rate of thesample increased with an increase in temperature. The linear relationship between the drying rate
and the free moisture content (|M-Me|) was found at each temperature. The above result indicates thatthe hot air-drying process of the sample comprises the first falling rate drying period.
Therefore, the measured drying data were fitted to the following exponential model (Eq. (1))(Koide et al., 2016) using the least squares method, and the values of the drying rate constant (k1)were determined at each temperature.

M − Me= exp ( −k1t )M0 − Me(1)

Where M: the moisture content at each preset time (% (d.b.)), M0: the initial moisture content(% (d.b.)), Me: the equilibrium moisture content (% (d.b.)), k1: the drying rate constant (h-1), and t:
the time (h). The values of Me in Eq. (1) was also calculated from following the equation (Muramatsu
et al., 2021). at each measurement condition.



rh = exp −50.61T −0.3675 exp ( −2.577  10−7 T 2.326 M e )(2)

The values of k1 and the root mean squared error (RMSE) of Eq. (1) are given in Table 1. The
solid line in Fig. 2 shows the results calculated from Eq. (1). As shown in Fig. 2, the measured results
matched well with the calculated results. Under all measurement conditions, the changes in the
moisture content of all samples caused by hot air drying could be estimated by Eq. (1).
The temperature dependency of k1 for grain (Murata, 1982) and beans (Muramatsu et al., 2007)
was expressed by the following Arrhenius-type equation:Ⓒ ISERD

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k1 = a1  exp  − 1 
 T

(3)

where a1 and b1 are parameters. Eq. (3) shows that the relationship between k1 and the reciprocal ofabsolute temperature (1/T) is approximately linear in a semilogarithmic plot. The values of k1 shownin Table 1 were fitted by the least squares method to Eq. (3). The values of the parameters and the
RMSE of Eq. (3) were: a1 = 772.5, b1 = 1838, and RMSE = 9.081×10-2. Eq. (3) was applicable for
examining the relationship between the drying rate constant and the temperature of the sample.

Fig. 2 Changes in the moisture content of the sample with drying
Table 1 Parameters in Eq. (1)Temperature (°C)
30
40
50
60

M0 (% (d.b.))
184.4
198.5
183.5
184.6

k1 (h-1)
1.746
2.311
2.506
3.115

Me (% (d.b.))
12.5
11.6
10.7
9.89

RMSE (% (d.b.))1.338
0.89951.052
0.6286

Water Absorption Characteristics
The initial moisture contents of the dried cooked rice were approximately 8 % (d.b.). The water
absorption curves of the sample are shown in Fig. 3. The moisture content of the sample increased
over time, exhibiting a gentle upward curve from the beginning of soaking, and did not approach
equilibrium under these measurement conditions. The water absorption rate of the sample increased
with an increase in soaking water temperature and on the other hand decreased with an increase insoaking time at each soaking temperature.
The moisture content of cooked rice (nonglutinous japonica rice) is usually approximately 65 %(w.b.), i.e., 150 % (d.b.). In this study, to evaluate the water absorption characteristics of the sample,
the ratios of the change in moisture content (Kubota, 1990) from 8 to 150 % (d.b.) (x) were calculated
from Eq. (4).

x=

M − M0M −8=
M T − M 0 150 − 8(4)Where x: the ratios of the change in moisture content from 8 to 150 % (d.b.), and MT: the target
or final moisture content (% (d.b.)). The values of x change from 0 to 1, and when “x = 1”, themoisture content of the sample has reached 150 % (d.b.).
The tendency of the changes in the values of x had the same with changes in the water absorption
rate. The values of x for the sample increased exponentially with an increase in soaking time.
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Therefore, the following first-order reaction rate equation (Kubota, 1990) was applied for analyzing
the water absorption characteristics of the sample.

dx= k2 (1 − x )dt(5)Where k2 is the water absorption rate constant (min-1). The unit of time (t) in Eq. (5) is “min”.
The values of k2 determined by the least squares method and the RMSE of Eq. (5) for eachtemperature are shown in Table 2. From the RMSE values, it was confirmed that the measured values
agreed well with those calculated from Eq. (5); thus, the ratios of changes in the moisture content of
the sample between 8 and 150 % (d.b.) could be estimated by Eq. (5).
The values of k2 shown in Table 2 increased with an increase in soaking temperature. The valuesof k2 were expressed as a function of temperature by using the following Arrhenius-type equation(RMSE = 0.04288).

 2606 
k2 = 681.0  exp  −

T 


(6)

Fig. 3 Changes in the moisture content of the sample during water absorption
Table 2 Parameters in Eq. (4)Temperature (°C)
70
80
90
98

k2 (min-1)
0.33400.46500.46630.6374

RMSE (-)
0.058930.054160.06033
0.05380

CONCLUSION
The thin-layer drying characteristics during hot air drying of cooked rice were measured at several
temperatures and relative humidity levels. The hot air-drying process of the sample was composedof the first falling rate, and the exponential model was applicable to predict the changes in moisture
content of the sample at each temperature. The drying rate constant of the sample increased as
temperature increased and was related to temperature by an Arrhenius-type equation.
The water absorption characteristics of dried cooked rice when soaking in water were measured
at four temperatures. The first-order reaction rate equation could be applied to explain the water
absorption process of samples. The water absorption rate constant was expressed as a function ofsoaking temperature by an Arrhenius-type equation.

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The changes in moisture content of the cooked rice during drying and the dried cooked rice
during water absorption can be easily predicted by using the drying model and the water absorption
model, respectively. These models will be useful in the determination of the endpoints or treatment
time for drying or water absorption. This information saves the input energy and the treatment time
and would lead to the establishment of optimized manufacturing conditions for cooked rice.
REFERENCES
Jiao, A., Xu, X. and Jin, Z. 2014. Modelling of dehydration-rehydration of instant rice incombined microwavehot air drying. Food and Bioproducts Processing, 92 (3), 259-265.
Koide, S., Orikasa, T., Koide, F., Muramatsu, Y. and Tagawa, A. 2016. Moisture content prediction of driedcooked rice during drying, preservation, and water absorption. J. Japan Assoc. Food Preservation Scientists,
42 (2), 59-64.
Kubota, K. 1990. Kinetics of quality conversion. In Reaction Engineering for Food, Kubota, K., Uno, J. andKobayashi, T. (Eds.), Tokyo, 1-45.
Luangmalawat, P., Prachayawarakorn, S., Nathakaranakule, A. and Soponronnarit, S. 2008. Effect oftemperature on drying characteristics and quality of cooked rice. LWT-Food Sci. Tech., 41 (4), 716-723.
Muramatsu, Y., Hashiguchi, M., Mi, D., Sorm, S., Sakaguchi, E. and Kawakami, S. 2021. Establishment of
optimizing manufacturing condition for cooked rice -Part I-, Equilibrium moisture content and latent heatof vaporization of cooked rice. Int. J. Environmental and Rural Development, 12 (1), 130-135.
Muramatsu, Y., Tagawa, A., Sakaguchi, E. and Kasai, T. 2007. Prediction of moisture content changes ofkidney beans during drying. J. Japan Assoc. Food Preservation Scientists, 33 (6), 295-302.
Murata, S. 1982. Characteristics of grain and estimation of drying rate. J. Japanese Soc. Agric. Machinery, 44(3), 517-523.
Ramesh, M.N. and Rao, S.P.N. 1996. Drying studies of cooked rice in a vibrofluidised bed drier. J. Food Eng.,
27 (4), 389-396.

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Research article
erd

Bamboo Charcoal as a Lactic Acid Bacteria Carrier for
Phosphate Removal
TAKAHIKO NAKAMURA
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan

NARONG TOUCH*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Email: nt207118@nodai.ac.jp
Received 8 January 2021

Accepted 15 October 2021(*Corresponding Author)

Abstract A decline in the demand for using bamboo products has led to abandoned bamboo
forests in Japan. To reduce the area of abandoned bamboo forests, the use of bamboo as aconstruction material and bamboo charcoal as an absorbent have gained considerable
attention in recent years. In the literature, many studies have described the formation of
biofilms on biochar, leading bamboo charcoal to be considered as a microbial carrier. The
aim of this study was to examine the potential of bamboo charcoal as the microbial carrier oflactic acid bacteria (LAB) for phosphate removal. Bamboo charcoal was immersed in a LAB
solution for 24 h for LAB to adhere to the bamboo charcoal. Then, the bamboo charcoal wasplaced in a bamboo fermented solution. Two types of bamboo charcoal, i.e., without
pretreatment and dissolved in tap water, were used in the experiments. The experiments werealso conducted with and without aeration to determine the effects of oxygenation. The
bamboo charcoal without pretreatment displayed an increase in the phosphate concentration,
indicating that phosphate was released from the bamboo charcoal. LAB-attached bamboo
charcoal demonstrated a much smaller increase in phosphate concentration, suggesting
phosphate was consumed by LAB. Experiments with dissolved bamboo charcoal also
indicated a reduction in the phosphate concentration. The removal rate of phosphatedecreased with an increase in the solution pH, suggesting that alkaline conditions limited theactivity of the bacteria. Furthermore, the redox potential of the solution became negative inthe solution without aeration. Overall, the results demonstrated that bamboo charcoal could
be a LAB carrier; however, the bamboo charcoal must be dissolved prior to its use forphosphate removal. Furthermore, aeration and an acidic during phosphate removal are needed
to obtain a higher removal rate when using LAB.
Keywords bamboo charcoal, microbial carrier, lactic acid bacteria, phosphate removal

INTRODUCTION
Although bamboo has been used in many different fields in Japan, a decrease in the demand forbamboo products has led to abandoned bamboo forests. According to a report by the Forestry Agencyof Japan, the total bamboo forest area in 2007 was approximately 1600 km2, which was 10% greaterthan in 1981. In 2007, the bamboo forest area covered approximately 0.6% of the total forest area inJapan, but up to 66% of the bamboo forest area was left unused. To reduce the area of abandoned
bamboo forests, several countermeasures have been proposed to increase the utilization rate ofbamboo. Historically, bamboo was primarily used as construction material and for household
furniture. In recent years, bamboo has been used as a fertilizer in agriculture (Cui and Wu, 2010; Liuet al., 2014), and bamboo biochar has been used as an absorbent for contaminant removal (Liu et al.,2012; Mohamed et al., 2015).
In previous reports, a large number of negative charges was observed on the surface of biochar(Yigit and Mazlum, 2007). These negative charges generate electrostatic repulsion between thebiochar surface and anions, making it difficult to adsorb phosphate ions on the surface. Furthermore,some kinds of biochar can release phosphate in aqueous solutions (Yao et al., 2012). For example,Ⓒ ISERD

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Jung et al. (2015) reported the release of phosphate from bamboo biochar. Therefore, when using
biochar for phosphate removal, it is necessary to modify the biochar surface with treatments using
acids, alkali, iron oxide, or magnesium ions (Stratful et al., 2001; Tansel et al., 2018). Biochar
impregnated with colloidal and nanosized metal oxyhydroxides can enhance the removal rate ofphosphate (Zhang and Gao 2013; Zhang et al., 2012). Dai et al. (2020) also reported phosphorus
removal in a solution using magnesium-modified biochar from bamboo. Li et al. (2020) reported theenhancement of phosphate adsorption using polyethyleneimine-modified biochar derived frombamboo biomass.
In addition to adsorption, the biological method is one of the various approaches for phosphateremoval. As biochar is a porous material, it can serve as a habitat for microorganisms (Egamberdieva
et al., 2018). Many studies have examined biofilm formation in biochar and its effect on soil
properties (Yang et al., 2019; Ajeng et al., 2020; Gorovtsov et al., 2020). According to the literature,
it is believed that organisms-attached biochar can increase the removal rate of phosphate in aqueous
solutions. However, to the best of our knowledge, there is a lack of information related to theemployment of organisms-attached bamboo charcoal for phosphate removal. In addition, as theefficacy of phosphate removal strongly depends on the properties of the biochar, a study of phosphateremoval capabilities is necessary before the widespread use of bamboo charcoal.
OBJECTIVE
This study examines the potential of bamboo charcoal as a microbial carrier for lactic acid bacteria(LAB) and its phosphate removal capabilities. It is believed that LAB-attached bamboo charcoal canincrease the removal rate of phosphate in aqueous solutions. Furthermore, this study focuses on
deciphering the effects of the pretreatment of bamboo charcoal for phosphate removal. As the releaseof phosphate from bamboo charcoal has been previously reported in the literature (Yao et al., 2012),
and bacteria need oxygen for their activities, the effects of oxygen supply (aeration) and solution pH
on the phosphate removal by bamboo charcoal are also examined.
METHODOLOGY
Material Used for the Experiments
Bamboo charcoal (Fig. 1a) and bamboo powder (Fig. 1b) are readily available products. The bamboo
charcoal was passed through 3.75 cm and 5.6 mm-mesh sieves. Only the residual on 5.6 mm-meshsieve was used in experiments, i.e., the diameter range of 0.56-3.75 cm. Two kinds of bamboo
charcoal were prepared, i.e., without pretreatment and dissolved in tap water (50 g of bamboo
charcoal in 500 mL of water). For the bamboo charcoal dissolved in tap water, the solution was
replaced until no further release of phosphate was observed. The bamboo powder was fermented for
four days, and then the supernatant (hereafter, called bamboo supernatant) was extracted and used in
the experiments.

(a) Bamboo charcoal(b) Bamboo powder

Fig. 1 Bamboo charcoal and bamboo powder used in the experimentsⒸ ISERD

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Experimental Procedures and Measurements
First, approximately 50 g of bamboo charcoal was placed in a LAB solution for 24 h to attach LAB
to the bamboo charcoal. Then, the bamboo charcoal was placed in the bamboo supernatant to assess
the phosphate removal. The LAB solution was produced by mixing 50 mL of LAB beverage with 1
L of deionized water. The experiments were conducted with and without aeration to examine theeffects of oxygen on LAB for phosphate removal. The experiments were conducted in a room withthe ambient temperature range of 25-30℃.
Temporal measurements of the solution pH, redox potential (ORP), and phosphateconcentration were conducted. The pH and ORP were directly measured by placing a pH/ORP meter(Horiba, D-73) into the solution. The solution in the bamboo charcoal layer was extracted using asyringe, and the phosphate concentration in the extracted solution was measured using a digital
Packtest (Kyoritsu, DPM2-PO4-D). A summary of these experimental procedures is shown below in
Fig. 2. A duplicate measurement was conducted, and the average value was used for discussion.
Phosphate concentration, pH and ORP were measured with relative errors of 0.1 mg/L, 0.1, and 1
mV, respectively.
Measurements
Phosphate

pH/ORP

Extracted solution

Fermentation (4 days)

Aeration
Supernatant
Phosphate: 2 mg/L

Tap water
Bamboo powder

Attachment (24h)Bamboocharcoal

LAB beverage(50 mL)

Bamboo charcoal(50 g)➢ No pretreatment

Deionized water(1 L)➢ Dissolved(50 g)
Diameter of 40 mm
Height of 185 mm

Fig. 2 Summary of experimental procedures
RESULTS AND DISCUSSION
Temporal Changes in Phosphate Concentrations (Bamboo Charcoal Without Pretreatment)
Figure 3 shows the temporal changes of phosphate concentration when using bamboo charcoal (nopretreatment) without aeration. The phosphate concentration in the bamboo supernatant wasapproximately 2 mg/L, and increased to 37 mg/L at day 20 after the experiment started (Fig. 3a).
This increase indicates a release of phosphate from the bamboo charcoal, which is in good agreementwith the findings by Jung et al. (2015).
When LAB-attached bamboo charcoal was used, the increase in the phosphate concentration
was smaller compared to the bamboo charcoal without LAB. This indicates phosphate removal by
LAB. Even though the LAB is attached to the bamboo charcoal, they effectively remove phosphatefrom the aqueous solution. These results suggest that LAB-attached bamboo charcoal can be anabsorbent for phosphate removal.
The removal rate of phosphate by LAB was 40% at day 2, 50% at day 6, and 56% at day 20,
see Fig. 3b. These removal rates are on the same scale as conventional biological methods, whichremove 20-40% of phosphorus (Ruzhitskaya and Gogina, 2017). Furthermore, it can be inferred from
Fig. 3b that the removal capacity rapidly decreased, as it was 40% at day 2, but only increased byⒸ ISERD

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40
Without LAB
LAB attached

35

Removal rate by LAB (%)

Phosphate concentration (mg/L)

10% from day 2 to day 6 and by 6% from day 6 to day 20. It is likely that the metabolic activity or
the bacteria growth was limited due to the lack of oxygen. Without aeration, the ORP decreased
significantly at day 20 when using LAB-attached bamboo charcoal to -300 mV vs. Ag/AgCl (nooxygen in water), while the ORP was maintained at 190 mV when using bamboo without LAB.
Moreover, the solution pH was 7 when using LAB-attached bamboo charcoal but climbed to 9 whenusing bamboo charcoal, indicating that the dissolution of bamboo charcoal increases the solution pH.
In summary, these results indicated that pretreatment and aeration are necessary when using LABattached bamboo charcoal for phosphate removal.

30
25

20
15
10
5

0
0

2

4

6

8

10

12

14

16

18

60
55
50
45
40
35
30
25
20
15
10
5
0

0

20

2

4

6

8

10

12

14

16

18

20

Operation time (day)Operation time (day)(a) Phosphate concentration(b) Removal rate of phosphate by LAB

Fig. 3 Changes over time of phosphate concentration and removal rate of phosphate by LAB
using bamboo charcoal (no pretreatment) without aeration
Temporal Changes in Phosphate Concentrations (Dissolved Bamboo Charcoal)
Based on the findings shown in Fig. 3, pretreatment of the bamboo charcoal and aeration are bothneeded for phosphate removal. Figure 4 shows the temporal changes of phosphate concentration
when using dissolved bamboo charcoal with aeration. The phosphate concentration of the bamboo
supernatant was approximately 2 mg/L and slowly increased to 12 mg/L on day 13 after theexperiment began (Fig. 4). In comparison with Fig. 3a, the release of phosphate from the bamboo
charcoal was strongly suppressed due to the dissolution of bamboo charcoal before its use in theexperiments. This indicates that bamboo charcoal without pretreatment is not an effective absorbent
for phosphate removal.

Fig. 4 Temporal changes of phosphate concentration using dissolved bamboo charcoal
with aeration
When using LAB-attached bamboo charcoal, a decrease in the phosphate concentration wasobserved, indicating phosphate removal by LAB. Up to 95% of phosphate was removed during thefirst 3 days due to a low initial concentration of phosphate. According to Fig. 3a, LAB removed 5
mg/L of phosphate on day 2 and 11.5 mg/L on day 6. Interestingly, according to Fig. 4, LAB couldⒸ ISERD

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not completely remove the 2.8 mg/L of phosphate produced on day 7; however, it was able to remove
8.3 mg/L of phosphate on day 13. As bacteria are involved in this reaction, it is believed from theseresults that pH and dissolved oxygen (DO) concentration may also affect phosphate removal.
Effects of DO Concentration and pH on Phosphate Removal
By providing aeration, the ORP was maintained at an oxidizing potential of 275 mV when using
bamboo charcoal without LAB, and the ORP was 245 mV with LAB-attached charcoal on day 13.
The slightly lower ORP was observed for LAB-attached charcoal, indicating a small oxygen
consumption by LAB. In other words, DO was enough for bacteria respiration when aeration wasprovided, which was considered to be less effect on the bacteria’s activity. In addition, it is known
that LAB is more active in acidic conditions; however, the dissolution of bamboo charcoal increases
the solution pH, potentially influencing the bacteria’s activity.
Figure 5 depicts the temporal changes in the solution pH when using dissolved bamboo charcoal
with aeration. The dissolution of the bamboo charcoal increased the solution pH with and without
LAB; however, the pH was lower with LAB-attached bamboo charcoal (Fig. 5a). This was attributed
to the activities of LAB which released lactic acid. The data from Fig. 5a indicate that the solution
pH was 6.3 at day 1, which induced the high phosphate removal rate of 95% on day 3. The solution
pH increased from 6.3 on day 1 to 7.9 on day 3, and then decreased to 6.9 on day 7. Although thesolution pH decreased from day 3 to 7, the pH value of 7.9 influenced the removal rate from day 3
to 7, i.e., a decrease in the removal rate to 55% was observed on day 7.
Similarly, a pH value of 6.9 on day 7 led to an increase in the removal rate to 68% on day 13. It
can be understood from these results that the removal rate is dependent on the solution pH. By
plotting the removal rate versus the solution pH (Fig. 5b), it can be observed that the removal rate
and pH were strongly correlated (R=-0.947), as expected. These results indicate that the solution pH
should be maintained in an acidic state (lower than 6.5) to achieve a higher removal rate.

(a) Temporal changes in pH and removal rate(b) Relationship between pH and removal rate

Fig. 5 Relationship between pH and removal rate
CONCLUSION
In this study, the potential of bamboo charcoal as a microbial carrier for LAB was evaluated, and its
ability to remove phosphate was investigated. The effects of oxygen supply and solution pH on thephosphate removal by bamboo charcoal were also examined. Without aeration, a negative redox
potential (ORP) was observed, indicating a large oxygen consumption by LAB. Thus, aeration isneeded when using LAB. Even with dissolved bamboo charcoal, the release of phosphate wasobserved, indicating that bamboo charcoal alone is not an effective absorbent for phosphate removal.
When LAB-attached bamboo charcoal was used, a decrease in the phosphate concentration wasobserved. This suggests that LAB-attached bamboo charcoal is an effective adsorbent for phosphateremoval. With aeration, the ORP was maintained in an oxidizing state, which had no impact onⒸ ISERD

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phosphate removal. However, the removal rate was found to depend on pH, where the removal rate
decreased with an increase in the solution pH. Therefore, the phosphate removal should be conductedunder acidic conditions (pH lower than 6.5) to obtain a higher removal rate.
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Research article
erd

Contribution of Sustainability Rice Cultivation Practicefor Farmers according to SRP Standard: A Case Study of
Ubon Ratchathani Province, THAILAND
NARAT RATTANACHAROEN*
Graduate School of Agriculture, Tokyo University of Agriculture, Tokyo, Japan
Email: 46318002@nodai.ac.jp, narat.stou@hotmail.com

RYUICHI YAMADA
Graduate School of Agriculture, Tokyo University of Agriculture, Tokyo, Japan
Received 25 January 2020

Accepted 18 October 2021(*Corresponding Author)

Abstract: Sustainable rice cultivation is the goal of agricultural development in Thailand.
With that in mind, the Thai rice department started the Sustainable Rice Platform (SRP) in
Ubon Ratchathani Province, one of the most important jasmine rice production areas ofThailand. Previous studies have shown that most of the paddy fields were in the essential
level or “working towards sustainable rice cultivation”, the intermediate level ofsustainability, while non-paddy fields achieved an overall Sustainable Rice Platform (SRP)
score that allowed them to claim to be sustainable rice farms. The purpose of this study was
to identify the significant factors that affected sustainability in the group of practices called“SRP theme” and the constraints of rice cultivation development. The study was conducted
on 85 farmers in Det Udom district, Ubon Ratchathani Province, Thailand. Questionnaires
and in-depth interviews were collected. The results showed that farm size had a significant
effect on the Pre-planting theme (a group of pre-plating activities), water management andnutrient management for the SRP score; a larger farm can lead to higher scores. The
integrated farming system had a significant effect on farm management, harvest and postharvest theme. Paddy fields that used the integrated farming system accomplished higherscores. The certified rice program had a highly significant effect on farm management, preplanting, harvest, and post-harvest theme, including the health and safety theme. Moreover,certified rice programs for farmers (Organic, Good Agricultural Practice - GAP and
Sustainable Rice Platform- SRP farmers) enabled higher sustainability rice cultivation scores.
Keywords: rice, sustainability, organic, SRP, GAP, certification

INTRODUCTION
Rice production plays an important role in Thai economy. Thailand was a top-5 rice exporter in 2019with about 10.3 million metric tons (Startista, 2020). However, this occupation is currently facedwith multiple challenges such as global market competition (USDA. 2020), declining yields, thecontamination of agrochemicals, biodiversity losses and greenhouse gas emissions (GHG) (G.S.
Bhullar, 2015). Rice cultivation accounts for more than half of Thailand's agricultural GHG
emissions (MNRE, 2013). As a result, Thailand is rated 20th of the world in terms of agricultural
CO2 emissions (FAO. 2018). It was found that farmers can reduce GHG emissions and make their
paddy fields more sustainable by improving some farm activities. The activities that affect theconditions include changing the way to manage water on a farm, the selection of rice cultivars,
nutrient management, and cultivation methods (H. L. Suihawati, 2018) that avoid the burning of rice
residue (Noppol, 2017). The Rice Department in Thailand started a sustainable rice cultivation
project in Ubon Ratchathani Province, one of the most important jasmine rice production areas ofThailand, by using the Sustainable Rice Platform (SRP). This standard was designed for farm-level
impact at the smallholder level and consists of 8 sets of actions called SRP themes, each with severalⒸ ISERD

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requirements, for a total of 46 types of requirements for sustainable rice production. These include:
1) Farm management, 2) Pre-planting, 3) Water use, 4) Nutrient management, 5) Pest management,
6) Harvest and postharvest, 7) Health and safety, and 8) Labor rights. Farmers who want toimplement the program must be trained and improve their farming activities following the SRP
standards. Within each theme, sustainability can be shown by a percentage score. To improve thesustainability of rice cultivation according to the SRP standards, there is a strong need to identify thefactors that impact the SRP scores in each SRP theme in order to boost the farmer’s sustainability inrice cultivation, not only reduce GHG emission but also to improve farming efficiency and economic
aspects.
OBJECTIVE
This research aimed to identify the significant factors that affected the sustainability in the group ofpractices and the constraints of rice cultivation development in Det Udom, Ubon Ratchathani
Province, Thailand.
METHODOLOGY
The researchers collected both quantitative and qualitative data by using a questionnaire as aninterview guideline to assess the characteristics of farmers and their farms in October 2018. The
sustainable scores were calculated by using SRP standard version 1.0 developed by SRP and IRRI.
(Wyn, 2015) The sustainable scores came from 46 requirements based on farmer’s activities. If theactivity belonged to idealistic sustainable rice cultivation, the farmer would receive a high score onthat requirement. In contrast, if the farm activities were not sustainable, the farmer would get a low
or zero score. Total scores were calculated and presented in percentage to clarify the level ofsustainable rice cultivation on farms. Stratified random sampling was used to select farmers fromeach of four types including SRP, organic, GAP and conventional farmer, according to the farmers’
list of extension service centers in Det Udom district, Ubon Ratchathani. The total sample size of 85
farmers comprised 11.3% of the farmers on this list.
This study identified the factors that affected each SRP theme score. Eight regression analysis
equations were operated based on the 8 SRP themes mentioned previously. All the dependent
variables comprised the total score on each theme, while the independent variables were thecharacteristics of farms and farmers. All independent variables were entered into the equation at thesame time, as shown in the following equation.
𝑌(1,2, . .8) = 𝑎 + 𝑏1𝑥1 + 𝑏2𝑥2 + 𝑏3𝑥3 + 𝑏4𝑥4 + 𝑏5𝑥5 + 𝑏6𝑥6 + 𝑏7𝑥7 + 𝑏8𝑥8 + 𝑏9𝑥9 + 𝑒 (1)Where Y1 = farm management scores, Y2= Pre-planting scores, Y3 = Water use scores, Y4 =Nutrient management scores, Y5 =Pest management scores, Y6 = Harvest and post-harvest scores,
Y7 =Health and safety scores, Y8 = Labor right scores, X1 = the certified practice of rice farm(dummy variable: certified/ noncertified), X2 = education period (years), X3 = Level of integration
on farm (dummy: 1 component integration), X4 = Level of integration on farm (dummy: 2component integration), X5 = source of income (dummy: multiple income sources), X6 = labors onfarm (person), X7 = yield (kg/Rai), X8 = farm size (Rai), X9 = income (Baht).
The data were evaluated and explained in the 8 equations using Statistical package for social
science (SPSS) version 23. The demographic features and farming practices of sample respondents
were determined using descriptive statistics and content analysis.
RESULTS AND DISCUSSION
Almost all the farmers in this study were descendants of farmers (98%). Over half of them were aged
40-59 years (63.52%). Most of them were full-time farmers and had more than 10 years of experience(88%). They learned agricultural techniques from their parents and grandparents and observed otherⒸ ISERD

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techniques from neighbors as well as extension agents. A common cropping system in the area is
integrated agriculture. They plant food plants such as basil, bananas, and weed grasses in homegardens and various vegetables as commercial field crops. The average rice yield was 352
kilograms/rai (0.16 hectare), while mean annual farm income was 117,936 baht. Moreover, half ofthe farmers' revenue (58.82%) came from their farms alone. The factors that give effects to the SRP
theme scores are provided in Table 1.
Table 1 Effects of farmer and farm characteristics on average SRP scores for each theme
Theme &
Constant

Certified
Practice(x1)
19.08(0.00)**(9.9928.18)

Education
Period(x2)
0.30(0.54)(-0.681.28)

Pre-plant
(Y2)
43.17

21.66
(0.00)**(11.8531.48)-0.45(0.39)(-1.520.60)

Water use
(Y3)
60.99

-2.22
(0.62)(-11.186.74)

0.20(0.67)(-0.761.17)

Nu mgt(Y4)
102.132.24(0.69)(-9.1313.62)-1.01(0.10)(-2.240.21)

Pest mgt
(Y5)
88.72

1.04
(0.76)(-5.837.92)-0.34(0.35)(-1.090.39)

Harvest
(Y6)
55.81

9.23
(0.02)*(1.1217.34)-0.25(0.56)(-1.130.62)

Health
(Y7)
57.21

9.61
(0.00)*(3.3313.90)

0.08(0.79)(-0.590.76)

Labor
right
(Y8)
91.69

0.10
(0.96)(-4.895.10)

0.17(0.51)(-0.360.71)

Farm mgt
(Y1)
29.36

Integration
component
1 (x3)
2 (x4)
3.25-11.27(0.47)(0.02)*(-5.83(12.34)
21.131.40)
1.75
-5.55
(0.72)(0.30)(-8.07(11.54)
16.195.08)
-3.51
-3.38
(0.43)(0.49)(-12.47(5.44)
13.106.33)
-7.98
-8.97
(0.16)(0.15)(-19.36(3.39)
21.323.36)
0.79
-5.37
(0.81)(0.15)(-6.08(7.67)
12.832.08)
-2.76
-9.99
(0.49)(0.02)*(-10.87(5.33)
18.781.21)
1.52
-5.51
(0.62)(0.11)(-4.75(7.81)
12.331.30)
0.38
-3.16
(0.87)(0.24)(-4.61(-8.585.38)
2.26)

IncomeSources(x5)
2.98(0.46)(-5.1311.09)

farm
Labor
(x6)
0.73
(0.74)(-3.745.20)

4.14(0.34)(-4.6212.90)-0.45(0.85)(-5.284.37)-4.42(0.27)(-12.423.57)-0.01(0.99)(-4.424.39)

6.69(0.19)(-3.4616.85)

0.04(0.98)(-5.555.64)-2.78(0.36)(-8.923.35)

2.41(0.16)(-0.975.79)

3.70(0.31)(-3.5310.94)

1.71(0.39)(-2.265.70)

2.86(0.31)(-2.748.47)

1.88(0.22)(-1.214.97)

1.43(0.52)(-3.035.90)

1.94(0.12)(-0.524.39)

Yield
(x7)
0.10
(0.12)(0.020.23)
0.03(0.66)(0.110.17))
0.06(0.30)(0.060.19)-0.04(0.61)(0.200.12)-0.01(0.72)(0.110.08)
0.05(0.37)(0.060.16)
0.03(0.46)(0.050.12)
0.00(0.83)(0.060.07)

R2
&
Radj
0.27
0.18

Farm
size
(x8)
0.03
(0.79)(-0.200.26)

Income0.30(0.01) *(0.050.55)-0.00(0.13)(0.000.00)

0.29
0.21

0.32
(0.00)**(0.980.55)-0.00(0.39)(0.000.00)

0.14
0.03

-0.31
(0.03)*(-0.060.02)

0.00(0.56)(0.000.00)

0.13
0.03

-0.10
(0.25)(-0.270.07)

0.00(0.24)(0.000.00)

0.10
0.00

0.00
(0.95)(-0.200.21)-0.00(0.68)(0.000.00)

0.13
0.03

-0.09
(0.26)(-0.250.06)-0.00(0.71)(0.000.00)

0.17
0.07

-0.08
(0.18)(-0.210.04)

0.00(0.64)(0.000.00)

0.10
0.00

(x9)
-0.00
(0.90)(0.000.00)

Source: Investigation by the author (2018)
Note: mgt = management, *p-value >0.05, **p-value >0.01, 95% Confidence Interval

The group of independent variables (x1-x9) statistically affected 6 of 8 dependent variables(SRP theme scores). All details are explained as follows:
Farm management Scores
𝑌1 = 29.36 + 19.08𝑥1 + 0.30𝑥2 + 3.25𝑥3 − 11.27𝑥4 + 2.98𝑥5 + 0.73𝑥6 + 0.10𝑥7 + 0.03𝑥8 −0.00𝑥9(2)Ⓒ ISERD

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In terms of farm management scores, farmers were required to update their crop calendar throughout
the crop cycle, keep recording of all fertilizers, pesticides, and machinery operations as well as
calculated quantities of water use, seed variety, yield, and production cost. They also had to attend
training or regularly seek professional advice on farm management. According to the Y1 equation,
certified practice of rice farm (x1) and integration component on farm (2 component integration : x4)
are the variables that contribute significantly to farm management scores. If farms or farmers use thecertified rice practice (Organic, GAP or SRP rice practice), the farm management scores increase
because farmers must attain training, report their crop calendar, and detail their agricultural activities(such as cost, yield, profit, timing of machine operation, etc.) to the inspectors of the government
extension agent, while conventional farmers are not required to do the same. Furthermore, farmers
who used integrated agriculture techniques will achieve higher scores on farm management, morecomponent is more sustainable scores. In contrast, farmers who used a monocrop technique got lower
farm management scores when compared to the integrated rice farmers.
Pre-planting Score
𝑌2 = 43.17 + 21.66𝑥1 − 0.45𝑥2 + 1.75𝑥3 − 5.55𝑥4 + 4.14𝑥5 − 0.45𝑥6 − 0.03𝑥7 + 0.03𝑥8 −0.00𝑥9(3)
To achieve high scores in pre-planting, farmers must have the documents to prove that the soil is safe
from heavy metal and there is no risk of soil salinity. Their farms must not be in primary forest; thefarmland must be flat or be sufficiently leveled. There can be no invasive species and the rice seedmust be pure and certified or traceable. Y2 equation shows that the certified practice of rice farm(x1) and farm size (x8) is a statistically significant factor that can increase the sustainability of the
pre-planting theme. Certified rice farmers have the condition to check the safety of soil and thequality of rice seed. Further, they are not allowed to cultivate in primary forest areas. This enables
certified farms to have higher sustainability scores while conventional farmers have higher risk toachieve lower scores. Additionally, the farmers with bigger farm size (x8) can raise theirsustainability in pre-planting of rice farms. If farmers want to develop the sustainability of the preplanting process, they must check soil quality, adopt land conservation practices such as covercropping, install erosion barriers or laser land leveling to adjust farm area to fit in the appropriate
slope at least every 3 years. This condition increase the production costs on land preparation amongsmallholder farmers and transform into the constraints of sustainable rice farm development for small
scale farmers. Bigger size farm plots will deliver price efficiency compared with smaller farms andprovide higher sustainability scores.
Water Use Score
𝑌3 = 60.99 − 2.22𝑥1 + 0.20𝑥2 − 3.51𝑥3 − 3.38𝑥4 − 4.42𝑥5 − 0.01𝑥6 + 0.06𝑥7 + 0.32𝑥8 −0.00𝑥9(4)
The sustainability of water use is focused on the efficiency of water management, which is consistedof water quality check, timely and appropriate crop establishment, and sufficient irrigation systemand safety water drainage. It was found that farm size (x8) had a significant effect on the water usescore of the Y3 equation. According to the geography of Det Udom district, which uses a rain-fed
rice production system, one of the most challenging factors is the amount of rain used for ricecultivation. Even though the farmers in this area have a good understanding of the local climate andplan well about timing the operation of rice crops, only the farmers who have larger farm areas haveenough space to keep rainwater in a pond or other system for supplementary irrigation. Regarding
this factor, the sustainability scores for water use theme increased as the size of rice farms increased.
Nutrient Management ScoreⒸ ISERD

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𝑌4 = 102.13 + 2.24𝑥1 − 1.01𝑥2 − 7.98𝑥3 − 8.97𝑥4 + 6.69𝑥5 + 0.04𝑥6 − 0.04𝑥7 − 0.31𝑥8 +0.00𝑥9(5)
The scores for nutrient management depend on the efficiency of soil fertility enhancement. Farmers
should use crop rotation techniques, as well as apply fertilizer based on the result of soil analysis andsplit the application of nitrogen fertilizers or use slow/controlled release / deep placement fertilizers.
Organic fertilizer must be the first choice to improve soil quality and must be applied in the nonflood areas. In the Y4 equation, it was found that a larger farm size (x8) can help farmers achieve
higher sustainable scores on nutrient management. Based on the interviews of the farmers, they prefer
to apply the organic manure on wetland or flooding periods of their rice farms. They believe that it’seasier and more effective than a deep placement fertilizer technique. For the farmers who have alarge farm area (and for who have the rainwater storage pond), however, flooding their paddy field
only for fertilizer leads to higher production costs. They choose to apply the fertilizers on dry land
instead for economic reasons. Even though it is not based on a complete understanding of nutrient
management, the action's result is appropriate for the situation. Furthermore, when it comes tofertilizers, a larger farm size provides more economies of scale, both in terms of cost and wage. For
all these reasons, large farms achieve higher scores.
Pest Management Score
𝑌5 = 88.72 + 1.04𝑥1 − 0.34𝑥2 + 0.79𝑥3 − 5.37𝑥4 − 2.78𝑥5 + 2.41𝑥6 − 0.01𝑥7 − 0.01𝑥8 +0.00𝑥9(6)
On pest management, farmers should understand and adopt the Integrated Pest Management (IPM)
technique for principal pest control on their farms. If farmers use a non-chemical methodology tocontrol weed, insect, disease, mollusk, and avoid killing rodents and birds, they achieve high scores.
In serious cases, pesticide and chemical substances are allowed to be applied carefully in the target
area following the label instructions. Pesticide application equipment should be calibrated andmaintained within the current crop cycle. According to the Y5 equation, there is no independent
variable on this equation that significantly affects the pest management scores.
Harvest & Post-harvest Score
𝑌6 = 55.81 + 9.23𝑥1 + 0.08𝑥2 + 1.52𝑥3 − 5.51𝑥4 + 2.86𝑥5 + 1.88𝑥6 + 0.03𝑥7 − 0.09𝑥8−0.00𝑥9(7)
Harvest and post-harvest scores are focused on the timing of the harvest; the rice moisture content
should be 21%-24%. All machines and equipment should be cleaned to prevent contamination. Riceshould be transported to the drying facilities within 12 hours and stored away from hazardous
substances. Rice stubble and rice straw should not be burned to mitigate GHG emissions. On the Y6
equation, the certified practice of rice farm (x1) and level of integration on the farm (2 component
with rice: x4) are the independent variables that significantly affected the scores. Farmers that employ
organic, GAP, or SRP rice programs must abide with the rules, which include not permitting farmers
to burn their rice straw or using contaminated harvesting machines. The conventional farmers in thisstudy burned their rice fields to save their production costs. However, it caused them to achieve lower
scores in this sustainable theme. Farmers who use the integrated cropping system will have various
kinds of agricultural commodities. To get their products, many activities will happen on theirfarmland and some of them can cause dirt or contamination in rice products. In that case, farmers
become more concerned about the effect on their harvest and post-harvesting activities. This will
help to increase the scores as well as the sustainability of the SRP. In contrast, farmers used themonocrop system and there was less concern about contamination, though it may cause lower
sustainable scores.
Health & Safety ScoreⒸ ISERD

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𝑌7 = 57.21 + 9.61𝑥1 + 0.08𝑥2 + 1.52𝑥3 − 5.51𝑥4 + 2.86𝑥5 + 1.88𝑥6 + 0.03𝑥7 − 0.09𝑥8 −0.00𝑥9(8)
To achieve high scores, farmers should prepare safety instructors for all farm laborers, prevent related
accidents and disease work. Further, first-aid kits should be available on the farms. Calibration andmaintenance of all equipment should be done within the crop cycle. Training for agriculturalchemical uses is needed if farmers use chemical elements on the rice farms. According to the Y7
equation, the certified practice of rice farm (x1) was statistically significant to the health & safety
scores. Participation in certified rice programs enables farmers to learn the effects of chemicals on
human health and to learn how to protect themselves.
Labor Rights Score
𝑌8 = 91.69 + 0.10𝑥1 + 0.17𝑥2 + 0.38𝑥3 − 3.16𝑥4 + 1.43𝑥5 + 1.94𝑥6 + 0.00𝑥7 − 0.08𝑥8 +0.00𝑥9(9)Labor rights scores focus on how farmers address human rights, including the wage and safety
conditions for laborers on their farms. Under this theme, no children below the minimum age canwork on farms or be around hazardous work. Further, employers must provide education for children.
There can be no forced, prison or bonded labor. Laborers must have the right to join or establish an
association or organization to negotiate their needs, received wages, and other benefits according tolocal and national laws. On the Y8 equation, independent variables on this equation did not have astatistical effect on labor rights scores.
CONCLUSION
The results of the analysis showed that there were three important independent factors that affected
the sustainability scores of rice cultivation, consisting of 1) Certified program of the farm, 2)
Integrated component of the farm, and 3) farm size. The use of certified rice programs has asubstantial impact on 4 SRP themes connected to document certification and training which are theimportant part to be the certified farmers. Certified farmers have already received extensive training,allowing them to better manage their farms, comprehend the importance of farm preparation, andharvest rice in a sustainable manner. Integrated components affected the management of farms. Morefarm components would encourage farmers to focus on their management, which will be reflected intheir farm management score and harvesting activities. While farm size affected the rice productionin pre-planting, water use and nutrient management which is related with farm investment. The larger
the farm, the better the chances of being a sustainable rice farm. All significant factors suggested that
two major issues need to be addressed to improve the sustainability of rice cultivation, 1) All farmers
require adequate knowledge and sustainable rice farming techniques, and the simplest way to achieve
this is to urge them to become certified farmers. 2) Farm size cannot be changed easily; therefore,
the government should assist farmers in making more profit in the same way, which is through cost
reduction. Farmers must participate in the cost-cutting initiative in order to improve their farms
sustainable. However, this study was limited in sample size and needed to improve the equation.
Future studies should apply this topic with additional budgeting to devise more accurate equations.
REFERENCES
Ellis, W. 2015. SRP standard for sustainable rice cultivation. Version 1.0 [PDF], Retrieved from www.
sustainablerice.org
Food and Agriculture Organization (FAO). 2018. World food and agriculture, Statistical book 2018. 254 pp.
Licence: CC BY-NC-SA 3.0IGO, Retrieved from https://www.fao.org/3/ca1796en/ca1796en.pdf
Gurbir, S.B. 2015. Sustainable rice production. Chapter 5 (107), Sustainable Agriculture Review, Springer
International Publishing, Switzerland.

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MNRE. 2013. Thailand’s third national communication document for cooperation with the UNFCCC
secretariat (UN climate change). 42, Ministry of Natural Resources and Environment (Thailand), Retrieved
from https://unfccc.int/sites/default/files/resource/Thailand%20TNC.pdf
Noppol, A. and Nathsuda, P. 2017. Practice for reducing greenhouse gas emissions from rice production innortheast Thailand. MDPU, Agriculture, Retrieved from https://doi.org/10.3390/agriculture7010004
STATISTA. 2020. Principal rice exporting countries worldwide in 2018/2019. In Shahbandeh, M., Retrieved
from https://www.statista.com/statistics/255947/top-rice-exporting-countries- worldwide-2011/
Susilawati, H.L. and Setyanti, P. 2018. Opportunities to mitigate greenhouse gas emission from paddy rice
field in Indonesia. IOP Conf. Ser., Earth Environ. Sci. 200 012027.
USDA. 2020. Grains: World market and trade. United States Department of Agriculture Foreign Agricultural
Service. USA. USDA, Retrieved from https://apps.fas.usda.gov/psdonline/circulars/grain-rice.pdfⒸ ISERD

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Research article
erd

Organic Agriculture Certification on Thai AgriculturalStandard in Upper Northeast Thailand
JIRAPHON CHOEICHIT
Office of Agriculture research and Development Region 3, Khon Kaen, Thailand.

CHULEEMAS BOONTHAI IWAI*
Integrated Land and Water Resource Management Research and Development Center inNortheast Thailand, Khon Kaen University, Khon Kaen, Thailand
Email: chuleemas1@gmail.com

SANITPIM SIMMATUN
Office of Agriculture research and Development Region 3, Khon Kaen, Thailand

WARAPHON WONGSIRIWAN
Office of Agriculture research and Development Region 3, Khon Kaen, Thailand
Received 25 February 2020

Accepted 18 October 2021(*Corresponding Author)

Abstract Many countries have controlled measures for imported agricultural commodities.
The Department of Agriculture has taken responsibility for the organic agriculture
certification, including the quality control of agricultural commodities within the Thai
Agricultural Standards (TAS) in the upper-northeast region of Thailand (11 provinces). The
objective of this study was to report the factors involved in obtaining and maintaining organic
agriculture certification within the entire chain of production. Within our initial year in 2018,
there were 73 farms with organic certification (21.92%) and 260 non-certified farms(78.08%) from a total population of 333 farms. The 100% organic certifications consisted of
32 certified farms (86.47%) and 5 non-certified farms (13.51%) from a population of 37
farms. A reassessment of 68 farms at the end of 2018 determined that 63 farms (92.65%) had
obtained organic certification versus 5 non-certified farms (7.35%). In the transition period
into 2019, 60 farms (28.17%) had obtained organic certification, whereas 153 farms werenon-certified (71.83%) from 213 farms. The 100% organic certification was achieved by 56
farms (94.92%) with only 3 uncertified farms (5.09%) from a population of 59 farms. Our reassessment produced 78 certified farms (98.73%) and only a single non-certified farm
(1.27%) from 79 farms. The trend of certifications over two years (2018 and 2019) showedthat certified organic agriculture production increased from 38.37 to 55.27%, whereas noncertifications decreased from 61.64 to 44.73%; from 438 to 351 farms, respectively. We
determined that there were six main reasons for non-certification of farms: the inability tosustain organic agricultural production within TAS; the lack of a buffer zone to deter
pollution from adjacent plantations; the lack of available recorded data for both traceability
and verification; the use of chemicals that did not follow TAS protocols; planting areas withinsome environments caused the contamination of hazardous substances; and, several farms
did not have the proper land-rights documents. Improvements and compliance within theseareas will, therefore, result in an environmental ecological balance, as well as increased foodsafety.
Keywords Thai agricultural standard, certification, organic agriculture

INTRODUCTION
Several interesting trends have emerged in the global food market, in which consumers have begun
to look for safer and better-controlled foods produced in more environmentally friendly, authentic,
local systems. Many countries have implemented controlled measures for the importation ofⒸ ISERD

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agricultural commodities, resulting in the enhanced recognition of food safety and quality for
consumption, and further consideration of the environment and the worker’s health, safety, andwelfare. Organic agriculture production has expanded in Thailand, from 37,684 hectare planting
areas in 2014 to 2,791 farm 45,587 hectare areas in 2015; an increase of 20.97% (2,791 farms)(National Agricultural Development Strategy, 2017). Global food markets demanded that Thailand
adhere to various standards in farming, such as the Good Agricultural Practice (GAP) and organic
certifications.
The certification body within Thailand’s Department of Agriculture is responsible for theinspection and adherence to standards, resulting in organic agriculture certification. The organic
agricultural standards cover provisions instituted within the Thai Agricultural Standard (TAS) 9000:
Part 1-2009 determines the holistic production management systems which enhance and promote anagro-ecosystem, including biodiversity and biological cycles. It emphasizes the use of natural
materials and avoids the use of synthetic materials, plants, animals, or microorganisms derived fromgenetic modification. An organic production system is designed to handle agricultural products withcareful emphasis on processing methods, to maintain the organic integrity and vital qualities of the
product at all stages. Accordingly, the organic production requirements for plants shall be usedthroughout the entire transition period of at least 12 months before the planting of annual crops, and18 months before the first harvest of organic produce of perennial crops. The producer’s transition
period occurs at the time organic practice and adherence to the prescribed standards begins, typicallywhen a farmer applies for certification (National Bureau of Agriculture Commodity and FoodStandards, Ministry of Agriculture and Cooperatives, 2009). However, farmers often lack theirknowledge and understanding of several TAS standards; such as the use of composts, cropping
systems, and the control of diseases and pests.
OBJECTIVE
The objective of this study, therefore, was to report upon the situation of organic farming practices
within the upper-northeast region of Thailand in the years 2018 and 2019 and to determine thefactors involved in obtaining and maintaining the organic agriculture certification within the entire
chain of production.
METHODOLOGYThis paper is based on the results from previous reports within this region, as well as the preliminary
results from an ongoing study. Our methodology consisted of the following elements:
1 . the Organic agriculture certification and the factors related to both obtaining and maintaining
certification throughout the entire chain of production, as well as within the 100% certification status,
2. the investigation and possible solutions for the prevention and recurrence of non-certification
within the transition from 2018 to 2019.
The area of study, the upper-northeast region of Thailand, included the following 11 provinces:
Kalasin, Khon Kean, Chiyaphum, Nakhon Phanom, Loei, Mukdahan, Sakon Nakhon, Nong Khai,
Bueng Kan, Nong Bua Lam Phu, and Udon Thani.
RESULTS AND DISCUSSION
Our study identified 73 farms with organic certification (21.92%) and 260 non-certified farms(78.08%) from a total population of 333 farms. The 100% organic certifications consisted of 32
certified farms (86.47%) and 5 non-certified farms (13.51%) from a population of 37 farms. A
reassessment of 68 farms at the end of 2018 determined that 63 farms (92.65%) had obtained organic
certification versus 5 non-certified farms (7.35%). In the transition into 2019, 60 farms (28.17%) had
obtained organic certification, whereas 153 farms were non-certified (71.83%) from 213 farms. The
100% organic certification was achieved by 56 farms (94.92%) with only 3 uncertified farms (5.09%)Ⓒ ISERD

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from a population of 59 farms. Our re-assessment produced 78 certified farms (98.73%) and only asingle non-certified farm (1.27%) from 79 farms. The trend of certifications over the two years (2018and 2019) showed that certified organic agriculture production increased from 38.37 to 55.27%,
whereas non-certifications decreased from 61.64 to 44.73%; from 438 to 351 farms, respectively.
Table 1 Inspection within the transitional period, certification and non-certification(2018 to 2019), 100 % organic certification, and re-assessment certification (TAS)
Inspection
Year/ inspections

2018

2019

Total

Certification

Non-certification

farms

Area
(hectare)

farms

%

Area
(hectare)

farms

%

Area
(hectare)Transition period

333

161.30

73

21.92

44.85

260

78.08

116.45

100 % organic
certifications

37

32.02

32

86.49

29.74

5

13.51

2.27

Re-assessment

68

114.6963

92.65

106.40

5

7.35

8.29

Transition period

213

110.54

60

28.17

42.18

153

71.83

68.37

100 % organic
certifications

59

41.06

56

94.92

38.46

3

5.08

2.59

Re-assessment

79

116.9678

98.73

116.92

1

1.27

0.04

Transition period546

271.84

133

24.36

87.02

413

75.64

184.82

100 % organic
certifications

96

73.07

88

91.67

68.21

8

8.33

4.86

Re-assessment

147

231.6514195.92

223.32

6

4.08

8.33

The results of our study in 2018 identified several areas of responsibility for organic agricultural
non-certification including 19 fruit farms and 42 vegetable farms: the inability to sustain organic
agricultural production within TAS: the lack of a buffer zone to deter pollution from adjacent
plantations; the absence of any available recorded data for both traceability and verification; the useof chemicals that did not follow TAS protocols; planting areas within some environments caused thecontamination of hazardous substances; and, several farms did not have the proper land-rights
documents.
In 2019, non-certification farms were present in 108 integrated agricultural farming systems,
including four fruit farms, 34 vegetable farms, and 11 herb farms with the same reasons above.
CONCLUSION
The finding through the transitional period of 2018 to 2019 was farmers’ lack of understanding oforganic agriculture production (TAS certification). 133 certified farms (24.36%) encompassing an
area of 87.02 hectare and 413 non-certified farms (75.64%) covering an area of 184.82 hectare froma population of 546 farms (271.84 hectare). Eighty-eight farms were identified for 100% organic
certifications (91.67%) in an area of 68.21 hectare, as well as eight non-certified farms (8.33%) in
an area of 4.86 hectare for a total of 96 farms (73.07 hectare). The non-certifications were due
primarily to the framers’ conversion back to the use of non-organic chemicals for pest and disease
control. Our re-assessment identified 141 farms (95.92%) in an area of 223.32 hectare and 6 noncertified farms (4.08%) in an area of 8.33 hectare from a population of 147 farms encompassing
231.65 hectare, due to the farmers’ lack of available recorded data for traceability and verification.
Further re-assessment resulted in an increase of certifications to 95.92%, demonstrating the farm’s
compliance to TAS standards, as well as the farmers’ acceptance of the required protocols, with anaverage score of 4.2, and an average application (TAS) score of 70.79 (Chawit, 2018).

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Table 2 Analysis of non-certification farms from 2018 to 20192018
Noncertification

2019
Noncertification

List

List

Integrated
system333

No organic agriculture production
according to TAS.
No buffer zone to deter from pollution andadjacent plantations.
No available recorded data for traceability
and verification.
Chemical use did not follow TAS
standards.
Several environments caused thecontamination of hazardous substances on
produce.
Planting areas had no land rights
documentation.

108

No organic agriculture production
according to TAS.
No buffer zone to deter from
pollution and adjacent plantations.
No available recorded data fortraceability and verification.
Chemical use did not follow TAS
standards.
Planting areas had no land rights
documentation.

Fruit

19

No organic agriculture production
according to TAS.
No available recorded data for traceability
and verification.
No buffer zone to deter from pollution andadjacent plantations.
Chemical use did not follow TAS
standards.
Planting areas had no land rights
documentation.

4

No organic agriculture production
according to TAS.
No buffer zone to deter from
pollution and adjacent plantations.
No available recorded data fortraceability and verification.
Planting areas had no land rights
documentation.

Vegetable

42

No organic agriculture production
according to TAS.
No buffer zone to deter from pollution andadjacent plantations.
Chemical use did not follow TAS
standards.
Planting areas had no land rights
documentation.

34

No organic agriculture production
according to TAS.
No buffer zone to deter from
pollution and adjacent plantations.
No available recorded data fortraceability and verification.
Chemical use did not follow TAS
standards.
Several environments caused thecontamination of hazardous substanceson produce.
Planting areas had no land rights
documentation.

In addition to the six main obstacles to obtaining organic agriculture certification (TAS),
Chawit, 2018; determined that two primary obstacles existed in both obtaining and maintain organic
certification according to the Thai Agricultural Standard 9000, Part 1-2009. Firstly, organic fertilizers
were difficult to obtain; and secondly, farmers lacked the knowledge and experience to create a bufferline for soil, water, and pest control.
Our recommendations to farmers seeking organic agriculture certification and adherence to TAS
practices included: 1. Working proactively to obtain the knowledge and understanding of organic
agriculture production for TAS certification; 2. Learning to create barriers or ridges (buffer zone)
necessary to buffer against contamination through the soil, water, or air from adjacent plantations; 3.
Generate the fertility and biological activity of the soil needed to maintain the necessary organic
materials according to Jiraschayaporn, 2017; in which a prototype for the production andmanagement of organic fertilizer was capable of producing an increase in organic matter (Surin,
Thailand); and 4. Pests, diseases, and weeds shall be controlled by the appropriate species andvarieties, including the appropriate rotation programs, mechanical cultivation, conservation ofnatural enemies of pests by providing favorable habitats, and maintaining the ecosystem. We notedin the above-mentioned research, that the average income per farmer was 193 USD per hectare.
ACKNOWLEDGEMENTSⒸ ISERD

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We wish to express our sincere gratitude to Mr. Chamlong Kokrum, Thesis Director in the Officeof Agricultural Development, Region 3, for his invaluable assistance and constant encouragement
throughout the course of this research. We are also grateful for the support provided by the
Agricultural Research Development Agency, a public organization.
REFERENCES
National Agricultural Development Commodity. 2017. National agricultural development strategy 2017 to
2021. Ministry of Agriculture and Cooperatives, Thailand.
Ministry of Agriculture and Cooperatives. 2009. Thai agricultural standard: TAS 9000 part 1-2009: Organic
agriculture. National Bureau of Agricultural Commodity and Food Standards, Plant Standard andCertification Division, Department of Agriculture, Ministry of Agriculture and Cooperatives, Thailand.
Ronruangrit, J. 2017. Research and development plant production on organic agriculture system in the Surinprovince. Ministry of Agriculture and Cooperatives, Thailand.
Sawatdisan, C. 2018. The study on organic plants production technology of farmers in the upper south. Ministryof Agriculture and Cooperatives, Thailand.

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Research article
erdApplication of APEX Model in Evaluating Streamflow and
Sediment Yield in Stung Chinit Catchment
NARETH NUT*
Faculty of Agricultural Engineering, Royal University of Agriculture, Phnom Penh, Cambodia
Email: nnareth@rua.edu.kh

MANUEL R. REYES
Sustainable Intensification Innovation Lab (SIIL), Kansas State University, Kansas, USA

GILBERT SIGUA
United States Department of Agriculture, Agriculture Research Service, Coastal Plains
Research Center, South Carolina, USA

MACHITO MIHARA
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, JapanSAKDANUPHOL CHAN
Faculty of Agricultural Engineering, Royal University of Agriculture, Phnom Penh, Cambodia

TAINGAUN SOURN
Department of International Cooperation and ASEAN, Ministry of Tourism, Phnom Penh,
Cambodia
Received 31 December 2020

Accepted 18 October 2021(*Corresponding Author)

Abstract Streamflow and sediment yield are important indicators to understand thealterations in hydrological processes as well as the supply and transformation of nutrients andbiological productivity in the ecosystem. The main objective of this study was to evaluate theperformance and applicability of the APEX model in estimating streamflow, sediment yield,
and quantifying the soil erosion in Stung Chinit Catchment. The result indicates that the
APEX model performed well in accurately simulating the monthly streamflow and annual
sediment yield in the watershed. The overall statistical indicators (NSE, R², and PBIAS) of
streamflow calibration (1997-2015) were 0.60, 0.62, and 2.50%, respectively. The validation
statistical indicators (NSE, R², and PBIAS) for streamflow were 0.71, 0.80, and 28.22%,
respectively. The mean annual surface runoff was 212.03 mm; varied from 72.56 mm to435.59 mm. The average annual sediment yield varied from 10.21 tons/ha/year in thelowlands of the Stung Chinit catchment main river channel to 68.2 tons/ha/year in thehighlands, with an annual average of 29.2 tons/ha/year. Most of the sediment yield came fromthe eastern part and near the outlet of the Stung Chinit catchment.
Keywords APEX model, sediment yield, streamflow, Stung Chinit catchment

INTRODUCTION
Soil erosion is a major environmental problem which affects people by degrading water quality,
depositing sediment in the channel, decreasing the reservoir effective capacity and increasing therisk of flooding (Umit et al. 2018). Due to some human activities such as forest burning, overgrazing,
deforestation, recreation, soil erosion rates have been increased above natural levels, a phenomenon
known as accelerated erosion. Accelerated surface erosion is a severe matter that reduces agricultural
productivity, finite arable lands, and reservoir capacity. Erosion and sedimentation in a catchment
are closely associated with natural processes which is mainly driven by rainfall and runoff processes.
Erosion is the movement and detachment of soil particles by natural forces, primarily caused byⒸ ISERD

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water and wind. Sediment yield is the amount of soil that is transported to surface water bodies withina time scale over a specific area (Issaka and Ashraf, 2017).
Sediment yield in a watershed varies spatially, depending on several contributing factors suchas topography, soil types, catchment area, climate (i.e., precipitation, wind, temperature, etc.),
vegetation cover, human-influenced soil erosion, forest fires, river discharge (Francipane et al. 2015).
In a watershed, the amount of sediment transported by a river system depends on the supply of
sediment and transport capacity of the flow. Therefore, the accuracy of the estimate of the sedimentyield from any watershed relies on understanding and representation of the multiple contributing
factors such as rainfall, runoff, and erosion processes. More discussion on sedimentation processes
can be found in earlier publications (Wilkinson and McElroy 2007; Francipane et al. 2015). Most
physical models normally require hydro-meteorological, topographical, soil, and land use data as the
input data for the model. Besides these data, models such as APEX, DSSAT, EPIC, and SWAT
(Ayele et al, 2017; Jeong et al. 2010) also require crop management data. APEX is capable ofevaluating the effects of various water and land management practices on watershed hydrology,
sediment yields and water quality at various environmental issues (Luo and Wang, 2019; Assefa etal. 2018; Van Liew et al., 2017; Ayele et al, 2017; Tuppad et al. 2010)
The Stung Chinit catchment is one of the major tributaries of Tonle Sap Lake. There is anintensified economic activity in the catchment, including major land concessions, infrastructuredevelopments and demographic pressures (CNMC, 2012). As a result, some soil erosion may occur
eroded from the upstream to the downstream of the catchment due to agricultural land expansion byencroaching to the forest land. Moreover, farmers suffer abnormal storms, floods and multiple kindsof droughts (meteorological, hydrological and agricultural), making them and their communities
highly vulnerable to water scarcity.
OBJECTVIESThe research aims to evaluate the performance and applicability of the APEX model in estimating
streamflow and sediment yield as well as identifying the soil erosion in Stung Chinit Catchment,
Cambodia.
MATERIALS AND METHODS
Study Area
Stung Chinit catchment covers an area of about 8,236 km2 and composed of the Stung Chinit andStung Taing Krasaing Rivers and other small streams that drain from the north. The mainstream,
Stung Chinit, flows 264 km south-westwards to the gentler slopes downstream before discharging
into the Tonle Sap Lake (CNMC, 2012). A measuring stream gauge is located in the middle of theriver along National Road 6, Kampong Thmar (Fig. 1).
Rainfall in the catchment increases with elevation, while the spatial distribution of annual
average rainfall ranges from 1200 to 1500 mm. Over 90% of the catchment’s annual rainfall isreceived during the wet season, from May to October, and the highest rainfall occurs in August(MOWRAM, 2014). Daily temperatures vary from 20°C in the coolest months of December toJanuary up to 35°C during the hottest months of April and May (CNMC, 2012). Farmers in Stung
Chinit and Taing Krasaing mainly cultivate traditional wet season rice and some dry season rice. A
large proportion of the catchment has poor quality soil, Acrisols, which covers 60.75% of the entire
catchment (CNMC, 2012). Agricultural land occupies 28.9% of the total catchment area (238,020ha), located mostly on poor Acrisols. Another 46.3% of the catchment area (381,327 ha) is occupied
by forestland, grassland, shrubland, soil and rock, urban settlements and water bodies. Of the total
agricultural land, rice takes up 154,014 ha, annual crops 49,197 ha, perennial crops 22,938 ha andvillage garden crops 7331 ha (CNMC, 2012).

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Fig. 1 Topography, hydrological and meteorological stations, and rivers of the study area
The APEX Model Application, Data Inputs and Model Setup to Predict Hydrology
The APEX model is an extension of the Environmental Policy Integrated Climate (EPIC) model(Williams, 1998), which is capable of evaluating the effects of various soil and water management
practices on the hydrology of the system, crop growth, and other environmental factors (Wang et al.,2014; Steglich et al., 2018). The APEX simulates watershed processes based on weather data, soil
characteristics, topography, vegetation, and management practices (Wang et al., 2012). Multiple
options are available in the APEX model in estimating evapotranspiration, surface runoff, peakrunoff rate, and available soil water capacity to derive hydrology of the system (Wang et al., 2012).
The APEX model requires some input data, including Geographic Information System (GIS)
data layers, climatic data, and management practices. The GIS data layers are digital elevation model(DEM), soil, and land use or crop covers (Table 1). A 30 m DEM was obtained from the UnitedStates Geographical Survey (USGS) website. The land use data was received from the Cambodia
National Mekong Committee (CNMC), 2015 (Fig. 2d). A harmonized world soil map prepared by
the Food and Agricultural Organization (FAO) with two levels were used for soil database
preparation of APEX (Fig. 2b).
During the model setup process, the APEX version 1501, developed by Texas A&M AgriLife
Research, Temple, Texas, USA, was used and divided into three steps. The first step was the processof setting up the APEX model and began with the processing of GIS data layers to delineate thewatershed boundary, subareas, and derive watershed characteristics from the Digital Elevation Model(DEM). The land use, soil data and slope was overlaid and used the dominant landuse/soil/slope,
while the land use of paddy rice was modified in the management file of APEX file based on theschedule of tradition rice cropping system which people mostly cultivate in the catchment (Table 2).
The dominant land uses in the catchment are evergreen forest (52.94%), paddy rice (26.82%),
grassland (6.23%), marsh/swarm (4.56%), shrubland (4.36%), agricultural land (3.6%) anddeciduous forest (1.49%) (Fig. 2d), while The dominant soils are Acrisols (55.13%), Gleysols(34.92%) and Vertisols (9.95%) (Fig. 2b). The second step was to integrate weather data of 12
catchments of Stung Chinit provided by WinRock International (Fig. 1) through the Arc-APEX
model interface. The third step was the process of performing an initial model run and complete
model setup procedures to create APEX model output files for further analysis.
The APEX can simulate all the key water balance components of the system. Precipitation, snow
melts, and irrigation are the main inputs to the system, which are then disseminated into various
components: surface runoff, subsurface/tile drainage flow, soil water, percolation, and evapoⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2021) 12-2transpiration (Williams, et al. 2006). In APEX, the key landscape processes across hydrologicalconnected units are called subareas. The subareas are the smallest unit in APEX with homogenous
watershed characteristics, such as soil types, land use/crop cover, slope, and management. There are
two options to estimate the runoff volume (Williams, et al. 2006) which are the modified Soil
Conservation Service (SCS) (NRCS, 2004) curve number (CN) and Green and Ampt infiltration(Green and Ampt, 1911) methods used in the APEX model. The SCS-CN runoff estimate method isa function of rainfall and retention parameter. The curve number is a function of land use, hydrologic
soil group and management practices. The subsurface flow is a function of the vertical and horizontal
flow and simulated as a simultaneous process (Wang et al., 2012). The horizontal flow consists of alateral flow, whereas the vertical flow (percolation) adds to groundwater storage, which is thensubjected to return flow or deep percolation. The vertical component of percolation is calculated asa function of soil water content, field capacity, and travel time. There are five options available toestimate the potential evapotranspiration such as Penman, Penman–Monteith, Baier and Robertson,
Priestly and Taylor, and Hargreaves methods (Williams, et al. 2006). The Hargreaves method is
dynamic and requires a lower data, and is a function of solar radiation, latent heat of vaporization,and temperature.
Table 1 Some required input data for APEX model setup
Data

SourceDEM (30×30m) resolution
Soil type FAO/UNESCO in 1984

ASTER-GDEM, USGS
http://www.fao.org/soils-portal/data-hub

Land use and Land Cover
Meteorological data (1990 – 2017)
Streamflow data (1997 – 2017)

Cambodia National Mekong Committee (CNMC), 2015
Rainfall data of 12 catchments and streamflow data
provided by Soparith Tes from Winrock International.

Table 2 Major crop management activity and cropping pattern in Stung Chinit catchment
Types of crop

Medium wet season rice

Management practices

Date

1st tillage
2nd tillage
3rd tillage
DAP fertilizer application
Sowing25-April
5-May
15-May15-May15-May1st stage fertilizer application after planting
2nd stage fertilizer application after planting
Harvest30-June30-July
10-November

Sensitivity Analysis, Model Calibration, and Validation
Model sensitivity analysis is a method of identifying key parameters that affect model performanceand are essential for model parametrization. The APEX model has huge sets of parameters related tohydrology, sediment, nutrients, crops, and other environmental factors. Sensitivity analysis is thefirst step for hydrological models, which helps to diagnose and narrow down the enormous sets ofparameters for calibration. Model calibration is a process in which model parameters are modified
so that a model output mimics observed data, whereas validation is the use of modified parameters
to simulate another set of observed data. The APEX auto-calibration and uncertainty estimator(APEX-CUTE) was used to perform sensitivity analysis and auto-calibration for the APEX
hydrology model (Wang et al., 2014), followed by manual adjustment of a few parameters. The firststep was to examine the APEX hydrology model outputs for modifications. Some default methods
and input parameters might need modification to get better simulation prior to sensitivity analysis
and calibration (Williams, et al. 2008). The second step included a sensitivity analysis, calibration,Ⓒ ISERD

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and validation of the APEX hydrology model. Streamflow was recorded at Kampong Thmar Station
located in the middle of Stung Chinit catchment from 1990 - 2017, while the sediment yield wasdone in 2005 - 2008. Model warm-up period (1990-1996) was used to initialize model parameters
and obtain better predictions. Streamflow records were split into two periods: calibration (1997 2015) and validation (2016 - 2017). The APEX hydrology model was verified in monthly basis for
the Stung Chinit catchment from the measuring gauge to the upstream of the watershed. Most of theparameters considered during calibration were related to soil properties and climate. The third step
includes evaluating the APEX model. The APEX model performance in predicting hydrology of thesystem was evaluated using commonly used statistical measures such as Nash–Sutcliffe efficiency(NSE), determination of coefficient (R2), and percent bias (PBIAS). NSE is a normalized statisticalmeasure that was proposed in Reference (Chad et al. 2015). PBIAS measures the deviation of model
prediction as an under- or overestimation from observation, while R2 is a statistic that will give some
information about the goodness of fit of a model.

(a)

(b)

(c)

(d)

Fig. 2 Model input data in the Stung Chinit catchment(a) meteorological and hydrological stations, rivers, outlets, and subareas;(b) FAO soil; (c) slope classifications;(d) land use and land cover in 2015 from CNMCRESULTS AND DISCUSSION
APEX Sensitivity Analysis, Calibration, and Validation for Streamflow
All relevant parameters for APEX hydrology components were included in the sensitivity analysis
in accordance with the reference (Wang et al., 2014). The results of the sensitivity analysis in the
Stung Chinit catchment illustrated that streamflow was sensitive to the following parameters: Return
flow ratio (RFPO), Groundwater residence day (RFTO), Hargreaves potential evapotranspiration(PET) equation exponent (PARM-34), Groundwater residence day (PARM-40), SCS curve number
index coefficient (PARM-42), runoff volume adjustment factor (PARM-92), runoff CN initial
abstraction (PARM-20) and soil evaporation coefficient (PARM-12), in order of decreasing
influence (Table 3). The most sensitive parameters were associated with soil characteristics,
groundwater residence day and climatic conditions. The parameter PARM-42 was found to be themost sensitive parameter for streamflow followed by PARM-34, possibly because ET was the second
most-dominant hydrological process after rainfall. Feng et al. (2015) showed that ET affecting theⒸ ISERD

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water yield of the catchment in their scenario analysis, while Assefa et al. (2018) depicted that ET
could be able to impact on hydrology. Variable CN nonlinear CN/SW with depth soil water weighting
method (NVCN = 0), which is a function of soil water content and is directly linked with ET, wasused. Parameters PARM-92 and PARM-20 were found to be the third and fourth most sensitive
parameters for streamflow prediction. Parameters APM and PARM-90 and PARM-92 were lesssensitive and thus not used for calibration.
Table 3 APEX sensitive parameters and final calibrated values for streamflow calibration
Description

Range

Defaultvalue

Optimal
value

RFPO

Return flow ratio: (Return flow)/(Return flow + Deep
percolation)

0.05 – 0.95

0.5

0.85

RFTO

Groundwater residence day

10 – 50

30

60

PARM (12)Soil evaporation coefficient

1-2

2

1.5

PARM (17)Soil evaporation plant cover factor

1.5 – 2.5

1.5

2.5

PARM (20)

Runoff CN initial abstraction

0.8 – 1.5

1

1

PARM (34)

Hargreaves PET equation exponent

0.5–0.6

00

PARM (40)Groundwater residence day

10 - 50

30

60

PARM (42)

SCS curve number index coefficient

0.3 -2.5

0.4

0.4

PARM (49)

Groundwater storage threshold

0.001 - 1.0

0.25

0.99

PARM (90)Subsurface flow factor

1–100

1

1

PARM (92)

Runoff volume adjustment factor

0.1–2.0

1

1

Parameters

The APEX hydrology model was calibrated by using the 18 years of the measured streamflow
data (1997 - 2015) (Fig. 4a) followed by validation (2016 - 2017) using the monthly parameters in
Fig. 4b. Model parameter initialization was carried out prior to calibration (warm-up period: 19901996). Final calibrated values of sensitive parameters are listed in Table 3. Based on statistical
performance measure ratings of Moriasi et al, (2007) as shown in Table 4, the simulation of APEX
model in identifying the water discharge showed very good agreement with the observed monthly
streamflow both calibration and validation for a monthly time step of NSE = 0.60, R 2 = 0.62 and
PBIAS = 2.50%, and NSE = 0.71, R2 = 0.80 and PBIAS = 28.22% for model calibration andvalidation, respectively (Table 5 and Fig. 3).
Table 4 Model performance evaluation rating
Statistic
R2
NSE
PBIAS

Unsatisfactory< 0.50< 0.50> ±25

Evaluation rating
SatisfactoryGood
0.50 ‒ 0.60
0.60 ‒ 0.70
0.50 ‒ 0.65
0.65 ‒ 0.75
±15 < PBIAS < ±25±10 < PBIAS < ±25

Very good
0.70 ‒ 1
0.75 ‒ 1< ±10

Table 5 APEX model performance on a monthly basis of observed and simulated
streamflow calibration (1997–2015) and validation (2016–2017) in Stung Chinit
Catchment
Station Name
Kampong Thmar

Component
Calibration
Validation

NSE
0.60
0.71

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R2
0.62
0.80

PBIAS (%)
2.50
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Fig. 3 The monthly comparison of time series measured and simulated streamflow
and corresponding precipitation data for Stung Chinit Catchment

(a)

(b)

Fig. 4 The monthly comparison of measured and simulated streamflow for (a) calibration(1997-2015), and (b) validation (2016-2017) periods for Stung Chinit Catchment
We illustrated a scatter plot with line 1:1 and regression lines to compare the results between
the observed and simulated monthly streamflows during calibration and validation (Fig. 4). The
model overpredicted the flow when the observed values were less than approximately 320 m3/s (Fig4a). The model had a large error of prediction when it predicted a monthly streamflow peak greaterthan 490 m3/s. During validation, the low-flow values (<150 m3/s) were scattered near the 1:1 line,
but most of the high-flow values (> 250 m3/s) were underpredicted (Fig. 4b).
APEX Annual Sediment Simulation
Due to the limited data of sediment yield for the model calibration, we could not do the calibrationon the sediment yield. The annual suspended sediment load was just estimated as shown in (Table
6). The annual sediment yield is mainly varied with the amount of surface runoff in the catchment.
The severe sediment rate of 68.14 ton/ha/year occurred in 1999. This can be the result of forest
decline due to the land encroachment and forest-logging in the catchment. Since then, the sedimentyield is declining dramatically. The huge erosion occurred in 2011 and 2013 because the country
experienced the flooding across the study area at that time; resulted in severe sediment occurrence.
Variability of Surface Runoff and Sediment Yield in the CatchmentⒸ ISERD

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The mean annual surface runoff was 212.03 mm (varied from 72.56 mm to 435.59 mm). The
sediment yield varied from 10.21 ton/ha/year in the riparian lowlands of the Stung Chinit main river
channel to 68.14 ton/ha/year primarily in the mountain highlands from, with an average sedimentyield rate of 29.62 ton/ha/year for the entire basin (Table 6).
Table 6 Water balance and sediment components
Year
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
Mean

PRECIP (mm)
1279
1182
1910
1550
1521
1196
1261
1271
1019
1581
1517
1412
1640
1468
1592
1447
1616
1352
931
1167
1095
1381

QSS (mm)
176.33
192.46435.59243.49209.23112.45
126.65172.6197.83
313.98261.03171.64284.64217.74347.19234.73355.71
189.3872.56
134.26103.16212.03QSW (mm)
176.28192.39435.43243.36209.11
112.4
126.59172.4897.79
313.76260.86171.55284.47217.60346.97234.61355.49189.2472.52
134.19103.09211.91

QTS (mm)
286.97306.70708.31495.76439.94243.95301.3
489.18385.16659.87566.53363.78532.77446.53641.92475.51652.86442.01184.78295.92257.83437.03YW (t/ha)
16.95
21.88
68.14
37.46
26.88
11.18
16.13
29.90
10.21
40.67
29.34
20.75
40.07
30.06
52.52
26.57
58.56
35.66
12.76
16.00
20.25
29.62

PRECIP = Precipitation; QSS= Surface runoff; QSW = Watershed outflow; QTS= Total flow from all subarea and
YW= Watershed sediment yield

CONCLUSION
Our results showed that the Stung Chinit catchment experienced soil loss during 2011 and 2013 dueto the big flooding occurrence in the catchment area. A calibrated and validated APEX model wasable to estimate streamflow and sediment yield. The model also provided a good qualitativedescription on the effects of land uses and geographic indicators on streamflow and sedimentestimation. The mean annual surface runoff was 212.03 mm varied from 72.56 mm to 435.59 mm,
while the sediment yield varied from 10.21 tons/ha/year in the lowlands of the Stung Chinit
catchment main river channel to 68.2 tons/ha/year in the highlands, with an annual sediment yield of
29.2 tons/ha/year. Most of the sediment yield came from the eastern part and near the outlet of thethe Stung Chinit catchment. Land use management in lowlands could be improved while practisingsome soil erosion control methods in highlands and minimizing inappropriate tillage practices inareas with slopes greater than 25 to prevent soil loss. Due to our data limitations, we did not compare
the impact of land use change on streamflow and sediment load in this watershed, but it is important
to determine how the drivers of streamflow and sediment load will be changed in response to land
use change and climate change in the watershed. Nevertheless, this research should be able to develop
a reliable physically-based streamflow model, which is capable of illustrating and defining thecritical source areas and conditions of sediment yield.

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ACKNOWLEDGEMENTS
This research and publication are made possible by the generous support of the American People
provided to the Royal University of Agriculture through Partnerships for Enhanced Engagement in
Research (PEER) Cycle 7 funded by the United States Agency for International Development(USAID), implemented by the National Academy of Sciences (NAS) under Sponsor Cooperative
Agreement No. AID-OAA-A-11-00012 of Subaward Number: 2000010295. The technical expertiseand contributions of his USDA-ARS partner is also appreciated. The contents are the sole
responsibility of the authors and do not necessarily reflect the views of NAS, USAID or the UnitedStates Government. Moreover, the research and publication are made possible by the generous
support of the American people through support by the United States Agency for International
Development to the Feed the Future Innovation Labs for Collaborative Research on Sustainable
Intensification (Cooperative Agreement No. AID-OAA-L-14-00006, Kansas State University).
Thanks to Kelly Robbins, Senior Program Officer, the National Academy of Sciences (NAS), for her
support and guidance on the research grant implementation. The author also profoundly thank to Dr.
Abeyou W. Worqlul from Texas A&M AgriLife Research and the United State Department ofAgriculture (USDA) for technical support, assistance, and consultation as well as the Institute ofTechnology of Cambodia (ITC) and International Fertilizer Development Center (IFDC) for data
provision.
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Bosch, D.D. and Tomer, M.D. 2017. Evaluating the APEX model for simulating streamflow and water
quality on ten agricultural watersheds in the U.S. Transactions of the ASABE, 60 (1), 123-146, Retrieved
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Research article
erd

Effects of Chemical Extraction Methods on Physicochemical
Properties of Shrimp Chitosan
SOCHEATH TONG*Division of Research and Extension, Royal University of Agriculture, Phnom Penh, Cambodia
Email: tongsocheath@yahoo.com

BORARIN BUNTONGDivision of Research and Extension, Royal University of Agriculture, Phnom Penh, Cambodia

LAIKONG SOPHAL
Division of Research and Extension, Royal University of Agriculture, Phnom Penh, Cambodia

SOKMEAN VANN
Division of Research and Extension, Royal University of Agriculture, Phnom Penh, Cambodia

ANTONIO ACEDO JR.
Institute of Crop Science, University of the Philippines Los Banos, Laguna, Philippines
Received 13 July 2021

Accepted 18 October 2021(*Corresponding Author)

Abstract Chitosan extraction methods have not been applied and optimized in Cambodia
whose seafood industry produced tons of shrimp shell waste yearly. This study adopted thechemical extraction method and optimized the deacetylation step from chitin to chitosan
using different concentrations of sodium hydroxide (NaOH). Shrimp waste (exoskeleton) was
sequentially treated with NaOH (3.5%) for deproteination at 80oC; HCl (4%) for
demineralization at 80oC; NaClO (0.315%) for decolorization at ambient temperature, andNaOH (40%, 50%, 60%) at 120oC for deacetylation. Chitosan yield, moisture content, total
ash, lipid, fiber, solubility, nitrogen content, viscosity, and degree of deacetylation were
determined. The commercial chitosan bought from a local market was included forcomparison. NaOH at 50% was found to be the optimum concentration for deacetylation
based on increased solubility (96.27%), reduced ash content (0.56%) and increased degree ofdeacetylation (83.23) as compared to that of 40% NaOH (93.61% solubility, 1.25% ash
content, and 74.45 degree of deacetylation) though chitosan yield in the former (20.59%) was
lower than that in the latter (25.23%). Increasing the NaOH level to 60% had no significant
advantage. Lipid and fiber contents were not significantly affected. The characteristics ofchitosan extracted with 50% NaOH at deacetylation stage were comparable to that of thecommercial chitosan.
Keywords shrimp shell, chitin, chitosan, deacetylation, NaOH concentration

INTRODUCTION
Cambodia’s seafood industry has long been faced with waste disposal problem, mainly shrimp shells
from factories producing dried shrimps for local and export markets. Habitually, seafood waste isburned, land filled, dumped at sea or left to get spoiled. This has negative impact on the environment,
biodiversity and human health. A sustainable solution is to transform shrimp shell waste into highvalue products, particularly chitin and chitosan which have multiple applications in agriculture, foodand beverage, medical, pharmaceutical. cosmetics and personal care, textile, environment, health,and water sectors. Global demand for chitin and chitosan is rapidly growing and is projected at
281,700 metric tons in 2027 (https://www.strategyr.com/market-report-chitin-and-chitosanderivatives-forecasts-global-industry-analysts-inc.asp). However, global supply may remain short byⒸ ISERD

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over 50% of demand as in 2022 projections of global demand of 155,500 MT against supply of only
70,000 MT.
Chitin, a crystalline polysaccharide with high molecular weight, is the second most abundantorganic compound after cellulose (Rinaudo, 2006; Kumari et al., 2015). It is considered as a natural
fiber that is found in shells of marine animals, such as shrimps and lobsters, insect shells and in cell
walls of several fungi and yeasts. In its structure, chitin is often linked to the other major constituentsof the carapace, forming covalent bonds with 30-40% proteins and a complex matrix containing 3050% calcium and phosphate carbonate and 20-30% of chitin. Extraction of chitin from shrimp shells
involves at least two steps: deproteinization which removes proteins and undesired materials such as
pigments and is often performed with dilute NaOH solutions, followed by demineralization whichremoves all minerals (e.g. CaCO3) by using dilute HCl solutions. A decolorization step can be added
to remove pigments and produce white product. The chitin produced is further processed by partial
deacetylation to produce chitosan. Chitosan is a cationic semi-crystalline linear aminopolysaccharide of 1-4 linked N-acetyl glucosamine and glucosamine units; a white, hard, inelastic
and nitrogenous polysaccharide (Cheba, 2011). It has three reactive functional groups, amine,
primary and secondary hydroxyls that offer potential for covalent and ionic modifications allowing
the improvement of its mechanical and biological properties. In addition, chitosan is a biodegradable,
nonallergenic, biocompatible, antimicrobial, renewable, nontoxic product. Both chitosan and chitin
have enormous economic value because of their flexible biological properties as well as their highnitrogen content (6.89%) as compared to synthetically substitute cellulose (1.25%). However, thecrystallinity and insolubility of chitin demote its commercial applications.
The degree of deacetylation of chitosan ranges from 56% to 99% with an average of 80%,depending on the crustacean species and the preparation methods (No and Lee, 1995; No et al., 2000).
Chitin with a degree of deacetylation greater than 50% is generally known as chitosan (Younes et al.
2014). In the deacetylation of chitin, several factors can influence the characteristics of resulting
chitosan product. Rege and Block (1999) found that temperature and processing time were the mostsignificant factors having noteworthy impact on degree of deacetylation and molecular weight. Tsaih
and Chen (2003) concluded that molecular weight and deacetylation of chitosan are principally
influenced by the concentration of NaOH, temperature, duration of reaction and recurrence ofalkaline treatment steps.
OBJECTIVE
This study is a first attempt to harness available experience elsewhere on the chemical extraction of
chitosan for shrimp shell waste of Cambodia’s seafood industry and determined the effects ofdifferent NaOH concentrations during the deacetylation step producing chitosan from chitin.
METHODOLOGY
Chitosan Extraction
Figure 1 shows the process flow for chitosan extraction. Shrimp shell waste was collected from a
local dried shrimp factory in Sihanoukville province, Cambodia, and brought to the Faculty of AgroIndustry, Royal University of Agriculture, Phnom Penh, Cambodia. The shells were properly washedwith clean water prior to chitosan extraction which followed the procedures of Divya et al (2014)
and Puvvada and Vankayalapati (2012).
The shrimp shells were deproteinized with 3.5% NaOH at 80oC for 3 hours with constantstirring at a solid to solvent ratio of 1:10 (w/v). Samples were then filtered under vacuum, and thefiltrate was washed with tap water for 30 minutes and oven-dried.
Demineralization was performed by washing the deproteinized shells with 4% HCl for 4 hours
at ambient temperature with a solid to solvent ratio of 1:10 (w/v), then filtered under vacuum. The
filtrate was washed for 30 min with tap water and oven-dried.
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The chitin produced was decolorized with 0.315% sodium hypochlorite for 15 min; with a solid
to solvent ratio of 1:10 (w/v), followed by washing in tap water and drying under vacuum for 2-3
hours until the powder was crispy.
Deacetylation of chitin to produce chitosan was done using 40, 50 or 60% NaOH for 3 hours at
120oC with a solid to solvent ratio of 1:10 (w/v). The resulting chitosan was washed to neutrality inrunning tap water, rinsed with distilled water, filtered, and dried at 60oC for 24 hr in the oven.
Chitosan yield was calculated by comparing the weight measurements of the raw material to thechitosan obtained after treatment (Kiruba et al., 2013).

Fig. 1 Process flow for the extraction of Chitosan from shrimp shell waste
Proximate Analysis
Moisture, fiber, fat and nitrogen contents were analyzed following the AOAC (2001, 2005) methods.
Total ash content was determined by the method of the Food Safety and Standards Authority of India(2012). Commercial chitosan (Sigma) was included in all relevant analysis as control.
Degree of Deacetylation
The titration method of Czechowska-biskup et al (2012) was followed. Dried chitosan (0.2 g) was
dissolved in 20 ml 0.1 M hydrochloric acid and 25 ml deionized water. After 30 minutes continuous
stirring, next portion of deionized water (25 ml) was added followed by stirring for 30 minutes. Whenchitosan was completely dissolved, solution was titrated with a 0.1N sodium hydroxide (NaOH)
solution using automatic burette (0.01 ml accuracy). Degree of deacetylation (DA) of chitosan was
calculated using formula (1):
𝑉 −𝑉

2
1
𝐷𝐴[%] = 2.03 × 𝑚+0.0042(𝑉 −𝑉 )
2

(1)

1

where m: weight of sample, V1, V2: volumes of 0.1 N NaOH corresponding to the deflection points,
2.03: coefficient resulting from the molecular weight of chitin monomer unit, 0.0042: coefficientresulting from the difference between molecular weights of chitin and chitosan monomer units.
Solubility
Solubility of chitosan was determined by placing chitosan powder (0.1 g in triplicate) into acentrifuge tube (known weight) then dissolving in 10 ml of 1% acetic acid for 30 min using an
incubator shaker operating at 240 rpm and 25oC. The solution was then immersed in a boiling water
bath for 10 minutes, cooled to room temperature and centrifuged at 10,000 rpm for 10 min. TheⒸ ISERD

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supernatant was decanted. The undissolved particles were washed in distilled water (25 ml) thenagain centrifuged a 10,000 rpm. The supernatant was removed and the undissolved pellets dried at
60oC for 24 hours. The dried pellets were weighed and the percentage solubility was calculated asfollows:[(Initial weight of tube + chitosan) - (Final weight of tube + chitosan)] x 100(Initial weight of tube + chitosan) – (Initial weight of tube)(2)

Viscosity
Viscosity of chitosan was determined with a viscometer. Chitosan solution was prepared in 1% acetic
acid at a 1% concentration on a dry basis. Measurement was made in duplicate using a No. 5 spindle
at 50 rpm on solutions at 25oC with values reported in centipoises (cPs) unit.
Statistical Analysis
A completely randomized design with three replications was used. Data were subjected to analysis
of variance and treatment mean comparison by least significant difference (LSD) test using the SPSS
Statistical Package.
RESULTS AND DISCUSSION
In general, higher deacetylation degree increases the better solubility and viscosity of chitosan, thebetter chitosan quality. Deacetylation with 40% NaOH resulted in highest chitosan yield of about
25.2% (Table 1). Increasing the concentration of NaOH to 50-60% significantly decreased chitosan
yield to about 20.6%. However, the degree of deacetylation was lower with 40% NaOH (74%) thanwith 50-60% NaOH (83%), the latter was comparable to that of commercial chitosan. Similarly,
deacetylation with 50-60% NaOH significantly increased the solubility and viscosity of chitosan
which were comparable to that of the commercial chitosan. Chitosan produced using 40% NaOH had
the lowest solubility and viscosity. Chitosan produced with 50% NaOH had moisture, ash, fiber andnitrogen contents which were statistically comparable to that of the commercial chitosan (Table 2).
With 40% NaOH, the chitosan produced had significantly higher ash and fiber contents and lower
nitrogen content than the commercial control. NaOH at 60% had similar effects as 50% NaOH exceptthat it had the lowest moisture content among treatments. Total fat content did not vary with treatment
and ranged from 1.12-1.49%
Table 1 Physicochemical characteristics of chitosan extracted from shrimp shells
using different NaOCl concentrations for deacetylation
NaOH concentration
Commercial chitosan
40% NaOH
50% NaOH
60% NaOH
Probability
LSD (5%)CV (%)

Yield of chitosan(%)
25.23a20.59b
20.63b
**
0.882
2.00

Degree ofdeacetylation
87.38a74.45b83.23a83.35a
**
5.342
3.00

Solubility (%)

Viscosity (log mPa/s)

95.65a93.61b96.27a96.29a
**
0.287
2.00

3.17b
2.84c
3.20a
3.18ab
**
0.022
0.00

Mean separation within columns by LSD, 5%. a, b, c Duncan's multiple range test

The results indicate that 50% NaOH was the optimum concentration for deacetylation of chitin
to produce chitosan. The chitosan produced had degree of deacetylation, solubility and viscosity of
83.23%, 96.27% and 3.20 log mPa/s, respectively, and proximate composition of 11% moisture
content, 0.56% total ash, 1.33% total fat, 1.47% total fiber and 7.29% nitrogen content which wereⒸ ISERD

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statistically similar to that of commercial chitosan. Previous studies have successfully extracted
chitosan from shrimp shell waste (e.g. Kandile et al., 2018; Nacer et al., 2019; Islam et al., 2020;
Rasweefali et al., 2021) with similar results as the present study except for the lower chitosan yieldobtained (Divya et al., 2014; Puvvada and Vankayalapati, 2012). Using lower NaOH concentration
for deacetylation may increase yield of chitosan but other physicochemical properties werecompromised. On the other hand, higher NaOH concentration gave no added benefit and may only
increase the cost of extraction.
Table 2 Proximate analysis of chitosan extracted from shrimp shells
using different NaOCl concentrations for deacetylation
NaOH concentration
Commercial Chitosan
40% NaOH
50% NaOH
60% NaOH
Probability
LSD (5%)CV (%)

Moisture content(%)
10.53ab11.78a11.00b
10.14c
**
0.208
9.00

Total ash
(%)
0.59b
1.25a
0.56b
0.55b
**
0.132
10.00

Total fat
(%)
1.12
1.16
1.33
1.49
ns
0.365
13.00

Fiber (%)
1.33b
1.78a
1.47ab
1.36b
**
1.563
1.00

Nitrogencontent (%)
7.12%a
6.12b
7.29a
7.34a
**
0.287
0.00

Mean separation within columns by LSD, 5%. a, b, c Duncan's multiple range test

CONCLUSION
Deacetylation is the final and critical stage to produce chitosan from chitin, both of which weresuccessfully extracted in this research. NaOH at 50% was optimum for the deacetylation step. The
physicochemical properties of chitosan extracted with 50% NaOH were comparable to that of thecommercial chitosan. Future research could delve into manipulation of other deacetylation conditions(e.g. temperature and duration of deacetylation) that could increase the yield of chitosan without
affecting the physicochemical characteristics.
ACKNOWLEDGEMENTS
This research was funded under the Higher Education Improvement Project (HEIP). International
Development Association (IDA) CREDIT No: 6221-KH, with support provided by the Royal
Government of Cambodia (RGC).
REFERENCES
AOAC. 2001. Analytical methods 1. Moisture Content; Method 3. Biuret Method, 124-130, Maryland.
AOAC. 2005. Official methods of analysis, Volume 1, AOAC International, Maryland.
Cheba, B.A. 2011. Chitin and chitosan: Marine biopolymers with unique properties and versatile applications.
Global Journal of Biotechnology &. Biochemistry, 6 (3), 149-153.
Czechowska-biskup, R., Jarosińska, D., Rokita, B., Ulański, P. and Rosiak, J.M. 2012. Determination of degreeof deacetylation of chitosan - comparison of methods. Progress on Chemistry and Application of Chitin
and Its Derivatives, XVII, 5-20.
Divya, K., Sharrel, R. and Jisha, M.S. 2014. A simple and effective method for extraction of high purity
chitosan from shrimp shell waste. Proceedings of the International Conference on Advances in Applied
Science and Environmental Engineering, 141-145.
FSSAI. 2012. Manual for analysis of beverages (coffee, tea, cocoa, chicory), sugar and sugar products andconfectionery product. Food Safety and Standards Authority of India, New Delhi.
Islam, A., Islam, M.S., Zakaria, M.U., Paul, S.C. and Mamun, A.A. 2020. Extraction and worth evaluation of
chitosan from shrimp and prawn co-products. American Journal of Food Technology, 15, 43-48.
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Kandile, N.G., Zaky, H.T., Mohamed, M.I., Nasr, S.A. and Ali, Y.G. 2018. Extraction and characterization of
chitosan from shrimp shells. Open Journal of Organic Polymer Materials, 8, 33-42.
Kiruba, A., Uthayakumar, V., Munirasu, S. and Ramasubramanian, V. 2013. Extraction, characterization andphysicochemical properties of chitin and chitosan from mud crab shell (Scylla Serrata), Indian Journal ofApplied Research, 3 (8), 44-46.
Kumari, S., Rath, P., Sri Hari Kumar, A. and Tiwari, T.N. 2015. Extraction and characterization of chitin andchitosan from fishery waste by chemical method. Environmental Technology and Innovation, 3, 77-85.
Nacer, B., Zohra, B. and Salah, J. 2019. Preparation and characterization of chitosan extracted from shrimp
shells waste and chitosan film: Application for Eriochrome black T removal from aqueous solutions.
Applied Water Science 9 (91), Retrieved from https://doi.org/10.1007/s13201-019-0967-z
No, H.K. and Lee, M.Y. 1995. Isolation of chitin from crab shell waste. Journal Korean Soc. Food Nutrition
24 (1), 105-113.
No, H.K., Lee, K.S. and Meyers, S.P. 2000. Correlation between physicochemical characteristics and binding
capacities of chitosan products. Journal of Food Science, 65 (7), 1134-1137.
Puvvada, Y.S. and Vankayalapati, S. 2012. Extraction of chitin from chitosan from exoskeleton of shrimp for
application in the pharmaceutical industry. International Current Pharmaceutical Journal, 1 (9), 258-263.
Rasweefali, M.K., Sabu, S., Sunooj, K.V., Sasidharan, A. and Martin Xavier, K.A. 2021. Consequences ofchemical deacetylation on physicochemical, structural and functional characteristics of chitosan extracted
from deep-sea mud shrimp. Carbohydrate Polymer Technologies and Applications, 2, 100032.
Rege, P.R. and Block, L.H. 1999. Chitosan processing: Influence of process parameters during acidic andalkaline hydrolysis and effect of the processing sequence on the resultant chitosan’s properties.
Carbohydrate Research, 321, 235-245.
Rinaudo, M. 2006. Chitin and chitosan: Properties and applications. Progress in Polymer Science (Oxford), 31(7), 603-632.
Tsaih, M.L. and Chen, R.H. 2003. The effect of reaction time and temperature during heterogenous alkali
deacetylation on degree of deacetylation and molecular weight of resulting chitosan. Journal of Applied
Polymer Science, 88, 2917-2923.
Younes, I., Hajji, S., Frachet, V., Rinaudo, M., Jellouli, K. and Nasri, M. 2014. Chitin ex-traction from shrimp
shell using an enzymatic treatment. Antitumor, antioxidant and antimicrobial activities of chitosan,International Journal of Biological Macromolecules, 69, 489-498, Retrieved from https://www.
strategyr.com/market-report-chitin-and-chitosan-derivatives-forecasts-global-industry-analysts-inc.aspⒸ ISERD

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Research article
erd

Evaluation of Organic Rice Contract Farming Model in
Cambodia
CHANMONY SOK*
Graduate School of Agriculture, Tokyo University of Agriculture, Japan
Email: Chanmony0223@gmail.com

TOMOHIRO UCHIYAMA
Faculty of International Agriculture and Food Studies, Tokyo University of Agriculture, Japan

NINA N. SHIMOGUCHI
Faculty of International Agriculture and Food Studies, Tokyo University of Agriculture, Japan
Received 15 January 2020

Accepted 29 October 2021(*Corresponding Author)

Abstract In Cambodia, organic farming under contract farming scheme is considered as oneof the measures for better access to markets and poverty reduction since 2012. Previous
literature revealed that organic rice farmers can generate more profit by engaging in contract
farming. But only a few organic farming cases under contract farming succeeded. Since there
was a lack of empirical study on current condition and issues of contract farming design andarrangement, this study clarified the effectiveness of organic rice contract farming
arrangement and determined the most suitable contract farming model for small-scale farmers
to maximize economic benefits. From a total of 5,053 organic rice contract farming
households in Preah Vihear province, a total of 90 respondents were randomly selected. In
the study area, two different organic rice contract farming models were found, namelyintermediary model (Model A) and the multipartite model (Model B). Economic analysis
approach revealed that even farmers in model A received a higher rice price than model B,
but there were still model A farmers who did side-selling much more than model B farmers.
Thus, third-party in model B seemed to play an essential role in contract farming to makeproper arrangements as well as to balance the bargaining between farmers and contractors.
In general, model B contract farming (also known as multi partite model) is recommended
for organic rice farmers to maximize their economic benefits as well as profits.
Keywords contract farming model, organic rice, small-scale farmers.

INTRODUCTION
In Cambodia, about 90% of the poor live in rural areas and rely on agriculture for their primarysources of livelihood (NIS, 2008). To promote and improve agricultural productivity and marketing
access for agricultural products, the government has been promoting contract farming (CF) andorganic farming to remove some constraints on agricultural growth and linkages to input and output
markets. (MAFF Cambodia, 2012). However, the advantages of CF can only be achieved if contract
arrangements are well managed and are mutually beneficial to both farmers and contractors. For CF
overview, various forms of CFs have been practiced in Cambodia since 1950, mainly throughinformal arrangements. But this stopped during the civil war between 1975 and 1979 (Couturier, etal. 2006). Recently, there have been a few organic rice contract farming reintroduced though some
contracts had already failed, and very few have succeed (Cai et al., 2008; Nou and Heng, 2013).
According to Cai et al. (2008) and Nou and Heng (2013) found that serious managerial issues
including remain, leasing to the poor management. As a result, farmers have often slipped out of thecontract before the end of the contract period.
Preah Vihear province, located in northern Cambodia, is known as the largest area producing
organic rice within contract farming. As shown in table 1, there are 32 Agriculture Cooperatives(ACs) with 5,053 total members. However, the actual sale was low in some years due to natural
disasters and some problems in contract farming arrangements.
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Table 1 Organic rice contract farming in Preah Vihear Province
Year

Agriculture
Cooperatives (AC)Member(HH)

Cultivatedarea(ha)Estimate-Productionin Contract (tons) (a)

2014
2015
2016
2017
2018

8
12
25
32
32

891
1,669
3,151
5,162
5,053

2,293
4,185
8,703
15,812
16,052

1,800
8,666
13,79526,53826,786

Actual sale
Tons
Percentage(b)(b)/(a)
1,466
81
2,790
32
11,47683
13,98453
1,555
43

Source: Provincial Agriculture Department, 2019

For this study, CF is defined as arrangements where farmers are the ones who provide land,
labor, and capital; and contractors provide technical supports, requirement supports, and market tofarmers.
Modalities of Contract Farming and Types of Contracts
According to FAO (2001) there are ﬁve contract farming models. 1) Centralized: an agribusinesscompany buys produce from many small-scale farmers with tight control over quality and quantity.
2) Nucleus estate: an agribusiness company combines CF with direct involvement in plantation
production. 3) Multipartite: farmers sign contracts in a joint venture established between an
agribusiness company and a local entity. 4) Intermediary: an agribusiness company may havecontracts with intermediaries who then sign contracts with a larger number of farmers. 5) Informal:
more informal verbal purchase agreements are signed on a seasonal basis, with inputs provided by
the company often being restricted to seed and fertilizer.
OBJECTIVE
This study aims to understand the effectiveness of organic rice contract farming (ORCF) arrangementand determine which contract farming model is the most suitable for small-scale farmers with respect
to maximizing benefit and farm incomes. Specifically, this study aims to:
1. identify the ORCF models by small-scale farmers in the study area;
2. determine the effectiveness of each contract farming model on small-scale farmers livelihood interm of income generated, and productivity; and3. evaluate the difference ORCF models with focus on benefit and contract enforcement.
METHODOLOGY
In this study, both primary and second data were collected. A total of 90 respondents were randomly
selected from 5,053 organic rice contract farming households within 2 different ORCF models in
Preah Vihear Province. Contractors, agricultural officers, NGOs, and union of agricultural
cooperative were interviewed using questionnaire forms and groups discussions. Descriptive andprofitability analyses were utilized.
RESULTS AND DISCUSSION
Organic Rice Contract Farming Models’ Characteristic
From field observation, in the study area, there are two different organic rice contract farming models
were identified as follows.
Intermediary model (Model A): Farmers and contractors are directly engaged to each other;farmers who provide land, labors, and capital; and contractors provide technological supports,
requirement supports, and market.
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Multipartite model (Model B): Union agriculture cooperative links farmers to contractors andtechnical support; there is support from NGOs to union and farmers; farmers who provide land, labor,
and capital and pay for union operation; and contractors provide markets.
Table 2 Arrangement of contract farming models
Categories
Farmers
Contract formulas
Contract format
Crop schedule
Pricing policies
Technical assistance
Loan
Input provision
Training provision
Communication
Monitoring
Cost of operation

Model A
Certified and cooperative
agriculture (AC) member
Based on market specifications
Legally formal agreement
Yes
Fixed before harvesting 1-3 weeks
by contractors
Sometimes
No
LimitedSometimes
Through cooperative
SometimesAC

Model B
Certified and cooperative member inUnion of AC
Based on market specifications
Legally formal agreement
Yes
Fixed before harvesting 1-3 weeks bycontractors and Union
Yes
Yes
LimitedFrequently
Through union cooperative
Sometimes
Union + AC

Source: Field survey, 2019

All farmers in both models are certified by the same certification institute. Contract farming
agreement, crop schedule, technical assistance, and input provision are similar in both contract
farming models. However, contract farming model A did not provide loans to ACs or farmers, while
ACs in model B could get loans from union agriculture cooperative. In addition, farmers in model B
could get more support than farmers in model A. For example, union agriculture cooperatives arewith farmers and contractors to set up price of organic rice. However, farmers in model B must pay
the union 30 riels/kg of their organic rice production and another 30 riels/kg as AC operation cost
while farmers in model A need to pay 30 riels/kg only as AC operation cost. Overall, all those support
and arrangements affected farmers’ productivity, as well as profits.
Organic Rice Farmers’ Characteristic in Both Contract Farming Models

Fig. 1 Income source of farmers in both models
Source: Field survey, 2019

Farmers in both models depend on organic rice cultivation as main income; this is about 50% of total
income, followed by off-farm income such as wages, construction name as a few, and livestock
breeding on their farms. Beside rice farming, farmers in both models produce other crops such as
cassava and cashew nuts. In addition, all farmers could grow organic rice once a year, and most of
the farmers do long maturity rice rather than medium maturity. Recently, direct-seeding method isthe common practice in organic rice cultivation in the study area while transplanting method isdecreasing.
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Table 3 Organic rice contract farmers' characteristic
Items
Number of Household (HH)
Family size (person)
Age (years)
Farming experiences (years)
Education (years)
Planted rice land size (ha)Income (rice) per HH
Income (rice) per ha (riels/year)

Model A
45
4.36
44.29
25.16
6.22
4.25
8,671,311
2,101,846

Model B
45
4.76
40.22
21.80
4.49
3.44
8,608,900
2,611,896

A-B(0.40)
4.07
3.36
1.73
0.81
62,411(510,050)

T-Stat(1.36)
1.80
1.46
2.65
1.86
0.07
(4.28)

*
**
*
**
**
*

Source: Field survey, 2019, Note: *Signification at level 0.06 to 0.10 **Signification at level less than 0.05

Farmers in model A are 4 years older and use 0.81ha of rice cultivation land more than farmers
in model B. Moreover, income from organic rice per HH are very similar in both models, but income
from organic rice per ha in model B is higher than farmers in model A meaning there are somedifferences in each productivity.
Profitability of Organic Rice Farming in Both Models
Table 4 Total production cost of organic rice production
Items
Variable cost
Fuel consumption ofLand preparation
Transportation
Seed
Threshing
Combine harvester
Fixed cost
Total labor cost
Family labor
Hired labors
Exchange labors
Total production cost

Unit: '000 riels /haModel A
Model B
Direct seeding
Transplanting
Direct seeding
Transplanting
MediumLate
MediumLate
MediumLate
Medium
Late
485.1
515.7
282.9
258.1
569.7
515.2
587.1
353.9
55.9
18.1
303.8
70.0
37.3
259.2
600.1
234.0
292.1
74.0
1,344.4

53.5
18.0
197.5
64.1
182.6
288.2
532.0
224.7
237.9
69.4
1,335.9

56.0
19.6
126.0
81.3
259.2
983.5
356.8
506.7
120.0
1,525.6

54.3
18.8
105.0
80.0
296.4
966.6
343.3
570.0
53.3
1,521.1

57.8
18.5
305.8
83.9
103.7
254.9
511.6
217.5
208.2
85.9
1,336.2

57.9
18.0
179.4
75.2
184.6
273.2
457.1
213.1
153.9
90.0
1,245.4

58.7
20.7
139.8
105.1
262.7
246.9
665.1
206.6
251.2
207.3
1,499.1

58.6
20.0
113.8
105.3
56.3
274.6
850.0
350.0
287.5
212.5
1,478.5

Source: Field survey, 2019, Note: Labors cost is 20,000 riels per 8 hours per person. 4050 riels= 1USD (2019/10/01)

As shown in Table 4, farmers in model A spent more on labor cost due to a lower use of combine
harvester services while farmers in model B received more support from the union including combine
services during harvesting. Overall, farmers in model B spent less in production cost than farmers inmodel A. Moreover, family labor and exchange labor are considered as noncash cost because farmers
did not pay in cash. However, farmers in model B still use more exchange labor than farmers inmodel A; this affected the cash income in both models. The study found that when there weredifferences in cash incomes, farmers’ decisions were also different.
In Table 5, all organic rice prices were already deducted from the cost of union and AC.
Therefore, contract farming model A provided higher price of rice than model B but yield in contract
farming model B was a higher in each category. From field observation, farmers in model B usedcombine harvester services during harvesting that could keep the high volume and quality of rice
(preventing grain loss), while almost farmers in model A had done the harvesting by hand. Therefore,
farmers in model B could generate more profit than farmers in model A, especially on cash income.
In addition, medium rice maturity usually could provide higher yield but during that time, there wasdrought in the middle of the cultivation season which affected the yield of medium maturity. Afterall, farmers in model B could generate more profit and cash income than farmers in model A eventhough farmers in model A got higher price.

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Table 5 Total profitability of organic rice production in both contract farming models
Unit: '000 riels/ha
Items
Model A
Model B
Cultivation method
Direct seeding
Transplanting
Direct seeding
Transplanting
Rice typeMedium Late Medium Late Medium Late Medium Late
Yield (Tons/ha)
1.74
1.64
2.05
2.00
1.96
1.87
2.30
2.15
Price (Riels/kg)
1,407
1,117
1,510
1,130
1,384
1,087
1,405
1,108
A.Gross revenues
2,448.6 1,831.9 3,095.5 2,260.0 2,712.7 2,027.7 3,231.5 2,382.2
a. Total Variable cost
485.1
515.7
282.9
258.1
569.7
515.2
587.1
353.9
b. Total Fixed cost
259.2
288.2
259.2
296.4
254.9
273.2
246.9
274.6
c. Total Labor cost
600.1
532.0
983.5
966.6
511.6
457.1
665.1
850.0
B.Total noncash cost
308.0
294.1
476.8
396.6
303.4
303.2
413.9
562.5
C.Total Production cost (a+b+c) 1,344.4 1,335.9 1,525.6 1,521.1 1,336.2 1,245.4 1,499.1 1,478.5
D.Total Cash income (A-C+B)
1,412.2
790.1 2,046.7 1,135.5 1,679.9 1,085.4 2,146.3 1,466.2
E.Total profit (A-C)
1,104.2 496.0 1,569.9 738.9 1,376.5 782.2 1,732.4 903.7
Source: Field survey, 2019, Noted: 4050 riels= 1 USD (2019/10/01)

Key Challenges and Main Concern in Both Organic Rice Contract Farming Models
From field observation in 2019, contractors in both contract farming models made late payment tofarmers which caused some problems in contract farming arrangement such as side-selling. Side
selling referred to farmers who sold some or all their contracted productions to other sellers besidethe contractors. Since those farmers immediately needed cash in hand, they decided to do side selling.
Therefore, farmers who did the side selling received lower unit price compared to unit price incontract farming. In addition, there were about 22.84% of farmer respondents in model A who didside-selling while model B had about 18.56%.
As shown in Fig.2, farmers in model B did side selling less than farmers in model A because
farmers in ACs in model B could get some loans from union to make the payments on time insteadof the late payment from contractors, while ACs in model A used their own capital to make payments
on time. So, it seems that union in model B has played an important role to keep good contract
arrangement.

Fig. 2 Reasons of farmers did side selling in both contract Farming models
Source: Author’s compilation based on field survey, 2019

Table 6 showed that farmers in model A had more concerns than farmers in model B in eachcategory because farmers in model A did not have any third party (e.g. union) to balance the powerof contractors and farmers as well as good arrangement. However, both contract farming modelⒸ ISERD180

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farmers still have concerns; thus, both contract farming models need to improve those conditions.
Moreover, farmers in model B also complained about the high interest rates from the union andoperation costs. In addition, poor infrastructure leads to higher spending on production cost of
farmers and union operation.
Table 6 General benefits and concern in both contract farming models
Categories
N
Concerns
Limited access to credit
Price bargain
Noncompliance
Poor infrastructure

Model A
45%
100

Model B
45

%
100

Total
90

%
100

31
31
33
37

69
69
73
82

15
20
26
38

33
44
58
84

46
51
59
75

51
57
66
83

Source: Field survey, 2019

CONCLUSION
Two different organic rice contract farming models were found in the study area, namely theintermediary model (Model A) and the multi-partite model (Model B). Model B farmers paid moreon third-party (union) operation and resulted in more support (e.g. training, loan) than model A
farmers. As results, model A farmers could get a higher price of organic rice than model B farmers.
However, with the current situation, that of having support from the union which allowed model B
farmers to generate more profit and cash income than farmers in model A. Moreover, there were stillmodel A farmers who did side-selling more than model B farmers. Thus, union in model B seemed
to play an essential role in contract farming to make proper arrangements while ensuring the farmers’
profits and balancing the power of farmers and contractors. Overall, with the current condition, contract
farming model B (also known as multi-partite model) is recommended for organic rice farmers tomaximize their economic benefits and profits.
Part of the limitations of this study was time constraint. Thus, further study should focus on the
key challenges in contract farming relationship within the supply chain in order to propose andcritically evaluate options for improving contract farming conditions for organic rice farmers andintroducing more efficient and sustainable contract design based on all actors in contract farming
using both qualitative and quantitative approaches.
REFERENCES
Cai, J., Luyna, U., Sununtar, S. and Ping, S. 2008. Rice contract farming in Cambodia: Empowering farmers
to move beyond the contract toward independence. ADBI Working Papers, 109, Asian Development Bank
Institute, Tokyo.

Couturier, J., Savun, S. and Ham, P. 2006. Inventory of farmer organizations in Cambodia. MAFF andMinistry of Foreign Affairs of France, Phnom Penh.
MAFF Cambodia. 2012. Policy document on promotion of paddy rice production and export of milled rice.
Ministry of Agriculture Forestry and Fisheries, Phnom Penh.
NIS Cambodia. 2008. Cambodian census. National Institute of Statistic (NIS), Phnom Penh.
Nou, K. and Heng, M. 2013. Emerging contract farming: A case of high quality rice in Cambodia. Phnom Penh,
Cambodia.
Provincial Department of Agriculture. 2019. Preah Vihear province annual report of contract farming 2019.
Preah Vihear Provincial Department of Agriculture, Ministry of Agriculture, Forestry and Fisheries, 6,
Cambodia.

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Research article
erd

The Distance Learning Model on Cross-Cultural
Agriculture: A Case Study of Thai and American 4-H club
SINEENUCH KHRUTMUANG SANSERM*
School of Agriculture and Cooperatives, Sukhothai Thammathirat Open University, Nontaburi,
Thailand
Email: sineenuch.san@stou.ac.th, tukstou@hotmail.com

BUMPEN KEOWAN
Sukhothai Thammathirat Open University, Nontaburi, Thailand

BENCHAMAS YOOPRASERT
Sukhothai Thammathirat Open University, Nontaburi, Thailand

NAREERUT SEERASARN
Sukhothai Thammathirat Open University, Nontaburi, Thailand

PONSARAN SARANROM
Sukhothai Thammathirat Open University, Nontaburi, Thailand
Received 15 January 2020

Accepted 29 October 2021(*Corresponding Author)

Abstract: Learning in the digital age of the 21st century and globalization era, a knowledgebased society, expects students to master the 21st century skills or global competencies rather
than being excelled in their academic performance. The cross-cultural learning concept
supports learning in this era that focuses on the learning of diverse people and culturaldifferences by organizing mutual learning on issues of mutual interests to create wide andvaried learning in line with the needs of the learners and the current trend of global change.
This learning is also in accordance with the needs of 4-H club members that has a variety oflearning needs as well as having a variety of learning styles. The objectives of this researchwere to develop and evaluate a learning model on cross-cultural distance education inagriculture. The research and development model were used. The populations were 1) 162 4H club members from Thailand and the United States. Quantitative data were collected fromthe sample size of 75 using a questionnaire and analyzed using descriptive statistics. 2)
educational experts in Thailand and the United States. 15 experts was determined by using
purposive sampling method. Qualitative data was collected using focus group and analyzed
by content analysis. The results showed that developing a learning model according to the 4H needs included learning interest, expectation, experiences, and knowledge. The
development of a model of distance learning management in cross-cultural agriculture for 4H is divided into 4 phases as follows: seminar defining the learning model, implementationof learning model, evaluation of learning Model, and conducting seminar and summarizing
the learning model. From the evaluation of learning model regarding learning characteristics,
learning methods, learning channels and tools, learning period, learning style and learning
support, 4-H revealed that they were appropriate usefulness and satisfaction at high level andhighest level.
Keywords learning model, cross-cultural, distance education, agriculture, 4-H club

INTRODUCTION
Learning in the digital age of the 21st century and the globalization era is a knowledge-based affair.
Students are expected to master 21st-century skills as well as global competencies apart fromexcelling in their academic performance (Turiman, 2011; OECD, 2018), which is driven by creativeⒸ ISERD

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power and involves the potential of knowledge and wisdom combined with the advancement of
information and communications technology (Sanguankaew, 2008). The curriculum in the 21st
century focuses on critique attributes, interdisciplinary project-based activities, and research-driven
coursework that can connect local communities, countries and the world. Occasionally, students cancollaborate with various projects around the world using a curriculum that emphasizes advanced
thinking skills, multiple intelligence, technology and multimedia (Sangkhaphan, 2013, p. 14)
The goal of Thailand and the United States' 4-H operations is to develop and empower
agricultural youth. This was done by establishing a 4-H groups in schools to promote and encourage
4-H members to gain knowledge and technology related to agriculture, strengthen their agricultural
skills and create attitudes to passion and interest in agriculture and agricultural professions.
Furthermore, the goal is also to develop leadership, thinking, and problems solving skills that can beapplied in their life in the future, especially in globalization and in the 21st century.
The cross-cultural learning concept supports learning in the digital age, focusing on the learningof diverse groups of people and cultural differences by organizing mutual learning on issues ofmutual interests in order to create wide and varied learning in line with the needs of learners and thecurrent trends of global advancement. This learning is also in line with the needs of 4-H clubmembers that have a variety of learning needs as well as having a wider variety of learning styles
with the use of modern technology for learning. Consequently, there is a need for novel forms ofcommunication through social media, chat platforms, and bulletin boards (Weeranakin et al., 2013;
Weeranakin et al., 2014).
Distance learning can transcend geographical boundaries, differences in socio-cultural contexts,
values, and expectations of diverse educational systems, though learners may prove to be its greatest
challenge (Gunawardena, 2014). Distance education is consistent with learning management in the
21st century that focuses on self-directed learning through the use of a variety of media. Therefore,
the application of distance education concepts in cross-cultural learning management between Thaiand American 4-H clubs involves the transfer of knowledge to and between learners in each country
through various types of media, thus allowing learners to have the opportunity to continuously learn
by themselves broadly and with cost-effectiveness.
For the reasons mentioned above, the researchers developed this study. It concerns thedevelopment of learning styles that are in line with the needs of young people in the 21st century whowant to learn from a variety of media and be able to connect local communities in their country withthe world through collaboration with global projects. Moreover, the information can be synthesized
as a guideline for the development of a model for managing distance learning across cultures, in linewith the needs of young people in the 21st century.
OBJECTIVES
The objectives of this research were to develop and evaluate a learning model on cross-cultural
distance education in agriculture of 4-H clubs in Prachamongkol School and Purdue Extension.
METHODOLOGYThis research used the research and development model. Data was collected in both quantitativeand qualitative research (Creswell, 2012). The populations were 1) 112 members of the 4-H club at
Prachamongkol School, Kanchanaburi Province in Thailand and 50 members of the 4-H club of theLegacy Learning Center from Marion County under the extension services of Purdue Extension of
Purdue University, Indiana, USA., totaling 162 persons. Quantitative data were collected from thesample size of 75 using a questionnaire containing questions on a five-point Likert scale andanalyzed using descriptive statistics. The questionnaire was divided into 4 parts including general
information, the context and operating conditions of 4-H, agricultural learning management, andthe need of 4-H for cross-cultural distance learning. 2) Educational experts in Thailand and theUnited States. 15 experts was determined by using purposive sampling method. Qualitative data

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was collected using focus group and analyzed by content analysis. The research conceptual
framework as shown in Fig. 1.
The context
and operating
conditions of
the 4-H club

Agriculturallearning
managementof the 4-H club

Development of a learningmodel on cross-cultural distanceeducation in agriculture

Evaluation of thelearning model oncross-cultural distanceeducation in agriculture

1. Age2. Grade
3. Projectinterests
4. Project
expectations
5. Experiencein Agriculture

1. 4-H group
information
2. Learning
management
3. Learning
outcome4. Learning
support

1. Expectations for participationin the project
2. Learning topics
3. Leaning style and learning
methods
4. Learning channels
5. Learning duration
6. What to exchange withmembers of different cultures
7. Learning supported
8. Recommendation for the
distance learning model oncross-cultural agriculture

1. Appropriateness2. Usefulness
3. Satisfaction

Fig. 1 The conceptual framework of the research
RESULTS AND DISCUSSION
The Context and Operating Conditions of 4-H Club in Prachamongkol School and Purdue
Extension
Thai and American 4-H club context and operating conditions are as follows: 70.0% of Thai 4-H
were females with an average age of 15.02 years old, 36.0% of whom were studying in 7th grade,while 64.0% of American 4-H were females with an average age of 13.56 years with 52.0%
studying in 6th grade. Most of them were interested in joining the project to exchange cross-culturallearning. In terms of culture, agriculture and food in foreign countries, most of the expectations of
4-H members in the project were to get to know and talk to new friends, speak languages, and learn
about the culture of foreign life. Based on the findings, there can be a discussion that in term of new
generation in the 21st century, 4-H club members who want to connect the world has a variety oflearning needs, learning styles with the use of modern technology for learning such as social media.
The school should provide opportunities for student growth through exploring the global throughcollaboration with projects.
Agricultural Learning Management of 4-H club in Prachamongkol School and Purdue
Extension
Agricultural learning management of 4-H club in Prachamongkol School consisted of learning by
doing, constructivism learning, cooperative learning, learning by technology. Agricultural learning
management of 4-H club in Purdue Extension School consisted of school enrichment, special
interest programs, after school, camps and conferences. Based on the findings, there can be a
discussion that the learning management for 4-H club should get in line with the curriculum in theⒸ ISERD

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21st century that focuses on the critique attributes, interdisciplinary project-based, research-driven,and connecting local communities with countries and the world.
Development of Learning Model on Cross-Cultural Distance Education in Agriculture of 4-H
Club in Prachamongkol School and Purdue Extension
Development of learning model on cross-cultural distance education in agriculture was conducted
in 4 phases as follows: 1) seminar defining the learning model on cross-cultural distance educationin agriculture, 2) implementation of learning model on cross -cultural distance education inagriculture, 3) evaluation of learning model on cross-cultural distance education in agriculture, and4) conducting seminars and summarizing the learning model on cross-cultural distance education inagriculture as shown in Fig. 2.

Fig. 2 Development of learning model on cross-cultural distance educationin agriculture of 4-H club
The learning model on cross-cultural distance education in agriculture of 4-H club wasdesigned based on student needs such as learning topics, learning time and learning channels. Manysocial media were used for this learning model including 1) Facebook page; Thai-American 4-H,
https://www.facebook.com/thaiamerican4H, 2) YouTube; for examples, https://youtu.be/
4p1yguMWvlI, https://youtu.be/GMGP1qA8tsY, and 3) LINE application. This learning model arein line with the needs of 4-H who want to learn from a variety of media to be able to connect local
communities to the country and the world through collaboration with projects.
Evaluating of the Learning Model on Cross-Cultural Distance Education in Agriculture of 4H Club in Prachamongkol School and Purdue Extension
The evaluation of learning management model on cross-cultural distance education was to assess
the learning styles and learning methods in 3 areas which are suitability, usefulness and satisfaction.
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Each area will evaluate in 6 aspects including learning characteristics, learning methods, learning
channels and tools used in learning, learning duration, learning style, and learning support. It was
found that the evaluation of learning styles and learning methods in all 6 aspects, Thai andAmerican 4-H club considered its appropriate usefulness and satisfaction at the high to highest level(Mean ranged from 3.64-4.74) as shown in Table 1.
Table 1 Evaluation of 6 aspects of learning styles and learning methods
in appropriate usefulness and satisfaction
Issue

1. Learning style1) Student-centered learning
2) Project Based learning3) Learning by doing
2. Learning tools
1) Discussion
2) Training
3) Demonstration
4) Group activities
5) Video
3. Learning Channels
1) Facebook
2) Skype
4. Learning time1) Duration of learning throughout
4 months
2) Time to exchange
2.1) Sunday (6.00-8.00 p.m.)2.2) Monday (6.00-8.00 p.m.)
5. Learning methods
1) Large group exchange once amonth1.1) Between 4H Thai-American
1.2) In each school2) Exchange subgroups2.1) Between 4H Thai-American
2.2) In each school3) Exchange subgroups on issues ofinterest
4) Learning from project
implementation
5) Exchange using video
6) Exchange of learning throughSkype7) Sharing Learning throughFacebook
6. Learning Supported
1) Teacher Consultant
2) School administrators
3) Parents
4) Operators from Sukhothai
Thammathirat Open University5) Operators from Purdue
Extension6) Related agencies

Appropriate

Usefulness

Satisfaction

Thai 4H

AmericanThai 4H

AmericanThai 4H

American(X)

4-H ( X )(X )4-H ( X )(X )4-H ( X )

4.18
4.02
4.30

4.36
4.24
4.12

4.18
4.16
4.38

4.20
4.24
4.16

4.16
4.06
4.42

4.12
4.08
4.32

4.04
4.16
4.32
4.26
4.06

4.04
4.16
4.52
4.40
4.12

4.02
4.28
4.34
4.12
4.06

4.00
4.20
4.36
3.88
4.12

3.94
4.02
4.14
4.02
4.20

4.00
3.96
4.24
3.96
4.40

4.52
4.28

4.48
4.16

4.64
4.46

4.56
4.32

4.44
4.38

4.36
4.36

4.16

4.16

4.18

3.96

4.24

4.24

4.24
3.94

4.24
3.76

4.28
4.00

4.20
3.72

4.00
3.96

4.08
3.64

4.52
4.42

4.52
4.60

4.30
4.34

4.40
4.40

4.26
4.22

4.32
4.16

4.56
4.48

4.60
4.60

4.16
4.18

4.20
4.32

4.38
4.26

4.40
4.20

4.18

4.12

4.14

4.00

4.20

4.16

4.36

4.36

4.36

4.00

4.16

4.12

4.32

4.36

4.34

4.28

4.32

4.40

4.46

4.44

4.34

4.20

4.18

4.00

4.46

4.44

4.42

4.48

4.38

4.60

4.74
4.12
4.34

4.60
4.04
4.28

4.62
4.18
4.28

4.60
4.20
4.20

4.48
4.20
4.20

4.32
4.20
4.08

4.32

4.32

4.28

4.28

4.40

4.36

4.54

4.56

4.40

4.40

4.46

4.44

4.24

4.20

4.16

4.04

4.12

4.04

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Based on the findings, there can be a discussion that the implications of this study are for teacher
and school to provide opportunities for student growth through exploring the global throughcollaboration with projects around the world and to engage in the advancement of information andcommunication technology in learning. The learning model for cross-cultural distance education inagriculture between the 4-H club should be flexible and fit to students needs such as learning topics,
learning styles, learning methods, learning tools, learning channels, learning time and learning
supported. In order to prepare 4-H club and youth for an inclusive and sustainable world, it should
be done by preparing them with the global competencies which is the capacity to be able to examine
local, global and intercultural issues, to understand and appreciate the perspectives and world viewsof others, to engage in open, appropriate and effective interactions with people from different
cultures, and to act for collective well-being and sustainable development (OECD, 2018).
Furthermore, student should engage in the cross cultural learning to see the world and explore thedifferent cultures to be fully engaged in the experience.
CONCLUSION
The results show that in terms of the context and operating conditions of Thai and American 4-Hclub, most of them were interested in joining the project to exchange cross-cultural learning. In termsof culture, agriculture and food in foreign countries, most of the expectations of 4-H members in the
project were to get to know and talk to new friends, speak languages, and learn about the culture offoreign life. Agricultural learning management of 4-H club included learning by doing,
constructivism, cooperative learning, learning by technology, school enrichment, special interest
programs, after school, camps and conferences. Development of learning model on cross-cultural
distance education in agriculture was conducted in 4 phases as follows: 1) seminar defining thelearning model on cross-cultural distance education in agriculture, 2) implementation of learningmodel on cross-cultural distance education in agriculture, 3) evaluation of learning model on crosscultural distance education in agriculture, and 4) conducting seminars and summarizing the learningmodel on cross-cultural distance education in agriculture. The evaluation of learning management
model on cross-cultural distance education was to assess the learning styles and learning methods in
3 areas which are appropriate, usefulness, and satisfaction. Each area was evaluated in 6 aspects
including learning characteristics, learning methods, learning channels and tools used in learning,learning duration, learning style, and learning support. It was found that Thai and American 4-H clubconsidered its appropriate, usefulness, and satisfaction at the high to highest level (Mean ranged from
3.64-4.74)
ACKNOWLEDGEMENTS
Authors are extremely thanks to Sukhothai Thammathirat Open University, Prachamongkol School,
Karnchanaburi Province in Thailand, Purdue Extension of Purdue University, and The Legacy
Learning Center from Marion County, Indiana, USA. for participated this study. We would like toacknowledge to Thai-American 4-H for providing their times and share their knowledge to contribute
this research and development study.
REFERENCESCharlotte, N.G. 2014. Globalization, culture and online distance learning. 75-107, In Olaf Zawacki-Richter andTerry Anderson (Eds.), Online Distance Education, Towards a Research Agenda, AU Press, Athabasca
University, Canada, Retrieved from https://doi.org/10.15215/aupress/9781927356623.01
Creswell, J.W. 2012. Qualitative inquiry and research design: Choosing among five approaches. Thousand
Oaks, Sage Publications, California.
OECD. 2018. Preparing our youth for an inclusive and sustainable world: The OECD PISA global competence
framework. The Organisation for Economic Co-operation and Development (OEDC), Directorate forⒸ ISERD

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Education and Skills, France, Retrieved from https://www.oecd.org/education/Global-competency-for-aninclusive-world.pdf
Sangkhaphan, S. 2013. 21st century skills: Why? “Teach less, Learn more”, Retrieved from http://www.
srn2.go.th/index.php?option=com_content&view=article&id=145:-21-&catid=44:2013-06-18-04-5902&Itemid=74
Sanguankaew, C. 2008. Dual mode: Learning in the 21st century. Retrieved from http://www.ku.ac.th/icted2008/download/lerning2_chadaporn.pdf
Turiman, P., Omar, J., Mohd, D.A. and Osman, K. 2011. Fostering the 21st century skills through scientific
literacy and science process skills. UKM Teaching and Learning Congress 2011, Retrieved fromhttps://core.ac.uk/download/pdf/82704246.pdf
Weeranakin, N., Zatun, S., Raksong, O., Asanok, M., Pongpipat, S. and Moolvilai, S. 2015. Developing an elearning model of rice farming for young farmers in Thailand. Rajamangala University of Technology Isan,
Faculty of Social Technology, Kalasin Campus, Retrieved from https://www.tci-thaijo.org/index.php/
eduku/article/view/78558
Weeranakin, N., Zatun, S., Tabsombut, P., Chalermsuk, T. and Moolvilai, S. 2014. The development of modelof online farming Kaowong Kalasin Sticky Rice Learning Center for new generation farmers in Kaowong
district, Kalasin Province. Rajamangala University of Technology Isan, Faculty of Social Technology,
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Research article
erd

A Case Study on Postharvest Handling Practices of Mango
Fruits in Selected Areas of Myanmar
THAN THAN SOE*
Yezin Agricultural University, Nay Pyi Taw, Myanmar
Email: thansoesoe@gmail.com

NYEIN NYEIN HTWE
Yezin Agricultural University, Nay Pyi Taw, Myanmar

MAY THU HLAING
Yezin Agricultural University, Nay Pyi Taw, Myanmar
Received 2 February 2020

Accepted 29 October 2021(*Corresponding Author)

Abstract Mango (Mangifera indica L.) is one of the most popular fruits in tropical countries.
The postharvest losses of mango fruits in developing countries are still high and facing the
economic loss. Myanmar mango is harvested only once a year, there is often an oversupply
which leads to low prices and product losses at harvest time. This study was conducted toinvestigate the existing handling practices and to identify the losses concerned with the major
problems facing the handling of mango in selected areas during mango season of May 2017.
A total of 120 respondents from mango growers of Mandalay and Sagaing regions wererandomly selected and interviewed using structured questionnaires. The total loss of 32%52% of mango fruits were observed during postharvest handling and transportation due topoor transportation infrastructure and bad road conditions in production sites. The temporarytransportation was used trailer which is driven by motorbike for local market and ten-wheeled
truck without cooling system was used for export market. The loss in harvesting stage was
10-20% responded by the growers due to the harvesting tool and which was picking the fruitwith a long bamboo-hook or ladder to reach the high plant. Thus, postharvest losses of mango
fruit were the highest percent in study areas. Currently, mango growers were directly sent tolocal wholesale and China border markets by non-refrigerated truck. No collective bargaining
takes place on the price and each farmer interacts individually with the brokers or buyers byreceiving market price. The 79% of mango growers were commonly practiced for temporary
bulk package of bamboo basket followed by the use of plastic crate of 15% from the farmsite to destined markets All growers mostly and currently used the packaging style ofindividual fruit wrapping by paper in plastic crate for export market. One of the major
constraints is the scarcity of labor in mango season by the results of 73% responded by the
mango growers. Regarding the perception of growers, more than 50% of respondents haveknowledge and experiences on postharvest handling managements, however, trainings on
systematic handling practices among the stakeholders were still needed to reduce the losses.
Keywords handling practices, harvesting, packaging, transportation, mango supply chain

INTRODUCTION
Mango (Mangifera indica L.) is an important tropical fruit around the world and it belongs to thefamily Anacardiaceae. The origin of mango is Indo-Burma region and it is one of the most important
exportable fruits in Myanmar. Myanmar is the sixth largest country in mango production in Asia.
The mango production areas in Myanmar are over 104,000 hectares with the average yield of 6.83
MT/ha (MOALI, 2018). More than one hundred varieties of mango are cultivated throughout
Myanmar. Major mango production areas in Myanmar are Mandalay Region, Sagaing Region andSouthern Shan State. Twenty kinds of mango species and more than 300 varieties are cultivatedthroughout Myanmar (VFRDC, 2003). Among these varieties, the exportable cultivars are Sein TaⒸ ISERD

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Lone, Mya Kyauk and Shwe Hin Thar. Out of them, Sein Ta Lone is very popular in both domestic
consumption and export markets of China, Taiwan, Russia and Singapore. Mango is one of the mostperishable fruits and have a short postharvest life of 4-8 days at room temperature (Carrillo et al.,2000). It is facing high postharvest losses in Myanmar and it is estimated in the range of 25-40%
from harvest to consumption stage (FAO, 2011). In order to increase food security, it is not enoughto increase the productivity in agriculture but there is also a great need to reduce the losses (Parfitt etal., 2010). The mango postharvest handling practices include series of operations such as harvesting,precooling, cleaning, selection, grading, washing, ventilation, grading, bagging, packaging anddistant transportation before they reach the market (Kader, 2005). Awareness and adoption of
postharvest handling technology of mango fruits by growers, producers and traders along the supply
chain are still weak in Myanmar. There is paucity of information on postharvest handling practices
and losses of mango concerned with the problems in commercial mango production. Therefore, thisstudy was carried out to investigate the existing handling practices and postharvest losses byidentifying the major problems facing by the mango growers.
RESEARCH METHODOLOGYThis study was conducted in major mango producing areas of Mandalay and Sagaing Regions in thecentral part of Myanmar. A total of 120 respondents from mango orchards in 6 villages of theseregions were randomly selected and interviewed using structural questionnaires. The survey was
conducted in May 2017 using random sampling procedure. The questionnaires were composed of
total 40 questions concerned with cultivation practices and postharvest handling practices of mango
fruit and demographic facts of gender, age, education level, employment, land holding size andincome. The problems encountering during harvesting, postharvest handling and growers’ perception,suggestions were also collected in this study. The collected data were transferred and analyzed byusing Statistical Package of the Social Science (SPSS) version 23.0 software.
RESULTS AND DISCUSSION
Assessment on Socio-Demographic Characteristics of the Respondents
Socioeconomics factors of mango growers include age, educational status and land holding size. It
reveals that the farm size of mango growers ranged from one to 14 hectares and about 40 % of mango
growers possessed 1-2 hectares, another 40 % possessed 3-4 hectares. The growers who possessedmore than 10 hectares were recorded as 10% in study areas (Fig.1). The most cultivated anddemandable mango varieties were Sein Ta Lone and Shwe Hinn Thar observing about 50% followed
by 24% of these two varieties and Yin Kwe mango (Fig. 2). It can be assumed that Sein Ta Lone andShwe Hin Thar mangoes are the most market demand by the consumers and other cultivars of Matheand Nga Mout were growing together with Sein Ta Lone and Shwe Hinn Thar mangoes. According
to survey, the age of mango respondents with the range of both 31-40 year and 41-50 years belonged
to 36% respectively whereas the rest of 28% were older than 50 years showing 18% and 10%
belonged to age group of 20-30 years in both study areas. The majority of household heads were
within the middle age and mainly males whereas the females were served as household workers in
the orchard. It is evident that the educational status of respondents ranged from primary to graduatelevel. Most growers were graduate level of 29% followed by the 27% of high school level. The restof 27% and 19% were secondary level and primary education level, respectively.
Handling practices of mango fruits include the stages of precooling, cleaning, sorting, grading,packaging and transportation from farm site to consumers. Individual fruit wrapping was commonly
practiced for local and distant markets. The bulk packaging items for mango fruits were bamboo
basket, plastic crate and wooden box. Among them, about 80% of bamboo basket was used for local
market followed by the 14% for plastic crate for export market. The rest of 4% was wooden box and
2% was carton box used in locally (Table 1). It can be assumed that bamboo basket is easily available
with low cost in Myanmar. It was agreed with the report of FAO (2011) and that packaging generallyⒸ ISERD

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provides protection for the product to reduce losses and to maintain fruit quality with theenhancement of product value.

Fig. 1 Distribution of mango farm size in study areas

Fig. 2 Distribution percent of different mango varieties among the respondents
handling practices of mango in study area
Table 1 Access to handling practices by packaging materials by mango growers
Item
Bulk packaging type
1.Wooden crate
2.Plastic crate
3.Bamboo basket
4. Carton box
Total
Individual packaging item
1.Paper
2.Net sac
Total

Respondents (%)
4.00 (n =100)
14,25 (n =95)
79 .75 (n=110)
2.00 ( n= 80 )100
100 (n =110)
0100

Losses of Mango during Handling Practices in Study Area
The survey was conducted to examine the main reasons of mango losses during the pre-harvest,
harvest and postharvest periods. There was no respondent for pre-harvest loss. However, postharvest
loss of mango during handling and transportation was higher than those of the harvest loss. About
65% of postharvest loss was recorded during handling practices and transportation followed by theharvest time loss of 32% was due to higher plants by the use of long bamboo pole and ladder. The
other losses of 1-2% were identified as wind condition, pest and disease infestation. Thus, total lossesof 32-52% were observed due to improper handling practices, transportation system and harvesting
practices (table-2). Most respondents reported that the mango fruits were mostly and temporarilytransported by 86% of trailers which was driven by motorbike from farm to local market.

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Table 2 Losses of mango fruits by the sample respondents in study areas
Item
Preharvest
Harvest time

Losses (%)
0
10-20

Respondents (%)

Postharvest
Others
Total

21-30
1- 2
32- 5265 (n=100)
3 (n=72)100

32 (n=100)

Reasons
Falling the small fruits due to wind
Due to harvesting toola) using a long stick or scissors to cut thefruit from the treeb) climbing the tree or using a ladder toreach high plant
During handling practices and transportation
Pest, disease infestation and climatic condition

The bad nature of road networks at the farm site and unfavorable factors during transportation
resulted in great postharvest losses. The following (Figs. 3 and 4) show knowledge background on
handling practices and growers perception on training requirement. More than 50% of respondents
had their own sets of criteria for postharvest handling managements and knowledge. However, halfof growers and labors had no knowledge concerned it and they still used traditional harvesting
method and handling practices that means mango directly piled on the ground with no paper, sheet
or straw with stack and also harvested mangoes with stalk which caused dropping the latex that
resulted in negative effects on fruit quality and increase in postharvest losses. Thus, about 80% of
respondents answered to give trainings on postharvest handling managements for labors and growers.
Therefore, educational training on postharvest managements such as biological pest control,advanced harvesting technique, systematic handling and packaging practices would greatly help in
reducing the postharvest losses of mango fruit.

Fig. 3 Postharvest knowledge by the mango growers in study areas

Fig. 4 Farmers' perceptions on postharvest training in study areasⒸ ISERD

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CONCLUSION
Almost 100% of the respondents were commonly practiced by paper packaging to individual fruit
for distant transportation along the sale process. Therefore, handling and packaging practices should
be systematically managed to reduce postharvest losses and to maintain the quality of the products.
It is suggested that the use of enough labors (pickers and packers) and they should be trained toreduce losses at harvest time and postharvest losses. It is needed to change the attitudes of growers
to adopt innovation in farming cultivation practices and community among the growers. Moreover,to be modernized orchard and easy to manage for harvest, changing the attitude of the growers is oneof the constraints and transportation as a result of undulations on roads are one of the major causesof postharvest losses. Furthermore, farmers do not have good storage facilities at the farm level, andthis forces them to sell their fruits immediately after harvest. And also, no collective bargaining takes
place on the price of mango. According to the study, some respondents in study areas were practicing
on sizing and grading of mango fruit for export market by the use of machinery and this may be
regarded as quality criteria. Although growers have the knowledge and awareness on postharvest
handling practices and managements for mango export market, they have not tried to carry out
practically and systematically these practices. Therefore, trainings and awareness program on
postharvest technologies in fruit production is needed to train the mango growers and stakeholders
for the advancement of postharvest handling practices. Moreover, cooperation with public andprivate partnership should support them to take these actions.
ACKNOWLEDGEMENTS
This study was financially supported by Technical Cooperation Program of Japan International
Cooperation Agency (JICA-TCP) at Yezin Agricultural University, Myanmar.
REFERENCES
Carrillo, L.A., Ramirez-Bustamante, F., Valdez-Torres, J.B., Rojas-Villegas, R. and Yahia, E.M. 2000.
Ripening and quality changes in mango fruit as affected by coating with an edible film. J. Food Quality
23, 470-486.
Food and Agriculture Organization (FAO). 2011. Perishability and produce losses. In Prevention of Postharvest
Food Losses, FAO/UNDP/AFMA Regional Training Workshop, 42-48.
Kader, A.A. 2005. Increasing food availability by reducing postharvest losses of fresh produce. Acta. Hort.
682, 2169.
Kader, A.A. 2008. Mango quality attributes and grade standards: A review of available information andidentification of future research needs (Report to the National Mango Board). Kader Consulting Services,
Bull., 152, 51, California.
Ministry of Agriculture, Livestock and Irrigation (MOALI). 2018. Myanmar agriculture in brief 2018. Ministryof Agriculture, Livestock and Irrigation, Nay Pyi Taw, Myanmar.
Parfitt, J., Barthel, M. and Macnaughton, S. 2010. Review food waste within food supply chains: Quantificationand potential for change to 2050. Philosophical Transactions of the Royal Society B: Biological Sciences,
365, 1554, 3065-3081.
Vegetables and Fruits Research Development Centre (VFRDC). 2003. Annual report of fruits and vegetables
research and development center. Myanmar Agriculture Service, Ministry of Agriculture, Livestock and
Irrigation, Myanmar.

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Research article
erd

Evaluation of Water Quality and Vegetable Productionin Cheung Ek Lake, Cambodia
OUM SOMARA
Graduate School of Agriculture, Tokyo University of Agriculture, Japan

MACHITO MIHARA*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Japan
Email: m-mihara@nodai.ac.jp
Received 6 September 2021

Accepted 29 October 2021(*Corresponding Author)

Abstract Wastewater management in Phnom Penh is always a concern for the Royal
Government of Cambodia as well as citizens of the capital. All wastewater and sewage fromthe households and the industries are untreated discharges into the city’s wetlands, such as
Cheung Ek, Tompun, Trabek Lakes. Cheung Ek Lake is the biggest and terminal lake in the
chain of water systems before discharging into Bassac and Mekong River. Apart from thepurification of the wastewater, the lake ecosystem also has an important economic function.
Local people use the lake for fishing and to cultivate aquatic plants such as water morning
glory (Ipomoea aquatica) and water mimosa (Neptunia oleracea). Considering these aspects,
the objectives of this study are to (i) analyze water quality in Cheung Ek Lake during therainy season; (ii) study the economic balance and the price-chain of water morning glory
production. The water samples were collected on three different days at three points in thelake (inlet, middle and outlet) and analyzed for pH, EC, Fe, DO, PO43- and NO3-. Semistructured questionnaires were designed for the economic analysis, and a total of 20 farmers
were interviewed for social characteristics, input and output costs, and the water morning
glory market channel of water morning glory production. Except for phosphateconcentrations which was higher at the inlet site, the other nutrient content poses no threat toenvironmental pollution. Additionally, the lake's chemical load were lower at the outlet thanat the inlet. In terms of economic benefit, the net profit from the production was 23.77 USD
per day/ha. Despite the fact that the farmers spent a lot of money on hiring the manpower,
the profits from the sale was sufficient. The production's economic efficiency was 1.80. The
result of water quality and economic showed lake perform a role in removing pollutants andprovide economic benefits to the farmers.
Keywords Phnom Penh, Cheung Ek Lake, water quality, water morning glory

INTRODUCTION
The explosive urban expansion throughout Asia has resulted in severe environmental problems,
including air and water quality issues and inadequate infrastructure (Varis et al., 2005). In the processof urbanization, economic development and the natural environment are linked by a series of positive
and negative effects. Wastewater management has become a concern for the Royal Government of
Cambodia since Phnom Penh city's population has grown from 1.4 million in 2008 to 2.1 million in2018 (NIS, 2019). Until now the city still doesn’t have proper wastewater treatment plan while its
population continue to grow as well as the expand of city. In the past, the wastewater from the urban
are discharged into 3 wetlands namely Tumpon Lake, Trabek Lake, and Cheung Ek Lake (Tharith etal., 2008). The wastewater is serviced by a combined sewer system, and flow is pumped to Cheung
Ek Lake (natural wetland) for treatment before it discharges to the Bassac River system (Visoth etal., 2010). However, the urbanization keeps intrude the wetlands area result in only Cheung Ek Lakeremained.
Cheung Ek Lake, the largest wastewater Lake in the city, knows as the production area for water
morning glory (WG) for almost four decades. The lake's surface area changes from 1,300 to 3,000Ⓒ ISERD

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ha during the dry and rainy seasons (Nara et al., 2015), given the potential for plant cultivation. Thiswetland system can potentially provide adequate wastewater treatment, environmental and economic
benefits (Brix et al., 2007; Koottatep et al., 2010). However, those study were conducted a decadeago and even before the starting of intrusion into the lake area. The uncontrolled human occupationon the lake’s bank has led to encroachment of the lake's surface area every year, especially from 2013
when the satellite cities project started (Sahmakum Teang Tnaut, 2019). Cheung Ek Lake was provento be effective in treating treated wastewater for bacterial contaminants, nutrients, detergents, andmetals (Irivine et al., 2008; Sovann et al., 2011; Visoth et al., 2010). However, as the lake's surface
area gets smaller, its potential for wastewater treatment reduce as well. High concentration ofphosphorus and deplete level of DO were reported at the point where wastewater from the city
discharge into the Mekong rivers (Chea et al., 2016). These could be the result of direct municipal
discharges and urban storm water runoff in densely populated areas. Therefore, the question
remained whether the lake could still offer ecosystem services to the city.
The purpose of this paper is to investigate the potential of Cheung Ek Lake in ecosystem services
in aspect of wastewater treatment and economic benefit. This paper consists of two specificobjectives: (i) analyze water quality in Cheung Ek Lake during the rainy season; (ii) study the
economic balance and the price-chain of water morning glory (Ipomoea aquatic) production.
METHODOLOGY
Study Area
The study was conducted on Cheung Ek Lake located at the south of Phnom Penh city (104°90’–
104°94’E and 11°46’–11°53’N). It is the catchment area where 80% of total wastewater from thiscatchment is drained into the lake (Van der Hoek et al., 2005). The lake’s surface area changes from1,300 to 3,000 ha approximately from dry to rainy seasons, with an average depth of 0.5-1.5 m in thedry season and 7–9 m in the rainy season. The average annual rainfall is 1,440 mm and elevation isaround 10 m above sea level (Nara et al., 2015).

Phnom Penh
city

Inlet

MiddleOutletFig. 1 Map of Cambodia and sampling point in Cheung Ek Lake (Google map)
Water Sampling and Analysis
Water sampling was conducted during the rainy season of September 2019 by using Heyroth Water
Sampler. Sampled water was kept in the plastic containers at 5 0C and transported to the laboratory
within 3 h of collection for analysis. The water samples were collected on three different days at the
inlet, middle and outlet. Totally 27 water’s samples were analyzed for pH, electrical conductivity(EC), iron (Fe), dissolved oxygen (DO), phosphate (PO43-) and nitrate (NO3-) using DR 900 portabledata-logging colorimeter instrument.
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Field Survey and Interview
The semi-structured questionnaires were created, and 35 respondents were surveyed. Among 35
respondents are include 20 farmers, 5 middlemen, 5 wholesalers, and 5 retailers whose involved in
the production and selling of water morning glory. Social characteristics of the farmers, economic
returns and efficiency of the production of water morning glory were analyzed based on semiquestionnaire survey.
RESULTS AND DISCUSSION
The analysis of physical and chemical parameters of water samples are given in Table 1. The resultof pH indicates moderately alkaline water in Cheung Ek Lake. The mean pH of Cheung Ek varied
from 6.98 to 7.15 at the different sampling sites. Lower pH in the middle point indicates the acidity
in the water and could be due to a high concentration of positive hydrogen ion in the water. Electrical
Conductivity of Cheung Ek Lake water were not significantly different among sampling sites,varying from 0.66 to 0.75 mS/cm. High conductivity in the lake indicates the mixing of sewage andthe rainfall during raining season. Nitrate contents were slightly different from each site, ranging
from 0.11 to 0.66 mg L-1. The high concentration in the outlet point, which could be due to the releaseof the nutrients from sediment where there is no plantation cultivated. The results of PO43- varied
drastically among different sampling sites in the lake, ranging from 1.42 to 5.29 mg L-1. PO43- were
maximum at the inlet and become lower in the middle and outlet. The high concentration of PO43- in
the inlet suggests urban runoff, industrial wastewater and chemicals used in the water for agriculture
activities. The low concentration of Iron (Fe) were observed in the outlet of the lake and ranged from0.03 to 0.05 mg L-1. DO of the lake ranged from 3.55 to 6.06 mg L-1. The maximum concentration of
DO were at the inlet and lower at the outlet. This further indicated the flow rate of the lake at different
sites and the process of dissolved solid breakdown through self-pollution regulating mechanisms of
the lotic water system.
Table 1 Discharge and chemical properties of inlet, middle and outlet of the lake
Location

Discharge(m3/s)pHEC(mS/cm)

Inlet
MiddleOutlet

42.12
33.91

7.06 ± 0.30
6.98 ± 0.27
7.15 ± 0.36

0.75 ± 0.04
0.72 ± 0.01
0.66 ± 0.02-

PO43(mg/L)

Fe(mg/L)(mg/L)
0.66 ± 0.29 5.29 ± 2.26 a* 0.03 ± 0.03
0.11 ± 0.16 1.42 ± 0.59 b* 0.05 ± 0.05
0.55 ± 0.18 1.90 ± 0.50 b* 0.06 ± 0.03
NO3

DO
(mg/L)
5.14 ± 2.24
6.06 ± 1.99
3.55 ± 0.66

Note: Values are mean ± SD (n=3), * p< 0.1

Table 2 Correlation matric of water quality in the lake
pH
EC
NO3PO43Fe
DO

pH

EC

NO3-

PO43-

Fe

1
-0.137**0.628-0.157-0.042*0.4801-0.247**0.646-0.2750.036

1-0.148-0.1260.083

1-0.186-0.2211-0.087DO

1

Significant difference at **p<0.01, * p< 0.05

Correlation matrix between different physical and chemical parameters are shown in Table 2.
A correlation matric was observed between some important water quality parameters of the lake,
which further indicates the interactions between water chemical constituents. The result showed that,
pH had a positive correlation with dissolved oxygen (DO) and nitrate (NO3-). According to Battas etal. (2019) pH greatly affects the adsorption rate of nitrate. It also affects the charge on the surface of
the adsorbent during the ion exchange process. Also, Electrical conductivity (EC) had a correlationⒸ ISERD

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with phosphate (PO43-) because the contamination of inorganic compounds in the solution ofphosphate ions contribute to electrical conductivity.
The water quality of the lake can be defined by two indicators such as concentration and load.
The concentration indicated in Table 1 and Table 3 show the load of four parameters in Cheung Ek
Lake between the inlet and outlet site. The result for PO43- , NO3- and DO showed a decreasing trend.
Iron (Fe) increased in both sites. As the outlet's load was reduced compared to the inlet’s load it canbe said that the lake can remove inflow pollutants (Fig. 2). In contrast to the JICA report, 2016 hasstated that the lake has been encroached by houses, factories, agricultural and other activities, andthey are no longer effective in performing their natural purification function. The reason could be
due to in rainy season the inverse flow direction of water coming from the Mekong River at thesoutheast part of the lake (outlet), colliding this water moving in the opposite direction (Sovann etal., 2011) pushed the wastewater back to the upper part of the lake which then made the concentrationand load of the parameters high in the lake (Nara et al., 2015).
Table 3 Nutrient load at the inlet and outlet-

Parameter

Inlet

Outlet3

28.08
222.81
1.26
216.50

18.65
64.42
2.03
120.38NO3 (g/m )PO43- (g/m3)
Fe (g/m3)
DO (g/m3)

Cheung Ek Lake

Inlet

NO3-

>

NO3-

PO43-

>

PO43-

OutletFig. 2 Functionof
Ek LakeFe< the Cheung
Fe
DO>Glory DO
Socio-Economic Aspects of Water Morning
Production

Table 4 shows the socio-economic characteristics of 20 respondents. The average household size was
6.1 people per household, which is higher than the national average of 5.3 people for the urban areas(NIS, 2019). On average, experience in farming water morning glory was 10.4 years and thecultivated area per household was 2.15 ha. The average harvest per day per ha was 164.5 bunch andthe average price was 0.37 USD per bunch.
Table 4 Socio-economic characteristics of water morning glory (WG) producers
Number of household (HH)

20.0

Average family size (person)

6.1

Average age of farmer (year)

37.8

Average year of experience in WG production (year)

10.4

Average planted area per HH (ha)2.15

Average harvest per day per ha (bunch)

164.5

Average price per bunch (USD)

0.37

Source: Field survey, 2019

Total Production Cost and Economic Return of Water Morning GloryⒸ ISERD

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Table 5 showed the result of the production cost (per day/ha) of water morning glory. The result
revealed that the total production cost was 29.58 USD per day/ha. The result also showed that mostof the expense during the production was on labor.
Table 5 Total production cost of water morning glory
Item

Price (USD)

Price (USD)

Item

Total variable cost (a+b)

28.43

Total fix cost (c)1.15-Variable cost (a)Pesticide

5.85
3.57

Land rent

0.68

Bamboo0.29

Gasoline

1.55

Boat

0.15

Plastic

0.22

Sprayer

0.01

Boat reparations

0.16

Rope

0.34

-Total labor (b)Family labor

22.58
7.98

Rent labor

14.59

Container
Total production cost
(a+b+c)Source: Field survey, 2019

0.01
29.58

Regarding economic return from production, this study examined several indicators, like grossrevenue, total cash income and net profit (Table 6). The results show that the gross revenue from theproduction was 53.35 USD per day/ha (Table 6). The cash income is referring to the income that thefarmers received without deducting labor of family involve in the production. In the water morning
glory production, the cash income that the farmers received was 32.90 USD per day/ha. Although
the farmers spent a lot on labor, the return from the sale was good enough. The economic efficiency
for the production was 1.80 (Table 6), suggested that the business with this product is profitable. The
value 1.80 of economic efficiency could be interpreted as follows: if 1 USD is spent on the production,
1.80 USD will be received from the sale of products. So, net profit was 0.80 USD per unit of expense.
Table 6 Economic efficiency of water morning glory
Gross revenue
(USD)
53.35

Cash income
(USD)
32.90

Net Profit
(USD)
23.77

Production cost
(USD)
29.58

Economic
Efficiency
1.80

Figure 3 shows the price chain in water morning glory production between farmers, middlemen,
wholesalers and retailers. The price of the water morning glory product varies from month to monthaccording to its availability and demand. The result of the questionnaire survey showed that the priceof water morning glory is lower in the dry season compared to the rainy season. The average market
price range for farmers and retailers were between 0.22 to1.38 USD per bunch. The difference in theprices can be seen between the first and final Price
supplier.
chain
Price per bunch (USD)

1.6
1.4
1.2

1

Average

0.8
Maximum

0.6

Minimum

0.4
0.2

0

0

1
Farmer2 Wholesaler
3
Middleman

Retailer4

5

Fig. 3 The price chain in the water morning glory productionⒸ ISERD198

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Water Quality in Cheung Ek Lake Effect on Economics of Farmers
Cheung Ek Lake plays an essential role in nutrient supply for the farmers during the cultivation ofvegetables. According to the questionnaire survey, fertilizer is not necessary for plant production in
the lake. Comparing to the amount of fertilizer needed in land cultivation of water morning glory
production is around 200-300 kg per hector, costing around 105 $-157 $ in one production cycle.
Therefore, the farmers from the lake can earn more by spending less on the extra cost of fertilizer
application. However, to think only the benefit, the other point of view also concerning to the qualityof the vegetable that product in the wastewater lake.
However, faecal and protozoan parasite contamination were detected in the lake's water morning
glory (Anh et al., 2007). According to Van der Hoek et al. (2009), people who were exposed towastewater at Cheung Ek Lake developed dermatitis. While low concentrations of potential toxic
element concentrations were identified in water spinach and fish created in Cheung Ek Lake
wastewater systems, indicating that these components pose a minor food safety risk (Marcussen etal., 2009; Chea et al., 2010).
CONCLUSION
Cheung Ek Lake is an important wetland, which used to be an efficient natural treatment plant for
wastewater and production of water morning glory in Phnom Penh. In this study, we emphasized onunderstanding the role of the lake as purify of wastewater. The results on the water quality of thelake indicate that it is becoming less polluted. The result of the chemical load during the rainy season
showed that the lake is taking part of purification as well. Nonetheless, the result with the economic
analysis from the farmers who cultivated water morning glory in Cheung Ek Lake shows a profitable
sign with economic efficiency 1.80.
Overall, Cheung Ek Lake is an essential part of urban ecosystem. This lake performs significant
role in removing pollutants from the water and provide economic benefits to the farmers.
Additionally, research on the quality during the dry season is required to continue monitoring thelake's water quality. The amount of heavy metal and parasite contamination will also be examinedfor health assessment.
REFERENCES
Anh, V.T., Tram, N.T., Klank, L.T., Cam, P.D. and Dalsgaard, A. 2007. Faecal and protozoan parasite
contamination of water spinach (Ipomoea aquatica) cultivated in urban wastewater in Phnom Penh,
Cambodia. Tropical Medicine & International Health, 12, 73-81.
Battas, A., Gaidoumi, A.E., Ksakas, A. and Kherbeche, A. 2019. Adsorption study for the removal of nitratefrom water using local clay. The Scientific World Journal, 1-10.
Brix, H., Schierup, H.H. and Arias, C.A. 2007. Twenty years’ experience with constructed wetland systems in
Denmark: What did we learn? Water Science and Technology, 56 (3), 63-8, Doi: 10.2166/wst.2007.522.
Chea, E., Dany, V. and Irvine, K. 2010. Level of Cr, Cu and Zn in food stuffs from a wastewater treatment
wetland, Phnom Penh: A preliminary assessment of health risks. Asian J. Water Environ. Pollu., 7, 23-30.
Chea, R., Grenouillet, G. and Lek, S. 2016. Evidence of water quality degradation in lower Mekong basin
revealed by self-organizing map. PLoS One, 11 (1), Doi: 10.1371/journal.pone.0145527
Irvine, K., Sampson, M., Visoth, Y., Yim, M., Veasna, K., Koottatep, T. and Rupp, J. 2008. Spatial patterns of
E. Coli and detergents in the Boeng Cheung Ek treatment wetland, Phnom Penh, Cambodia. The 6thInternational Sympossium on Southeast Asian Water Environment, University of Tokyo, 78-81, Tokyo.
Japan International Cooperation Agency (JICA). 2016. The study on drainage and sewerage improvement
project in Phnom Penh metropolitan area. Final report 2, 33.
Koottatep, T. and Panuvatvanich, A. 2010. Constructed wetlands for effective wastewater treatment. In Water
Resources and Development in Southeast Asia, Irvine, K., Murphy, T., Vanchan, V. and Vermette, S.
(Eds.), Southeast Asia Center, 179-92, New York.
Marcussen, H., Dalsgaard, A. and Holm, P.E. 2009. Element concentrations in water spinach (Ipomoea
aquatica Forssk.), fish and sediment from a wetland production system that receives wastewater from
Phnom Penh, Cambodia. Journal of Environmental Science and Health, Part A, 44, 67-77.
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Nara, I., Kensuke, K., Endan, S. and Yuji, S. 2015. Monitoring land use and land cover effects on water quality in
Cheung Ek Lake using ASTER images. American Journal of Environmental Sciences, 11 (1), 1-12.
Nation Institute of Statistics (NIS). 2019. Cambodia inter-census population survey 2019 final report. 10,
Retrieved from https://www.nis.gov.kh/index.php/km/15-gpc/85-general-population-census-of-cambodia
Sahmakum Teang Tnaut. 2019. Facts and figures: The last lake, Phnom Penh, Cambodia. 40 (3-4), Retrieved
from www.teangtnaut.org
Sovann, C., Kim, I.N., Suthipong, S., Kok, S. and Chea, E. 2011. A dynamic modelling approach as a decisionmaking tool for assess hydrologic and water quality pressures on natural wetlands treatment of wastewater inPhnom Penh, Cambodia.
Tharith, S., Sovanlandy, P. and Rasmey, M. 2008. An investigation of heavy metals in water spinach in Boeng Tompun
Lake, Phnom Penh, Cambodia. Technical report, Retrieved from https://www.researchgate.net/publication/
341821519
van der Hoek, W., Anh, V.T., Cam, P.D., Vicheth, C. and Dalsgaard, A. 2005. Skin diseases among peopleusing urban wastewater in Phnom Penh. UA Magazine, 14, 30-31.
van der Hoek, W., Anh, V.T., Ersbøll, A.K., Vicheth, C., Cam, P.D. and Dalsgaard, A. 2009. Peri-urban aquaticplant culture and skin disease in Phnom Penh, Cambodia. Journal of Water and Health, 7 (2), 302-311.
Varis, O., Biswas, A., Lundqvist, J. and Tortajada, C. 2005. Water management in megacities. A Journal of
the Human Environment, 34 (3), 267-268.
van der Hoek, W., Anh, V.T., Cam, P.D., Vicheth, C. and Dalsgaard, A. 2005. Skin diseases among peopleusing urban wastewater in Phnom Penh. UA Magazine, 14, 30-31.
Visoth, T., Yim, M., Vathna, S., Irvine, K. and Koottatep, T. 2010. Efficiency of Phnom Penh’s natural
wetlands in treating wastewater discharges. Asian J. Water Environ. Pollute., 7, 39-48.

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Research article
erd

Impacts of Land Use-Land Cover Changes on Streamflow
and Water Balance of Stung Sangkae Catchment Using
SWAT
NARETH NUT*
Faculty of Agricultural Engineering, Royal University of Agriculture, Phnom Penh, Cambodia
Email: nnareth@rua.edu.kh

MACHITO MIHARA
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan

JAEHAK JEONG
Blackland Research & Extension Center, Texas, USA

BUNTHAN NGO
Royal University of Agriculture, Phnom Penh, Cambodia

SAKDANUPHOL CHAN
Faculty of Agricultural Engineering, Royal University of Agriculture, Phnom Penh, Cambodia

GILBERT SIGUA
United States Department of Agriculture, Agriculture Research Service,
Coastal Plains Research Center, South Carolina, USA

MANUEL R. REYES
Sustainable Intensification Innovation Lab., Kansas State University, Kansas, USA
Received 31 December 2020

Accepted 15 November 2021(*Corresponding Author)

Abstract Land use-land cover changes (LULCC) brought by increasing population and fooddemand could affect not only the fluxes of water, sediment, contaminants and energy, butalso ecological, physical and socioeconomic aspects in the environment. In this study, theSoil and Water Assessment Tool (SWAT) model was used to examine the effects of LULCC
on hydrological processes of Stung Sangkae catchment in Tonle Sap Basin, Cambodia. The
performance of the model was evaluated through uncertainty sensitivity analysis, calibration,and validation. The time series of LULCC were used to estimate the streamflow and the waterbalance in the catchment based on five interval years (1998, 2003, 2008, 2013, and 2018).
From 1998 to 2018, the coverages of forest land, wetland, and the paddy rice decreased by
5.1%, 1.4%, and 1.2%, respectively. The forest land and wetland were converted into
cultivated land with an increase of about 7.6% over the study periods. These changes resulted
in significant variations of water balance (2000-2018) namely: i) an increase of averageannual surface runoff (SURFQ) by 10 mm; ii) 3 mm reduction of the average annual lateralflow (LATQ); iii) 6.2 mm reduction of the average annual groundwater (GW); iv) reductionof the average annual evapotranspiration (ET) by 0.97 mm; and v) an increase of averageannual water yield by 0.9 mm. On a monthly basis, the model results had shown a reasonableagreement with the observed values as shown by the coefficient of determination (R2) = 0.41,
Nash Sutcliff efficiency (NSE) = 0.40, and percent of bias (PBIAS) = 0.34. Based on thevalidated water discharge and water balance results in 2018, LULCC have impacted theenvironmental sustainability, especially the streamflow that caused flooding at thedownstream watershed due to decline in forest cover at the watershed.
Keywords land use-land cover, Stung Sangkae Catchment, streamflow, SWAT model,water balanceⒸ ISERD

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INTRODUCTION
In Cambodia, the annual increase of population is always followed by the increasing demand forland, food, housing, and other social needs of the people. In Battambang, Cambodia in 2005, the total
population of the province was 952,306 (185,868 families) and increased to 1,066,928 (205,351
families) in 2018 (NCDD, 2010). Several studies have shown that the land changes caused by theincrease of urbanization, agricultural activities, and devastation of forest area have caused widechanges of streamflow and water balance in the watershed. As expected, there will be shortage ofwater due to the increase in water demand for all types of land use activities. However, the knowledgeof the effects of LULCC on various hydrological processes of Stung Sangkae catchment in Tonle
Sap Basin is not well understood. Additionally, the impact of LULCC on the streamflow and thewater balance in the catchment, where the research is targeted to create accessibility of important
information of water resources for sustainable resources management is not yet fully identified. Since
2005, people have cleared forested areas to cultivate maize and/or cassava. Most of these products
are being exported to Thailand. Over time, newly cleared land would require more and more fertilizer
to improve land productivity and this activity may contribute to degradation of water resources due
to eutrophication if no countermeasures are taken properly. Currently, an estimated 191,492 ha offorest cover is left, of which 150,992 ha is under the forestry administration’s management and40,000 ha is under the provincial department of the environment. However, protected areas are
increasingly under threat from land encroachment for large-scale agricultural land development(Sotheary, 2015).
As described above, the streamflow and water balance such as the surface runoff andgroundwater are being affected by LULCC. Despite progress in assessing and projecting LULCC
impacts, vulnerability and adaptation studies in Cambodia is still failing to provide sufficientunderstanding of existing vulnerabilities, thereby constraining mitigation responses, current andprojected risks in constantly changing contexts. Building resilience to LULCC variability,
understanding the hydrology-sensitive linkages between sectors and promoting sustainable
development and integrated hydrological cycle risk management require policies and plans that are
informed by scientific evidence.
To address the potential impacts of LULCC on hydrology and water balance, the Soil and Water
Assessment Tool (SWAT) model was used in Stung Sangkae catchment. Although, nowadays, there
are many hydrological models to help calculate the water discharge more accurately, easily andquickly than the traditional measurement method, SWAT was proven to be quite effective. Soil andWater Assessment Tool model, is a basin-scale model integrated with ArcGIS to help improve theaccuracy of the simulated result of streamflow from rainfall and physical properties of the basin. As
mentioned earlier, SWAT model has a good reputation for best use in agricultural watersheds and its
uses have been successfully calibrated and validated in many areas around the world (Ang andOeurng, 2018; Gassman et al., 2007). It has the most comprehensive literature database of 4200
articles compiled by the Center for Agriculture and Rural Development, Iowa State University(CARD-ISU, 2020).
OBJECTIVES
The objective of this research was to evaluate the impacts of LULCC on streamflow, surface runoff(SURFQ), lateral flow (LATQ), ground water (GW), evaporation and transpiration (ET) and water
yield in Stung Sangkae catchment in Tonle Sap Basin, Cambodia (Fig. 1).
METHODOLOGY
Site Description
This study was carried out in Stung Sangkae catchment containing the Tonle Sap Lake. This lake is
the greatest lake in South East Asia and one of the world richest biodiversity located in the NorthⒸ ISERD202

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western part of Cambodia (Fig. 1). Stung Sangkae catchment is the third largest of Tonle Sap Basinriver system with an area of 6,051 km2. Stung Sangkae River is one of the key sources of water in
Battambang, Cambodia. The natural habitats of this region form a complex network ofinterconnected landscapes and watersheds that provides important ecosystem services to the region(Killeen, 2012). The majority of the catchment area is mostly lowlands with elevations of less than
100 m above the mean sea level, and with gentle slopes. There are six (6) main soil types within thecatchment area and 13 land uses. Of the 13 land uses, 25% are planted with annual crops such as
cassava (Manihot esculenta L.), corn (Zea mays L.), sugarcane (Saccharum officinarum L.) etc. and
24% is under rice production. Battambang Province receives most of its rainfall during the southwest
monsoon from May to November, as most of the regions in Cambodia. According to the MekongRiver Commission in 2008, long-term rainfall between 1920 and 2004, with 60 years of complete
data, averaged 1,318 mm/year. Typically, there is very little rainfall from December to March (onaverage 5.6% of the annual total), and because of high temperatures and evaporation rates throughMay, there is usually little standing water in most paddy fields until June.

Fig. 1 A map of Stung Sangkae catchment showing the Great Lake, stream gauge andrainfall stations with a background of 30 m resolution DEM
SWAT Modeling
Soil and Water Assessment Tool is a physically based semi-distributed continuous time model
developed by United States Department of Agriculture-Agricultural Research Service (USDA-ARS)(Arnold et al., 1998). Soil and Water Assessment Tool can be operated to estimate, predict, andassess the effects of soil characteristics, land management, and climate change on water resource,
sediment, nutrient cycling and crop growth in the enormous complicated watersheds (Neitsch et al.,2002). Soil and Water Assessment Tool model simulates various hydrologic processes, including
surface runoff calculation, using either Natural Resources Conservation Service curve number
method or the Green and Ampt infiltration equation. For the quantification of evapotranspiration,
SWAT model offers several approaches such as, Pristley-Taylor, Hargreaves, or Penman-Monteith
methods. Groundwater flow, lateral flow and percolation are assessed through mass balance of theunderlying system (Anand et al., 2018).
In this research, the required input data of SWAT model in Stung Sangkae catchment werecollected from different sources both locally and globally. A digital elevation model (DEM) with a
30 m resolution was retrieved from the Shuttle Radar Topography Mission (SRTM). Stream/river in2010 and administrative province/district in 2014 data obtained from the open source site atⒸ ISERD

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www.opendevelopmentcambodia.net. A land use-land cover map was developed by the SERVIR
Mekong from 1998 to 2018 based on satellite imagery. A soils map of 16 soil types developed by
Crocker in 1962 and was classified based on the FAO/UNESCO in 1984 with the classification up
to two levels (0-30 cm and 30-100 cm) were utilized during the simulation process. Rainfall data
(1995‒2018) were obtained from Department of Meteorology (DoM) of Ministry of Water
Resources and Meteorology (MoWRAM) and satellite image from bias correction. Daily andmonthly streamflow data (2000‒2018) were obtained from Department of Hydrology and River
Work (DHRW) of Ministry of Water Resources and Meteorology (MoWRAW).
For a better estimation of model parameters in order to simulate the streamflow to match theobserved value, the model was calibrated manually by adjusting several default parameters. We
calibrated daily streamflow from 2000 to 2010 with a basis of LULCC from SERVIR-Mekong in
2003, where the simulation period between 1995 and 1999 serving as the warm-up period. Then themodel with modified parameters is validated by running different time period to ascertain model
consistency between the observed and simulated values. In the study, we validated daily streamflow
from 2011 to 2018 with a basis of LULC from SERVIR-Mekong in 2003. After the evaluation of
SWAT model rating, we modified different LULCC layers (1998, 2008, 2013, and 2018) as an input
parameter. All simulated results from calibration and validation were evaluated by three quantitative
statistics: i) Coefficient of determination (R2); ii) Nash-Sutcliffe efficiency (NSE); and iii) Percent
Bias (PBIAS).
RESULTS AND DISCUSSION
LULC Change Analysis
Table 1 summarized the relative areas of each land use class for the years 1998, 2003, 2008, 2013
and 2018. The result has shown that during the study period (1998-2018), the forest land, wetland,and paddy rice has decreased by 5.10%, 1.44%, and 1.20%, respectively. These land uses wereconverted into cultivated land with an increase of the agricultural land by 7.60%. The changes invarious land uses was due to increasing human influence through the development of urban area andthe process of industrialization and modernization.
Table 1 Summary of LULC change in Stung Sangkae catchment from 1998 to 2018 (%)
LULC
Agricultural land (AGRR,ORCD)
Forest (FRSD,FRSE,FRST)
Wetland Forest (WETF,WETL,WETN)
Rice (RICE)

1998
45.60
23.83
25.33
5.02

2003
47.62
20.74
24.44
6.97

2008
47.29
20.62
24.22
7.63

2013
48.07
20.43
23.99
7.25

2018
53.20
18.74
23.89
3.82

Change
7.60
-5.10
-1.44
-1.20

Model Sensitivity Analysis
In the study, we analyzed the five most sensitive parameters which influenced water quantity in
Stung Sangkae catchment namely: 1) Manning’s “n” (CH_N2); 2) Effective hydraulic conductivity(CH_K2); 3) Groundwater delay (GW_DELAY); 4) Threshold water depth in the shallow aquifer
for return flow (GWQMN); and 5) Threshold water depth in the shallow aquifer for “revap”(REVAPMN). The fitted value of model parameters was illustrated in Table 2. Sensitivity analysis
of different parameters was performed for streamflow.
Impact of LULCC on Streamflow
The model was calibrated for the 2000–2010 period, while the validation period was done from 2011
to 2018. The model performance was reasonably good with limited rainfall data as shown in Table
3. Fig. 2 presented the simulation results of LULCC in 1998, 2003, 2008, 2013 and 2018 about streamflow.
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Results of the simulation LULCC were not significantly different. However, the result of streamflow
has increased with the range from 1.6 m3/s to 781 m3/s due to the loss of forestland converted into
the agricultural land. Several simulation studies revealed that LULCC due to deforestation haveincreased the mean annual streamflow (Anand et al., 2018; Oeurng et al., 2019; Quyen et al., 2014).

Table 2 Parameters use for calibration and validation
Parameter
CH_N2
CH_K2
GW_DELAYGWQMNREVAPMN

Definition
Manning’s “n” value for the main channel
Effective hydraulic conductivity in the main
channel alluvium (mm/h)
Groundwater delay (days)
Threshold depth of water in the shallow aquifer
required for return flow to occur (mm H2O)
Threshold water depth in the shallow aquifer for“revap” ( mm )Default range-0.01‒0.3
0‒500

Fitted value
0.22
5

0‒500
0‒5000

40
1500

0‒500

500

Table 3 Summary result of model performance efficiency evaluation of the monthly stream
flow for Stung Sangkae catchment
Calibration (2000-2010)

Validation (2011-2018)

A basis of LULC from SERVIR-Mekong
R2
NSE
PBIAS

1998
0.40
0.40
1.06

2003
0.41
0.40
0.34

2008
0.41
0.40
-0.19

2013
0.41
0.41
-0.60

2018
0.41
0.40
0.88

1998
0.28
0.21
31.24

2003
0.28
0.22
30.52

2008
0.28
0.22
30.05

2013
0.28
0.22
29.73

2018
0.28
0.21
31.10

Fig. 2 Daily and monthly streamflow (cm) in calibration and validation periods
Impact of LULCC on Water Balance
Due to LULCC from 1998 to 2018, the average annual change in SURFQ, LATQ, GW, ET and water
yield was approximately 277 mm, 77 mm, 297 mm, 764 mm, and 668 mm, respectively. Fig. 3
presented the spatial distribution of water balance in Stung Sangkae catchment under the gauging
station. The water yield and the surface runoff came to catchment has increased by 0.9 mm and 10Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2021) 12-2mm, respectively; the lateral flow, the ground water and the evapotranspiration has declined by 3
mm, 6.2 mm, and 0.97 mm, respectively. Moreover, the changes shown in Fig. 3, in terms of thedifferent hydrologic components such as surface runoff, water yield, and ET were in agreement withthe results reported by other researchers (Anand et al., 2018; Dey and Mishra, 2017; Kundu et al.,2017; Remondi et al., 2016; Wagner et al., 2017). However, we noted that the impacts of LULCC on
the water balance varied significantly for each sub-basin due to urbanization. Our results were similar
to several studies that investigated the correlation between urbanization and the water balance intropical regions (Anand et al., 2018; Gumindoga et al., 2014; Remondi et al., 2016; Wagner et al.,2013).

Fig. 3 Change in water balance from 1998 to 2018 for Stung Sangkae catchment
CONCLUSION
Based on the LULCC data provided by SERVIR Mekong, results showed that from 1998 to 2018,
the forest land, wetland, and paddy rice had decreased by 5.10%, 1.44%, and 1.20%, respectively.
These led to the increase of agricultural land by 7.6%. This increase in agricultural land resulted in
the increase of average annual surface runoff (SURFQ) by 10 mm, reduction of 3 mm in the averageannual lateral flow (LATQ), reduction of the average annual ground water (GW) by 6.2 mm, decreaseof 0.97 mm in average annual evapotranspiration (ET), and an increase of average annual water yieldby 0.9 mm. Moreover, the model captured a reasonable agreement with the observed values inmonthly basis. Based on the validated water discharge and water balance results in 2018, LULCC
have impacted the environmental sustainability, especially the streamflow that caused flooding at thedownstream watershed due to declined forest cover at the watershed.
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ACKNOWLEDGEMENTS
This research and publication are made possible by the generous support of the American People
provided to the Royal University of Agriculture through Partnerships for Enhanced Engagement in
Research (PEER) Cycle 7 funded by the United States Agency for International Development(USAID) and implemented by the National Academy of Sciences (NAS) under Sponsor Cooperative
Agreement No. AID-OAA-A-11-00012 of Subaward Number: 2000010295. The contents are thesole responsibility of the authors and do not necessarily reflect the views of NAS, USAID or theUnited States Government. Moreover, the research and publication are made possible by thegenerous support of the American people through support by the United States Agency forInternational Development to the Feed the Future Innovation Labs for Collaborative Research on
Sustainable Intensification (Cooperative Agreement No. AID-OAA-L-14-00006, Kansas State
University). Thanks to Kelly Robbins, Senior Program Officer, the National Academy of Sciences(NAS), for her support and guidance on the research grant implementation, and also thanks to theUnited State Department of Agriculture (USDA), as well as the Institute of Technology of Cambodia(ITC), and International Fertilizer Development Center (IFDC) for data provision, technical support,
assistance, and consultation.
REFERENCES
Anand, J., Gosain A.K. and Khosa, R. 2018. Prediction of land use changes based on land change modeler andattribution of changes in the water balance of Ganga basin to land use change using the SWAT model.
Science of the Total Environment, 644, 503-519, Retrieved from Doi: 10.1016/j.scitotenv.2018.07.017
Ang, R. and Oeurng, C. 2018. Simulating streamflow in an ungauged catchment of Tonlesap lake basin in
Cambodia using soil and water assessment tool (SWAT) model. Water Science, 32 (1), 89-101, Retrieved
from Doi: 10.1016/j.wsj.2017.12.002
Arnold, J.G., Srinivasan, R., Muttiah, R.S. and Williams, J.R. 1998. Large-area hydrologic modelling andassessment part I: Model development 1. Journal of American Water Resources Association, 34 (1), 7389.
CARD-ISU. 2020. SWAT literature database for peer-reviewed journal articles. Retrieved from https://www.
card.iastate.edu/swat_articles/
Crocker, C.D. 1962. The general map of the Kingdom of Cambodia and the exploratory survey of the soils of
Cambodia. Joint Publication, Royal Cambodian Government Soil Commission/USAID, Save Cambodia's
Wildlife, Agriculture, Atlas of Cambodia: Maps on Socio-Economic Development and Environment 2nded., Phnom Penh, 137.
Dey, P. and Mishra, A. 2017. Separating the impacts of climate change and human activities on streamflow:
A review of methodologies and critical assumptions. J. Hydrol. 548, 278-290, Retrieved from https://doi.org/10.1016/j.jhydrol.2017.03.014
Gassman, P.W., Reyes, M.R., Green, C.H. and Arnold, J.G. 2007. The soil and water assessment tool:
Historical development, applications, and future research directions. Transactions of the ASABE, 50,
1211-1250, Retrieved from Doi:10.13031/2013.23637.
Gumindoga, W., Rientjes, T., Shekede, M., Rwasoka, D., Nhapi, I. and Haile, A. 2014. Hydrological impactsof urbanization of two catchments in Harare, Zimbabwe. Remote Sens, 6, 12544-12574, Retrieved fromhttps://doi.org/10.3390/rs61212544
Killeen, T.J. 2012. The cardamom conundrum: Reconciling development and conservation in the Kingdom of
Cambodia. National University of Singapore Press, Singapore.
Kundu, S., Khare, D. and Mondal, A. 2017. Past, present and future land use changes and their impact on waterbalance. Environmental Management, 197, 582-596, Retrieved from http://dx.doi.org/10.1016/j.
jenvman2017.04.018
National Committee for Democratic Development and Decentralization (NCDD). 2010. Battambang provincial
profile. National Committee for Democratic Development and Decentralization, Phnom Penh.
Neitsch, S.L., Arnold, J.G. and Srinivasan, R. 2002. Soil and water assessment tool (SWAT) user’s manual,
Version 2000. Grassland Soil and Water Research Laboratory, Blackland Research Center, Texas
Agricultural Experiment Station, Texas Water Resources Institute, Texas Water Resources Institute,
College Station, Texas.

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Oeurng, C., Cochrane, T.A., Chung, S., Kondolf, M.G., Piman, T. and Arias, M.E. 2019. Assessing climatechange impacts on river flows in the Tonle Sap Lake basin, Cambodia. Journal of Water, 11, 618, Retrieved
from http://dx.doi.org/10.3390/w11030618
Quyen, N.T.N., Liem, N.D. and Loi, N.K. 2014. Effect of land use change on water discharge in Srepok
watershed, Central Highland, Viet Nam. International Soil and Water Conservation Research 2 (3), 74-86.
Remondi, F., Burlando, P. and Vollmer, D. 2016. Exploring the hydrological impact of increasing urbanisation
on a tropical river catchment of the metropolitan Jakarta, Indonesia. Sustain. Cities Soc., 20, 210-221,
Retrieved from https://doi.org/10.1016/j.scs.2015.10.001
Sotheary, K. 2015. Current status of infrastructure development, future planning and investment and past
climate change impacts (Khmer version). A Presentation during the Urban Climate Resilience in Southeast
Asia Partnership Project Dissemination in Battambang, Provincial Department of Public Work andTransportation, Battambang.
Wagner, P.D., Bhallamudi, S.M., Narasimhan, B., Kumar, S., Fohrer, N. and Fiener, P. 2017. Comparing theeffects of dynamic versus static representations of land use change in hydrologic impact assessments.
Environ. Model. Softw., Retrieved from https://doi.org/10.1016/j.envsoft.2017.06.023
Wagner, P.D., Kumar, S. and Schneider, K. 2013. An assessment of land use change impacts on the water
resources of the Mula and Mutha Rivers catchment upstream of Pune, India. Hydrol. Earth Syst. Sci., 17:2233-2246, Retrieved from https://doi.org/10.5194/hess-17-2233-2013Ⓒ ISERD

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Research article
erd

The Possibility of Producing and Distributing Healthy
Cassava Seeds in Cambodia
TAMON BABA*
College of Letters, Ritsumeikan University, Kyoto, Japan
Email: babatmn@gmail.com

HISAKO NOMURA
Faculty of Agriculture, Kyushu University, Fukuoka, JapanPAO SREAN
Faculty of Agriculture and Food Processing, National University of Battambang, Cambodia

THA THAN
Faculty of Agriculture and Food Processing, National University of Battambang, Cambodia

KASUMI ITOInternational Center for Research and Education in Agriculture, Nagoya University, Japan
Received 31 December 2020

Accepted 15 November 2021(*Corresponding Author)

Abstract This study discussed the possibility of producing and distributing healthy cassava
seeds in Cambodia. Since 2015, there has been no official healthy seed certification anddistribution system in Cambodia despite the rapid spread of the Sri Lankan Cassava Mosaic
Disease in Southeast Asia. To improve cassava production and its sustainability, we
conducted interviews using a structured questionnaire in Battambang and Pailin Provincesfrom April to November 2017 and received responses from 205 cassava producers. The
results showed that most producers reused seeds from the previous years' harvest andindicated considerable market interest for healthy cassava seeds in Cambodia. Finally, we
found that training and information on healthy seed production combined with stringent pest
and disease monitoring efforts are essential. This study suggests that a market-based, healthycassava seed distribution system can be established in Cambodia.
Keywords cassava, seed production and distribution, Cambodia, sustainable,market-based solution

INTRODUCTION
Cassava (Manihot esculenta Crantz) is one of the largest staple crops in the world and one of themost important cash crops in Cambodia (FAO, 2020; MAFF, 2018). Although there are many uses
for cassava starch, from food to cosmetics, its utilization as a source of biofuel has increased its
demand in recent years. Cassava propagates from the cuttings of the remaining cassava stems after
its tuber is harvested (Tokunaga et al., 2018). Although propagation makes cassava grow fastercompared to plant growth from seed germination, once contaminated with a virus or a phytoplasma,
this propagation method has a negative impact. It could easily spread diseases like witches' broom(Alvarez et al., 2013) and harmful pests, such as mealybugs, red mites, and scale insects. Furthermore,
recently, Sri Lankan Cassava Mosaic Disease (SLCMD), which severely affects cassava and spreads
through whitefly and human factors, has spread rapidly in Southeast Asia (Wang et al., 2016; Uke etal., 2018).
In Cambodia, the government-led cassava extension system has been limited (MAFF, 2015;
Tokunaga et al., 2018). The Department of Agricultural Extension of the Ministry of Agriculture,
Forestry, and Fisheries (MAFF) was established in 1995. However, their activities are limited due toa lack of funding, technical expertise, extension materials; an inadequate production and distributionⒸ ISERD

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system; and human resources to support extension processes. As a result, an official system forproducing and distributing cassava seeds has yet to be established.
In Ratanakiri and Battambang Provinces of Cambodia and Dak Lak and Tay Ninh Provinces ofVietnam, cassava seeds are informally distributed and self-regulated, without any active quality
certification schemes (Delaquis et al., 2018). Thus, traders play an important role in the long-distanceseed movement. The use of farm-saved seed and exchanges among acquaintances within thecommunity are most common. However, given the spread of SLCMD, this informal and selfregulated method of seed distribution has increased the chances of humans spreading the disease.
To remedy this situation and promote the country's economic growth, the Royal Government of
Cambodia (RGC) recently announced its "National Policy on Cassava 2020-2025," which declaredcassava as one of the potential crops for agro-industrial development in Cambodia (RGC, 2020).
Therefore, MAFF and its allied universities are required to "promote and encourage propagation
farms and private cassava stem suppliers to sell and distribute healthy and disease-free cassava
stems." (RGC, 2020). However, even though this policy is relatively new, there have not been any
detailed discussions about the possibility of enabling the production of healthy cassava seeds.
Prior to the current policy discussion, since 2016, we have been conducting a project titled"Development and Dissemination of a Sustainable Production System Based on Invasive Pest
Management of Cassava in Vietnam, Cambodia, and Thailand" supported by the Japan Science andTechnology Agency and the Japan International Cooperation Agency. The project aims to establish
a sustainable production system that utilizes healthy seeds by developing a market-based
dissemination model that supports the private sector, producers, and the government, with amanagement system for invasive cassava diseases and pests. For this project, it was essential first to
identify the producers' cassava seed preferences, distribution, propagation methods, and demand for
healthy cassava seeds. Our projects contribute to creating a certified production and distribution
system for healthy cassava seeds, in line with the one envisioned by the Royal Government of
Cambodia.
OBJECTIVE
This study aims to discuss the potential for healthy cassava seed production and distribution in the
Cambodian market by characterizing the present status of cassava seeds, including producers'
preferences for cassava varieties and their demand for healthy cassava seeds based on a structured
questionnaire interview. Finally, the project mentioned above focusing on the production system of
healthy seeds was used as a case study.
METHODOLOGY
We interviewed producers about the 2016-2017 cassava production cycle in two Districts of Pailin
Province and six Districts of Battambang Province, northwest of Phnom Penh, the capital of
Cambodia, from April to November 2017 using a structured questionnaire. The total planted area of
134,385 ha in Battambang is the largest cassava production land area among all Provinces andproduces 3,769,266 tons of cassava per year. Pailin Province has the fifth largest cassava plantedarea of 59,067 ha in Cambodia, producing 1,477,175 tons, the third-largest in terms of quantity(MAFF, 2018).
A stratified random sample based on the cassava planted area was applied to select the
respondents. The total respondents included 205 cassava producers: 144 from Battambang Provinceand 61 from Pailin Province. All the questionnaires were valid. Then, qualitative and quantitative
analyses were applied.
RESULTS AND DISCUSSION
Some characteristics of the respondents are profiled below (Table 1). In the survey, only the primarycassava producers in the household were considered, comprising 93% males and 7% females. TheirⒸ ISERD

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average age, cassava planting times, and cultivated area was 49 years for males and females, 4.08.
and 3.73 ha, respectively. As discussed below, 40% of producers purchased seeds for the 2016-2017
cycle. While currently there is no healthy seed distribution system, approximately 68% of
respondents showed a willingness to buy healthy seeds, and 72% showed a willingness to become
healthy seed producers.
Table 1 Descriptive summary of survey respondents
Variables
Gender (1=male, 0=female)Age (years)
Province (dummy)
Cassava planting times before the 2016-2017
cycle (times)
Total cassava cultivated area (ha)Purchased seeds for the 2016-2017 cycle or not(1=yes, 0=no)
Want to buy healthy seeds (1=yes, 0=no)
Want to be a healthy seed producer(1=yes, 0=no)

Mean
0.93
49.00
0.70

Std. Dev.
0.26
13.29
0.46

Min.
0
21
0

Max.
1
78
1

4.08

3.03

0

16

3.73

4.65

0.09

40

0.40

0.49

0

1

0.68

0.47

0

1

0.72

0.45

0

1
(N=205)First, the survey inquired about the cassava varieties used by the producers (Table 2). While
78.9% of answers included "Unknown" or nicknames in Khmer, such as "Kor Teul" (long neck) and"Masao" (starch), others provided a variety name. Although we cannot confirm the accuracy of theprovided variety names, our survey reveals that they mostly use Thai varieties such as Rayong 9,
Rayong 90, and Houybong. Based on visual checks done by a descriptor created by our project, thevarieties called "Unknown," "Kor Teul," and "Masao" include KU50 and Rayong 7, which are also
from Thailand. The name "Masao" implies that producers care about the starch contents of thevariety; Masao varieties often have a reputation of containing a high starch content. We find that
Cassava producers prefer high starch content varieties. However, they do not have a very strong
preference over the specific variety and can accept the variants distributed in the market.
Table 2 Cassava varieties used by the surveyed producers
VarietyUnknown
Kor Teul
Masao
Malay
MeyongNamdeng
Red Petiole(Kandeng,
Kanteng)

Unknown
Number ofanswers%

Variety

71
61
25
3
1
1

33.3%
28.6%
11.7%
1.4%
0.5%
0.5%

6

2.8%

Rayong 2
Rayong 3
Rayong 4
Rayong 5
Rayong 9
Rayong 11
Rayong 90
81
85
89
Houybong

Thai varieties
Number ofanswers
1
1
2
1
9
1
9
6
1
1
13

%
0.5%
0.5%
0.9%
0.5%
4.2%
0.5%
4.2%
2.8%
0.5%
0.5%
6.1%
(N=213)

Second, the results showed that 40.0% of those surveyed did not buy cassava seeds because
they reused the seeds harvested from their fields in the previous cycle. Further, 76.9% of those whopurchased seeds bought them in their neighborhood, while 11.5% bought seeds imported fromThailand, and the remaining 11.5% bought seeds brought by road from Vietnam. This resultⒸ ISERD

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complements the results of the previous study by Delaquis et al. (2018). These results show that seeds
can easily be imported and transported across different regions; diseases and pests could easily spread.
Third, we asked producers, "Do you want to purchase healthy seeds if they are available on themarket?" To this, 139 (67.8%) producers answered affirmatively, and of those, 48.8% bought seeds
in the 2016-2017 cycle. It implies 33.1% (=48.8% x 67.8%) of producers might purchase healthy
seeds in the future. Further, the average percentages of producers who want to buy healthy seeds ineach "Actually purchased group" and "Not purchased group" are significantly different at a𝑥 2 statisticof 8.227 (p-value<0.01) (Fig. 1).

Pearson chi2(1) = 8.227 Pr = 0.004

Fig. 1 Producers who want to purchase healthy seeds based on the 2016-2017 purchase record
Fourth, 71.7% of producers answered yes to the question, "Do you want to produce healthy
seeds as a business?" Furthermore, the producers with a large cassava cultivation area were moreinterested in healthy seed production than smaller ones (Fig. 2). Additionally, this is statisticallysignificantly different at a𝑥 2 statistic of 10.262 (p-value<0.01). It implies that the larger the cassava
area producers have, the higher the willingness to be healthy cassava producers. Thus, larger landarea producers recognize the business opportunities present in the production of healthy seeds.

Pearson chi2(2) = 10.262 Pr = 0.006

Fig. 2 Producers who want to produce healthy seeds by cassava cultivation area
Thus, we find that producers can accept new varieties, and those who purchased stem seeds forthe 2016-2017 cycle are interested in purchasing healthy seeds. Additionally, those with a production
area of 1 ha or more are more interested in producing healthy seeds than those with less than 1 ha ofcassava production area. These results suggest that there is a potential market for healthy seed cassava
in Cambodia. Further, since the existing seed distribution method could spread pests and diseases
across Cambodia, establishing a market-based certified healthy seed production system could preventthe spread of pests and diseases like SLCMD.

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Based on the results above, our project started a healthy seed production system in Cambodia
on a trial basis (Fig. 3). In Cambodia, the National University of Battambang (NUBB) has a Cassava
Propagation and Distribution Center. In 2018, the project selected two varieties, KU 50 and Rayong
7, and started producing healthy seeds through careful monitoring and Polymerase Chain Reaction(PCR) testing. Then, the varieties were sold to three producers who wanted to be healthy seedproducers in Battambang Province (Producer A: 1,351 healthy seeds), Banteay Meanchey Province(Producer B: 599 healthy seeds and 400 additional healthy seeds in 2019), and the other producer in
Banteay Meanchey Province, who stopped production immediately because of weather conditions.
We found these producers interested in the project through the survey and personal communications
in our pursuit to find healthy seed producers, and we also introduced them to the NUBB. The priceis 1$ per 1 bunch (20 seeds), which was the market cassava price at the time of the study. Two
producers in Banteay Meanchey Province were also supported by Deutsche Gesellschaft fürInternationale Zusammenarbeit. In 2019, in addition to these three producers, two more producers in
Battambang and Oodar Meanchey Provinces and the General Directorate of Agriculture (GDA) fieldin Battambang Province started to be healthy seed producers. With the prevalence of the spread of
SLCMD, gradually more producers became interested in becoming healthy seed producers.

Fig. 3 The healthy cassava seed distribution system at NUBB
These producers were trained periodically to monitor cassava fields and could independently
execute such monitoring techniques. They also received information packages and training on pests
and diseases and how to treat them. The monitoring system recommended by the project is as follows.
1. When the cassava plants start producing leaves, check each border and the middle of the fieldcarefully to find abnormal plants shorter than other plants or those that are yellow. 2. Check the stemfrom the bottom to the bud and the surface of the leaves to find pests, such as whitefly, mealybug,
red mite, and scale insect, diseases such as witches' broom, and SLCMD; and 3. Remove pests byhand, in case there are few. If the pest infestation is severe, use recommended chemicals to control
whitefly, a Sri Lankan cassava mosaic virus vector. 4. Finally, and most importantly, remove infectedor suspicious SLCMD plants from the field, bury or burn them, and replace them with healthy
cuttings.
At the time of harvest, and if the PCR test result of their samples at NUBB is negative, Producer
A and Producer B can sell these healthy seeds to the general producers who value such seeds. After
multiplying healthy seeds, the producers sold them in 2019 (Producer A: 2,000 stems (1 GDA field))and 2020 (Producer A: 2,400 stems (1 general producer and 1 GDA field); Producer B: 1,095 stems(11 general cassava producers)), while other healthy seed producers did not sell because they were
under multiplying their stems. Some of these general producers have become interested in producing
healthy seeds. They have joined our monitoring training to sell such seeds to other producers as abusiness.
These findings show that NUBB and healthy seed producers can become sources of trusted
cassava seeds for producers in Cambodia. While Cambodia has no official seed distribution system,
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healthy seeds produced in this trial are not free from the risk of disease. Therefore, monitoring is an
essential part of healthy seed production. Nevertheless, the results show that a healthy seedproduction system centered on NUBB with well-trained healthy seed producers can positively affectthe cassava sector in Cambodia.
CONCLUSION
The study clarified that cassava producers in Cambodia could accept and produce healthy cassava
seeds. Producers care about the starch contents of the variety, though they do not have a very strong
preference for the specific variety and can accept variants distributed in the market. Those whopurchased seeds in the 2016-2017 cycle are still interested in purchasing healthy seeds. Additionally,
those with a cassava production area of 1 ha or more are more interested in producing healthy seeds
than those with less than 1 ha. Further, we demonstrated that the pilot project in Battambang Province
had created a healthy production system for cassava seeds in Battambang and Banteay Meanchey
Provinces, which has seen positive results. We emphasize that monitoring is an integral part of thehealthy seeds production system. While SLCMD has been spreading, producers have a high demand
for a healthy seed market. Therefore, our market-based production system can contribute toward
creating sustainable cassava production to help producers increase their income and improve thecountry's economic growth while meeting the policy aims of the Royal Government of Cambodia.
ACKNOWLEDGEMENTS
This research was supported by Science and Technology Research Partnership for Sustainable
Development (SATREPS) in collaboration between Japan Science and Technology Agency (JST,JPMJSA1508) and Japan International Cooperation Agency (JICA). We would also like to thankDeutsche Gesellschaft für Internationale Zusammenarbeit for their cooperation.
REFERENCES
Alvarez, E., Pardo, J.M. and Truke, M.J. 2013. Detection and identification of 'Camdidatus Phytoplasma
asteris', Related phytoplasma associated with a witches' broom disease of cassava in Cambodia.
Phytopathogenic Mollicutes, 3 (2), 77.
Delaquis, E., Andersen, K.F., Minato, N., Le Cu, T.T., Karssenberg, M.E., Sok, S., Wyckhuys, K.A.G., Newby,
J.C., Burra, D.D., Srean, P., Phirun, I., Le, N.D., Pham, N.T., Garrett, K.A., Almekinders, C.J.M., Struik,
P.C. and de Haan, S. 2018. Raising the stakes: Cassava seed networks at multiple scales in Cambodia andVietnam. Front. Sustain. Food Sys., 2, 73.
Food and Agriculture Organization (FAO). 2020. Food and Agriculture Statistics, Retrieved from http://
www.fao.org/faostat/en/#home
MAFF (Ministry of Agriculture, Forestry and Fisheries in Cambodia). 2015. Agricultural extension policy inCambodia. Ministry of Agriculture, Forestry and Fisheries, Cambodia.
MAFF (Ministry of Agriculture, Forestry and Fisheries in Cambodia). 2018. Annual reports of the Ministry ofAgriculture, Forestry and Fisheries. Cambodia.
RGC (Royal Government of Cambodia). 2020. National policy on cassava 2020-2025. Royal Government of
Cambodia.
Tokunaga, H., Baba, T., Ishitani, M., Ito, K., Kim, O., Ham, L.H., Le, H.K., Maejima, K., Namba, S., Natsuaki,
K.T., Dong, N.V., Nguyen, H.H., Nguyen, N.C., Vu, N.A., Nomura, H., Seki, M., Srean, P., Tanaka, H.,
Touch, B., Trinh, H.X., Ugaki, M., Uke, A., Utsumi, Y., Wongtiem, P. and Takasu, K. 2018. Sustainable
management of invasive cassava pests in Vietnam, Cambodia, and Thailand. In Crop Production underStressful Conditions: Application of Cutting-edge Science and Technology in Developing Countries,
Springer Singapore, 131-157, Singapore.
Uke, A., Hoat, T.X., Quan, M.V., Liem, N.V., Ugaki, M. and Natsuaki, K.T. 2018. First report of Sri Lankan
cassava mosaic virus infecting cassava in Vietnam. Plant Dis., 102 (12).
Wang, H.L., Wang, X.W., Cui, X.Y. and Liu, S.S. 2015. First report of Sri Lankan cassava mosaic virus
infecting cassava in Cambodia. Plant Dis., 100 (5), 1029.

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Research article
erd

The Current Status of Cassava Producers and Healthy
Cassava Seed Production and Distribution Trial in Vietnam
NIEN CHAU NGUYEN*
Faculty of Agronomy, Nong Lam University, Ho Chi Minh City, Vietnam
Email: nien.nguyen@hcmuaf.edu.vn

TAMON BABA
College of Letters, Ritsumeikan University, Kyoto, JapanHISAKO NOMURA
Faculty of Agriculture, Kyushu University, Fukuoka, JapanKASUMI ITOInternational Center for Research and Education in Agriculture, Nagoya University, Japan
Received 26 January 2021

Accepted 15 November 2021(*Corresponding Author)

Abstract This study discusses the current status of cassava producers in Vietnam, the demandfor healthy cassava seeds, and the potential for a healthy seed production and distribution
system. Owing to the recent spread of Sri Lankan Cassava Mosaic Disease in South East
Asia, the government-led agricultural extension system and the informal cassava production
and distribution system in Vietnam have sought a "health" seed production system. To
improve the existing system and contribute to sustainable cassava production in Vietnam, we
conducted interviews using a structured questionnaire in Dong Nai, Gia Lai, and Tay Ninhprovinces from April to December 2017 and received responses from 182 cassava producers.
The results show that the majority of cassava producers rely on this crop for their income.
Therefore, they are interested in purchasing healthy seeds, and their willingness to pay isstatistically significantly higher than the purchasing price in all three provinces. Based on the
results and the existing cassava production and distribution system in Dong Nai, this project
instituted a monitoring system, polymerase chain reaction testing, and a healthy seedcertification system. This study found that seed producers face several difficulties, including
implementing a monitoring and management system. Thus, there is potential for establishinga healthy cassava seed production and distribution system in Vietnam.
Keywords cassava, seed production and distribution, Vietnam, willingness to pay

INTRODUCTION
Cassava (Manihot esculenta Crantz) is one of Vietnam's three most important food crops, with532,600 ha of cultivated area, an annual average yield of 18.8 tons per ha, and fresh root production
exceeding 10.27 million tons (GSO, 2018). Cassava is grown in as many as 40 of the country's 63
provinces. Vietnam ranks seventh in cassava production in the world (FAO, 2020).
The Sri Lankan Cassava Mosaic Disease (SLCMD) was first reported in Cambodia in 2015
(Wang et al., 2016) and was then found in Tay Ninh in 2018 (Uke et al., 2018). Since then,Vietnamese cassava producers have faced substantial challenges, as the disease drastically decreases
cassava yields (Fargette et al., 1988; Fauquet and Fargette, 1990; Makeshkumar, 2016). According
to Vietnam's Plant Protection Research Institute, the estimated annual cassava yield loss will be
between 12.7 percent and 34.6 percent. The starch content is expected to decrease by 1.02 percent to18.97 percent. SLCMD has spread rapidly using whiteflies as a vector; it is also spread throughinfected stem distribution as cassava can be quickly propagated from stems, which are transported
as "seed" to multiple locations.

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In Ratanakiri and Battambang provinces in Cambodia and Dak Lak and Tay Ninh provinces inVietnam, informal and self-regulated seed distribution systems are managed by private producers
and traders (Delaquis et al., 2018). Although these systems appear to work well in normal situations,once the stems are infected with SLCMD, the disease can rapidly spread through human factors, suchas traders and transporters, who distribute cassava seeds over a wide range.
In Vietnam, it is essential to understand the current production and stem movement situation,
including the socio-economic condition of cassava producers, to discuss the possibility of healthy
seeds. The seeds are considered healthy if they are not detected positive for SLCMD in thepolymerase chain reaction (PCR) testing. Thus, production and distribution should be carried out
through the market mechanism.
Vietnam has a public extension system founded in 1993, organized into five levels—central,provincial, district, commune, and village or hamlet. All 63 provinces have their own extension
centers (Tokunaga et al., 2018). Furthermore, an official cassava seed production and distribution
system exist in addition to the informal, self-regulated distribution system. As part of the official
system, the Hung Loc Agricultural Research Center (HLARC) in Dong Nai province in southern
Vietnam breeds, produces and distributes cassava varieties. Private producers under HLARC
propagate and distribute these stems among "general producers" who primarily cultivate cassava for
its roots and potential buyers of healthy cassava seeds in the province. This system, however, has nomonitoring methods, nor does it employ PCR testing or have any certification. Hence, there is apotential risk of the distributed stems becoming contaminated with viruses or phytoplasma, further
spreading the disease.
Therefore, since 2016, we have been executing a project titled "Development and Disseminationof a Sustainable Production System Based on Invasive Pest Management of Cassava in Vietnam,
Cambodia, and Thailand," supported by the Japan Science and Technology Agency and the Japan
International Cooperation Agency. This project aims to improve the current cassava seed production
and distribution system centered at HLARC and establish a sustainable production system that uses
healthy seeds. This system can be established by developing a market-based dissemination modelthat supports the private sector, producers, and the government and devising a management system
for invasive cassava diseases and pests. To improve the system, it is essential to first identify cassava
producers' seed preferences, their demand for healthy cassava seeds, and the current situation of
cassava production. However, sufficient information is not yet available.
OBJECTIVE
This study aims to discuss the current status of cassava producers and stem distribution in southern
Vietnam, including their cassava seed preferences. Further, the potentiality of a healthy cassava seedproduction and distribution system is also discussed, and producers' willingness to pay (WTP) for
healthy seeds is estimated. Finally, the improved cassava seed production and distribution systemdeveloped by the project is explained, and challenges are discussed.
MATERIAL AND METHODS
Study Site
A series of semi-structured interviews based on a questionnaire was conducted in southern Vietnam's
Dong Nai, Gia Lai, and Tay Ninh provinces (Fig. 1) from April to December 2017. First, we checked
the government census database and contacted local government offices to determine the cassava
producer population of the provinces; however, we discovered it to be fluctuating. However, thepurpose of the study was to capture the potential for seed production, the selection of seed farmers,
and willingness to pay. Thus, we used purposive sampling with equal selection based on cassava
plantation area to categorize the respondents into three groups: less than 1 ha, between 1 ha and lessthan 5 ha, and more than 5 ha. As a result, the total number of respondents was 182—60 in Dong
Nai, 61 in Gia Lai, and 61 in Tay Ninh.
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The three provinces mentioned above are the primary cassava cultivation areas in Vietnam(GSO, 2018). Tay Ninh and Gia Lai have the largest (64,800 ha) and second-largest (61,600 ha)
cassava production areas among all provinces and produce 2,024,000 tons and 1,207,100 tons,
respectively. Dong Nai stands at the 10th position among the country's 58 provinces and contains
five municipalities with 15,700 ha of cassava production area and 399,700 tons of production. The
main cassava production center in Dong Nai is the Xuan Loc district, and in Tay Ninh, it is the Tan
Chau district. In Gia Lai, the Dak Po and Krong Pa districts are the two leading cassava production
centers. Therefore, these locations were chosen for surveying.

Fig. 1 Survey areas in Vietnam
Theoretical Model
The concept of WTP is derived from the Hicksian welfare measure of compensating variation (CV).
The CV measure asks what compensating payment or offsetting change in income is necessary to
make an individual indifferent to an increase in price. This is often interpreted as the new price set.
The concept can be illustrated by following the standard economic theory of indirect utility function(Bateman et al., 2002), which can be written in the general form:
𝑉 = (𝑌, 𝑃, 𝑄)(1)where (𝑉) describes the economic wellbeing or maximum amount of utility a respondent can derivefrom their income (𝑌), given the prices of goods they face (𝑃) and the level of environmental quality(in this case, getting healthy, clean seeds not infected by pests or disease [𝑄]). WTP is defined as theamount that must be taken away from a person's income while keeping this utility constant:
𝑉 (𝑌 − 𝑊𝑇𝑃, 𝑃, 𝑄1 ) = 𝑉(𝑌, 𝑃, 𝑄0 )(2)where (𝑄0 ) and (𝑄1 ) are the alternative levels of the good or quality indexes (𝑄1 >𝑄0 , indicating that
(𝑄1 ) refers to improved environmental quality).
The WTP was estimated following Mitchell and Carson (1981, 1984), and the payment card
method of contingent valuation was used to estimate the WTP for healthy seeds. Producers wereasked how much they would be willing to pay to obtain a certified healthy cassava seed.
However, an open-ended payment card CVM question can generate a high number of zero
responses (Green et al., 1998). In that case, the distribution of WTP could be censored by the left toa zero value. To address this, Halstead et al. (1991) recommended using the Tobit regression modelas the more theoretically correct econometric model for the open-ended CVM format.
The Tobit regression model considers both the censored and continuous observations in theprocess of estimation. Following Kim and Cho (2002), the Tobit regression model can be expressed
by:
𝑊𝑇𝑃𝑖𝑇𝑜𝑏𝑖𝑡 = 𝑋𝑖′ 𝛽 + 𝑒𝑖

(3)′where 𝑊𝑇𝑃𝑖𝑇𝑜𝑏𝑖𝑡 is the unobserved continuous dependent variable; 𝑋𝑖 is a vector of explanatory
variables; β is a vector of coefficients; ei is an independently distributed error term, assumed to beⒸ ISERD

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normal with zero mean and constant variance σ2 ; and i = 1, 2, . . . . , n denotes individuals in thesample. The observed WTP variable is given by:
𝑋 ′ 𝛽 + 𝑒𝑖.
𝑊𝑇𝑃𝑖 = { 𝑖0𝑖𝑓 𝑊𝑇𝑃𝑖𝑇𝑜𝑏𝑖𝑡 > 0
𝑖𝑓 𝑊𝑇𝑃𝑖𝑇𝑜𝑏𝑖𝑡 ≤ 0(4)

Empirical Model and Hypothesis
The Tobit regression model can be expanded to include the socio-economic variables being
hypothesized to influence producers' willingness to pay for healthy cassava seeds(𝑊𝑇𝑃ℎ𝑒𝑎𝑙𝑡ℎ𝑦𝑠𝑒𝑒𝑑𝑙𝑖𝑛𝑔 ). The empirical model is presented in the following:
𝑇𝑜𝑏𝑖𝑡
𝑊𝑇𝑃ℎ𝑒𝑎𝑙𝑡ℎ𝑦𝑠𝑒𝑒𝑑𝑙𝑖𝑛𝑔= 𝛽0 + 𝛽1 𝑔𝑒𝑛𝑑𝑒𝑟 + 𝛽2 𝑇𝑎𝑦𝑁𝑖𝑛ℎ + 𝛽3 𝐺𝑖𝑎𝐿𝑎𝑖 + 𝛽4 𝑡𝑜𝑐𝑎ℎ𝑎 +𝛽5 𝑓𝑢𝑙𝑙𝑡𝑖𝑚𝑒 + 𝛽6 𝑒𝑥𝑝𝑒𝑟𝑖𝑒𝑛𝑐𝑒 + 𝛽7 𝑐𝑎𝑡𝑖𝑚𝑒𝑠 + 𝛽8 𝑐𝑎𝑚𝑎𝑖𝑛 + 𝛽9 𝑙𝑎𝑏𝑜𝑟 +𝛽10 𝑑𝑎𝑐𝑡𝑢𝑎𝑙𝑝𝑢𝑟𝑐ℎ𝑎𝑠𝑒 + 𝛽11 𝑑𝑤𝑖𝑙𝑙𝑖𝑛𝑔𝑛𝑒𝑠𝑠 + 𝛽12 𝑑𝑠𝑡𝑒𝑚𝑠𝑢𝑝𝑝𝑙𝑖𝑒𝑟 + 𝑒𝑖

(5)where the dependent and independent variables are defined in Table 1, 𝛽0 𝑡𝑜 𝛽12 are coefficients,and 𝑒𝑖 is the error term ~𝑁 (0, 𝜎 2 ).
The study hypothesizes that older producers, experienced producers, producers with larger land
areas devoted to cassava, producers with more family members engaged in cassava production, andproducers who would like to be healthy seed producers will have higher 𝑊𝑇𝑃ℎ𝑒𝑎𝑙𝑡ℎ𝑦𝑠𝑒𝑒𝑑𝑙𝑖𝑛𝑔 .
RESULTS AND DISCUSSION
Status of Cassava Producers in Southern Vietnam
Table 1 shows the socio-economic situation of the respondents. Among the cassava producers
surveyed, 86 percent were men and the rest were women; the average age of the respondents was
48.63 years. Their total cassava plantation area was 2.90 ha. Sixty percent of the respondents werefull-time producers and had an average of 23.82 years of general farming experience. They had
planted cassava 11.43 times on average, and 63 percent of them cited cassava production as theirmain source of income.
Table 1 Descriptive summary
Variables
genderage
DonNai
TayNinGiaLaitocahafulltime
experiencecatimescamainlabor
dactualpurchasedwillingness
dstemsupplier(1=male, 0=female)(years)Province (Don Nai=1, otherwise=0)
Province (Tay Nin=1, otherwise=0)
Province (Gia Lai=1, otherwise=0)
Total cassava cultivated area (ha)General farm working status (1=full time,
0=part time)Years of farming experience (years)
Number of cassava plantings done before
2016/2017 cycle (times)
Cassava as main income source (1=yes, 0=no)
Number of family members engaged in cassava
farming
Purchased seeds for the 2016/2017 cycle(1=yes, 0=no)
Want to buy healthy seeds (1=yes, 0=no)
Want to be a producer of healthy seed (1=yes,
0=no)Note: N=182Ⓒ ISERD

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Mean
0.86
48.63
2.01

Std. dev.
0.35
10.48
0.82

Min.
0
23
1

Max.
1
70
3

2.90

2.55

0.4

17

0.60

0.49

0

1

23.82

9.67

2

50

11.43

6.38

0

31

0.63

0.49

0

1

2.10

0.97

1

7

0.27

0.44

0

1

0.66

0.48

0

1

0.35

0.48

0

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The average family consisted of 4.51 members, of which 2.10 were engaged in cassava farming.
This information shows that our respondents were introduced to cassava production recently, and forsome of them, it has become an important cash source, making it a sort of family business. In otherwords, they depend on cassava production for a living. In addition, 27 percent of the respondents
purchased seeds for the 2016/2017 farming cycle, and 66 percent of them were interested inpurchasing healthy seeds if they were available in the market; moreover, 35 percent of the producers
wanted to make a business of producing healthy seeds.
Cassava Varieties
The cassava varieties used by the producers are shown in Table 2. Since these producers can cultivate
different varieties simultaneously, the total number is not equal to the number of respondents.
Whereas 17.4 percent of the respondents mentioned the variety of cassava they cultivated as"Unknown," others answered with specific variety names. In Dong Nai, KM325 (21 cases) andKM140 (20 cases) were preferred. In Tay Ninh and Gia Lai, KM419 and KM94 were the major
cassava varieties. Although this study could not confirm their claimed variety, it was found that theKM series was the most popular choice in southern Vietnam.
Table 2 Cassava varieties used by producers
Varieties
KM419
KM94
KM325
KM140
KM98-5
KM95
KM98
KM505
KM96
Unknown

Dong Nai
5
7
21
20
1
0
0
0
1
5

Tay Ninh
48
8
1
1
2
0
0
1
0
2

Gia Lai
13
9
1
1
6
4
2
0
2
25

Total
66
24
23
22
9
4
2
1
1
32

Percent
35.9
13.0
12.5
12.0
4.9
2.2
1.1
0.5
0.5
17.4

Note: N=184

Among the respondents, 72.5 percent did not purchase cassava seeds for planting or replanting
and instead used stems from the previous cycle. Of the remaining producers, 52.0 percent bought
stems from their neighbors or relatives. These community-level stem exchanges are dominant in
Vietnam and Cambodia (Delaquis et al., 2018). Another 46.0 percent bought stems from seed dealers
because they wanted to explore new varieties with higher starch content. In Dong Nai, one cassava
producer bought stems from the HLARC. Based on our interviews, most seed dealers were from the
Tay Ninh province. This fact is consistent with a previous study's finding that Tay Ninh is "the highly
commercialized 'cassava seed basket' of Southern Vietnam" (Delaquis et al., 2018).
Healthy Cassava Seed and Distribution System
We also asked the respondents whether they would purchase healthy stems if they were available inthe market, and 65.9 percent of the producers answered yes, of which the percentages for Dong Nai,
Tay Ninh, and Gia Lai were 23.08, 18.68, and 24.18, respectively. In contrast, 28.03 percent of
producers would not purchase healthy stems, of which the percentages in Dong Nai, Tay Ninh, and
Gia Lai were 4.95, 14.84, and 8.24, respectively. Another 6.05 percent of producers would like tohave more information about the growth status, yield, and starch content of healthy varieties before
making a decision.
Further, we found that the respondents' WTP for healthy cassava seeds was significantly higher
than the actual purchasing seed price in all three provinces (Table 3). Thus, we confirmed that there
is a potential market for healthy cassava seeds.
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Table 3 Purchase, seed price, and WTP for healthy cassava seeds by province
Purchase for cassava seed
% (producers)
Yes
No
Other
23.08
4.95
4.95
Dong Nai
(42)
(9)
(9)
18.68
14.84
0.00
Tay Ninh
(34)
(27)
(0)
24.18
8.24
1.10
Gia Lai
(44)
(15)
(2)
Note: Price in VND, 22500 VND ~ 1 USD
Province

Mean of seed price(95% C.I.)

Mean of WTP(95% C.I.)

18546(16837-20255)
11528(8418-14637)
12593(10578-14607)

24091(19630-28552)
22875(17140.45-28609.55)
17500(15841-19159)

t statistic
2.61
4.2
3.64

Table 4 presents the factors that influence producers' 𝑊𝑇𝑃ℎ𝑒𝑎𝑙𝑡ℎ𝑦𝑠𝑒𝑒𝑑𝑙𝑖𝑛𝑔 . The results show thatthe number of cassava plantings done before the 2016/2017 cycle influences 𝑊𝑇𝑃ℎ𝑒𝑎𝑙𝑡ℎ𝑦𝑠𝑒𝑒𝑑𝑙𝑖𝑛𝑔 .
When we run the pair-wise regression, older producers, producers with larger cassava land area,
producers with more family members engaged in cassava production, and producers who would liketo be healthy seed producers had higher 𝑊𝑇𝑃ℎ𝑒𝑎𝑙𝑡ℎ𝑦𝑠𝑒𝑒𝑑𝑙𝑖𝑛𝑔 at the statistically significance level of
p<0.10. However, the effects of these individual factors diminish with the number of times they had
previously planted cassava. There was a strong correlation between number of years planting cassava
and age, so we excluded age. Apart from that there were no other strong correlations. Thus, we canconclude that when producers are experienced with cassava cultivation, they understand theimportance of purchasing healthy seeds and perhaps the high risk of purchasing unknown seeds that
could spread pests and disease. You may as well say that older people prefer to purchase healthycertified seeds.
Table 4 Determining factors that influence producers' WTP
𝑊𝑇𝑃ℎ𝑒𝑎𝑙𝑡ℎ𝑦𝑠𝑒𝑒𝑑𝑙𝑖𝑛𝑔

VARIABLES
gender

2,551(3,153)
2,008
TayNinh(2,632)-2,364
GiaLai(2,463)
464.4
tocaha(362.3)-392.7
fulltime(2,071)10.84
experience(106.7)313.8
catimes(161.6)-395.5
camain(1,975)-710.3labor(907.2)-1,541
dactualpurchase(2,158)
7,635
dwillingness(7,407)2,659
dstemsupplier(1,979)9.803e+07
var(e.willprice)(1.298e+07)
9,355
Constant(9,918)114
Observations
Note: *** p<0.01, ** p<0.05, and * p<0.10, respectivelyⒸ ISERD

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Thus, following the current situation and the existing cassava production system centered at the
HLARC, our project tested the healthy seed production system. We did so because the organization
has played an important role as a cassava center, and producers and traders in Dong Nai and Tay
Ninh provinces buy cassava seeds from the HLARC (Fig. 2). As a "stock seed production field," theHLARC produce healthy seeds after careful field monitoring and PCR testing, and it sold seeds tothree producers in Dong Nai province in 2018 (Producer A, Producer B, and Producer C). These
producers found business prospects in healthy cassava seed production and were trained periodicallyon how to monitor cassava fields and to execute such monitoring by themselves. They also received
pest and disease information packages and were expected to become proficient at healthy seedproduction.

Fig. 2 Healthy cassava seed distribution system centered at HLARC
The project faced several challenges. In the existing system, the HLARC issues seeds to
producers for free, along with necessary tools such as production techniques, fertilizers, andchemicals, because it does not have enough fields to test new varieties and wants producers to
propagate and test them. Although, as part of our project, we wanted the HLARC to "sell" seeds to
producers so that our system could work in a market-based manner in future, the producers who used
to get seeds for free from the HLARC did not want to "purchase" them. In addition, producers weremore interested in "higher starch content" than "healthy" seeds. It was complicated to make themunderstand how healthy seeds are essential for sustainable production.
Furthermore, the monitoring system needed to produce healthy seeds had not been properly
implemented by the seed producers from the beginning. Our project provided them with information
packages and training on pests and diseases, including how to treat them, and tried to train them tomonitor cassava fields to avoid infections, pests, and their spread. As cassava has grown well for along time without monitoring, seed producers were averse to the idea of monitoring their fields. This
prevented the early mitigation of infected seeds when SLCMD spread in Dong Nai province in 2018.
Consequently, although the HLARC and seed producers inspected their fields and removed
suspicious seeds about two months after the planting in which the infection was detected, its spreadbecame worse in the province. Even the higher level of monitoring afterwards failed to completely
contain the spread of the infection.
Facing these challenges, however, Producer C produced healthy seeds for at least three cycles
and sold them to general producers, whereas Producers A and B stopped production. The reason forthis was that they were both producers in Dong Nai. Producers A and B were not following themonitoring protocol because the disease was not found in Dong Nai in the same year as in Tay Ninh.
Consequently, when the producers found their cassava infested, they could not continue harvesting
healthy cassava as the disease rapidly spread to other provinces, including Dong Nai. In contrast,
Producer C had predicted the status of SLCMD. Therefore, he followed the protocol and his cassava
production remained healthy. Although there is room for improvement in the monitoring done by
Producer C, the current findings show that our healthy seed production and distribution systemfollowing the existing system could work. To develop the system, it is essential for HLARC and the
project to provide every possible assistance to seed producers, teach them the importance ofmonitoring and management of healthy seeds for sustainable cassava production, and effectively
implement a monitoring and management system.
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CONCLUSION
This study analyzed the current status of cassava producers, their demand for healthy cassava seeds,
and the potential of a healthy seed production and distribution system in Vietnam. Cassava producers
depend on cassava production for their livelihood and tend to use varieties that are predominant intheir communities. In addition, they have a preference for the KM series, which indicates that thevariety is well-accepted as a healthy seed in the area. A production and distribution system of healthy
seeds has a potential market because the respondents in all three provinces were interested inpurchasing healthy seeds, and their WTP was statistically higher than their actual seed purchasing
price. Our project created a healthy seed production system in Dong Nai province. Although there
were many challenges, such as low awareness among seed producers about the importance offollowing the monitoring protocol and the rapid spread of SLCMD, one seed producer succeeded inpropagating healthy seeds by monitoring their production. Considering the existing system andproducers' preferences, we continue to explore ways to implement an efficient monitoring andmanagement system to mitigate the impact of SLCMD and distribute healthy seeds.
ACKNOWLEDGEMENTS
This research was supported by the Science and Technology Research Partnership for Sustainable
Development (SATREPS) in collaboration between the Japan Science and Technology Agency (JST,JPMJSA1508) and the Japan International Cooperation Agency (JICA).
REFERENCES
Deepthi, D.C. and Makeshkumar, T. 2016. Elimination of cassava mosaic disease through meristem culture
and field evaluation for yield loss assessment in cassava genotypes. J. Root Crops, 42 (1), 45-52.
Delaquis, E., Andersen, K.F., Minato, N., Le Cu, T.T., Karssenberg, M.E., Sok, S., Wyckhuys, K.A.G., Newby,
J.C., Burra, D.D., Srean, P., Phirun, I., Le, N.D., Pham, N.T., Garrett, K.A., Almekinders, C.J.M., Struik,
P.C. and de Haan, S. 2018. Raising the stakes: Cassava seed networks at multiple scales in Cambodia andVietnam. Front. Sustain. Food Syst., 2, 73.
Fargette, D., Fauquet, C. and Thouvenel, J.C. 1988. Yield losses induced by African cassava mosaic virus in
relation to the mode and the date of infection. Int. J. Pest Manag., 34 (1), 89-91.
Fauquet, C. and Fargette, D. 1990. African cassava mosaic virus: Etiology, epidemiology and control. Plant
Dis., 74 (6), 404-411.
Food and Agriculture Organization (FAO). 2020. Food and agriculture data. Retrieved from http://www.fao.
org/faostat/en/#home
GSO. 2018. Press release: Statistical yearbook of Vietnam 2017. General Statistic of Vietnam, Statistical
Publishing House, Vietnam.
Mitchell, R.C. and Carson, R.T. 1981. An experiment in determining willingness to pay for national water
quality improvements. Report to the U.S. Environmental Protection Agency, Resources for the Future.
Washington, D.C.
Mitchell, R.C. and Carson, R.T. 1984. A contingent valuation estimate of national freshwater benefits. Reportto the U. S. Environmental Protection Agency, Resources for the Future. Washington, D.C.
Tokunaga, H., Baba, T., Ishitani, M., Ito, K., Kim, O., Ham, L.H., Le, H.K., Maejima, K., Namba, S., Natsuaki,
K.T., Dong, N.V., Nguyen, H.H., Nguyen, N.C., Vu, N.A., Nomura, H., Seki, M., Srean, P., Tanaka, H.,
Touch, B., Trinh, H.X., Ugaki, M., Uke, A., Utsumi, Y., Wongtiem, P. and Takasu, K. 2018. Sustainable
management of invasive cassava pests in Vietnam, Cambodia and Thailand. In Crop Production underStressful Conditions: Application of Cutting-edge Science and Technology in Developing Countries,
Springer Singapore, 131-157, Singapore.
Uke, A., Hoat, T.X., Quan, M.V., Liem, N.V., Ugaki, M. and Natsuaki, K.T. 2019. First report of Sri Lankan
cassava mosaic virus infecting cassava in Vietnam. Plant Dis., 1-2 (12).
Wang, H.L., Wang, X.W., Cui, X.Y. and Liu, S.S. 2016. First report of Sri Lankan cassava mosaic virus
infecting cassava in Cambodia, Plant Dis., 100 (5), 1029.

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Research article
erd

Measurement of Postharvest Losses of Sesame (Sesamum
indicum L.) from Harvesting to Storage at Farm Level
HNIN THIDA NYO*
Department of Agriculture, Ministry of Agriculture, Livestock and Irrigation, Myanmar
Email: hninnyo@gmail.com

NYEIN NYEIN HTWE
Department of Agricultural Extension, Yezin Agricultural University, Myanmar

KYAW KYAW WIN
Yezin Agricultural University, Myanmar
Received 20 January 2020

Accepted 26 November 2021(*Corresponding Author)

Abstract During a crop’s transition from farm to consumer, much of the crop is lost due toseveral factors, including improper handling, inefficient processing facilities, andbiodegradation due to microorganisms and insects. This study was conducted with two
objectives: to measure the extent of postharvest losses of pre-monsoon and post-monsoon
sesame in field operations, i.e. in the harvesting, stacking, drying of stalks, threshing andwinnowing processes, and also to determine the quantity lost with the use of different typesof packaging materials used for storage. The research was conducted in Pwintphyu andPakokku Townships, Magway Region, Myanmar in July and December 2016. The
postharvest losses were measured at harvesting, stacking, stalk drying, threshing and thewinnowing stages on the farms. When comparing postharvest losses, losses were higher in
pre-monsoon sesame than post-monsoon sesame, except at the harvesting stage. The total
losses were found to be more in the pre-monsoon crop (21.34%) compared to the postmonsoon crop (11.88%). In regard to contribution to total losses, the storage loss accounted
for the major part (71.42%) of the total postharvest losses in pre-monsoon sesame. For theremaining losses, 22.35% occurred during stalks drying and threshing process, 3.47% whenstacking, with 1.45% of loss during harvest and 1.31% at winnowing. For post-monsoon
sesame, storage losses comprised 91.08% of total losses, followed by harvest loss (6.48%),stalks drying and threshing (1.68%), winnowing (0.59%) and stacking (0.17%). To assess thestorage losses resulting from the use of different packaging materials, two types of packaging
materials were tested. The harvested sesame seed was stored in pioneer superbags and woven
polypropylene bag for eight months at farmers’ houses. At the end of this period, weightlosses for the pre-monsoon sesame occurred in sesame stored in both superbags and woven
polypropylene bags. However, losses for the post-monsoon sesame occurred only the woven
polypropylene bag.
Keywords sesame, postharvest, losses, stacking, stalks drying, storage

INTRODUCTION
Reducing postharvest losses, especially in developing countries, could be a sustainable solution toincrease food availability, reduce pressure on natural resources, eliminate hunger and improve
farmers’ livelihoods (Hodges et al., 2011). During the crop transition from farm to consumer, it
undergoes several operations such as harvesting, threshing, cleaning, drying, storage, processing andtransportation. During these processes, crop is lost due to several factors. These include improper
handling, inefficient processing facilities, biodegradation due to microorganisms and insects, etc.
(Kumar and Kalita, 2017). Postharvest losses increase with an increase in area under crop and withincreased time of storage, while they decrease with improvements in the type of storage and methodof storage (Nag et al., 2000).
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Postharvest losses in less developed countries have been subject to a relatively small number ofstudies, and are mostly guesstimates derived from questionnaires rather than actual measurements.
However, this approach may be misleading because postharvest losses may be due to a variety offactors which varies from commodity to commodity, from season to season, and to the variety ofcircumstances under which commodities are grown, harvested, stored, processed and marketed(Tyler, 1982). Therefore, it is important not only to work with figures that are good estimates related
to a particular crop, time and place, but also to be aware that there will be variations at other times
and in other situations.
OBJECTIVESThe study was conducted with two objectives: to measure the extent of postharvest losses of premonsoon and post-monsoon sesame in field operations and to determine the quantity losses
associated with the use of different types of packaging materials used during storage.

METHODOLOGY
Field Experiment
The research was conducted in Pwintphyu and Pakokku Townships which are situated in the Magway
Region of Myanmar, in July 2016 and December 2016. The experiments were carried out in six
farmers’ fields in Pwintphyu Township for the pre-monsoon sesame crop and in six farmers’ fields
in Pakokku Township for the post-monsoon sesame. The plot size was 15m x 15m with two plots ineach farmer’s field. The variety of sesame grown in this study was black sesame (Samou Nei). The
postharvest losses were measured at the harvesting, stacking, stalks drying, threshing and thewinnowing stages on the farms.
Determination of Quantity Losses
Harvest losses: The sesame plants in the experimental plots were harvested according to normal
practice (using a sickle). Left over sesame pods on the harvested plots (both on the ground and on
unharvested standing plants) were thoroughly collected, cleaned, dried, weighed and stored
separately in paper bags. Losses for each plot are determined by the following equation (Appiah
et.al., 2011).
Harvesting losses = Weight of left over grains / Total weight of harvested grains × 100
Stacking losses: The harvested sesame stalks are placed on plastic nets. Stalks were separately piled
for each plot, and this method was used in the field stacking. After removing the stalks for drying,
all the grains remaining on plastic nets were collected, cleaned, dried and kept in paper bags for eachplot. If farmers used a threshing floor, the stalks were piled on the floor directly and the grains on
the floor were collected by the farmers. After the farmers’ had finished the stacking stage, the grains
remained on threshing floor were collected to determine losses (Appiah et.al., 2011).
Stacking losses = Weight of left over grains / Total weight of harvested grains × 100
Stalk drying and threshing losses: The ground was covered with canvas and the stalks were placed
upright and dried on these canvases. This method was used for in-field processing but not for thosedried on a threshing floor. After drying, stalks were moved and threshed on another canvas groundcover. The sesame grains for each plot that remained on all canvases were collected, cleaned, dried
and kept in paper bags. Where farmers did their drying on a threshing floor, the stalks were dried on
the floor directly and the grains on the floor were then collected by farmers. After they had completed
this process, the grains remaining on the threshing floor were collected to determine losses (Appiah
et.al., 2011).

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Drying and threshing losses = Weight of left over grains / Total weight of collected grains × 100
Winnowing losses: Two canvasses were spread on the floor, one for the winnowed grain and theother for the discarded chaff. Grains from the discarded chaff were collected, cleaned, dried andweighed the grain to determine losses (Appiah et.al., 2011).
Winnowing losses = Weight of grains collected from chaff / Total weight of collected grains × 100
Storage losses: Two different packaging materials were used to store the grain; woven
polypropylene bag and pioneer superbags, with storage in six farmers’ houses for a period of eightmonths. The quantity loss was determined at two-month intervals during this storage period. Quantity
losses is calculated using the formula (Appiah et.al., 2011).
Storage losses = (Initial weight of grains – Final weight of grains) / Initial weight of grains × 100
RESULTS AND DISCUSSION
Total Postharvest Losses for Pre-monsoon and Post-monsoon Sesame
When comparing postharvest losses, the losses were higher in pre-monsoon sesame than postmonsoon sesame except in regards to harvesting losses. The losses that occurred on farm before
storage were found to be at a maximum in the stalks drying and threshing stage (4.77%) followed bystacking losses (0.74%), harvest losses (0.31%) and winnowing losses (0.28%) for the pre-monsoon
crop. In post-monsoon sesame, the maximum quantity losses were found at the harvest stage (0.77%)
followed by the stalks drying and threshing process (0.2%), winnowing (0.07%) and stacking(0.02%). The total losses were greater in the pre-monsoon crop (21.34%) than the post-monsoon crop
(11.88%) (Table 1). The losses during harvesting and stacking showed a highly significant difference
between the two different crops. Also, stalks drying and threshing losses, winnowing losses and total
losses showed a significant difference, but storage losses were non-significant between the pre andpost-monsoon crops (Table 1).

Fig. 1 Proportion of postharvest losses of (a) pre-monsoon (b) post-monsoon sesame
In regard to total losses, storage loss comprised the major part with 71.42% of the total
postharvest losses for pre-monsoon sesame. The remaining losses consist of, 22.35% in stalks drying
and threshing process, 3.47% during stacking, 1.45% at harvest loss and 1.31% of during winnowing(Fig. 1 a). In post-monsoon sesame, storage losses represented 91.08% of total losses, followed byharvest loss at 6.48%, stalks drying and threshing loss with 1.68%, and winnowing loss at 0.59% of
total losses. The loss during the stacking process was only 0.17% of total losses (Fig. 1 b). The losses
during storage are a result of several factors, both biotic (insects, pests, rodents, fungi) and abiotic(temperature, humidity, rain) (Abedin et al., 2012). In India, the postharvest losses of sesame were
estimated at different stages across four different marketing channels. The total losses at farm level
were 46.75%, 37.58%, 35.85% and 51.84% respectively as part of the total losses in supply chain.
Harvest losses of sesame in four different marketing channels were 10.57%, 9.32%, 6.72% andⒸ ISERD

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16.54% of total losses. Collection losses were 4.88%, 4.66%, 5.88% and 9.93% of total losses; while
8.94%, 5.59%, 6.16% and 8.46% of total losses occurred at the threshing stage. Winnowing lossesof sesame, 8.13%, 7.45%, 6.72% and 4.78% were found in these four marketing channels, and aconsiderably high amount of losses occurred in drying/packaging with these being 8.94%, 7.45%,7%
and 8.09% respectively. The storage losses at the processing level in the four marketing channels
were 15.04%, 8.07%, 8.12% and 12.13% of total losses in the supply chain (Kumarasamy and Sekar,2014).
Table 1 Postharvest losses of pre-monsoon and post-monsoon sesame
Pre-monsoon

Post-monsoon

Percentage of losses

Percentage of losses

Activity
Harvest losses
Average
Range
Stacking losses
Average
Range
Stalks drying and threshing losses
Average
Range
Winnowing losses
Average
Range
Storage losses
Average
Range

0.31
0.77
0.11 to 0.71
0.58 to 1.17
t = -3.788, P = 0.004‫٭٭‬, df = 10
0.74
0.02
0.24 to 1.11
0.01 to 0.06
t = 4.195, P = 0.008‫٭٭‬, df = 5.021
4.77
0.20
1.91 to 10.09
0.04 to 0.37
t = 3.582, P = 0.016‫٭‬, df = 5.021
0.28
0.07
0.09 to 0.56
0.03 to 0.09
t = 3.148, P = 0.024‫٭‬, df = 5.225
15.24
10.82
7.63 to 21.93
3.19 to 23.43
t = 1.235, P = 0.245ns, df = 10

Total losses
Average
Range

21.34
11.18 to 29.99
t = 2.27, P = 0.047‫٭‬, df = 10
Note: **significant at 1% level; *significant at 5% level; ns = non-significant

11.88
4.42 to 24.41

Effects of Packaging Materials and Storage Durations on Total Weight of Stored Sesame
The harvested sesame seed/grain was dried, weighed and stored in two types of packaging materials,
pioneer superbags and woven polypropylene bag, for eight months at the farmers’ houses. Every twomonths during this period, samples were taken, cleaned and weighed. Pests were found in the stored
sesame, therefore, one of the main factors causing reduction in weight may be pest infestations during
the storage period. Insects alone can cause 36 to 43 percent storage loss (Bala et al., 1990).
Sufficiently airtight storage systems, although allowing insects and other aerobic organisms toinitially survive, oxygen concentrations are decreased below those permitting further insect
development (Chanda, 2013). In pre-monsoon sesame, the weight of stored seed/grain (500 g)
decreased significantly in two months (482.88 g) a trend that continued until four months (477.96 g),
and which then again significantly decreased by six months, with a loss of 464.97 g and on into theeighth month, when sesame weight decreased to 446 g. In post-monsoon sesame, the initial stored
weight (500 g) was not significantly reduced in the first two months (497.19 g), or for the periods
following (in four months (494.45 g), in six months (494.24 g), but it then decreased significantly inthe six to eight month period to 469.84 g. Therefore, it can be seen that storage losses of pre-monsoon
sesame (10.8%) was higher than post-monsoon sesame (6.03%) in the eight months of storage (Table
2).

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Table 2 Mean effects of packaging materials and durations on total weight of stored sesame
Stored weight (g)Treatment

Pre-monsoon sesame
Post-monsoon sesame
Packaging materials (P)Superbag484.01 a497.12 a
Woven polypropylene bag
464.72 b
485.17 b
LSD0.05
6.46
5.93
Storage duration (D)Initial storage
500.00 a
500.00 a
2 months
482.88 b
497.19 a
4 months
477.96 b
494.45 a
6 months
464.97 c494.24 a
8 months
446.00 d
469.84 b
LSD0.05
10.22
9.38
Pr > FP
0.00000.0002D
0.00000.0000
P×D
0.00030.0000CV (%)
2.62
2.32
Note: In each column, means with the same letter are not significantly different at 5 % level

Fig. 2 Combination effect of packaging materials Fig. 3 Combination effect of packaging
materials and storage duration on
and storage durations on the total weight of
total weight of post-monsoon
stored pre-monsoon sesame
sesame stored pre-monsoon sesame
The combination effect of packaging materials and storage durations on the total weight ofstored pre-monsoon sesame is shown in Fig. 2. In the first two months of storage, the weight ofseed/grain stored in the superbags did not fall, whereas seed stored in the woven polypropylene bags
was significantly reduced. After four months storage, the weight of sesame stored in the superbags
was significantly different to the weight at initial storage. The weight of stored sesame in the woven
polypropylene bags was also not significantly different than the weight of stored seed/grain weight
for two months, however, it was significantly different to the weight of sesame after six months
storage. From six months to eight months storage, the weight of sesame stored in superbags did not
significantly decrease, while the weight of sesame stored in woven polypropylene bag had decreased
significantly by eight months from the weight at six months (Fig. 2). By the end of the storage period
measured (eight months), the weight loss of pre-monsoon sesame stored in superbags was 6.36%,
while for sesame in woven polypropylene bag there was a loss of 15.24%.
The combination effect of packaging materials and storage durations on the total weight ofstored post-monsoon sesame is shown in Fig. 3. The weight of stored sesame in superbags did not
significantly decrease over eight months storage, while the weight of sesame stored in woven
polypropylene bag maintained similar weights for the first six months and then decreased
significantly at eight months storage with a 10.82% weight loss (Fig. 3). As the packaging materials
are airtight, insects and aerobic microorganisms creates an inhibitory environment over time byⒸ ISERD

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increasing carbon dioxide concentration and decreasing oxygen due to their respiratory metabolism(Adler et al., 2000). If the weight loss of pre-monsoon and post-monsoon sesame during storage iscompared, losses of pre-monsoon sesame occurred in both the superbags and woven polypropylenebags, however, losses of the post-monsoon sesame were found only in the woven polypropylene bags.
This might be due to the initial seed moisture content at time of storage, as the initial moisture content
of pre-monsoon sesame was higher than that of post-monsoon sesame. When using airtight storage
methods, it is important to have a very well dried product at the beginning of the storage period(Hayma, 2003). Also Ben et al. (2009) reported that one of the main challenges of using hermetic
bags is that the grain to be stored should be thoroughly dried to avoid mold and the rotting of grains.
CONCLUSION
The range of the total postharvest losses of pre-monsoon sesame and post-monsoon sesame were(11.18% to 29.99%) and (4.42% to 24.41%). Storage losses were the highest contributor to losses
among all the postharvest processes for sesame in both seasons. Storage losses can be mitigated byuse of efficient storage technology, and upgrading both infrastructure and storage practices. When
comparing postharvest losses, the losses were higher in pre-monsoon sesame than for post-monsoon
sesame, except for harvest losses. Although the losses in harvesting, stacking, stalk drying andthreshing, winnowing and total post-harvest losses were significantly different, the difference in theamount lost during the storage stage for pre and post-monsoon crops were non-significant. The
differences of losses that occurred during stacking, stalk drying and threshing and winnowing were
due to the different handling practices of farmers. Therefore, if farmers had a good threshing floor,
post-harvest losses would be reduced and a better quality product produced. In regard to the
packaging materials, a significant difference of total weight of stored sesame that was lost can beseen for the different packaging materials surveyed. Storage in superbags resulted in far less sesame
weight loss than storage in woven polypropylene bags.
ACKNOWLEDGEMENTS
This study was financially supported by Technical Cooperation Program of Japan International
Cooperation Agency (JICA-TCP).
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Irvine, K. and T. Koottatep, 2010. Natural wetlands treatment of sewage discharges from Phnom Penh,
Cambodia: Successes and future challenges. Asian J. Water Environ. Pollut., 7, 1-2.

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IJERD – International Journal of Environmental and Rural Development

erdInternational Society ofEnvironmental and Rural Development

Philosophy of ISERD:
Recently, in developing countries, subsistence agriculture is being converted to export-oriented mono-culture,and the amounts of agricultural chemicals applied to the farmland are increasing every year. The appliedchemicals in farmland cause serious environmental problems downstream such as eutrophication, unusual
growth of aquatic plants, decrease in dissolved oxygen and accumulation of bottom mud in water resources.
Also, there seem to be many cases in which people apply agricultural chemicals without understanding its
impact to health and food safety. Therefore, it is necessary to promote and enhance understanding ofsustainable rural development among local stakeholders including farmers.
Sustainable rural development aims to meet human needs while preserving the natural environment. As
it should cover not only social and economic development but also natural environment conservation, no
single organization can achieve sufficiently the aspirations of sustainable rural development. Collaboration
among international, governmental and non-governmental organizations, together with the academe andscientific sector, is indispensable.
The knowledge and intelligence accumulated in universities and research institutions are also expected
to make the programs facilitated by the international, governmental and non-governmental organizations
more adequately implemented and meaningful to societal development. However, these cases especiallythose implemented locally have been scattered without having been summarized well or recorded in annals
academic or scientific societies.
So, the International Society of Environmental and Rural Development founded in 2010, aims to discussand develop suitable and effective processes or strategies on sustainable rural development focusing on
agricultural and environmental aspects in developing countries. The ultimate goals of the society are tocontribute to sustainable rural development through social and economic development in harmony with thenatural environment, and to support the potential or capacity building of local institutions and stakeholders in
the rural area with academic background.
Purposes of ISERD:
The primary purposes of ISERD are to contribute to sustainable rural development through social andeconomic development in harmony with the natural environment and to support the potential or capacity
building of local institutions and stakeholders in the rural area with academic background.
In order to enhance the realization of the primary purposes of ISERD, the secondary purposes are;- to facilitate interaction among international, governmental, non-governmental organizations and local
communities,- to hold conferences or symposia on environmental and rural development,- to edit the International Journal of Environmental and Rural Development,- to confer some awards based on scientific achievement, research paper or poster presentation, and- to encourage and develop local awareness concerning sustainable rural development.
Membership:
There shall be two categories of membership.
(a) Individual(b) Organizational
An application for membership of ISERD shall be submitted to the secretariat of ISERD, where is located in
the Research Center at Institute of Environmental Rehabilitation and Conservation (Japan) by writing or byother appropriate means.
Also, every presenter who attends the International Conference on Environmental and Rural
Development (ICERD) is registered as an Individual Member of ISERD.

IJERD – International Journal of Environmental and Rural Development

Council of ISERD:
The affairs of ISERD shall be governed and managed by the ISERD Council. The councilors are as follows.
President
Prof. Dr. Mario T. Tabucanon, United Nations University, Institute for the Advanced Study of
Sustainability, Japan
Deputy Presidents
Prof. Dr. Bunthan Ngo, Royal University of Agriculture, Cambodia
Prof. Dr. Anan Polthanee, Khon Kaen University, Thailand
Prof. Dr. Eiji Yamaji, The University of Tokyo, Japan /Institute of Environmental Rehabilitation and Conservation, Japan
Executive Secretary / Editor-in-Chief of IJERD
Prof. Dr. Machito Mihara, Tokyo University of Agriculture, Japan /Institute of Environmental Rehabilitation and Conservation, Japan
Managing Editors
Dr. Narong Touch, Tokyo University of Agriculture, Japan
Dr. Shinobu Terauchi, Institute of Environmental Rehabilitation and Conservation, Japan
Dr. Jeeranuch Sakkhamduang, Institute of Environmental Rehabilitation and Conservation /Association of Environmental and Rural Development, Thailand
Treasurer
Dr. Lalita Siriwattananon, Rajamangala University of Technology Thanyaburi, Thailand
Regional Vice Presidents
Dr. Shafiqullah Rahmani, Ghanzni University, Ministry of Higher Education, Afghanistan
Prof. Dr. Barry N. Noller, The University of Queensland, Australia
Prof. Dr. Sinisa Berjan, Embassy of Bosnia and Herzegovina in Japan /University of East Sarajevo, Bosnia and Herzegovina
Dr. Buntong Borarin, Royal University of Agriculture, Cambodia
Dr. Ping Li, Institute of Grassland Research, China
Prof. Dr. Dieter Trautz, University of Applied Sciences, Germany
Dr. Sri Wahyuni, Islamic University of Riau, Indonesia
Prof. Dr. Hiromu Okazawa, Tokyo University of Agriculture, Japan
Prof. Dr. Nang Hseng Hom, Yezin Agricultural University, Myanmar
Prof. Dr. Junaid Alam Memon, Institute of Business Administration Karachi, Pakistan
Prof. Dr. Regucivilla A. Pobar, Bohol Island State University, Philippines
Dr. Chuleemas Boonthai Iwai, Khon Kaen University, Thailand
Dr. David R. Ader, University of Tennessee, USA
Dr. Nguyen Khoi Nghia, Cantho University, Vietnam
ISERD Secretariat:
Research Center, Institute of Environmental Rehabilitation and Conservation (ERECON)
2987-1 Onoji Machida-Shi, Tokyo 195-0064, Japan
Tel/Fax: +81-42736-8972
E-mail: iserd.secretariat@gmail.com
Webpage: www.iserd.net
Collaborated with

Association of Environmental and Rural Development (AERD)
93/64 Moo.3, Sinsab Village 2, Bungyeetho Sub-district, Thanyaburi District,Pathum Thani 12130, Thailand
Tel/Fax: +66-2957-8064
E-mail: iserd.secretariat@gmail.com
Webpage: www.iserd.net

Institute for the Advanced Studyof Sustainability
All articles and reports published in this journal were accepted through a peer-review process. However,most articles and reports published in this journal were presented at the International Conference on
Environmental and Rural Development that was co-organized by United Nations University, Institute for
the Advanced Study of Sustainability.

IJERD – Environmental and Rural Development

Vol. 12 No. 2

December 2021