ISSN 2185-159X

erd

International Journal ofEnvironmental and Rural Development

Volume 14 Number 1

June 2023

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. Santa Pandit, Institute of Environmental Rehabilitation and Conservation, Japan
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:
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
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Publisher of International Journal of Environmental and Rural Development:
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Tel/Fax: +81-42736-8972
E-mail: hq-erecon@nifty.com
Webpage: www.erecon.jp

IJERD – International Journal of Environmental and Rural Development (2023) 14-1

Contents
Simple Weir Types and Their Prospects for Small-Scale Irrigation Development in Northern Zambia
Alex Lushikanda Kabwe, Masahiro Hyodo, Hidehiko Ogata,
Yoshihiro Sagawa, Yoshinao Adachi and Masayuki Ishii

1

Development of a Simple-Concept Water Allocation Model at the Farm-Block-Level for
Efficient Water Management
Naohisa Nakashima and Tetsuro Fukuda

9Clarification of Water Use under the Complicated Irrigation System and its Modelingin the Boribo-Bamnak River Basin, Cambodia
Heng Salpisak, Tadao Yamamoto and Takashi Inoue

17

Improvements in Preservation Properties of Homemade-Style Pickled Cucumber in Cambodia
Sokly Sorm, Shuki Muramatsu, Masataka Uchino,
Yoshiki Muramatsu, Daiki Oka, Narong Touch, Yuri Tanioka,
Takahiko Nakamura, Toru Nakajima, Motoe Sekido,
Shotaro Kawakami, Chim Chay, Mari Arimitsu andMachito Mihara

25

Reuse of Unavailable Phosphate in Soils Using Solar Cell-Powered Electrokinetic Treatment
Narong Touch and Takahiko Nakamura

32

Impact of a Drip Irrigation System on Planning and Management of Water Delivery
in a Large-Scale Irrigation Scheme in Morocco
Dayyabu Muhammad Zaharaddeen, Katsuyuki Shimizu,
Yuri Yamazaki, Vinay Nangia, Anas Mansouri,
Mohamed Belaarabi and Lahcen Ousstous38

Conditions of Bio-Slurry Application in Crop Production in Kampong Cham Province, Cambodia
Chan Makara Mean, Lyhour Hin, Sophoanrith Ro, Nareth Nut,
Nam Sok, Lytour Lor and Bart Frederiks

45

Determination of Histamine Level and Its Correlation with Viable Bacterial Count in
Cambodian Fermented Fish
Lengheang Choeng, Chanthol Peng, Leangey Set andSeyha Doeurn

52

Evaluation of Soil Erosion Risk from Weathering Effects on K Factor of RUSLE in
Cobija, Bolivian Amazonia
Juan Uego Perez and Machito Mihara

59

Assessment of Antibacterial Activity of Lactic Acid Bacteria Isolated from Fermented Foods against
Escherichia coli O157:H7 and Proteus penneri and Their Potential as Starter Cultures
Sineth Chev, Siveng Meng, Borarin Buntong,
Chinda Chhe and Rithy Chrun

65

Nitrogen Removal from Mining Dewatering and the Fate of Water Release to a River
Barry Noller

71

Development of Erosion Protection Zones in the Catchment of the Kalimanci Reservoir,
North Macedonia
Ivan Minchev, Ivan Blinkov, Aleksandar Trendafilov
and Bozhin Trendafilov

77

On-farm Effects of Subsurface Drainage System on Chinese Cabbage (Brassica pekinensis L. Rupr.)
Production in Rainy Season at Svay Rieng Province, Cambodia
Tithya Kang, Saravuth Tum, Vanchey Ros, Nimul Chun,
Chhun Hong, Borarin Buntong, Kimchhin Sok,
Siranet Roeurn and Sophoanrith Ro

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IJERD – International Journal of Environmental and Rural Development (2023) 14-1

Prediction of Land Use Change through the Cellular Automata-Markov Model:
A Case Study of the Upper Sangkae River Basin in Cambodia
Vanna Chey, Tadao Yamamoto and Takashi Inoue

91

Educational Material Research on the Color of Crayfish for Conversion to Edible Resources
Saki Higuchi, Honami Ono, Hiroaki Honda, Sarvesh Maskey,
Akira Kurosawa, Toshihiro Suzuki, Nobuyuki Takahashi,
Hiromu Okazawa and Kouji Takeda

98

Evaluating Water Purification Capacity of Patinopecten yessoensis Shells Inoculated with
Effective Microorganisms
Kosei Moroishi and Machito Mihara

106

Impact Assessment of New Dam Construction in Nam Ngum Watershed on
Electric Generation at Num Ngum 1 Dam
Koshi Yoshida, Keigo Noda, Task Kato and
Keoduangchai Keokhamphui

112

Verifying Optimum Flying Conditions for UAV Photogrammetry in Assessing Hydro-structural
Facilities
Sarvesh Maskey, Hiyori Iseki, Kiseki Kurashina,
Ke Zhang and Hiromu Okazawa

119

Information Transfer among Mango Contractors: Sources, Channels, and Priorities
Dia Noelle Velasco, Katsumori Hatanaka, Nina Shimoguchi
and Ramadhona Saville

126

Effect of Bio-slurry and Chemical Fertilizer on Soil Enzyme Activity
Moeurb Ang, Hong Cheang, Dyna Theng, Nareth Nut,
Lyhour Hin, Lytour Lor, Kasuni H. H. Gamage andGanga M. Hettiarachchi

134

Household Income Diversity of Small-scale Cassava Producers in Vietnam
Nien Chau Nguyen, Tamon Baba, Hisako Nomura andKasumi Ito

139

The Effects of Green Manure on Sustainable Agriculture Soil Conservation
under Open Field Conditions
Mala Suon, Sopheak Tith, Thangrak Veu, Pisidh Voe,
Socheat Ngy, Sothea Hill and Chhouk Chheang

147

Habitat Evaluation of Agricultural Waterways where Environmental Improvement Was Practiced
for Recreation
Masayuki Nitta, Mitsuru Ohira, Muneyuki Aoki and
Masahiro Nakajima

153

Temperature Sensitivity (Q10) of Organic Carbon in Red-yellow Soils and Its Conservation Strategies
Keiji Arostegui and Machito Mihara

163

National versus Local Climatic Variability and Implications for Communities in Protected Areas:
The Case of Lake Malawi National Park
Dickson M. Mazibuko, Lameck Fiwa, Maskey Sarvesh and
Hiromu Okazawa

170

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IJERD – International Journal of Environmental and Rural Development (2023) 14-1

Research article
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Simple Weir Types and Their Prospects for Small-Scale
Irrigation Development in Northern Zambia
ALEX LUSHIKANDA KABWE*
United Graduate School of Agricultural Sciences, Tottori University, Tottori, Japan
Email: d21a3003k@edu.tottori-u.ac.jp

MASAHIRO HYODO
Faculty of Agriculture, Tottori University, Tottori, JapanHIDEHIKO OGATA
United Graduate School of Agricultural Sciences, Tottori University, Tottori, JapanYOSHIHIRO SAGAWA
Sanyu Consultants INC, Tokyo, JapanYOSHINAO ADACHI
Sanyu Consultants INC, Tokyo, Japan

MASAYUKI ISHII
Academic Assembly, Shimane University, Shimane, Japan
Receive 19 January 2023

Accepted 8 May 2023(*Corresponding Author)

Abstract In Zambia, simple weir technology is increasingly gaining popularity as analternative method for river water diversion among rural small-scale farmers. The now widelyadopted technology was first introduced in the Northern Province region of Zambia to promotesmall-scale irrigation in local communities. These small-scale facilities are constructed acrossthe width of the river using forest materials such as poles, twigs, thatching grass, and tree bark
strips. These types of irrigation structures produce an adequate head of water enough for thediversion of water from the river into a canal conveying water for irrigation. However, simple
weirs that farmers have been constructing with forest materials are observed to experiencechallenges such as breaching, and often break down and collapse within six to seven months.
Therefore, the objective of this research was to investigate the characteristics of simple weirs
constructed by farmers on a self-help basis for community-based small-scale irrigation
schemes in the Luapula, Muchinga, and Northern Province regions of Zambia. We observed
the simple weirs constructed before the start of irrigation season (May) and simple weirs built
in the operational phase (May-November) and we characterized simple weirs as 1) single-line
weir, 2) inclined weir, 3) trigonal weir, and 4) double-line weir. The results show an
improvement in the irrigated area by small-scale farmers since the introduction of simple weirs.
The findings revealed that challenges that were often encountered on the simple weirs were
not solely caused by river flooding, but also by compromises in the construction,
inconsistencies in maintenance, and lack of measures to sustain and protect the weirs. It wasalso observed that simple weirs in operation were regularly maintained and repaired during
the irrigation season. Despite the challenges farmers were experiencing with the simple weirs,
farmers persistently conducted maintenance activities, replaced worn-out poles and thatchinggrass and de-silted before the start of the irrigation season.
Keywords simple weir types, small-scale irrigation, river water diversion, arid land

INTRODUCTIONⒸ ISERD

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Most of the smallholder farmers live in rural areas in sub-Saharan Africa (SSA) and constitute about
70% of the continent’s population in the bracket of poor people (Sakaki and Koga, 2013). This groupof farmers is viable, but marginalized and vulnerable since they entirely depend on seasonal rainfall
for their agricultural activities. Rainfed farming practiced by small-scale rural farmers produces a
low agricultural yield that is frequently influenced by weather-induced changes. The problems
associated with rainy season farming are numerous and not limited to 1) farming within 3-4 months
in which to produce enough food crops to last up to the following harvest and 2) during the dry
season, there is a prevalent shortage of fresh and nutritious crops. Based on the mentioned challenges,
smallholder irrigation is promoted in SSA as a strategic intervention to enhance agricultural
production, productivity, and farm household incomes (Osewe et al., 2020). To acceleratesmallholder irrigation development in rural areas in SSA, low-cost irrigation technologies like river
diversion simple weirs have been widely promoted for gravity irrigation. One of the gravity irrigation
methods that has become popular in rural areas in SSA is river water diversion. The Southern Africa
region is cited with a potential irrigable area of more than 3 million hectares (Xie et al., 2021) forriver water irrigation schemes.
Simple weirs have been used in establishing community irrigation schemes in rural areas inSouthern African countries such as Malawi, Mozambique, and Zambia (Lautze et al., 2017). In thenorthern region provinces of Zambia, small-scale local farmers construct simple weirs on the rivers
in the dry season (May-November). The simple weir irrigation technology has increasingly become
one of the irrigation methods among smallholder irrigation farmers in the rural areas in Zambia(Luapula, Muchinga, and Northern provinces) (Colenbrander et al., 2012). This is because simple
weirs are community demand-driven technologies, relatively cost-effective, and adaptable to rural
environments with the potential for gravity irrigation (suitable topography and surface flowing
rivers). In Zambia, surface water from rivers and springs are the primary sources of water accessedby farmers for small-scale irrigation. Farmers have been accessing irrigation water using manuallyoperated technologies like watering cans, buckets, and 20-25ltr plastic containers. However, this typeof irrigation has less impact on the irrigated area expanded and irrigation production. Simple weirs
have been introduced to develop small-scale irrigation in Zambia. The simple weir irrigation
technology has attracted the attention of the majority of small-scale farmers in the rural area.
However, most of the simple weirs constructed by farmers themselves do not continuefunctioning throughout the irrigation season as many of them are either breached, partially destroyed,or washed away and needed to be either repaired, rehabilitated, or reconstructed after the annual
floods. Farmers claim that, based on their experiences with simple weirs, the contributing factors to
the challenges experienced include high peak discharges, weakness of structures, small canal intake,and excessive accumulation of sediment particles upstream of the weirs. Since the introduction of
simple weirs as an alternative method of irrigation in the northern region of Zambia a decade ago, todate little information has been disseminated on the performance and challenges of these types ofsmall-scale irrigation facilities.
OBJECTIVE
To explore the prospects of the simple river water diversion weirs constructed by local communities
for small-scale irrigation in the northern region of Zambia by 1) characterizing the simple weirs
structures, construction, and materials 2) studying the challenges of simple weirs, 3) assessing theeffectiveness of simple weir maintenance during and before the irrigation seasons, and 4) assess theimpact of the simple weir on small-scale irrigation development.
METHODOLOGY
Study Area and Data Collection
The study was conducted in Zambia’s northern provinces shown in Fig.1. Geographically, Zambia
lies in the tropics at an elevation of 1,200m above sea level with a sub-tropical climate due to itsⒸ ISERD

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latitude and high-altitude location. The climate in Zambia is characterized by three distinctive
seasons all year, dry and hot (August to November), dry and cool (May to August), and a wet rainyseason (December to April). Zambia is divided into three agroecological zones with Zone III,
covering the northern region of Zambia, receiving the highest amount of rainfall between 1,000 mm
to 1,500 mm per year (Brigadier et al., 2015). The rainy season increases both in intensity andduration from the southern region to the northern region. In Zambia’s northern region, surface
flowing water is sufficient to support dry-season irrigation.

Fig. 1 Location of Luapula, Muchinga, and Northern Provinces in Zambia
The collection of primary data was conducted through discussions and interviews with
agricultural extension officers, farmer groups, and simple weir users. The study reviewed theliterature on small-scale irrigation development, focusing on low-cost irrigation technologies in rural
areas in Zambia. The primary data used in this study was collected from 55 sites in three provinces.
The study area was clustered into three provinces and 55 simple weirs were randomly selected from
Luapula province 22 sites (72 participants), Muchinga province 15 sites (31 participants), andNorthern province 18 sites (69 participants). 172 simple weir users participated in the discussion in
Table 1. The data was collected between August 20th and November 30th, 2022.
Table 1 Location of simple weir sites, number of simple weirs, and users who participated
Province

Number of simple weirs andsites

Number of simple weir users
who participated

LuapulaMuchinga
Northern
Total

22
15
18
55

72
31
69
172

Simple Weirs Small-Scale Irrigated Agriculture
During the seven-month dry season, small-scale farmers resort to irrigation to supplement rain-fed
agricultural production. Vegetable growing is the common system of agriculture between May andDecember in rural areas in Zambia. This type of agriculture during the period is the principal
livelihood for the majority of the people in the region. Crops that are produced using simple weirirrigation include cabbage, tomatoes, onions, watermelons, carrots, and Irish potatoes. These crops
are generally irrigated and widely cultivated on sites supplied with river water diverted by simple
weirs.
RESULTS AND DISCUSSIONSⒸ ISERD

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Characteristics of the Simple Weir Types
In Zambia, simple river water diversion structures are usually constructed of simple materials ofpoles, thatch grass, and clay soil bunds (Food and Agriculture Organization, 2014). Although simple
weirs are generally constructed for one irrigation season, they are viable facilities. Farmers areusually advised to dismantle the weirs as a coping strategy to flood damage and store material to
avoid depletion of forest for the reconstruction in the following irrigation season. Figure 2 shows
four simple weir types that are conventionally used for irrigation and are part of improved methods
for small-scale irrigation (Bekele et al., 2006).

(1) Single-line weir: It
consists of a single
line of wooded poles
constructed across thewidth of a river. Thisweir type is suitable
for rivers which arewider and shallower.
It is recommended on
hard riverbed
foundations.

(2) Inclined weir: Thisweir has one mainpole placed
horizontally across thewidth of a river andsupported byriverbanks ofrelatively the sameheight. It is
recommended onrivers which areslightly deeper andnarrow with stony(3) Trigonal weir: The
weir consists ofseveral tripod stands
constructed withround poles. The
tripod stands arealigned across thewidth of the river toform a weir. This weirtype is suitable on
rocky riverbeds.

(4) Double-line weir:This weir type has twoparallel lines of poles
constructed across theriver, spaced at 0.20.5 m. The space
between the parallellines is filled with clay
soil to minimise water
loss by seepage.

Fig. 2 Characterization of simple weir types and constructions methods:(1) single-line weir, (2) inclined weir, (3) trigonal weir, (4) double-line weirSingle-Line Weir
Single-line simple weirs are constructed using round forest poles (0.8-0.1 m diameter) and adultwrist-size bundles of thatch grass (Fig. 2-1). A single row of poles is embedded vertically into theriverbed across the width of a river. According to available data, the intra-spacing of poles ranges
between 0.5 to 1 meter from each other across the river. The wooden poles are connected by purlins
tied across using tree bark strips. The weir is reinforced at the base of the pole line by ramming clay
soil. Thatching grass is used to reduce water seeping through the weir. The weir causes the waterlevel to rise upstream and diverted into the canal off-taking on its upstream side.
Inclined Weir
The inclined weir is constructed where the narrow and straight river section has a good formation ofriverbanks on both sides and relatively the same height. One pole (0.2-0.3 m diameter) is used as across member where slanted poles (about 0.1 m in diameter) are supported (Fig. 2-2). The crossmember pole is placed horizontally across the river to the preferred flood height and anchored by theriverbanks. The slanted fixed poles are approximately inclined at 600 angles to the river flow. The
slated poles are connected using the purlins and covered with thatching grass to minimize water loss
downstream. Clay soil is compacted at the base to provide anchorage and reduce seepage. The waterrises above the historical flood level and is diverted into the canal conveying irrigation water.
Trigonal WeirⒸ ISERD

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This type of weir is recommended on riverbeds with stones or hard rock foundations. A single tripod
is constructed using 3 by 2 m (approximately) long poles and tree bark strips. The three poles areconnected at the top of one end. The front with two long poles covered with thatch grass faces
upstream, the other pole shunts downstream to provide stability. Several tripods are constructed andlater aligned in a single line across the river to form a weir (Fig. 2-3). Water is prevented from being
lost through seepage using the thatching grass. Depending on the width of a river two or more tripods
can be erected across. During the rainy season, the tripods are removed from the river channel andstored for use in the following irrigation period.
Double-Line Weir
The double-line weir has two parallel rows of round poles placed vertically into the riverbed (Fig. 24). The space between the two parallel rows of poles across the river is approximately 0.2 to 0.5
meters (Food and Agriculture Organization (FAO), 2015). The space between the two rows of polesis filled with clay soil to reduce water loss through leakage. The double-line weir impounds flowing
river water in a small earth pond formed upstream. Water is diverted from the ponds and supplied
downstream to the fields. The double-line weir can also be used as a fishpond. Apart from divertingwater for irrigation, the double-line weir can also be used as a crossing point.
Analysis of Reasons for Adoption of Simple Weirs for Irrigation
Information and farmers’ experiences in Figs. 3 and 4, were collected from different sites between
2014 and 2017. Figure 3 summarises the reasons farmers expressed about the simple weir as atechnology for irrigation. The findings of this study included exploring the motivation and interestof the local farmers in simple weir irrigation. The results show multiple reasons presented in Fig. 3
for using simple weirs for small-scale irrigation development. The responses presented are based on
the information collected from the farmers. It was found that about 26% of the population of smallscale farmers using simple weirs stated easy construction, and 19% mentioned the use of local
materials of forest products like poles and thatch grass in the construction of simple weirs as amotivating factor. 15% of simple weir users’ interest in simple weir was about enhancing household
livelihood while 14% of the farmers stated agricultural activities throughout the year, a vital reason(Bjornlund et al., 2019). About 13% of the farmers expected improvement in the area irrigated whileother farmers stated a reduction in manual labor required to lift water for irrigation from the source
to the crops. The reasons given by farmers for adopting simple weirs for irrigation purposes
substantially varied. These responses were noted during the site visits and interviews. The responses
farmers advanced according to (Colenbrander et al., 2012) represent the solutions seen by farmers as
most promising for developing low-cost irrigation systems in rural areas. According to the responsesof the farmers interviewed, easy construction, livelihood diversification, and increasing land underirrigation have been the basis for adopting simple weirs in the northern region of Zambia.

Fig. 3 Farmers' responses on the adoption of simple weirsⒸ ISERD

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Analysis of the Attributing Factors to Stagnant Development of Small-Scale Irrigation and
Low Adoption of Simple Weirs in the Northern Region
Figure 4 summarises the responses of the farmers from the study sites with simple weirs used for
irrigation in the northern region province of Zambia. The responses varied with 18% of the farmers
stating weir breaching challenges, 17% of the farmers expressing weir leakages as their concern, and
27% of the farmers mentioning high labour demand for repair and maintenance as challenges(Dakpalah et al., 2018). While 5% of the farmers stated deforestation as more poles are required tobe harvested for construction from the forest. Fig. 4 Farmers' responses collected from simple weirsites.

Fig. 4 Farmers' responses collected from simple weir sites
Analysis of the Maintenance Activities of Simple Weirs by Farmers
Figure 5 shows the flood damage control strategy farmers practice at the end of the irrigation period(December). Based on the observation during the site visits, it was observed that about 7% of thetotal number of weirs were deliberately dismantled, 47% partially dismantled and 50% of the total
number of the weirs remained un-dismantled. Though dismantling of weirs during the off-season isrecommended as a flood damage control measure, it is not implemented on all simple weirs because
weirs are sometimes used to divert river water to supplement rainfall during dry spells.

Fig. 5 Maintenance activities carried out on simple weirs by farmers
Simple Weir Impacts in Promoting Small-Scale Irrigation in Northern Region
Figure 6 refers to the period between 2014-2016, in which 876 hectares were brought under irrigation
using simple weirs. In 2014, 2015, and 2016, the land expanded for irrigation in hectares was 292,
214.6, and 369.4 respectively. In 2016, there was a significant increase in the area brought underirrigation largely due to farmers’ increasing interest in simple weirs and farmer-to-farmer knowledge
sharing and skill transfer (Japan International Cooperation Agency (JICA), 2017).
Ⓒ ISERD

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Fig. 6 Number of hectares irrigated by diverting river waterusing the corresponding number of simple weirs
CONCLUSION
This study focused on the simple weirs that have been introduced in the northern region of Zambia.
Simple weirs characterized by four types single, line, double line, inclined, and trigonal weirs are
increasingly becoming popular in small-scale irrigation development in the northern region rural
areas in Zambia. The use of simple weirs to divert river water for irrigation is relatively ‘’new’’ inZambia. The use of locally available materials of forest materials and the need to supplement
household income and food requirements has motivated the majority of small-scale farmers in thenorthern region to engage in dry season irrigation (May-December). Despite the promising results inenhancing irrigation water accessibility, there are still some structural challenges with simple weirs.
This study suggests the need for improvement in the construction and selection of construction
materials for simple weirs.
ACKNOWLEDGEMENTS
The authors would like to thank the Ministry of Agriculture staff in Luapula, Muchinga, and Northern
provinces of Zambia for their contributions to this study. Furthermore, we would like to thank theInternational Platform for Dryland Research and Education of Tottori University and are also gratefulto Japan International Cooperation Agency for its support.
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smallholder irrigation in the Republic of Zambia. JICA, Tokyo, Japan.
Lautze, J., Phiri, Z., Smakhtin, V. and Saruchera, D. 2017. The Zambezi river basin, Water and sustainable
development (1st ed), ISBN 9781315282053, London, UK.
Osewe, M., Liu, A. and Njagi, T. 2020. Farmer-led irrigation and its impacts on smallholder farmers’ crop
income, Evidence from southern Tanzania. International Journal of Environmental Research and Public
Health, 17 (5), 1512, Retrieved from DOI https://doi.org/10.3390/ijerph17051512
Sakaki, M. and Koga, K. 2013. An effective approach to sustainable small-scale irrigation developments in
Sub-Saharan Africa. Paddy and Water Environment, 11, 1–14, Retrieved from DOI https://doi.org/10.1007/
s10333-011-0287-x
Xie, H., You, L., Dile, Y.T., Worqlul, A.W., Bizimana, J.-C., Srinivasan, R., Richardson, J.W., Gerik, T. and
Clark, N. 2021. Mapping development potential of dry-season small-scale irrigation in Sub-SaharanAfrican countries under joint biophysical and economic constraints, An agent-based modelling approachwith an application to Ethiopia. Agricultural Systems, 186, 102987, Retrieved from DOI https://doi.org/10.1016/j.agsy.2020.102987Ⓒ ISERD

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Research article
erd

Development of a Simple-Concept Water Allocation Modelat the Farm-Block-Level for Efficient Water Management
NAOHISA NAKASHIMA*
Department of Agro-environmental Science,
Obihiro University of Agriculture and Veterinary Medicine, Obihiro, Japan
Email: nnakashima@obihiro.ac.jp

TETSURO FUKUDA
Hino-sato, Munakata City, Fukuoka Prefecture, Japan
Received 4 February 2023

Accepted 8 May 2023(*Corresponding Author)

Abstract It is crucial to establish appropriate water management in agriculture. Due tofinancial difficulties, it is also necessary for farmers to work together with government
agencies in water management. Existing water allocation models, however, require much
effort to collect data. They are also black boxes difficult for farmers to understand, which may
discourage farmers from participating in irrigation planning. In this study, we attempted toconstruct a farm-block-level water balance model with a simple tank model concept and easilycollectible data. The model consists of two parts that reproduce the water distribution processfrom the farm block intake to each field (Canal Tank Model; CTM) and the water balance
process in the paddy field (Paddy Tank Model; PTM), respectively. The model coefficientswere identified using data from 2002 to 2003, and the model validity was evaluated using datafrom 2004 and 2005. The CTM coefficients were identified for 2002 and 2003 because of thedifferent land use patterns. The CTM runoff coefficients and hole heights were changed ondays when the farmers were considered to have operated diversion ratios significantly. The
PTM coefficients were identified using the SDFP method and trial and error referring to thegroundwater level. However, the PTM seepage holes were fixed to the corresponding values
that the vertical seepage was approximately 5 mm/d based on the on-site survey. As a result,despite the arbitrary water manipulation by farmers, the same CTM coefficients for 2002,
2003, 2004 and 2005, when the land use pattern was similar, were able to reproduce the water
allocation well. This water allocation model can be used to estimate the optimal delivery water
management rate and to quantitatively evaluate the excess water withdrawal resulting from thelabor reduction in water management.
Keywords water balance model, excess water withdrawal, participation irrigation
management (PIM), prediction of water demand

INTRODUCTION
More than 90% of the total irrigation water is used for rice production (Khepar et al., 2000). However,the Organization for Economic Cooperation and Development (OECD) has addressed the idea that
irrigation water is consumed unproductively and inefficiently (Fujimoto and Tomosho, 2003). On
the other hand, recently, participation in irrigation management (PIM) is under great practice aroundthe world. This method is for all farmers to get enough water, which is difficult to achieve with a
top-down system, because of the financial pressure to maintain the irrigation system and the difficultyof taking care of fringe in the system by only the government (Saito, 2010). Yamamoto (2005)
recommended that water use efficiency during abnormal dry spells should be improved by promoting
PIM in paddy field irrigation in the Asian monsoon region. Irrigated water allocation models or waterbalance models become one of the decision-making support systems for SVP (Shared Vision
Planning) in PIM. Murase and Kawasaki (2004) suggested that when consensus gets formed,
optimization and equity become essential factors. Trade-offs achieve equity among the interests ofⒸ ISERD

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stakeholders under optimized conditions. It suggests that equity is only contented once optimizationis contented for water allocation. Then, the water balance components need to be quantified throughfield experiments. However, quantifying water balance components are often complicated becauseof the excessive time and expenditure involved in the execution (Khepar et al., 2000), especially indeveloping countries where water scarcity is a common phenomenon and optimized water allocationis strongly demanded.
In addition, the water balance model in a small district at the end of an irrigation system inwhich farmers' water demand finally needs to be met should be simulated to make satisfactorydecision-making. In the case of open ditches, taking water into paddy fields is related to each otherfield. Thus, the degree of freedom of water management in each paddy field declines (Toyota et al.,1984). Toyota et al. (1984) declared that this agreement between water management in ditches andfields greatly affected water intake into paddy fields. Hence farm-block-level analysis was necessary.
The smaller the analysis area, however, the more significant the impact of human disturbance,
making it difficult to simulate water allocation in small-scale fields. The delivery water requirement
would differ from the degree of each farmer’s diverging operation at a small canal (Furuki et al.,1979). This large human activity impact caused a few model developments of simulating water
allocation at a farm-block level.
To explain human activity with a physical model could be a fault, but a statistical model might
be acceptable. The tank model could reproduce this uncertainty, described as a semi-physical andsemi-statistics model.
OBJECTIVE
This paper aims to develop a conceptual water allocation model acceptable to some land-use andirrigation systems changes and access to understanding decision-making processes. This model
calculates the water balance and allocating process in the small-scale paddy fields area through thesemi-physical and semi-statistic tank model.
METHODOLOGY
Target Area
The study area is typical paddy fields (farm-block-level, about 30 ha) located in the middle area of
the Chikugo River in Fukuoka Prefecture, Japan (Fig. 1).

12

B-4

55

8

32

45

54

A-4

Water intake

30 40
11

B-3
5

To downstream

3

B-1
50

A-2
31 41 28

51
100 m

1

46
4
9

Water intake

29

A-1

To downstream
0

7
47

B-2
10

A-3

2

49 6

Water intake

Velocity survey points(and) Water-stage recorder

Farm ditch
Drainage ditch

Fig. 1 The irrigation system and survey points in the study area
The number indicates each branch or release point. Irrigation started from three points (Nos.1, 3, and 9). The black andwhite circles show the survey points where water discharge was measured weekly. The water-stage recorders were installedat the white circle points. The different colored hatches describe the targeted areas for irrigation intakes water from threepoints.

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The area was separated into A- and B-blocks by north and south roads. Moreover, each block
was broken into four sub-blocks corresponding with field-block-level by north and south runningfarm roads and ditches. Each sub-block was regarded as one big paddy lot in this research. The study
area had changed its crop planting (land-use) pattern. The land-use pattern was similar in 2002 and2004 when the whole B-block cultivated the soya bean, and in 2003 and 2005 when part of the Bblock (B-2 and B-3 sub-block) was used for the soya bean. The land-use changes made the water
allocation complex and significantly affected the model parameters.
Measurement of Water Flow in Ditches
A propeller current meter and water stage recorders measured the water velocity and water level in
only one direction in a branch point in the ditches (Fig. 1, B-direction). The former measurement was
conducted once every week and the latter were recorded hourly. The scale observed the water level
simultaneously with the propeller measurement, multiplied by velocity to estimate the observed
discharge. The balance equation calculated the water discharge in the other direction (D-direction)
in a branch point from the observed discharge, which is also considered an observed flow in themodel. The water level measured hourly by the water stage recorder was converted to the discharge
by using the following approximate formula obtained from the relationship between the weekly
measured flow and the water level:
𝑄 = 𝛼ℎ𝛽(1)where Q is discharged, h is measured water level,  and  are coefficients of approximate expression.
Measurement of Water Balance in Paddy Fields

Fig. 2 The structure of the canal tank model (CTM, a), paddy tank model (PTM, b)
and its layout in the allocation model (c)Each CTM was installed at the branch point and PTM was placed in each block. B-direction was where water velocity wasmeasured, and D-direction was where the water flow was calculated by water balance.

We targeted three paddy fields from A-2, B-2, and B-3 sub-blocks. The ponding water depth wasmeasured hourly by a data logger. The precipitation (R) was observed at the nearby A-2 sub-block.
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The elevation of the overflow weir at the outlet was measured weekly because a farmer did notfrequently operate the outlet and used to calculate the amount of water release (Qout) by overflow
computing. Evapotranspiration (ET) was estimated by multiplying the ET ratio and potential ET by
the Penman method from meteorological data. Percolation (P) was estimated by the water balance
equation as:
𝑃 = 𝑄𝑖𝑛 + 𝑅 − 𝐸𝑇 − 𝑄𝑜𝑢𝑡 + ∆ℎ(2)where h was a variation of ponding depth. All values were averaged or totaled daily. N-type waterrequirement survey evaluated the groundwater recharge from paddy fields. The vertical percolation
was about 5 mm/d at the middle point in the field free from levee seepage. The groundwater level
was measured hourly near No.1 (which was used to calibrate the paddy tank model). The amount ofwater runoff from paddy fields at block level was estimated from observed discharge in the drainage
ditches (Fig. 1) by outflow minus inflow in the drainage.
Model for Water Allocation Through Ditches
The whole water distribution process in the study area was represented in two parts; in ditches andinside paddy fields. At the first step of computation of water allocation, the canal tank model (CTM,
Fig. 2a) described the water distribution process through ditches, CTM installed at each branch point(Fig. 2c). The pipe size in CTM represented the water dividing rate at a branch for each direction,
including wastewater ratio (e.g., branch point No.3). The outflow yi from each i-th number of a pipe
was computed as:
𝑦𝑖 = 𝑎𝑖 (𝑥 − ℎ𝑖 )1.5 (𝑥 ≥ ℎ𝑖 )(3)where ai is the coefficient of discharge, x is the storage water depth, hi is the pipe height, and an
output flow occurs only when the storage water depth is higher than the pipe height.
The parameters were calibrated manually but in a rational manner. The water-dividing operation
depends on the land-use pattern and rice growth stage (e.g., rooting, ripening, etc.); thus, the pipe
size parameter was determined by each period manual to consist of observed discharge. The biggest
impacts on the water allocation operation were mid-summer drainage and water stopped before
maturation. The timing of changing parameters was decided from the paddy water depth of the survey
fields. The heavy rain causing excess irrigation water also changed the drainage operation at water
release points. CTM parameters were calibrated in 2002 and 2003 (calibration period) and validated
in 2004 and 2005. The parameter determined in 2002 was applied to 2004 with a similar land-use
pattern year, and the parameter in 2003 was applied to 2005 for the same reason.
Model for Water Balance in Paddy Fields at Sub-Block-Level
The paddy tank model (PTM) structure is shown in Fig. 2 bottom left. The pipe of a0 represented avertical percolation reaching the groundwater: a1 represented a lateral percolation through the leveedraining to the drainage ditches: a2 described water release from a surface and a3 was for groundwater
flow. The sum of lateral percolation and the water release defined the runoff from paddy fields. This
simple model can adapt to a flexible scale. For example, Jayadi et al. (2000) applied one PTM to 300
ha paddies. In this study, PTM described block-level paddy fields, i.e., A-block and B-block.
The input data for PTM were precipitation, ET, and paddy water intake calculated from CTM.
The target output for determining parameters was the groundwater level (GWL). SDFP (Kadoya andNagai, 1980) and the trial-and-error method decided the parameters. The vertical percolation a0 was
determined without the optimization method because the N-type water requirement was about 5
mm/d; therefore, a0 was estimated at 0.070 or 0.075. The ponding depth, the height of the levee, andthe outlet overflow weir height in the site were considered to decide the storage depth in the uppertank. The parameter calibrated by data in 2002 and 2003 was applied to data in 2004 and 2005 forⒸ ISERD

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testing the versatility. As with CTM validation, the identified model coefficients for 2002 wereapplied to the coefficients in 2004, when land use was similar, and the coefficients identified in 2003
were applied to the coefficients in 2005. Hereafter we call 2002 and 2003 a calibration period and2004 and 2005 a validation period.
RESULTS AND DISCUSSION
Applicability of CTM
The simulated water allocation through irrigation ditches by CTM in calibration terms showed good
agreement with the observed flows (Fig. 3a), especially at the endpoint of the irrigation system No.
55 (Fig. 2c) where recorded hourly flow (absolute errors was 5.5 mm/d). No. 46 reproduced reverse
flow when a reversal of hydrodynamic gradient occurred between adjacent branches, and water
flowed through the irrigation ditch opposite the normal flow direction.
CTM well-predicted water allocation in 2004 and 2005 (Fig. 3b, absolute error at No.55 were
6.3 and 18.0 mm/d, respectively), indicating that CTM has robust reproducibility to some extent
regardless of drought season or rainy season because 2002 was drought and 2004 was rainy season.
Also, good agreement suggested that water allocation operation was similar when the land use pattern
was similar.
The CTM concept is apparent, simple, and easy to customize. CTM merely requires discharge
data in irrigation ditches. Taniguchi and Satoh (2006) described that grasping the actual water usage
required a series of observations of quantitative water allocation and enormous instruments andefforts. CTM can be one of the resolutions for these problems. Resource Division Planning
Department Kyushu Agricultural Administration Office (1997) applied the CTM to about 4,600 ha
district in Kasegawa, Saga prefecture, to analyze water distribution. The more the command area
becomes extensive, the more the number of operation points changing the water-diverging ratio
increases. Consequently, diversion operation increases its randomness and decreases the effect on
the tank parameters, leading the parameters to be decided at one value. CTM has to be improved in
the following two aspects. First, the present CTM could not precisely explain the reverse flow that
occurred frequently and extensively. Second, long-term data needs to be collected to increase theaccuracy of CTM's prediction.
Applicability of PTM
The estimated GWL from PTM demonstrated well fitted with the observed value, shown in Fig. 4a.
PTM also simulated the water runoff from A-block and its relative error was around 50% and 28%
in 2002 and 2003, respectively (Fig. 4b). An unsteady flow and seepage from the weir shutter werean obstacle to measuring the drainage discharge, causing some outlier values, and leading to thefitting error being worse. However, the calculated flow reproduced the other observed trend well,and the identified parameters could be used for prediction.
The prediction of GWL and runoff from paddy fields, shown in Fig. 4, demonstrated good
agreement with observed values and proved PTM’s versatility. However, although simulated GWL
in 2004 well matched with observed GWL, the predicted runoff had difficulties at reproducibility.
The relative error of runoff in 2004 was about 200% due to the failure to reproduce the small observed
values in the denominator of the relative error equation. The high error in 2004 was caused by using
the same parameter through 2004 and 2005 even though the land use pattern changed. However, theprediction in 2005 showed good fitting simulation both for GWL and runoff.
Future development was that the model's sensitivity to land use should be improved. In thisstudy, the block level was considered to be one paddy tank. However, the sub-block could be
regarded as one paddy tank to improve sensitivity, and the model would deal with various land use
patterns in more detail. Furthermore, the paddy lot management schedule should be taken for
calibrating PTM parameters into account. The PTM coefficient could be changed according to therice growing stage or water management schedule.
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Fig. 3 Water allocation in ditches
The black solid line, outline of a green circle, and red square stand observed flow in the B-direction and D-direction,
respectively. The green and red solid lines represent CTM's simulated values in B- and D-direction, respectively. The minus
value at No.46 demonstrates the reverse flow.

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In this study, the simulation model was developed to predict water allocation and balance witheasily available data at the farm block level. Kuo et al. (2006) calculated the water demand of paddy
and upland crops by CROPWAT designed by Smith (1991) at the ChiaNan Irrigation Associationthat could estimate the soil moisture but not include the paddy lot water management or delivery
water management, thus could not evaluate the water productivity. The present model in this study
can estimate and consider both lot water management from PTM and delivery water managementfrom CTM. The proposed model can also apply to farm and large-scale levels, including complex
land use areas.

Fig. 4 Comparison between calculated and observed GWL (a) and water runoff (b) frompaddy fields in the calibration term (2002-2003) and validation term (2004-2005)
Solid lines are calculated and dotted lines are observed values (a).

The developed model becomes a decision-making support system for SVP (Shared Vision
Planning) in PIM. Murase and Kawasaki (2004) suggested that optimization and equity were
essential for forming consensus. The equity is comforted by trade-offs among stakeholders' interests
under optimized conditions. This model can optimize water management or land use patterns bysimulating the water balance and allocation process. Thanks to the tank model's semi-physicalcharacteristics, the participant intuitively understands the operation of the water diversion and waterbalance component to which the model parameters correspond.
CONCLUSION
This study calculated water balance through irrigation ditches and paddy fields in the area using
understandability concepts and accessible collecting data by connecting the canal tank model (CTM)to the paddy tank model (PTM). An easily understandable and collectible data structure is essential
for the decision-making process. The present model parameters are consistent and capable ofpredicting water allocation and balance with similar land use patterns. For example, a simulation by
CTM and PTM under a scenario of saving irrigation water because of a lack of precipitation could
predict how the groundwater level would change. If the groundwater level could be predictable, it
could avoid wet or drought injury to the crop.
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Using available data for this type of study is important because it is difficult to gather large
amounts of actual data on water allocation at every branch of the irrigation system every week forseveral years. This paper aims to build a model based on a simple tank model concept and data thatcan be easily collected. The data used in this study spans from 2003 to 2005. Nonetheless, we havedemonstrated that it is possible to develop an accurate model for our intended purpose, as the methodof collecting actual data has remained consistent even today. In the future, the remaining issue is toaccommodate the changing land use, and the PTM parameters should be calibrated at each paddy,
upland, and greenhouse (Kato, 2005). To some extent, the tank model parameters have generality
attributed to the semi-physical character, which means that human activity to change irrigation
management can be reproduced by the present model.
REFERENCES
Fujimoto, N. and Tomosho, T. 2003. A viewpoint to apply water pricing to the Asian humid tropics. Paddy
and Water Environment, 1 (2), 75-83, Retrieved from DOI https://doi.org/10.1007/s10333-003-0014-3
Furuki, T., Yamashita, A., Sato, H. and Ezaki, K. 1979. Studies on conveyance loss in paddy field irrigation.
Bulletin of the National Research Institute of Agricultural Engineering, 1-30. (in Japanese)
Jayadi, R., Fukuda, T., Nakano, Y. and Kuroda, M. 2000. Deterministic optimization of irrigation water
allocation in a low-lying paddy area with creek networks. Journal of the Faculty of Agriculture, Kyushu
University, 44 (3-4), 419-429, Retrieved from DOI https://doi.org/10.5109/24343
Kadoya, M. and Nagai, A. 1980. Runoff analysis method, Optimize identification of storage function modelby SDFP. Journal of JSIDRE, 48 (12), 65-70. (in Japanese)
Kato, T. 2005. Development of a water quality tank model classified by land use for nitrogen load reduction
scenarios. Paddy and Water Environment, 3 (1), 21-27, Retrieved from DOI https://doi.org/10.1007/s10333-005-0069-4
Khepar, S.D., Yadav, A.K., Sondhi, S.K. and Siag, M. 2000. Water balance model for paddy fields underintermittent irrigation practices. Irrigation Science, 19, 199-208, Retrieved from DOI https://doi.org/10.
1007/ PL00006713
Kuo, S.F., Ho, S.S. and Liu, C.W. 2006. Estimation irrigation water requirements with derived crop coefficientsfor upland and paddy crops in ChiaNan Irrigation Association, Taiwan. Agricultural Water Management,
82 (3), 433-451, Retrieved from DOI https://doi.org/10.1016/j.agwat.2005.08.002
Murase, M. and Kawasaki, H. 2004. Research on model for participation consensus formation in low-water
management. Dam Engineering, No. 213, June 2004, 9-15. (in Japanese)
Saito, K. 2010. To think of irrigation management. Journal of JSIDRE, 1046-1048. (in Japanese)
Smith, M. 1991. CROPWAT manual and guidelines. FAO, Rome, Italy.
Taniguchi, T. and Satoh, M. 2006. Impact of irrigation water stability on on-farm water distribution in a paddy
field. Journal of JSIDRE, 246, 17-23. (in Japanese)
Toyota, M., Suzuki. M., Nishiide, T. and Tomota, A. 1984. Characteristics of water management in paddy field
open canal system. Journal of JSIDRE, 991-998. (in Japanese)
Yamamoto, K. 2006. Paddy field characteristics in water use, Experience in Asia. In Water and Agriculture,
Sustainability, Markets and Policies, 287-315, OECD Publishing, Paris.

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Research article
erd

Research
Clarification of Water Use under the Complicated Irrigation
articleSystem and its Modeling in the Boribo-Bamnak River Basin,
Cambodia

HENG SALPISAK
Graduate School of Agriculture, Hokkaido University, Sapporo, JapanTADAO YAMAMOTO*
Research Faculty of Agriculture, Hokkaido University, Sapporo, Japan
Email: tady@env.agr.hokudai.ac.jp

TAKASHI INOUE
Research Faculty of Agriculture, Hokkaido University, Sapporo, Japan
Received 14 February 2023

Accepted 8 May 2023(*Corresponding Author)

Abstract Effective, equitable, and sustainable management of water resources in river basinsrequires clarification of the current river basin situation and potential water use and waterbalance challenges. This study performs a water balance calculation involving an analysis of
the appropriate water distribution of the Boribo-Bamnak River basin in Cambodia. This river
basin covers the Boribo and Bamnak basins, both of which are interlinked by the Bamnak
headworks. Together, this constitutes an integrated irrigation and drainage system. The Soiland Water Assessment Tool (SWAT) model was used to simulate rainfall-runoff in the BoriboBamnak basin over a study period of nine years (2010-2018), whereupon a simulated daily
streamflow was applied to the water balance computation in the river basin according to thewater distribution ratio at Bamnak headworks. The SWAT model yielded NSE, PBIAS, andRSR values of 0.55, 9.70, respectively, and 0.67 for model calibration. It also obtained valuesof 0.51, 3.70, and 0.70 for model validation of the three quantitative statistics, NSE, PBIAS,
and RSR. The results of the calculated water balance indicate that although the Bamnak and
Boribo Rivers have abundant water in the wet season, they have faced water shortages in thedry season during every year of the study period except 2016. Irrigation safety during the dry
season is always low (approximately 10%). Attaining a desirable safety level of 80% in all
existing irrigation areas would require additional water resources of approximately 6.0 × 106
m3 for the Boribo River basin and 107 m3 for the Bamnak River basin. In light of the abovefindings, this study provides recommendations for coordination strategies to improve water
resource management and development plans in the river basin.
Keywords water balance, water distribution, SWAT model, water shortage, irrigation,
safetyINTRODUCTION
Irrigation is a mechanism for increasing agricultural production, thereby increasing the income ofrural poor regions, and developing the economy. In this regard, it is a focus of the Royal Governmentof Cambodia as described in the Rectangular Strategy (CSIRO, 2013), a planning and development
document. As a result, Cambodia has witnessed the planning and implementation of many water
resources and irrigation development in recent years, many of which have focused on river basins(Masahiko, 2013). However, the rapidly increasing demand for water has intensified the competition
for water resources, highlighted concerns about the equity of water allocation, the sustainability ofwater usage, social friction among water-user communities, and the long-term sustainability of water
resources and environmental impact of irrigation (MOWRAM and JICA, 2014). Indeed, the BoriboBamnak River basin (MOWRAM, 2018) has been affected by a large increase in water use demandⒸ ISERD

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due to the expansion of irrigated areas, as well as competition for water allocation between upstream
and downstream users.
Thus, it is crucial to address water use by assessing water supply and water demand forappropriate management and planning of water resources in the basin. Researchers have used manymethods to assess and predict the intra- and interannual availability of water resources within acatchment. Among these methods, decision support tools, such as hydrologic models, can help
researchers to develop better management strategies for local and regional water resources (Chea andOeurng, 2017). Hydrological models have been developed to help calculate water discharge moreaccurately, easily, and quickly than when using traditional measurement methods. One such method
is the SWAT (Soil and Water Assessment Tool) model, which is a basin-scale model integrated withArcGIS to improve the accuracy of simulated streamflow from rainfall and the physical propertiesof a basin (Ang and Oeurng, 2018). Regrettably, conventional water supply-oriented simulation
models are often insufficient for addressing contemporary water resource management problems(Yates et al., 2005). Therefore, this study uses the SWAT model to simulate streamflow in acatchment and then performs the computation to describe the water balance and amount of water
available for allocation under current conditions.
OBJECTIVE
This study aimed to (1) predict water balances involving different scenario evaluations of water
distribution at Bamnak headworks in the Boribo-Bamnak River basin, and (2) clarify current water
management problems by studying water distribution at Bamnak headworks.
METHODOLOGY
Study Area
The Boribo-Bamnak River basin is located within two provinces of Cambodia, namely Kampong
Chhnang, and Pursat, and has a total catchment of 1258 km2 (Fig. 1). It covers the Boribo andBamnak River basins, both of which are interlinked at Bamnak headworks (located on the Bamnak
River, an upstream tributary of the Boribo River) and constitutes an integrated irrigation and drainage
system (Fig. 2). The climate in the basin is influenced by tropical monsoon systems with distinct wet
and dry seasons. The wet season, from May to November, receives approximately 90% of the total
annual rainfall, ranging from 1200 mm to 1800 mm, and the dry season, from December to April, ischaracterized by the prevalence of hot and dry air with high potential transpiration demands. In thebasin, agriculture is the predominant water-consuming sector and twelve main irrigation schemes
have been developed; these have been classified into six schemes using water from the Bamnak River(Pursat Province) and the other six schemes using water from the Boribo River (Kampong Chhnang
Province) as shown in Table 1.

Fig. 1 Study area

Fig. 2 Schematic Bamnak headworksⒸ ISERD

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Table 1 Identified irrigation schemes in the Boribo-Bamnak River basin
No

Scheme Name

Total Command Area (ha)I. Bamnak River (Pursat Province)
1 Bamnak
2 Chamkar Krouch
3 Kampong Lor
4 Thlea Maom
5 Tram Mneash
6 Trapeang Khley
Sub-total
II. Boribo River (Kampong Chhnang Province)
1 Achang (1)2 Dambok Krahorm
3 Kamping Tatao
4 Lum Hach
5 O Rolus
6 O Chenhchraim
Sub-total
Total

Total Farmland Area (ha) Using Water
Irrigated from the Target Rivers
EW
W
D

6,000
350
130
3,500
1,200
300
11,480

600
100
30
500
120
100
1,450

2,400
100
100
2,000
1,080
200
5,880

1,122
70
30
1,222

10,300
150
700
3,289
640
170
15,24926,729

1,450

1,400
300
3,289
640
170
5,799
11,679

750
150
700
1,600
2,822

(1) Including four sub-schemes: Banteay Thlok, Kum Reab, O Sanlang, and Svay Ka’er

EW: Early wet season rice, W: Wet season rice, D: Dry season rice
Sources: (1) MEIHO Engineering Inc. 2018. Final report, Survey on basic information in river basins (phase 3),
JICA; (2) Field study in Cambodia, April 2022.

SWAT Modeling Approach
The SWAT model is a physically based, semi-distributed, agro-hydrological, continuous hydrologicalmodel developed to enable water resource managers to determine the most appropriate strategy or
solution by considering the impact of different management practices on streamflow and non-point
source pollution (Arnold et al., 1998).
In this study, the SWAT model was used to simulate, using available data, daily streamflow inthe catchment of Boribo-Bamnak. Running a comprehensive SWAT model requires spatial input
data including a Digital Elevation Model (DEM), land use, soil type, and meteorological data. Eachdata input was obtained from different sources, such as a DEM with a resolution of 30 m downloaded
from ASTER GDEM2. Soil-type data with a resolution of 250 m was retrieved from the FAO soil
map, and land use data were obtained from the Ministry of Water Resources and Meteorology(MOWRAM) of Cambodia. Daily meteorological data from 2007 to 2018 were provided by theProvincial Department of Water Resources and Meteorology (PDWRAM) of the Kampong Chhnang
and Pursat Provinces, respectively. The observed daily streamflow at Boribo River station was
required by SWAT-CUP to be calibrated between 2010 and 2015 and validated from 2016 to 2018using the SUFI-2 method.
Irrigation Water Requirements
The irrigation water requirement (IWR) is the amount of water needed to fulfill crop waterrequirements after effective rainfall, thereby ensuring a disease-free crop in large fields under nonrestricting soil and water conditions and adequate fertility (Solangi et al., 2022). In this study, theaverage five-day water requirements for proposed cropping patterns of each crop variety in the
Boribo-Bamnak River basin were estimated using the following equation Eq. (1)𝐼𝑊𝑅 = (𝐸𝑇0 × 𝐾𝑐 + 𝑃𝑅 + 𝐿𝑃 − 𝐸𝑅)⁄𝐼𝐸(1)

where IWR is the irrigation water requirement for a division unit, ET0 is reference evapotranspiration,
calculated using the FAO Penman-Monteith method (FAO, 1998), Kc is the crop coefficient defined
based on FAO guidelines (for the case of paddy) since there is no observed data in the basin, PR is
the percolation rate (3.0 mm per day in this study, referring to JICA (2012)), LP is the land
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IJERD – International Journal of Environmental and Rural Development (2023) 14-1

preparation requirement, estimated by assumption using two methods of direct sowing under dry soil
and transplanting under wet soil, ER is effective rainfall, calculated following JICA (2012), and IE
is irrigation efficiency, obtained from water losses during conveyance and application to the fieldand defined following JICA (2012).
Water Balance Study
The water balance was computed using a simplified diagram of the present condition of water
resource facilities and irrigation water uses in the river basin (Fig. 3). The fundamental formula fora water surplus or deficit at a major point where a large amount of water is taken from the river isexpressed as follows Eq. (2)
𝑄𝑠𝑑 = 𝑄 + 𝑄𝑟𝑓 − 𝑄𝑞 − 𝑄𝑟𝑚𝑓

(2)

where Qsd is the surplus or deficit of water at the calculation point, Q is the river runoff from the relevant
catchment area, Qrf is the return flow from paddy fields to the river (17% of the irrigation demand wasused in this study after JICA, 2012), Qq is a summation of irrigation water demand, and Qrmf is the river
maintenance flow, which was supplied to the downstream part of the river in order to preserve the river
as a part of the landscape (0.1 m3/s/100 km2 was applied, based on the JICA, 2012).
The water balance calculation was executed from upstream to downstream following thenatural flow direction for a time unit of five days for nine years (2010–2018). To confirm the securityof the irrigation water supply to the Boribo-Bamnak River basin, this calculation was performed asfollows: (1) identification of the impacts of existing irrigation schemes in the basin, (2) assessmentof impacts from the viewpoint of the safety levels of irrigation water supplies, and (3) assessment of
the impacts of water distribution at Bamnak headworks.
An evaluation of the safety level of the irrigation water supply is made as follows (1) a waterbalance was performed at each scheme outlet in terms of deficit or surplus, i.e., the net available flow
subtracting the irrigation water requirement (IWR), such that a deficit occurs when the net available
flow is less than the IWR, (2) for each year, when the deficit was more than or equal to fourcontinuous five-day units (20 days), this year is judged to be a deficit year, and (3) each irrigation
scheme is successful if the safety level is less or equal to 1/5 (80% dependability). The formula todefine the safety level at each irrigation scheme is expressed as Eq. (3)𝑆𝑎𝑓𝑒𝑡𝑦 𝐿𝑒𝑣𝑒𝑙 = (𝑥 + 1)⁄𝑛(3)where x is the number of years with twenty-day successive deficits (irrigation failures) and n is thetotal number of simulated years. In this study, for nine years of successful irrigation, the 1/5 term canbe stated as 2/9. Consequently, if the safety level is less than or equal to 2/9, the scheme is deemed
successful, and we can determine that water resources are secured with 80% dependability.
To calculate the probability of the deficit/storage required for a safety level 1/5, we use Eq. (4)𝑦 = 𝑐 × ln(𝑥) + 𝑏(4)

where y is the probable deficit in x% non-exceedance, c and b are constants, ln is the natural logarithm,
and x is the percentage of exceedance.
Water distribution at Bamnak headworks is an important point of the water balance calculationin the Boribo-Bamnak River basin. In this study, water distribution at Bamnak Headworks wasincorporated into the water balance calculation in two ways. (1) Water was allocated equally to Pursat
and Kampong Chhnang (i.e., 50% each) during the wet season (May–October) and allocated 75% toPursat Province, and 25% to Kampong Chhnang Province during the dry season (November toApril); refer to the field study in Boribo-Bamnak River basin, March 2022. (2) Water was allocatedequally to Pursat and Kampong Chhnang Provinces (i.e., 50% each) either in the wet season or dry
season (refer to the regular rule of fair and sustainable water distribution).
Additionally, water management was considered through a study on actual water distribution
using existing data for discharge at Bamnak headworks from 2018 to 2019.

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Boribo River

Boribo River

Bamnak River

Bamnak River

CA6

CA7

CA1

CA3

124

234

388

135

O Chenhchraim irr.
170 haLum Hach3289 haBamnak Right irr.
500 haBamnak HW

CA9

143

Bamnak Left irr.
5,500 haCA8

Lum Hach HW

CA2
CA4

14

110
Chamkar Krouch irr.
350 haTram Mneash HW

Tram Mneash irr.
1,200 ha

38
CA5

43
O Rolus irr.
640 haAchang HW

Trapeang Khley irr.
300 haThlea Maorm irr.
3,500 haAchang irr.
10,300 ha

CA10

26

Thlea Maorm HW 1&2

Kampong Lor HW

Kampong Lor irr.
130 haTonle Sap Lake

Kamping Tatao irr.
1,000 haCA11

Dambok Krahorm irr.
150 haDambok Krahorm HW

3

Irrigation systems;- O' Sanlang- Kum Reab
- Svay Ka'er- Banteay Thlok

LegendCA i ; Catchment area, the i is a serial number given by the study performer
xxx ; Catchment area in square kilometers (km2); River flow
; Return flow or drain; Headworks/Intake; Irrigation〇〇〇 irr.
; Name of irrigation area
; Province Boundary
xxxx ha; Command area in ha

Tonle Sap Lake

Fig. 3 Diagram of present-day water use in the Boribo-Bamnak River basin
RESULTS AND DISCUSSIONSWAT Calibration and Validation for Streamflow
Figure 4 represents the simulated streamflow for the daily time step (calibrated from 2010 to 2015
and validated from 2016 to 2018) compared with observed data. The model performance is shown tobe satisfactory in terms of calibration and validation with NSE values of 0.55 and 0.51 according to theevaluation criteria of Moriasi et al. (2007). We noted, however, that the hydrological simulations did
not perform well during the dry season (November-April) due to inaccuracies in the estimateddischarge at the observation station. The estimated discharge was calculated via water level
observation by applying H-Q curves produced by the River Basin Water Resources Utilization
project of JICA in 2018. Because these water discharge measurements were conducted only duringhigh-water level periods, they did not cover the entire range of water levels experienced during
periods when the relationship between water level and discharge is known to be stable. This
relationship was, therefore, not defined for low flow conditions.

Fig. 4 Daily streamflow during the calibration and validation periodsⒸ ISERD

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Referring to the information about water management in the Boribo-Bamnak River basin
obtained through a field study conducted in March 2022, we found that the water level in the river
was very low in the upstream region, drying up in the downstream region during the dry season. Thisvariation is known to be challenging for the farmers in the river basin and has been reported bynumerous farming households located in the upstream and downstream parts of the river basin (27households in Pursat Province and 6 households in Kampong Chhnang Province). Simulated
streamflow from the SWAT model was used for the water balance study.
Water Balance Study
The water balances of the Bamnak River in Pursat Province and the Boribo River in Kampong
Chhnang Province were calculated taking into consideration the ratios of water distribution at
Bamnak headworks. Fig. 5 shows the results of the first case of water distribution at Bamnak
headworks (wet season: Pursat = Kampong Chhnang = 50%; dry season: Pursat = 75%, Kampong
Chhnang = 25%). Fig. 6 illustrates the results of the second case (wet season and dry season: Pursat= Kampong Chhnang = 50%). Water resources are sufficient during the wet season; however, water
shortages frequently occur in the dry season. Indeed, a water deficit occurred annually during the dry
season every year between 2010 to 2018, except for 2016. Thus, the irrigation safety is approximately
10% either in Pursat and Kampong Chhnang Province under these two ratio cases. This indicates thatthe Bamnak and Boribo Rivers lack sufficient water to guarantee 80% irrigation safety for existingareas of irrigation. By calculating the probability of the deficit/storage required for a safety level of
1/5, the water deficit is estimated in both cases as approximately 6 million cubic meters in Kampong
Chhnang Province and 10 million cubic meters in Pursat Province.
The Bamnak and Boribo Rivers have abundant water during the wet season. The irrigation of
wet season paddy was examined without dry season rice taken into the calculation; as a result, theirrigation safety during the wet season paddy was 80% in both provinces by virtue of the natural river
flow alone. Under these conditions, water distribution at Bamnak headworks is not considered to be
an issue during the wet season (May to October).

Fig. 5 Hydrograph showing surplus and deficit water between 2010 and 2018
Water allocated at Bamnak headworks: Pursat = Kampong Chhnang = 50% during the wet season; andPursat = 75%, Kampong Chhnang = 25% during the dry season.

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Fig. 6 Hydrograph showing water surplus and deficit between 2010 and 2018
Water allocated at Bamnak headworks: Pursat = Kampong Chhnang = 50% during the wet anddry seasons

According to our calculations, although 100% of the water was distributed to Pursat during thedry season, it was insufficient to maintain the irrigation water required for existing dry-season ricein this province (1,222 ha). Moreover, river maintenance flow in both provinces could be secured incase equitable water distribution at Bamnak was made and dry season rice in both provinces was nottaken into calculation.
Water Distribution at Bamnak Headworks
The actual water distribution at Bamnak headworks was estimated based on available data for 2018and 2019. Which were obtained from Pursat PDWRAM (recorded water level) and the JICA River
Basin Water Resources Utilization project (H-Q curve). The water distribution at Bamnak headworks
was found to be similar to the distribution ratio of the first case study in the water balance calculation(Fig. 7). On average, the ratios of water distribution were made as 40% and 30% to Kampong
Chhnang Province, respectively, and 60% and 70% to Pursat Province, respectively, in the wet anddry seasons.

Fig. 7 Water distribution at Bamnak headworks in 2018 and 2019
To assist water management in the basin, the Bamnak headworks were constructed in 2010 by
MOWRAM with the base idea of allocating 50% of the water available to Pursat Province and 50%
to Kampong Chhnang Province. In practice, this concept has been difficult to realize because thetotal width of four intake gates to Pursat Province is 8.8 m (=2.2 × 2 × 2) when the total width of twoⒸ ISERD

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spillway gates to Kampong Chhnang Province is 3.0 m (=1.5 × 2) (Fig. 2). Therefore, fair, andsustainable water distribution at Bamnak headworks must be made based on a consensus between
province stakeholders.
CONCLUSION
This study has shown that the SWAT model is an appropriately sensitive model for predicting daily
streamflow in the Boribo-Bamnak River basin. It provides insights into the importance of better
analysis relationships, which depends mostly on the quality of available data and the necessity for
additional hydrological observation.
The results of water balance studies in the Boribo-Bamnak River basin clearly indicate that theavailability of water in the river is not sufficient to supply all water demands for existing irrigation
schemes in Pursat and Kampong Chhnang Provinces. Water shortages occurred in the dry season
almost every year during the study period (2010-2018). Therefore, to ensure sustainable water use in
the river basin, a study of the possibility of constructing reservoir dams in the upstream region ofboth the Bamnak and Boribo Rivers should be considered.
In terms of water management at the Bamnak headworks, this study suggests that Pursat
PDWRAM should make efforts to communicate with Kampong Chhnang PDWRAM and related local
authorities, for example, the Farmer Water User Communities, in order to appropriately implement
water flow operations that ensure sustainable water use while avoiding conflicts among water users.
REFERENCES
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, 89-101, Retrieved
from DOI https://doi.org/10.1016/j.wsj.2017.12.002
Arnold, J.G., Srinivasan, R., Muttiah, R.S. and Williams, J.R. 1998. Large area hydrologic modeling andassessment part I, Model development. Journal of the American Water Resources Association, 34, 73-89,
Retrieved from DOI https://doi.org/10.1111/j.1752-1688.1998.tb05961.x
Chea, S. and Oeurng, C. 2017. Flow simulation in an ungauged catchment of Tonle Sap Lake Basin in
Cambodia, Application of the HEC-HMS model. Water Utility Journal, 17, 3-17, Retrieved from URL
www.ewra.net/wuj/pdf/WUJ_2017_17_ 01.pdf.
Smith, D., and Hornbuckle, J. 2013. A review on rice productivity in Cambodia and water use measurement using
direct and indirect methods on a dry season rice crop. Sustainable Agriculture Flagship, Commonwealth
Scientific and Industrial Research Organization, Australia.
FAO. 1998. Crop evapotranspiration. Irrigation and Drainage Paper No. 56, Food and Agriculture Organizationof the United Nations.
JICA. 2012. Special assistance for project implementation for west Tonle Sap irrigation and drainage
rehabilitation and improvement project. Japan International Cooperation Agency, Tokyo, Japan.
Masahiko, H. 2013. Training for river basin water balance analysis. MOWRAM, Phnom Penh, Cambodia.
Meiho Engineering Inc. 2018. Final report, Survey on basic information in river basins (phase 3). River Basin
Water Resources Utilization Project, MOWRAM-JICA.
Moriasi, D.N., Arnold, J.G., Van Liew, M.W., Binger, R.L., Harmel, R.D. and Veith, T.L. 2007. Modelevaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of
the ASABE, 50, 885-900, Retrieved from DOI 10.13031/2013.23153
MOWRAM and JICA. 2014. Background of the project, The project for river basin water resources utilizationin the Kingdom of Cambodia. Ministry of Water Resources and Meteorology and Japan International
Cooperation Agency.
MOWRAM. 2018. Official acknowledgement of the pilot Boribo-Bamnak river basin management committee,
No. 138 Pra Kor. Ministry of Water Resources and Meteorology, Cambodia.
Solangi, G.S., Shah, S.A., Alharbi, R.S., Panhwar, S., Keerio, H.A., Kim, T., Memon, J.A. and Bughio, A.D.
2022. Investigation of irrigation water requirements for major crops using CROPWAT model based on
climate data. Water, 14, 2578, Retrieved from DOI https://doi.org/10.3390/w14162578
Yates, D., Sieber, J., Purkey, D. and Huber-Lee, A. 2005. WEAP 21, A demand-, priority-, and preferencedriven water planning model, Part 1, Model characteristics. Water International, 30, 487-s500, Retrieved
from DOI https://doi.org/10.1080/02508060508691893Ⓒ ISERD

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Research article
erd

Research article
Improvements in Preservation Properties of HomemadeStyle Pickled Cucumber in Cambodia

SOKLY SORM
Graduate School of Agriculture, Tokyo University of Agriculture, Tokyo, JapanSHUKI MURAMATSU*
Showa Women’s University, Tokyo, Japan
Email: s-muramatsu@swu.ac.jp

MASATAKA UCHINO*Tokyo University of Agriculture, Tokyo, Japan
Email: muchino@nodai.ac.jp

YOSHIKI MURAMATSU
Tokyo University of Agriculture, Tokyo, JapanDAIKI OKATokyo University of Agriculture, Tokyo, Japan

NARONG TOUCHTokyo University of Agriculture, Tokyo, JapanYURI TANIOKA
Tokyo University of Agriculture, Tokyo, Japan

TAKAHIKO NAKAMURATokyo University of Agriculture, Tokyo, JapanTORU NAKAJIMATokyo University of Agriculture, Tokyo, Japan

MOTOE SEKIDO
Yamanashi Gakuin Junior College, Yamanashi, JapanSHOTARO KAWAKAMITokyo University of Agriculture, Tokyo, JapanCHIM CHAY
Royal University of Agriculture, Phnom Penh, Cambodia

MARI ARIMITSU
Institute of Environmental Rehabilitation and Conservation, Tokyo, Japan

MACHITO MIHARATokyo University of Agriculture, Tokyo, Japan
Received 16 December 2022

Accepted 10 May 2023(*Corresponding Author)

Abstract Pickled cucumbers selling at wet markets in Cambodia are popular among local
people. It has been reported that pickles using homemade recipes are at a high risk of spoilingand causing food poisoning, as there are no heating steps in the production process. Therefore,
it is necessary to improve the hygienic conditions of the food supply to make safe pickles in
Cambodia. Heat treatments using hot pack filling and pasteurization lead to microbiologicallyⒸ ISERD

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safe products and extended shelf life. This study aimed to examine the effect of heat treatments(hot pack filling and pasteurization) on preservative properties and to evaluate the acceptabilityof the pickled cucumbers prepared with the heating process. Pickled cucumbers prepared withand without the heating process were made using a traditional Cambodian recipe and stored at
30 °C for 7 days. The presence of total viable bacteria, coliforms, Escherichia coli, yeasts, andmolds in the pickled products was tested during the storage periods. The samples without theheating process resulted in contamination with coliforms, E. coli, yeasts, and molds and werein an initial putrefactive state because of the number of total viable bacteria. On the other hand,coliforms, E. coli, yeasts, and molds were not detected in the samples prepared with the heatingprocess from Day 0 to Day 7. This result indicated that the pasteurization treatment killed
many spoilage microbes, including foodborne pathogens. To investigate the acceptability ofthe pickled cucumbers prepared with the heating process, sensory evaluation tests were
performed. From the results of the sensory evaluation and questionnaire survey, there was thepossibility of acceptance of the pickled cucumbers prepared with the heating process madeeither in Japan or Cambodia by the Cambodian panelists; however, further improvement in thesoftness of the pickles was commented upon.
Keywords cucumber, homemade-style pickle, pasteurization, sensory evaluation,
acceptability

INTRODUCTION
Pickled cucumbers are popular pickles in Cambodia. Nearly all Cambodian people like to eat pickles
in their daily diet. These pickles are mostly produced at home using traditional recipes and are usuallysold at wet markets in Cambodia. The Ministry of Health in Cambodia reported that after eating thesehomemade-style pickled cucumbers, many people suffer from symptoms of food poisoning,
including diarrhea, abdominal pain, fever, and nausea (MoH, 2016). A review report has describedthat important foodborne pathogens have been detected in the food supply in Cambodia (Thompson
et al., 2021). Studies by Muramatsu et al. (2020a, 2020b) and Chrun et al. (2017) showed that somemicroorganisms could cause food spoilage and food poisoning in homemade pickled products soldat wet markets. The current preparation method for homemade-style pickles is generally as follows.
Fresh vegetables are washed with tap water. Then, they are submerged in boiled water or normaltemperature water along with seasonings. The pickles are then soaked for two to four days at room
temperature. The room temperature ranges from 25 to 35 °C according to the tropical climate of
Cambodia. Homemade pickles are commonly stored at room temperature at approximately 30 °C
during and after the production of pickles. Muramatsu et al. (2022) prepared three kinds ofhomemade-style pickles using traditional Cambodian recipes and evaluated the microbial quality of
those pickles. The report revealed that microbial growth was observed in all pickles starting at Day
0, which poses a high risk of food spoilage and food poisoning. Therefore, we focused on the
production process for obtaining microbiologically safe products. Therefore, this study aimed to
examine the effect of thermal preservation methods on the microbial quality of pickled cucumbers.
The heating step is considered to affect the taste of the pickled cucumber, and therefore we also
investigated the acceptability by Cambodian people.
Pickled cucumbers were prepared with and without the heating process following theCambodian homemade-style recipes. For the purpose of providing safe pickle products in Cambodia,
we aimed to investigate the effect of the heating process (hot pack filling and pasteurization) on the
microbial quality of cucumber pickles. The acceptability of these pickled cucumbers was examinedbased on sensory evaluation in Cambodia.
OBJECTIVE
The objectives of this study were 1) to examine the effect of the heating process (hot pack filling andpasteurization) on the preservative properties of the pickled cucumbers and 2) to evaluate theacceptability among Cambodian people of the pickled cucumbers prepared using the heating process.
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METHODOLOGY
Materials, Production Process, and Procedure for Samples Testing
The pickled cucumbers were prepared with and without a heating process according to traditional
Cambodian recipes (Muramatsu et al., 2022) as samples for the test. All ingredients and seasonings
were purchased at a supermarket in Tokyo, Japan. The seasoning mixture was prepared using 30.6
grams of salt and 700 ml of water. The ingredients used to make the samples were 200 g (5 pieces)of cut fresh cucumbers, 4.5 g (1 piece) of garlic, and 1.0 g (2 pieces) of chili. All ingredients weremixed with the seasonings. Figure 1 shows the production process of pickled cucumbers with theheating process. Cucumbers were washed with tap water and wiped with a paper towel. Cucumberswith diameters of 2.2-3.2 cm were cut into lengths of 7 cm using a knife. The garlic was peeled andsliced. A piece of chili was sliced into rings. The liquid seasoning was heated to boiling. The heatedliquid seasoning, 120 ml, a piece of cucumber, and a few slices of garlic and chili were placed into a
glass bottle up to 3-5 mm from the bottle lid. After closing the lid of the bottle (sealing), the bottle
was turned upside down. The hot glass bottle filled with seasoning and cucumber was submerged in
hot water at a temperature of 80 °C. Then, the hot water was heated to boiling in a pot. After coming
to a boil, the glass bottle was maintained in boiling water for 10 minutes to raise the center
temperature of the cucumber to above 75 °C. After this pasteurization, the glass bottle was cooled atroom temperature in an inverted state for a few hours.
Fresh Cucumber

Glass bottle

Boiling liquid seasoning

Sealing(hot pack filling)

Pasteurization(boiling 10 min, center
temperature >75 C)

Pickled cucumber

Slice garlic and chili

Fig. 1 Production process of pickled cucumber prepared with the heating process
The pickled cucumbers without a heating process were prepared using the same seasoning andingredients as the heated sample shown in Fig. 1. After placing the ingredients into the glass bottle,
the liquid seasoning at room temperature was added. The lid of the glass bottle was closed.
Preparation of the Samples with the Heating Process for Examination of Preservability
To examine the preservability of cucumber pickles, the samples were observed for 7 days, as thevendors who sold pickles at wet markets reported that the shelf life of their products wasapproximately 2-4 days according to our survey and that the products were kept for 3-4 days during
preparation by the traditional recipe.
The food properties of the samples during the storage periods, the Brix values, salt
concentrations, and pH of the pickle liquid seasoning, were measured by using a Brix refractometer(Atago, Tokyo, Japan), a salt meter (Horiba, Kyoto, Japan), and a pH meter (Horiba), respectively.
To investigate the safety of the samples, microbiological tests were conducted by detecting total
viable bacteria, coliforms, E. coli, yeasts, and molds. In total, 10 g of solid and liquid pickled
cucumber was mixed with 90 ml of phosphate-buffered saline (PBS) (ELMEX, Tokyo, Japan) andplaced in a sterilized storage bag. To mix well, samples were crushed using a hammer. After mixing,
1 ml of the sample suspension was mixed with 9 ml of PBS. A series of diluted samples were used
for the detection of total viable bacteria, coliforms, E. coli, yeasts, and molds in the samples.
Commercial sheet-shaped, dry, and ready-made microorganism detection media with nonwoven
fabric, MC-media PadTM (JNC Corporation, Tokyo, Japan), were used for the detection of
microorganisms. One milliliter of sample solution at each dilution was spread onto each specific MCⒸ ISERD

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media PadTM. After spreading, the MC-Media PadTM "Aerobic Count (AC)", MC-Media PadTM "EC",and MC-Media PadTM "YM" were incubated at the set temperature of 35 °C for 48 hours, 24 hours,and 25 °C for 72 hours, respectively for assessment of total viable bacteria, coliforms, E. coli, yeasts,
and molds. After incubation, the log10 CFU/g was calculated using media on which there were 30300 colonies available to count. Three repetitions were carried out for the detection.
Sensory Evaluation of the Pickled Cucumber Made in Japan and Cambodia
For sensory evaluation, we prepared pickled cucumber samples with two pasteurization times, 10
and 20 minutes, similar to the samples prepared for the examination of preservability, as shown in
Fig. 1. It was assumed that a longer pasteurization provided a higher killing effect on the microbes
but that the texture might be unfavorably affected. Therefore, two kinds of pickled samples were
evaluated. The pickled cucumbers pasteurized for 10 minutes raised the center temperature to above
75 °C, and those pasteurized for 20 minutes raised the center temperature to above 80 °C.
We aimed to show that the pickles made in Japan following Japanese sanitation guidelines werealso able to produce in Cambodia, especially by using household cooking utensils. Besides, varietiesof cucumber for pickles are assumed to be different between Cambodia and Japan. And the difference
may affect the texture of the pickles, especially with heating samples. It was also important that how
acceptable for Cambodian people both pickles made in Cambodia and Japan. Therefore, we prepared
pickles made in Cambodia and Japan using local products for sensory evaluation.
The samples made in Japan were prepared using ingredients and seasonings purchased in Japan.
The samples made in Cambodia were prepared using ingredients and seasonings purchased in
Cambodia. All sensory was conducted in Cambodia. The panelists evaluated 2 samples with heatingfor 10 and 20 minutes. Twenty panelists evaluated the samples made in Japan at the Royal Universityof Agriculture (RUA) in Phnom Penh, and another 20 panelists evaluated the samples made in
Cambodia at a wet market in Prey Nop district in Preah Sihanouk. The purpose of sensory evaluationin this study is not a comparison pickles made in Cambodia and Japan. We aimed to investigate theacceptability of respective pickles. Therefore, no particular problem occurs when the panels weredifferent between the products in Cambodia and Japan.
The age of the evaluating panelists was 21-28 years (average: 23 years) at RUA and 22-60 years(average: 31 years) at the wet market. The color, sweetness, sourness, saltiness, flavor, texture, andoverall evaluation of each sample were quantified using a five-point hedonic scale (1: strongly dislike,
2: dislike, 3: neutral, 4: like, and 5: strongly like) for the sensory test (preference type).
RESULTS AND DISCUSSION
Examination of the Preservability of the Pickles Prepared with the Heating Process
To investigate the effects of the heating process on the quality of the samples, the nutritional
properties, and microbial quality were examined. During the storage period of 7 days, the Brix value,salt concentration, and pH values were measured (Table 1). The average Brix values of the pickled
cucumbers prepared with and without the heating process were 4.9 and 4.2, respectively. There is asignificant difference in the value of Brix. But the difference in Brix values between pickles withheating and without heating is assumed not to affect the preservation stability of the samples. The
average salt concentrations in the pickles prepared with and without heating were 4.9 and 4.3,
respectively. The Brix value and salt concentration were generally constant throughout the storage
period.
On the other hand, the pH value of the sample prepared with heating was 5.3 on Day 0 and 5.3
on Day 7, and that of the sample without heating was 5.5 on Day 0 and 4.3 on Day 7 (data not shown).
While the pH values of the heated samples were stable, those of the nonheated samples decreased
over time. This indicated that the pickled cucumber prepared without the heating process contained
microorganisms producing acids in the samples.

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Table 1 Nutritional properties of the pickles prepared with and without heating
Measured item

Brix (%)

Salt (%)

pH

Pickles with heating

4.9 ± 0.25 *4.9 ± 0.20

5.3 ± 0.18

Pickles without heating

4.2 ± 0.10 *4.3 ± 0.41

4.6 ± 0.35

(Mean ± standard deviation), the symbol (*) means a significant difference (p < 0.05).

Next, we examined the microbial quality of the pickled cucumbers by measuring the number of
total viable bacteria, coliforms, E. coli, yeasts, and molds. The total viable bacteria on Day 0 weremore than 5.00 log10 and over 7.00 log10 after Day 3. Coliforms were detected in samples from Day
0 to Day 7, and there were samples positive for E. coli. Yeasts and molds were detected in somesamples. A similar result was reported by Muramatsu et al. (2022). From the result of the experiment
for measuring the microbial quality of the pickles without heating, the pickles contained unacceptable
numbers of total viable bacteria on Day 3 for eating. Besides, coliforms, E. coli, yeast, and moldwere detected. Yeast and mold can cause putrefaction. Contamination of E. coli implies a risk of thepresence of other enteric pathogens. Enterohemorrhagic E. coli is classified as a severe hazard, which
is life-threatening for the general population, based on International Commission on MicrobiologicalSpecifications for Foods (Matthews et al., 2017). Taking this into consideration, the pickled
cucumbers without a heating process in this study were not safe for consumption.
On the other hand, coliforms, E. coli, yeasts, and molds were not detected in any of the samples
subjected to the heating process. In addition, total viable bacteria were almost not detected throughout
the storage time. The heating time for pasteurization was decided based on the effect of heating on
the texture of the cucumber. Due to this, the bactericidal effect of the heated samples seemed tochange depending on this condition. However, the number of CFU/g among the samples in whichsome total viable bacteria were detected was at most 5.00 log10. These results indicate that the heat
treatment was effective in killing microbes, but this heating step was barely effective for somemicroorganisms. For food preservation, a sufficient amount of salt and/or a lower pH value is
supposed to be used. Since the samples with the heat treatments, namely, the hot pack filling and 10
minutes of pasteurization, maintain their qualities sufficiently until Day 7, the process of adding heat
treatments may be a suitable procedure to make safe products that do not change the traditional taste.
Sensory Evaluation of the Samples Made in Japan and Cambodia
To investigate the acceptability characteristics of pickled cucumbers during the heating process,sensory evaluation tests were performed. Fig. 2 shows the results of the sensory evaluation tests ofsamples (a) made in Japan and (b) made in Cambodia. The average values of each sensory item forthe pickled cucumbers pasteurized for 10 min and 20 min made in Japan ranged from 2.8-3.6 and2.4-3.8, respectively (Fig. 2a). In the overall evaluation, both the 10- and 20-minutes pasteurization
samples scored approximately 3.0. There was no significant difference in accordance with the paired
t-test (5% significance level) between all characteristics, except for texture. The average value of
texture for the samples with 10 min of pasteurization was higher than that of the sample with 20 minof pasteurization, which was 3.4 and 2.4. This result showed that longer pasteurization affected the
texture of the cucumber. However, the overall evaluation scores were both approximately 3.0. Thisis a representative evaluation of whether or not the sample was considered acceptable. The results
indicated that the samples made in Japan were considered acceptable in the Cambodian market.
Figure 2b shows the results of the evaluation of pickled cucumbers with the heating process made in
Cambodia. The average scores of all evaluated items ranged from 2.6-3.6 and 2.3-4.0, respectively.
Except for color and texture, there were no significant differences between the evaluated items
according to a paired t-test (5% significance level).
Because the average score for color was close to 4.0, Cambodian panelists preferred the colorof the sample with pasteurization for 20 min made in Cambodia. The texture of the sample withpasteurization 20 min was given a lower rating score of 2.3. The heating treatment presumably causedⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2023) 14-1

a change in the texture of the cucumbers. Although the average values of sourness and flavor forboth samples did not exceed 3.0, the overall evaluation score given by the panelists was nearly 3.0.
Based on the results, the samples pasteurized for 10 min and 20 min made in Cambodia may also be
acceptable in the Cambodian market. In addition, the t-test for each characteristic used the averagescore between the samples made in Japan and Cambodia with 10 and 20 minutes of pasteurization.
There were no significant differences. Since a similar evaluation was obtained, there did not seem tobe differences in quality.
a

Color
5
4
3
2
1

Overall
Evaluation

Texture*Overall
Evaluation

Sweetness

Texture*Sourness

FlavorColor*
5
4
3
2
1

b

Sourness

Flavor

Saltiness

Pasteurization 10 min
Pasteurization 20 min

Sweetness

Saltiness

Pasteurization 10 min
Pasteurization 20 min

The symbol (*) means a significant difference (p < 0.05).

Fig. 2 Sensory evaluation of pickled cucumbers with pasteurization for 10 min and 20 min:(a) samples made in Japan and (b) samples made in Cambodia
Most Cambodian panelists commented that there was a lack of sourness for these pickled
cucumbers. Some panelists commented that sweetness and saltiness were lacking. If thesecharacteristics were to be improved, the overall evaluation would receive a higher rating. The heating
treatments, hot pack filling, and pasteurization were effective in killing microorganisms and wererecommended for pickle production. Although a longer heating process affected the texture (softness)of the pickled cucumbers, they received a nearly normal score on the overall evaluation from theCambodian panelists. From the results of the sensory evaluation and questionnaire survey, there was
the possibility of acceptance of the pickled cucumbers prepared with pasteurization made either inJapan or Cambodia by the Cambodian panelists; however, further improvement in the softness of the
pickles was commented upon. Regarding improvements for the product, some food additives arerecommended as they do not affect the softness of pickles and are effective in keeping
microbiological safety.
CONCLUSION
To investigate the effect of the heating process on the preservative properties of pickled cucumber,pickles using a traditional Cambodian were prepared. While the products that did not undergo theheating process were highly contaminated by microbes, the products prepared with the heatingprocess did not show the presence of coliforms, E. coli, yeasts, and molds for 7 days at 30 °C. This
result showed that the heating process killed many spoilage microbes, including foodborne pathogens.
The heating process is considered to be effective in providing safe products and extending shelf life.
Sensory evaluation tests were conducted in Cambodia. From the results, there was the possibility ofacceptance of the pickled cucumber prepared with the heating process by the Cambodian people.
There were comments from panelists that further improvement in the softness of the pickles wasneeded.
REFERENCES
Chrun, R., Hosotani, Y., Kawasaki, S. and Inatsu, Y. 2017. Microbiological hazard contamination in fermentedⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2023) 14-1

vegetables sold in local markets in Cambodia. Biocontrol Science, 22 (3), 181-185, Retrieved from DOI
https://doi.org/10.4265/bio.22.181
Matthews, K.R., Knile, K.E. and Montville, T.J. 2017. Food Microbiology (4th ed). American Society for
Microbiology, ASM Press, ISBN 978-1-555-81938-5, USA.
Ministry of Health (MoH). 2016. Press release of the Ministry of Health of the Kingdom of Cambodia on theprevention of health problems caused by food poisoning. Cambodia, Retrieved from URL www.cdcmoh.
gov.khMuramatsu, S., Uchino, M., Tanikoka, Y., Sorm, S., Oka, D., Muramatsu, Y., Nakajima, T., Sekido, M.,
Nakamura, T., Chay, C. and Mihara, M. 2020a. Evaluation of bacterial contamination levels in pickles soldat wet market in Cambodia, Part 1, In case of samples from Kampong Cham and Phnom Penh. International
Journal of Environmental and Rural Development, 11 (1), 115-120, Retrieved from DOI https://doi.org/10.
32115/ijerd.11.1_115
Muramatsu, S., Uchino, M., Sorm, S., Tanikoka, Y., Oka, D., Muramatsu, Y., Nakajima, T., Sekido, M.,
Nakamura, T., Chay, C. and Mihara, M. 2020b. Evaluation of bacterial contamination levels in pickles soldat wet market in Cambodia, Part 2, Detection of several food-poisoning bacteria of 48 samples from Phnom
Penh. International Journal of Environmental and Rural Development, 11 (1), 121-126, Retrieved from
DOI https://doi.org/10.32115/ijerd.11.1_121
Muramatsu, S., Sorm, S., Uchino, M., Sekido, M., Muramatsu, Y., Oka, D., Tanioka, Y., Nakamura, T.,
Nakajima, T., Arimitsu, M. and Mihara, M. 2022. Microbial behavior in Cambodian homemade-style
pickles. International Journal of Environmental and Rural Development, 13 (1), 169-175, Retrieved from
URL https://iserd.net/ijerd131/13-1-27.pdf
Thompson, L., Vipha, J., Hok, L. and Ebnar, P. 2021. Towards improving food safety in Cambodia, Current
status and emerging opportunities. Global Food Security, 31, Retrieved from DOI https://doi.org/10.1016/
j.gfs.2021.100572Ⓒ ISERD

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Research article
erd

Reuse of Unavailable Phosphate in Soils Using Solar CellPowered Electrokinetic Treatment
NARONG TOUCH*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Email: nt207118@nodai.ac.jp

TAKAHIKO NAKAMURA
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Received 18 December 2022

Accepted 10 May 2023(*Corresponding author)

Abstract Electrokinetic treatment (ET) is widely used for soil remediation, specifically forremoving heavy metals from soil. Till date, we have focused on the nutrients released in soils
using a solar cell-powered ET, which contributes to increasing the productivity of organic
farming. Previously, when a 1.5 V solar cell was used in ET, the release of ammonium ionsand the growth of microorganisms were observed. However, no release of phosphate ions wasobserved. Thus, it is presumed that a 1.5 V solar cell is insufficient to release phosphate insoils. Therefore, this study aims to examine the effects of solar cell voltage on the release ofphosphate in soils. In laboratory experiments, an anode (oxidation reaction) and a cathode(reduction reaction) were installed in andosol mixed with cow manure compost, and a 3 or 6
V solar cell was used to produce an electric current between the two electrodes. Sixty-two days
after the current generation, the chemical properties of the soil were measured. The results
suggest that soil redox conditions can be controlled by changing the solar cell voltage. Fromthe pH distributions, a higher voltage of solar cells was used and a large change in pH was
obtained. Furthermore, a decrease in soil redox potential was obtained by increasing the solar
cell voltage. From the phosphate distributions, a 6 V solar cell is required to release phosphatein soils. It is recommended that applying ET powered by a 6 V solar cell (potential gradient:0.12 V/cm) facilitates nutrient release in soils, which is the most important factor in organic
farming.
Keywords solar cell, voltage, electrokinetic treatment, soil reduction, phosphate, organic
farming

INTRODUCTION
According to the Ministry of Agriculture, Forestry, and Fisheries of Japan, organic farming is a
strategy to achieve sustainable agriculture. The government has proposed many countermeasures tofacilitate organic farming (MAFF, 2019). Hence, productivity-enhancing technologies andimplementation systems are required.
In organic farming, because nutrients are supplied by the decomposition of organic matter,
facilitating this decomposition is crucial in providing higher productivity. As the decomposition oforganic matter depends on the Soil Chemical Environment (SCE), controlling SCE is imperative inenhancing the productivity of organic farming. According to Yan and Hou (2018), understanding
SCE is useful for ensuring healthy soil that can sustain crop production. Therefore, to provide higher
productivity in organic farming, a technology that can control the SCE to activate bacterial
metabolism for enhancing the decomposition of organic matter is required.
Electrokinetic Treatment (ET) is a technology for generating a low-intensity electrical field
between two electrodes buried in soils by applying a direct current or constant voltage (an external
power supply). ET has been widely used for a few decades to remove contaminants, such as dyes
and heavy metals (Hanay et al., 2009, Almomani and Baranova, 2013). Kim et al. (2010) reportedchanges in soil pH and electrical conductivity owing to ET application in soil. Additionally, ET canⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2023) 14-1

be used to control SCE. Previously, a battery was used to apply a direct current or a constant voltage,
but now a solar system is also used as an external power supply of ET (Liu et al., 2020). However, alarge potential gradient, for example, 3-5 V/cm, is commonly applied to soils, which causes large
variations in the SCE. This, in turn, influences soil biology, limiting the decomposition of the organic
matter.
We thought that by decreasing the potential gradient (i.e., the solar cell voltage), the effects on
soil biology could be reduced. As such, in our previous study (Touch and Nakamura, 2022), a 1.5 V
solar cell (potential gradient: 0.03 V/cm) was used in ET. Following the application, the release ofammonium ions and the growth of microorganisms were observed, which would also be useful fororganic farming. However, no release of phosphate was observed. Thus, a 1.5 V solar cell wasinsufficient to release phosphate in soils. As increasing the voltage of the solar cell facilitates
reactions on the electrode surface in soils, using a higher voltage of the solar cell may cause therelease of phosphate.
OBJECTIVE
This study aims to examine the effects of solar cell voltage on the release of phosphate in soils.
Specifically, we examined changes in electrode potential by increasing the solar cell voltage, the soil
redox conditions (pH and redox potential), and nutrient release following the application of solar
cell-powered ET. This was conducted by applying ET to andosol mixed with cow manure compost
with a generated electric current for two months.
METHODOLOGY
Experimental Procedures and Operations
Commercial products, i.e., dried cow manure compost (fully matured, nitrogen 1.09%, phosphate
2.29%, potassium 2.28%) and andosol (volcanic derived soils with high contents of organic matterand aluminum compounds), were used in laboratory experiments. First, the compost was mixed with
andosol at a volume ratio of 47% (generally, 40-60% was used). The mixture was then used in theexperiments, which were conducted under three conditions without treatment (Control), treated witha 3 V solar cell (SC-3V), and treated with a 6 V solar cell (SC-6V). For Control, an electrode wasinstalled in the mixture to measure the soil potential continuously (Fig. 1a).

⊕

Voltage logger⊝ (for potential measurement)(a) Control(c) Electrode: carbon fibers

2 cm Tap water (prevention of soil drying by evaporation)

14 cm

Reference electrodeCow manure compost-mixed andosol
Voltage logger(b) SC-3V or SC-6V⊝
Solar cell (3 or 6 V)
1ΩRemoval of 1 cm-surface soil before soil sampling⊕⊝⊕ Voltage logger
⊝

3 cm

14 cm

(d) Soil sampling
Cathode (10 cm ×10 cm)

Anode (10 cm ×10 cm × 2)

49 cm
Soil sampling at intervals of 5 cm
1 cm

56 cm
Plastic container: 14 cm × 56 cm × 26 cm

Fig. 1 Experimental devices and operationsⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2023) 14-1

For SC-3V or SC-6V, two electrodes were installed in the soil layer (Fig. 1b). To generate anelectrical current, one electrode was connected to the positive terminal, and the other was connectedto the negative terminal of a solar cell (3 V or 6 V) using the circuit shown in Fig. 1b. Different
voltages of the solar cells were obtained by connecting a 1.5 V solar cell (Tamiya, 1.5 V-500 mA) in
series. An external resistance of 1 Ω was loaded between the anode and solar cell. The electrodematerial was carbon cloth (News Company, PL200-E), which was heated at 500°C for 1 h before
using it, as Nagatsu et al. (2014) suggested. The heated carbon cloth with a width of 10 cm and heightof 10 cm was separated into fibers to form a brush-type electrode. The electrode was placed in aplastic net (1-mm mesh) and installed in the soil layer (Fig. 1c). The anode surface area was 0.02 m2(10 cm × 10 cm × 2), while the cathode surface area was 0.01 m2 (10 cm × 10 cm). A smaller cathodesurface area compared with the anode surface was made to obtain a higher reduction at the cathode.
After installing both electrodes, the container was filled with tap water. Consequently, a 2 cm
water layer was formed on the soil surface, which can prevent the soil from drying owing toevaporation. The voltage at both terminals of the external resistance was measured every 15 minusing a voltage logger (T&D Corp., MCR-4V) to calculate the circuit current according to Ohm’slaw. The current density was obtained by dividing the current by the surface area of the anode, i.e.,
0.02 m2. The electrode and a reference electrode (Toyo Corp., W-RE-7A) placed in the soil layer
were connected to the voltage logger using the circuit shown in Figs. 1a and 1b to measure theelectrode potential.
Analyses
Two months after the experiments started, soil sampling was conducted. The surface soil of 1 cm
was removed, and pH and redox potential (ORP) were measured using a pH/ORP meter (Horiba, D50) at intervals of 5 cm from the anode. Soil samples were collected (Fig. 1d) after pH and ORP
measurements. Furthermore, each soil sample was centrifuged at 6000 rpm for 5 min (As One, CN2060) to extract pore water. Finally, each ion concentration in pore water (phosphate, PO43-;
ammonium, NH4+; potassium, K+) was measured. The ion concentration was measured using
PACKTEST (Kyoritsu Corp., WAK), except for K+ concentration which was measured using a K+
meter (Horiba, K-11).
RESULTS AND DISCUSSION
Variations of Electrode Potential with Different Voltages of Solar Cells

Electrode potential (V)Figure 2 depicts temporal changes in the electrode potential during the experiments. For SC-3V and
SC-6V, the electrode potential refers to the potential of the cathode in which a reduction reaction
occurs. For Control, the electrode potential decreased temporally, and mostly stabilized at -0.48 V
on Day 62 after the experiment started. The low potential was observed because cow manure compost
was used, and it took approximately two months for its reduction. On Days 50-60, the peak electrodepotential ranged from -0.70 V (night-time) to -0.94 V (daytime) for SC-3V and -0.90 (night-time) to-1.14 V (daytime) for SC-6V.
0.5

Control

SC-3V

SC-6V

0
-0.5
-1
-1.5
Connection failure

-2
0

5

10

15

20

25
30
35
40
Operation time (day)

45

50

55

60

Fig. 2 Comparison of electrode potential with and without using the solar cell
Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2023) 14-1

1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0

SC-3V

Current density (A/m2)

Current density (A/m2)

Compared with the Control, more reduction was obtained when a high-voltage solar cell wasused, and there was a large decrease in the electrode potential when the solar cell voltage wasincreased from 3 V to 6 V. This is because the reactions on the electrode are more active owing toan increase in electrical current when the voltage of the solar cell increases. As shown in Fig. 3, thecurrent density was approximately 0.06-1.30 A/m2 for SC-6V and 0.01-0.61 A/m2 for SC-3V. The
system current can vary using different solar cell voltages, that is, by changing the solar cell voltage,soil reduction can be controlled.

SC-6V

0.14
0.12

SC-3V

SC-6V

0.1
0.08
0.06
0.04
0.02
0

0

5 10 15 20 25 30 35 40 45 50 55 60 65
Operation time (day)25

30

35 40 45 50 55
Operation time (day)60

65

Fig. 3 Comparison of current densities generated by SC-3V and SC-6V
Changes in Redox Conditions at the End of the Experiment
Figure 4 shows changes in pH and ORP due to the current generation at the end of the experiment.
In Fig. 4, 0 and 49 cm refer to the soil samples at the anode (oxidation) and cathode (reduction),
respectively (SC-3V and SC-6V). In Fig. 4a, the pH at the anode was 6.21 for Control, which
decreased to 6.18 for SC-3V and 3.56 for SC-6V. These decreases were caused by oxidation reactions
at the anode. However, the pH at the cathode was 6.44 for Control, which increased to 6.72 for SC3V and 7.11 for SC-6V. These increases were caused by reduction reactions at the cathode. From the
pH distributions, a distance of 25 cm from the electrode were influenced by the current generation
using a 3 V or 6 V solar cell.

Fig. 4 Changes in pH and ORP due to current generation at the end of the experiment
Decreased soil ORP was observed on using a 3 V or 6 V solar cell compared to Control, except
at the anode of SC-6V. The soil ORP ranged from -150 to -112 mV for Control and -190 to -150 mV
for SC-3V and SC-6V, respectively (Fig. 4b) which disagrees with our previous study (Touch andNakamura, 2022) that reported an increase in ORP when using a 1.5 V solar cell. By increasing thesolar cell voltage, a large decrease in soil ORP can be obtained.
Nutrient Release Owing to Current GenerationⒸ ISERD

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The distributions of ammonium (NH4+), phosphate (PO43-), and potassium (K+) are shown in Fig. 5.
The release of NH4+ was observed, which parallels our previous study (Touch and Nakamura, 2022).
A 1.8- to 2.3-fold increase in NH4+ concentration was observed within 5−20 cm of the anode (Fig.
5a). However, no significant difference was observed between SC-3V and SC-6V at 10−30 cm of
the anode, suggesting that a 3 V solar cell is enough to release NH4+ in soils. The increase in NH4+
concentration was low near the cathode compared with that near the anode. This is because of the
reduction reactions near the cathode, which induce denitrification. In Particular, the NH4+
concentrations in SC-6V were lower than those of Control within 5 cm from the cathode.
No differences in PO43- concentration were observed between Control and SC-3V (Fig. 5b),suggesting no release of PO43- despite using a 3 V solar cell. Interestingly, a 2- to 7-fold increase in
PO43- concentration was observed within 20−45 cm of the anode for SC-6V. Within 15 cm of theanode, no increase in PO43- concentration was observed. This was because of the release of calcium
ions at this distance (Fig. 5c) following the decrease in pH (Fig. 4a), leading to the fixation of PO43by the calcium ions. An increase in K+ concentration was also observed. Compared with the Control,
maximum 1.3-fold (SC-3V) and 1.6-fold (SC-6V) increases in K+ concentration were observed
within 5-20 cm of the anode (Fig. 5d). However, a smaller increase in K+ concentration was observed
near the cathode (20-45 cm of the anode), except for the cathode. A decrease in sediment pH induced
the dissociation of metal compounds, causing the release of metal ions (e.g., Ca2+, K+), which can fix
PO43- in littoral sediments (Touch et al., 2017; Touch et al., 2018).
In summary, applying ET powered by a 6 V solar cell can release nutrient compounds in soils,
such as NH4+, PO43-, and K+. These releases are caused by the enhancement of organic matterdecomposition in soils and the decrease in soil pH following ET application.

Fig. 5 Comparison of nutrient concentration distributionsⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2023) 14-1

CONCLUSIONS
Laboratory experiments were conducted to examine the effects of solar cell voltage on the release ofphosphate in soils. Specifically, we examined changes in the electrode potential by increasing thesolar cell voltage, the soil redox conditions (pH and redox potential), and nutrient release after
applying solar cell-powered ET to andosol mixed with cow manure compost. The system current
increased as the solar cell voltage increased, which effectively induced reactions on the electrode.
By changing the solar cell voltage, electrode potential, and soil redox conditions were controlled.
From the pH distributions, 25 cm from each electrode was influenced by the application of ET. A
larger influence was obtained with a higher voltage of the solar cell. From the ORP distributions, alarge decrease in soil ORP was obtained by increasing the solar cell voltage. Hence, soil redox
conditions can be varied using solar cells of different voltages. From the PO43- distributions, a 6 V
solar cell is required to release PO43- in soil. It was also highlighted that decreasing the pH near theanode decreased the PO43- concentration. Finally, applying ET powered by a 6 V solar cell (potential
gradient: 0.12 V/cm) facilitates nutrient release in soils.
ACKNOWLEDGMENTS
The authors gratefully acknowledge partial funding from the Tokyo University of Agriculture:
FY2021 Grant-in-Aid for Sustainable Agriculture Research Projects. The authors would like to thankthe students of the Rural Environmental Engineering Laboratory, Tokyo University of Agriculture,
for their efforts in collecting data.
REFERENCES
Almomani, F. and Baranova, E.A. 2013. Kinetic study of electro-Fenton oxidation of azo dyes on boron-doped
diamond electrode. Environmental Technology, 34 (11), 1473-1479, Retrieved from DOI https://doi.org/
10.1080/09593330.2012.758644
Hanay, O., Hasar, H., Koçer, N.N. and Ozdemir, O. 2009. Removal of Pb from sewage sludge byelectrokinetics, Effect of pH and washing solution type. Environmental Technology, 30 (11), 1177-1185,
Retrieved from DOI https://doi.org/10.1080/09593330903144058
Kim, K.J., Cho, J.M., Baek, K., Yang, J.S. and Ko, S.H. 2010. Electrokinetic removal of chloride and sodium
from tidelands. Journal of Applied Electrochemistry, 40 (6), 1139-1144, Retrieved from DOI https://doi.
org/10.1007/s10800-010-0082-1
Liu, R., Wang, H., Liu, Z. and Tao, C. 2020. Electrokinetic remediation with solar powered for electrolytic
manganese residue and researching on migration of ammonia nitrogen and manganese. Journal of Water
Process Engineering, 38, 101655, Retrieved from DOI https://doi.org/10.1016/j.jwpe.2020.101655
Ministry of Agriculture, Forestry and Fisheries of Japan (MAFF). 2019. Current situation and policy on organic
agriculture in Japan, Retrieved from URL https://www.maff.go.jp/e/policies/env/sustainagri/
attach/pdf/organicagri-1.pdf
Nagatsu, Y., Tachiuchi, K., Touch, N. and Hibino, T. 2014. Factors for improving the performance of sedimentmicrobial fuel cell. Journal of Japan Society of Civil Engineers Ser B2 (Coastal Engineering), 70 (2), 10661070, Retrieved from DOI https://doi.org/10.2208/kaigan.70.I_1066 (in Japanese)
Touch, N. and Nakamura, T. 2022. Benefits of applying microbial fuel cell technology in organic farming forsustainable agriculture. International Journal of Environmental and Rural Development, 13 (2), 49-54.
Touch, N., Takata, H. Yamaji, S. and Hibino, T. 2018. Changing organic matter characteristics of littoral
sediment by solar cell-combined sediment microbial fuel cell. International Journal of Environmental
Science and Development, 9 (3), 62-66, Retrieved from DOI 10.18178/ijesd.2018.9.3.1074
Touch, N., Yamaji, S., Takata, H. and Hibino, T. 2017. Solar cell-combined sediment microbial fuel cell forpreserving sediment and water environments. International Journal of Environmental Protection, 7 (1), 3745, Retrieved from URL http://paper.academicpub.org/Paper?id=17530
Yan, B. and Hou, Y. 2018. Soil chemical properties at different toposequence and fertilizer under continuous
rice production, A review. IOP Conference Series: Earth and Environmental Science, 170 (3), 032107,
Retrieved from URL https://iopscience.iop.org/article/10.1088/1755-1315/170/3/032107/pdfⒸ ISERD

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Research article
erd

Research
Impact of a Drip Irrigation System on Planning andarticleManagement of Water Delivery in a Large-Scale Irrigation
Scheme in Morocco

DAYYABU MUHAMMAD ZAHARADDEEN*
United Graduate School of Agricultural Sciences, Tottori University, Tottori, Japan
Email: talk2deenee@yahoo.com

KATSUYUKI SHIMIZU
Faculty of Agriculture, Tottori University, Tottori, JapanYURI YAMAZAKI
Faculty of Agriculture, Tottori University, Tottori, Japan

VINAY NANGIAInternational Center for Agricultural Research in the Dry Areas (ICARDA), Rabat, Morocco

ANAS MANSOURIInternational Center for Agricultural Research in the Dry Areas (ICARDA), Rabat, Morocco

MOHAMED BELAARABI
Regional Office for Agricultural Development in Tadla (ORMVAT), Morocco

LAHCEN OUSSTOUS
Regional Office for Agricultural Development in Tadla (ORMVAT), Morocco
Received 19 January 2023

Accepted 10 May 2023(*Corresponding Author)

Abstract Increasing water scarcity is lowering the agricultural production of the Tadla region
in Morocco. This necessitates the Moroccan government to actively stimulate farmers about
converting their irrigation systems from surface irrigation (furrow) to drip irrigation andsubsidize the investment costs by 80%–100%. Therefore, this study aimed to clarify the impactof the drip irrigation system on the planning and management of water delivery after theconversion program from surface (furrow) irrigation to drip irrigation in the Beni Amir
irrigation district on the right side of the Tadla region. The water management practices before
and after conversion were gathered through discussions and interviews with officials andrepresentatives of the management team responsible for the study irrigation scheme. An open
questionnaire survey was also conducted, focusing on farmers' irrigation management
practices such as on-farm water distribution methods, application rate, water adequacy, andequity water satisfaction level before and after conversion, and the results were analyzed bypaying attention to their farms' upstream, midstream, and downstream locations. The analysis
reveals that most of the interviewed farmers indicated satisfaction with equitable water
distribution. Some variations in the water management system may occur due to theconversion project, such as an increase in irrigation time and increased cost and labor in water
management. These will have an impact on the CDA's (Agriculture Development Center)overall water management monitoring and planning at the tertiary canal, as well as farmers'
water management labor.
Keywords water scarcity, surface irrigation, drip irrigation, water management

INTRODUCTIONⒸ ISERD

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Morocco is among the most water-stressed countries in the world. Since the late 1970s, Morocco has
seen its water inflows (from surface water) decline, from an annual average of 22 billion m3 between
1945 and 1978 to an annual average of 15 billion m3 between 1979 and 2018 (World Bank, 2022).
The main strategy for adaptation to climate change in this region is the conversion from surface
irrigation to drip irrigation. Consequently, the region needs rational and sustainable management ofirrigation water. One of the solutions to save water in this area is to optimize irrigation inputs basedon water availability and agricultural water demand according to the real needs of crops and inagreement with their phenological development. This necessitates the Moroccan government toactively stimulate farmers about converting their irrigation systems from surface irrigation (furrow)to drip irrigation and subsidize the investment costs by 80%–100%. Farmers owning more than 5 hacan apply for a subsidy of 80%, while those with 5 ha or less can apply for subsidies of 100%. Thesesubsidies are part of the National Irrigation Water Saving Plan of 2007, which was summarized in
the Green Morocco Plan in 2008. The National Irrigation Water Saving Plan aims to counterbalance
the water deficits that the country faces. According to the plan, stimulating the conversion of 550,000
ha (of these, 217,940 ha will be through collective conversion and 332,060 ha through individual
conversion (Belghiti, 2009)).
The Irrigation Management Transfer (IMT) of the 1970s attempted to establish the water user’s
association (WUA) after government-built irrigation facilities and transferred management to the
WUA. Also, in participatory irrigation management (PIM) proposed by the World Bank since the1990s, beneficiary farmers' participation in all irrigation development processes (construction,
operation, management, and maintenance) has been required (Samad and Vermillion, 1999). Many
researchers have proposed ways to manage and regulate the allocation and distribution of commonly
held resources by human communities. Elinor Ostrom's framework has inspired a robust commons
literature that investigates how human communities manage and regulate the allocation anddistribution of commonly held resources. The earliest, and perhaps most well-known, strand in thiscommon’s literature deals with the distribution of natural resources, with an emphasis on the use or
consumption of these resources (Azergun, 2020). Eight frameworks were designated by Ostrom forequitable and effective management of the commons (the commons are those things or resources thatpeople own together), which requires both effective institutional arrangements and shared social
capital among system participants (Ostrom, 2009; Ostrom et al., 2003).
OBJECTIVE
A brief survey was conducted to clarify the impact of drip irrigation on the planning and managementof water delivery after the conversion program from surface to drip irrigation at the Beni Amir
irrigation scheme in the Tadla region. The data collected and the results analyzed can be used as
preliminary findings to guide future research.
METHODOLOGY
Study Area
The Beni Amir irrigation district is located on the right side of the irrigated perimeter of the Tadla
region in the southwest of Morocco and has a total irrigated area of 34,000 ha. The outline of theBeni Amir irrigation district is shown in Fig. 1. The study area is in the arid and semi-arid regions,
receiving about 300 mm of rainfall per year, most of which is received during the rainy season from
November to March. The main crops are alfalfa, olives, maize, fruits (citrus), sugar beets, wheat, andvegetables. The irrigation water source is the Ahmed El Hansali Dam reservoir. Water released fromthe dam is distributed to the fields via the main, lateral (14 canals), and tertiary canals. Surface
irrigation has been commonly practiced, and drip irrigation has been recently introduced under theGreen Morocco Plan.

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IJERD – International Journal of Environmental and Rural Development (2023) 14-1

Fig. 1 The outline of the study area
The red line is the main canal, and the numbers represent farm blocks served by 14 lateral canals.

Data Collection and Analysis Methods
Data were gathered through discussions and interviews with officials and members of the irrigation
scheme's management team. The layout of the irrigation system of the Beni Amir irrigation district
was collected from the Regional Office on Agriculture Enhancement, Tadla (ORMVAT). Regarding
the management and operation of the irrigation organization, a guided discussion was held with the
responsible management team, which is Watershed Management Agency (ABHOER). An open
questionnaire survey with 13 farmers (4 farmers at upstream, 5 farmers at midstream, and 4 atdownstream locations) was conducted. The information gathered consists of farmers’ socioeconomic
conditions, farming methods, satisfaction levels for water sufficiency and equity, and some of theirchallenges regarding the newly introduced drip irrigation methods. The questions were asked
individually through a face-to-face interview with farmers in the study of irrigation scheme. The fieldsurvey was conducted in September 2022, and it was an extreme drought year when compared withthe last 20 years' record of rainfall data. Also, Farmers were unable to obtain water from the dam dueto the drought, so they dug deeper wells up to 500 meters to get water. This eventually led to an
overuse of groundwater, which has resulted in decreased quality and quantity for many farmers. The
water management structure and distribution systems of the Beni Amir irrigation scheme were
investigated before the conversion.
The irrigation scheme has established water management organizations in which government
agencies control, plan, and decide on water distribution methods for beneficial farmers. This is a rarecase in the management of public irrigation schemes. Although there is WUA, it does not function
regarding PIM. In an ideal situation, WUA, which is composed of beneficiary farmers, takes on the
responsibilities of operation, management, and maintenance of the irrigation systems after theirdevelopment through the PIM concept. Hence, it may be required to investigate how equitable water
distribution was accomplished without the PIM concept of water management. Elinor Ostromsuggests 8 frameworks to initiate sound collective action for equitable and sustainable commonsmanagement, which it seeks to employ in various scales and configurations. Therefore, Ostrom’s
frameworks were used to diagnose the current water management system of the Beni Amir irrigation
scheme.
Water Management System and PlanningIn each irrigation season, the water delivery plan from the dam to the Beni Amir irrigation district isdecided in consultation with ABHOER, which is responsible for water resources management in the
Tadla region, and ORMVAT, which is responsible for water distribution planning and managementin the irrigation districts of the Tadla region. The amount of water to be distributed is communicatedto the Agriculture Development Center (CDA), which is responsible for managing the distributionof water to the tertiary canals. The CDA coordinates the farmers' requests for water distribution,
determines the date, time, and volume of water to be distributed to each field, and distributes water
to the tertiary canals. The responsibility of water distribution in the field canals is left to each farmer
during his scheduled irrigation period, which is decided by the ORMVAT and ABHOER (KatsuyukiⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2023) 14-1

et al., 2022). The schematic diagram of water supply and management responsibilities is shown in
Fig. 2.

Fig. 2 The schematic diagram of water supply and responsibilities for management
RESULTS AND DISCUSSIONS
General Evaluation of Water Management Concerning Ostrom’s 8 Frameworks
for Managing the Commons
The survey result in Fig. 3 revealed that even though the study irrigation scheme is run by governmentorganizations, the majority of farmers who were surveyed expressed satisfaction with how fairly
water is distributed and managed. As a result, it is necessary to examine how equitable water
distribution was accomplished without the PIM concept of the water management system.

Fig. 3 Survey result of farmer’s satisfaction with equity water distribution
The Beni Amir irrigation scheme's adherence to the eight frameworks for managing thecommons with the rules employed in water management and planning will help explain how it wasable to sustain itself without using the PIM concept while still providing fair water distribution tofarmers.
Table 1 demonstrated that the 8 management frameworks proposed by Elinor Ostrom had been
adhered to. This supported the irrigation system's successful management and equitable water
distribution to farmers.

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Table 1 Eight frameworks of managing the common by Elinor Ostrom
Nos.

8 Frameworks of managing the common by Elinor Ostrom

1
2
3
4
5
6
7
8

Commons need to have clearly defined boundaries
Rules should fit local circumstances
Participatory decision-making is vital
Commons must be monitored
Sanctions for those who abuse the commons should be graduatedConflict resolution should be easily accessible
Commons need the right to organize
Commons work best when nested within larger networks

ResultYes
Yes
Yes (by Govt)
Yes
Yes (by Govt)
Yes
Yes (by Govt)
Yes (by Govt)

Effect of Change to Drip Irrigation on Water Management
The conversion is done in such a way that farmers utilize the tertiary canals to get and store water in
the newly constructed small pond for drip irrigation purposes. The storage capacity of the pond forfarmers with less than 5 ha is 3,200 m3 (20 m x 20 m x 8 m) and is connected to the tertiary canal as
the main water source. Water is temporarily stored before being pumped to the overhead tank andused for drip irrigation. Therefore, farmers can store water during their scheduled rotation time anduse it for drip irrigation as needed.
The findings of this study indicated that the conversion project may cause certain changes to thewater management system, which could have an impact on the CDA's and farmers' long-termmonitoring and planning of water use. The changes are highlighted below.
Storing More Water in the Newly Constructed Small Ponds for Drip Irrigation
Farmers have a chance to store enough water more than is required during their existing scheduled
rotation time. If before the conversion, 3 hours were scheduled for each farmer, now that farmers canstore water, they may need at most 24 hours (30 l/s X 3600 X 24 = 2,592 m 3) to be able to haveenough water to pump to their overhead tank. Therefore, the average water rotation time will
increase, making it difficult to adjust with non-converted farmers to achieve equity in water
distribution during times of scarcity.
The ability of farmers to divert and store adequate water during their unscheduled rotation phase
may lead to an increase in water theft. Therefore, CDA will increase the level of supervision andmonitoring. Consequently, the CDA's labor and water management costs will rise as well. However,when there is enough water in their ponds, farmers can schedule their irrigation period as desired.
Farmers will then spend less time managing their water resources.
Change in the Cropping Pattern
According to the survey, most of the farmers’ cropping patterns changed after the conversion to drip
irrigation. Before the conversion, farmers usually plant cereal and forage crops such as maize, alfalfa,
etc. to provide food for their livestock. After the conversion, farmers are now planting fruit trees,
particularly citrus and olive trees, as they are high-value crops and to compensate for the running
expenses of drip irrigation. The non-converted farmers may require more water to irrigate their cereal
and forage crops through surface irrigation. Since the CDA allocates an equivalent amount of water
to farmers before the conversion, the water allocation plan will change with the conversion. This will
also affect the water scheduling plans of both the CDA and the farmers to suit each farmer’s irrigation
method.
Farmers’ Low Capacity for Using Drip IrrigationⒸ ISERD

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The survey showed that many farmers have limited knowledge about the operation and maintenanceof drip irrigation. This makes them reluctant to introduce the conversion project. The partial
conversion of some farms may require regular monitoring and supervision to ensure proper
scheduling is followed. This will increase the CDA's water management labor and costs.
Increase in Groundwater Use
Farmers are now able to pump water from wells and store it in their small ponds. This will increase
groundwater withdrawal and may lead to groundwater overexploitation. The impact of theoverexploitation of groundwater resources on their quantity and quality can be witnessed by many
farmers, as discussed during the survey. Also, farmers increased the frequency and duration of their
irrigation after the conversion project. Due to the extreme drought of the year 2022, farmers cannot
get water from the canals. Therefore, most farmers try to deepen their wells to about 500 m to getadequate water to store in their small ponds.
CONCLUSION
The impact of the drip irrigation system on water delivery planning and management following theconversion of surface (furrow) irrigation to drip irrigation was studied. Based on the findings, thefollowing were concluded.
(1) Farmers had equitable water distribution, as most farmers interviewed expressed satisfaction withequitable water distribution. Compliance with Ostrom’s eight frameworks may aid in the successful
management of the irrigation system and equitable water distribution to farmers.
(2) Some changes occur as a result of the conversion project, which may have an impact on the
CDA's and farmers' overall water management monitoring and planning. These include as follows;(i) Storing more water in the newly constructed small ponds for drip irrigation(ii) Change in the cropping pattern(iii) Farmers’ low capacity for using drip irrigation(iv) Increase in groundwater use
ACKNOWLEDGMENTS
This work was supported by IPDRE, Tottori University.
REFERENCES
Azergun, N. 2020. Resource allocation at an income-sharing community, An application of Elinor Ostrom's
commons framework. Economic Affairs, 40 (3), 367-384, Retrieved from DOI https://doi.org/10.1111/ecaf.
12423
Belghiti, M. 2009. Le plan national d’économie d’eau en irrigation (PNEEI), Une réponse au défi de lararéfaction des ressources en eau. Hommes Terres et Eaux, Revue Marocaine des Sciences et Techniquesdu Développement Rural, 39, 34-36, Retrieved from URL http://www.abhatoo.net.ma/maalamabibliographique/developpement-economique-et-social/developpement-economique/agriculture/ressources-en-eau-et-lutte-contre-la-secheresse/le-plan-national-d-economie-d-eau-en-irrigation-pneeiune-reponse-au-defi-de-la-rarefaction-des-ressources-en-eau (in French)
Katsuyuki, S., Hiroki, U., Vinay, N., Anas, M., Mohamed, F., Belaarabi, M. and Lahcen, O. 2022. Water
distribution management and water-saving potential in a large-scale irrigation district. Journal of Arid Land
Studies, 32-S, 71-75, Retrieved from DOI https://doi.org/10.14976/jals.32.S_77
Ostrom, E. 2009. A general framework for analyzing sustainability of social-ecological systems. Science, 325,
419-422, Retrieved from DOI https://doi.org/10.1126/science.1172133
Ostrom, E., Dietz, T. and Stern, P. 2003. The struggle to govern the commons. Science, 302, 1907-1912,
Retrieved from DOI https://doi.org/10.1126/science.1091015
Samad, M. and Vermillion, D. 1999. Assessment of participatory management of irrigation schemes in Sri
Lanka, Partial reforms, partial benefits. International Water Management Institute, Research Report 34, 1Ⓒ ISERD43

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8, Retrieved from DOI https://www.iwmi.cgiar.org/Publications/IWMI_Research_Reports/PDF/pub034/
Report34.pdf
World Bank. 2022. Country climate and development report. Morocco, Retrieved from URL https://
openknowledge.worldbank.org/bitstream/handle/10986/38240/Morocco_CCDR.pdf?sequence=13&isAll
owed=yⒸ ISERD

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Research article
erd

Research article
Conditions of Bio-Slurry Application in Crop ProductioninKampong Cham Province, Cambodia

CHAN MAKARA MEAN*
Faculty of Agricultural Engineering / Faculty of Agronomy,
Royal University of Agriculture, Phnom Penh, Cambodia
Email: meanmakara321@gmail.com

LYHOUR HIN
Faculty of Agricultural Engineering, Royal University of Agriculture, Phnom Penh, Cambodia

SOPHOANRITH RO
Faculty of Agronomy, Royal University of Agriculture, Phnom Penh, Cambodia

NARETH NUT
Faculty of Agricultural Engineering, Royal University of Agriculture, Phnom Penh, Cambodia

NAM SOK
Faculty of Agricultural Engineering, Royal University of Agriculture, Phnom Penh, Cambodia

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

BART FREDERIKS
Independent Bioenergy Consultant / Biogas Technology and Information Center,
Royal University of Agriculture, Cambodia
Received 16 January 2023

Accepted 10 May 2023(*Corresponding Author)

Abstract Bio-slurry is an organic fertilizer produced from the decomposition of organic wasteor residues in anaerobic digestion. It is applicable for improving vegetable production as it
contains necessary nutrients such as nitrogen (N), phosphorus (P), and potassium (K) for plant
growth and organic matter that improves soil structure and water-holding capacity. About
29,000 biodigesters have been installed across Cambodia using animal waste to produce
biogas, so huge quantities of bio-slurry are produced. Therefore, this study aimed (1) to assess
the conditions of bio-slurry application in crop production in rural areas, (2) to determine NPK
content in the bio-slurry, and (3) to estimate annual bio-slurry production and NPK production
from biodigesters. The research was conducted between April and September 2022 byselecting 30 farming households that have biodigesters and use bio-slurry for crop cultivationin Prey Chhor District, Kampong Cham Province. It was found that 70% of the farmers usedbio-slurry for rice cultivation and 16.7% for backyard vegetables, basically before planting.
The nutrient content of slurry produced from cow manure consists of 0.20% N, 0.22% P, and
0.44% K. Most farmers preferred to use solid slurry for rice cultivation and liquid slurry forvegetables such as chili peppers, sweet peppers, eggplant, spinach, mustard greens, andcucumbers. However, bio-slurry was commonly mixed with chemical fertilizer in the crop
growth stage. Farmers are willing to use both slurry and chemical fertilizers as this helps theplants to grow well and have higher yields.
Keywords bio-slurry, biodigesters, crop production, vegetables, chemical fertilizer

INTRODUCTIONⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2023) 14-1

The installation of biodigesters has increased in rural Cambodia due to the need to help small-holder
farmers manage animal waste and convert it into energy for cooking and other applications in theirlivelihoods. They also utilize bio-slurry, a by-product produced from biogas production, as organic
fertilizer for crops. According to a 2019 assessment report released by the National Biodigester
Program (NBP), almost 29,000 digesters have been constructed across Cambodia in the period 20062012. Farmers normally raise cattle and use animal manure as a substrate for the biodigesters, andapply slurry, sometimes mixed with compost or other organic fertilizer, to their backyard vegetablegarden and rice cultivation (Hyman and Bailis, 2018). In 2020 alone, of the planned 1,500
biodigesters, 703 were constructed, which was equivalent to 47% (NBP, 2019). Among all the
installed biodigesters, it is reported that there are approx. 2,353 digesters used by small-holder
farmers in Kampong Cham Province, which is well-known for agricultural production on a large
landscape. Among all the districts in this province, Prey Chhor, Choeung Prey, and Kong Meas had
the highest number of biodigester installations compared to others (PDAFF, 2021).
In Cambodia, vegetable production was reported to be approx. 716,000 tones in 2020, eventhough this country experienced covid-19 pandemic and strict lockdowns. Yet, it was seen as a great
opportunity for the agricultural sector to increase local production by reducing dependency on
agricultural imports from the neighboring countries. Until now, it is also noticed that chemicalfertilizer has still been in high demand, as farmers consume it in their crop production whencompared to organic fertilizer in the form of compost or bio-slurry (Phnom Penh Post News, 2021).
Technically, bio-slurry is considered one of the most efficient organic fertilizers, when applied tocrops, since it is produced through anaerobic digestion. Therefore, it can be used instead of chemicalfertilizer in every stage of crop growth. Furthermore, slurry also helps increase crop yield by 30%,
when compared to chemical fertilizer, which leads to a reduction in production costs of 50% (Hyman
and Bailis, 2018). One study showed that a 25 m3 digester can produce 9,780 kg of bio-slurry
annually, consisting of 76 kg of nitrogen (N), 107 kg of phosphorus (P), and 107 kg of potassium(K), respectively (Kissan, 2019). That finding also indicated that bio-slurry contains 93 % water and
7% dry matter of which 4.7% was organic matter and 2.5% was inorganic matter (Kumar et al., 2015).
In addition, the utilization of bio-slurry was efficient in accelerating crop growth and increasing
vegetable yield in both seasons. Aina (2018) illustrated that 50% bio-slurry mixed with 50% chemicalfertilizer was more efficient than 100% of chemical fertilizer in promoting crop growth and yield
because the bio-slurry had only high N content, whereas other nutrients were obtained from chemicalfertilizer.
Bio-slurry can be a major solution for farmers who intend to use organic fertilizer to improvetheir crop production, and this comes at the right time due to the increase of biodigesters in rural
areas.
OBJECTIVE
This study aimed to (1) to assess the conditions of bio-slurry application in crop production in rural
areas, (2) to determine NPK content in the bio-slurry, and (3) to estimate annual bio-slurry production
and NPK production from biodigesters.
METHODOLOGY
The study was conducted between April and September 2022 by starting with collecting basic
information and designing a questionnaire for a survey. The study employed purposive sampling asa case study by selecting 30 households with biodigesters in Svay Prey commune, Prey Chhor District,Kampong Cham Province (Fig. 1) due to high household biodigester consumption. To obtainsufficient information, data such as type of bio-slurry application, size of the biodigester, type of
substrates used for biodigesters, and crop type were collected.
To determine the NPK content in bio-slurry, samples were collected from 3 different household
digesters in the studied area, packed, and stored at 5 0C for laboratory analysis. For the lab’s activities,
these three samples were mixed then using reagents (TN, TP, TK diluting with a sample with a mass
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IJERD – International Journal of Environmental and Rural Development (2023) 14-1

of 100 g for each parameter to determine NPK content following ISO 11261, 11263, and 17319
respectively whereas, total organic carbon (TC) also measured by Walkley and Black method.
Estimation of daily and annual bio-slurry production from biodigester using cow dung as a
substrate can be calculated based on the following Eq. (1). This estimation is based on the research
by Kumar et al. (2015), who found that 1 kg of cow dung produces 0.3 kg of bio-slurry, or 30%,
daily. Technically, daily manure fed into biodigesters sized 4, 6, and 8 m3 is equal to 30, 50, and 70
kg/day, respectively (Hyman and Bailis, 2018).
𝑄𝑠𝑙𝑢𝑟𝑟𝑦 (

𝑡𝑜𝑛𝑠
𝑦𝑒𝑎𝑟

) = 𝐷𝑎𝑖𝑙𝑦 𝑚𝑎𝑛𝑢𝑟𝑒 (𝑘𝑔
𝑑𝑎𝑦) × 𝑝𝑒𝑟𝑐𝑒𝑛𝑡 𝑜𝑓 𝑏𝑖𝑜 − 𝑠𝑙𝑢𝑟𝑟𝑦 𝑥 365 𝑑𝑎𝑦𝑠

(1)

Fig. 1 A map of Prey Chhor District, Kampong Cham Province
Data Analysis and Interpretation
Descriptive statistics were employed to analyze quantitative data collected in the survey, andfrequency tests were also used in the hypothesis to examine the relationship between two variables
to determine the significant difference in data. Besides this, data was also organized in tables andgraphs based on the types of questions and responses in Microsoft Excel.
RESULTS AND DISCUSSION
General Characteristics of Farm Households
Among 30 households, there are 50% of female farmers and 50% of male farmers whose age was
57±12.17 years (Table 1). The average household size was 4 ± 1.35. For the education status, 56.7%
of farmers were at the primary school level, whereas only 26.6 % went to high school, and 16.7 %were illiterate. Regarding biogas installation, 100% of biodigesters are concrete fixed-dome digesters,of the sizes 3, 4, 6, and 8 m3, 53% of biodigesters had a volume of 6 m3, while 20% were 4 m3
biodigesters. The farmers mostly raised cows, so that cow manure could be used as a main substrate
for biogas production. Of all the interviewees, 97% used cow manure as a substrate.
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Nutrients in Bio-Slurry / Substrate Source (Cow)
Table 2 shows that bio-slurry contained 0.2% total nitrogen (TN), 0.22% total phosphorus (TP),0.44% total potassium (TK), and 2.77% total organic carbon (TOC). With this result, the C/N ratio
was calculated to be 13.9, while the pH was 7.11. In contrast, based on the study of (Kumar et al.,2015), the nutrient content of bio-slurry from cattle was between 1.4% and 1.8% of TN, 1.1-2% of
TP, and 0.89-1.2% of TK. The result of low NPK content in this study might be due to different cow
species and feed types used for cows in Cambodia, whereas they raised the local breed of cattle andmostly fed their local grass and brewery waste with a high protein content.
Moreover, the nutrient content of compost consisted of 0.5-1.5% TN, 0.4-0.8% TP, and 0.51.9% TK, while the nutrient content of fresh cattle manure contained 0.5-1% TN, 0.5-0.8% TP, and
0.5-0.8% TK in the same study. Additionally, Bonten et al. (2014) indicated that cattle slurry consistsof 1.3-1.5% of N, 0.3-2.8% of P, and 0.3-1.4% of K, whereas swine slurry consists of 1.8-2.7% of
N, 0.8-3.3% of P, 0.5-0.8% of K, respectively.
Table 1 General characteristics of the farmers
Variables
Sex
Male
FemaleAge (year)
Household size (person)
Education
Illiteracy
Primary school
Secondary school
High school
Type of biodigester
Concrete fixed dome
Other types
Digester size (m3)3468Type of substrate
Cow manure
OthersNumber of interviewees
PersonPercentage (%)

Mean ± SD
57 ± 12.17
4 ±1.35
-

15
15
5
17
0
8
30
0
1
6
16
3
29
1

50.00
50.00
56.70
0.00
26.66
100.00
0.00
3.00
20.00
53.00
10.00
97.00
3.00

Table 2 Nutrient content in bio-slurry freshly produced from cow manure
No.
1
2
3
4
5
6

Parameters
Total nitrogen (TN)Total phosphorus (TP)Total potassium (TK)
Total organic carbon (TOC)
C: N Ratio
pH

Unit

Testing result (%)

g/100gg/100gg/100gg/100g
g/g
-

0.20
0.22
0.44
2.77
13.90
7.11

Estimation of Daily Bio-slurry Production
Table 3 compares the annual bio-slurry production by three sizes of biodigesters. Generally, the 8 m3
digester requires 70 kg/day of cow manure and can produce 21 kg of bio-slurry daily or 8 tons/a. For
a 6-m3 sized digester, the daily and annual bio-slurry production would be 15 kg and 5 tons/year
respectively for the 4-m3 digester, about 9 kg of bio-slurry is produced per day, or 3 tons/year. In
comparison with Kumar et al. (2015), animal manure generated 256.2 Mt each year, and total annual
biogas slurry was 76.8 Mt/year which was a huge amount of bio-slurry produced from biodigesters
and they were recoverable approx. 60% of total produced dung (resourced from cattle+ buffalo) whileⒸ ISERD

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the total estimated potential of biogas plants was in total 12 million plants for generating biogas andbio-slurry daily in India.
Table 3 Estimation of daily and annual bio-slurry production
Digester volume (m3)Daily slurry production(kg/day)

Annual slurry (ton/year)

4
6
8

9
15
21

3
5
8

Figure 2 shows the comparison of NPK content in bio-slurry annually produced in the threesizes of biodigesters. It is seen that the annual TK yield in bio-slurry was higher than the others.
Starting with annual TK production in bio-slurry, it varied from 1.45 to 3.37 tons/year of P produced
from an 8 m3 sized digester, while TN of 0.66 tons/year was obtained from one unit of a 4 m 3 sizeddigester, 1.1 tons/year for a 6 m3 sized digester, and 1.53 tons/year for an 8 m3. However, the finding
was relatively low when compared to Kumar (2015) who found that nitrogen content was 1.15 Mt in
76.8 Mt slurry produced annually. Additionally, Martinez-Suller et al. (2010) found that the average
TN, TP, and TK yields from cattle slurry were 3.43 kg/m3, 0.56 kg/m3, and 4.41 kg/m3 respectively.
NPK in bio-slurry ( tons/yr.)4
Nitrogen (N)Phosphorus (P)Posstasium (K)

3

2

1

0
4

6

8

Volume of biodigester (m3)

Fig. 2 Comparison NPK content in bio-slurry annually produced in different sizes of digester
Proportion of the Farmers Applying Bio-Slurry for Crop Production
It is observed that most of the farmers applied the slurry in solid state (Fig. 3). About 63.3 % of the
farmers applied solid slurry for their crop production, whereas only 13.3% consumed liquid bioslurry, and around 23% (Table 4) used both solid and liquid bio-slurry in their crop production.
Table 4 Type of slurry application
Type of slurry application
Wet
Dry
Both

Numbers

Percentage (%)

4
19
7

13.33
63.33
23.33

Nevertheless, all the interviewees were willing to utilize dry or solid slurry for their riceproduction, and they all also applied liquid slurry for leafy vegetables such as water morning glory,
lettuce, onion leaf, mustard greens, and spinach. Additionally, 70% of the farmers utilized solid slurry
for fruity vegetables like eggplants, cucumbers, sweet peppers, and chili peppers, whereas 30%
preferred liquid slurry. On the other hand, it is observed that before having biodigesters, therespondents used chemical fertilizer only, for both rice and vegetables. After the installation of biodigesters, the consumption of chemical fertilizer for rice production was reduced by 39% and by 35%Ⓒ ISERD

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for vegetable production. Concerning the liquid slurry application, one study (Musse et al., 2020)
reiterated that a mixture of bio-slurry in liquid state and N-inorganic fertilizer applications provided
a high yield of green bean (fruity vegetable) and improve both soil physio-chemical properties.

Fig. 3 Types of slurry application and percentage of chemical fertilizer use in different crops
CONCLUSION
In conclusion, bio-slurry production varies based on the amount of cow dung fed into biodigesters
daily. In the meantime, the nutrient content of bio-slurry had higher potassium (K) than other subnutrients such as nitrogen (N) and phosphorus (P). For bio-slurry application, most farmers always
applied solid bio-slurry for crops, and all farmers prefer to use solid slurry for rice and liquid forms
for vegetables. Furthermore, the use of slurry can replace and reduce chemical fertilizers in crop
production. Finally, the farmers still mix chemical fertilizer with bio-slurry because they think it is
key to obtaining good quality and high-yield crops. Therefore, further research should be performed
to identify the impacts of bio-slurry on crop growth and yield for better documentation and wider
adoption.
ACKNOWLEDGEMENTS
The study was made possible thanks to the project “Reduction of Greenhouse Gas Emission throughPromotion of Commercial Biogas Plant in Cambodia” implemented by the United Nations Industrial
Development Organization (UNIDO), which provided funding for this survey study, and I would liketo acknowledge to “Higher Education Improvement Project (HEIP)” funded by the World Bank toRoyal University of Agriculture (RUA) for sponsoring my master’s degree study. Also, many thanks
to all the farmers and local authorities in the Prey Chhor District for their kindness in allowing forthe survey.
REFERENCES
Aina, O.A., Agboola, K., Adava, I.O. and Eri, A. 2018. Effect of organic (cow dung slurry) and inorganic (N:P: K 15: 15: 15) fertilizer on the growth and yield of tomato (Lycopersicon Lycopersicum) in Anyigba,
Kogi state, Nigeria. European Journal of Agriculture and Forestry Research, 6 (5), 15-27, Retrived fromhttps://www.eajournals.org/wp-content/uploads/Effect-of-Organic-Cow-Dung-Slurry-and-Inorganic-1.pdf
Bonten, L.T.C., Zwart, K.B., Rietra, R.P.J.J., Postma, R., De Haas, M.J.G. and Nysingh, S.L. 2014. Bio-slurry
as fertilizer, Is bio-slurry from household digesters a better fertilizer than manure? A literature review.
Wageningen: Alterra (Alterra-report 2519)-45, Retrieved from URL https://library.wur.nl/WebQuery/wurpubs/454883
Hyman, J. and Bailis, R. 2018. Assessment of the Cambodian national biodigester program. Energy for
Sustainable Development, 46, 11-22, Retrieved from DOI https://doi.org/10.1016/j.esd.2018.06.008
Kissan, B. 2019. Bio-slurry application in agriculture service for former. Bakhabar Kissan Agriculture News,
Retrieved from URL https://bakhabarkissan.com/bio-slurry-will-increase-vegetable-production-upto-30Ⓒ ISERD

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Kumar, S., Malav, L.C., Malav, M.K. and Khan, S.A. 2015. Biogas slurry, Source of nutrients for eco-friendly
agriculture. International Journal of Extensive Research, 2, 42-46, Retrieved from URL https://cyberleninka.org/article/n/281060.pdf
Martínez-Suller, L., Provolo, G., Brennan, D., Howlin, T., Carton, O.T., Lalor, S.T.J., and Richards, K.G. 2010.
A note on the estimation of the nutrient value of cattle slurry using easily determined physical and chemicalparameters. Irish Journal of Agricultural and Food Research, 49 (1), 93-97, Retrieved from URL http://www.jstor.org/stable/20788569
Musse, Z.A., Yoseph Samago, T. and Beshir, H.M. 2020. Effect of liquid bio-slurry and nitrogen rates on soil
physicochemical properties and quality of green bean (Phaseolus vulgaris L.) at Hawassa Southern Ethiopia.
Journal of Plant Interactions, 15 (1), 207-21, Retrieved from DOI https://doi.org/10.1080/17429145.2020.1781270
National Biodigester Program (NBP). 2019. Market study on medium-scale and large-scale biodigesters in
Cambodia. National Biogas Program, General Directorate of Animal Health and Production (GDAHP),
Cambodia.
Phnom Penh Post. 2021. Cambodian vegetable production status in 2020. Fresh Plaza, Retrieved from URL
https://www.freshplaza.com/article/9283610/cambodian-vegetable-production-at-716-000-tons-in-2020
Provincial Department of Agriculture, Forestry and Fisheries in Kampong Cham (PDAFF) . 2021. The statisticof biodigesters installed in Kampong Cham Province by NB. Ministry of Agriculture, Forestry and Fisheries,
Cambodia.

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Research article
erd

Determination of Histamine Level and Its Correlation with
Viable Bacterial Count in Cambodian Fermented FishLENGHEANG CHOENG
Faculty of Chemical and Food Engineering, Institute of Technology of Cambodia,
Phnom Penh, Cambodia

CHANTHOL PENG*
Research and Innovation Center / Faculty of Chemical and Food Engineering,
Institute of Technology of Cambodia, Phnom Penh, Cambodia
Email: peng@itc.edu.kh

LEANGEY SET
Research and Innovation Center / Faculty of Chemical and Food Engineering,
Institute of Technology of Cambodia, Phnom Penh, Cambodia

SEYHA DOEURN
Research and Innovation Center / Faculty of Chemical and Food Engineering,
Institute of Technology of Cambodia, Phnom Penh, Cambodia
Received 15 February 2023

Accepted 12 May 2023(*Corresponding Author)

Abstract Nem trey (NT), Sangvak (SV) (minced fish), and Nem sbek chrouk (NC) (mincedfish mixed with pork skin) are fermented fish products popular in Cambodia; NC and NT are
ready for direct consumption after two or three days of fermentation, while SV must be
additionally grilled before consuming. However, food safety standards for these products
including control of biogenic amines such as histamine are neglected, which could pose ahealth problem. Biogenic amines are nitrogenous organic chemical compounds mainly
produced from the decarboxylation of amino acid, histidine, by the activity of certain bacteria
associated with fish products processed under poor hygiene and unstable temperature control.
This study aimed to determine the histamine level in NT, SV, and NC products and studied its
correlation with the viable bacterial count (BVC). Twenty-six samples, NT (n=12), SV (n=5),
and NC (n=9), were collected from different producers from Battambang (BB) and Kratie (KT)provinces. A histamine test kit utilizing a colorimetric enzymatic assay, was used to determine
histamine level. The BVC was done using the spread plate technique on Luria Bertani agar
media incubated at 37oC for 24h. For KT province, NT and NC contained BVC (log10 CFU/g)in the range of 5.74±0.02 to 6.57±0.01 and 5.52±0.01 to 5.98±0.01, while histamine (mg/kg)
ranged from 0 to 156.43±0.13 and 28.76±0.71 to 73.87±0.13, respectively. SV, NT, and NC
from BB province contained the BVC (log10 CFU/g) ranging from 6.02±0.16 to 6.56±0.15,
5.97±0.15 to 6.04±0.15, and 5.69±1.18 to 6.12±0.11, while histamine (mg/kg) ranging from
6.10±0.44 to 54.52±0.00, 0 to 10.90±0.14, and 0 to 38.54±0.00, respectively. The BVC andhistamine showed a significant correlation, with a value of 0.448 (p-value < 0.05). Therefore,
raw materials, processing, and storage conditions along the production chain should be
evaluated in further studies to ensure safety of the fermented fish products.
Keywords biogenic amine, viable bacterial count, fermented fish, food safety

INTRODUCTION
Fish and fishery products have long been associated with people's socioeconomic lives. To preservefish, fermentation is one of the oldest and most cost-effective methods (Uochoi, 2019). Fishfermentation is practiced in many parts of the world, but the most popular practice is found inSoutheast Asia, including Cambodia. Generally, the common fermented fish product in CambodiaⒸ ISERD

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includes prahok (fish paste), teuk trey (fish sauce), trey praherm; trey proma (salted fish), and mamtrey, paork, and nem (other fermented fish) that have played an essential part of the typical diet inCambodia involved to fermented fish (Ly et al., 2018, 2020). Among these types of Cambodian
fermented fish products, Nem such as Nem trey (NT), Sangvak (SV) (minced fish), and Nem sbek
chrouk (NC) (minced fish mixed with pork skin) are the fermented fish products that usually take
two to three days for fermentation. These ready-to-eat appetizers, except for Sangvak, which needs
to be grilled before consumption, are popular among Cambodians.
Potentially pathogenic bacteria such as Bacillus, Clostridium, and Staphylococcus were foundin traditional Cambodian fermented fish products (Chuon et al., 2014; Ly et al., 2018). So, fermented
fish products can contain microorganisms that affect human health. Chemical compounds andmicrobiological contamination can cause acute poisoning or long-term disorders such as cancer(Ruiz-Capillas and Herrero, 2019). Another study reported that many bacterial isolates from
Cambodian fermented fish products were from the non-lactic acid bacteria (LAB) genera, including
Staphylococcus, Bacillus, Clostridium, Virgibacillus, Kocuria, Clostridium, Lisinibacillus,
Psychrobacter, Lantibacillus, and Micrococcus (Chuon et al., 2014).
Next to microorganisms, a toxic chemical substance such as biogenic amines (BAs) is the mostcommon compound associated with fermented fish (Visciano et al., 2012). Biogenic amines are basic
nitrogenous chemicals with various structures that may be found in various foods, including fish andfishery products, meat and animal products, cheeses, wine, beer, and other fermented meals andbeverages (Durak-Dados et al., 2020). Histamine, tyramine, putrescine, cadaverine, and bphenylethylamine are the most significant BAs in foods and drinks, both qualitatively andquantitatively, as a result of the decarboxylation of histidine, tyrosine, ornithine, lysine, andphenylalanine, respectively (Spano et al., 2010). Fish and fish products show the highest levels of
BAs in previous studies (Linares et al., 2011; Durak-Dados et al., 2020). Among all types of biogenic
amines, histamine (HIS) is the most concern BAs related to food safety (EFSA, 2011) as histamine
has been shown to cause severe symptomatology such as skin rashes, headache, nausea, diarrhea,
and variations in blood pressure (Botello-Morte et al., 2022). The synthesis of histamine in mackerel
and other marine fish carrying high levels of endogenous histidine is linked to the action of microflora
rather than the activity of a decarboxylase found natively in fish (Durak-Dados et al., 2020).
Histamine consumption of 8-40 mg, 40-100 mg, and more than 100 mg may generate mild, moderate,and severe poisoning, respectively (Sahu et al., 2016). European Union limited the histamine levelin food products by 100 mg/kg on average, no one sample exceeds 200 mg/kg, and no more than two
samples may each have a value of more than 100 ppm, but less than 200 ppm for nine samples tested(EFSA, 2007).
Microorganisms, known as factors, that affect the formation of biogenic amines and histamine
formation, have been reported. The genus Photobacterium, Aeromonas hydrophila, andEnterobacteria such as Morganella morganii, Enterobacter aerogenes, Raoultella planticola, andKlebsiella oxytoca are involved in the accumulation of histamine in fish and seafood products(Fernández-No et al., 2010; Küley et al., 2013). Some fungi (yeast and molds) are implicated in BAs
formation, although their significance is debatable in several ways (Tristezza et al., 2013). Poor raw
material quality and improper handling are two reasons for including BAs in fermented fish (RuizCapillas and Herrero, 2019).
OBJECTIVE
According to the relation between histamine level and microorganisms, this study aimed to determine
the histamine level and identify the correlation between histamine level and viable bacterial count in
Cambodian fermented fish, Nem, collected from two provinces, including Battambang and Kratie.
This study provides insight into predicting the safety of the fermented fish product and can be a
supporting document for standard quality development for the fermented fish product in Cambodia.
METHODOLOGYⒸ ISERD

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Samples Collection
Twenty-six samples were collected from local producers in two provinces in Cambodia, Kratie (KT)and Battambang (BB) provinces. From KT, there were 11 samples collected, and separated into three
types of samples such as fermented fish packaged by banana leaves, Nem Trey (KTNTB) threesamples; fermented fish packaged by plastic, Nem Trey (KTNTP) four samples; and fermented fishmixed with pork skin, Nem Sbek Chrouk (KTNCB) four samples were collected. Whereas for BB
province, 15 Nem samples were collected including Songvak (BTBSV) five samples, Nem Trey
(BTBNT) five samples and fermented fish with pork skin, Nem Sbek Chrouk (BTBNC) five samples.
Table 1 Description of collected samples

BTBSV

Main
ingredient
Fish
Fish and pork
skin
Fish

Nem trey (packaged by banana leave) (n=3)

KTNTB

Fish

Nem trey (packaged in plastic) (n=4)

KTNTP

Nem sbek chrouk (packaged by banana leave) (n=4)

KTNCB

Fish
Fish and pork
skin

Province

Type and number of samples

Battambang

Nem trey (fermented fish) (n=5)
Nem sbek chrouk (fermented fish mixed with porkskin) (n=5)
Songvak (fermented fish) (n=5)

KratieSample
code
BTBNT
BTBNC

Viable Bacterial Count Analysis
The enumeration of viable bacterial count (BVC) was done using the spread plate technique. For
each Nem product, a homogenized sample of 10g was diluted with 90 mL of phosphate-bufferedsaline (PBS). Appropriate dilutions of the samples were prepared using the same diluent. Then 0.1mL
aliquots of each dilution were applied to Luria Bertani agar media and spread on its surface until
completely absorbed. Plates were then incubated at 37℃ for 24 hours. The colonies counting of BVC
were presented as logarithms colony-forming units per gram (log10 CFU/g).
Histamine Concentration Analysis
The sample preparation and extraction followed the manufacturer's instructions for the extraction kit(Kikkoman Biochemifa, Tokyo, Japan). 10 g of each Nem sample was first homogenized, and 1 g of
the homogenized sample was diluted with 24 ml of sample treatment buffer (EDTA) in a centrifuged
tube. The tube was vortexed for 30 mins and then boiled for 20 mins. The tube was cold by placing
it on an ice box (until < 20℃). The tube was vortexed again and put in an ice box to separate thephase. The tube was centrifuged 10 000 x g for 5 min; then the supernatant was collected. 11 ml ofdeionized water was added to the colorimetric reagent vial. 6 ml of buffer vial was added to the
enzyme reagent vial. The concentration of histamine (mg/kg or ppm) (HIS) was calculated by Eq.
(1).
𝐻𝐼𝑆 = (𝐸𝑠 − 𝐸𝑏) ÷ (𝐸𝑠𝑡𝑑 − 𝐸𝑐) × 100(1)

The absorbance of the sample, Es, was measured by mixing extracted sample solution,colorimetric reagent, and enzyme solution. Eb stands for absorbance of sample blank obtained bymixing extracted sample solution, colorimetric reagent, and buffer. The absorbance of standard
solution, Estd, by mixing standard histamine solution, colorimetric reagent, and enzyme solution.
The last absorbance of reagent blank, Ec, got by mixing Distilled water, colorimetric reagent, andbuffer. Absorbance was measured using a spectrophotometer (UV-1280, Shimadzu, Japan) with a 1
cm optical wavelength of 470 nm.

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Statistical Analysis
Results units of the quantitative bacterial viable count were log10 CFU/g. The histamine content andviable bacterial count were analyzed with statistical analyses using the Statistical Package for theSocial Sciences (SPSS, Version 20.0.0 for Windows, 2018; IBM Co., Somers, NY, USA). Data wereanalyzed for the degree of variation by calculating the result’s mean and standard deviations (SDs).
The significance of differences was evaluated using analysis of variance (ANOVA). A p-value ofless than 0.05 was considered statistically significant. The correlation value was determined using
the Pearson Correlation coefficient.
RESULT AND DISCUSSION
Evaluation of Viable Bacterial Count and Histamine Level
Figures 1 and 2 described the result of HIS and BVC, respectively. For KT province, Nem trey
packaged by banana leaves and plastic (KTNTB and KTNTP) contained HIS (mg/kg) in the range
from 6.35±0.48 to 156.43±0.13, while BVC (log10 CFU/g) showed a range from 5.74±0.02 to
6.57±0.01. However, Nem sbak chrouk described the HIS (mg/kg) in the range 228.76±0.71 to
73.87±0.13. At the same time, BVC (log10 CFU/g) presented from 5.52±0.01 to 5.98±0.10. On theother hand, from BB province, NT showed the range of HIS (mg/kg) from 0 to 10.90±0.14, while
BVC (log10 CFU/g) represented from 5.97±0.15 to 6.04±0.15. NC showed a range of HIS (mg/kg)
and BVC (log10 CFU/g) from 0 to 38.54±0.00 and 5.69±1.18 to 6.12±0.11, respectively. For
Songvak, the data represented 6.10±0.44 to 54.52±0.00 and 6.02±0.16 to 6.56±0.15 for HIS(mg/kg) and BVC (log10 CFU/g), separately.

Fig. 1 Viable bacterial count in all samples
The result of all samples was compared with maximum limits. The US Food and Drug
Administration (FDA) set the maximum of histamine in fish and fish products at 50 mg/kg (Ly et al.,2020), while European Food Safety Authority set the limit of histamine in fishery products at 200
mg/kg (EFSA, 2007). Seven in twenty-six samples exceed 50 ppm, and no one above 200 mg/kg.
The safety of these fermented products should be slightly concerning. Previous studies on
Cambodian fermented fish showed that the histamine concentration loaded in products ranged from32 to 840 mg/kg (Ly et al., 2020). This result showed higher histamine levels, but it might becomparable with a concentration of histamine studied in this paper as the Nem products requiredⒸ ISERD

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HIS (mg/kg)

only a few days to consume, while other fermented fish mentioned in that previous study were othertypes of fermented products that require a longer time to consume (Paork Chav, Paork Chau, and
Mam Trey). The Malaysian fermented fish, Budu, detected 187 mg/kg of histamine concentration(Saaid et al., 2009). Histamine was found at a high concentration in Feseekh, Egyptian fermented
fish (521 mg/kg) (Rabie et al., 2011).
The microbial ranged from 5.52 to 6.32 log10 CFU/g. The total cell counts identified on otherCambodian fish products were 5 to 7 log10 CFU/g for Prahok (fermented fish paste), 5 to 8 log10
CFU/g for Kapi (fermented fish), and 2 to 6 for Toeuk Trey (fermented fish sauce) (Chuon et al.,2014). The viable plate count found 6 log10 CFU/g in the Indonesian salt-fermented fish product(Kusmarwati et al., 2020). This information may be compared with each other for the same type of
products (fermented fish products).
160
150
140
130
120
110
100
90
80
70
60
50
40
30
20
10
0

a
b

c
d
e
f

g
h

n

q

i

p

j

k

l

m

o
s

r

r

p

r

C1 C2 C3 C4 C5 NT1 NT2 NT3 NT4 NT5 SV1 SV2 SV3 SV4 SV5 CB1 CB2 CB3 CB4 TB1 TB2 TB4 TP1 TP2 TP3 TP4
BN TBN TBN TBN TBN TB TB TB TB TB TB TB TB TB TB TN TN TN TN TN TN TN TN TN TN TNT
B B B B B B B B B B B B B B B K K K K K K K K K K K
Samples CodeFig. 2 Histamine content in all samples
As determined by One-way ANOVA and LSD tests in SPSS 2018. The significant differencesof all samples are shown in script on the bar chart in Fig 1 and 2 for BVC and HIS, respectively.
Statistically significant differences (p<0.05) were found among the defined concentration ofhistamine, except BTBSV2, KTNTP1, and BTBNT5 showed non-significant differences (p>0.05)
and pair of BTBNT2 and BTBSV5 found that non-significant differences also (p>0.05). However,for the viable bacterial count, statistically significant differences (p<0.05) were found, but some of
the group samples were described that they are non-significant differences (p>0.05). Moreover,comparing histamine levels with 50 ppm showed non-significant differences (p>0.05). In contrast,
the significance differences (p<0.05) were found in analyzing 200 mg/kg histamine levels using the
One Sample T-test. Table 2 showed the significant moderate correlation between histamine
concentration and bacterial viable count value r=0.448, p<0.05, n=26 was found using Pearson
Correlation. Sample form Kratie showed a non-significant different (p>0.05) between banana leave
packaging and plastic packaging through Paired Samples T-test.
Table 2 Correlation between BVC and HIS by Pearson Correlation

Histamine content

Viable bacterial count
0.448
0.022
26

Pearson Correlation
Significant
Number of samples

The histamine concentration and microbial loaded in these Nem samples were correlated.
Therefore, to prevent the increase of histamine levels in Nem products, the elimination of microbial
through applied raw material quality, good hygiene production, and cold processing line play animportant factor in reducing histamine in food.
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CONCLUSION
The histamine level, a formation chemical concerning food safety, in Cambodian fermented fish
products, was studied on 26 samples collected from 2 different provinces in Cambodia. The range ofhistamine concentration was detected from 0 to 156.43±0.13 mg/kg, with seven samples exceeding
the maximum limit of 50 mg/kg set by the FDA. Microbial loads of each product were also
determined, and the results ranged from 5.52±0.01 to 6.32±0.07 log10 CFU/g. The correlation
between histamine and bacterial concentration was significantly correlated with a moderatecorrelation on the positive side (r=0.48). This result is important for setting limits of food safety
criteria for local fermented products. It is important to note that to reduce the risk of the formationof histamine concentration of the Nem product, reduction or elimination of certain bacteria species
through the hygienic practice through food supply chains such as raw material, operating, andtemperature controlling shall be applied.
ACKNOWLEDGEMENTS
The work was funded by Cambodia Higher Education Improvement Project (Credit No. 6221-KH)
through sub-project HEIP-ITC-SGA#17.
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Visciano, P., Schirone, M., Tofalo, R., Suzzi, G., 2012. Biogenic amines in raw and processed seafood.
Frontiers in Microbiology, 3, 1-10, Retrieved from DOI https://doi.org/10.1016/j.fm.2013.07.001Ⓒ ISERD

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Research article
erd

Evaluation of Soil Erosion Risk from Weathering Effects on
K Factor of RUSLE in Cobija, Bolivian Amazonia
JUAN UEGO PEREZ
Graduate School of Agro-Environmental Science, Tokyo University of Agriculture, Japan
E-mail: uego.juan@gmail.com

MACHITO MIHARA*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Japan
E-mail: m-mihara@nodai.ac.jp
Received 15 January 2023

Accepted 12 May 2023(*Corresponding Author)

Abstract Soil erosion by water is a serious problem in the Amazonia region of Bolivia. In thearea of Cobija, Bolivia, around 8 Mg ha-1 of Amazon soil is lost to the nearby watershedannually. The physical weathering of soils under natural conditions is one of the key processes
for understanding structural changes in the soil. The soil erodibility (K) factor in RUSLE
represents the susceptibility of soils to erosion, which can be measured with the standard unit
plot experiment or through calculation with particle sizes and organic matter. Soil weathering
affects soil particle distribution that is closely related to the K factor. Therefore, the purposeof this research is to evaluate and determine the change in the distribution of soil particles aswell as the K value. The experiment was conducted in a laboratory setting. A total of 120 canscontaining 1 g of soil each were used and treated with different periods and volumes of water
added to represent weathering. The simulated weather conditions were set in line withconditions observed in Bolivian Amazonia. The pipette method was used to determine the
distribution of soil particles. The results indicated slight changes in the distribution of the soil
particles, reducing the percentage of fine sand and increasing the silt content, which affected
the K factor as well as the estimate of soil losses based on RUSLE.
Keywords soil erosion, weathering, RUSLE, soil particle, Amazonia, Bolivia

INTRODUCTION
Weathering soils under natural conditions is a pivotal process to quantify sustainability assessmentsof forestry and land use, as well as to evaluate the rate of soil losses in the field. Accelerated
weathering occurs as a consequence of deforestation and the loss of plant cover, which exposes thesoil to the direct impact of temperature and wet-drying processes. The impact of raindrops on the soil
causes changes in the percentage distribution of soil particles, ultimately altering the values in the Kfactor of the Revised Universal Soil Loss Equation (RUSLE) and influencing the results of soil loss
calculations. For this study, a total of 120 containers filled with the soil from the Bolivian Amazon
were subjected to weathering conditions identical to the study area, maintaining the same temperature
and applying water for various periods. The objective was to determine if the changes observed in
the percentage distribution of soil particles. After a 100-days experimental period, the pipette method
was used to assess particle distribution in the soil, followed by the calculation of the K factor as wellas other factors in the RUSLE. Accordingly, this study aimed to discuss the weathering effects on
the K factor and the amounts of soil loss.
OBJECTIVE
The objective of this study was to assess soil erosion risk, focusing on the weathering effects on the
K factor and the amounts of soil loss in Cobija, Bolivian Amazonia, using the Revised Universal Soil
Loss Equation (RUSLE).
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METHODOLOGY
Site Description

Fig. 1 Location of the soil sample collection in the city of Cobija, Bolivian Amazonia
Cobija is a Bolivian city, serving as the capital of the Department of Pando and the Province ofNicolás Suárez. Over the past two decades, Cobija has experienced substantial deforestation rates(Bolivian Institute, 2015). This process was greatly influenced by the regional development strategy
initiated by the Bolivian Government in 2015. Local farmers gradually transformed the forested
landscape into an urban city. The climate in the study area is classified as equatorial, characterizedby hot and humid conditions with a tropical transition. There is a distinct dry season from June toAugust, and the average annual precipitation is 2016 mm (Mayoralty of Cobija, 2020). The researcharea spans 14 km2, with an average annual temperature ranging from 32˚C to 24˚C. The monthly
average air moisture ranges from 80 to 85 percent. The terrain is undulating, with elevations ranging
from 100 to 120 meters above sea level.
Soil Sample Source and Preparation
Twenty soil samples were collected from an area of 60 ha in the Bolivian Amazonia that was recently
deforested. And after mixing to give a homogenous sample the soil was air-dried. A quantity of 5.4
kg of each soil sample was transported from Bolivia to Japan for physical experiments conducted in
the Land and water laboratory using engineering equipment at the Tokyo University of Agriculture,
Tokyo, Japan.
Weathering Experiment
A weathering experiment was undertaken to replicate the climatic conditions prevalent in the
Bolivian Amazon. A total of 120 soil containers were meticulously prepared, with each container
containing 1 g of soil. These cans were then subjected to a controlled environment in an incubator,
simulating the temperature conditions found in the Bolivian Amazon.
To mimic the effects of rainfall, 0.4 ml of water was carefully added to each soil can at specificintervals of 2, 4, and 12 hrs. This process was repeated 100 times for each treatment, ensuring
sufficient replication for reliable analysis and accurate data collection.
Determination of Soil Particle Distribution Experiment using the pipette method
To determine the percentage distribution of particles in the soil samples before and after the treatment,
the pipette method was employed for each treatment and repetition. This method allows for thedetermination of the percentage of coarse sand, fine sand, silt, and clay. The experiment involvedⒸ ISERD

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using 10 g of dry soil, with the organic matter content initially removed with a previous treatmentusing H2O2. A 20 ml solution of sodium hexametaphosphate at a concentration of 6% was preparedfor each analysis. The gravel and sand content were collected by filtering the soil through sieves witha mesh size of 2.0 and 0.2 mm, respectively. The remaining silt and clay contents were placed in 500
ml measuring bottles, and 20 ml of the 6% sodium hexametaphosphate solution was added.
Subsequently, 10 ml of the solution was collected at different time intervals based on Stokes' law todetermine the content of clay, silt, and fine sand.
Brief Description of the RUSLE
The RUSLE represents how climate, soil, topography, and land use affect rill and inter-rill soil
erosion caused by raindrop impact and surface runoff (Renard et al., 1997). It has been extensively
used to estimate soil erosion loss, assess soil erosion risk, and guide development and conservationplans in order to control erosion under different land-cover conditions, such as croplands, rangelands,
and disturbed forest lands (Millward and Mersey, 1999; Boggs et al., 2001) The RUSLE is expressedby Eq. (1) as follows.
A = R × K × LS × C × P(1)

Table 1 summarizes the terms for estimating the factors using Eq. (1), where A is the averageannual soil loss in t/ha; R is the rainfall-runoff erosivity factor; K is the soil erodibility factor; L isthe slope length factor; S is the slope steepness factor; C is the cover-management factor; and P is
the support practice factor. Table 1 summarizes the methods for estimating these factors.
Table 1 Summary of methods for developing RUSLE used in this research
Term
R
K
LS

Methods

References

A regression model based on the measurement of annual precipitation
uses averages monthly precipitation and average annual precipitation
Experimental models based on soil properties (composition of coarse
sand, fine sand, silt, clay, percentages.
Estimated from actual ﬁeld measurements of length and steepness
calculated from DEM data with various approaches

Renard and Fremund, 1994
El-Swaify and Dangler, 1976
Hickey, 2000;
Van Remortel et al., 2001

C

Land use comparison table

Silva et al., 2007

P

Table of P values for different conservation practices

Bertoni and Lombardi Neto,
1985

RESULTS AND DISCUSSION
Soil Erodibility K Factor
Soil Erodibility K Factor was calculated using inherent soil properties following the procedure fortropical soils and determined using inherent soil properties, following the El-Swaify and Dangler(1976) procedure for tropical soils, which uses the percent-modified silt (0.002-0.2 mm), percent
modified sand (0.1-2.0 mm), base saturation, percent unstable aggregates, and percent very fine sand.
The values for the measured soil properties were used to calculate K Factor using Eq. (2).
K = −0.03970 + 0.00311X1 + 0.00043X2 +0.00185X3 + 0.00258X4 − 0.00823X5(2)

Where X1 is the percent unstable aggregates < 2.0mm, X2 is the product of the percent ofmodified silt (0.002-0.01 mm) by the percent of modified sand (0.1-2.0 mm) present in the sample,
X3 is the percent base saturation of the soil, X4 is the percent silt present (0.002-0.05 mm), and X5 isthe percent of modified sand in the soil (0.1-2.0 mm). The calculated results of K factor weresummarized in Table 2.
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Table 2 Changes in soil properties for calculating the RUSLE K-factor with weathering
Fraction
Silt (0.002-0.05 mm)
Modified silt (0.002-0.01 mm)
Fine sand (0.02-0.2 mm)
Modified sand (0.1-2.0 mm)
Aggregates (< 2.0 mm)
Base saturation (%)

Control T0(0 h)29.05%
29.60%
28.68%
7.24%
0.78%
25.56%

Treatment T1(2 h)
30.85%
31.50%
27.89%
5.89%
0.52%
25.56%

Treatment T2(4 h)
31.88%
32.50%
26.84%
5.78%
0.29%
25.56%

Treatment T3(12 h)
33.48%
33.60%
24.70%
5.56%
0.25%
25.56%As shown in Table 2, the results were used to calculate the K factor and also indicated a rise in
the percentage of soil clay and silt particles following the treatment. These notable increases served
as an indication that the soil was exposed under the harsh climatic conditions prevalent in the
Bolivian Amazon region, where has a discernible impact on the changes in soil particle distribution.
The climate in the study area plays a pivotal role in enhancing the weathering effects, leading tochanges in the soil composition and structure. The heightened exposure to the Amazonian climate
accelerates the breakdown of soil particles, making them more vulnerable to weathering processes.
Thus, the relationship between climate and the weathering effect is crucial in understanding thealterations in soil particle distribution and their implications for soil erosion.
Table 3 Changes in particle size-dependent variations in RUSLE K-factor with weathering
Value
X1
X2
X3
X4
X5
K values (hundreds of acre ft ton in.)K values (Mg h MJ-1mm-1)

Control T00.78
214.30
25.56
29.05
7.24
0.11750.0154Treatment T1
0.52
185.53
25.56
30.85
5.86
0.12030.0158Treatment T2
0.29
187.85
25.56
31.88
5.78
0.12390.0163Treatment T3
0.25
186.82
25.56
33.48
5.56
0.12930.0170In Table 3, the impact of varying K values in the Revised Universal Soil Loss Equation(RUSLE) is elucidated concerning alterations in particle size distribution. These modifications are
intricately linked to shifts in the soil particle distribution following the weathering experimental
treatment. The data presented therein offers a comprehensive insight into the progressive changes inK values, thereby providing valuable information about the soil erosion susceptibility resulting fromshifts in particle size distribution due to the experimental weathering treatment.

Fig. 2 Changes in soil particle distribution with weathering
As shown in Fig. 2, the changes in the percentage distribution of soil particles in the soil revealed
an interesting trend; there is a tendency for the proportion of fine sand to decrease while the silt
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content experiences a slight increase. This suggests that the weathering processes and exposure to
the climatic conditions in the study area contribute to the transformation of soil particle composition.
Specifically, the finer sand particles exhibit a decreasing presence, potentially due to theirsusceptibility to weathering and erosion. On the other hand, the slight increase in silt content could
be attributed to the redistribution of soil particles caused by weathering processes. Overall, theseobservations highlight the intricate relationship between weathering, soil particle distribution, andthe impact of climatic conditions in shaping the composition of soil samples.
Table 4 Annual soil losses in the city of Cobija
Year
2017
2018
2019
2020
2021
Average

A0 (t/ha year)
9.36
8.41
10.36
8.48
11.11
9.54

A1 (t/ha year)
9.81
8.82
10.86
8.89
11.65
10.01

A2 (t/ha year)
10.03
9.02
11.10
9.09
11.91
10.23

A3 (t/ha year)
10.15
9.12
11.23
9.20
12.05
10.35

Average Annual Soil Loss in the City of Cobija
The results applied all the factors of the RUSLE on the different treatments to obtain the annual soil
loss per unit area are summarized in Table 4. The average annual soil losses were in the range of 10< t/ha/year before the effects of weathering, but the values were beyond 10 < t/ha/year after affecting
weathering. Also, there was a tendency that the values of Treatment 3 affected higher weathering
were higher than those of other treatments affected lower weathering. Figure 3 showed the increasing
trends in the average annual soil losses, A value, in the City of Cobija, based on the changes in soil
particle distribution due to weathering processes.

Fig. 3 Increase in A values (annual soil loss) with weathering
CONCLUSION
Soil erosion by water remains a big concern in the Amazonia region. This study aimed to assess theweathering effects on the K factor of the Revised Universal Soil Loss Equation (RUSLE) in Cobija,
Bolivian Amazonia. The experiments utilized Bolivian Amazon soil were conducted to replicate themeteorological conditions prevalent in the study area. The pipette method was employed to measure
the distribution of soil particles in a sample. The experimental results indicated remarkable changes
in soil particle distribution with weathering, and the changes affected K value as well. This trend
influences the final results of RUSLE, the average annual soil losses, A value.
In conclusion, this study highlights the significant impact of weathering on the K factor of the
Revised Universal Soil Loss Equation (RUSLE) in the Cobija region of Bolivian Amazonia. TheⒸ ISERD

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experimental investigation involving Bolivian Amazon soil, conducted to mimic the local
meteorological conditions, revealed alterations in soil particle distribution due to weathering. While
the specific changes in K values were not presented in this manuscript, the observed trend of
weathering-induced shifts in soil particle distribution undoubtedly plays a crucial role in influencing
the accuracy of the RUSLE model's predictions, particularly in terms of average annual soil losses.
On the basis of this research outcomes, it is suggested that the soils should not be exposed forlong period after deforestation. Soils should be covered by some sheets or residues as mulching for
decrease weathering effects on soil structure.
ACKNOWLEDGMENTS
We would like to express special gratitude to research fellows in the Laboratory of Land and Water
Use Engineering, Tokyo University of Agriculture for always meaningful discussion.
REFERENCES
Bertoni, J. and Lombardi, N.F. 1985. Conservação do solo. Piracicaba-SP, 392, Retrieved from https://www.passeidireto.com/arquivo/21438632/conservacao-de-solo/12
Boggs, G., Devonport, C., Evans, K., and Puig, P. 2001. GIS-based rapid assessment of erosion risk in a small
catchment in the wet/dry tropics of Australia. Land Degradation and Development, 12 (5), 417-434,
Retrieved from DOI https://doi.org/10.1002/ldr.457
Bolivia National Statistical Institute. 2015. Annual report, Retrieved from URL https://www.ine.gob.bo/
El-Swaify and Dangler, E.W., S.A. 1976. Erosion of selected Hawaii soils by simulated rainfall. Soil Science
Society of America Journal, 40, 769-773, Retrieved from DOI https://doi.org/10.2136/sssaj1976.0361599
5004000050040x
Hickey, R. 2000. Slope angle and slope length solutions for GIS. Cartography, 29 (1), 1-8, Retrieved from DOI
https://doi.org/10.1080/00690805.2000.9714334
Keesstra, S.D., Bouma, J., Wallinga, J., Tittonell, P., Smith, P., Cerdà, A., Montanarella, L., Quinton, J.N.,
Pachepsky, Y., van der Putten, W.H., Bardgett, R.D., Moolenaar, S., Mol, G., Jansen, B. and Fresco, L.O.
2016. The significance of soils and soil science towards the realization of the United Nations’ sustainable
development goals. Soil, 2 (2), 111-128, Retrieved from DOI https://doi.org/10.5194/soil-2-111-2016
Millward, A.A. and Mersey, J.E. 1999. Adapting the RUSLE to model soil erosion potential in a mountainous
tropical watershed. Catena, 38 (2), 109-129, Retrieved from DOI https://doi.org/10.1016 /S03418162(99)00067-3
Mortatti, J. and Probst, J.L. 2002. Silicate rock weathering and atmospheric/soil CO 2 uptake in the Amazon
basin estimated from river water geochemistry, Seasonal and spatial variations. Chemical Geology, 197 (14), 177-196, Retrieved from https://doi.org/10.1016/S0009-2541(02)00349-2
Renard, K.G., Foster, G.R., Weesies, G.A. and Porter, J.P. 1991. RUSLE, Revised universal soil equation.
Journal of Soil and Water Conservation, 46 (1), 30-33, Retrieved from URL https://www.jswconline.
org/content/46/1/30
Renard, K.G. and Fremund, J.R. 1994. Using monthly precipitation data to estimate the R-factor in the revised
USLE. Journal of Hydrology, 157 (1-4), 287-306, Retrieved from DOI http://dx.doi.org/10.1016/ 00221694(94)90110-4
Ryzak M., Bieganowski A., 2011. Methodological aspects of determining soil particle-size distribution using
the laser diffraction method. Journal of Plant Nutrition and Soil Science, 174 (4), 624-633, Retrieved from
DOI https://doi.org/10.1002/jpln.201000255
Silva, A.M., Schulz, H.E. and De Camargo, P.B. 2007. Erosão e hidrossedimentologia em bacias hidrográficas,
Segunda edição. Revista e ampliada. RiMa, ISBN 978-85-7656099-9, Brasil.
Soil Survey Staff. 1999. Soil taxonomy. A Basic System of Soil Classification for Making and Interpreting
Soil Surveys, USDA, 869. USA.
Wischmeier, W.H. and Smith, D.D. 1978. Predicting rainfall erosion losses, A guide to conservation planning.
U.S. Department of Agriculture, Washington, USA.

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Research article
erd

articleAssessment of Antibacterial Activity of Lactic Acid Research
Bacteria
Isolated from Fermented Foods against Escherichia coli
O157:H7 and Proteus penneri and Their Potential as Starter
Cultures

SINETH CHEV*
Faculty of Agro-Industry, Royal University of Agriculture, Phnom Penh, Cambodia
Email: chevsineth9999@gmail.com

SIVENG MENG
Faculty of Agro-Industry, Royal University of Agriculture, Phnom Penh, Cambodia

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

CHINDA CHHE
National Institute of Science, Technology, and Innovation, Phnom Penh City, Cambodia

RITHY CHRUN
Faculty of Agro-Industry, Royal University of Agriculture, Phnom Penh, Cambodia
Received 15 January 2023

Accepted 15 May 2023(*Corresponding Author)

Abstract Fermented fish and vegetables produced by spontaneous fermentation are the mostwell-known traditional foods in Cambodia. Even though fermented foods provide healthbenefits related to nutrition, probiotics, and postbiotics, some of them are not safe due to thesurvival of bacteria harmful to humans. The purpose of this research is to examine in vitro theantibacterial activity of lactic acid bacteria (LAB) isolated from fermented fish and vegetables
against E. coli O157:H7 and Proteus penneri, histamine forming LAB, and the survival of
LAB in low pH levels and high salt concentration using pH and salt tolerance tests. LAB was
isolated from 134 naturally fermented fish and vegetables from four different provinces andidentified using the Biolog GEN III MicroStation semi-automated system. The antagonistic
properties of these isolates against E. coli O157:H7, and Proteus penneri were examined using
a co-culture method at 24, 48, and 72 hours of incubation times. As a result, 36 strains of LAB
were identified from a total of 134 samples. Seven LAB species out of 36 strains can survive
at pH 3 for 6 hours, while four of these seven LAB can tolerate pH 2. Lactobacillus plantarum,
Lactococcus lactis, Lactobacillus gasseri, Leuconostoc lactis, and Leuconostoc gilidum havea significant capacity to inhibit E. coli O157:H7 and Proteus penneri growth when compared
to control. These five LAB do not produce histamine and can tolerate up to a 10% salt
concentration. All the results demonstrate that Lactobacillus plantarum, Lactobacillus lactis,
Lactobacillus gasseri, Leuconostoc lactis, and Leuconostoc gilidum have great potential for
use as starter cultures for suppressing pathogenic bacteria growth in fermented fish andvegetables.
Keywords fermented fish and vegetables, E. coli 0157:H7, lactic acid bacteria,
antimicrobial activity, pH and NaCl tolerance

INTRODUCTION
The nutritional balance and food security of traditional fermented foods have made them popularthroughout Asia. Across several Asian nations, methods for preserving crops, vegetables, meat, andfishery products seem to be well-developed. Moreover, Food preservation was the prime purpose ofⒸ ISERD

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fermentation, which was achieved by the synthesis of inhibitory metabolites including organic acid,ethanol, and antimicrobials combined with decreased water activity (Anal, 2019).
Cambodia is a kingdom in Southeast Asia that borders Vietnam, Laos, and Thailand. There aremany varieties of fresh fish and vegetables caused by the Tonle Sap Lake in the north of Cambodia
is recognized for its extensive river system and favorable climate for agriculture(LeGrand et al.,2020). Mostly in the traditional Cambodian diet, fermented foods play a significant role. There aredifferent fermented foods ready to eat (Chrun et al., 2017). It is well known that five groups offermented fish and vegetables including Pra hok (Fish paste), Pha’ork (Fermented fish), Trey
proheum (Salt Fish), Mam (Fermented Fish), and Chruk (Fermented vegetable) (LeGrand et al.,2020) and have their benefit in term nutritional function such as vitamins, proteins, essential fatty
acids, and amino acids (Nuraida, 2015). In addition, at the same time add value to agricultural
products (Chrun et al., 2017).
Microbiological research on Asian fermented foods reveals that the identification of 68 samplesof fermented vegetables from a local market in Cambodia contained Enterobacter spp. in 24% of thesamples (Chrun et al., 2017). Another study that examined 13 samples of fermented fish in Cambodia
discovered that the majority of the microbial communities were gram-positive cocci and rods suchas Bacillus, Clostridium, Staphylococcus, and Tetragenococcus (Chuon et al., 2014). In the case ofVietnam was found that unprocessed fish and poultry are likely to be contaminated with Salmonella
and in the absence of proper kitchen hygiene and may contaminate processed foods. Raw poultry
samples were found high levels of contamination with E. coli (45%), Campylobacter jejuni (28.3%),
and Salmonella (8.3%) and high-risk food classification. Additionally, raw fish, meat, and vegetables
all contained E. coli at rates of 21.3%, 6.6%, and 18.5%, respectively. This article confirmed theimportance of hygienic working practices when preparing food. (Thi et al., 2006). The purpose ofthis research is to examine in vitro the antibacterial activity of lactic acid bacteria (LAB) isolated
from fermented fish and vegetables against E. coli O157:H7 and Proteus penneri, histamine forming
LAB and and the survival of LAB in low pH level and high salt concentration using pH and salt
tolerance tests.
OBJECTIVE
The objective of this research is to examine in vitro the antibacterial activity of lactic acid bacteria(LAB) isolated from fermented fish and vegetables against E. coli O157:H7 and Proteus penneri,histamine forming LAB and the survival of LAB in low pH levels and high salt concentration using
pH and salt tolerance tests.
METHODOLOGY
Sample Collection Methods
Fermented fish and vegetable samples are divided into five groups such as Pra hok (Fish paste),
Pha’ork (Fermented fish), Mam (Fermented fish), Salted fish (trey proheum) and Chruk (Fermented
vegetable). All samples were collected from 4 provinces such as Kompong Thom, Siem Reap,
Kandal, and Kompong Cham province. All samples are purchased from small-scale producers andlocal markets. There are 134 samples in total. For fish paste (Pra hok, n=17), Fermented fish (Pha’ork,n=30), Fermented fish (Mam, n=11), and Fermented vegetables (Chruk, n=76). All samples weresealed in plastic sample bags and stored in cool boxes during transportation to the laboratory which
was less than 24 hours. After the arrival, all samples were immediately studied for their identification.
Sample Identification
Pure colonies were conducted with several tests before using Biolog System (Semi-Auto
Microstation) for identification. These tests helped to avoid misidentification and save a lot of money
since the Biolog System is costly. Most important tests such as Gram staining, Catalase, and OxidaseⒸ ISERD

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are alternatives yet also help to give information on bacterial characteristics. The suspected pure
LAB were sub-cultured two times to ensure the purification of the colony on MRS agar before culture
on BUG Agar before identification with the Biolog system. By using GENIII-Microplate (BIOLOG)
within protocol-C, inoculate pure colony from BUG Agar into Inoculating Fluid-C (IF-C) (provided
by BIOLOG) within 92 to 95% Turbidity by using a Turbidity Meter (BIOLOG). Using an electric
multi-dispense micropipette (SARTORIOUS), dispense 100 microliters in each microplate well thenincubate the plate at 30oc for 20 to 24 hours and using Microstation (BIOLOG) accompany with
Microlog Software (BIOLOG) for interpreting the ID result of identification(Al-Dhabaan & Bakhali,2017).
Antimicrobial Activities by Co-culture Method
10% of LAB suspension (9 Log CFU/ml) was inoculated with 6 Log CFU/ml of indicator E. coli
0157:H7 and Proteus penneri in each tube of MRS broth. This experiment was performed underaerobic conditions at 30 0C in the water bath for 72 hours. Every 24 hours, the presence of indicators
was determined by streaking on selective Agar and incubating at 350C (Balouiri et al., 2016).
pH and Sodium Chloride Tolerance
LAB against E. coli 0157:H7 and Proteus penneri by co-culture method have been conducted with
pH and sodium chloride tolerance. Selected LAB isolates were grown in MRS broth at 30°C
overnight before being sub-cultured in new MRS broth by using HCl (0.1M) adjusted pH to 2 and 3
and used to adjust the salt content in MRS broth (5%, 6%, 7%, 8%, 9%, and 10%). Following an
incubation period of 24 hours at 30°C (Dimic et al., 2015). After this, Streak Method on MRS Agar
was used to confirm the tolerance of each LAB (Balouiri et al., 2016).
Determine the Concentration of Histamine Produced by Lactic Acid Bacteria
LAB was refreshed on MRS Agar at 30 0C for 24 hours. Inoculate one loop full colony of both Lactic
acid bacteria in TSB broth with histidine and incubate at 30 ℃ for 24 hours centrifuge 6000 rpm/min
for 15 min. Suspend 1 ml of supernatant in 9 ml of sterile saline for dilution 10-fold. After dilutionthat supernatant was used in the enzymatic histamine assay (Leszczyocha and Pytasz, 2018).
Histamine concentration was calculated as follows.
Histamine concentration (mg/L = ppm) = (Es - Eb) ÷ (Estd - Ec) × 4 × 25 × dilution factor
RESULTS AND DISCUSSION
The LAB species isolates were examined based on selective agar media called MRS and sub-cultured
for few times until obtained a pure culture. The later suspected colony was Gram-positive, clusteredcocci or bacilli, catalase-positive, and oxidase positive. LAB was later identified by using Biolog
semi-auto system as shown in Fig. 1. Of 134 samples, 98 samples were rejected due to the absenceof a suspected colony. group of Mam (n=11) isolated as L. lactis and P. parvulus (27%). There are
12% of group Prahok (n=17) isolated as P. parvulus and P. pentosacues. Other groups of Pha’ork(n=30) detected 10% were L. garvieae, P. parvulus, and P. pentosaceus. And 37% of group Chruk(n=76) isolated as Lactobacillus, P. parvulus, P. pentosaceus, L. alimentarius, L. mali, L. gasseri, P.
acidilactici, L. acidophilusBGA, L. lactis, P. sanguinis, Leu. gelidum, Tetra. solitarius, L. garvieae,
L. reuteris, L. plantarum, Leu. citrem, L. bifermentans, and L. salivarius. We found the relevance of
the identification LAB by the API 50 CHL system from fermented food in Cambodia, thus three
species of lactic acid bacteria were found, including Lactobacillus acidophilus and Lactobacillus
plantarum. strains Y'11b,2, Y'11e,2, and Y'85,1. (Sophakphokea1 et al., 2021). According to (Ly etal., 2022) to study dentiﬁcation, Classiﬁcation and Screening for γ-Amino-butyric Acid Productionin Lactic Acid Bacteria from Cambodian Fermented Foods by using Matrix-assisted laserⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2023) 14-1

desorption/ionizing time-of-flight mass spectrometry (MALDI-TOF MS) and partial 16S rDNA
sequencing were used to identify 68 LAB. And the result shows as one Lactobacillus futsaii, two
Lactobacillus namurensis, and three Lactobacillus plantarum strains were found in fermented foodin Cambodia.

Fig. 1 Isolated LAB from fermented fish and vegetables in Cambodia
Table 1 Result of antimicrobial activities by co-culture method
SpeciesnTime
E. coli 0157:H7
24 h+++
Leuconostoc lactis
3
48 h
++
72 h
+
24 h
++
Lactobacillus gasseri
3
48 h
72 h
24 h
+++
Lactobacillus plantarum
3
48 h
++
72 h
+
24 h
++
Lactococcus lactis
3
48 h
72 h
24 h
+++
Leuconostoc gelidum
3
48 h
+
72 h
+
24 h
++
Lactococcus garvieae
3
48 h
+
72 h
+
24 h
+++
Lactobacillus mali
3
48 h
++
72 h
++
“+” represent to positive or resistance and “-” represent to negative or susceptible

Proteus penneri
+++
+
+++
+
++
+
+
+++
++
++
+
+++
+
-

According to the results shown in Table 1. Lactic acid bacteria are able to against E. coli
0157:H7 such as Lactobacillus gasseri and Lactococcus lactis. Moreover, Lactic acid bacteria able
to against Proteus penneri were Lactobacillus mali, Lactococcus garvieae, Leuconostoc gelidum,
Lactococcus lactis, Lactobacillus plantarum, and Leuconostoc lactis. Hassanzadazar et al. (2012)
studied about antibacterial activity of Lactic Acid Bacteria against Escherichia coli, Listeria
monocytogenesis, Bacillus cereus, and Salmonella enteritidis, and reported that lactic acid showed
the strongest inhibitory activity against gram-positive bacteria than gram-negative bacteria. Similarly,
Muzikowski (2009) also reported some species of Lactobacilli against different gram-positive andgram-negative bacteria were determined by agar-well diffusion assay. It also shows the antagonistic
effect of the antibacterial agent on the growth of other gram-positive and gram-negative pathogenicⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2023) 14-1

microorganisms which E. coli, Listeria monocytogenes, Salmonella enterica, Staphylococcus aureus
and Bacillus cereus.
The pH tolerance is an important characteristic of species that hoped to affect the gastrointestinal
tract. Moreover, tolerance to salt was an important cause of cell membrane structure can become
damaged by salt. A study by Azam et al. (2017) focused on the isolation and characterization of
Lactobacillus spp. from kefir samples in Malaysia mentions that Lactobacillus spp. isolated fromkefir E was unable to survive in all pH conditions (pH 2, 3, and 4). All isolates tested did not survive
pH 2.0, most of the isolated Lactobacillus spp. from kefir samples were able to tolerate the moderate
pH levels of pH 3.0, pH 4.0, and all the isolated Lactobacillus spp. from kefir samples survived at
0.3-0.5% bile concentration after incubation. The Lactobacillus spp. from kefir H conferred thehighest survival rate at 0.3% and 0.5% bile concentration, with a survival rate of 96.89 ± 0.02% and96.84 ± 0.02%, respectively. Subsequently, the survival rate in bile salt condition was followed byisolated Lactobacillus spp. from kefir G and kefir C. (Hassanzadazar et al., 2012) research was done
into the Investigation of antibacterial, acid, and bile tolerance properties of lactobacilli isolated from
Koozeh cheese. The screening process involved 28 different Lactobacillus species that were obtained
from Koozeh cheese, a typical cheese. A control pH of 7.5 was used while the acid tolerance test wasinvestigated at pH 2.0 and 3.0 with 5 N HCl. Results showed that only one out of twenty-eight isolates
have the ability to tolerate acid and bile salts. The ability to produce histamine of LAB was acceptable
due to the concentration of histamine higher than 200 ppm will cause the disease in a human(Leszczyocha and Pytasz, 2018, Food Safety Authority of Ireland, 2005).
Table 2 Result of salt, pH tolerance test, and Histamine of identified bacteria fromfermented samples
pH and salt tolerance
Bacteria species

Salt (%)
pH
5
6
7
8
9
10
2
3
Lactococcus garvieae
+
+
+
+
+
+
0%
14%
Lactobacillus mali
+
+
+
+
+
+
21% 50%
Leuconostoc lactis
+
+
+
+
+
+
10% 13%
Lactobacillus gasseri
+
+
+
+
+
+
12% 18%Lactobacillus plantarum
+
+
+
+
+
+
32% 52%
Lactococcus lactis
+
+
+
+
+
+
26% 44%
Leuconostoc gelidum
+
+
+
+
+
+
0%
20%
“+” represent to positive or resistance and “-” represent to negative or susceptible

Histamine
concentration
ppm
2.35
4.70
6.79
7.05
7.8
10.1
3.9

CONCLUSION
Seven Lactic acid bacteria out of 36 species, such as Lactobacillus mali, Lactococcus garvieae,
Leuconostoc gelidum, Lactococcus lactis, Lactobacillus plantarum, and Leuconostoc lactis wereisolated and identification by using Biolog System (Semi-Auto Microstation) were found fromfermented fish and vegetables. according to this study two species of LAB inhibition against E. coli
0157:H7 and all these seven species inhibitions against Proteus penneri. The identified bacteria
isolated were subjected to different salt concentrations (5%, 6%, 7%, 8%, 9%, and 10%). Bacteria
species Lactococcus garvieae, Lactobacillus mali, Leuconostoc lactis, Lactobacillus plantarum,
Lactococcus lactis, Leuconostoc gelidum can tolerate with salt up to 10% and tolerate either pH3 inrate (14%, 50%, 13%, 18%, 52%, 44%, and 20%) nor pH2 in rate (21%, 10%, 12%, 32%, and 26%).
In contrast, Lactococcus garvieae and Leuconostoc gelidum weren’t tolerated with pH2. On the other
hand, these seven species LAB were not histamine-producing bacteria due to the level of histamine
concentration lower than 10 ppm. All the results demonstrate that Lactobacillus plantarum,
Lactococus lactis, Lactobacillus gasseri, Leuconostoc lactis, and Leuconostoc gelidum have a great
potential for use as starter cultures for suppressing pathogenic bacteria growth in fermented food.

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IJERD – International Journal of Environmental and Rural Development (2023) 14-1

ACKNOWLEDGEMENTS
This work was supported by World Bank under Higher Education Improvement Project (HEIP), IDA
Credit No. 6221-KH, Sub-project Partnership Program to Enhance Agro-Industry Education andResearch Project SGA#02, Faculty of Agro-Industry, Royal University of Agriculture.
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Al-Dhabaan, F.A.M. and Bakhali, A.H. 2017. Analysis of the bacterial strains using Biolog plates in thecontaminated soil from Riyadh community. Saudi Journal of Biological Sciences, 24 (4), 901-906,
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Anal, A.K. 2019. Quality ingredients and safety concerns for traditional fermented foods and beverages from
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Azam, M., Mohsin, M., Ijaz, H., Tulain, U.R., Ashraf, M.A., Fayyaz, A., Ul Abadeen, Z. and Kamran, Q. 2017.
Lactic acid bacteria in traditional fermented Asian foods. Pakistan Journal of Pharmaceutical Sciences, 30(5), 1803-1814. Retrived from URL https://pubmed.ncbi.nlm.nih.gov/29084705/
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Chrun, R., Hosotani, Y., Kawasaki, S. and Inatsu, Y. 2017. Microbioligical hazard contamination in fermented
vegetables sold in local markets in Cambodia. Biocontrol Science, 22 (3), 181-185, Retrieved from DOI
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Chuon, M.R., Shiomoto, M., Koyanagi, T., Sasaki, T., Michihata, T., Chan, S., Mao, S. and Enomoto, T. 2014.
Microbial and chemical properties of Cambodian traditional fermented fish products. Journal of the Scienceof Food and Agriculture, 94 (6), 1124-1131, Retrieved from DOI https://doi.org/10.1002 /jsfa.6379
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International Quarterly Journal. 3 (3), 181-185, Retrieved from URL http://www.pubmedcentral.nih.gov/
articlerender.fcgi?artid=PMC4299980
LeGrand, K., Borarin, B. and Young, G.M. 2020. Tradition and fermentation science of prohok, An ethnic
fermented fish product of Cambodia. Journal of Ethnic Foods, 7 (1), 1-19, Retrieved from DOI https://doi.org/10.1186/S42779-019-0027-1
Leszczyocha, M. and Pytasz, U. 2018. The histamine content in some samples of food products. Czech Journalof Food Sciences, 22 (3), 81-86, Retrieved from DOI https://doi.org/10.17221/3410-cjfs
Ly, D., Mayrhofer, S. and Domig, K.J. 2022. An evaluation of the phenotypic antibiotic susceptibility ofpotential lactic acid bacteria starter cultures isolated from Cambodian fermented foods. Frontiers in Food
Science and Technology, 2, 1-11, Retrieved from DOI https://doi.org/10.3389/frfst.2022.892319
Muzikowski, J.A. 2009. Self-assessment of TQM progress. Annual Technical Conference, ANTEC,
Conference Proceedings, 3 (1), 4007-4011.
Nuraida, L. 2015. A review, Health promoting lactic acid bacteria in traditional Indonesian fermented foods.
Food Science and Human Wellness, 4 (2), 47-55, Retrieved from DOI https://doi.org/10.1016/j.fshw.
2015.06.001
Say Sophakphokea et al. 2021. Identification of lactic acid bacteria isolated from local commercial yahe
(fermented caridean shrimp) products. Ras Microbiology and Infectious Diseases, 1 (3), 1-5, Retrieved
from DOI https://doi.org/10.51520/2766-838x-11
Stanojevic-Nikolic, S., Dimic, G., Mojovic, L., Pejin, J. and Stanojevic, S. 2015. Antimicrobial activity oflactic acid against pathogen and spoilage microorganisms. Journal of Food Processing and Preservation,
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Thi, H.A., Dao, A.N.H. and Yen, P.T. 2006. Escherichia coli contamination in raw food available in factories,
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262-265, Retrieved from DOI https://doi.org/10.1196/annals.1373.033Ⓒ ISERD

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Research article
erd

Nitrogen Removal from Mining Dewatering and theResearch
Fate articleofWater Release to a River
BARRY NOLLER*
Sustainable Minerals Institute, University of Queensland, Australia
Email: b.noller@uq.edu.au
Received 30 January 2023

Accepted 15 May 2023(*Corresponding Author)

Abstract Seepage water in underground mining voids arises from interception with aquifers
that may become contaminated with nitrogen (N)-based explosive during undergroundblasting operations. The nitrogen-contaminated water may be pumped from undergroundmining voids and stored at the surface or discharged to a nearby river without treatment if
sufficient dilution is achieved to minimize effects on the aquatic environment and pastoral
activities. Maximum N concentration in dewatering water was observed to be 200 times thereceiving water of the nearby river when compared against ANZECC/ARMCANZ (2000)
water quality guidelines. This study sought to identify sources of N contamination ofunderground seepage water, pumped to the surface for discharge to the nearby river. The levelof protection (for an aquatic ecosystem) specified the water quality objectives to be achieved
following water release. The ANZECC/ARMCANZ (2000) has three levels of aquatic
ecosystem protection, and ‘Level 2 Aquatic Ecosystem’ was selected being described asapplying to slightly–moderately disturbed systems including rural streams receiving runoff
from land disturbed to varying degrees by grazing or pastoralism, nearby or adjacent to urban
areas. The study considered river flow data, underground dewatering production, discharge
rates, and river water quality for upstream and downstream of the discharge point, as well as
quantities of explosives used underground at specified % N in explosives estimated to remain
following blasting. The most important nitrogen form present in the mine discharge
wastewater was found to be oxidized-N (>93%). Only 0.54 % of end-of-pipe discharge wasmeasurable in the downstream river and indicated that rapid dilution and removal of oxidizedN (nitrate/nitrite) by biota could be achieved. The level of oxidized-N expressed as load
discharged to the river showed that the quantity of N discharged was similar in magnitude to
the spillage of 4% explosive.
Keywords nitrogen, explosive, mining, dewatering, discharge, cattle, aquatic species

INTRODUCTION
Seepage water in underground mining voids arises from interception with aquifers that may becomecontaminated with nitrogen-based explosives during underground blasting operations. Ammonium
nitrate used commonly as an explosive is the same as the common fertilizer. Nitrogen (N)contaminated water may be pumped from underground mining voids and stored at the surface fortreatment or discharged to a nearby river without treatment if sufficient dilution is achieved tominimize effects to the aquatic environment and pastoral activities and can be demonstrated andapproved by Government regulators. Existing nitrogen (N)-contaminated water added upstream
arises from local agricultural and urban activities and may affect the aquatic ecosystem. This study
sought to identify sources of nitrogen contamination of underground mining seepage water, pumped
to the surface for discharge to the nearby river and if additional nitrogen (N)-contaminated water
pumped to the river gives further effects on the aquatic ecosystem. The level of protection (for an
aquatic ecosystem) specified the water quality objectives to be achieved following water release
follows the ANZECC/ARMCANZ (2000) levels of aquatic ecosystem protection.

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IJERD – International Journal of Environmental and Rural Development (2023) 14-1

OBJECTIVE
The objective of this study is to identify sources of N contamination of underground seepage waterfrom a mining operation that is pumped to the surface for discharge to a nearby river and to identify
if the level of protection (for an aquatic ecosystem) of the specified water quality criteria can beachieved following water release.
METHODOLOGY
The study is based on a site in Queensland, Australia, and considered river flow data, undergrounddewatering production from mining, discharge rates, and river water quality upstream anddownstream of the discharge point (Noller, 2006).
The level of protection (for an aquatic ecosystem Environmental Value - EV) is the level ofaquatic ecosystem condition specified by water quality objectives (WQOs) to be achieved for theintended water. The Queensland Water Quality Guidelines (QWQG, 2006) were developed
concurrently with the EVs and water quality objectives (WQOs) and release process. These aretechnical guidelines for deriving WQOs for rivers in Queensland and include locally and regionally
relevant water quality data for fresh, estuarine, and marine waters.
The ANZECC/ARMCANZ (2000) established three levels of aquatic ecosystem protection thatare applied by QWQG (2006). The levels of aquatic ecosystem protection are: (i) Level 1: Highecological/conservation value ecosystems - effectively unmodified or other highly valued systems;(ii) Level 2: Slightly–moderately disturbed ecosystems - ecosystems in which aquatic biologicaldiversity may have been adversely affected to a relatively small but measurable degree by humanactivity; and (iii) Level 3: Highly disturbed ecosystems - measurably degraded ecosystems of lower
ecological value. The EVs and WQOs identified that the study river is: A level 2 Aquatic Ecosystem.
This is described by ANZECC/ARMCANZ (2000) as an ‘Ecosystem in which aquatic biologicaldiversity may have been adversely affected to a relatively small but measurable degree by humanactivity’. The biological communities remain in a healthy condition and ecosystem integrity is largely
retained. Typically, such systems have slightly to moderately cleared catchments and/or reasonably
intact riparian vegetation. Slightly–moderately disturbed systems could include rural streams
receiving runoff from land disturbed to varying degrees by grazing or pastoralism. This description
fits the surrounding area of the study mine and river.
Ammonium nitrate is the key explosive used in the underground workings at the study mine.
The quantities of ammonium nitrate explosives with specified % N used at the underground minegave an estimate of remaining explosives following blasting. As a general rule, 1 tonne of rock uses
1 kg of explosive. Some ammonium nitrate may be spilt during charging and was estimated to be 4%
based on collecting residues and weighing them (Noller, 2006).
Water quality was collected and analyzed for dewatering from an underground source, to thedischarge point, following discharge to a local river, upstream and downstream at the following sites:(i) Dewatering from underground; (ii) Dewatering storage tank at exit to discharge pipe before
discharge to the local river; (iii) Downstream local river beyond mixing zone; and (iv) Upstream ofthe local river, including an historical gauging site of 40 years operation. Water samples werecollected by mine staff and water quality data was measured by the mine laboratory for pH, total
dissolved solids (TDS), suspended solids (SS), N forms as total unfiltered nitrogen, total filtered N,
nitrite and nitrate (oxidized-filtered), particulate N (>0.45 µm), organic-N (total - oxidized-N) andammonium ion (filtered). Filtration for N was conducted on-site using 0.45 µm cartridge membranefilters with a plastic syringe.
The site water budget included water quality of water consumed on site, water discharged
quantities, and surface runoff from sub-catchments on site. The Queensland regulator has a large
number of monitoring sites and gauging stations on the study site river (N and M, 2006). An upstream
gauging station with 40 years of records was selected as having the most complete and relevant set
to the discharge of the study mine (Noller, 2006).

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RESULTS AND DISCUSSION
Table 1 gives the average monthly river flow (ML) for September to February at the main upstream
gauging station which corresponds to the release of water from the mine. January and February andthe annual summer rains (see Table 1 for rainfall during the study period). The data record formonthly flow at the upstream gauging station over 40 years had the corresponding average monthly
flow for the period ending 2,400 hrs. and was 68,970 ±178,630 ML. According to the Queensland
Environmental Authority water from the mine must not be discharged to the river when the flow rate
at the main upstream gauging station is less than 20 ML (Noller, 2006). For the period November–
December (Table 1) the total underground transfer from the discharge tank to the river was 11,222
kL/month, based on a rate of 362 kL/day. The accumulated groundwater from the mine that wasdischarged to the river contained a consistently high total N level that was primarily oxidized-N.
Table 1 Monthly River flow (ML) at the main upstream gauging station over
40-years period
Month
September
OctoberNovember
DecemberJanuary
February

MeanaStandard deviationa

14,575
17,384
31,67850,762
115,284
210,310Percent (%)

23,85027,49147,532
11,106
319,054379,291

Monthly rainfall (mm)at mineb

44.41
1.34
15.17
16.52
15.64
8.79

134
216
141
-

Source and explanation: a. NR&M (2006); b. Noller (2006)

Table 2 gives a summary of ammonium nitrate used by the mine during the period from
September to February. It is noted that all explosives were consumed in the explosion, apart fromspillage (Noller, 2006). Assuming that spillage was 4%, 2,009 kg ammonium nitrate was dissolvedin the underground water system from September to February. The established guide of 4,000
kg/month was equivalent to 1,400 kg-N/month and the loss of 160 kg is 56 kg-N. The calculated loadof N released from the rising water main, discharge tank, and via the pipe was compared with thetotal ammonium nitrate used and spillage at the mine (Table 2). Percent N in explosives gave a total
N budget, together with an estimate of how much remains following blasting.
Table 2 Total ammonium nitrate (as % of explosive use) consumption over a 6-month
periodExplosive Accounting
period (% Explosive
use)a
May
OctoberNovember
DecemberJanuary
February
Total

Total ammonium
nitrate (kg)a
7,467.4
11,778.9
4,099.1
6,435.7
10,714.8
11,784.2
52,280.0

Spillage ammonium
nitrate estimated at
4% (kg)a
299
471
164
257
426
471
2091

Total
ammonium
nitrate-N (kg)b
2,614
4,122
1,435
2,253
3,750
4,124
18,298Spillage-N
estimated at 4%
(kg)b
104.5
164.9
57.4
90.1
150.0
165.0
731.85

Source and explanation: a. Noller (2006); b. Factor for ammonium nitrate - N = Total x 0.35; molecular weight = 80

Table 3 gives the calculated and measured loads of N from underground dewatering anddischarged to the river, including a summary of the oxidized-N discharged from the mine to the river,showing that the quantity of N discharged was similar in magnitude to the spillage of 4% explosive.
Table 4 gives the predicted and measured oxidized–N concentration in the river based on end-ofⒸ ISERD73

IJERD – International Journal of Environmental and Rural Development (2023) 14-1

pipe discharge and river mean flow. The difference between measured and calculated concentrations
indicates lower recent flow in the river compared with the historical record. Some particulate formsof N arose from the mine dewatering, but most N present was filterable, as expected from explosive
residues. Some particulate N (100 µg/L) was also present in river water (Noller, 2006), but data was
not included in Tables 3-5.
Table 3 Calculated and measured loads of nitrogen from underground dewatering
Measured nitritenitrate-N end ofpipe (µg/L)a21,80019,80017,60018,900-End of pipe
discharge (kL)aMonth
OctoberNovember
DecemberJanuarySum

5,260
11,222
7,157
9,030
-

Nitrogendischarged end ofpipe (kg-N)a
114.7
222.2
126.0
170.7
633.6

Spillage of 4%
explosive
as -N (kg)a
269.4
297.5
(Nov-Jan)
165.0
731.85

Source and explanation: a. Noller (2006)

Table 4 Predicted and measured nitrate and nitrate – N concentration in riverMonthRiver mean
monthly
flow (ML)a

End of pipe
discharge(kL)b17,384
31,67850,762
115,284

5,260
11,222
7,157
9,030

OctoberNovember
DecemberJanuary
Range

MeasuredOxidized -N
end of pipe(µg/L)b
21,80019,80017,60018,900

Dilutionratiob
3,305
2,823
7,093
12,767Predicted
Oxidized -N
river (µg/L)b

MeasuredOxidized-N
river (µg/L)b

6.6
7.0
2.5
1.5
1.5-7.0

997
254
166
12
997-12

Source and explanation: a. NR&M (2006); b Noller (2006)

Table 5 Nitrogen in underground seepage water and following discharge to river

Rising water main (µg/L)

20,900Total N (filtered<0.45µm)a
19,200Discharge Tank (µg/L)

19,900End of pipe discharge (µg/L)
River upstream 10m (µg/L)
River downstream 10m(µg/L)
River main upstream
gauging station 40 years(µg/L)
Queensland water quality
guideline (µg/L)b,c

Site

Total Na

Oxidized-Na

Ammonia-Na

20,000270

20,50031,3000.10

20,20018,70018,700

130

500

400

50

60

1,100

0.50

0.17

70

750

-

0.29

21

<250

-

<10

<10

Source and explanation: a. Noller (2006); b. QWQG (2006) annual median; c. QWQG (2006) guideline for OrganicN <200µg/L =total-N – oxidized-N

Table 5 gives N in underground seepage water and following its discharge to the river. The mostimportant N form present in the mine discharge wastewater was found to be oxidized-N (>93%).
Only 0.54 % of end-of-pipe discharge was measurable in the downstream river and indicated that
rapid dilution and removal of oxidized-N by biota could be achieved. The level of oxidized-N
expressed as load discharged to the river showed that the quantity of N discharged was similar inⒸ ISERD

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magnitude to the spillage of 4% explosive. The accumulated groundwater from the mine that isdischarged to the river contains a consistently high total N level that is primarily oxidized-N.
The historical upstream gauging station data for the river (Table 5) shows that total N has been
consistently higher than the Queensland water quality guideline Level 2 water quality guideline,
including upstream of the mine, for a long period of time. The results in Tables 5 and 6 show that theriver has had a consistently high nitrogen load that exceeds the current guideline. An additional loadto the river was added by the mine discharge. Table 6 gives water quality in underground seepage
water and following discharge to the river for pH, total dissolved solids, and suspended solids. pH
was marginally lower than the mine dewatering which also contributed to salinity. Suspended solids
remained at or lower than the guideline.
Table 6 Water quality in underground seepage water and following discharge to the river
Site
Rising water main
Discharge Tank
End of pipe discharge
River upstream 10m
River downstream 10m
River main upstream
gauging station 40 years
Queensland water quality
guidelines

pHa

Total dissolved solids (mg/L)a

Suspended solids (mg/L)a

8.18
8.18
8.16
7.90
7.8

2,280
2,280
913
247
260

6
6
2
4
5

7.7

-

-

6.5-8.2-<6

Source and explanation: a. Noller (2006); b. QWQG (2006) annual median.

Total N in river upstream water was 500 µg/L which exceeded the Queensland water quality
guideline (Table 5). The river 10m below discharge was 1,100 µg/L Total N which also exceeded theguideline (QWQG, 2006). Some particulate N (100 µg/L) arose from the mine dewatering but mostN present was filterable (Noller, 2006).
Ammonia in the river upstream (60 µg/L) and downstream river (70 µg/L) both exceeded theQueensland water quality guideline level of 10 µg/L (Table 5). The addition of ammonia from themine to the river was therefore 10 µg/L and the level at the river downstream exceeded the QWQG
(2006) guideline. The discharge of any ammonia from the mine dewatering was compromised by theexisting river load.
Oxidized-N in the river upstream was 50 µg/L which exceeded the guideline (<40 µg/L). The
river downstream level was 170 µg/L and indicated an addition of 120 µg/L oxidized-N to the riverfrom mine dewatering. However, comparison with the end of pipe discharge and river downstream
oxidized-N indicated efficient removal of oxidized-N. The oxidized-N discharged from the end of
the pipe was in the key form of oxidized-N i.e., 18,700/20,200 X 100 = 92.6 % of Total-N. However,the discharge of any oxidized-N like ammonia from mine dewatering was compromised by theexisting river load. Although the oxidized-N at the end of the pipe was 18,700 µg/L, the difference
between the river upstream and river downstream was only 120 µg/L.
Organic-N concentration, calculated as the difference between total and oxidized-N, was very
low. The upstream river level was <100 µg/L compared with the river downstream level of 330 µg/L,
the latter exceeding the QWQG (2006) guideline figure of 200 µg/L. This may be due to the presenceof urea or a similar soluble organic form of nitrogen from pastoral and crop activities.
The most important N form present in the mine discharge was therefore the oxidized-N (>93%)
and organic-N was less important. Some particulate-N was also present. The fact that only 0.54 % of
end-of-pipe discharge remained measurable in the river downstream indicated that rapid dilution andremoval of oxidized-N by biota was occurring. Maximum N concentration in dewatering water forthis study was observed to be 200 times the receiving water of the nearby river when comparedagainst ANZECC/ARMCANZ (2000) water quality guidelines and ‘Level 2 Aquatic Ecosystem’ thatwas selected for this river receiving runoff from land disturbed to varying degrees by grazing or
pastoralism, nearby or adjacent to urban areas.
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CONCLUSION
The study showed that accumulated underground groundwater from the mine dewatering being
discharged to the river had a consistently high total N level that was primarily oxidized-N (>93%)
and was derived from 4% ammonium nitrate spillage from blasting. Although only 0.54 % of endof-pipe mine discharge was measurable in the downstream river and indicated that rapid dilution andremoval of oxidized-N by biota could be achieved, the Total N in river upstream water was 500 µg/L
which exceeded the QWQG (2006) water quality guideline (Table 5). The river 10m below discharge
was 1,100 µg/L Total N which also exceeded the guideline (QWQG, 2006), but most N present was
filterable (Noller, 2006). Ammonia in river upstream (60 µg/L) and downstream river (70 µg/L) bothexceeded the QWQG (2006) water quality guideline level of 10 µg/L (Table 5).
The selected ‘Level 2 Aquatic Ecosystem’ Slightly–moderately disturbed ecosystemsecosystems in which aquatic biological diversity may have been adversely affected to a relatively
small but measurable degree by human activity for the receiving water of the nearby river whencompared against ANZECC/ARMCANZ (2000) water quality guidelines for this river receiving
runoff from land disturbed to varying degrees by grazing or pastoralism, nearby or adjacent to urban
areas. However, the presence of excess Total N in the river water from upstream agricultural andurban activities compromised the mine water discharge. The discharge of any ammonia from themine dewatering was also compromised by the existing river load.
Thus, treatment options for the mine-discharged water were required and focused on the removalof oxidized N. Ammonia was effectively removed by a shift in the equilibrium of its dissolved form
prior to its transfer to the surface, i.e., the ammonia was either removed as nitrogen gas or converted
to nitrate. The co-cations in the solution are alkaline and alkaline earth metals and not hydrogen ionsas the pH are relatively high.
ACKNOWLEDGEMENTS
I acknowledge the use of the University of Queensland and its facilities of the former National
Research Centre for Environmental Toxicology that were located at Queensland Health Forensic andScientific Services, Coopers Plains QLD 4108, Australia for providing facilities, funding, and accessto the laboratory.
REFERENCESANZECC/ARMCANZ. 2000. ANZECC & ARMCANZ (2000) water quality guidelines. Canberra, Australia,
Retrieved from URL https://www.waterquality.gov.au/anz-guidelines/resources/previous-guidelines/
anzecc-armcanz-2000
Noller, B.N. 2006. Unpublished report. The University of Queensland.
NR&M. 2006. Old natural resources & mines. NR&M Watershed, Brisbane, Australia, Retrieved from URL
http://www.nrm.qld.gov.au/watershed/precomp/138007/
QWQG. 2006. Queensland water quality guidelines. Brisbane, Australia, Retrieved from URL http://www.
epa.qld.gov.au/environmental_management/water/water_quality_guidelines/Ⓒ ISERD

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Research article
erd

Research article
Development of Erosion Protection Zones in the Catchmentof the Kalimanci Reservoir, North Macedonia

IVAN MINCHEV*
Hans Em Faculty of Forest Sciences, Landscape Architecture and Environmental Engineering,Ss. Cyril and Methodius University in Skopje, Republic of North Macedonia
Email: ivan.minchev@sf.ukim.mk

IVAN BLINKOV
Hans Em Faculty of Forest Sciences, Landscape Architecture and Environmental Engineering,Ss. Cyril and Methodius University in Skopje, Republic of North Macedonia

ALEKSANDAR TRENDAFILOV
Hans Em Faculty of Forest Sciences, Landscape Architecture and Environmental Engineering,Ss. Cyril and Methodius University in Skopje, Republic of North Macedonia

BOZHIN TRENDAFILOV
Hans Em Faculty of Forest Sciences, Landscape Architecture and Environmental Engineering,Ss. Cyril and Methodius University in Skopje, Republic of North Macedonia
Received 26 February 2023

Accepted 20 May 2023(*Corresponding Author)

Abstract Construction of reservoirs is a priority for ensuring sustainability of water resources.
In the Republic of North Macedonia, there are 23 big and over 120 small water reservoirs. On
the other hand, erosion and the filling of reservoirs with sediment is one of the main problems
in reducing the lifespan of the reservoir. The total annual accumulated sediment in all thereservoirs in the Republic of Macedonia is 3,000,000 m3 (Erosion map of RM, 1993). The
selected study area for the current research is the Kalimanci reservoir in the frames of thecatchment of the Bregalnica River, North Macedonia. The main method used to estimate thesediment transport on catchment level is the Erosion Potential Method (EPM; Gavrilovic
method), and the validity is assessed on the basis of accumulated sediment in the reservoirs.
The EPM method only estimates the total transported sediment at one point. To estimate how
the sediment is transported, re-transported, and accumulated in the river bed, a hydraulicsediment transport model (HEC RAS) was used. Then the critical sub-catchments from anerosion point of view are delineated. Most of the critical sub-catchments are situated aroundthe Kalimanci reservoir, while the middle of the catchment experiences erosion of medium
severity, and the highest parts of the Bregalnica River are the least critical. The largest part ofthe sediment transported by the Bregalnica River (nearly 75%) is deposited in the valleys.
With the aggregation of the previous steps, the erosion zones of the Kalimanci reservoir wereidentified.
Keywords erosion, bathymetry, GIS, zoning, erosive sediment material

INTRODUCTION
The soil and the water are two out of three components of the natural environment. Water is arenewable resource, but the soil genesis on the other hand is a long-term process. So, in other words
the soil is not a renewable resource (Blinkov et al, 2003). Soil erosion is deemed as the mostimportant, most dangerous, and most spread type of soil degradation and it is the limiting factor of
the sustainable use of the land and development of the areas, states, and regions.
The construction of reservoirs is a priority for providing sustainability of the water resources.
In the Republic of North Macedonia, there are 23 big and over 120 small water reservoirs. On theother hand, erosion and filling the reservoirs with sediment are one of the main problems in reducingⒸ ISERD

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the lifespan of the reservoir. The total annual accumulated sediment in all the reservoirs in the
Republic of Macedonia is 3,000,000 m3 (Erosion map of RM, 1993). It is estimated that worldwide,
annually, from 0.5% to 1% of the total storage of reservoirs is lost because of filling up the reservoirs
with sediment (White, 2001).
Soil erosion is the main cause of filling up the water reservoirs with sediment. The intensity ofthe erosive processes in the catchment is the main driver for sedimentation but on the other hand, it
is very important where those processes occur. If the erosion hotspots are in the vicinity of thereservoir or on the main waterway it can be assumed that the produced sediment will be mostlytransported into the reservoir. In this manner, it is very important to perform zoning of the reservoir
catchment to prioritize anti-erosive activities and do appropriate land management.
OBJECTIVE
The main objective of this study was to develop a methodology for erosion protection zones in thecatchment of a water reservoir. The case study for the development of this model is the Kalimanciwater reservoir.
METHODOLOGY
The study area is situated in the North-East part of North Macedonia, and it is encompassing the
middle and the upper catchment of the Bregalnica River. The catchment of the Kalimanci reservoir
is taken as a case study (Fig. 1). The area of the catchment of the reservoir is 1,135.3 km 2, and thelength of the longest Bregalnica River is 94 km. The dam was built in 1969 and the total reservoir
storage was 127x106 m3.
The catchment of the Kalimanci reservoir mainly consisted of natural-rural elements: forests
46.1%, arable land 19.1% meadows 18.2%, and shrubs 12.7%. The geology consists of granites andgranite porphyry 20.3%, marl clay, sands, and gravel 16.6%, and also more than 20% consists of notstable schist formations. The main soil type is cambisol and cambisol with regosol 29% and alsoranker 37%. The annual total rainfall in the catchment is from 591 mm, on the lower slopes, to 1114
mm on the highest peaks or the mean value is 748 mm.

Fig. 1 Study area showing catchment of the Kalimanci reservoir in North Macedonia
The main method used to estimate sediment transport on the catchment level is the Erosion
potential method (EPM) developed by Professor Gavrilovic (1972). At the moment, there are several
methods used for estimating erosion on-site and on the catchment level. Blinkov and Kostadinov(2010) in their paper stress the good and bad sides of several models for the estimation of erosion:
EUROSEM, USLE, PESERA, KINEROS, WEP, WEPP, and EPM. Several of these methods canmodel erosion from different points of view. Only a few deals with the transport and deposition of
the sediment: EUROSEM, WEPP, and EPM. EPM was chosen to be used in the study because it has
the unique trait that was developed in the Balkan region, south Serbia, which is very similar inclimatic conditions to North Macedonia, secondly, the ability to predict sediment transport anddeposition was developed with calibration of deposited sediment in the existing reservoirs and also
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the data produced about the erosion potential in North Macedonia was developed with the EPM, so
the results would be comparable and the methodology would be transferable (Mincev, 2018).
The validity of the model is assessed with the accumulated sediment in the reservoirs. The
Kalimanci reservoir was measured for deposed sediment 12 times, between 1969 and 1997. The
measuring was done on already established profiles. To estimate the current situation, in 2013, theaccumulated sediment was measured directly through bathymetric measurements using ecosounding equipment on the established transect profiles in the reservoir.
RESULTS AND DISCUSSION
From the measurements can be distinguished two separate periods 1969-1985 and 1985-2013
according to the rate of sedimentation. In the first period, the annual sedimentation of the reservoir
is 467,686 m3/year and in the second the sedimentation decreased to 214,325 m3/year. The
sedimentation in the first period is more than double. According to Mincev (2015), this can be
accounted to different factors: climate change, migratory processes, changes in land use and animalhusbandry, the effects of implemented erosive measures and works, and consolidation of thesediment. The annual sedimentation of 214,325 m3/year will be taken as the true sedimentation of
the recent period and will be compared with the modeled values of the transported sediment.
The EPM method only estimates the total transported sediment at one point. To estimate how
the sediment is transported, re-transported, and accumulated in the river bed, a hydraulic sedimenttransport model HEC-RAS was used. The hydraulic calculations were done in the HEC-RAS on
transect profiles. The output of the software was the total load of transported sediment of the
Bregalnica River in the reservoir and zones of sedimentation in the river bed based on cumulative
input and output of sediment.

Fig. 2 Zones of sedimentation in the main Bregalnica River, Position of the historic
flooding areas (left); sedimentation output of the HEC-RAS software (right)
From the HEC-RAS model, there can be distinguished three general zones of accumulation of
sediment (Fig. 2). If the profiles of accumulation are spatially transferred on the map it can be seenthat accumulation of the sediment is in the larger valleys: Machevo – Mitrashinci, Razlovci andTrabotivishte - Delchevo. Almost 75% of the input sediment in the Bregalnica River is deposited in
the valleys. So, it can be concluded that all of the erosive hot spots upstream of the Bregalnica Riverare with lower erosion risk because a large portion of the sediment is deposited in thegeomorphological expansions, flattened areas, or small valleys along the Bregalnica River. Afterconsidering this, there can be distinguished two zones of sedimentation, before and after thegeomorphological expansions (Fig. 3). So, in this sense, the first zone is the immediate zone aroundⒸ ISERD

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the reservoir which encompasses catchments that have short transport distances and most of thesediment is deposited in the reservoir. The second zone is before the geomorphological expansions
and in this case, 75% of the sediment is left behind and a small amount of the produced sediment istransported in the reservoir.

Fig. 3 Zones of sedimentation in the catchment of the Kalimanci reservoir
The EPM model produced quantities of transported sediment on the sub-catchment level in
m3/km2/ann. These quantities were transformed into 4 categories according to the severity of theerosive processes in the sub-catchment (I – High risk > 300 m3/km2/ann.; II – Medium risk 201-300
m3/km2/ann.; III – Low risk 71-200 m3/km2/ann. and Very low risk <70 m3/km2/ann.) (Fig. 4a).
The next step is a combination of the severity of the erosive processes with the sedimentation
zones. The rule imposed here is: if the sub-catchment is in the second sedimentation zone, then theseverity of the erosion of the highest class is lowered by one category; if the sub-catchment is in thefirst sedimentation zone, then the severity of the erosion classes remains the same class (Fig. 4). The
final step is defining a buffer zone around the reservoir with a distance of 100 m in which the land
management practices are reduced to a minimum.

Fig. 4 Erosion severity on sub-catchment level (a), erosion protection zones
in the catchment of the Kalimanci reservoir (b)Ⓒ ISERD

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Figure 4b below shows the proposed zones around the Kalimanci reservoir in terms of erosion,
where zone I represents the most critical zone, and accordingly, the catchments in zone IV are theleast critical in terms of erosion.
The buffer zone is out of category and in this zone, there should not be any activities that would
disturb the natural regime: conservation of agricultural practices, forests with a protective character
without any invasive interventions, and construction activities that should be aimed at protecting theland from erosion, without major disturbances of the land.
In Zone I, activities should be aimed at soil conservation and forest practices that promotesustainability. Forestry activities should protect both the quantity and quality of forest resources in
the medium and long term by balancing cuts/removals and yields, preferring techniques thatminimize direct or indirect damage to forests, soil, and water resources. Appropriate practices should
be undertaken to increase the increment in the direction of economic, environmental, and social
benefits. It should also be considered the conversion of abandoned agricultural land into forest land
if it contributes to the acquisition of economic, ecological, social, and cultural values.
CONCLUSION
The main motive for the preparation of this paper was to prepare a methodology for zoning thereservoirs in terms of erosion. There are examples of making such zones, but they are based on expert
judgment. The goal, in this case, was to make an exact and applicable procedure, which will be
reproducible on another case study and further the obtained results will be comparable.
The development of the methodology for the zoning of the reservoir catchment in terms oferosion should be understood as a basis for future considerations on the approach to its improvement.
The research was done with an empirical model using measured bathymetric measurements of thereservoirs, to confirm the reliability of the results. The methodology is aligned to be able to use
standardized spatial databases, which with standard reclassification fit easily into the model. Fromprevious research, EPM methodology has been implemented in part because existing databases aretaken as a finished product and directly reclassified, without any corrections.
The zoning of the reservoir catchment is a prerequisite for integrated catchment management.
The approach of forming zones in the catchment areas of the reservoirs with spatial (GIS) support
and cartographic display will facilitate the work of future spatial planners from several areas:urbanism, forestry, agriculture, pasture management, etc.
REFERENCES
Blinkov, I., Trendafilov, A. and Kaevski, I. 2003. The role of the forests on the water and sediment discharge.
Research project, Ss. Cyril and Methodius University in Skopje, Forestry Faculty Skopje, Macedonia.
Blinkov, I. and Kostadinov, S. 2010. Applicability of various erosion risk assessment methods for engineering
purposes. BALWOIS Conference 2010, Ohrid, Macedonia.
Gavrilovic, S. 1972. Engineering of torrents and erosion. Izgradnja, Special Issue, Belgrade, Yugoslavia.
Institute for Water Development. 1993. Erosion map of the Republic of Macedonia. Institute for Water
Development of Republic of Macedonia.
Mincev, I. 2015. Development of methodology for determination of protection zones around water reservoirs
from aspect of soil erosion and sediment transport. Doctoral Thesis, UKIM Forestry Faculty in Skopje,
North Macedonia.
Mincev, I. 2018. Measuring v.s modeling sediment discharge, Case study: Kalimanci reservoir, Macedonia.
Soil and Water Resources Protection in the Changing Environment, 88-100, Zlatic, M. and Kostadinov, S.
(Eds.), Schweizerbart Science Publishers, Advances in Geoecology, Vol. 45, ISBN 978-3-510-65418-5.
White, W.R. 2001. Evacuation of sediments from reservoirs. Thomas Telford, London, UK.

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Research article
erd

On-farm Effects of Subsurface Drainage System on Chinese
Cabbage (Brassica pekinensis L. Rupr.) Production in Rainy
Season at Svay Rieng Province, Cambodia
TITHYA KANG*
Svay Rieng University, Svay Rieng, Cambodia
Email: kang_tithya@mail.sru.edu.kh

SARAVUTH TUM
Svay Rieng University, Svay Rieng, Cambodia

VANCHEY ROS
Svay Rieng University, Svay Rieng, Cambodia

NIMUL CHUN
Svay Rieng University, Svay Rieng, Cambodia

CHHUN HONG
Svay Rieng University, Svay Rieng, Cambodia

BORARIN BUNTONGRoyal University of Agriculture, Phnom Penh, Cambodia

KIMCHHIN SOKRoyal University of Agriculture, Phnom Penh, Cambodia

SIRANET ROEURN
Royal University of Agriculture, Phnom Penh, Cambodia

SOPHOANRITH RO
Royal University of Agriculture, Phnom Penh, Cambodia
Received 4 February 2023

Accepted 20 May 2023(*Corresponding Author)

Abstract Vegetable production in Cambodia is unstable during the rainy season due tosaturated soil conditions, leaving the comparative market advantage to neighboring Vietnam
and Thailand. One potential solution that has been proposed is the introduction of a Subsurface
Drainage (SD) system, as elucidated in our previous studies. In the current study, SD systems
was installed on plots of Chinese cabbage in Svay Chrum District, Svay Rieng Province, todetermine their potential in increasing the production period and productivity during the rainyseason. The treatments consisted of three SD systems within three growing conditions (GC)
including open-field, plastic house, and net house including five replications with a total of 45
plots. The results of the experiment showed positive improvement in terms of growth and yieldof Chinese cabbage at a rate of 15% and 22% for SD2 and SD3 systems respectively; and 58%
and 66% for net house and plastic house conditions, respectively. The extension of the
production period from intermittent to year-round is of great benefit to vegetable producers,
and will lead to improved market connections and better production margins, stabilizing
income generation. However, the analysis still excluded the cost-effectiveness and efficiencyof the experiment due to the absence of detailed data on expenditures, including the cost ofdrainage pipes, construction of the net and plastic houses, and water consumption.
Keywords on-farm, subsurface drainage (SD), Chinese cabbage, rainy seasonⒸ ISERD

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INTRODUCTION
Agriculture is an important mainstay of the Cambodian economy to lift many people out of poverty.
In 2021, the share of agriculture in Cambodia's gross domestic product (GDP) was 22.85%, including
the contributions of fishery at approximately 5.5%, livestock at 2.6%, forestry at 1.6%, and crops atabout 13% (MAFF, 2021). Although the major occupation of the Cambodians is agriculture, thecountry is a net agricultural importer, giving vegetable imports worth approximately USD 200
million annually (Thira et al., 2020). The heavy reliance of the country on neighboring countries'
vegetables is associated with the highly seasonal productions of Cambodian producers lasting foraround only three months from late December to late March. The period is appropriate for vegetableproduction as the weather is relatively mild and dry (Wandschneider et al., 2019). Moreover, rice
farmers are free from rice production and some of them opt to produce vegetables for additional
income, causing the volume of vegetables to reach a peak while the price falls to the lowest one (IRL,
2007). After the period, water becomes scarce and the soil becomes too dry whereas the wet season
faces the problem of too much rainfall, causing waterlogging, high pests, and diseases(Wandschneider et al., 2019). The discontinuous supply of vegetables at stable volume has caused
the vegetable value chain to break and loss of competitiveness to the neighboring countries, namely
Vietnam and Thailand. It is reported that local capacity for vegetable production could supply
approximately 45% of the market demand and 70% is in the peak period of the production in dry
season (CPS, 2019). A wide variety of vegetables was cultivated across the country, including leafy,
stem, and fruit-bearing, root, bulb, tuberous, leguminous green vegetables, etc. Fruit-bearing
vegetables were planted on 35,000 ha; leafy and stem vegetables on almost 6,000 ha. Vegetables are
increasingly recognized as essential for food and nutritional security. Vegetable production is a key
component of farm diversification strategies to provide a promising economic opportunity for
reducing rural poverty and unemployment in developing countries (Pepijn et al., 2018). Chinese
cabbage (Brassica pekinensis L. Rupr.) is annually grown as a salad crop. It is indigenous to China
and eastern Asia, where it has been in cultivation since the fifth century. Two more or less distinct
species of Chinese cabbage are grown. The leaves are long, dark green, and oblong or oval, and they
do not form a solid head. It is also called Chinese mustard (Kalloo et al., 1993). Chinese cabbage(Brassica pekinensis L. Rupr.) is a popular leafy vegetable of Cambodian farmers and consumers
among many kinds of vegetables for their daily food security and income generation (Um Raingsey,2015). The drainage system provides substantial benefits to agricultural production which could
contribute to (i) increasing farm income, (ii) intensification and diversification of cropping; and (iii)
generation of employment (Datta et al., 2004). Proper management of irrigation practices could
provide various benefits to crop production such as extended crop season, increased yield, andimproved aeration of the root zone. However, the development of drainage systems has been lagging
far behind the development of irrigation, leaving agriculture at a high risk of losing productive lands
due to waterlogging and salinization (Abdel, 2000). There is no exception for Cambodia where theintroduction of Subsurface irrigation systems has been very limited and hardly found at any
Cambodian farm. Unstable quantity on the supply side has been one of the reasons behind the lossof production competitiveness to the neighboring countries including Vietnam and Thailand. The
experience from the collaboration between Svay Rieng University with Svay Rieng Agricultural
Cooperatives shows that vegetable producers are facing severe issues of waterlogging during the wet
season causing their production to be least productive and delayed (Hong et al., 2021). Therefore,
the introduction of the SD system is essential to study in determining its potential contribution tovegetable production during the rainy season which could also be essential for other vegetableproducers across the country. The on-farm experiment was conducted with farmers in Svay Chrum
District, Svay Rieng Province to solve the problem of unproductive soil due to high water content(saturation) by the installation of a subsurface drainage with plastic house and net house. Draining
water from the production area under plastic houses and net houses would help farmers solve theproblem of highly saturated soil and continue their production during the wet season. The system
will be of great benefit to vegetable producers in terms of a production period that can be extended
from intermittent to year-round. This will lead to a better market connection and production marginwhich is stable in income generation.
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OBJECTIVE
The overall objective of the research is to determine the appropriateness, potential, and suitability ofthe subsurface drainage under different growing conditions with Chinese cabbage as per field
application of vegetable producers in increasing the period and productivity during the rainy season.
MATERIALS AND METHODS
Experimental Site
The experiment was conducted in Svay Chrum District, Svay Rieng Province, Cambodia (Fig. 1)
with fifteen farmers’ fields of vegetable producers who are members of Svay Rieng Agricultural
Cooperatives (SAC). The experiment was carried out from August to November 2022. The soil
characteristics of the experimental fields are located on the saturated soil of abandoned paddy fields
with soil pH of around 5.5 of the loamy soil (averagely, clay: 17.5%, silt: 39.4%, and sand: 41.4%).
The rainy seasonal precipitation ranges from 142.4 mm to 248.9 mm, while the temperature ranges
from 27.9oC to 29.8oC, and the humidity ranges from 80% to 92.5% (Table 1).

Fig. 1 The experimental location in Svay Chrum District, Svay Rieng, Cambodia
Table 1 Monthly rainfall, temperature and humidity during growing season in 2021-2022
Month
Aug
Sept
Oct
Nov
Total

Rainfall (mm)
2021
2022
218.8
174.3
255.5
238.5
254.2
248.9
248.4
142.4
976.9
804.1

Temperature (oC)
2021
2022
30.0
29.4
29.3
29.8
28.8
27.9
29.0
29.0
117.0
116.0

Humidity (%)
2021
2022
91.0
87.5
96.0
85.0
92.5
92.5
86.0
85.0
365.5
350.0

Experimental Design
The factorial design is used, containing fifteen farmers’ fields with five replications and nine
combined treatments including three SD systems and three GCs. The same design of the Subsurface
drainage (SD) systems (SD1 = No Subsurface drainage pipe, SD2 = 2 rows Subsurface drainage pipe
per bed, SD3 = 3 rows Subsurface drainage pipe per bed) were applied under the different Growing
Conditions (GC) of open field (OP), net house (NH), and plastic house (PH). One farmer’s field wasused as one GC, and three SD systems were allocated. The pipes were sawed in a row at every 2 cm
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with 1/3 dept of pipe size to make holes for water inlets to drain through outlets to the nearby canal.
The total land area for each farmer’s field was 5 m x 15 m =75 m2. The net house was fully coveredby a 150-mesh net, and the plastic house was surrounded covered by a 150-mesh net with 300 UVplastic covering on top of the roof.

Fig. 2 Illustration of the experimental design for each farmer’s field
Agronomic Practices
The Chinese cabbage seedlings were grown on the raised bed with the PVC pipe being buried
underneath (sawed side goes to the ground) at a depth of 20 cm under the root zone. Mechanicalmethods were used for pest management. The weeding was controlled every week till the harvestingby hand. During the experiment, the diseases were not observed. The insects were normally bothered
during the experiment, even in the net house or plastic house condition. The chemical methods ofcrop protection were used by spraying natural pesticides and by hand picking. For the irrigation, theplants were irrigated from pumped water sources by hand spraying with 20 liter-bucket. In case there
was not enough or no rain, the water was applied at field capacity. Some agronomic traits such as
root length, stem height, leaf area, and stem density (survived stem: is the total stem which is still
alive both useful and useless stems at the harvesting date, useful stem: is the good stem which canbe consumed, loss stem: is the died stem which cannot be survived at the harvesting day, damage
stem: is the total of useless stems and died stems), and weight (estimated max yield: is the average
weight of complete useful stems with 100% density at the harvesting date, useful yield: is the weightof good or consumable stems, loss yield: is the estimated weight of died stems which cannot be
survived at the harvesting day, damage yield: is the estimated weight of useless and died stems) of
the cabbages were collected. The collected data was analyzed as a factorial design using Statistix 8
program for the analysis of variance (ANOVA) and Minitab 20.4 for LSD mean comparison at pvalue p<0.01, p<0.05. Before the analysis, the data were normalized to exclude the covariance being
observed from the differentiation among farmer's plots.
RESULTS AND DISCUSSION
Effects on Agronomic Traits
To compare vegetative effects on the Chinese cabbage growth, the four key parameters were
measured from the experiment including root length, stem height, leaf area, and leaf number. The
result of the experiment is summarized in Tables 2-5.

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Table 2 A root length change of Chinese cabbage
Treatment (Tr)At planting day

Root length (cm)At harvesting day

Increase

2.43
2.51
2.42

9.39c
10.14b
11.30a

6.97c
7.62b
8.88a

2.47
2.45
2.43
6
ns
ns
ns

8.99c
10.21b
11.63a
18
**
**
ns

6.52c
7.76b
9.19a
18
**
**
ns

Growing condition (GC)Open field (OF)Net house (NH)
Plastic house (PH)
Subsurface drainage (SD)
SD1
SD2
SD3
CV (%)
Sig. (GC)
Sig. (SD)Sig. (GC X SD)

Table 3 Stem eight change of Chinese cabbage
Treatment (Tr)Growing condition (GC)Open field (OF)Net house (NH)
Plastic house (PH)
Subsurface drainage (SD)
SD1
SD2
SD3
CV (%)
Sig. (GC)
Sig. (SD)Sig. (GC X SD)

Stem height (cm)At planting day At 1st week At 2nd week At harvesting day Increase
9.09
9.13
9.05

14.74 c14.89 bc
16.12 a24.47c24.83bc
26.03a26.44c27.19b30.09a17.35c18.07b
21.03a

9.17
9.03
9.07
2
ns
ns
ns

13.59 c15.73 b16.41 a5****
ns

24.00c25.21b
26.13a6****
Ns

26.60c27.83b
29.28a7****ns

17.44c18.80b
20.21a8****
ns

Table 4 Maximum leaf area change of Chinese cabbage
Treatment (Tr)Growing condition (GC)Open field (OF)Net house (NH)
Plastic house (PH)
Subsurface drainage (SD)
SD1
SD2
SD3
CV (%)
Sig. (GC)
Sig. (SD)Sig. (GC X SD)

Maximum leaf area (cm2/leaf)
At planting day At 1st week At 2nd week At harvesting day Increase
8.90
8.98
9.03

28.54c30.10b34.82a81.03c90.60b97.24a187.25c196.87b206.43a178.35c187.89b197.41a

8.88
9.04
8.98
3
ns
ns
ns

29.03c31.81ab32.63a16****
ns

85.07c90.91b92.88a21****
Ns

189.20c
197.87b203.48a
19
**
**
ns

180.32c188.84b194.50a
20
**
**
ns

Tables 2 to 4 show that the level of changes for root length, stem height, and leaf area at thedifferent growing stages of the Chinese cabbage are statistically different after the planting stages.
Growing conditions and Subsurface drainage systems could make a significant impact on the growthof cabbage with a p-value less than 0.01. Overall, the level of increase of growing condition in Plastic
House (PH) is observed to be better than Net House (NH) and Open Field (OF), while the level ofⒸ ISERD

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increase of SD3 is observed to be better than SD2 and SD1. Plastic House (PH) performed the best
as well as SD3, but the interaction of GC x SD was not significantly detected for root length, stemheight, and leaf area of the cabbage in all growth stages.
Table 5 Leaf number change of Chinese cabbage
Subsurface
drainage(SD)
SD1
Open Field (OF)
SD2
SD3
SD1
Net House (NH)
SD2
SD3
SD1
Plastic House (PH)SD2
SD3
CV (%)
Sig. (GC)
Sig. (SD)Sig. (GC X SD)

Growing conditions(GC)

At planting
day
2.99
2.97
2.97
2.98
2.99
2.99
2.98
2.97
2.99
1
ns
ns
ns

Number of leaves (leaf/stem)
At harvestingAt 1st week At 2nd week
day
3.63h
7.45e
10.06i
3.88g
8.59d
10.54h3.91fg8.40d10.80g
3.96ef8.75d
11.25f
4.03cd9.22c
12.55d
4.11ab
9.77ab
12.75c3.98de9.16c
12.15e4.10bc
9.69ab
12.96b
4.18a10.07a13.27a
2
9
5
**
**
**
**
**
**
**
*
**

Increase
7.07i
7.57h
7.83g
8.26f
9.55d
9.77c
9.18e
9.99b
10.28a5******

The finding (Table 5) shows that leaf numbers were not significant at planting. At the later stage,
the level of changes for the number of leaves at the different growing stages of the Chinese cabbage
were statistically different. All parameters of growing conditions (GC) and Subsurface drainage (SD)systems could make a significant impact on the growth of cabbage with a p-value less than 0.01. In
addition, the interaction of GC x SD was significant. Overall, the best performance of crop growth
was observed under plastic house conditions with Subsurface drainage systems type 2 (SD2) and 3(SD3).
Effects on Productivity
The Stem density, stem weight, and yield per hectare were measured and calculated from theexperiment to compare productivity effects. The results from the experiment are provided in Tables
6 and 7.
Table 6 Stem density on the harvesting day of Chinese cabbage
Growing conditions Subsurface(GC)drainage (SD)
SD1
Open field (OF)
SD2
SD3
SD1
Net house (NH)
SD2
SD3
SD1
Plastic house (PH)SD2
SD3
CV (%)
Sig. (GC)
Sig. (SD)Sig. (GC X SD)

Survived stem
9.57h
13.92g14.92f17.78e19.68d20.68c20.09cd
22.00b
23.32a4
ns
ns**Ⓒ ISERD

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Stem Density (stem/m2)
Useful stem
Loss stem
7.44g
15.43a8.16fg11.08b8.80f
10.08c16.16e7.22d
17.86d5.32e
19.23c
4.32f
18.29cd
4.91ef21.09b3.00g
22.36a
1.68h
4
4
**
**
**
**
**
**

Damage stem
17.56a16.84ab16.20b
8.84c
7.14d
5.77e
6.71de
3.91f
2.64g
4
**
**
**

IJERD – International Journal of Environmental and Rural Development (2023) 14-1

The result (Table 6) shows that the level of changes for the density of survived stem, useful
stem, loss stem, and damaged stem on the harvesting day of the Chinese cabbage are statisticallydifferent. All parameters under growing conditions and Subsurface drainage systems could make asignificant impact on the productivity of cabbage with a p-value less than 0.01. The interaction of
GC x SD was significant. In overall, the plastic house condition with Subsurface drainage system
type 3 was observed to be the best performance for survived stem and useful stem, while under plastic
house condition with Subsurface drainage system type 2 and net house condition with Subsurface
drainage system type 3 were observed to be better performance compared to Subsurface drainage
system type 1 in all growing conditions. In addition, open field condition with Subsurface drainage
system type 1 was observed to be the worst performance for loss stem and damage stem.
Table 7 Yield of Chinese cabbage
Growing
conditions(GC)
Open field(OF)
Net house(NH)
Plastic
house (PH)

Subsurface
drainage (SD) Estimated max yield
SD1
SD2
SD3
SD1
SD2
SD3
SD1
SD2
SD3

CV (%)
Sig. (GC)
Sig. (SD)Sig. (GC X SD)

Total yield (ton/ha)
Useful yield

Loss yield

Damage yield

9.53g
10.58fg
11.58f21.57e25.65d28.40c26.70d31.97b
34.51a3******

19.77a14.37b
13.27b
9.63c
7.64d
6.38d
7.17d
4.55e
2.59f
3
**
**
**

22.50a21.84a21.32a11.79b
10.25c
8.52d
9.79cd
5.92e
4.07f
3
**
**
**

32.03i32.42h
32.90g33.36f35.90e36.92d36.49c37.90b38.58a1******

The result (Table 7) shows that the level of changes for the estimated maximum yield, usefulyield, loss yield, and damage yield of the Chinese cabbage are statistically different. All parameters
under growing conditions and Subsurface drainage systems could make a significant impact on the
productivity of cabbage with a p-value less than 0.01. The interaction of GC x SD graduallydeveloped and became significant. In overall, the plastic house condition with Subsurface drainage
system type 3 was observed to be the best performance for estimated maximum yield and usefulyield, while under plastic house condition with Subsurface drainage system type 2 and net housecondition with Subsurface drainage system type 3 were observed to be better performance comparedto Subsurface drainage system type 1 in all growing conditions. In addition, open field condition with
Subsurface drainage system type 1 was observed to be the worst performance for loss yield anddamage yield.
Discussion
The result of the experiment indicated high productive benefits for the Chinese cabbage in terms ofyield at a rate of 15% and 22% for SD2 and SD3 systems respectively; and 58% and 66% for net
house and plastic house conditions respectively. In comparison to the previous assignment conductedat the same location during the dry season, the increase is 26% to 34%, respectively (Hong et al.,2021). The yield from the experiment was slightly better than the one being conducted during thedry season at the Royal University of Agriculture with a yield of 28 tons/ha (Teb Kimheng, 2015).
This would be more precise with the full-control condition of experimentation which would bepossible in generalizing the actual condition of the country. In addition, a ﬁeld experiment was
conducted in paddy ﬁelds during the rainy seasons (October to May) from 2011 to 2015 to evaluate
a suitable drainage system for improving the grain yield of lowland paddy soil. The saturated
hydraulic conductivity of the soil in all treatments increased, which resulted in improved soil
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properties, water movement, and drain discharge rates (Mehdi et al., 2016). The results of theexperiment were quite better in comparison to the installation of a subsurface drainage system
resulting in an improvement of paddy yield by 13.27% and an increase in soil organic carbon content.
However, it was the first year after the installation of the subsurface drainage; the yield could be
expected to improve considerably during the succeeding seasons with appropriate and better
cropping and irrigation management practices (Sahana et al., 2023). The increase was due toimprovement in soil physical properties viz., infiltration rate, porosity, and chemical properties (lowpH, EC, ESP) and improved nutrient availability in the drained field. Similarly, Abdel-Dayem, andRitzema (1990) reported an increased yield of many crops to a tune of 10% for rice, 48% for berseem,
75% for maize, and more than 130% for wheat under a subsurface drainage system. The increase
was because of decreased soil salinity, and improved air and water condition in crop root zones. The
poor yield of maize in the undrained field due to poor soil physicochemical properties viz., shallow
water table depth, high pH, EC, and ESP (Stieger and Feller, 1994; Samad et al., 2001 and Zhang etal., 2015), which limits the growth and development of crops in waterlogged saline-alkali soil
(Arumugam et al., 2019). In addition, the enormous increase would result in reducing of water stressand strong drops of rain under the plastic house protection during the rainy season. This would bringenormous economic benefits for farmers. It is reported that the consumption of vegetables in
Cambodia is approximately 1,062 million tons per year (SAAMBAT Project, 2020). This would
translate into approximately contribution of 79,650-116,820 tons with the application of Subsurface
drainage and approximately contribution of 307,980-350,460 tons with the application of growing
condition (Net house and Plastic House) for the wet season production (June to December) for
Cambodia with the application of the drainage under the net house or plastic house condition at the
maximum scenario. There is still another concern regarding the cost of the drainage pipe and growing
structures, which was included in the production. A more detailed analysis of the cost and benefit of
the product will be included in future research assignments to make the drainage system and net orplastic house growing condition more determined and applicable for the rainy season.
CONCLUSION
The growth of the Chinese cabbage within the Subsurface drainage (SD2 and SD3) systems andgrowing conditions (NH and PH) performed better under both saturated and drought conditions. At
the time of rain, the cabbage could continue its growth with less effect, while during the time ofdrought, cabbage could maintain its yield, possibly because of good aeration of the soil and less soil
compaction after a strong drop of rain. The analysis still excluded the cost-effectiveness andefficiency of the experiment due to the absence of detailed expenditures on drainage pipe,
construction of the net and plastic house, and water consumption is also excluded. Anyway, future
research should be conducting a detailed analysis of the loss of other nutrients in soils, water
consumption, and possible economic loss as a result of drainage systems and conduct a detailed
analysis of the economic benefits of drainage systems with actual price estimation.
ACKNOWLEDGEMENTS
The authors would like to acknowledge the sub-research project “Effects of Drainage System andGreen House on the Productivity of Vegetable Production” funded by “Higher Education
Improvement Project (HEIP)” through Svay Rieng University, Cambodia.
REFERENCES
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Balusamy, A., Udayasoorian, C. and Jayabalakrishnan, R. 2019. Effect of subsurface drainage system on maize
growth, yield and soil quality. International Journal of Current Microbiology and Applied Science, 8 (2),1206-1215, Retrieved from DOI https://doi.org/10.20546/ijcmas.2019.802.140
Indochina Research Limited (IRL). 2007. Fruit and vegetable traders, Baseline study. Indochina Research
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Center for Policy Study. 2016. Report, Vegetable demand and supply for boosting food production. Phnom
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Vegetables_Produced_under_Boosting_Food_Production.pdf
Datta, K.K., Tewari, L. and Joshi, P.K., 2004. Impact of subsurface drainage on improvement of crop
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Ehsan, G. 2018. Agricultural drainage. Extension Bulletin E3370, Michigan State University, Michigan, USA.
Heather, F. and Ron, F. 2021. Environmental benefits of tile drainage. University of Guelph. Guelph, Canada.
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cabbage (Brassica pekinensis L. Rupr.) of farmers in Svay Rieng Province, Cambodia. Journal of
Agricultural Science and Technology, B 11, 121-125, Retrieved from DOI https://doi.org/10.17265/21616264/ 2021.03.003
Jafari-Talukolaee, M., Ritzema, H., Darzi-Naftchali, A. and Shahnazari, A. 2016. Subsurface drainage toenable the cultivation of winter crops in consolidated paddy fields in Northern Iran. Sustainability, 8 (3),249, Retrieved from DOI https://doi.org/10.3390/su8030249
Joanna, E.A., James A.K. and Mark, S.K. 2013. Drainage water management on yield effects and farm
profitability. Kieser and Associates Environmental Science and Engineering, Kalamazoo, USA.
Kalloo, G. and Rana, M.K. 1993. Genetic improvement of vegetable crops. Elisver Publisher, Amsterdam, The
Netherlands.
Ministry of Agriculture, Forestry, and Fishery. 2021. Share of agriculture in GDP of Cambodia. Ministry ofAgriculture, Forestry, and Fishery, Cambodia.
Ministry of Rural Development. 2020. Need assessment of traceability system for vegetable value chain.
Sustainable Assets for Agriculture Markets, Business and Trade (SAAMBAT) Project, Phnom Penh,
Cambodia.
Nijland, H.J, Croon, F.W. and Ritzema1, H.P. 2005. Subsurface drainage practices. Wageningen
Environmental Research (Alterra), Wageningen, Netherlands.
Plastics Pipe Institute. 2002. Agriculture and drainage - Inseparable science. Plastics Pipe Institute. Dallas,
USA.
Ritzema, H.P. and Ksellk, R.A.L. 1996. Drainage of irrigated lands. Food and Agriculture Organization of theUnited Nations. Rome, Italy.
Sahana, V.H., Narayana, R.K., Bhat S.N. and Polisgowdar, B.S. 2023. Effect of subsurface drainage on soil
nutrients and crop yield in saline vertisol under TBP command area. The Parma Innovation Journal, 12 (4),245-248, Retrieved from URL https://www.thepharmajournal.com/archives/2023/vol12issue4/PartC /123-678-714.pdf
Schreinemachers, P., Simons, E.B. and Wopereis, M.S. 2018. Tapping the economic and nutritional power ofvegetables. Global Food Security, 16, 36-45, Retrieved from DOI https://doi.org/10.1016/j.gfs.2017.
09.005
Teb Kimheng. 2015. Effect of compost on Chinese cabbage. Royal University of Agriculture, Phnom Penh,
Cambodia.
Thira, P., Reach, S. and Buntong, B. 2020. Vegetable farming practices in Cambodia, Case study of smallscale vegetable farmers in Kandal, Kampong Chhnang and Battambang Provinces. International Journal ofEnvironmental and Rural Development, 11 (1), 57-62, Retrieved from URL https://iserd.net/ijerd111 /111-9.pdf
Um Raingsey. 2015. How to grow Chinese cabbage. RFA, 1. Phnom Penh, Cambodia.
Wandschneider, T., Pel, D., Men, P., Lim, S. and Tech, R. 2019. Structure and conduct of vegetable market inCambodia, Key findings from a survey of wholesale traders in Phnom Penh and Siem Reap Cities.
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Virginia State University, Petersburg, USA.

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Research article
erd

Prediction of Land Use Change through the Cellular
Automata-Markov Model: A Case Study of the Upper
Sangkae River Basin in Cambodia
VANNA CHEY
Graduate School of Agriculture, Hokkaido University, Sapporo, JapanTADAO YAMAMOTO*
Research Faculty of Agriculture, Hokkaido University, Sapporo, Japan
Email: tady@agr.hokudai.ac.jp

TAKASHI INOUE
Research Faculty of Agriculture, Hokkaido University, Sapporo, Japan
Received 19 January 2023

Accepted 20 May 2023(*Corresponding Author)

Abstract The expansion of agricultural land and the diminishment of forest cover in
Battambang Province (Cambodia) has been recently reported. At the same time, while forest
cover has decreased, the amount of water resources in the river basin has been variable. The
aim of the current study was to forecast land use change in the upper Sangkae River basin ofBattambang Province by 2030. For this purpose, remote sensing and geographic information
systems (GIS) methods were used to analyze satellite data from 2014 to 2018, using thegenerated maps as data input in the cellular automata (CA)-Markov model. We also integrated
the CA-Markov model and GIS spatial analyst tools to assess what will most likely occur inthe presence of policy intervention from land use development planning by 2030. Additionally,
the model simulated actual and predicted land use in 2022 for accuracy assessment, using the
Kappa Index of Agreement for confirmation. Based on the findings, the modeled scenario
predicted the increase in built-up land and the decrease in the natural forest cover by 2030 in
the absence of a land use policy. Additionally, the findings suggested that in the absence of aland use policy, forest cover will suffer from continued deforestation until forest loss reaches
the protected area boundary. Conversely, in the presence of a land use policy, the model shows
an increase in forest cover by 2030, even though some areas would be allocated under
economic land concessions for industrial agriculture. Moreover, non-forest cover, such as
farmlands and paddy fields, is not expected to decline, whereas built-up land is forecast to
dramatically increase, with or without policy intervention. This study sheds light on the use ofpractical evaluation tools for governmental land use policies and development planning.
Keywords CA-Markov model, land use change, government land use planning, prediction

INTRODUCTION
Land use/land cover has been considered the main factor in changing the hydrological cycle since it
directly influences evapotranspiration and soil moisture contents (Gupta et al., 2015). In this regard,
significant land use changes in Battambang Province (Cambodia) have been recently reported. For
example, previous research (Sourn et al., 2021) found a considerable increase in agricultural land,with a dramatic decrease in forest cover between 1998 and 2018. These changes were driven by
population growth, economic growth, landmine clearance projects, and social and economic land
concessions (SLCs and ELCs, respectively). Based on the Cambodia Land Law of 2001 (OpenDevelopment Cambodia), the term SLC refers to the social purpose of allowing beneficiaries to build
residential constructions and/or cultivate land belonging to the state for their subsistence. The term
ELC refers to the economic purpose of allowing beneficiaries to clear the land for industrial andagricultural exploitation.
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Understanding land use change has become an increasing matter of interest and concern amonglandscape planners and environmentalists because it influenced the global environment (Subedi etal., 2013). Land use/land cover mapping derived from remotely sensed data has long been an area of
focus for many researchers (Civco et al., 2002; Araya and Cabral, 2010). Meanwhile, recent
advancements in geographic information systems (GIS) and remote sensing tools/methods haveenabled researchers to effectively model land use change (Araya and Cabral, 2010).
In general, modeling land use dynamics is a complex process (Subedi et al., 2013), due to factors
such as natural settings, society, economics, culture, politics, and legal aspects (Lambin, 1997).
Various models for land use simulation and prediction have been used in GIS such as statistic,
dynamic, and machine learning modeling (Aburas et al., 2019). Based on historical spatio-temporal
data, the cellular automata (CA)-Markov module in IDIRISI software was first used in this study tosimulate and predict future land use change, due to its widespread use by scholars to understandlandscape change at the global level (Wang et al., 2021). It was also used to analyze the related
effects and natural resource management strategies (Brown et al., 2000). However, this model did
not consider land use policies and socio-economic factors (Subedi et al., 2013).
OBJECTIVE
Therefore, the present study examines the SLCs, ELCs, and potential areas for forest communities
according to the local government’s 2030 master plan (Open Development Cambodia). The primaryobjective is to integrate the CA-Markov model and GIS-based spatial analyst tools to enhance thepredictive land-use change map.
METHODOLOGY
Study Area
The study focused on the upper Sangkae River basin, situated in Battambang Province (the largest
agricultural area in Cambodia), with a total drainage area of 3,062 km2 (Vanna et al., 2020) (Fig. 1).
The elevation ranges from 13 to 1,400 meters above sea level. Based on Mekong River Commission(MRC) land use data in 2010, 53.13% of land use within this basin was covered by forest, followedby agriculture at 44.41%, built-up land at 2.03%, and water bodies at 0.44%. More than one million
people live in this province, with an annual population growth rate of 2.28% (Hagenlocher et al.,2016). Meanwhile, human activities have been affected in this watershed by landmine clearance andexplosive remnants of war projects, and land concessions (Sourn et al., 2021).

Fig. 1 Map of the study area
Data Input and Image ClassificationⒸ ISERD

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Freely available Landsat 8 (Path 127-128, Row 51) images in 2014, 2018, and 2022 were acquired
from the U.S. Geological Survey (https://earthexplorer.usgs.gov/). The images were mosaicked andcomposited using Bands 1-7 and projected in UTM 48N using ArcGIS 10.5. Due to prior knowledgeof the Sangkae River basin, the images were classified by hard supervised classification, a popularalgorithm of maximum likelihood based on signature files (Rawat and Kumar, 2015). According to
the user’s knowledge, a signature was processed by using the on-screen digitizing feature to create
5–12 vector files of the training site for each class. Land cover was identified, following MRC landuse-2010 and satellite imagery, while land use was aggregated into five major classes: forest cover,farmlands, paddy fields, water bodies, and built-up areas. The stratified randoms of more than 500
points were created for each image using the Create Accuracy Assessment Points tool in ArcGIS.
They were then manually checked and compared by using existing land use and the Google EarthEngine, as reference data. The overall accuracy and Kappa coefficient (Table 1) of the classified
images were larger than 95% and 0.90, respectively.
Table 1 Accuracy assessment of image classification
Year
LULC2022
LULC2018
LULC2014

Overall accuracy
95.06
95.40
96.00

Kappa coefficient
0.92
0.94
0.95

Land Use Change Modeling and Prediction Process
In this study, three land use maps (2014, 2018, and 2022) were converted into ASCII files and thenimported into IDIRISI software for land use change simulation and prediction. First, land use
predictions in 2022 and 2030 were performed with the CA-Markov model (Eastman and Toledano,2018) by inputting suitability maps, transition areas, and a transition probability matrix, all computedfrom the Markov chain analysis of the 2014 and 2018 images. Second, the 2018 image was set as thebase map. Third, the VALIDATE module was used to assess the model’s validity, which was
confirmed by the statistical Kappa Index of Agreement (KIA). Fourth, the predicted land use in 2030
was generated by using the projected transition probability matrix derived from the simple poweringof the base matrix (Takada et al., 2010). Finally, according to the presence of a future land use policy,
another land use map was created by overlaying the development areas onto the predicted land use
map in 2030.
The Markov and CA-Markov Models
The Markov model is a convenient tool for simulating land use/land cover change when variationsin the landscape are difficult to describe (Kumar et al., 2014). Specifically, it depicts land use/landcover change from one period to another and uses it as a basis for predicting future changes. Table 2
presents the conversions of land use from one class to another for the 2014–2018 study period. The
CA-Markov model combines the cellular automata-Markov chain and the multi-criteria/objective
procedures for land use/land cover prediction (Eastman and Toledano, 2018). In particular, it
allocates land based on the suitability of the land for end covers (along with a cellular automatonrule) to promote spatial contiguity (Eastman and Toledano, 2018). In addition, by using the Markov
chain analysis outputs, especially the transition area file, the CA-Markov model applies a contiguity
filter to grow land use from one time to a later time.
Table 2 Transition probability matrix from 2014 to 2018Land use classes
Forest coverFarmlands
Built-up land
Paddy fields
Waterbody

Forest cover
0.74350.15570.00140.02250.0710

Farmlands
0.25100.75030.20350.29210.1909Ⓒ ISERD

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Built-up land
0.00050.01620.76660.00030.0140Paddy fields
0.00050.05490.02510.68510.0019Waterbody
0.00450.02290.00340.00000.7222

IJERD – International Journal of Environmental and Rural Development (2023) 14-1

Regarding the suitability for predictive land use, it refers to the suitability of a cell for particular
land use (Eastman and Toledano, 2018). Normally, suitability images are constructed with multicriteria evaluation, a common method for assessing/aggregating the “constraint and factor” criteria.
Constraints are usually represented as a Boolean image (0 and 1), while factors define some degreeof suitability for all geographic regions. In this study, the factors were empirically developed byusing the underlying land use change dynamics between 2014 and 2018.
Additionally, various factors, such as proximity to roads, water, canals, and existing land use
were generated and standardized on a continuous scale of 0 (least suitable) to 255 (most suitable),using a fuzzy module. The factors of each land use class were then aggregated by employing pairwise
comparison associated with the analytical hierarchy process in the weighted linear combination
method. For more information on the Markov and CA-Markov models, see references (Subedi et al.,2013; Wang et al., 2021; Eastman, 2012; Hamad et al., 2018).
RESULTS AND DISCUSSION
Accuracy Assessment of the CA-Markov Model(d)

Validation of the model is an essential pre-condition for research that predicts land use/land coverchanges (Wang et al., 2021). The model validation in this study was achieved by simulating actualand predicted land use images in 2022, based on known land use in 2014 and 2018, and a KIA
statistics-based assessment. According to Fig. 2, the actual and predicted land uses in 2022 are similar,
except for the forest cover class, due to the map accuracy during image classification. In addition,
the Kappa is 1 when the observed agreement is perfect, or 0 when the observed agreement is equal
to the expected agreement (Pontius, 2022). The statistics derived from the VALIDATE module in
IDIRISI software show that the Kappas for no information (Kno = 0.94), for location (Klocation =0.94), for quantity (Kquantity = 0.94), and for standard (Kstandard = 0.92) were larger at 0.90 (Wanget al., 2021). Thus, the model was deemed valid and reliable for land use change projection.

Fig. 2 The comparison of actual (a) and predicted (b) land uses in 2022
Prediction of Future Land Use
The land use prediction maps for 2030 are shown in Figs. 3(a) and 3(b). Specifically, the model
scenario without a land use policy (Figure 3(a)) predicted that the farmlands will cover 52.12% of
the total area of the upper Sangkae River basin, followed by forest cover (38.42%), paddy fields(6.69%), built-up land (1.82%), and water bodies (0.95%) (Table 3). Additionally, forest cover andfarmlands are expected to decrease in area by 2030, compared to the predicted land use in 2022
(Table 3). However, this decrease will contribute to an increase in built-up land by 0.22%. It should
be noted that the decline of forest cover in the study area has been observed over the past few decades.
According to previous research (Sourn et al., 2021), deforestation was observed from 1998 to 2013.
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such as the Phnom Samkos Wildlife Sanctuary and the Samlot Multiple Use Area. The expansion ofagricultural land in the upper Sangkae River basin will most likely reach these protected areas,
reflecting the minor decline in forest cover predicted by the model.
With the presence of a land use development policy, the land use map in 2030 was achieved(Fig. 3(b)). If land use planning succeeds, then the positive impact on the natural forest cover in thisbasin can be seen in an increase in reforestation by 2030. In this case, our predicted land use showsthat forest cover and built-up land of high and low population density increase by 0.78%, 0.20%, and100%, respectively. Moreover, forest cover is predicted to increase, even though some areas at the
upstream part of the river basin have been offered and allocated under ELCs. Nevertheless, thefarmlands and paddy fields will decrease by 3.05% and 0.02%, respectively. Field surveys of current
land use in mountain areas confirm that natural forests, even in protected areas, are being cut andburned to expand agricultural land. Therefore, it is predicted that deforestation will continue in theabsence of effective land use policies. The land use policy here, however, is the planning ofafforestation for forest communities by local governments. This policy is believed to help increase
forest cover in the future.

Fig. 3 The predicted land use in 2030
Overall, these decreases and increases are the result of government policies on land allocation.
For instance, land use changes from farmlands to the built-up area of low population density appear
as a new land use class. In this case, the land was allocated under SLCs. Meanwhile, the built-up
area’s expansion is expected to increase, due to the increase in the number of new marriages andresidential development plans. Furthermore, there will be a slight decline in paddy fields, while water
bodies will remain stable from 2018 to 2030.
Table 3 Predicted land use in 2030

Land useclasses

Predicted LU2022

Without a land use policy
Rate ofPredicted LU 2030
changes
Area
Area (ha)(%)(%)
117,678.13 38.42−0.19
159,570.39 52.12−0.06

With a land use policy
Rate ofPredicted LU 2030
changes
Area
Area (ha)(%)(%)
120,619.33 39.39
0.78
150,436.29 49.14−3.05

Forest coverFarmlands
Built-up land(high density)
Built-up land
(low-density)
Paddy fields
Water bodies

118,132.18
159,732.80

Area
(%)
38.61
52.18

4,914.26

1.61

5,579.82

1.82

0.22

5,538.65

1.81

0.20

-

-

-

-

-

6,386.96

2.09

100.0020,360.63
2,922.47

6.65
0.95

20,477.64
2,909.35

6.69
0.95

0.03
0.00

20,311.63
2,922.47

6.63
0.95

−0.02
0.00

Total

306,215.34-

306,215.34--

306,215.34--

Area (ha)Ⓒ ISERD

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Based on the guidelines from the Ministry of Land Management, Urban Planning, andConstruction, 6,386 hectares (built-up land with low population density) of state land in the Samlot
district of Battambang Province and its shared border with the Koh Krala district were converted into
SLCs for the poor and retired soldiers. Specifically, these individuals were legally authorized tooccupy one hectare of land with one house. This project was implemented under the Battambang
Provincial Administration. Conversely, according to the Sub-degree on Reclassification of State
Permanent Forest Reserve and Granting of ELCs for agro-industry investment in 2009 (OpenDevelopment Cambodia), 5,200 hectares of ELCs (Fig. 3(b)) in the Samlot district were converted
from forest for development purposes (e.g., rubber plantations). However, we found that this zoning
area only experienced tree cutting.In this study, the objective influences on land use patterns under
the local government’s land use development plan were successfully predicted by using the CAMarkov model. This model was effective because the land use planning focused on built-up landwith low population density and farmland zoning. However, there are still the challenges ofpredicting land use change when considering human activities (e.g., commercial and/or urban
development) and investments in land use development policies.
CONCLUSION
This study was the first attempt to predict future land use change and the effects of governmental
land use planning in the upper Sangkae River basin of Cambodia. Land use prediction has become acritical issue, due to the uncertainty of land use policies and the capacity of available models.
However, spatiotemporal land use dynamics through the CA-Markov model confirmed that it is avaluable tool for simulating and predicting future changes in the landscape. Moreover, the limitationsof this model were fulfilled with assistance from ArcGIS tools. It is hoped that our results will not
only be used to assess the impact of future land use changes on the hydrologic environment but also
be integrated with climate change prediction models to contribute to future water demand projections.
ACKNOWLEDGEMENTS
This study was fully supported by the Ministry of Education, Culture, Sports, Science, andTechnology (MEXT) in Japan.
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Research article
erd

Research article
Educational Material Research on the Color of Crayfish
forConversion to Edible Resources

SAKI HIGUCHI
Graduate School of Agro-Environment Science, Tokyo University of Agriculture, Tokyo, Japan

HONAMI ONO
Graduate School of Agro-Environment Science, Tokyo University of Agriculture, Tokyo, JapanHIROAKI HONDA
Technical Department, Uniflows Co., Ltd
SARVESH MASKEY
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, JapanAKIRA KUROSAWA
Faculty of Agriculture, Tokyo University of Agriculture, Tokyo, JapanTOSHIHIRO SUZUKI
Faculty of Applied Biosciences, Tokyo University of Agriculture, Tokyo, JapanNOBUYUKI TAKAHASHI
Faculty of Applied Biosciences, Tokyo University of Agriculture, Tokyo, Japan

HIROMU OKAZAWA
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan

KOUJI TAKEDA*
Teacher Education Course, Tokyo University of Agriculture, Tokyo, Japan
Email: k2takeda@nodai.ac.jp
Received 9 February 2023

Accepted 22 May 2023(*Corresponding Author)

Abstract The crayfish (Procambarus clarkii) is an invasive alien species consumed as a foodsource worldwide. However, there is an extremely low demand for it as a food resource inJapan, and it is typically targeted for extermination. One reason for the lack of progress inconsidering crayfish a sustainable food resource is limited education on the issue duringsecondary education programs. It is well known that astaxanthin is the pigment responsible
for the body color of common red crayfish and crustaceans such as shrimp and crabs. At thesame time, while there are ample study materials on plant pigments in the science education
curriculum in junior high and high schools in Japan, there are no such materials to ourknowledge that focus on animal pigments. Therefore, this research sought to develop teachingmaterials to deepen understanding of color as a food component of crayfish through anexperiment involving extracting and separating their pigments. Using pigments extracted fromred crayfish exoskeletons, we developed experimental teaching materials to observe
astaxanthin by employing thin-layer chromatography and high-performance liquid
chromatography. In addition, an experiment was conducted to observe the effect of different
foods on crayfish body color. For the experiment, food was developed to make crayfish bodies
white (decolorized) and orange. When the decolorized crayfish were fed norbixin or bixin,
which are components of the orange annatto pigment, norbixin tended to accumulate as orange
in the exoskeleton more than bixin based on the apparent body color change, color extraction
from images, and thin-layer chromatography. These findings are expected to be useful forⒸ ISERD

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science and nutrition education, supporting the development of the students’ awareness andunderstanding of crayfish as a food resource.
Keywords education, teaching material, Procambarus clarkii, pigment, food resource, SDGs

INTRODUCTION
Crayfish (Procambarus clarkii), which live in rivers, ponds, rice paddies, swamps, and other bodies
of water in the city, are a globally invasive alien species native to the United States (Gheradi, 2013).
Although the damage they cause to ecosystems is regarded as a problem, crayfish are used as a foodresource in the United States, China, and European countries (Hara, 2021). Furthermore, in the future,
their excrement and shells are expected to be used as agricultural resources such as fertilizers, as raw
materials for textiles, and as medical resources (Ifuku et al., 2004; Yihun et al., 2016).
Crayfish were introduced to Japan in 1927 as food for bullfrogs. Since then, the species’ highfertility rate and omnivorous nature have led to substantial damage to local ecosystems andagriculture. Thus, crayfish have become a well-known representative of alien species in Japan. As
part of environmental protection activities, crayfish are routinely exterminated and culled, but they
are not actively used. One reason for this is the lack of opportunities for students to learn about theusefulness of crawfish as a resource in elementary and secondary education. In elementary education,
crayfish are familiar observation materials because of their ease of care and management; however,in secondary education, they are only treated as an invasive alien species and representatives ofcrustaceans. Therefore, we thought that, in order to promote the recognition of crayfish as a foodresource, experimental materials focusing on the useful food components contained in crayfish might
be necessary. We focused on carotenoid pigments, which are a factor in crayfish body color thatchildren are likely to be interested in and have functional properties such as antioxidant effects andnutrients. In Japanese secondary education, carotenoid pigments are derived only fromphotosynthetic organisms, and their functions are rarely discussed. Among carotenoid pigments,
astaxanthin, which is found in the wild crayfish, salmon, and crustaceans (shrimp and crab) that arefamiliar to the Japanese people, is utilized in a variety of products because of its high functionality.
Although the usefulness of astaxanthin is known commercially, it has not yet been used in Japanese
secondary education. Therefore, the development of experimental teaching materials focusing on
astaxanthin using crayfish will provide new science experiment teaching materials focusing on
animal pigments and will enable students to learn about the usefulness of crayfish.
Astaxanthin is abundant in the exoskeletons of crayfish. The exoskeleton can easily extract
pigments, and the use of molting shells obtained each time the crayfish grows is useful as a type ofteaching material for collecting samples without killing the organism. Astaxanthin in the exoskeletonof crayfish exists in free and ester forms. However, the form of astaxanthin in exoskeletons derived
from molted shells is unknown. Therefore, in this study, we will examine the separation conditions
using thin-layer chromatography (TLC) and high-performance liquid chromatography (e-HPLC),
which are treated in secondary education, as teaching materials for observing the ontogeny ofastaxanthin in molting shells.
Previously, we produced crayfish that changed their body color to blue or pink by feeding
astaxanthin to genetically fixed white crayfish (Takeda, 2021). We also found that feeding anothercarotenoid pigment, annatto pigment, to white crayfish turned their bodies orange. However, the foodpigment annatto contains bixin and norbixin as components, and the difference in body color due tothese components is unknown. Wild crayfish are familiar for use as general teaching material, butsince they retain their original colors, they must be decolored. Therefore, in this study, as teachingmaterial to explore the factors involved in rearing, we prepared decolorized wild crayfish diets andconducted feeding tests of diets containing mainly bixin and norbixin. Then, the experiment willcompare the body color change for each color value and study the conditions to observe thesubstances that cause these body colors by TLC.
OBJECTIVEⒸ ISERD

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This research explored the development of teaching materials focusing on pigments, which are both
body color factors and nutrients in crayfish, with the aim of utilizing them in science and foodeducation to highlight their usefulness as food resources.
METHODOLOGY
Experiment Focusing on Astaxanthin Contained in Crayfish Exoskeleton and
Separation of Astaxanthin using TLC
We experimented to explore astaxanthin in crayfish exoskeletons as a body-color factor. Acetone
containing 0.01% astaxanthin (Fujifilm Wako) and krill were used as controls. It has been reported
that krill have astaxanthin and esters of astaxanthin (monoesters, diesters) (Takaichi et al., 2003).
Since the eyes of krill contain substantial amounts of these carotenoids (Maoka et al., 1985), krill
eyes were used in the experiment.
The sample for the experiment included the exoskeletons of living crayfish and molted
exoskeletons. For pigment extraction, the abdominal segment of each exoskeleton was shredded toabout 1 mm, and 100 μl of acetone was added to 0.01 g of the material. They were mixed lightly,
allowed to stand for 15 minutes, and centrifuged for 20 seconds. Each sample was spotted on a
TLC plate (TLC silica gel 60 F254 [4 × 8 cm], Sigma-Aldrich), and then the TLC was placed in thesolvent (petroleum ether: acetone = 7:3) in the deployment tank to separate the pigments.
Isolation of Astaxanthin Using e-HPLC“Kotori” (Uniflows, Japan) is an HPLC developed for educational purposes. It is smaller and cheaper
than the general HPLC. Thus, it is used in high schools in Japan. An e-HPLC was used to detectastaxanthin contained in the molted exoskeletons of crayfish. As a control, 0.001% astaxanthin(Fujifilm Wako) was dissolved in acetone, and 100 μl of acetone was added to 0.01 g of theabdominal segment as a sample. A Cadenza CD-C18 column (Φ6 × 50 mm) (manufactured by Intact
Co., Ltd.) was equilibrated with 50% methanol: THF (1:1) eluent at 600 μL/min at room temperature(25 C). Each sample of 2.7 μL was injected into the column; then, the peak of astaxanthin was
detected at 405 nm.
Creation of Bait for Decolorization and Feeding Tests
Material containing no carotenoid pigments was used to create decolorization bait. Rice powder wasused as a carbohydrate, soybean, pork bone, and fish powders were used as protein, and sardine oil
was used as a lipid. Rice powder, soybean powder, pork bone powder, fish powder, and sardine oil
were mixed at 2:3:2:2.8:0.2, and an appropriate amount of water was added. The ingredients werethen molded into a round shape, steamed for 20 minutes, and then solidified and used as feed. Four
crayfish aged about 8 weeks old were selected for a feeding test in which any changes to their bodycolor after consuming the decolorization bait were observed. The crayfish were fed 0.05 g of bait
once a day in the morning for 8 weeks. In addition, it was confirmed that there was no bait left overfrom the previous day, and any molted exoskeletons were removed, the water was changed daily
before feeding. As a control experiment, commercially available crayfish bait (Kyorin) was used
under the same conditions.
Pigment-containing bait was then created using the decolorization bait before it underwent
steaming. The bait and pigment were mixed at a ratio of 9:1, and about 0.5 ml of water per 1 g ofbait was added to assess the degree of viscosity. The pigments used were norbixin (Fujifilm Wako)
and bixin (Fujifilm Wako); they are components of annatto pigment (Scooter, 2009) used for foodcoloring. The ingredients were then molded into a round shape, steamed for 20 minutes, thensolidified. This pigment-containing bait was then used in a feeding test of crayfish decolored using
decolorization bait. Any changes to the crayfish’s body color were observed. Four crayfish were fedⒸ ISERD

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norbixin-containing bait, and four were fed bixin-containing bait. A piece of pigment-containing bait
was fed at a rate of 0.03 g per 0.1 g of crayfish weight in the morning once a day for 9 days. In
addition, it was confirmed that there was no bait left over from the previous day and any molted
exoskeletons were removed; the water was changed daily before feeding.
Color Extraction from an Image of Body Color Change
Pictures were taken of the subject crayfish every day under the same conditions. The red, green, andblue (RGB) values of the sixth abdominal segment were measured using a color selection software
called Spoitkun. The resulting data were expressed as the average value ± standard deviation.
Confirmation of Color Change Due to Boiling
It was important to confirm how the color would change after boiling as this is how crayfish areprepared as food. Therefore, we compared the color of the first pectoral leg of wild crayfish andcrayfish colored using norbixin before and after boiling for 15 min.
Detection of Substances Causing Body Color Using TLC
Acetone containing 0.01% norbixin (Fujifilm Wako) and 0.01% bixin (Fujifilm Wako) was used asa control, and the tail fins of crayfish were used as a sample. For each 0.01 g of tail fin mass, 50 μlof acetone was added. The solution was lightly mixed and then centrifuged for 20 seconds to extract
the pigment. After pigment extraction, each sample was quickly spotted on a TLC plate (TLC Silica
gel 60 RP-18 F254s [5×7.5 cm], Sigma-Aldrich). Then, the TLC was placed in the solvent (water:acetone 1:9) in the deployment tank to separate the pigments.
RESULTS AND DISCUSSION
Experiment Focusing on Astaxanthin Contained in Crayfish Exoskeleton and
Separation of Astaxanthin using TLC
Astaxanthin esters were mainly present in the abdominal segment of the crayfish (lane 3) as well as
the krill (lane 2), and astaxanthin was also detected (Fig. 1A). Astaxanthin was observed as a major
pigment in the abdominal segment of the molted exoskeleton (lane 4) (Fig. 1A). Although it has beenreported that astaxanthin esters and astaxanthin are the main pigments in the exoskeleton of wild
crayfish (Nakagawa et al., 1974), no research was found describing the predominance of freeform
astaxanthin in molted exoskeletons. This experiment revealed that there is a difference in the presenceof astaxanthin in crayfish exoskeletons before and after molting.
Since crustacean molting is a lifelong phenomenon, molted exoskeletons can be continuously
collected as samples for experiments. In addition, since the pigment contained is mainly astaxanthin
in the free form, it is expected that it will be easy for children to understand. Using molted
exoskeletons for experiments to observe pigments contained in the exoskeletons of crayfish isconsidered suitable.
Isolation of Astaxanthin Using e-HPLC
As with the control freeform astaxanthin, elution peaks were also confirmed in the molted
exoskeleton at 200 s–230 s (Fig. 1B). Freeform astaxanthin was confirmed to be the main pigment
contained in the molted exoskeleton using not only TLC but also e-HPLC.
“Kotori” can be used to confirm astaxanthin in a short time. Thus, it is possible to perform
multiple analyses even within a typical 50-minute class period. The device and column are very small
compared to general HPLC, and, since it is very portable, it is considered suitable for conducting
advanced experiments aimed at separating astaxanthin in various educational settings.
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Fig. 1 Isolation of astaxanthin in wild crayfish exoskeletons A (TLC), B (e-HPLC)
Creation of Bait for Decolorization and Feeding Tests
In the feeding test using TL2-3 cm crayfish for 8 weeks, the bodies of the crayfish fed with thecommercial bait turned brown (Fig. 2A-a) while the bodies of the crayfish fed with decolorized bait
turned white (Fig. 2A-b). Body color changes to blue and white with each molt are known to occur
by feeding horse mackerel with a low amount of carotenoid pigment. However, horse mackerel bait
is likely to cause contamination and odor in the breeding water. The decolorized bait created in thisexperiment can also be used as an alternative bait, which is considered to have the advantage of easeof breeding.
In the feeding test with pigment-containing bait, the bodies of all four crayfish consuming thenorbixin-containing bait (Fig. 2B-abc) rapidly changed to orange while those consuming the bixincontaining bait gradually changed to yellow, although there were individual differences (Fig. 2Bdef).
In our previous research, genetically fixed white crayfish fed with a diet containing annatto pigment(TCI, Japan) diet turned orange. However, in that research, it was unclear whether it was norbixin or
bixin that was related to the orange body color. In this study, decolored wild crayfish turned darkorange when fed with norbixin (Fig. 2B-c) and yellow when fed with bixin (Fig. 2B-f). Thus, it wasapparent that norbixin is the main factor contributing to orange body color. Fig. 2 shows the changeover time in the crayfish with the most colored body on day 9.

Fig. 2 Body color change by feeding test A: commercial bait (Left) and decolorized bait
(Right) B: Norbixin (Left) and Bixin (Right)
Color Extraction from an Image of Body Color Change
When crayfish color is expressed as a mixture of Red (R), Green (G), and Blue (B) in 16 bits (256steps) using color extraction of images taken over time, the R value did not change significantly
for either control, bixin, or norbixin. In terms of G values, it was confirmed that the feeding periodⒸ ISERD

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of bixin was almost constant while norbixin was gradually declining. In addition, the B value wasalmost zero in one day for norbixin while, for bixin, it gradually decreased (Fig. 3).
In Japan industry standard color names, yellow is R ≒ G > B (255, 212, 0), and orange is R >G > B (243, 152, 0). In addition, both orange and yellow become darker orange and yellow as the B
value decreases to 0. Therefore, orange and yellow can be compared from the relative ratio of R and
G. This result supports the visual color shown in Fig. 2B. Efforts to quantify changes in the color of
the eyes seen using color extraction software will lead to activities to grasp observation events morescientifically and can be used for not only science but also STEAM education.

Fig. 3 Changes in RGB values of crayfish exoskeletons over time using
pigment-containing baits
Confirmation of Color Change Due to Boiling
Just as many crustaceans turn red when boiled, wild crayfish are red black before boiling (Fig. 4A)
but turn red when boiled (Fig. 4B). Interestingly, the first pectoral leg of a crayfish, which had turnedorange with norbixin (Fig. 4C), remained orange (Fig. 4D) when boiled. Orange has the same effecton food palatability as red (Birren, 1963). Although boiled crayfish as food have typically come only
in red, the above finding can be used to develop new colors of crayfish for food products. It is also
hoped that crayfish will be used as a teaching material for the development of crayfish as a foodsource in Japan.

Fig. 4 Change in color of the first pectoral leg before and after boiling
Detection of Causative Substances of Body Color using TLC
TLC revealed bands at the same position in norbixin (lane 1) and the tail fans colored by norbixin(lane 2) and bixin (lane 3) and the tail fans colored by bixin (lane 4) (Fig. 5). This confirmed that thepigments contained in the bait were accumulated in the body. In this experiment, a tail fan derived
from a living body was used, but the same result was obtained for the molted exoskeleton (data notshown).
By conducting this experiment in parallel with the feeding test, it is possible to use it asmultiscale experimental teaching material to detect changes in body color and substances that cause
body color.
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Fig. 5 Separation of norbixin and bixin in TLC
CONCLUSION
Astaxanthin is contained in red crustaceans and fish. It is a factor in body color as well as an important
substance with antioxidant effects. The exoskeleton of the crayfish contains a large amount ofastaxanthin and is also useful as a teaching material because crayfish is treated in educational courses
and is a familiar creature. In addition, the development of experimental materials focusing on
astaxanthin using crayfish will be a new scientific experimental material focusing on animal
pigments and will enable students to learn about the usefulness of crayfish.
In this study, astaxanthin contained in crayfish exoskeletons was isolated using TLC and eHPLC. TLC is an experimental technique used in secondary education for the separation of pigments
derived from photosynthetic organisms. The e-HPLC is an instrument developed for educational
purposes and used in secondary schools specializing in science education. In this study, we haveclarified the experimental conditions under which astaxanthin can be detected in more detail and ina shorter time by using e-HPLC as well as TLC; these experimental methods can be implemented inschool education. Interestingly, we found that the presence of astaxanthin in the exoskeleton of wild
crayfish in living tissue differed from that derived from molting.
For wild crayfish, we developed a decolorized bait that regulated the carotenoid pigments
contained in the material and succeeded in whitening it. In addition, by feeding bait containing
norbixin and bixin, which are components of annatto pigment for food coloring, it was revealed thatbody color turned dark orange with norbixin and yellow with bixin. Furthermore, it was clarified that
norbixin turns a dark orange color in a shorter period of time than bixin from changes in appearance,
TLC, and color extraction.
The findings and experimental methods of this research can be implemented in schools and usedas new experimental materials focusing on animal pigments. Since these are teaching materials that
focus on color, it is expected they will be used in science and food education that will lead to theedible use of crayfish.
ACKNOWLEDGMENTS
We thank Mr. Kenshin Yuasa for his cooperation. This work was supported by the Tokyo NODAI
Research Program for Sustainable Agriculture and JSPS KAKENHI Grant number JP18K02989.
REFERENCES
Birren, F. 1963. Color and human appetite. Food Technology, 17, 553-555.
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Gheradi, F. 2013. Crayfish as global invaders, Distribution, impact on ecosystem services and management
options. Freshwater Crayfish, 19 (2), 177-187, Retrieved from DOI https://doi.org/10.5869/fc.2013.v192.177
Hara, Y. 2021. Development and issues of integrated rice-aquaculture farming and research trends in China. Ejournal GEO, 16 (1), 70-86, Retrieved from URL https://researchmap.jp/hara_yuta/published_papers/31351252/attachment_file.pdf
Ifuku, S., Nogi, M., Abe, K., Yoshioka, M., Morimoto, M., Saimoto, H. and Yano, H. 2004. Preparation ofchitin nanofibers with a uniform width as α-chitin from crab shells. Biomacromolecules, 10 (6), 1584-1588,
Retrieved from DOI https://doi.org/10.1021/bm900163d
Maoka, T., Katsuyama, M. and Kaneko, N. 1985. Stereochemical investigation of carotenoids in the Antarctic
krill Euphausia superba. Bulletin of the Japanese Society of Scientific Fisheries, 51 (10), 1671-1673,
Retrieved from URL https://www.jstage.jst.go.jp/article/suisan1932/51/10/51_10_1671/_pdf
Nakagawa, H., Kayama, M., Yamada, H. and Asakawa, S. 1974. Studies on carotenoprotein in aquatic animals,
IV, Carotenoid pigments in crayfish (Procambarus clarkii). Journal of the Faculty of Fisheries and Animal
Husbandry, Hiroshima University, 13, 1-13, Retrieved from URL https://ir.lib.hiroshima-u.ac.jp/41206/files/ 35023
Scooter, M. 2009. The chemistry and analysis of annatto food colouring, A review. Food Additive andContaminants, 26 (8), 1123-1145, Retrieved from DOI https://doi.org/10.1080/02652030902942873
Takaichi, S., Matui, K., Nakamura, M., Muramatu, M. and Hanada, S. 2003. Fatty acids of astaxanthin esters
in krill determined by mild mass spectrometry. Comparative Biochemistry and Physiology, Part B
Biochemistry and Molecular Biology, 136 (2), 317-322, Retrieved from DOI https://doi.org/10.1016/S1096-4959(03)00209-4
Takeda, K., Yururi, M. and Asanuma, S. 2021. New ways of teaching science. Science Impact Ltd., 16-18.
Takeda, K., Yururi, M. Jitsuno, M., et al. 2021. An impact of biological pigments as teaching material. Open
Access Government, 406, 262-263.
Yihun, F.A., Egusa, M., Kaminaka, H., Izawa, H., Morimoto, M., Saimoto, H. and Ifuku, S. 2016.
Protein/CaCO3/chitin nanofiber complex prepared from crab shells by simple mechanical treatment and its
effect on plant growth. International Journal of Molecular Sciences, 17 (10), 1600, Retrieved from DOI
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Research article
erd

Research article
Evaluating Water Purification Capacity of Patinopecten
yessoensis Shells Inoculated with Effective Microorganisms

KOSEI MOROISHI
Graduate School of Agro-Environmental Science, Tokyo University of Agriculture, Japan

MACHITO MIHARA*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Japan
Email: m-mihara@nodai.ac.jp
Received 15 January 2023

Accepted 25 May 2023(*Corresponding Author)

Abstract In Japan, the installation of biotopes, defined as aquatic systems aiming to recreatea natural environment, has been popular since the 20th century. Due to the closed character ofmany biotopes and high nutrient inputs, one of the main issues related to water quality in abiotope is the occurrence of blue-green algae. In this environment, reduction and control ofthe blue-green algae cannot be done by chemicals. Water quality must be maintained by othernon-chemical means. Therefore, this study aims to investigate the effectiveness of
patinopecten yessoensis shells inoculated with effective microorganisms as a method for
nutrient and water quality control in a biotope environment. In Japan, huge numbers of
patinopecten yessoensis shells are left out in the open because they cannot be properly handled.
At the same time, patinopecten yessoensis shells are porous and have been studied for water
purification. Accordingly, this research has focused on the water purification capacity ofpatinopecten yessoensis shells inoculated with effective microorganisms. In the study
experiment, patinopecten yessoensis shells inoculated with lactobacillus, bacillus subtilis var.
natto, and saccharomyces cerevisiae were used to purify water samples taken from a pond in
Yatoyama Park in Kanagawa Prefecture, Japan. To compare nitrogen removal capacity, theexperiments consisted of 8 treatments in total. In the first group of four treatments,
patinopecten yessoensis shells were burned at 600 degrees to increase pore size anddistribution, and were then inoculated with the aforementioned microorganisms. In the second
group of four treatments, patinopecten yessoensis shells were not burned, and were only
inoculated with the microorganisms. Uninoculated burned and unburned shells were used ascontrol treatments. The experimental results showed total nitrogen removal rates of 42% for
unburned and uninoculated shells, 0% for lactobacillus-inoculated unburned shells, 45% forbacillus subtilis var. natto-inoculated unburned shells, and 58% for saccharomyces cerevisiaeinoculated unburned shells. Regarding the burned shells, results showed 51% nitrogen
reduction at the uninoculated shells treatment. Lactobacillus-inoculated burned shells reduced
nitrogen by 47%, bacillus subtilis var. natto-inoculated burned shells reduced by 34% andsaccharomyces cerevisiae-inoculated burned shells reduced the nitrogen in the water sample
by 69%. Since this was a short-term experiment, a long-term experiment as well as fieldapplicable methods need to be discussed in the future.
Keywords water purification, microorganism, patinopecten yessoensis, lactobacillus,
bacillus subtilis var. natto, saccharomyces cerevisiae

INTRODUCTION
Biotope is a term used to describe a biological space; biotopes attracted attention in Germany in the
1970s when environmental problems arose. In Japan, the expansion of urban areas due to rapid
population growth since the period of high economic growth has led to a decrease in farmland andforest land. Accordingly, the habitat and growth environment for living organisms has decreased,
and biodiversity has been damaged due to environmental changes, invasions, and pollution. For thesereasons, biotopes have begun to be created in many places since the end of the 20th century. However,Ⓒ ISERD

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since biotopes are closed water systems with high nutrient inflow, the occurrence of blue-green algae
has become one of the problems. The use of chemicals is an effective means to suppress and control
the occurrence of blue-green algae. However, the use of chemicals in biotopes with biodiversity canlead to the destruction of biodiversity. Hence, it is necessary to maintain water quality by meansother than chemicals.
In Japan, about 300,000 to 600,000 tons of patinopecten yessoensis are caught annually, and it
is said that “about half of the catch is shells of patinopecten yessoensis” (Fishery Waste Disposal
Guidelines Revised, Ministry of the Environment, 2020). The patinopecten yessoensis shells would
normally be properly disposed of at a processing plant, but the huge number of shells is causing ashortage at the plant. As a result, many shells are left out in the open without being properly handled.
However, patinopecten yessoensis shells are porous and have been studied for water purification.
Accordingly, research attention has been focused on the water purification potential of patinopecten
yessoensis shells inoculated with effective microorganisms.
OBJECTIVE
The purpose of this study is to investigate the effectiveness of patinopecten yessoensis shells
inoculated with effective microorganisms as a method of nutrient removal and water quality
management in a biotope environment. There has been little discussion of water purification using
patinopecten yessoensis shells inoculated with effective microorganisms.
The objectives of this study were to investigate the water quality in the biotope, to evaluate theinoculation capacity of microorganisms in patinopecten yessoensis shells, and to evaluate andcompare the water purification capacity of patinopecten yessoensis shells inoculated with effective
microorganisms.
METHODOLOGY
Field Survey
This study was conducted at 3 biotopes in Yatoyama Park, Zama City, Kanagawa Prefecture, Japan(Site 1 - Site 3). Yatoyama Park has been developed as a natural ecology observation park in a placethat retains a satoyama atmosphere. It is a place being rich in biodiversity with fireflies in the summer
and waterflow in the fall and winter. However, according to the manager of Yatoyama Park,
eutrophication of the biotope and the occurrence of blue-green algae have been confirmed. There areconcerns about the impact on people who visit the park and the negative effects on the surrounding
environment. Water samples were collected approximately once a month from June 2021 to February2022, and total nitrogen (TN), total phosphorus (TP), potential hydrogen (pH), electric conductivity(EC), and suspended solid (SS) were measured. The water quality level in the biotope was determinedbased on the environmental standards listed by the Ministry of the Environment.
Water Purification Experiment Using Patinopecten yessoensis Shells Inoculated with
Effective Microorganisms
In the study experiment, discarded patinopecten yessoensis shells from Aomori Prefecture,
lactobacillus, bacillus subtilis var. natto, and saccharomyces cerevisiae were used. Thesemicroorganisms were used because they have been used in water purification and are relatively easy
to obtain.
Discarded patinopecten yessoensis shells were crushed with a hammer and then divided into
two groups, with one group being unburned (U) and the second group being burned at 600 degrees
to increase pore size and distribution (B). In addition, the burned shells were rinsed once in water toremove the calcium hydroxide generated after burning.

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The unburned and burned shells were inoculated with the above-mentioned microorganisms for
3 days. Uninoculated burned and unburned shells were used as control treatments, in total theexperiments consisted of 8 treatments.
After inoculation, the shells were rinsed under running water to wash away the easily detachedmicroorganisms. The inoculation capacity of patinopecten yessoensis shells was evaluated by
performing a colony count using a mixed culture method for lactobacillus and a plate dilution method
for bacillus subtilis var. natto, and saccharomyces cerevisiae.
In addition, to compare the nitrogen removal capacity, patinopecten yessoensis shells were
immersed in 1 L of water from the biotope at Yatoyama Park for a water purification experiment for
3 days. The ultraviolet absorption spectrophotometric method was used to measure total nitrogen.
The details of the 8 treatments are as follows.
Table 1 Combination of shell processing and microorganisms
Unburned and uninoculated shells
Lactobacillus-inoculated unburned
shellsBacillus subtilis var. natto-inoculated
unburned shells
Saccharomyces cerevisiae-inoculated
unburned shells

UC

Burned and uninoculated shells

BC

UL

Lactobacillus-inoculated burned shells

BL

Bacillus subtilis var. natto-inoculatedburned shells
Saccharomyces cerevisiae-inoculated
unburned shells

UB
US

BB
BS

RESULTS AND DISCUSSION
Water Quality In Biotope

Fig. 1 Changes in total nitrogen (TN) in the biotope (26 July 2021 to 4 February 2022)

Fig. 2 Changes in total phosphrus (TP) in the biotope (26 July 2021 to 4 February 2022)

Figure 1 indicates the change in total nitrogen. The average value of total nitrogen measured at eachwater sampling site was 1.84 mg L-1 at Site 1, 0.66 mg L-1 at Site 2, and 0.73 mg L-1 at Site 3. The
data tended to be higher in summer and fall, which seems to be due to precipitation, fallen leaves,Ⓒ ISERD108

IJERD – International Journal of Environmental and Rural Development (2023) 14-1

and waterfowl. Figure 2 indicates the change in total phosphorus. The average total phosphorus
measurement data for each water sampling site was 0.29 mg L-1 for Site 1, 0.03 mg L-1 for Site 2 and0.07 mg L-1 for Site 3. As with the total nitrogen data, the data tended to be higher in the summer andfall, which seems to be due to precipitation, fallen leaves, and waterfowl. Also, the reason there is nodata for Site 1 on the 112th day is that the water source was buried by sediment, and water sampling
was impossible.
In addition, both total nitrogen and total phosphorus tended to be higher at Site 1. This is because
Site 1 is closer to the inflow point than other sampling sites, resulting in a greater inflow of sediment.
The biotope at Site 1 has been found to have poor water quality compared to the environmental
standards set by the Japanese Ministry of the Environment (Table 2). Therefore, there is a need forwater purification. The source of nitrogen inflows and their relationship to the surrounding
environment, such as waterfowl and vegetation, also need to be analyzed in detail.
Table 2 Environmental standards for total nitrogen (TN) and phosphorus (TP) in lakes
Item type
Ⅰ
Ⅱ
Ⅲ
Ⅳ
Ⅴ

Standard value
Total nitrogen
0.1 mg/L or less
0.2 mg/L or less
0.4 mg/L or less
0.6 mg/L or less
1.0 mg/L or lessTotal phosphorus
0.005 mg/L or less
0.010 mg/L or less
0.030 mg/L or less0.050 mg/L or less
0.100 mg/L or lessNote: Ministry of the Environment, 2022

Microorganism Inoculation Capacity of Patinopecten yessoensis Shells
Figure 3 shows the number of microorganisms inoculated on patinopecten yessoensis shells. The
number of microorganisms inoculated with lactobacillus on unburned shells was 2.8.E+05 cfu g-1,that with bacillus subtilis var. natto on unburned shells was 6.0.E+05 cfu g-1, and that with
Saccharmyces cerevisiae on unburned shells was 2.3.E+07 cfu g-1. Also, the number ofmicroorganisms inoculated into the burned shells with lactobacillus was 1.9.E+07 cfu g-1, that into
the burned shells with bacillus subtilis var. natto was 2.6.E+05 cfu g-1, and that into the burned shells
with Saccharmyces cerevisiae was 1.6.E+07 cfu g-1.

Fig. 3 Amount of microorganisms inoculated in each shell
The amount of inoculated lactobacillus was increased by burning the shells at 600 degrees. The
amount of bacillus subtilis var. natto and Saccharmyces cerevisiae inoculated was not significantly
changed by burned shells. The change in the amount of inoculum seems to be caused by changes in
the pore size, specific surface area, and organic matter content of the patinopecten yessoensis shells.
A more detailed analysis of pore size, distribution, and specific surface area will be necessary to
determine the relation between the pore and the number of microorganisms inoculated.
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Nitrogen Removal Capacity of Patinopecten yessoensis Shells Inoculated with
Effective Microorganisms
The experimental result according to the Fig. 4 showed total nitrogen removal rates of 42% for
unburned and uninoculated shells, 0% for lactobacillus-inoculated unburned shells, 45% for bacillus
subtilis var. natto-inoculated unburned shells, 58% for saccharomyces cerevisiae-inoculated
unburned shells. Regarding the burned shells, results showed 51% nitrogen reduction at theuninoculated shells treatment. Lactobacillus-inoculated burned shells reduced nitrogen by 47%,
Bacillus subtilis var. natto-inoculated burned shells reduced by 34% and saccharomyces cerevisiaeinoculated burned shells reduced the nitrogen in the water sample by 69%. The highest total nitrogen
removal rate was indicated by the treatment of burned shells inoculated with saccharomyces
cerevisiae. Watabe et al. (2014) mentioned that saccharomyces cerevisiae is ableto incorporate
nitrogen into the fungus itself. Hence, its removal capacity seems to be significantly different fromthat of other microorganisms. The reason that the inoculation of burned shells with lactobacillus did
not remove total nitrogen seems to be that the rinsing process after the inoculation was not performed
properly.

Fig. 4 Changes in total nitrogen (TN) in water purification experiments
CONCLUSION
In this study, the water quality in the biotope was determined, and at the same time, themicroorganism inoculation capacity of patinopecten yessoensis shells and the water purification
ability of patinopecten yessoensis shells inoculated with effective microorganisms were evaluated.
The water quality of the biotope at the subject site was found to be inadequate and in need ofwater purification. It is necessary to conduct a more detailed survey because of the influence of thesurrounding environment, including fallen leaves, precipitation, waterfowl, and vegetation.
The microorganism inoculation capacity of patinopecten yessoensis shells was evaluated to acertain capacity for all microorganisms. Among them, Saccharmyces cerevisiae was found to have ahigh inoculation capacity. It is assumed that the size of the Saccharmyces cerevisiae was suitablewith the internal pore size and specific surface area of the patinopecten yessoensis shells. In the future,
it is necessary to study the relationship between microorganism inoculation capacity and pore size,and specific surface area.
The water purification ability of patinopecten yessoensis shells inoculated with effective
microorganisms was evaluated for total nitrogen removal except for lactobacillus-inoculated
unburned shells. The highest removal capacity was observed in burned shells inoculated with
Saccharmyces cerevisiae. This was a short-term and small-scale experiment. Future experiments
should be conducted to consider long-term and field applicability for the reuse of patinopecten
yessoensis shells.

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ACKNOWLEDGEMENTS
In preparing this paper, I would like to express my sincere gratitude to Associate Professor Toru
Nakajima of the Department of Production and Environmental Engineering, Faculty of Regional
Environmental Sciences, Tokyo University of Agriculture, for his enthusiastic guidance on
experimental methods, paper structure, and presentation, despite his busy schedules amidst theconfusion of the social situation. I would also like to thank the graduate students at the samelaboratory for their detailed guidance on experimental methods and analysis of the data obtained.
REFERENCES
Asari, M. 2005. Application of scallop shell and thinning wood charcoal to water purification promoting project
for the rebuilding of nature-oriented brook. Journal of the Japan Society of Agricultural and RuralEngineering, 73, 9, 41-42, Retrieved from DOI https://doi.org/10.11408/jjsidre1965.73.9_823
Kanagawa Prefectural Park Association. 2022. Zama Yatoyama Park, Kanagawa, Japan, Retrieved from URL
http://www.zamayatoyama.kanagawa-park.or.jp/index.html
Kobaishi, K. and Kawahigashi, T. 2020. Oyster shell utilization as a water purification material. Annual Report,
Research Institute for Science and Technology, 31, 11-20.
Kudo, A., Kudo, F. and Izumi, M. 2008. Experimental study on the water environment in rural areas and water
quality improvement using a regional resource as the contact material. Proceedings of the National
Conference of the Japanese Society for Agricultural and Rural Engineering, 60-61.
Ministry of Agriculture, Forestry and Fisheries. 2022. Ministry of Agriculture, Forestry and Fisheries, Tokyo,
Japan, Retrieved from URL https://www.maff.go.jp/
Ministry of the Environment. 2022. Ministry of the Environment, Tokyo, Japan, Retrieved from URL
https://www.env.go.jp/
Ministry of the Environment. 2020. Fishery waste disposal guidelines, Revised. Ministry of the Environment,
Tokyo, Japan, Retrieved from URL https://www.env.go.jp/content/900535373.pdf
Murakami, C., Miura, S. and Hamagami, K. 2015. Factors in the increase of nutrient salts in a small reservoir
with blooms of blue green algae. The Society of Agricultural and Rural Engineering, 5 (5), 520-521.
Murakami, K. et al. 2002. Purification of polluted river water using microbial film bioreactors. Bulletin ofTokyo Kasei University 2 Natural Sciences, 44, 127-131, Retrieved from URL http://library.jsce.or.jp/jsce/open/00035/2002/57-7/57-7-0187.pdf
Nagasuna, K. and Shiomi, H. 2021. Effect of surface microstructure on organic matter removal ability of
microorganism-supported sintered alumina body. Journal of the Society of Materials Science, Japan, 70 (6),445-450, Retrieved from DOI https://doi.org/10.2472/jsms.70.445
Narita, M. et al. 2007. Purification of polluted water with a microbe membrane bioreactor, Effect of purifying
wastewater with variation to immobilized support. Journal of the Japan Society of Home Economics, 58(4), 203-209, Retrieved from DOI https://doi.org/10.11428/jhej.58.203
Sato, T. and Fukuda, M. 2003. Effective use of fishery waste. Hokkaido Development Civil Engineering
Research Institute, Monthly Report, No. 606, Retrieved from URL https://thesis.ceri.go.jp/db/files/
0005511040.pdf
Watabe, T., Fujii, R., Iefuji, H. and Kitamoto, H. 2014. Nitrogen removal from, and candida utilis biomass
production from shochu wastewater. Journal of the Brewing Society of Japan, 109 (2), 82-88, Retrieved
from URL https://agriknowledge.affrc.go.jp/RN/2010871540.pdfⒸ ISERD

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Research article
erd

Impact Assessment of New Dam Construction in Nam Ngum
Watershed on Electric Generation at Num Ngum 1 Dam
KOSHI YOSHIDA*
Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
Email: kyoshida@edu.k.u-tokyo.ac.jp

KEIGO NODA
Gifu University, Gifu, JapanTASK KATO
Tokyo University of Agriculture and Technology, Tokyo, JapanKEODUANGCHAI KEOKHAMPHUINational University of Laos, Vientiane, Laos
Received 14 January 2023

Accepted 25 May 2023 (*Corresponding Author)

Abstract Lao PDR is a landlocked country and around 90% of the country is located in
Mekong River Basin. Average annual rainfall is around 1,900 mm and 35% of the annual flowin the Mekong River is from Lao tributaries. Given the abundance of water resources in Laos,many hydropower dams have been constructed in the country. The generated electricity isexported to Thailand and other surrounding countries and has become an important means ofearning foreign currency for Laos. In particular, the Nam Ngum 1 dam has been in operation
since 1971 in the Nam Ngum watershed near Vientiane, the capital of Laos, and several
additional dams have been completed in this watershed since 2010. Hydropower has great
potential to boost the national income and raise living standards in Lao PDR. At the same time,hydropower reservoirs have a large number of potential cross-sector impacts, includingchanges in the downstream water environment. The purpose of the current study was toevaluate the impact of the construction of multiple dams in the Nam Ngum watershed on theriver flow regime, as well as on the hydropower generation of the preceding Nam Ngum 1
dam. In this study, the fully distributed TOPMODEL was developed and applied to analyze
the water flow in the Nam Ngum watershed with a spatial resolution of 1 km X 1 km.
Simulated river discharge and dam storage were in good agreement with observed data.
Subsequently, we investigated the impact of the construction of the Nam Lik 1/2, Nam Ngum
2, and Nam Ngum 5 dams, which were newly developed after 2010. Results indicated thatnew dam construction has positive effects in decreasing flood flow during the rainy season
and increasing discharge in the dry season, while electricity generation at the Nam Ngum1
dam also increased by 6.8%.
Keywords water resource development, hydropower, multi reservoirs, Laos

INTRODUCTION
Lao PDR is a landlocked country and around 90% of the country is located in Mekong River Basin.
Average annual rainfall is around 1,900 mm and 35% of annual flow in Mekong is from Lao
tributaries, so many hydropower dams have been constructed against the backdrop of abundant water
resources. The generated electricity was exported to Thailand or surrounding countries and has
become an important means of earning foreign currency for Laos. Electricity demand in Laos has
been growing at a high rate of more than 10% since 1999, both in terms of consumption and peak
power and according to the national power supply development plan, demand exceeded supply until
around 2014. To meet this growth in demand, the Lao government has decided to utilize its abundantⒸ ISERD112

IJERD – International Journal of Environmental and Rural Development (2023) 14-1hydropower resources, which are domestically produced energy, and to actively promote thedevelopment of power sources (Uematsu, 2019).
In particular, the Nam Ngum 1 Dam has been in operation since 1971 in the Nam Ngum
watershed near Vientiane, the capital of Laos, and several dams have been completed in thiswatershed since 2010. Hydropower has great potential to boost the national income and raise living
standards and create opportunities for the establishment of electricity-using industries in Lao PDR.
While hydropower reservoirs also have a large number of potential cross-sector impacts, includingchanges in downstream flows and water quality, dam safety, and resettlement of living people(Lacombe et al., 2014). Likewise, Kudo et al. (2013) assessed how to change the flow discharge into
Nam Ngum 1 reservoir due to new dam construction, however, impact on hydropower generation
was not obtained.
OBJECTIVE
The purpose of this study was to evaluate the impact of the construction of multiple dams in the Nam
Ngum watershed on the river flow regime, as well as on the hydropower generation of the preceding
Nam Ngum 1 dam.
METHODOLOGY
Study Area
The Nam Ngum watershed in Laos is a tributary of the Mekong River. The river length is about 415
km, and the catchment area is about 17,000 km2. The land use in the basin is paddy fields (16%),
forests and bushes (72%), and residential land (only 0.2%), making the basin still rich in nature. In
this watershed, several large-scale dams were constructed after 2010 to meet the increasing electricdemand of domestic and surrounding countries (Fig. 1).

Fig. 1 Nam Ngum watershed and dams’ location
Nam Ngum 1 Hydroelectric Power Plant is located on the Nam Ngum River about 90 km northof Vientiane, the capital of Laos, and its reservoir has active storage of 4,700 MCM (million m3),
which started operation in 1971. As the main power source for the metropolitan area, its generation
capacity was 155 MW until 2017. The utilization rate of the Nam Ngum 1 power plant was initially
66%, but the Nam Song and Nam Leuk power plants developed in 1995 and 2000, respectively,
increased the flow rate by an average of 65 m3/s and 15 m3/s, respectively, and the utilization rate
has increased to 74%. After 2018, the capacity was improved to 235 MW by the JICA project(Uematsu, 2019).
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Nam Ngum 2 Hydroelectric Power Plant was completed in 2011, which is located about 100
km north of Vientiane, the capital of Laos, and is the second power plant on the Nam Ngum River.
The Nam Ngum 2 Power Project is a concrete surface impermeable rockfill dam with a dam heightof 181 m. The installed capacity is 615 MW, and 100% of the power be exported to Thailand. Its
basin area accounts for 67% of the Nam Ngum 1 power plant basin area, having an effective storage
capacity of 2,620 MCM. Nam Ngum 5 was completed in 2012, with a dam height of 99 m. With acatchment area of 413 km2 and an effective storage capacity of 251 MCM, the project is smaller thanthe Nam Ngum 2 power project (Kudo et al., 2013).
The Nam Lik 1/2 Power Project started operation in 2011, having 100 MW power generationand 101 m height concrete surface impermeable dam in the middle reaches of the Nam Lik River, atributary of the Nam Ngum River. With a medium-sized active storage capacity of 540 MCM, thisdam is expected to smooth the flow conditions in the lower reaches of the dam throughout the year
and increase the dry season flow.
Rainfall-Runoff Model
To evaluate the river water flow, a distributed water cycling model was developed and applied toanalyze the water balance in the basin. TOPMODEL was employed for the rainfall-runoff analysis.
Such a distributed model can include the spatial distribution of topography, land use, and soil
characteristics. Therefore, TOPMODEL is widely used for hydrological characteristic analysis, water
management, water quality analysis, and future forecasting. TOPMODEL was proposed by Beven
and Kirkby (1979) based on the contributing area concept in hill slope hydrology. This model isbased on the exponential transmissivity assumption, which leads to a topographic index ln (a/To/tanb),
where a is the upstream catchment area draining across a unit length, To is the lateral transmissivity
under saturated conditions, and b is the local gradient of the ground surface. Figure 2 illustrates theconceptual structure of the water cycle as estimated by TOPMODEL. For details, refer to Yoshida etal. (2017).

Fig. 2 TOPMODEL structure
Dam Operation Model
Large scale dams having quite huge water storage capacity makes a significant effect to control riverwater discharge (Hanasaki et al., 2003). Normally, the dam reservoir stores water in the rainy season
and releases water in the dry season so that downstream river discharge becomes stable compared to
the variation of natural river flow. In the Nam Ngum watershed, several dams have more than 250
MCM capacity which is mostly used for electric generation. In this study, a simple dam storage modelⒸ ISERD

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was applied to describe the river discharge stabilization effect (Juthithep et al., 2014). The storage ofa reservoir Vres (m3) can be calculated by the following equation.
Vrest+∆t=Vrest+(Qint-Qoutt)×∆t(1)

Qoutt=Qpwt+Qspillt(2)

Qpwt =Qpwmax×(Vrest/Vresmax)(3)

Where Qin is the inflow of a reservoir (m3/s) calculated by flow accumulation along the upstream
river network, Qout is the outflow of a reservoir (m3/s), Qpw is the turbine discharge (m3/s), Qpw is thespillway discharge (m3/s), Vresmax is active storage(m3) and Qpwmax is maximum turbine flow (m3/s).
1 Dam Case and 4 Dam Case Scenarios
In this study, we used the data from 2002-2010. During this period, only the Nam Ngum 1 plant was
operating, so first we checked model performance under the 1dam case scenario. And then, 4 dams’
case was also simulated by using the same input data and compared with the 1 dam case scenario toinvestigate the impact of newly developed dams on downstream river flow and hydropower
generation at Nam Ngum 1 dam, considering Nam Lik 1/2, Nam Ngum 2, and Nam Ngum 5, whichwere newly developed after 2010. To evaluate the hydropower generation at Nam Ngum 1 dam, therelation between turbine discharge and hydropower generation was used in Fig. 3.

Fig. 3 Relation between turbine discharge and hydropower generation at Nam Ngum 1
RESULTS AND DISCUSSION
By using the proposed model, river flow at Pakkanhoung (catchment area of 14,300 km2) station was
simulated from 2002 to 2010. The first 5 years of data were used for parameter calibration, and thelatter 4 years of data were used for validation. Parameters were calibrated by the try-and-error method
to maximize the Nash-Sutcliffe efficiency (NSE). Solid line and plot in Fig. 4 show the calculated
and observed river discharge at Pakkanhoung station under 1 dam case. Estimated NSE were 0.59
and 0.50 in the calibration and validation periods respectively. Model performance can be evaluatedas “satisfactory” if NSE > 0.50 (Moriasi et al., 2007). The reason for the relatively low accuracy isthat there is no station in a relatively high-elevation area. The dashed line in Fig.4 shows riverdischarge under 4 dam cases. Due to the flow regulation effect of multiple dam reservoirs in upstream,
positive effects to decrease in flood flow in the rainy season and to increase discharge in the dry
season were obtained. Especially, minimum discharge in the dry season increased from 221 m3/s to
264 m3/s and it contributed to generating more electricity. Figure 5 shows the comparison betweenⒸ ISERD

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calculated and observed monthly storage at Nam Ngum 1 reservoir for 2002-2004. The correlation
coefficient between the calculated and observed values is R = 0.65. Calculated storage ranging morethan 3,000 MCM shows relatively good agreement, however, the calculated values are slightly
overestimated when storage became less than 3,000 MCM. Figure 6 shows the annual hydropower
generation with 1 dam case and 4 dam cases. Under the 1 dam case, annual hydropower generation
varied from 857.8 -1077.6 GWh. Under the 4-dam case, annual hydropower generation was increased
by 6.8% due to the flow regulation effect of newly developed dams upstream, however, the incrementin 2004 was only 3.2%. The year 2003 was a drought year so dam storage at the end of rainy season
in 2003 was relatively small. That is why additional release discharge was insufficient to increasehydropower generation in the dry season of 2004. The electricity demand for air conditioners
increases especially during the dry season when the weather becomes very hot, but the amount ofelectricity generated decreases due to a decrease in the flow of rivers. In 2002, 30% of domestic
power consumption was imported, but the import price from Thailand was 10% higher than the priceof electricity exported by the Lao PDR, resulting in a loss of foreign currency earned through exports.
Under the Independent Power Producer (IPP) concession of new dam construction projects, most of
the generated electricity is exported to Thailand. However, in Vientiane city capital of Laos also,
electricity demand increases by around 10% per year, so even a small amount of increment in Nam
Ngum 1 hydropower dam can contribute to reducing the electricity import from Thailand.

Fig. 4 Calculated and observed river discharge at Pakkanhoung station

Fig. 5 Calculated and observed monthly storage at Nam Ngum 1 reservoirⒸ ISERD

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Fig. 6 Estimated annual hydropower generation under 1 Dam and 4 Dam cases
CONCLUSION
In this study, the fully distributed TOPMODEL was developed and applied to analyze the water flowin the Nam Ngum watershed to assess the impact of newly developed dams on downstream river
flow and hydropower generation in the Nam Ngum 1 dam. Simulated river discharge and dam storage
were in good agreement with observed data, and then, we investigated the impact of dam construction
considering NamLik1/2, NamNgum2, and NamNgum5, which were newly developed after 2010. As
a result, new dam constructions have positive effects to decrease flood flow in the rainy season andto increase discharge in the dry season, and electricity generation at the Nam Ngum1 dam also
increased by 6.8%. In this simulation, the same simple reservoir model was used in 1 dam and 4 damcases due to the lack of data, however, normally reservoir operation rule curve became more complex
under multiple dam operations. Therefore, the dam operation model should be improved by using
the actual rule curve and river flow data after 2010.
ACKNOWLEDGEMENTS
This research was supported by JST SICORP Grant Number JPMJSC20E3, and the MEXT/JSPS
Grant-in-Aid for Scientific Research (KAKENHI) no.20KK0346 and no. 23H02324.
REFERENCES
Beven, K.J. and Kirkby, M.J. 1979. A physically based, variable contributing area model of hydrology.
Hydrological Sciences Journal, 24 (1), 43-69, Retrieved from DOI https://doi.org/10.1080/02626667909491834
Hanasaki, N., Kanae, S., Oki, T., and Mushiake, K. 2003. Development of a globally applicable reservoir
operation model. Annual Journal of Hydraulic Engineering, JSCE, 47, 181-186, Retrieved from DOI
tps://doi.org/10.2208/prohe.47.181 (in Japanese)
Kudo, R., Masumoto, T., Horikawa, N. and Yoshida, T. 2013. Assessment of combined impact of climatechange and water resources development on hydrological cycle in the Nam Ngum River Basin.
Transactions of JSIDRE, 81 (1), 57-66, Retrieved from DOI https://doi.org/10.11408/jsidre.80.31 (inJapanese)
Lacombe, G., Douangsavanh, S., Baker, J., Hoanh, C. T., Bartlett, R., Jeuland, M. and Phongpachith, C. 2014.
Are hydropower and irrigation development complements or substitutes, The example of the Nam Ngum
River in the Mekong Basin. Water International, 39 (5), 649-670, Retrieved from DOI https://doi.
org/10.1080/02508060.2014.956205
Moriasi, D.N., Arnold, J.G., Van Liew, M.W., Bingner, R.L., Harmel, R.D. and Veith, T.L. 2007. Modelevaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of
the American Society of Agricultural and Biological Engineers, 50 (3), 885-900, Retrieved from DOI
https://doi. org/10.13031/2013.23153Ⓒ ISERD

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Uematsu, S. 2011. Optimization of reservoir operation for the Nam Ngum 1 hydropower station. Koei Forum,
19, 53-62. (in Japanese)
Vongphet, J., Masumoto,T., Minakawa, H. and Kudo, R. 2014. Application of a DWCM-AgWU model to the
Chao Phraya river basin with large irrigation paddy areas and dams. Applied Hydrology, 26, 11-22,
Retrieved from URL https://cir.nii.ac.jp/crid/1370567180094926336
Yoshida, K., Tanaka, K., Noda, K., Homma, K., Maki, M., Hongo, C., Shirakawa, H. and Oki, K. 2017.
Quantitative evaluation of spatial distribution of nitrogen loading in the Citarum River basin, Indonesia.
Journal of Agricultural Meteorology, 73, 31-44, Retrieved from DOI https://doi.org/10.2480/agrmet.D-1500020Ⓒ ISERD

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Research article
erd

Research article
Verifying Optimum Flying Conditions for UAV
Photogrammetry in Assessing Hydro-structural Facilities

SARVESH MASKEY*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Email: sm207888@nodai.ac.jp

HIYORI ISEKI
Department of Bioproduction and Environment Engineering, Tokyo University of Agriculture,
Tokyo, JapanKISEKI KURASHINA
Graduate School of Agriculture, Tokyo University of Agriculture, Tokyo, JapanKE ZHANG
Graduate School of Agriculture, Tokyo University of Agriculture, Tokyo, Japan

HIROMU OKAZAWA
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Received 9 February 2023

Accepted 25 May 2023(*Corresponding Author)

Abstract Monitoring hydro-structural infrastructure is becoming an important and challenging
issue. In Japan, there are an increasing number of aging hydro-structural facilities, which need
to be inspected to guarantee their strength and durability function. Unmanned Aerial Vehicle(UAV) photogrammetric images have been used in the detection of structural deterioration ofvarious infrastructure. However, there is a challenge in determining the optimum flying
conditions (altitude, angle of camera, and flying patterns) of UAVs for obtaining images. The
designs, shapes, and sizes of hydro-structural facilities also pose a challenge for obtaining ideal
images. In this study, verification of various flying conditions for producing images and 3Dmodels was proposed for water gates and open surface water channels. Additionally, anevaluation method for the images and 3D models was suggested. In this study, UAV was usedfor visual inspection and obtaining the image of the water gate and open surface water channel
at the Tone diversion gate in Saitama, Japan. Various geometric patterns were pasted on thesurface and walls of the structures to evaluate the detection of the patterns with the images
taken from UAVs at different flying conditions. The obtained ortho-mosaic images were
processed by a PIX4D mapper to obtain a point cloud-based 3D model and were comparedwith the actual measurements of the patterns. The results of the study suggested that altitudeand camera angles affected the quality of images significantly. Cameras at lower angles
provided better images, although cameras at high altitudes with wider angles also
demonstrated a high degree of efficiency. The circular flying pattern generated satisfactory
results, where flyovers were conducted multiple times while changing altitudes and angles of
the camera. Additionally, this study proposes a method named “leveling” for the evaluation ofimages and 3D models.
Keywords UAV photogrammetry, hydro-structural assessment, 3D models, level

INTRODUCTION
In Japan, many hydro-structural facilities were constructed during the post-war period and are now
in deteriorating conditions (MAFF, 2022). The Ministry of Agriculture, Forestry and Fisheries has
begun full-scale efforts for 'stock management' to extend the service life of facilities and reduce life
cycle costs to reduce such damage and ensure safe living conditions in the future. Stock managementⒸ ISERD

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consists of continuous facility monitoring, periodic functional diagnosis, deterioration forecasting
based on this, investigation of efficient deterioration countermeasure methods, formulation offunctional maintenance plans, and implementation of appropriate countermeasure works promptly.
Among these, facility monitoring, and functional diagnosis are often time-consuming and laborintensive, such as visual inspection, percussion inspection, and surveying. However, the workforce
and inspection technicians are decreasing due to a decrease in population and aging, resulting in aserious shortage of manpower, (Tabata et al., 2018). Machines and robots are expected to play anactive role in solving these problems. Unmanned Aerial Vehicles (UAVs) can take aerial
photographs by flying at lower altitudes than manned aircraft and other vehicles that have beencommonly used with high-resolution aerial photographs (Miyazaki et al. 2018). Therefore, researchis being conducted to construct 3D models and use them for inspections with the aim of recording
information on deterioration and damage at a higher resolution from the aerial photographs taken(Saito et al., 2022). Previous studies have shown that a 3D model can be produced in detail fromaerial images by flying a UAV at low altitude and taking photographs, however, the sides of abuilding cannot be accurately modeled when the camera angle is directly below the angle of abuilding (Miyazaki et al., 2018). It has also been found that cracks and exposed rebar can be identified
from images taken by UAVs (Tabata et al., 2018). However, there lacks of optimal imaging techniquefor hydro-structural facilities by varying the imaging conditions, such as flight altitude and camera
angle.
OBJECTIVE
The objectives of this study were to verify optimum flying patterns for UAV imaging and 3Dmodeling focusing on camera altitude and angles in hydro-structural facilities assessment.
Additionally, this study tries to develop a method for quantitatively evaluating 3D models.
METHODOLOGY
Description of the Study Site
In this study, a field survey was conducted in two hydro-structural facilities of Tone Water Supply
Works of Japan Water Agency in Gyoda City, Saitama Prefecture, Japan. The water gate and open
surface water channel were the target structures for this study (Fig.1). The width and height of thewater gate were approximately 17.4 m and 7.3 m respectively. Likewise, the width and height of thechannel were 14.4 m, and 2.5 m, respectively.

Fig. 1 Water gate (left) and open surface water channel (right)
Installation of Ground Control Points (GCPs) and Real Time Kinetic Survey
Ground control points (GCPs) were set up around the facility and their positional information wasmeasured. The GCPs were surveyed using the RTK satellite positioning system (Real Time
Kinematic Global Navigation Satellite System). The RTK survey was done to increase the location
accuracy.

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Flight Conditions of UAV Survey
Small rotary-wing UAVs (Inspire 2/DJI and ANAFI/Parrot) were used for aerial photography, with
the Zenmuse X5S (RGB) camera mounted on the Inspire 2 and RGB camera on ANAFI (Fig. 2).
Inspire 2/DJI was used for the water gate, and ANAFI/ Parrot was used for the water channel due toits easy operation for a smaller area. Aerial photography was performed using a flight planningapplication (Pix4D capture/Pix4D, Pix4D scan/Pix4D) installed in UAVs. The UAV was flown indouble grid and circular flight for the water gate and grid (oblique and horizontal) for the water
channel with an overlap of 80% for both the top and side. The flight altitude was set to the lowest
altitude at which it was possible to fly, with the grid/double-grid flight pattern flown at 20 m, and thecircular flight pattern at 20 m, 30 m, and 40 m (Table 1). The camera angle was 45 , 60 and 80 for
all flight paths (Table 2).
Table 1 Flight plan parameters for the Water gate survey
Flight path
Double grid
Circular flight

Flight altitude (m)
20
20
30
40

Flight angle (°)
45, 60, 80
45, 60, 80
45, 60, 80
45, 60, 80

Table 2 Flight plan parameters for open water channel survey
Flight path
Oblique grid
Horizontal grid

Flight altitude (m)2020Flight angle (°)
60
45, 60, 80

Fig. 2 Drones used in this study
Inspire 2 (left) and ANAFI (right)

Dimensional Measurements of the Hydro-structural Facilities
Measurements of facilities were conducted for the target structures. Seven measurements were taken
for sections of the water gate and two measurements were carried for the channels, respectively. A
measuring tape was used for the measurements, and measurements were taken while pulling the tapeat each end to prevent the center from sagging.
Conversion of Aerial Image Data into 3D Models
Pix4D mapper (Pix4D) application was used to create 3D models (point clouds) from aerial images(USDA, 2022). First, aerial images were added to the Pix4D mapper software for initial processing.
In the initial processing, characteristics of geographical features were extracted as key points fromthe images added to the Pix4D mapper. Images with the same key points are then searched for andⒸ ISERD

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matched. The camera's internal and external parameters were corrected. To improve the positional
accuracy of the 3D model and the ortho mosaic image, GCP latitude, longitude, and elevation data
were added and optimized for re-estimation with respect to camera positioning information andimage distortion. Finally, point clouds were densified based on automatic tie points and comparedand evaluated from the resulting 3D models.
Evaluation of the Model
Reproducibility of 3d Models with the Actual Image
The reproducibility of the target structures in the 3D models (point clouds) created from different
flying conditions was checked. The point cloud data were compared with the aerial images to assessthe differences. The dimensions of the 3D model were measured by creating polylines in Pix4D
mapper. The polylines were created in such a way that they were close to the positions measured
during the survey; three polylines were created at one measurement site, the mean error and standard
deviation from the actual measurement were calculated, and the values were compared for eachflying condition.
Leveling of 3d Models and Actual Images
An evaluation method unique to this study was developed where three types of patterns (triangle,
circle, and square) were classified into levels from 1 to 5 (Fig. 3). The points and levels were set sothat the smaller the side length of the pattern (shown in fig. 3 by yellow line) higher the point andlevel. For the triangular pattern, point 1 was given for level 1 where the side length was 20 cm,
likewise, points and levels were assigned for each length and pattern. Additionally, the level was set
to 0 if the figure was not visible in the 3D data. These patterns were pasted on the surface of thetarget structures and aerial images were taken. Verification for actual images and 3D models was
performed with points allotted for each level. The aerial imaging conditions were evaluated bycomparing the average of the points. Furthermore, multiple regression analysis was performed toassess the influence of altitude and camera angle on the levels.
Level 1 (1 point ) : 20 cm

Level 1 (1 point ) : 10 cm

Level 1 (1 point ) : 10 cm

Level 2 (2 point) : 10 cm

Level 2 (2 point) : 6.0 cm

Level 2 (2 point) : 4.5 cm

Level 3 (3 point) : 5.0 cm

Level 3 (3 point) : 4.5 cm

Level 3 (3 point) : 3.0 cm

Level 4 (4 point) : 2.5 cm

Level 4 (4 point) : 2.5 cm

Level 4 (4 point) : 1.5 cm

Level 5 (5 point) : 1.3 cm

Level 5 (5 point) : 1.5 cm

Level 5 (5 point) : 0.7 cm

Fig. 3 Geometric patterns with dimensions and allocated points for the level
RESULTS AND DISCUSSION
Reproducibility Evaluation of 3D Models (Point Clouds)
A 3D model was created by combining aerial images obtained under various flight conditions toverify the differences and the dimensional error compared to the measured facility. The results
showed that for the double grid flight pattern, the camera angle affected the results (Fig. 3, left image).
The reproducibility was high for 45° followed by 60° angles for the pillar sections of the gate. Similar
results were obtained for circular flight patterns, where reproducibility was high for 45° followed by
60° angles (Fig. 4, right image). On the other hand, when the camera angle was at an angle of 80°,
the reproducibility increased with altitude for the upper part of the water gate indicating thatmodeling depended on the flight altitude (Fig. 5, left image). Furthermore, there was no difference
in recognizing the pattern pasted insides of the open channel for all flight conditions, however, at a
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camera angle of 80°, reproducibility was lower (Fig. 5, right image). In addition, a comparison of thedimensions of the facility measured and the dimensions of the 3D model showed that the errors were
within 10 cm for all flight methods (Table 3, Table 4, Table 5 and Table 6).

Fig. 4 3D point cloud model created from aerial images of water gate
Grid flight pattern (left) and circular flight pattern (right) at varying camera angles
at an altitude of 20 m

Fig. 5 3D point cloud model created from aerial images of a circular flight patternover a flow control
Weir at different altitudes at a camera angle of 80 ° (left image), 3D points cloud model created from aerial
images of a grid flight over an open channel at an altitude of 20 m with varying camera angles (right image)Evaluation of Level
The result of the level is shown in Tables 3 to 6. In the case of the double grid flying pattern, when
the UAV flying altitude was fixed and the camera angle varied, the level became lower as the camera
angle was moved closer to the nadir, indicating that the camera angle had a significant effect onleveling. In addition, it was understood that too many photographs are not good for the leveling, since
the level of the result of the analysis of the three patterns together was not the highest. In circularflight, the higher the flight altitude, the lower the level, indicating that the altitude of the flight also
has a significant effect.
Table 3 Level and dimensional error assessment during double grid flight over water gate
Level evaluation
Aerial image
3D modelMeasurement error (cm)Avg. error
Std. deviation

Altitude(m)Angle ( )No. of
pics

20

45

440

3.12

1.28

2.41

±3.51

20

60

314

2.81

1.20

1.67

±2.57

20

80

747

2.79

0.93

1.77

±2.38

1501

2.97

0.84

1.35

±1.85

Total

Furthermore, from the result of levels at each altitude when the camera angle was 80 °, it was
found that it was necessary to take photographs while keeping the camera angle close to the nadir.
The results of the multiple regression analysis of altitude and angle effect on the image and modellevels for the double grid and circular flight are shown in Tables 7 and 8. According to the analysis,Ⓒ ISERD

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the influence of altitude is high at both the image levels and model levels. Furthermore, at the modellevel, the angle was also found to influence the level, although not to a large scale.
Table 4 Level and dimensional error assessment of circular flights over water gate
Altitude (m)Angle ( )No. of
pics

20
20
20
30
30
30
40
40
40

45
60
80
45
60
80
45
60
80

75
78
80
78
81
80
76
78
78

Level evaluation
3D
Aerial image
model
2.65
0.90
2.60
0.98
1.66
0.56
1.88
0.90
1.99
0.79
1.87
0.67
1.39
0.68
1.36
0.67
1.28
0.74

Measurement error (cm)Avg. error

Std. deviation

2.05
1.82
1.60
3.51
2.48
2.22
2.77
3.50
1.98

±3.01
±2.24
±3.63
±4.71
±3.69
±3.14
±3.54
±4.53
±2.77

Table 5 Level and dimensional error assessment for each combined circularly flown aerial
image of water gate
Combination flight pattern
Circular
Circularflightflight
20 m 45
30 m 60
20 m 45
30 m 80
20 m 45
40 m 60
20 m 45
40 m 80
20 m 60
30 m 80
20 m 60
40 m 80
30 m 45
40 m 60
30 m 45
40 m 80
30 m 60
40 m 80
20 m 45 + 30 m 60 +40 m 80
Total

No. of
pics
156
155
153
153
158
156
156
156
159

Level evaluation
3D
Aerial image
Model
2.70
1.28
2.77
1.30
2.83
1.24
2.77
1.18
2.79
1.26
2.74
1.24
2.07
0.90
2.04
0.93
2.29
0.89

Measurement error (cm)Avg. error

Std. deviation

1.94
1.44
1.73
1.20
1.63
1.65
1.37
2.44
1.53

±2.59
±2.18
±2.25
±2.07
±2.21
±2.61
±1.76
±2.85
±1.88

234

2.79

1.21

1.87

±2.86

704

2.64

0.98

1.70

±2.10

Table 6 Level and dimensional error assessment during grid flying overan open water channel
Direction
Oblique 1
Oblique 2
Oblique
1and 2
Horizontal
Horizontal
Horizontal

Level evaluation
Aerial image
3D model
3.08
2.00
3.03
1.96

Measurement error (cm)Avg. error
Std. deviation
2.33
±2.94
3.17
±1.17

Altitude
(m）

Angle
(°)

No. of
image

20
20

60
60

258
240

20

60

498

3.05

2.06

2.00

±1.26

20
20
20

45
60
80

158
330
126

2.68
3.18
2.37

1.23
1.82
1.18

4.33
4.83
3.00

±3.50
±5.32
±5.40

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Table 7 Multiple regression analysis of level (Images)
Altitude
Camera angle

Coefficient-0.0636-0.0105

Std. deviation
0.01150.0067t-5.5186-1.5765

p-value***t-2.4277-1.8443p-value***p < 0.01 *** p < 0.05 ** p < 0.1 *Table 8 Multiple regression analysis of level (3D model)
Altitude
Camera angle

Coefficient-0.0144-0.0063

Std. deviation
0.00590.0034p < 0.01 *** p < 0.05 ** p < 0.1 *CONCLUSION
In this study, the optimum UAV flying conditions for UAV imaging were investigated for water gate
and open surface channels. The aerial imaging conditions were compared using three methods:
reproducibility of the 3D model, comparison of the measured dimensions of the facility and thedimensions of the 3D model, and an original evaluation method called 'leveling', to investigate themost suitable flight pattern. According to the results of this study, the following conclusions were
made: (i) Images obtained by circular flight patterns with various combinations were effective forthe water gate. (ii) For open surface water channels, the camera angle should not be close to the nadir.
(iii) For quantitively assessing aerial imaging, figure leveling is useful. (iv) For planning UAV
imaging assessment of hydro-structural facilities, the altitude of the UAV should be set followed by
the angle of the camera. However, the results of this study showed deficiencies in modeling the upper
part of the columns and shadowy areas, and the upper part of the columns from aerial images. In the
future, it is desirable to analyze images taken from the ground to compensate for areas such as thetops of columns, which are difficult to take images by automatic UAV flight. In addition, as hydrostructural facilities are in different shapes and sizes, it is necessary to conduct more similar studies.
ACKNOWLEDGEMENT
The authors like to acknowledge Tone Water Supply Works of Japan Water Agency for assistingand providing guidance for the survey.
REFERENCES
Ministry of Agriculture Forestry and Fisheries. 2022. Stack management of agricultural irrigation facilities.
Ministry of Agriculture Forestry and Fisheries, Japan, Retrieved from URL https://www.maff.go.jp/j/nousin/mizu/sutomane/attach/pdf/220202-1.pdf
Miyazaki, S., Yamazaki, F. and Liu, W. 2018. Development of a 3D model of the landslide based on drone
flights after the northern Kyushu heavy rainfall. Proceedings of the Symposium on Disaster Mitigation andResilience of the Infrastructures and Lifeline Systems, 8, 49-52, Retrieved from DOI https://doi.org/10.1109/IGARSS. 2018.8517376.
Saito, S., Fujiu, M. and Hukuoka, T. 2022. Proposal of remote inspection method for labor-saving of bridge
inspection through adaptations of AI and VR technology to real bridges. Infrastructure Maintenance
Practices, 1 (1), 372-377, Retrieved from DOI https://doi.org/10.11532/jsceim.1.1_372
Tabata, Y., Ji, D., Dajiro, H., Shrestha, A. and Pang-Jo, C. 2018. Unmanned inspection-oriented UAV bridge
inspection and damage detection using deep learning. Journal of Japan Society of Civil Engineers, 74 (2),62-74, Retrieved from DOI https://doi.org/10.2208/jscejcm.74.I_62
United States Department of Agriculture. 2022. Pix4Dmapper exercise 1: Image processing for UAS imagery,
Retrieved from URL https://fsapps.nwcg.gov/gtac/CourseDownloads/Training/Remote_Sensing/Pix4D/01_Documents/Final_Pix4Dmapper_ex1.pdfⒸ ISERD

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Research article
erdInformation Transfer among Mango Contractors:
Sources, Channels, and Priorities
DIA NOELLE VELASCO*
Graduate School of International Food and Agricultural Studies,Tokyo University of Agriculture, Tokyo, Japan
Email: 13821001@nodai.ac.jp

KATSUMORI HATANAKA
Faculty of International Agriculture and Food Studies,Tokyo University of Agriculture, Tokyo, Japan

NINA SHIMOGUCHI
Faculty of International Agriculture and Food Studies,Tokyo University of Agriculture, Tokyo, Japan

RAMADHONA SAVILLE
Faculty of International Agriculture and Food Studies,Tokyo University of Agriculture, Tokyo, Japan
Received 15 January 2023

Accepted 25 May 2023(*Corresponding Author)

Abstract Information transfer is vital in improving knowledge and proper technology
implementation, especially in agriculture. This paper aimed to describe the information systemamong the Pangasinan mango contractors. Specifically, it aimed to 1) identify the sources of
information for the mango contractors, 2) determine information channels for informationtransfer, 3) establish the type of information that mango contractors prioritize, 4) determine
the challenges and issues in the transfer of information, and 5) recommend interventions toimprove information transfer among mango contractors. The study area is Pangasinan,
Philippines, the country's top mango-producing province. The research used a purposive
sampling of 55 mango contractors covering six mango-producing municipalities. Descriptive
statistics and correspondence analyses were employed in the study. Results showed that mostmango contractors generally receive information on the production and marketing of mangoes
from farm technicians and buyers. They usually get information on production technologies
from farm technicians and other mango contractors. Expectedly, they get their information on
mango marketing from their buyers. On the other hand, information transfer usually happens
through mobile phones and during farmers' meetings. Furthermore, contractors prefer to get
information on the buying price of mangoes, followed by the quality requirements of buyers.
Contractors also choose to have a face-to-face conversation when obtaining information. The
next preference is through text and calls using mobile phones. In summary, mango contractors
still prefer the traditional information system through face-to-face conversations, text, andmobile phone calls. This has implications for the implementation of modern technologies used
for information dissemination. Mango contractors might not be receptive to new ways ofreceiving communication, even if the information might be urgent or essential. It is
recommended that contractors be trained to use modern communication technologies to makethem more receptive to other communication channels.
Keywords information transfer, correspondence analysis, mango contractors,
communications

INTRODUCTIONⒸ ISERD

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Communication within the commodity system is an invaluable component that is often overlooked.
Most of the time, people focus much on production technologies or market development. However,new developments in production technologies and discovering new market opportunities will notmatter if this information is not adequately communicated along the value chain. Players in the chain
cannot act on the latest developments if they do not know there are new developments. For example,
Indian agriculture is plagued by insufficiency and inefficiencies in conveying pertinent information
to the farming industry, not a lack of technology or R and D activities. While Indian agriculture hasflourishing technologies that can help their farmers, they can still improve the communication ofsuch technologies to the farmers. This disconnect can be the key to further development of theiragricultural sector. Therefore, developing agriculture's information and communication technology(ICT) can catalyze the sector's growth (Behera et al., 2015).
Agricultural information is an essential element that interacts with other production factors likeland, labor, capital, and management competence. The availability of pertinent, trustworthy, andbeneficial knowledge and information can arguably increase the productivity of these othercomponents. To enable farmers to make better decisions, take advantage of market possibilities, andmanage ongoing changes in their production systems, agricultural organizations have handled theinformation supplied by extension, research, education, and others (DEMİrYÜrEK, 2010).
Vidanapathirana (2012) cited Maningas et al. (2000) and found that having information in the handsof farmers leads to their empowerment by giving them control over their resources and decisionmaking procedures. They pointed out that a system for delivering vital information and technologicalservices effectively and efficiently aids the clients' crucial role in decision-making for better
agricultural production, processing, trading, and marketing. Therefore, to manage and enhance
specific agricultural information systems, it is necessary to understand how they work.
Attention should be given to the provision of education and training on the implementation of
joint technologies and their combined impact on farms since it was discovered that education andinformation availability were among the factors influencing the adoption of multiple technologies(Toma et al., 2018). Proper channels for information transfer also play a critical role in technology
transfer. Farmers can learn about agricultural topics from various sources, including extension
services, the media, other farmers, input suppliers, etc. (Adhiguru et al., 2009). Thus, looking at thedetails surrounding the information system within a value chain is imperative. Likewise, Sugiarti etal. designed an e-commerce information system for mango in 2019. However, the one that they built
was just for one enterprise. The authors conducted meetings directed toward the store's owners andrepresentatives. The prepared documentation became the basis of the design of the e-commerce
information system. On the other hand, Vanany et al. (2016) developed an electronic traceability
system for mango in Indonesia. The abovementioned research tackled one case study with one supply
chain network. They mentioned the difficulty in delivering accurate information in Indonesia
regarding traceability. They recognize the importance of quality information primarily for the global
market. These pieces of literature mainly focus on the role of ICT, not just in the mango industry andthe agriculture sector in different countries. It shows the importance of holds and catalyzes anindustry's growth. It also emphasizes how crucial the transfer of information is for the sector.
Table 1 Historical performance of mango (2000-2020)
Year
20002009
20102020
20162020

Production
MetricGrowthton (Mt)
rate (%)

Area
HectareGrowthrate (%)

925,247-0.70

163,106

3.90

5.70

-4.50

793,296-0.93

187,530

-0.14

4.20

-0.80

86.10

-2.10

747,987-2.30

186,630

-0.14

4.00

-0.94

78.40

-2.20

Source: DA, 2022

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Yield / unit area
In Mt/haGrowthrate (%)

Yield / tree
kg/tree
Growthrate (%)
No data
No dataavailable
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On the other hand, the Philippine mango industry's performance has declined these past few
years for several reasons. One of the primary reasons is the pest infestation from Cecid flies and Fruitflies. Other problems beset the industry include the following: 1) high cost of inputs/production cost;2) improper farm practices/excessive use of chemicals; 3) lack of economies of scale; 4) productionseasonality; 5) unproductive mango trees; 6) prevalence of infestation and diseases; 7) limited accessto information and technologies; 8) high post-harvest losses; 9) inadequate/limited post-harvest andprocessing facilities; 10) limited access to resources and direct market, 11) unstable supply and prices,12) multi-layer marketing, and 13) difficulty in accessing export markets (DA, 2022). For the past
two decades, mango production has been going down for the following parameters: production, areaof production, productivity per area, and productivity per tree. These pieces of information can befound in Table 1.
Despite these challenges, mango remains to be the third most highly exported fruit crop in 2020,
with a PhP 35.520B ($716.019M) contribution to GVA in agriculture (Department of Agriculture(DA), 2022). This shows that mango is still one of the top-priority commodities in the country.
Furthermore, this commodity system should be studied further to help improve its economic
performance.
This study builds on the existing literature and analyzes the transfer of information among themango contractors in the study area. It delves into the sources of information and channels of
information transfer as well as the priorities of mango contractors regarding the information theyneed and the mode of information transfer.
OBJECTIVE
This paper aimed to describe the information system among the Pangasinan mango contractors.
Specifically, it aimed to 1) identify the sources of information for the mango contractors, 2) determine
information channels for information transfer, 3) establish the type of information that mango
contractors prioritize, 4) determine the challenges and issues in the transfer of information, and 5)
recommend interventions to improve information transfer among mango contractors.
METHODOLOGY
The study area for the research is Pangasinan since it is the top mango-producing province in the
country, contributing about 29% of the total production in 2020 (DA, 2022). It is also strategicallylocated since its climatic conditions and soil types are ideal for mango production (dela Cruz, 2007).
Furthermore, it has developed road networks that make it accessible to processors and exporters in
Metro Manila.
The primary data were collected through key informant interviews and surveys on the players.
Key informants such as employees from the Office of the Provincial Agriculturist of Pangasinan,mango experts from the academe, and other mango players from other provinces were interviewed
during the research. This provided a different perspective outside of the Pangasinan mango industry.
On the other hand, structured questionnaires were employed for the survey on the mango players,which includes sections for the demographic profile, farm profile, production and marketing
practices, sources and type of information, and channels of the information channel. The researchalso used purposive sampling on 55 mango contractors covering six mango-producing municipalities
ranging from small to large-scale operators. Unfortunately, there is no list of mango contractors since
they are considered transient players in the industry. Some mango contractors do not regularly
operate annually, especially if they do not have enough capital to finance their operations. As a result,
the researchers had to interview known mango contractors in the area and get recommendations fromthese contractors on who could be interviewed.
Secondary data were collected from online journals and online portals of the DA. Descriptive
statistics and correspondence analyses were also employed in the study. This determines theassociation between and among the variables, such as sources, types, and information channels.
XLSTAT was used to run the correspondence analysis for this research.
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RESULTS AND DISCUSSION
Most mango contractors live in San Carlos City (50.91%) and Malasiqui (30.91%) since most of themangoes come from these municipalities. On average, mango contractors who were interviewed
were aged 49.48 years. The oldest who was interviewed was aged 69, while the youngest was 29
years old. On the other hand, the interviewed mango contractors are highly educated, with about
41.82% being college graduates and approximately 29.09% being high school graduates.
In terms of farming (generally), these contractors have been farming for an average of 23.18
years. However, some of them just shifted from general agriculture to mango farming specifically.
On average, they have been mango farming for about 19.64 years. Approximately 38.18% (21contractors) operate at a medium-scale (500-3,000 fruit-bearing trees or FBTs), while 32.73 (18contractors) operate at a small-scale (less than 500 FBTs) and about 29.09% (16 contractors) operate
at a large-scale (more than 3,000 FBTs).
Sources of Information
The results (Fig. 1) showed that most mango contractors generally receive information on the
production and marketing of mangoes from farm technicians and buyers. They usually get
information on production technologies from farm technicians and other mango contractors.
Expectedly, they get their market information (price, volume, and quality specifications) from theirbuyers. As the computed p-value is lower than the significance level alpha=0.05, there is a link
between the type of information that mango contractors and sources of information as shown in Table
2. Logically, farm technicians and other mango contractors provide production technology
information. With an Eigenvalue of 100%, it can be said that the quality of the analysis is very high(shown in Table 3).

Fig. 1 Graphical representation on sources of information
Table 2 Test of independence between type of information and sources of information
Chi-square (observed value)
Chi-square (critical value)DF
p-valuealpha174.11621.026
12< 0.0001
0.05

Table 3 Eigenvalues and percentages of inertia
Eigenvalue
Inertia (%)
Cumulative %

F1
0.970
75.20775.207F2
0.320
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Information Channels
On the other hand, information transfer usually happens through mobile phones and during farmers'
meetings (Fig. 2). Farm technicians generally hold round table discussions with contractors to show
them new technologies for better mango production. On the other hand, They usually get their market
information from their buyers through their mobile phones. As the computed p-value is lower than
the significance level alpha=0.05, there is a link between the sources of information that mango
contractors get and the information channel as shown in Table 4. Thus, these mango contractors
getting their production technology information during farmers' meetings provided by farmtechnicians is logical. Also, since the buyers are primarily located in Manila, it would be logical forthem just to use mobile phones in their transactions. With an Eigenvalue of 100%, it can be said thatthe quality of the analysis is very high (shown in Table 5).

Fig. 2 Graphical representation on information channels
Table 4 Test of Independence between sources of information and information channel
Chi-square (observed value)
Chi-square (critical value)DF
p-valuealpha54.4160
9.48804.0000< 0.0001
0.0500

Table 5 Eigenvalues and percentages of inertia
Eigenvalue
Inertia (%)
Cumulative %

F1
0.370
76.16676.166F2
0.116
23.834100.000

Priority Information
Based on the results (Fig. 3), mango contractors prioritize getting market information like price,
demand quality, and demand volume, ranked 1, 2, and 3, respectively. It is followed by production
processing and packaging technologies, ranked 4, 5, and 6, respectively. As the computed p-value islower than the significance level alpha=0.05, there is a link between the rank and the type of
information (shown in Table 6). Earning good money is crucial to mango contractors since theirproduction has been low these past few years. Thus, the ranking that mango contractors gave themarket information is logical. With an Eigenvalue of 87.24%, it can be said that the quality of theanalysis is high as shown in Table 7.

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Fig. 3 Graphical representation on priority information
Table 6 Test of Independence between ranking and priority information
Chi-square (Observed value)
Chi-square (Critical value)DF
p-valuealpha298.3640
37.652025.0000<0.00010.0500

Table 7 Eigenvalues and percentages of inertia
Eigenvalue
Inertia (%)
Cumulative %

F1
0.489
54.04154.041

F2
0.300
33.19487.235F3
0.099
10.89898.133

F4
0.016
1.776
99.909

F5
0.001
0.091
100.000

Fig. 4 Graphical representation on priority information channel
Priority Information Channel
Contractors also choose to converse face-to-face when obtaining information (Fig. 4). The next
preference is through text and calls using mobile phones. As the computed p-value is lower than thesignificance level alpha=0.05, there is a link between the rank and the type of information channelⒸ ISERD

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(shown in Table 8). Mango contractors are pretty old-fashioned when it comes to communication.
They prefer more traditional tracks of information transfer. Furthermore, farmers' meeting is also an
excellent venue to socialize and catch up among the mango contractors since most are friends andrelatives. They do not prefer using the internet or applications since they do not have Android or
smartphones and are reluctant to learn to use these gadgets. With an Eigenvalue of 87.42%, it can besaid that the quality of the analysis is high as shown in Table 9.
Table 8 Test of independence between ranking and priority information channel
Chi-square (Observed value)
Chi-square (Critical value)DF
p-valuealpha248.000
26.2960
16.0000< 0.0001
0.0500

Table 9 Eigenvalues and percentages of inertia
Eigenvalue
Inertia (%)
Cumulative %

F1
0.679
75.30175.301

F2
0.109
12.11987.420F3
0.101
11.23798.657

F4
0.012
1.343
100.000

CONCLUSION
In summary, most mango contractors generally receive information on the production and marketingof mangoes from farm technicians and buyers. Furthermore, information transfer usually happens
through mobile phones and during farmers' meetings. Moreover, contractors prefer to get informationon the buying price of mangoes, followed by the quality requirements of buyers. Mango contractors
also prioritize getting market information like price, demand quality, and volume. Contractors alsochoose to have a face-to-face conversation when obtaining information, followed by text and mobile
phone calls. Mango contractors currently get information through traditional means since they valuesocial interaction with their colleagues in the industry. Even with the aid of technology, thecontractors also appreciate personal touches like having conversations through calls and texts.
Furthermore, most mango contractors still prefer the more traditional information systemthrough face-to-face conversations, text, and mobile phone calls. This has implications for the
implementation of modern technologies used for information dissemination. Mango contractors
might not be receptive to new ways of receiving communication. However, it seems like social
networks are essential to these contractors. It is recommended that contractors be trained to use
modern communication technologies to make them more receptive to other communication channels.
REFERENCES
Adhiguru, P., Birthal, P.S. and Kumar, B.G. 2009. Strengthening pluralistic agricultural information delivery
systems in India. Agricultural Economics Research Review, 22 (1), 71-80, Retrieved from DOI
https://doi.org/10. 22004/ag.econ.57382
Behera, B.S., Panda, B., Behera, R.A., Nayak, N., Behera, A.C. and Jena, S. 2015. Information communication
technology promoting retail marketing in agriculture sector in India as a study. Procedia Computer Science,
48, 652-659, Retrieved from DOI https://doi.org/10.1016/j.procs.2015.04.148
dela Cruz, A.A. 2007. Contractual arrangements in agriculture (Northern and Central Luzon Component).
Philippine Institute for Development Studies, Discussion Paper Series No. 2007-21.
Demiryürek, K. 2010. Information systems and communication networks for agriculture and rural
people. Agricultural Economics 56 (5), 209-214, Retrieved from DOI https://doi.org/10.17221/1/2010AGRICECON
Department of Agriculture. 2022. Philippine Mango Industry Roadmap 2021-2025, Retrieved from URL
https://www.da.gov.ph/wp-content/uploads/2023/05/Philippine-Mango-Industry-Roadmap.pdf
Sugiarti, Y., Tjachja, A., Maman, U., Mintarsih, F., Anwas, E.O.M., Syarifah, E. and Hidayatullah, S. 2019.
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Design and build mango e-commerce information system. The 7th International Conference on Cyber and
IT Service Management (CITSM 2019), 1-4, Retrieved from DOI https://doi.org/10.1109/CITSM47753.
2019.8965402
Toma, L., Barnes, A.P., Sutherland, LA. et al. 2018. Impact of information transfer on farmers' uptake ofinnovative crop technologies: A structural equation model applied to survey data. The Journal ofTechnology Transfer, 43, 864-881, Retrieved from DOI https://doi.org/10.1007/s10961-016-9520-5
Vanany, I., Mardiyanto, R., Ijtihadie, R.M., Andri, K.B. and Engelseth, P. 2016. Developing electronic mango
traceability in Indonesia. Supply Chain Forum: An International Journal, 17 (1), 26-38, Retrieved from
DOI https://doi.org/10.1080/16258312.2016.1143206
Vidanapathirana, N.P. 2012. Agricultural information systems and their applications for agriculture and ruralcommunity development, A review study. In The 35th Information Systems Research Seminar in
Scandinavia–IRIS, 1, 1-14, Retrieved from URL https://www.researchgate.net/profile/NisansalaVidanapthirana/publication/336252494_Agricultural_information_systems_and_their_applications_for_development_of_agriculture_and_rural_community_a_review_study/links/5d96f2de299bf1c363f5a008/A
gricultural-information-systems-and-their-applications-for-development-of-agriculture-and-ruralcommunity-a-review-study.pdfⒸ ISERD

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Research article
erd

Effect of Bio-slurry and Chemical Fertilizer on Soil Enzyme
Activity
MOEURB ANG*
Faculty of Agricultural Engineering and Agronomy, Royal University of Agriculture,
Phnom Penh, Cambodia
Email: moeurb.ang@gmail.com

HONG CHEANG
Faculty of Agronomy, Royal University of Agriculture, Phnom Penh, Cambodia

DYNA THENG
Faculty of Agricultural Engineering, Royal University of Agriculture, Phnom Penh, Cambodia

NARETH NUT
Faculty of Agricultural Engineering, Royal University of Agriculture, Phnom Penh, Cambodia

LYHOUR HIN
Biogas Technology and Information Center and Faculty of Agricultural Engineering,
Royal University of Agriculture, Phnom Penh, Cambodia

LYTOUR LOR
Biogas Technology and Information Center and Faculty of Agricultural Engineering,
Royal University of Agriculture, Phnom Penh, Cambodia

KASUNI H. H. GAMAGE
Department of Agronomy, Kansas State University, Manhattan, Kansas, U.S.A

GANGA M. HETTIARACHCHI
Department of Agronomy, Kansas State University, Manhattan, Kansas, U.S.A
Received 22 April 2023

Accepted 30 May 2023(*Corresponding Author)

Abstract Organic nutrient sources are an effective way to improve soil fertility and increase
crop yield. Bio-slurry provides tremendous nutrient potential for the vegetative andreproductive growth of field crops and its long-term sustainability. Application of the bioslurry on the field can help to reduce fertilizer use, maintain productivity, and improve soil
health. Soil enzyme activity was enhanced by swine slurry. Enzyme activity following
fertilization takes precedence over microbial biomass in the short term. The study aimed (1)to study the effect of bio-slurry and chemical fertilizer on soil enzymes activity, and (2) tocompare the biomass growth of corn using bio-slurry and chemical fertilizer. The research was
conducted from November to December 2022 at the Throckmorton Plant Sciences Center,
Department of Agronomy, Kansas State University, United States. The experiment was
conducted in pots under greenhouse conditions with 5 treatments, including Treatment 1:
Control (without fertilizer), Treatment 2: bio-slurry, Treatment 3: urea, Treatment 4: NH4NO3
and Treatment 5: KNO3+NaNO3. Each treatment was conducted in 3 replications with 1 pot
per replication and 2 seeds per pot. The activities of soil enzymes, biomass of corn above
ground and root were collected and analyzed. Corn plants treated with bio-slurry and inorganic
fertilizer were found to have a non-significant growth of corn soil β-glucosidase enzyme with
4.41 mg/L, 3.83 mg/L, 4.23 mg/L, 4.11 mg/L, and 4.14 mg/L, respectively. With regard toaboveground and belowground biomass, no significant differences between the control andother treatments were observed. The results showed that bio-slurry released low amounts ofenzyme activity to the soil and provided good growth conditions to corn.
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Keywords crop, corn, slurry, soil fertility, soil health

INTRODUCTION
Corn (Zea mays L.) is the most vital cereal worldwide (Ka et al., 2022). USA, China, and Brazil contribute
63% of the global corn production while Mexico, Argentina, India, Ukraine, Indonesia, France, Canada
and South Africa are also major corn-producing countries (FAO, 2010). In Cambodia, commercial pig
farms have increased due to their ability to control the environment necessary for fast pig growth andeffective disease prevention (MAFF, 2019). Daily wastewater generated from the pig farm depends on
the type of pigs such as sows, fatteners, and piglets at 64 m3/head, 24 m3/head, and 20 m3/head,respectively (Kulpredarat, 2016).
Bio-slurry is a by-product of anaerobic digestion. The bio-slurry contains 93% water and 7%
dry matter, of which 4.5% is organic matter and 2.5% inorganic matter, easily available plant
nutrients, and high amount of nutrients and micronutrients. Total nitrogen, total phosphorus, andpotassium were 2.1%, 1.1%, and 0.98% and micronutrients like Fe, Cu, Mn, and Zn were 0.34 ppm,
0.004 ppm, 0.088 ppm, and 0.023 ppm respectively. It's can be used as fertilizer directly or addedwith other organic materials on crops. (Kumar et al., 2015).
Soil enzymes are produced by animal manure, plants, and microorganisms. They areprominently secreted by microbes and stimulate microbial activity in this biome (Chernysheva et al.,2021). Soil microorganisms mainly synthesize extracellular enzymes such as β-glucosidase,hydrolases urease, phosphatase, glycosylating enzymes, and many more. Soil enzymes play a vitalrole in the biodegradation of organic compounds in soil and become the most delicate indicator ofchange in microbial activities that occur in the soil environment (Hueso et al., 2012).

OBJECTIVE
The objectives of the study were to determine study the effect of bio-slurry and chemical fertilizer
on soil enzyme activities and to compare the biomass growth of corn using bio-slurry and chemicalfertilizer.
METHODOLOGY
The experiment was conducted at Throckmorton Plant Sciences Center, Faculty of Agronomy,
Kansas State University, The United States (39°11'37.3"N 96°35'04.2"W), during the autumn from
November to December 2022. DKC59-82RIB corn variety was used and planted in pots ingreenhouse condition. The experimental plots were followed a completely randomized design (CRD)with five treatments and 3 replications. The treatments were T1 (control), T2 (bio-slurry), T3 (urea),
T4 (NH4NO3), and T5 (KNO3+NaNO3). Recommended doses of fertilizer applied for corn were 190,
30, and 100 kg/ha for N, P, and K, respectively. The soil was watered before planting the seeds,
following maximum water holding capacity (MWHC) equivalent to 1 liter of water per pot.
The bio-slurry was collected from the College of Civil Engineering, at KSU, and used swine
manure as substrate. Four samples, each about 1 kg of bio-slurry, were taken for nutrient content
analysis. The samples contained 957.72 mg/L TN, 43.71 mg/L TP, 598.74 mg/L TP, 120.50 mg/L,
22.68 mg/L Mg, 12.13 mg/L S, and micronutrients (0.10 mg/L Al, 0.37 mg/L Fe, and 152.49 mg/L
Na) (Kansas State Soil Testing Lab., 2022)
Soil samples were taken from two locations in each pot at the depth of 0-5 cm at 3 weeks after
planted and transported back to the laboratory in plastic trays. For enzymatic analysis, 1-g of the wet
soil was mixed with 1 mL of p-Nitrophenyl-β-D-glucosidase (PNG) solution, 4 mL MUB at pH 6.0-,
and 0.25-mL toluene. The solution was hand-shaken slowly a few seconds, capped, and then placedin the incubator for 1 hour at 37 0C. Afterwards, the sample was withdrawn, cooled down at the room
temperature, and then added with 1 mL of 0.5M CaCL2 and 4 mL of 0.1M THAM buffer pH 12. Thissecond mixture was hand-shaken for another few seconds and then poured into a beaker through apaper filter Watman No. 2. Before the prepared soil solution was tested in the spectrophotometer,Ⓒ ISERD

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this equipment had to be first tested with six levels of pre-prepared solutions to verify its accuracy.
Those solutions contained p-nitrophenol diluted solutions of 0, 1, 2, 3, 4, and 5 mL; six levels ofwater in reverse order from 5 to 0 mL; each 1 mL of CaCl2; and each 4 mL of THAM pH 12. Afterthe accuracy was verified, the soil samples were then analyzed using this equipment. (Eivazi and
Tabatabai, 1978). Values were corrected for a blank (Substrate added immediately after the additionof CaCL2 and Tris NaOH) and for adsorption of released para-nitrophenol 𝜌𝑁𝑃 in the soil (Vuorinen,1993). β-glucosidase activity is expressed as 𝜇𝑚𝑜𝑙 𝜌𝑁𝑃 𝑟𝑒𝑙𝑒𝑎𝑠𝑒𝑑 𝑔−1 dry soil ℎ−1.
Each soil was air-dried 24 hours. Afterwards, the dried soil was ground and sieved to obtain soil
particles of less than 2 mm for soil pH, soil moisture content, and plant nutrients analysis. Soil pH
was determined using ORION Star A11 Bench top pH meter with a soil-water ratio of 1:10 (Bruce
et al., 1982). Soil moisture content was calculated by subtracting the weight of the dry soil, ovendried at 105 0C for 48 hours until it reached a constant weight.
Two kinds of corn biomass were measured four weeks after planting. Aboveground biomass
was collected by cutting all corn stems in each pot from the stem base, then oven-dried at 60 0C for
72 hours and weighed. Underground biomass was collected by separating the soil clods and brushing
the roots gently before soaked in distilled water to ensure that all soil was removed. Then, clean roots
were oven-dried at 60 0C for 72 hours and weighed.
RESULTS AND DISCUSSION
Soil Enzyme (β-glucosidase)In terms of β-glucosidase activity, there were no significant differences among the treatments (Table
1). On the other hand, the mean concertation of β-glucosidase in soil was found to decrease among
grand mean of 4.13 𝜇𝑚𝑜𝑙 𝜌𝑁𝑃 (Table 1)
Table 1 Effect of different fertilizer on Soil enzyme activity
Mean (𝜇𝑚𝑜𝑙 𝜌𝑁𝑃)
4.33
3.83
4.23
4.11
4.14
4.13
0.08
0.69

Treatments
Control
Bio-slurry
Urea
NH4NO3
KNO3+NaNO3Grand meanSE
Pr (>F)
Source: Kansas State Soil Testing Lab., 2022

Fig. 1 Competition of corn aboveground biomass in different treatmentsⒸ ISERD

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Soil Moisture Content
The result showed no significant difference among the treatments (P > 0.05). We were able tomaintain the soil moisture evenly among the treatment (Table 2). In terms of aboveground biomass,
it was observed that there are no significant differences between the control and the other treatmentswith reactions of 10.1%, 9.20%, 8.90% and 8.70%, respectively (Fig. 1; P > 0.05). However,
aboveground biomass of swine slurry treatment was higher than others.
No significant differences in the underground biomass were observed between the control andother treatments (P > 0.05), with reduction of 20.10%, 20.60%, 22.07%, and 21.50% for the swine
slurry, urea, NH4 NO3 and KNO3 + NaNO3 treatments, respectively (Fig. 2).
Table 2 Effect of different fertilizer on Soil moisture
Treatment
Control
Bio-slurry
Urea
NH4NO3
KNO3 + NaNO3

Mean (%)
2.71
2.63
2.79
2.65
2.68

SD
0.08
0.08
0.21
0.08
0.11

Kansas State Soil Testing Lab (2022)

Fig. 2 Underground biomass
CONCLUSION
The results of this research demonstrated that swine slurry treatment cannot affect to soil enzyme
activity (β-glucosidase), aboveground biomass, and underground biomass for a short term.
According to the results obtained in this study, it is proposed to continue studying the soil enzyme
activities for a long term and Phospholipid fatty acid (PLFA).
ACKNOWLEDGEMENTS
The authors would like to express our sincere thanks to the Higher Education Improvement Project(HEIP) funded by World Bank via Royal University of Agriculture (RUA) for financial support andThrockmorton Plant Sciences Center, Department of Agronomy, Kansas State University (KSU) forthe laboratory and facilities.
REFFERENCESⒸ ISERD

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Research article
erdHousehold Income Diversity of Small-scale Cassava
Producers in Vietnam
NIEN CHAU NGUYEN*
Agronomy Faculty, 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, Nagoya, Japan
Received 8 February 2023

Accepted 30 May 2023(*Corresponding Author)

Abstract This study clarifies how small-scale cassava producers endeavor to stabilize theirhousehold income. We conducted the survey between April and December 2017 in Dong Nai,
Tay Ninh, and Gia Lai provinces, which are major cassava-producing provinces; 182 smallscale cassava producers were randomly selected for interviews. According to the results, eachhousehold has 4.5 members, of which 2.1 are involved in cassava production. The average
household income was $7,071.29 per year, while the average income per employee was$3,535.15, which is 36.8% less than the average income of Vietnamese employees. The
primary income is derived from two sectors: $3,648.41 (51.59%) and $3,422.88 (48.41%)
from agricultural and non-agricultural incomes, respectively, along with $25.0 (0.4%) and$14.7 (0.2%) from remittance and pensions, respectively. Further, the cassava income shared
23.57% and 12.16% of agricultural and total household incomes, respectively, with an averageof $859.81. As their primary sources of income, some small-scale cassava producers produce
industrial crops, such as rubber trees, sugarcane, cashew, tobacco, and acacia. Moreover, they
produce vegetables and fruits and engage in animal husbandry activities and agro-processing.
In terms of non-farm income, they work as hired laborers and receive a stable income fromthe government or private companies. Thus, small-scale cassava producers in Vietnam
stabilize their household income with multiple income sources and do not rely heavily on
cassava.
Keywords cassava, production, producers, socioeconomic status, income, Vietnam

INTRODUCTION
Vietnam is a lower middle-income country; however, its economy has grown by an average ofapproximately 6.7% annually since Doi Moi (renovation) in 1986 (Cameron et al., 2020). The
agricultural, forestry, and fishery sectors constituted 12.36% of the economic structure. In 2019,labor productivity reached an annual average income of 4,159 USD per employee (GSO, 2017a).
However, the average income varies between regions and provinces; for example, the central
highlands had a per-employee income of 3,223.1 USD, while the Southeast had a per-employee
income of 5,596.4 USD (GSO, 2017a).
After rice and corn, cassava is the third most crucial staple crop in Vietnam’s agricultural sectors.
In addition to rubber trees, coffee, tea, and cashew nuts, cassava is classified as an industrial crop,and it is the third most important export crop. According to Kim et al. (2000), cassava plays anⒸ ISERD

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important socioeconomic role. Furthermore, it generates employment opportunities in rural areas: inthe north, this crop is used as food and feed for livestock, whereas in the south, it is a raw material
for small-scale starch processing factories. This crop is grown on 513,000 hectares in 40 out of 63
provinces, with an annual production of 9.85 million tons (GSO, 2018a). In recent years, there has
been an increase in the quantity of cassava production in Vietnam. Vietnam ranks ninth in the worldin terms of cassava production, accounting for 3.5% of the world’s old total cassava production (FAO,2019). Statistical results from GSO (2018b) revealed that 7.42 million tons of cassava (75.3%) served
domestic processing factories, while other 2.43 million tons (24.7%) were exported mainly to China(88.1%) and other countries, such as Korea (2.7%), Malaysia (1.6%), and the Philippines (1.5%).
Therefore, influenced by processing industries that use cassava starch and export demand, theprice of cassava roots has fluctuated over the years. For example, in November 2012, the Prime
Minister of Vietnam issued a decree mandating that all organizations and individuals producing,
mixing, and trading petrol in Vietnam for use in conventional vehicle engines must use a biofuel
known as E5 gasoline. Specifically, 95% RON 92 gasoline is blended with 5% bioethanol to produce
E5 gasoline. The price of cassava roots has increased because bioethanol is made mainly fromcassava starch (Nguyen et al., 2017). In January 2017, however, when the National Petroleum Groupbegan selling RON 95 gasoline, the market share of E5 gasoline decreased significantly, resulting ina decline in the alcohol production industry. Moreover, compared with 2017, the amount of exported
cassava decreased by 37.7% in 2018 (GSO, 2017b; GSO, 2018b).
Small-scale cassava producers, who play an essential role in the cassava sector in Vietnam, arehighly susceptible to volatile cassava prices. Therefore, to earn a stable income, they might haveincome might rely on something other than cassava production. Previous studies suggested that
farmers in rural areas tend to cultivate multiple crops, raise livestock and poultry in their spare time,
and work as hired labor (Duong and Izumida, 2002; Minot et al., 2006; Nguyen et al., 2013; Hoang
et al., 2014; Nguyen, 2017; Nguyen et al., 2019). Moreover, some farmers profit from specific crops,
such as tea (Saigenji and Zeller, 2009). However, the income diversity of small-scale cassava
producers in Vietnam needs to be studied. Therefore, it is necessary to discuss their income status tosustain and develop the cassava sector and increase cassava producers’ income in Vietnam.
OBJECTIVE
This study discusses how small-scale cassava producers stabilize their household income in Vietnam.
METHODOLOGY
From April to December 2017, we randomly interviewed 182 cassava producers in the Xuan Loc
district of Dong Nai province (60 producers), Tan Chau district of Tay Ninh province (61 producers),
and Dak Po and Krong Pa districts of Gia Lai province (61 producers), regarding the 2016-2017
cassava production cycle. These three provinces occupy 26% of the total land used for cassava
cultivation and produce 34% of total cassava production in Vietnam (Fig. 1) (GSO, 2018a).
The questionnaire was designed to understand farmers' management capacity including age,education, farming experience, and labor. Moreover, to analyze all income sources of cassava
producers included in the study, four main income sectors, including agriculture income, non-farmincome, pension, and remittance were generated in the questionnaire. In each sector, in the context
of activities that generated income (plus or minus), producers were requested to clarify theirrespective contribution percentages. Microsoft Excel and R version 4.1.2 were used to analyze thedata using descriptive and correlation statistics.
RESULTS AND DISCUSSION
Cassava Producers’ Profile and Annual IncomeⒸ ISERD

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In this study, 182 cassava producers, with an average age of 48.6 years and a gender ratio of 14.3%
and 85.7% female and male, respectively, were interviewed. The interviewees’ education levels wereas follows: 14.3% no school, 42.9% elementary, 27.5% secondary school, 12.1% high school, and3.3% bachelor. Their cultivation experiences were 23.8 years and 11.4 years for cassava production.
Averagely, each family comprised 4.5 members, two of whom were the primary laborers for cassava
production. Of the cassava farmers, 60.4% and 39.6% produced cassava full-time and part-time,
respectively. Each cassava producer utilized 2.9 ha of land for a total of 5.1 ha of cultivation land.

Fig. 1 Location of study sites, land use and production of cassava cultivation(a) study site (light green); (b) land use for cassava cultivation (total: 596,000 ha);(c) cassava production (total 10,309,700 tons), (made from GSO (2019))

As shown in Table 1, the income sources of cassava producers were categorized into four sectors.
This diversity is consistent with Minot et al. (2006) and Nguyen et al. (2017) study, in the sense thatrural farmers maintain their income by relying on a variety of sources, including subsistence
production of staple crops, commercial production of a broader range of agricultural commodities,
and non-farm activities. The annual average total income of each household was $7,071.3. The
average income per employee was $3,535.7 because each household had two main laborers. Thiswas 36.8% less than the average income of Vietnamese employees according to a government
declaration (GSO, 2017a).
Two primary income sources of cassava producers were agriculture at $3,648.4 (51.6%) andnon-farm at $3,383.2 (47.8%). An insignificant income was derived from remittances at $25.0 (0.4%)
and pension at $14.7 (0.2%). Haggblade et al. (2010) found that the non-farm sector accounted for
51% of the income of farmers in rural areas of Asian developing countries, similar to cassava
producers in Vietnam. This comparison demonstrates that agricultural income is essential for cassava
producers in Vietnam.
Table 1 Sharing income ($ per year) from a different source of cassava producers (N=182)
Sectors
Total income
Agriculture
Non-farm
RemittancePensionAverage
7,071.3
3,648.4
3,383.2
25.0
14.7

%
100.0
51.6
47.8
0.4
0.2

SD
10,717.17
9,472.74
5,078.94
336.93139.73Hire Labor and Agriculture Income Sources of Cassava Producers
According to Kim et al. (2015), cassava is a source of income for poor farmers as it can be easily
cultivated, adapted to poor soil, and has low investment costs. Cassava producers in this studyⒸ ISERD141

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generally cultivated cassava in areas with poor soil. Other crops, such as industrial and staple crops,
were grown in better soil areas. We identified eight different jobs in this study, as shown in Fig. 2.
Cultivation (hired by other farmers for planting or harvesting products and so on) and work at local
factories and companies were the three most attractive employments of cassava producers, sharing a
total of 89.3%. Moreover, cassava producers joined the community government, soldiers, policemen,teachers, and nurses.

Fig. 2 Sharing employments (%) in hire labor activity of cassava producers (N = 182)
Table 2 shows that cassava cultivation accounted for 23.6% of agricultural income, with anannual average of $859.8. In contrast, income from industrial crops accounted for 76.7%, with anannual average of $2,797.1, while agro-processing products, stable crops, and vegetable and fruit
crops contributed an insignificant amount of income in the agricultural sector. Concurrently, income
from animal husbandry was negative $131.6 (-3.6%) annually.
Table 2 Income components of the agricultural sector ($ per year) (N = 182)
Income sources
Industrial crops
Cassava
Agro-processing products
Staple crops
Vegetables and fruits
Animal husbandry

Average
2,797.1
859.8
49.5
48.7
25.1
-131.6

%
76.7
23.6
1.4
1.3
0.7
-3.6

SD
7,954.64
2,617.84
440.552,339.03
937.15
1,683.22

Farmers from various rural areas rely on other main crops for their income in the agricultural
sector. For example, according to Nguyen et al. (2013), rice, soya bean, and sweet potato are themain income crops for farmers in Cam My commune, Ha Tinh Province. Industrial crops, such as
rubber trees (60.6%), sugarcane (21.7%), cashews (8.7.0%), tobacco (6.4%), and acacia (5.5%) are
the main source of income for cassava producers in the agricultural sector (Fig. 3A). In contrast,
black pepper resulted in a slightly negative income ($-9.0 per year) for cassava producers.
According to GSO (2018), areas where rubber trees, sugarcane, and cashews were planted in
Vietnam were 969,700 ha, 281,000 ha, and 299,900 ha, respectively, with Dong Nai, Tay Ninh, and
Gia Lai serving as the three main production areas for these crops. In this study, the cassava producers
that planted rubber trees, sugarcane, cashew, tobacco, and acacia were 25 (with an average farm of
3.2 ha), 21 (with an average area of 3.9 ha), 44 (with an average farm of 1.9 ha), 9 (with an averagearea of 1.2 ha), and 8 (with an average farm of 3.5 ha), respectively. In addition, when cassava
producers cultivated more than one industrial crop, we discovered that seven cassava producers grewrubber trees and sugarcane, six cultivated cashew and acacia, one cultivated cashew and tobacco, andanother cultivated rubber trees, cashew, and acacia.
In vegetable and fruit crop cultivation (Fig. 3B), income sources were from banana (39.7%),
watermelon (29.8%), dragon fruit (24.0%), and mango fruits (9.4%). Similarly, in staple crop
cultivation (Fig. 3C), corn (60.7%), rice (28.2%), and bean (11.2%) were the income sources.
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In animal husbandry activities, cassava producers’ rear cows, pigs, goats, deer, chickens, ducks,
and squabs. The negative income sources were mainly derived from rearing cattle ($-163.6 annually)and pigs ($-20 annually). The major cause of cassava production was cattle and pig deaths caused by
epidemic diseases. A study by Chu et al. (2019) revealed a similar situation when animal husbandry
epidemic diseases caused a lack of 47.6% of farmers in the Da River basin.

Fig. 3 Sharing income (%) in crop cultivation of cassava producers (N = 182)
Non-farm Income Sources of Cassava Producers
Non-farm activities vary from continent to country. Haggblade et al. (2010) grouped diverse rural
non-farm activities as follows: mining and natural resources, manufacturing, construction, utilities,
commerce, and services. Non-farm income sources of cassava producers were grouped into nine
categories, as described in Section 4. The data indicates the positive and negative income derived
from different activities. Hired labor activity comprised the main income source for non-farms. This
activity contributed up to 81.5% ($2,757.2 annually). In this sector, middleman activity, specializing
in cassava roots and stems, was the second source, gaining 10.9% ($368.6 annually). Grocery was
third, at 5.83% ($195.8 yearly). A small amount was shared for the activities, including transport bya motor (1.0%), preparing motors or cars (0.8%), cashew nut businesses (0.6%), transportation bycar (0.5%), and selling feed for the animal (0.1%).
Generally, cassava producers obtain a good revenue for their commercial activities. However,food booth activity resulted in a -1.3% ($-42.7 per year). This result may explain why farmers
produced and sold food to inhabitants and fed their households during activities at food booths.
Table 3 Sharing annual income ($) in the non-farm sector of cassava producers (N = 182)
Income sources
Hired labor
Middleman
Grocery
Transport by motor
Repair motors or cars
Cashew nuts businessTransport by car
Selling feed for animal
Food boothAverage
2,757.2
368.6
195.8
35.0
27.1
21.0
18.2
3.0
-42.7

%
81.5
10.9
5.8
1.0
0.8
0.6
0.5
0.1
-1.3

SD
3,114.14
4,094.96
1,147.45
332.62271.38283.02245.9640.43
443.95

Correlation between Income and Total Land Area and Cassava Land Area
Analysis results indicated a correlation between total income and land use for crop production (Fig.
4A) and land use for cassava production (Fig. 4B), with the correlation coefficients (r) being 0.37
and 0.41, respectively. However, we observe that few farmers are pulling the correlation to become
positive liners. The results suggest that cassava producers with more agricultural and cassava land
will have more income. This finding is per the study of Minot et al. (2006), who found that expandingⒸ ISERD

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the areas of cultivation is one of the various methods to improve farmers’ income. A study of Nguyen
et al. (2017) showed that ethnic minorities in the Northern Mountains of Vietnam could increase 15%
income per capita when they increase 1,000 m2 crop land.

Fig. 4 Correlations between total income and total agricultural area (A) or
cassava cultivated area (B) (N = 182)
Encounter Problems in Cassava Production
Other than income from cassava, we observed that cassava farmers diversified their sources ofincome. This section discusses the issues cassava farmers face and the possible reasons why cassava
producers need to rely on more than cassava production as their primary income source. Cassava
production in Vietnam has encountered various biotic and abiotic stressors. Moreover, other issues
related to varieties, changing root prices, and cultivation technologies have also challenged producers.
This study summarizes 11 problems in cassava production, as shown in Fig. 5. Up to 87.9% of
cassava producers encountered low prices for tuber selling. Half of the cassava producers had issues
with pests and diseases, and nearly one-third had problems with adverse weather during cassava
farming. High-cost input and seedling die had caused trouble for approximately 10% of cassava
producers. In addition, other issues, including low yield and technology, difficulty finding labor, highlabor cost, counterfeit fertilizer and pesticides, and poor transportation, also affected a few cassava
producers.

Fig. 5 Encounter problems in cassava production (N=182)
CONCLUSIONⒸ ISERD

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This study investigates the household income diversity of small-scale cassava producers in Vietnam.
We utilized a sample of 182 cassava producers cultivating cassava fields of 2.9 ha on average, with
11.4 years of experience in cassava production in Dong Nay, Tay Ninh, and Gia Lai provinces.
The results showed that, on average and yearly, total household income was $7,071.29, of which$3,648.41 (51.59%) was from agricultural and $3,422.88 (48.41%) from non-farm sources. The
average income from cassava production was $859.81, which accounted for 12.16% of the total
household income and 23.57% of agricultural income. The various agricultural income sources
included seven types of crops, six types of vegetables and fruits, seven types of animal husbandry
operations, and three types of agro-processing businesses. Further, they engaged in eight kinds ofoff-farming work and were hired as laborers; this income accounted for a significant portion of thetotal household income. We also observed problems encountered in cassava production, which
explains why cassava farmers cannot only produce cassava. Due to fluctuations in tuber prices, pests
and diseases, and adverse weather, cassava producers in Vietnam diversify their income sources.
They do not overly rely on cassava and stabilize their household income.
ACKNOWLEDGEMENTS
This research was supported by the Science and Technology Research Partnership for Sustainable
Development (SATREPS) in collaboration with the Japan Science and Technology Agency (JST,JPMJSA1508) and Japan International Cooperation Agency (JICA).
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Research article
erd

The Effects of Green Manure on Sustainable Agriculture Soil
Conservation under Open Field Conditions
MALA SUON*
Department of Food Processing, Faculty of Agriculture and Food Processing,
National Meanchey University, Sisophon, Cambodia
Email: suon.mala.mcu@moeys.gov.kh

SOPHEAK TITH*
Faculty of Agriculture and Food Processing,
National Meanchey University, Sisophon, Cambodia
Email: tethsopheak@gmail.com

THANGRAK VEU
Department of Veterinary, Faculty of Agriculture and Food Processing,
National Meanchey University, Sisophon, Cambodia

PISIDH VOEFaculty of Agriculture and Food Processing,
National Meanchey University, Sisophon, Cambodia

SOCHEAT NGY
Faculty of Agriculture and Food Processing,
National Meanchey University, Sisophon, Cambodia

SOTHEA HILL
Faculty of Agriculture and Food Processing,
National Meanchey University, Sisophon, Cambodia

CHHOUK CHHEANG
Faculty of Agriculture and Food Processing,
National Meanchey University, Sisophon Cambodia
Received 16 January 2023

Accepted 10 June 2023(*Corresponding Author)

Abstract Green manure is a type of crop that is used for soil enhancement, both physical andbiological. It is enriched with organic matter that provides nutrients to the soil and improves
soil fertility. However, improper chemical use by farmers results in soil degradation andadverse effects on beneficial soil microorganisms. To mitigate this problem, farmers need touse fertilizer only as required. The purpose of the current study was to grasp the efficacy ofgreen manure on soil improvement, with consideration of the principles of sustainableagriculture. The research aimed to study the effect of green manure on soil properties
including soil pH, soil EC, and available nitrogen. Experiments were carried out in field
conditions at the National Meanchey University, Cambodia, from June 25 to July 25, 2022.
The experiment was laid out in a randomized complete block design (CRBD) with 4
treatments and 8 replications utilizing green manure produced from different plants. Treatment
T0 represented the control, T1 Glycine max, T2 Vigna radiata, and T3 Crotalaria Juncea.
The result showed that green manure has a significantly positive effect on soil properties
such as pH, electric conductivity, and available nitrogen. T3 produced the highest posttreatment soil pH and reduction in soil electric conductivity (EC), which averaged 7.14 and
0.46, respectively. T2 provided the greatest amount of available nitrogen, while untreated soil
was not significantly different among treatments. Therefore, the application of green manure
can be a vital choice in soil improvement for sustainable agriculture and increased yield.

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Keywords green manure, fertilizer, soil, sustainable agriculture

INTRODUCTION
Soil health is defined as the capacity of the soil to function as a living system, with ecosystem andland use boundaries. It sustains plant and animal productivity, maintains or enhances water andair quality, and promotes plant and animal health. It is based on the interaction, balance, and stabilityof the physical, chemical, and biological properties of soil, which have direct effects on nutrient
cycling, soil structure, water availability, and pests and diseases, ultimately affecting crop healthand yield (Patil and Solanki, 2016).
Consequently, fertilization increases efficiency and obtains better quality product recovery inagricultural activities. Fertilizer use has increased by 70%, and pesticide use has increased severalfold (Savci, 2012; Tilman et al., 2002). As a result, fertilization causes the accumulation of heavy
metals in soil and plant systems. Long-term unbalanced use of agrochemicals may lead to acommunity shift of beneficial microorganisms with dangerous consequences for soil physical andchemical structure (Hamidov et al., 2007). Soil structure in agricultural productivity is very
important and it is regarded as an indicator. Unconsciously, the fertilizing of soil, just as in thedeterioration of the structure is caused by industrial emissions. Especially NaNO3, NH4NO3,
KCI, K2SO4, and NH4Cl demolish the structure, such as fertilizers, soil, and soil structure, anddeterioration is difficult to obtain high-quality and efficient products (Shaviv, 2001). Moreover, soil
degradation has strong negative economic impacts since a large part of the population relies on
agriculture as a primary source of income (Lal, 2015). More than 500 million hectares of tropicalarable land and 33% of the earth's land surface globally face a decline in soil health (Lamb et al.,2005).
Therefore, green manure is considerable for use in soil improvement in terms of sustainableagriculture because it provides numerous benefits to crop production and soil health (Magdoff, 2001).
According to Pandey et al., (2008), green manuring helped advance the soil's physical andbiochemical anatomy, prevented leaching losses of nutrients, and added water-holding capacity.
The approved use of green manuring resulted in high organic matter reserves which added bothsoil physical and chemical properties if compared to controlled fields. This is because they can help
conserve, maintain, or replenish soil resources, including organic matter, nitrogen and othernutrient inputs, and physical and chemical properties (Sarrantonio and Gallandt, 2003). Several
studies have investigated cereal-legume intercropping. Legumes are found in natural ecosystems
and are key to promoting ecosystem efficiency such as nitrogen fixation, soil microbial health,and ecological network of biodiversity of soil (Duchene et al., 2017; Zhang et al., 2021). Likewise,
Ablimit et al. (2022) revealed that microbial phylotypes were grouped into four major ecologicalclusters. The application of green manure led to significantly increased soil pH, nutrient contents,and enzyme activities, and significantly reduced the relative abundance of potential plant
pathogens compared with monocropping, which should ensure high and stable maize yield underlong-term continuous cropping (Charron and Sams, 1999).
We conduct research based on sustainable agriculture in an effort to achieve Cambodia’s action
plan of Zero Growth on Chemical Fertilizers by 2050. The outcome of the research will be sharedwith farmers in an effort to maintain the environment and increase food safety.
OBJECTIVE
The research aims to enhance the soil property by inoculation of green manure from different
plants, (i) Glycine max, (ii) Vigna radiata, and (iii) Crotalaria Juncea, in an open field at the
National Meanchey University, Cambodia.
METHODOLOGYⒸ ISERD

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Experimental Design and Plantation
This research was carried out at National Meanchey University from June 25, 2022, to July 25, 2022.
The experiment was carried out by randomized complete block design (RCBD) consisting of four
treatments and three replications (Table 1). Each block had a 2 m x 2 m diameter and a length of 0.5
m for a total area of 66.5 m2. For the plantation, each plant was planted in the experimental field
by using different types of plants for comparison. Green manures were plowed into the soil to a depthof 10 cm length after one month of plantation. Each treatment was plowed two times per day after
fermentation. Treatment zero was the control, treatment one (T1) used Glycine max, treatment two(T2) used Vigna radiata, and treatment three (T3) used Crotalaria Juncea.
Table 1 Treatment and composition
Treatment
Control
Treatment 1
Treatment 2
Treatment 3

Inoculation
Uninoculated
Glycine max
Vigna radiata
Crotalaria Juncea

Reference: Blomme et al. (2022)

Soil Chemical Analysis
Soil samples were collected before and after plantation in the field experiment of the National
Meanchey University. Upon collection, soil samples were sent immediately to the soil laboratory
for further analysis including soil pH, soil electrical conductivity (EC), and available nitrogen, which
followed the method of Kjeldahl (Cunniff, 1995). Soil pH was determined using the method of Kumar
et al. (2014), while EC was analyzed according to the method proposed by Kargas et al. (2022).
Data Analysis
Data were analyzed for analysis of variants (ANOVA) using the R program version (4.0.3). The
differences among means were tested by Duncan’s multiple range tests at p ≤ 0.05.
RESULTS AND DISCUSSION
Before planting, soil pH was detected to be the same value for all treatments. This was due to soil
experimentation being in the same condition. However, the effect of intercropping on soil pH result
displayed that application of green manure enhances soil pH significantly, increasing among
treatments ( Fig. 1) As a result, treatment 3 (T3) and treatment 4 (T4) provided the highest soil pH
values, which ranged from 6 to 7. Our research strongly agreed with Kawu (2020), and found thatincorporating green manure crops significantly influenced soil pH at harvest. This phenome isdue to a major contribution of soil decomposition by microbial activity when incorporated into thesoil (Msimbira and Smith, 2020). Previous studies have reported higher soil organic matter, nitrogen,phosphorus, potassium, calcium, and magnesium contents due to incorporating green manure (Biswas
and Mukherjee, 2001; Herrera et al., 2007).
Soil reduction regarding electrical conductivity was examined and was found without significant
difference relative to the control, which ranging from 1.20 to 1.44 dSm-1. However, soil EC was foundsignificantly reduced after incorporating green manure into the soil among different treatments (Fig.
2). Moreover, treatment three (T3) resulted in the greatest reduction in soil EC, with a value of 0.49
dSm-1. Similar results, indicating that green manure reduced soil EC, were obtained by Bhayal et al.
(2018). This decrease was due to the addition of readily decomposable organic matter in the form ofgreen manure with accumulation of the CO2 either may be due to the precipitation of Fe2+, Mn2+ andconsequent adsorption of other cations on the exchange site and decomposition of organic acid (Harish
and Devasenapathy, 2010).
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Fig. 1 The effect of green manure on soil pH before and after plantation

Fig. 2 The effect of green manure on soil electric conductivity
Green manure is usually considered as a cover crop sown to enhance the fertility of the soil
between two crops demanding high nitrogen inputs (Sanaullah et al., 2022). After incorporation
in soil, the result displayed that green manure had significantly increased the available nitrogen(P < 0.05). Barradas et al. (2001), in an experiment with eight species of green manure, observedthat white lupine and common vetch were the species that accumulated the highest total N in
the whole plant, with amounts of 251.6 and 228.1 kg/ha, respectively. Our result agreed with thoseof Salahin et al. (2013), finding that green manure has significantly increased soil organic matter,soil health, and crop growth. Moreover, the author found that green manure increased SOM andTN which was obtained from V. radiata and S. aculeata. There may be a difference in time andspecies of plant in this result. On the other hand, after incorporation into the soil, the nutrients in theplant biomass were released during the process of decomposition (Piotrowska and Wilczewski,2012).

Fig. 3 The effect of green manure on soil available nitrogenⒸ ISERD

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CONCLUSION
The incorporation of Glycine max, Vigna radiata, and Crotalaria Juncea as green manure showed
a positive response on soil pH, soil electrical conductivity, and available nitrogen . Therefore,
we concluded that treatments 1, 2, and 3 provided a positive result for soil health, but only treatment
2 provided the greatest value of available nitrogen.
ACKNOWLEDGEMENTS
I would like to express my profound gratitude to Mr. Sopheak TITH for his contribution as alaboratory technician at the Faculty of Agriculture and Food Processing, and the Dean of the Facultyof Agriculture and Food Processing for the contributions to the completion of my project titled"The effects of green manures on sustainable agriculture soil conservation under open field". We
would also like to acknowledge the National Meanchey University for supporting this research.
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Research article
erd

Habitat Evaluation of Agricultural Waterways where
Environmental Improvement Was Practiced for Recreation
MASAYUKI NITTA*
Sado Island Center for Ecological Sustainability, Niigata University, Sado, Japan
Email: nitta@cc.niigata-u.ac.jp

MITSURU OHIRA
Field Science Center for Northern Biosphere, Hokkaido University, Hokkaido, Japan

MUNEYUKI AOKI
Department of Civil and Environmental Engineering, Toyo University, Kawagoe, Japan

MASAHIRO NAKAJIMA
Institute of Agriculture, Tokyo University of Agriculture and Technology, Fuchu, Japan
Received 28 May 2022

Accepted 10 June 2023(*Corresponding Author)

Abstract In rural areas, agricultural irrigation and drainage systems developed for paddy fields
have a high potential to become components of green infrastructure by providing ecosystemservices. In order to manage and operate agricultural waterways as green infrastructure, thehabitat evaluation of aquatic organisms is important. In this context, we conducted a habitat
evaluation of aquatic organisms in the waterway network where environmental improvement
was practiced to promote recreational use by residents. Based on evaluation results, thephysical characteristics of canals with high biodiversity were investigated. The Evaluation
Program for Fish Habitats in Agricultural Canals, which was developed for non-professional
users such as residents, was applied to biological (fishes and crustaceans) and physical datacollected in the waterway network in the town of Koura, Shiga Prefecture, Japan. The model
generated by the program showed high fitness (0.80 for fishes, 0.76 for crustaceans), whichsuggests the program applies to waterway networks including various types of watercourses.
The characteristics of the canals which were assigned a high habitat score by the program
included 1) deeper water depth, 2) higher velocity for fish, 3) lower velocity, 4) higher
vegetation coverage, and 5) gravel canal bed for crustaceans, relative to the low-scoring canals.
The canals in diversion parks developed as part of environmental improvement efforts tended
to have these characteristics and higher scores. Therefore, our findings suggest that conserving
irrigation canals and developing diversion parks in waterway networks, which were conducted
as part of environmental improvement efforts in the target area, contributes not only topromoting recreational use by residents but also to habitat conservation.
Keywords habitat evaluation, agricultural waterways, environmental improvement,
green infrastructure

INTRODUCTION
Green infrastructure is defined as a strategically planned network of natural and semi-natural areas
with other environmental features designed and managed to deliver a wide range of ecosystemservices in both rural and urban settings (European Commission, 2013). Agricultural waterways for
irrigation and drainage have been historically developed in rice-farming regions. Such waterways
were traditionally used not only for irrigation but also for fisheries, recreation, and domestic use.
Therefore, agricultural waterways have a high potential to become components of green
infrastructure by providing ecosystem services.

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However, recent modernization of agricultural landscapes and infrastructures modified only for
efficient agricultural production and accelerated to use as grey infrastructure (Lee et al., 2015). Thus,
improving irrigation infrastructures as green infrastructure based on sustainable ecosystem service
use, such as recreational use, is a recent fundamental challenge (Matsuno et al., 2006; Katayama etal., 2015; Nishida, 2018). In this context, the habitat evaluation of aquatic organisms is important tomanage and operate agricultural waterways as the green infrastructure.
Currently, agricultural waterways in rice-farming landscapes have been modified for themodernization of irrigation systems. Particularly, irrigation canals have been converted into pipelines
to distribute water efficiently. Further, even in open canals, concrete lying degrades habitat
conditions. Such negative impacts of modification for aquatic organisms have been reported (e.g.,
Nishida et al. 2018) and could be a significant concern for the availability of ecosystem services.
However, consideration of the availability of such waterways for people is limited in planning andmanaging agricultural landscapes as green infrastructure in addition to habitat conservation andrestoration.
In a waterway network in Koura town, Shiga Prefecture, Japan, environmental improvement
was practiced promoting the recreational use of residents. Recreation constitutes cultural ecosystemservices of agricultural waterways and is important from a well-being perspective for the formationof rural living environments. However, it is not known that such modification for recreational use
benefits to restoration of ecosystem services (Lin et al., 2020). In restoration practice, considering
the habitability of aquatic organisms with such environmental improvement is key for the availabilityof wider ecosystem services (Matsuno et al., 2006).
OBJECTIVE
The study aims to assess the habitability of aquatic species in agricultural waterways adapted forrecreational purposes.
METHODOLOGY
Study Area
The study was conducted in a waterway network in the town of Koura (35.2 N, 136.26 E), Shiga
Prefecture, Japan. Koura town is a rural area located on the alluvial fan formed by the Inukami River(Fig. 1). In this area, it was planned to convert all irrigation systems to pipelines for water shortagein 1981.
N

Lake Biwa

Inukami River

Shiga Prefecture
Koura Town
0 1

2km

Fig. 1 Location of the study area, Koura Town, Japan
An aerial photograph is quoted by the Geospatial Information Authority of Japan and modified partially.

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However, implemented the water environment improvement project in 1989, the irrigation anddrainage canals were drastically altered to improve for recreational use by the residents: (1) the
irrigation plan was modified to maintain open canals; (2) diversion parks were developed utilizing
the pipeline discharge and diversion points; (3) the open irrigation canals were environmentallyprotected by masonry revetments; (4) sands and gravels were added to the irrigation canal beds; and(5) landscape facilities such as flower beds were installed
Data Collection
Based on the characteristics of the waterway network in this area, a total of 26 canal sections
containing a variety of environmental conditions were selected as survey sites (Fig. 2). Each of thesurvey sites was 20 m in length and the width was the canal width. We conducted a biological andenvironmental survey on 10-18 August 2018.
As the physical environment varies depending on the type of canal, the survey sites werecategorized into four canal types: diversion park (No. 1 to No. 6, Fig. 3a); drainage canal (No. 7 toNo. 11, Fig. 3b); irrigation canal A (No. 12 The
to Inukami
No. 20,Fig. 3c); and irrigation canal B (No. 21 to No.
River
The Inukami River26, Fig. 3d).
: Diversion park
: Drainage canal

The Inukami River

The Inukami River
The
InukamiRiver
River
The
InukamiThe Inukami River: Irrigation canal A(wider)The Inukami River: Irrigation canal B(smaller): Open canal: Pipeline
Weir

0m

500m

Fig. 2 Location of survey sites with canal typeFig. 3 Example of four canal types in the study areaa) diversion park; b) drainage canal; c) irrigation canal A; andd) irrigation canal BⒸ ISERD155

The Inukami River

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In this waterway network, irrigation water is introduced from the Inukami River, after that, water
is distributed into diversion works of each village through pipelines. The diversion park as the waterpark was developed in diversion points and the associated canals. The survey sites of diversion parks
were located in one of the associated canals to compare other canal sites. The Irrigation Canal A is
the main canal and has a wider canal width for carrying water to areas of paddy fields. Irrigation
Canal B is a small canal that branches off from Canal A and supplies water directly to each paddy
field. In diversion parks the environmental improvement commonly modified the canal structure forrecreational use: the canal width was widened; gravel was laid on the streambed; the slope of therevetment was made gentler; and emergent plants were planted. In this waterway network, vertical
drops were constructed between irrigation canals and drainage canals. However, fish migration was
thought to mainly come from the Inukami River through pipelines. Thus, we did not consider theeffects of barriers to fish migration.
To measure physical characteristics, cross sections were placed at 5 m intervals in each site. We
conducted a field survey including both physical characteristics and biological sampling. To examine
the hydraulic conditions of survey sites, water depth, water velocity, canal width, and wetted width
were measured. The difference between canal width and wetted width was used as land width acrossthe canal. Water depth and water velocity were measured across cross sections, and the points weredivided into quarters. A uniaxial electromagnetic anemometer (Kenek, LP40) was used to measurewater velocity. The percentage of streambed material (concrete, large gravel (cobble, > 64 mm),small gravel (pebble and granule, 2-64 mm), sand and silt (< 2 mm)) and vegetation cover were
measured visually. We also measured water temperature, electric conductivity, and pH at the sametime as those samples. However, the remarkable differences among sites were not shown.
We conducted biological sampling for fish and crustaceans. Two fyke-nets (mesh size: 5 mm)
were set at both ends of the sampling section and hand nets (2 mm) were used to collect fish andcrustaceans inside the survey site. The sampling effort of each site was fundamentally ten minutesby three persons. However, areas of the survey site (i.e., canal width) differed among sites. Thus, thesampling effort was adjusted to the area of the survey site to ensure an equivalent sampling effort
among survey sites. After collecting fish and crustaceans, we identified species and counted
individuals of each species. After that, we released sampled fish and crustaceans to the sampling site.
Analysis
To evaluate aquatic habitat, the "Evaluation Program for Fish Habitats in Agricultural Canals"(Watabe et al., 2018; 2020) (hereafter referred to as the "EPFH"), which was developed as a simple
evaluation method by non-specialists, was applied. EPFH was developed and published free ofcharge by the National Agriculture and Food Research Organization (NARO, 2018). In ecosystemfriendly measures, it is important to conduct continuous monitoring surveys and adaptive
management, such as updating and modifying facilities, to prevent habitat degradation. However,there are issues such as the significant cost of continuing monitoring surveys and the difficulty ofinterpreting the results of environmental assessments without specialists. EPFH was developed as asimple evaluation tool to address these issues. In this study, the EPFH was selected based on theassumption that it would be operated by non-specialists (local residents) who are the maintenancemanagers of the agricultural waterways.
In this program, the evaluation score is calculated using Eq. (1). This is a regression equation,
which is positively correlated with both the number of species and the number of individuals
identified and is explained by the physical environmental conditions such as water depth and watervelocity (Watabe et al., 2018).
y=a0 +a1x1 +a2x2 +a3x3 +a4x4 +a5x5(1)

Where y is the evaluation score, a0 is the constant term, a1 to a5 are the coefficients of eachvariable, and x1 to x5 are environmental indices. The values of a0 and a1 to a5 are determined so thatboth the correlation coefficient r1 between the evaluation score y and the number of species and theⒸ ISERD

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correlation coefficient r2 between the evaluation score y and the number of individuals are high. The
goodness of fit of the model F is defined by the following Eq. (2);
𝑟 +𝑟2
2

𝐹= 1

(2)

where r1 represents the correlation coefficient between the evaluation score and the number of species,and r2 represents the correlation coefficient between the evaluation score and the number ofindividuals. The goodness of fit ranges from values of -1 to 1. In this study, to confirm the reliabilityof the accuracy of this program, a correlation test of the correlation between the evaluation score andShannon-Wiener's diversity index H' (Whittaker, 1972) was also conducted.
The Kruskal-Wallis’s test was conducted to analyze differences in scores of habitat evaluation
among canal types. If the test showed significant differences, multiple comparisons were made using
the Steel-Dwass method to determine a pair of canal types with significant differences among thefour canal types. All of the statistical analyses were performed using R version 4.0.5 (R Core Team,2021). The results of this analysis were shown for biological data but not for physical environments.
Because the variations were very large depending on the site characteristics. Thus, we focused on the
numerical difference of the physical environments.
RESULTS AND DISCUSSION
Status of Physical Environments of Waterways and Aquatic Organisms
The physical environmental conditions of canal type are shown in Fig. 4. Average canal width ofsurvey sites ranged from 50.0 to 446.5 cm, and the land width ranged from 0 to 146.0 cm. Water
depth ranged from 3.2 to 43.7 cm, and water velocity ranged from 1.7 to 38.7 cm/s. Vegetation coverranged from 0 to 51%. Streambed materials were largely varied.
Diversion parks tended to have relatively wider canal widths and deeper water depths. Only thediversion park contained canals with a water depth of more than 30 cm. This is because the diversion
park includes the canals through which pipeline water flows before it is diverted, and thus hasabundant water flow. As for water velocity, the drainage canals tended to be slower. Vegetation covertended to be higher in diversion parks and drainage canals. This is because aquatic plants wereplanted in the diversion park at the time of environmental improvement for landscaping, and also
because sediments were deposited in the drainage canals due to the slow water velocity andvegetation growth. Comparing canal bed materials, there was no concrete in the diversion park. The
percentage of small gravel tended to be lower in the drainage canal than in the diversion park.
Irrigation canals A and B showed similar trends.
The results of the aquatic organism survey are shown in Table 1. In total, 657 individuals of 13
fish species and 4,039 individuals of 4 crustacean species were observed. Among the fish species,
dark chub Nipponocypris sieboldii was most abundant (351 individuals at 12 sites), followed byAmur goby Rhinogobius sp. (153 individuals at 10 sites). Among crustaceans, the number offreshwater shrimps Paratya compressa was largely abundant (3,630 individuals at 21 sites). Japanese
freshwater crab Geothelphusa dehaani, which is an indicator species for good water quality (Ministryof the Environment, 2017), was found at 15 sites (57.7%) with 211 individuals so water quality inthe study area was suggested to be relatively good. Among fish species, Japanese medaka Oryzias
sp. (59 individuals at 3 sites) and weather loach Misgurnus anguillicaudatus (14 individuals at 4
sites), which were listed as endangered species on the Red List 2020 (Ministry of the Environment,2020), were included.
Aquatic Habitat Evaluation
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Based on the data of physical conditions and aquatic organisms, the EPFH was performed to evaluate
the habitat quality of the survey sites. As a result, the goodness-of-fit of the model F was 0.80 forfish and 0.74 for crustaceans (Table 2). The correlation between the model score and ShannonWiener's diversity index H' showed a strong correlation for fish (r = 0.63, p < 0.01). On the other
hand, no significant correlation was detected for crustaceans (r = 0.37, p = 0.90). This is thought tobe that the extremely large number of freshwater shrimps compared to other crustacean species
skewed the results of the analysis, resulting in a low correlation with Shannon-Wiener's diversity
index H', which takes into account the evenness of the number of individuals of each species.

Fig. 4 Boxplots of physical environmental conditions of survey sites by canal typea) canal width; b) water depth; c) water velocity; d) vegetation cover; and percentage of streambed
materials: e) concrete, f) sand and silt, g) small gravel and large gravel. Crosses in each figure indicate
the average value.

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The goodness-of-fit of the model in this study was higher than that of the previous study (0.71,
Watabe et al., 2018), which supports that the EPFH applies to waterway networks containing
different canal types such as size, structure, and role for irrigation. On the other hand, though thegoodness-of-fit of the model for crustaceans was not low, the correlation with Shannon-Wiener's
diversity index was weak. Thus, the model score as an indicator of habitat quality might be usefulfor habitat evaluation for this taxon.
Table 1 Results of biological survey (fish and crustaceans)
Taxon

Number ofindividuals

SpeciesFish

Nipponocypris sieboldii
Rhynchocypris lagowskii
steindachneri
Oryzias sp.
Rhinogobius sp.
Cobitis sp. BIWAE type B
Odontobutis obscura
Opsariichthys platypus
Plecoglossus altivelis
Misgurnus anguillicaudatus
Nipponocypris temminckii
Rhynchocypris oxycephalus jouyi
Pseudogobio esocinus
Tribolodon hakonensis
Crustaceans Geothelphusa dehaani
Procambarus clarkii
Paratya compressa
Palaemon paucidens

Observed sites

Standard length

Number Ratio (%)

Mean ± S.D. (cm)

351

12

46.2

5.8 ± 2.7

22

5

19.2

4.7 ± 1.8

59
153
1
3
22
24
14
3
1
3
1
211
163
3,630
35

3
10
1
3
3
7
4
2
1
1
1
15
10
21
7

11.5
38.5
3.8
11.5
11.5
26.9
15.4
7.7
3.8
3.8
3.8
57.7
38.5
80.8
26.9

2.5 ± 0.6
3.5 ± 0.7
7.0 ± 0.0
3.1 ± 1.1
5.9 ± 2.1
11.8 ± 1.3
8.0 ± 0.7
7.8 ± 2.3
4.7 ± 0.0
9.3 ± 1.5
9.7 ± 0.0
1.5 ± 0.6
5.8 ± 2.2
2.0 ± 0.4
4.3 ± 0.4

Table 2 Fitness of the EPFH model (fish and crustaceans)
Goodness of fit of the model F
calculated by EPFH

Correlation coefficient of the model andShannon-Wiener's diversity index H’

Fish

0.80

0.63**

Crustaceans

0.74

0.37

Significant difference is indicated by *p < 0.05, **p < 0.01, and ***p < 0.001, if detected

2) Environmental factors identified by the EPFH model
Based on the EPFH model for fish, five factors were identified as effective factors on fish habitat:water depth, water velocity, land width, vegetation cover, and percentage of sand in the streambed
material (Table 3). Four of the factors, except land width, had a positive effect on habitat. Thus, theresults indicated that good fish habitat had the following characteristics: (1) deeper water depth; (2)higher water velocity; (3) narrower land width; (4) higher vegetation cover; and (5) a greater
proportion of small gravel in the streambed material.
As effective environmental factors on crustacean habitat identified by the EPFH model, fivefactors were identified: water depth, water velocity, land width, vegetation cover, and percentage ofconcrete in the streambed material. Among these factors, only vegetation cover had a positive effecton crustacean habitat, while the other four factors had negative effects. Thus, the results indicatedthat good crustacean habitat had the following characteristics: (1) shallower water depth; (2) lower
water velocity; (3) narrower land width; (4) higher vegetation cover, and (5) a smaller proportion of
concrete in the streambed material.

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Table 3 Environmental factors and coefficients comprising the fish habitat model

Coefficients

Water depth

Watervelocity

Land width

Vegetation
cover

Streambed material(small gravel)

0.034

0.021

-0.018

0.014

0.02

Table 4 Environmental factors and coefficients comprising the crustacean habitat model

Coefficients

Water depth

Watervelocity

Land width

Vegetation
cover

Streambed material(concrete)-0.046-0.049-0.0050.022-0.015

3) Habitat score estimated by the model and its comparison by canal typeFigure 5 shows the habitat score for fish and crustaceans of each survey site, which was calculatedby the model. The score ranges from 1 to 5, with higher scores indicating better habitat at that site.
The site with a score of 5 for fish habitat was only No. 2 (Diversion Park), and the sites that scored
5 for crustacean habitat were No. 1 (Diversion Park) and No. 13 (Irrigation Canal A).
To examine differences in habitat quality among channel types, the mean habitat scores and themean Shannon-Wiener’s diversity index H’ are compared. Comparing the habitat scores, thediversion park was the highest (3.3 score), followed by the drainage canal (3.0 score), irrigation canal
A (1.9 score), and irrigation canal B (1.7 score) in order of highest to lowest (Table 5). As a result of
the Kruskal-Wallis’s test, significant differences were detected for the fish score (p < 0.01), while nosignificant differences were detected for crustaceans (p = 0.075). Multiple comparisons for fishmodel scores suggested the scores significantly differ between the diversion park and irrigation canal
A (p = 0.029, < 0.05, Table 6) and between the diversion park and irrigation canal B (p = 0.012, <0.05, Table 6). The drainage canal was not significantly different from irrigation canals A and B,
although the mean habitat score was high.

D.P.

I.C. A

D.C.

I.C. B

Fig. 5 Habitat score for fish and crustaceans at each survey site
D.P. indicates Diversion Park, D.C. indicates Drainage Canal,
I.C.A indicates Irrigation Canal A, and I.C.B indicates Irrigation Canal B.

Table 5 Habitat score and Shannon Weiner's diversity index H’ by canal type
Canal type
Diversion park

Fish
Habitat score(Mean ± S.D.)
3.3 ± 0.8

H
(Mean ± S.D.)'
1.2 ± 0.9

Crustaceans
Habitat score
H'(Mean ± S.D.)(Mean ± S.D.)
3.5 ± 1.4
0.8 ± 0.5

Drainage canal

3.0 ± 1.2

1.0 ± 0.6

3.8 ± 0.4

0.4 ± 0.4

Irrigation canal A

1.9 ± 0.8

0.3 ± 0.5

3.2 ± 1.0

0.3 ± 0.3

Irrigation canal B

1.7 ± 0.5

0.3 ± 0.6

2.7 ± 1.0

0.2 ± 0.5

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Table 6 Results of multiple comparisons using the Steel-Dwass method tofish habitat score
Combination of comparison
Drainage canalvsDiversion park
Drainage canalvsIrrigation canal A
Drainage canalvsIrrigation canal B
Diversion parkvsIrrigation canal A
Diversion parkvsIrrigation canal B
Irrigation canal AvsIrrigation canal B

t-value
0
1.796
1.896
2.772
3.052
0.523

p-value
1
0.275
0.230
0.029
0.012
0.954

The canals in the diversion park have the highest discharge among canal types. These canals arelocated upstream of the irrigation system and thus carry water before being diverted to canals A and
B. Thus, the conservation practice would benefit from ensuring such habitat property. In addition,
the environmental improvements in the canals of the diversion parks created habitat structure as
follows: the canal width was widened; gravel was laid on the canal ed; the slope of the revetment
was made gentler; and emergent plants were planted. Such habitat modification might support toconservation of functional habitat characteristics for fish such as higher vegetation cover (Nishida etal., 2011) and coverage of natural material on canal beds (Katano et al., 2003) among factors of fish
habitat characteristics. The average habitat score (and Shannon-Wiener index) of the diversion park
was higher than drainage canal, although the difference was not significant. Those environmental
modifications for recreation, such as gravel beds against concrete lying, may positively affect suchhigher habitat value. However, the higher scores in drainage canals might not be negligible becauseof their greater canal width, water depth, and vegetation cover.
On the other hand, high scores of crustaceans were found in shallow canals, though we did notconduct a detailed analysis per canal type because of the unconfident model score. Further, theirdistribution was tended to different from fish. Thus, branched irrigation canals might have habitat
value for crustaceans, and considering the effects of preservation of those canals as open canal andtheir availability for recreational use has remained a future challenge of this study.
CONCLUSION
The canals in diversion parks developed by environmental improvement had higher habitat value forfish. This habitat is characterized by the following conditions: (1) deeper water depth, (2) higher
water velocity, (3) greater vegetation cover, and (4) a higher proportion of gravel in the canal bed
material. Among these variables, canal bed materials in diversion parks were different from drainage
canals, though both canals have higher discharge in an agricultural waterway network (i.e. higher
availability for fish). Irrigation canals are generally modified into pipelines with the current
modernization of irrigation systems. Our result suggested that conserving and improving theenvironment of irrigation canals for recreation, particularly in water diversion canals, benefits
ensuring higher value of fish habitat. Therefore, our findings demonstrated a way to evaluate themulti-functionality of agricultural waterways from the aspect of recreational use and habitat
conservation as green infrastructure.
ACKNOWLEDGEMENTS
We would like to thank Yuta Shimizu and Sho Takayama for their generous cooperation in
conducting the analysis. Also, we would like to thank Takuto Fujimori, Seiya Aihara, and Masato
Kondo for their generous cooperation in conducting the survey. This study is supported by the Toyo
University Faculty of Science and Technology Policy Research 2020 and JSPS KAKENHI Grant
Number 18K05876.

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Temporal changes in fish assemblage and environmental factors in the drainage channels were improvedby using an eco-friendly construction method. Transactions of The Japanese Society of Irrigation, Drainage
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DOI https://doi.org/10.2307/1218190Ⓒ ISERD

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Research article
erd

Temperature Sensitivity (Q10) of Organic Carbon in
Red-yellow Soils and Its Conservation Strategies
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 16 December 2022

Accepted 10 June 2023(*Corresponding Author)

Abstract Soil respiration (SR) is the second largest flux of carbon in most terrestrial
ecosystems after photosynthesis. Research indicates that a slight change in climate conditions
induces a variation of the SR that could be equal to the release of CO2 by fossil fuel emissions.
For this reason, it is important to study what conditions control the variation of SR. Soil
temperature is an important predictor of SR when there is no severe drought stress. The
estimation of SR rates by the effect of temperature has been expressed with the Q10 relationship.
This study aims to determine the Temperature Sensitivity (Q10) coefficient of the red-yellow
soil organic carbon and estimate its conservation strategy using biochar. To analyze
temperature sensitivity, each treatment was kept under 25ºC and 35ºC for 150 days, and thesoil respiration ratio (SRR) as well as soil organic carbon (SOC) content were measured by
the spectrophotometry method. Lastly, a treatment of biochar at 5% was added as a carbon
conservation mechanism. The experimental results showed a significant difference in SOC
content between different temperature conditions. After 150 days under treatment, 35ºC
treatment had a significant reduction of SOC in contrast with 25ºC treatment (3.65 and 6.02
mg C/g respectively). The addition of biochar resulted in higher values of SOC at the same
temperature, relative to non-biochar treatments. The Q10 value was higher in soil withoutbiochar (1.82), while the addition of biochar reduces the coefficient to 1.12. The SRR was
reduced gradually with higher values at 35ºC, however, the biochar reduced the emission at
25ºC lower than other treatments. The results indicated that the Q10 value of red-yellow soil
can be affected by the addition of biochar, which works as a carbon source to maintain andincrease SOC content and reduce the release of CO2 in the short term.
Keywords soil organic carbon, soil respiration rate, temperature sensitive, biochar

INTRODUCTION
The soil organic carbon is part of the organic matter in more than 50% of the content. This fulfills an
important role in plant feeding, stabilization of soil structure, soil fertility, and most important,climate change effects mitigation. The soil carbon is dynamic by the interaction of the ecosystem;
however, human activity impacts can destabilize SOC into either a net of carbon or a source ofgreenhouse gases (GHG) in the atmosphere (Trivedi et al., 2018).
The alteration of climate has a considerable effect on the SOC stocks, although it is variable
depending on the type of soil and location, Changes in temperature lead to an increase in extreme
drought events, followed by the loss of carbon in the soil. Efforts towards a better understanding of
the SOC dynamic have indeed been made, however, the mechanism of stabilization and conservationof SOC stocks are still complicated to apply and understand. Further research must focus on thevariation of soil and temperature, as well as conservation strategies (Pribyl, 2010).

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According to De Oliveira Marques et al. (2017), the Red-yellow soil (Udults soil taxonomy),
mainly located in the Amazon area, represents an important amount of global soil carbon, making
this area vulnerable to deforestation activities and land uses.
The conservation of carbon stocks in the Amazon area has had an impact on the political decisionof governments to act on reforesting rather than permitting deforestation. However, deforestation has
been accelerated and the fragmentation process of the Amazon area is resulting in significant changes
in carbon stock, as well as biomass soil (Barros and Fearnside, 2016).
Lloyd and Taylor (1994) remarked that the increase of microorganism activity in soil is
stimulated by the increase in temperature, leading to an augment of microbial CO2. This process
reduces the SOC, which contributes to the global warming problem. In a short period (one year), theincrease in temperature results in a considerable change in microbial activity and decomposition rate.
It has been demonstrated that the decomposition of SOC is higher as the temperature increases,
with the biggest proportional increase observed at low temperatures. Are important issue is toestimate in detail to what extent the rising temperature could destabilize SOC and make it available
for the decomposition process. The proportion of SOC stored in the world’s soils is still argued and
it is vulnerable to the impacts of warming of this century (Crowther et al., 2016).
In this study, we model approaches of changes in carbon availability by microbial activity thatare needed to have a better understanding of the Red-yellow soil carbon. The Amazon area has an
ecological function connected with the SOC, respiration rate, decomposition of organic matter, andestimation of conservation strategies that must be investigated.
OBJECTIVE
This study aims to determine the Temperature Sensitivity (Q10) coefficient of the Red-yellow soilorganic carbon, under different conditions of temperature (25 and 35ºC) and estimate its conservation
strategy using biochar. The present research provides a new mechanism of climate change mitigation
and a better understanding of soil and biochar.
METHODOLOGY
Soil Sample Source and Preparation
The current investigation involved sampling and analyzing three different sites of Red-yellow soil tomeasure parameters such as SOC and SRR. The sites were selected from Miyako Island, which islocated in Okinawa Prefecture, south of Japan. The soil sample was collected from a non-disturbed
forested area with four repetitions at each site (Carter and Gregorich, 2008). 1000g of soil was
sampled, after that, air-dried soil was sieved and weighed into a labeled tray followed by adding 5%(w/w) of biochar as a biochar treatment and 0% of biochar for control. Samples were kept at
approximate field capacity moisture conditions. Each treatment was divided into soil at ambientconditions (25ºC) and warm conditions (35ºC), and biochar rate (0% and 5%).
Soil Organic Carbon Determination
Each one of the treatments and repetitions was analyzed by the spectrophotometric procedure oforganic carbon contents of soil (Wallinga et al., 1992). 50 mg (±0.5 mg) of soil was weighed 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 sulfuric acid wasadded followed by putting the flasks in a boiling water bath for 45”. The samples were cooled in thesink and made up to the volume with distilled water. The samples were centrifuged for 10” at 1000
g force.
For the preparation of the standard series, 100 mL flasks containing 1000 mg sodium oxalate
with volumes of 0, 25.0, 50.0, 75.0 and 100.0 mL were used as standard into the volumetric flask.
These standard series worked as 0, 5, 10, 15, and 20 mmol Cr+3 per liter of solution of standard series.
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The absorbance of spectrophotometer Beam 4 nm was measured in a 1 cm cuvette at a wavelengthof 590 nm within 2 hours after oxidation. SOC percentages 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
10 g of air-dried soil was weighed from each treatment into a 450 mL glass bottle followed by adding
3 mL of distilled water. The soil and water were mixed in the bottles and then covered with perforated
films to reduce evaporation. The SRR was determined by using the infrared gas analyzer IR400 attime zero and measured 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 using Eq. (1),𝑆𝑅𝑅 = (𝐶𝑂2𝑓 − 𝐶𝑂2𝑖 ) ∗ 𝑉 ∗

1000

(1)

𝑆

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 number ofsoil (S) was 10.0 g. Four repetitions were measured for each one of the treatments.
Temperature Sensitivity (Q10)
The temperature response of SR was estimated through a Q10 function using Eq. (2),10

𝐶𝑖35º𝐶 −𝐶𝑓35º𝐶 𝑇𝑅−𝑇𝑊

𝑄10 = (𝐶𝑖25º𝐶 −𝐶𝑓25º𝐶)(2)

where Q10, the dependent variable, is the temperature sensitivity of SOC (carbon fluctuation
coefficient at one temperature over the flux of a temperature 10º higher), Ci and Cf are the initial andfinal carbon respectively (at 25ºC and 35ºC), and finally, TR is the temperature at the regularcondition and TW is the warmer temperature of soil (Meyer, et al., 2018).
Statistical Analysis
The comparison of the average of each one of the treatments was analyzed using the Shapiro-Wilk
Normality and Levene Homogeneity test. The one-way ANOVA tests were performed to determine
if there were differences through variance analysis. Then, the Tukey test was applied to determine
the differences 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
The fluctuation of SOC in a period of 150 days at different treatments of temperature and biochar isshown in Fig. 1. The SOC started at similar conditions, with a value of around 10 mg/g in alltreatments. However, values of SOC were decreasing gradually for different rates. Firstly, the resultof soil at 25ºC vs. 35ºC with no biochar (Fig. 1a) showed a significant effect of the temperature in
the loss of carbon. At day 150, the 35ºC was 3.65 mg/g, considerably lower than 25ºC soil with 6.02
mg/g (p<0.05). This difference was described by McTiernan et al. (2003), where the decomposition
rate of carbon components increased as temperature rose and was faster in tropical systems.
The addition of biochar kept the carbon content slightly constant. This is shown in Fig. 1b,
where the values of treatments started at just over 10 mg/g and decreased just above 7 mg/g. The
addition of biochar can increase the SOC (Singh et al., 2012) with the carbonized biomass having aslower decomposition process than fresh plant residues that are kept in the soil for longer periodsⒸ ISERD

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depending on the amendment type, type of soil, soil conditions and plants, values even in warm
conditions kept constant most of the experiment time. Figure. 1c compares treatments in ambientconditions (25ºC) for 150 days. As expected, the reduction of soil carbon was lower than treatment
at warmer conditions, moreover, the addition of biochar increased values of soil carbon by 1 mg/g.

Fig. 1 Soil organic carbon decomposition in 150 days in different conditionsa) no biochar addition at 25ºC vs 35ºC; b) biochar addition at 25ºC vs 35ºCc) 25ºC with biochar vs no biochar; and d) 35ºC with biochar vs no biochar.

The most remarkable outcome was the contrast of treatments at higher temperatures. Figure 1d
provides information about the effect of temperature in soil with biochar addition. As with theprevious experiment, values of SOC started above 10 mg/g, followed by a considerable reduction
after 150 days. The 0% biochar sample drastically reduces the SOC amount from 10.05 mg/g at day
0 to 3.65 mg/g at day 150. This reduction is explained clearly in different experiences regarding
carbon and organic matter degradation by the effect of temperature (Xu et al., 2019).
On the other hand, the addition of biochar showed a significant difference in the rate ofdegradation and soil organic carbon amount. This value started just below 11 mg/g (10.97 mg/g at
day 0) and decreased gradually to 7.39 mg/g at day 150. This value represents more than double the
0% biochar sample at day 150. The action of biochar seems to have several features that preserveand increase the organic carbon amount in the soil. According to Zimmerman et al. (2011), the highsurface area and porosity of biochar can increase the nutrient retention capacity of soil and improve
the stability of SOC, as well as increase little inputs with higher C: N that will favor the growth andprotection of SOC stocks. Nevertheless, Zimmerman reports the enhanced mineralization of existingsoil carbon in response to biochar addition as found in the soil respiration rate (Fig. 2).
The action of biochar protects the original soil's organic carbon by reducing carbon emissions.
This protection is mainly caused by the variety of aryl functional structures that are derived fromaromatic rings (Atkinson et al., 2010). These two main features make the biochar recalcitrant andstable. First, the structure and porosity that physically avoid leaching and enzymatic breakdown oforganic material and the chemical structure of biochar that relates to the type of biochar andtemperature of production (Kasozi et al., 2010). In this case, the O/C ratio is the essential feature of
the recalcitrance, which keeps the soil organic carbon at a higher level.
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The soil respiration showed different rates per month. It can be seen in Fig. 2a that the effect oftemperature was slightly higher at the beginning of the experiment, yet there were no significant
differences at day 150. Values started over 8 µL CO2/h/g and decreased just over 2 µL CO2/h/g. The
addition of biochar had a different effect on SRR, showing a higher release of CO 2 at 35ºC. In thelast three months of the analysis, there was a significant effect between the biochar application andno application (Fig. 2b).

Fig. 2 Soil respiration rate in 150 days in different conditionsa) no biochar addition at 25ºC vs 35ºC; b) biochar addition at 25ºC vs 35ºCc) 25ºC with biochar vs no biochar; and d) 35ºC with biochar vs no biochar

At ambient conditions (25ºC), the SRR did not show significant changes to the effect of biochar.
Values kept constant, starting just over 8 µL CO2/h/g and dropping just below 2 µL CO2/h/g as shownin Fig. 2c. On the other hand, Fig. 2d shows the increase of SRR with the addition of biochar in thelast period of analysis. By the addition of biochar, values started around 12 µL CO2/h/g and dropped
to 4 and 2 µL CO2/h/g at 35ºC and 25ºC respectively. The increase in temperature in soil reflects asignificant change in microbial activity in the short term. The addition of biochar in soil has affected
the SOC amount but the effect on SRR does not show a stabilization in the short-term, as this depends
on temperature and microbial activity (Xu et al., 2019). Additionally, Xu et al. (2019) describe theactivation and stabilization of carbonized material over a longer period (more than one year), which
increases the amount of soil carbon and reduction of CO2 emission.
Finally, the temperature sensitivity (Q10) described as a coefficient of the effect of temperature
in soil organic carbon showed a positive effect of the biochar action. As described in Eqs. (3) and(4), the values of initial SOC were 9.53 and 10.05 mg/g for treatment without biochar and withbiochar respectively at 25ºC and 10.97 and 10.27 mg/g for treatment without and with biochar
respectively at 35ºC. After 150 days, final values are 3.65 and 6.02 mg/g for treatment withoutbiochar, and 7.39 and 7.07 mg/g when biochar is applied.
10

𝐶𝑖35º𝐶 −𝐶𝑓35º𝐶 𝑇𝑅−𝑇𝑊

𝑄10 = (𝐶𝑖25º𝐶 −𝐶𝑓25º𝐶)

10

10.05−3.65 35−25= ( 9.53−6.02 )= 1.82Ⓒ ISERD

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10

𝐶𝑖35º𝐶 −𝐶𝑓35º𝐶 𝑇𝑅−𝑇𝑊

𝑄10 = (𝐶𝑖25º𝐶 −𝐶𝑓25º𝐶)

10

10.97−7.39 35−25= (10.27−7.07)= 1.12(4)

The outcome of Eq. (3) provides information on the coefficient value of Red-Yellow soil organiccarbon with no addition of biochar. This coefficient (1.82) represents a higher dependency of SOC
and microbial activity by the effect of temperature. In contrast, the Eq. (4), the addition of biochar
reduced this coefficient to 1.12, which represents a reduction of this dependency and an increase inresilient carbon amount. According to Yang Liu and Zhang (2017), the rate of Q10 reaction value
increases in a certain degree of temperature dependence, thus, the more temperature-dependent the
SOC, the higher the value will be Q10.
CONCLUSIONS
It is demonstrated that Red-Yellow soil is highly affected by the effect of temperature, and it can be
reduced significantly and so, degraded the soil. Although this type of soil has low organic carbon
content, this reduction can be covered by biochar. This black material fulfills a role as a carbon source
to maintain and increase SOC content. Connected to this, the addition of biochar not only affects the
carbon content but increases the amount of recalcitrant carbon in the soil over longer periods. Due tothe high content of Aryl Groups and higher O/C rate, the recalcitrant carbon reduces themineralization and the degradation of carbon, this allows a higher concentration of SOC even inwarm conditions of temperature. It seems to be that biochar works as an important conservation
strategy by reducing temperature sensitivity (Q10). Although studies over a longer period must be
considered, this outcome represents an alternative for Red-yellow soil in climate change impact andconservation of carbon in the soil.
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Atkinson, C., Fitzgerald, J. and Hipps, N. 2010. Potential mechanisms for achieving agricultural benefits frombiochar application to temperate soils, A review. Plant Soil, 337 (1-2) 1-18, Retrieved from DOI https://doi.org/10.1007/s11104-010-0464-5
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, Retrieved from DOI https://doi.org/10.1016/j.foreco.2016.08.002
Carter, M. and Gregorich, E. 2008. Soil sampling and methods of analysis (2nd ed.). Canadian Society of Soil
Science, 33-37. Pinawa, Manitoba, Canada.
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, Retrieved from DOI https://doi.
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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
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Kasozi, G., Zimmerman, A., Nkedi-Kizza, P. and Gao B. 2010. Catechol and humic acid sorption onto a rangeof laboratory, Produced black carbons (Biochar). Environmental Science and Technology, 44 (16), 61896195, Retrieved from DOI https://doi.org/10.1021/es1014423
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, Retrieved from DOI https://doi.org/10.1016/j.soilbio.2020.108055
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Remacle, J. and De Santo, A.V. 2003. Changes in the chemical composition of Pinus sylvestris needle litter
during decomposition along a European coniferous forest climatic transect. Soil Biology and Biochemistry,
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Meyer, N., Meyer, H., Welp, G. and Amelung, W. 2018. Soil respiration and its temperature sensitivity (Q 10),
Rapid acquisition using mid-infrared spectroscopy. Geoderma, 323, 31-40, Retrieved from DOI https://doi.
org/10.1016/j.geoderma.2018.02.031
Pribyl, W. 2010. A critical review of the conventional SOC to SOM conversion factor. Geoderma, 156 (3-4),
75-83, Retrieved from DOI https://doi.org/10.1016/j.geoderma.2010.02.003
Singh, B., Cowie, A. and Smernik, R. 2012. Biochar carbon stability in a clayey soil as a function of feedstock
and pyrolysis temperature. Environmental Science and Technology, 46 (21), 11770-11778, Retrieved from
DOI https://doi.org/10.1021/es302545b
Sparda, A., Miller, R., Anderson, G. and Hsieh, Y. 2016. Real-time soil CO2 respiration rate determination andthe comparison between the infrared gas analyzer and microrespirometer (MicroRes®) methods.
Communications in Soil Science and Plant Analysis, 48 (2), 214-221, Retrieved from DOI https://doi.org/
10.1080/00103624.2016.1254235
Trivedi, P., Singh, B. and Singh, B. 2018. Soil carbon storage (1st ed.). Elsevier, 18, Amsterdam, theNetherlands.
Walinga, I., Kithome, M., Novozamsky, I., Houba, V. and van der Lee, J. 1992. Spectrophotometricdetermination of organic carbon in the soil. Communications in Soil Science and Plant Analysis, 23 (1516), 1935-1944, Retrieved from DOI https://doi.org/10.1080/00103629209368715
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, Retrieved from DOI https://doi.org/10.1016/j.geoderma.2019.02.017
Yang, C., Liu, N. and Zhang, Y. 2017. Effects of aggregate size and glucose addition on soil organic carbon
mineralization and Q10 values under wide temperature change conditions. European Journal of Soil
Biology, 80, 77-84, Retrieved from DOI https://doi.org/10.1016/j.ejsobi.2017.04.002
Zimmerman, A., Gao, B. and Ahn, M. 2011. Positive and negative carbon mineralization priming effects
among a variety of biochar-amended soils. Soil Biology and Biochemistry, 43, 1169-1179, Retrieved from
DOI https: //doi.org/10.1016/j.soilbio.2011.02.005Ⓒ ISERD

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Research article
erdNational versus Local Climatic Variability and Implications
for Communities in Protected Areas: The Case of Lake
Malawi National Park
DICKSON M. MAZIBUKO
Graduate School of Agro-Environmental Science, Tokyo University of Agriculture, Japan
Faculty of Basic and Applied Sciences, University of Malawi, Zomba, Malawi

LAMECK FIWA
Faculty of Agriculture, Lilongwe University of Agriculture and Natural Resources, Malawi

MASKEY SARVESH
Faculty of Regional Environment Science, Tokyo University of Agriculture, Japan

HIROMU OKAZAWA*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Japan
Email: h1okazaw@nodai.ac.jp
Received 22 May 2023

Accepted 20 June 2023(*Corresponding Author)

Abstract Understanding the rainfall dynamics of a nation/region is key to decision-making,especially regarding agriculture within protected areas. This study focused on the area of Cape
Maclear and the adjacent villages located within the Lake Malawi National Park (LMNP). By
gaining insight into how communities whose agricultural activities interact with protectedareas operate, we can gain insight into the long-term sustainability of the LMNP. This study
aimed to assess the historical rainfall dynamics for Cape Maclear using 35-year annual rainfall
and temperature data. Rainfall trends were established and compared with recorded events.
The results indicated that Cape Maclear rainfall trends resonate with reported national drought
events, though with variations. This provides a proxy possibility of making localized
predictions of such events. Analysis of the return period shows annual rainfall of between 500900 mm occurs every 2-3 years, indicating no significant shifts from what has been observedin the past. Due to the sensitivity and fragility of the LMNP ecosystem, there is a need todesign local solutions for the communities living within the park to enable them to better
prepare for future climatic shocks, especially rainfall inadequacies.
Keywords climate, community, drought, rainfall, protected area

INTRODUCTION
Protected areas face several challenges, and one emerging challenge is climate change. Global
climatic change is receiving a lot of attention due to the diverse impacts currently felt and being
projected. Besides broader climatic variabilities, local scale events have been observed. Ngongondo
et al. (2021) assessed drought and floods in Malawi and found variations in the frequency andintensity of these events across all districts in Malawi, indicating that their occurrence is notnationally homogenous. It is predicted that climate change will lead to an altered frequency, intensity,and duration of localized climatic shocks such as droughts and temperature extremes (Chen et al.,2018), with diverse impacts. For communities living in protected areas, whose alternative livelihoods
are sought from protected natural resources, such climatic shocks will impact ecosystems.
Ecosystems impacts vary in their extent, however for communities embedded within protected areas,such impacts could be particularly pronounced for both people and the protected area itself. The
existence of agriculture within protected areas is illegal in most countries (Tranquilli et al., 2014).
For Lake Malawi National Park, however, there are settlements inside the National Park. This isⒸ ISERD

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because, at its founding in 1981, a presidential directive stopped the eviction of any persons that werealready living in the park. The two key livelihood activities within the National Park are agriculture
and harvesting of non-timber forest products (NTFP). Agriculture is thought of as a threat to park
diversity due to people-nature conflicts that result as communities extract livelihoods from protectedareas. These conflicts include deforestation for fuel needs, especially in tropical Africa (Wade et al.,2020), population growth leads to agricultural expansion at the expense of parkland (Sardjo et al.,2022; Joppa et al., 2009), agricultural inputs that negatively impact on diversity within protectedareas, and other direct human-animal conflicts (Mohan, et al., 2020) due to proximity of existence.
For the sustainability of agriculture within protected areas, there is a need for agriculture production
approaches that minimally impact protected area diversity. In Italy, organic agriculture is a dominantagricultural practice within protected areas (Grandis and Triantafyllidis, 2010). The decision
regarding what kind of agricultural practice to enact depends, to some large extent on theunderstanding of the climatic atmosphere of a given locality. In a predicted changing climate, andfor protected areas supporting agriculture, an understanding of local climate dynamics is thus key ininnovating ways to mitigate the impacts. Lake Malawi National Park provides fuelwood that is soldfor income alongside other non-timber forest products that support livelihoods. For communities
existing within protected areas, the need for fertile agricultural land can also lead to Park incursions.
Such incursions could lead to park-community conflicts.
The Lake Malawi National Park (LMNP) was established in 1980 (Abbot and Mace, 1999) as
the only protected area in Malawi with human settlements within its legal boundaries. A government
order at the outset, stipulated that there should be no relocation of communities already living within
the park. This scenario poses unique conservation and sustainability challenges. Key challenges
include overexploitation of fisheries (Sato et al., 2008), deforestation, and climate change (Markham,
2018). Over time, agriculture is emerging as a challenge in part due to the growing human populationthat requires more land for food production. These challenges pose a threat to the biodiversity of
LMNP.
OBJECTIVE
Climatic shocks such as droughts and their associated rainfall variability, could lead to additional
direct and indirect impacts on the protected area. An understanding of historical climatic events could
partially enable some preparedness. However, since the occurrence of such shocks is not nationallyhomogenous, this study sought to assess local rainfall dynamics in the LMNP within the national
context. Specifically, this study sought to qualitatively assess how national drought events comparewith localized rainfall trends. Secondly, to determine local rainfall dynamics during four known
drought years in Malawi and LMNP, and finally to assess how rainfall during drought shocks relates
to impact crop productivity, i.e., the onset of the growing season and overall crop water requirements.

Fig. 1 The study site indicated in map of Malawi(A) showing the relative position of the larger Chembe village community; Mangochi, (B) showing the wider Monkey Bay
area and Chembe village community (within Cape Maclear), (C) and the surrounding Lake Malawi National ParkⒸ ISERD

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METHODOLOGY
The study area comprises five enclaved villages within LMNP; 14 02'S by 34 53'E (Fig. 1). The
park is also a world heritage site. The climate is tropical with annual temperature ranging between
19.6 ºC to 21.4 ºC minimum and between 29 ºC to 30.7 ºC, maximum. Average annual rainfall ranges
between 600 mm to 1600 mm with pronounced variations between seasons. This study used historicaldaily rainfall data for a period of 35 years (1st January 1979 to 31st December 2015) collected fromthe Department of Climate Change and Meteorological Services for Monkey Bay weather station,
which is the closest to the study site. The rainfall dynamics of interest were documented drought andflooding events of 1985-1986; 1988-1989; 1991-1992; 1994-1995; 2001-2002; 2005-2006; and2012-2013. This paper utilized the MarkSim DSSAT Weather Generator to obtain maps and a
Microsoft Excel spreadsheet for computation and graphics.
RESULTS AND DISCUSSION
Reported and Local Rainfall Comparison
The study site generally showed reduced annual rainfall amounts in all the years with nationallyreported drought and flooding events (Fig. 2); five droughts and 2 floods. During the 35 years, rainfall
is observed to have been extremely variable with no clear trend in direction as indicated by the weakcoefficient of determination (r2 =0.003) as shown in Fig. 2. Overall, the data shows more drought
than flooding. It can be noted however that annual rainfall values of above 1,200 mm and below 600
mm are associated with flooding and drought respectively. After 2015, Malawi experienced twoserious flooding events; first, the 2015 La Niña driven flooding and the 2019 flooding caused bycyclone Idai (Ngongondo et al., 2021) mostly affecting the southern region of the country.

Fig. 2 Documented drought (Red) and flooding (Green) seasons/years
between 1980 and 2015 in Malawi and LMNP
Regarding the prediction of localized climatic shocks from national data, this work provides
some positive indications. The national drought records are in sync with local scale data (in terms ofdecreasing trends). This observation thus provides opportunities for the formulation of informed
presumptions regarding possible future climatic shocks for climate modeling studies. While this is
the case, the extent of such shocks, and associated adaptations, should be determined and understoodin a local context.
Rainfall DynamicsⒸ ISERD

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To assess the rainfall dynamics during these drought events, the overall distribution of rainfall wasassessed (Fig. 3). The amounts of rainfall and its duration during the crop growing season in Malawi(October to April) were compared with an 1880-81 season as a reference.

Fig. 3 Relative rainfall amounts across the six months growing season for four seasons
Including reference (Green); showing various skewness of precipitation amounts across the growing season

During the 1985-86 drought, adequate rainfall was available around December after which it
steadily declined. In the 1991-92 season, inadequate rainfall was recorded early in the season andadequate rainfall amount fell after February when no cropping could be done. 1994-95 had lessrainfall except only during January and February. For the 2003-04 season, there were some consistentmedium rainfall amounts throughout the rainy season irrespective of the national drought.
Crop Productivity
First, the general requisite conditions for the onset of the growing season (GS) and the broader
rainfall amount that support crop productivity were assessed. Fiwa et al. (2014) refer to the onset of
GS as when 25 mm of rainfall is experienced in the first 10-day period from a given rainfall event,and at least some additional 20 mm within the next 20 days after the onset of GS. Based on Fiwas’
determination, seasons 1991-92 and 2003-04 for the study site had adequate conditions for planting.
However, Allen et al. (1998) consider an annual rainfall range of 500-700 mm as a minimum
requirement for crop productivity in the case of maize. Maize has been chosen as an example as it isa staple crop for the country. From this criterion, the study site had adequate rainfall for two droughtyears/seasons (1985-86 and 2003-04).
Table 1 Cape Maclear rainfall dynamics during nationally reported drought events
The year/season 1980-81 is included as a reference. RE= Rainfall event; GS= growing season,
and REF means reference (season)

Season1985_86
1991_92
1994_95
200304(REF)-1980_81

First rainfall
event(amount;mm)
10 Oct (0.1)
13 Oct (8.1)
15 Oct (0.9)
18 Nov (0.1)
1 Oct (5.3)

The onset of thegrowing season(Rainfall 1st 10days) (mm)6 Nov (50.5)
10 Dec (76.3)
3 Dec (46.4)
12 Dec (71.6)
30 Nov (185.0)

Intervening RE
(mm)
0 (-)
6 RE (25.8)
0 (-)
4 RE (6.9)
2 RE (26.4)

RE after the
10th day of
GS onset(mm)
6 RE (10.7)
5 RE (21.1)
1 RE (3.1)
5 RE (20.4)
4 RE (42.8)

Annualprecipitation
(mm)
538.8
391.6
388.6
520.5
704.3

The season 1991-92 had satisfied requirements for the onset of the growing season but theannual rainfall was way below the minimum required to support crop production. The apparent
discrepancy between the two crop-growing requirements necessitates that they be considered
concurrently in determining optimal conditions for agricultural productivity. Another keyⒸ ISERD

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observation during the four seasons is a lack of adequate rainfall during one or both key months ofcrop growth (Fig. 3). Issues of spatiotemporal rainfall distribution within the growing season are thus
key in deciding what crops to grow.
Rainfall Return Period
An analysis of the return period shows that the highly expected annual rainfall ranges are between
500-900 mm/y during every 2-3 years. The Return period of 1000 mm/y of annual rainfall indicates
4 years in Fig. 4. From the analysis (and without absolutism), rainfall events above 1000mm(normally observed to be associated with floods) can be predicted to occur at least every 4-5 years.
In a broader sense, the area is not particularly wet. From an agricultural perspective, it is prudent forfarming communities to invest in crops with moderate to low water requirements.

Fig. 4 Rainfall return period for Cape Maclear, Lake Malawi National Park
Implications for Park Enclave Communities
The current global climate change predictions point to an increase in the frequency of drought andflooding shocks (Zhao et al., 2020). Drought events limit crop productivity as moisture is a key
determinant for plant growth. For rural communities, it entails a lack of income from Agri-basedlabor, general food insufficiency, and social instability. These pressures inadvertently lead to the useof other ecosystem services (specifically forests), leading to incursions into protected parkland. The
desperate harvesting and overuse of NTFP and parkland incursions lead to the depreciation ofprotected forest resources. Ultimately, the park’s long-term sustainability will be compromised.
Conservation of agricultural approaches is one way to adapt to rainfall variability and droughts.
Vegetables for example, due to their higher water demand than other crops (Manuel et al., 2017),
might benefit from mulching technology or utilizing seasonal riverbanks with residual moisture. With
the prevailing global change, climate-smart agriculture approaches must be promoted to ensure thesustainable utilization of resources from the National Park.
CONCLUSION
Understanding localized climate dynamics is key as it enables concerned stakeholders to makeappropriate decisions during shock events. The rainfall trends for Cape Maclear resonate withnational ones for drought years reported for Malawi. The association observed between national
rainfall dynamics and those local to Cape Maclear signal the potential of using projected national
future climatic events at a local level; especially where stochastic approaches are utilized. Suchprojection would ensure preparedness for various shocks, ensuring the preservation of the fragile
protected area. Rainfall dynamics during drought years generally indicate amounts acceptable forcrop production but with uneven seasonal distributions. These seasonal distributions are hard toⒸ ISERD

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predict, but the production of early maturing crops could be a good safety net. Overall, there exist
differences in rainfall spread, amounts, and the onset of growing seasons. The main limitation of thestudy has been a focus on rainfall only and a lack of verification of the observed climate dynamics
and actual productivity assessments. Future studies should focus on other climate variables such astemperature and how associated impacts on agricultural production.
ACKNOWLEDGEMENTS
The authors are particularly appreciative to Mr. John Matewere and Mr. Brighten Ndawala (theleaders of a community vegetable garden in Chembe Village, Cape Maclear, Mangochi, Malawi) for
fruitful discussion and background information. This paper is based on a broader idea conceived
during this discussion. We thank Prof. Tetsu Sato, the principal investigator of SATREPS, and all
the members of the “Integrated Natural Resource Management System in Lake Malawi National
Park (IntNRMS) Project” under the SATREPS program.
FUNDING
This study was funded by the “Integrated Natural Resource Management System in Lake Malawi
National Park (IntNRMS) Project” under the SATREPS program provided by the JST and JICA
(JPMJSA1903). This work was also supported by research programs of the Tokyo NODAI ResearchInstitute, Tokyo University of Agriculture.
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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. Santa Pandit, Institute of Environmental Rehabilitation and Conservation, Japan
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
Prof. Dr. Ping Li, Institute of Grassland Research, China
Prof. Dr. Dieter Trautz, Osnabrück University of Applied Sciences, Germany
Dr. Sri Wahyuni, Islamic University of Riau, Indonesia
Dr. Kasumi Ito, Nagoya University, Japan
Prof. Dr. Nang Hseng Hom, Yezin Agricultural University, Myanmar
Prof. Dr. Junaid Alam Memon, Institute of Business Administration Karachi, Pakistan
Prof. Dr. Anthony Makinato Penaso, 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-Ddistrict, 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,every article or report published in this journal was presented at the International Conference on
Environmental and Rural Development (ICERD) that was collaborated with the United Nations University
Institute for the Advanced Study of Sustainability.

IJERD – Environmental and Rural Development

Vol. 14 No. 1

June 2023