ISSN 2185-159X

erd

International Journal ofEnvironmental and Rural Development

Volume 7 Number 2

December 2016

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 CABI International, EBSCO, Google Scholar, 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. Jeeranuch Sakkhamduang, Institute of Environmental Rehabilitation and Conservation,
Southeast Asia Office / Association of Environmental and Rural Development, Thailand
Dr. Junaid Alam Memon, Pakistan Institute of Development Economics, Pakistan
Dr. Julian Torillo, Jr., Bohol Island State University, Philippines
Dr. Carlos Onan Tovar Mendoza, Honduras Embassy in Japan, Japan
Editorial Advisory Board:
Dr. Venkatachalam Anbumozhi, Asian Development Bank Institute, Japan
Dr. Robert J. Farquharson, The University of Melbourne, Australia
Prof. Dr. Keishiro Itagaki, Tokyo University of Agriculture, Japan
Dr. Chuleemas Boonthai Iwai, Khon Kaen University, Thailand
Prof. Dr. Arata Koga, University of Veterinary and Animal Science, Pakistan
Prof. Dr. Robert J. Martin, University of New England, Australia
Prof. Dr. Bunthan Ngo, Royal University of Agriculture, Cambodia
Dr. Hiromu Okazawa, Tokyo University of Agriculture, Japan
Prof. Dr. Salvador Catello, University of the Philippines, Philippines
Dr. Rajendra P. Shrestha, Asian Institute of Technology, Thailand
Prof. Dr. Murari Suvedi, Michigan State University, USA
Prof. Dr. Mario T. Tabucanon, United Nations University, IAS, Japan
Dr. Vidhaya Trelo-Ges, Khon Kaen University, Thailand
Editorial Secretariat:
Dr. Shinobu Terauchi, Institute of Environmental Rehabilitation and Conservation, Japan

IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Contents
Soil Types and Geographical Forms of the Degraded Uplands of Bohol, Philippines
Jose T. Travero

1

Influence of Dissolved Organic Carbon on the Ecotoxicology of Copper on Aquatic Biota:
Implication for the Revision of Water Quality Standardization in Cambodia
Lyly Soeung and Chuleemas Boonthai Iwai

6

Influence of Water Hardness on Ecotoxicology of Copper on Aquatic Biota:
Implication for the Revision of Water Quality Standardization in Lao PDR.
Naksayfong Khounnavongsa and Chuleemas Boonthai Iwai

12

Comparison of the Water Footprint of Cassava and Sugarcane in Northeast, Thailand
Naruemol Kaewjampa, Nipaporn Chaisri
and Chuleemas Boonthai Iwai

18

Variation in Storage Temperatures for Foot and Mouth Vaccine in Cambodia
Socheat Sieng, Stephen. W. Walkden-Brown and James Kerr

24

Soil Amendments for Maize Cultivation by Crop Rotations in Upland Cropping Systemsof Southeast Cambodia
Tara Pin, Kongkea Phan, Vannaro Pin, Oeun Hornand John M. Schiller

32

Improving Upland Rice Production for Sustainability of Rice Self-Sufficiency
in Ratanakiri Province, Cambodia
Sophal Var, Edna A. Aguilar and Pompe C. Stacruz

38

Current Agricultural Conditions and Constraints in Paktya Province of Afghanistan
Abdul Malik Dawlatzai and Machito Mihara

44

The Analyses of Efficiency and Factors Affecting Efficiency of Agricultural Cooperatives
in Lower Northern Region of Thailand
Anucha Wittayakorn-Puripunpinyoo and Naiyana Jullaphun

52

Diversity of Aquatic Insects in the Organic and Conventional Rice Fields in Khon Kaen Thailand
Duangrat Thongphak and Chuleemas Boonthai Iwai

57

Variation in Grain Morphology of Upland Rice Varieties from Luang prabang Province Lao PDR
Vua Xiongsiyee and Chanakan Prom-U-Thai

63

Influence of Coral Nursery Units on Fish Assemblage
Jesrelljane Aaron-Amper, Samuel J. Gulayan
and Josueh M. Gulayan

70

Utilization of Corncob as Feedstuff on Growth Performance, Feed Utilization
and Carcass Composition of Nile Tilapia (Oreochromis niloticus L.)
Rungkan Klahan, Panuphong Yotha andMontree Punyathong75

Characteristics of Transformation of Traditional Upland Farming System in Cambodia:
A Case Study of Snuol Commune, Kratie Province
Shinobu Yamada, Machito Mihara and Kumiko Kawabe

81Comparison of Rice Plant Development with Different Transplanting Density
under SRI Practices in the Lysimeter
Ishwar Pun, Eiji Yamaji and Sophy Ches

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Adaptation Strategies to Changing Environment by an Organic Farm in Laguna, Philippines
Nina Shimoguchi and Loida Mojica

93

Diversity of Plant Growth Promoting Rhizobacteria Communities Associated with Thiamethoxam
in Cassava Production Systems
Phrueksa Lawongsa and Pimupsorn Panomkhum

99

Impact Assessment of Land Use Change on Ecosystem Services and Livelihood Security of Rural
Highland Communities in Saysathan District, Sayaboury Province, Lao PDR
Bouavonh Biachampah, Panomsak Promburom
and Budsara Limnirankul

106

Investigation of Vibration Characteristics of a Hand Tractor using MEMS Sensor
Phon Sovatna, Eiji Inoue, Muneshi Mitsuoka and Zhen Li

113

Policy Analysis for Biodiversity Conservation in Cambodia: The Protected Areas System
Somaly Chan120

Peanut Yield and Changes of Soil properties by Intercropping in Upland Cropping Systemsof Southeast Cambodia
Tara Pin, Kongkea Phan, Vannaro Pin, Oeun Hornand John M. Schiller

128

Systems Analysis and Modelling of Pollution Loading for Management of Calumpang Riverin Batangas City, Philippines
Diane Carmeliza N. Cuaresma, Ben Patrick U. Soliguin,
Rowena A. Japitana, Ruby A. Abao
and Jesusita O. Coladilla.

134

Differences in Benthic Cover and Fish Assemblage Inside and Outside Marine Protected Areas
Jesrelljane Aaron-Amper and Samuel J. Gulayan

141

Influence of Meteorological Variable Combinations on Reference Evapotranspiration Estimatedby the FAO56 Penman-Monteith Method
Hiromu Okazawa and Yasushi Takeuchi

147

Determining C Factor of Universal Soil Loss Equation (USLE) Based on Remote Sensing
Kuang Ting Kao, Ayako Sekiyama and Machito Mihara

154

Factors Affecting Householders’ Acceptance to Adopt Reduce, Reuse and Recycle - 3Rs Programin Domestic Waste Management in Mekong Delta, Vietnam
Ngo Thi Thanh Truc and Nguyen Thi Thu Trang

162

Earthworm Communities and Activities in Rice Ecosystem under Different Soil Salinity Levels
in Northeast Thailand
Ajcharawadee Kruapukee, Chuleemas Boonthai Iwai andNaruemol Kaewjampa

169

Spatial Analysis of Ecosystem Disservice via Disamenity of Mosquitoes– A Case Study in Nagoya City, Japan
Kiichiro Hayashi, Akira Sugiyama and Makoto Ooba

174

Socio-Economic and Spatial Evaluation of Ecosystem Services in Nagoya, Japan
Makoto Ooba, Hideyuki Ito and Kiichiro Hayashi

182

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Research article
erd

Soil Types and Geographical Forms of the Degraded Uplandsof Bohol, Philippines
JOSE T. TRAVERO*
Bohol Island State University, Bohol, Philippines
Email: kinandamata@gmail.com
Received 5 January 2016

Accepted 11 July 2016(*Corresponding Author)

Abstract The main objective of this study was to identify the soil types and geographical forms
in the degraded uplands of Bohol. This was accomplished by gathering secondary data fromconcerned institutions and from previous research results. Bohol is geographically locatedbetween 123°40' and 124°40' East longitude and extends from 9°30' to 10°15' North latitude, inthe central portion of Visayas. It is generally flat and plain with only few mountainous areas at
the northeastern portion suitable for massive cultivation of agricultural products. Some of thesemountainous areas, particularly those preserved from degradation, can serve as habitat forinteresting flora and fauna as well as natural land forms that travelers look for, such as thelandform for which Bohol has been noted, the Chocolate Hills. The existing general land use
data of Bohol has 13 categories. The top three categories in terms of area are the agriculturalland, timberland and infra utilities. Agricultural land constitutes about 66.54% of the province
total land area while timberland is only 24.6%. Approximately 167,160 hectares or 40.6% of
the total provincial land area have slope gradients of 0-8%, largely covering the central ofnorthern areas which comprise the prime agricultural zone utilized or irrigated and rainfed
palay and corn production. The areas with 8-18% slopes accounted for 29% which is mostly
planted with coconut, corn and subsistence crops and open/idle and eroded land areas. The
rolling to mountain areas with slopes of 18% and above cover about 123,930 hectares or 30%
of Bohol land area. Areas with slopes of 18% and above have been disturbed and exploited
particularly for subsistence farming. Soil types of the degraded uplands of Bohol are ofdifferent soil classification. The most extensive soil type is Ubay clay which occurs from thecentral (Carmen and Sierra Bullones) to the north and northeastern (San Miguel to Alicia) andnorthwestern areas of Bohol. Faraon clay predominates at the southern municipalities of Lila,
Dimiao, Valencia and Garcia Hernandez.
Keywords soil types, degraded uplands, rainfed palay, subsistence farming

INTRODUCTION
Bohol is an island province in Central Philippines. With a land area of 4,821 square kilometers (1,861
sq mi) and a coastline 261 kilometres (162 mi) long, Bohol is the tenth largest island of the Philippines.
The terrain of Bohol is basically rolling and hilly, and about half the island is covered in limestone.
Near the outer areas of the island are low mountain ranges. The interior is a large plateau with irregular
landforms. Chocolate Hills are more than 1,200 uniformly cone-shaped limestone hills named for thegrass growing on the hills that turns brown in the summer, making the landscape look like chocolate
mounds.
Bohol is geographically located between 123°40' and 124°40' East longitude and extends from9°30' to 10°15' North latitude, in the central portion of Visayas. It is generally flat and plain with only
few mountainous areas at the northeastern portion suitable for massive cultivation of agricultural
products. The slopes of these mountainous areas have good potential for commercial/urban and even
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industrial site development because of their natural drainage capacity. Some of these mountainous
areas, particularly those preserved from degradation, can serve as habitat for interesting flora and fauna
as well as natural land forms that travelers look for, such as the landform for which Bohol has been
noted, the Chocolate Hills, (Bohol Provincial Agriculture Profile, 2011). Cramb (2000) as cited by
Newby and Cramb said that land degradation in densely-populated upland areas represents major
environmental threats. (Newby and Cramb, 2007)
This study was done to identify the soil types and geographical forms in the degraded uplands ofBohol province through secondary data.
METHODOLOGY
The island province of Bohol is the tenth largest island in the country. Geographically, it lies between
123 40’ and 124 40’ East longitude and extends from 9 30’ to 10 15’ North latitude This oval shaped
province is located in the central portion of the Visayas lying between Cebu to the northwest and Leyteto the northeast. It has a land area of 4,821 square kilometres (1,861 sq mi) and a coastline 261
kilometres (162 mi) long (OIDCI, 2006).
Collection of data was mainly done through the access of secondary sources available in aparticular government agency like the Office of the Provincial Agriculturist of Bohol, the Local
Government Units and the Department of Agriculture of the national government of the Philippines.
The researcher has also collaborated with the Agricultural Training Institute through the conduct ofFocus Group Discussion with the upland farmers to validate the information on soil types andgeographic forms in their respective areas.
The degraded agricultural upland sites being observed by the researcher include the farmcommunities of Carmen which is an interior municipality and central part of Bohol and the degradedupland farms of Mayana, Jagna and Taytay, Duero in the eastern part of the province.

Fig. 1 The study site: Bohol, Central Philippines
RESULTS AND DISCUSSION
Geologic Features
As manifested in the project preview of an Australian Center for International Agricultural Research(ACIAR) funded project, within the agricultural province of Bohol, 45% of the island is designated as
agricultural land and supports 80% of the island’s population. However, nearly two thirds of the
agricultural land has a slope of greater than 18% and receives more than two metres of rainfall per year.
In a previous ACIAR project, it was concluded that activities that have the highest adverse impact onⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

agricultural sustainability (and therefore long term economic sustainability) in the upper Inabanga (thelargest watershed on Bohol), included: up and down cultivation on sloping lands, continuous use ofnutrient-depleting crops such as corn and cassava, and extensive cultivation of steep upland soils(ACIAR, Bohol, 2012).
Bohol may have been developed from the magnetic tectonic mechanism which resulted from theunder thrusting of the southwest Philippine Plates east of Samar Island and Surigao in Northern
Mindanao. The Mines and Geosciences Bureau of the Department of Environment and Natural
Resources showed eleven (11) major geologic formations in the Bohol mainland and offshore islands.
The most extensive are Carmen formation, Maribojoc and Wahig limestones, Ubay volcanic andKabulao conglomerates (OIDCI, 2006).

Fig. 2 The degraded uplands of the central part of Bohol
Physiography
Bohol’s mainland exhibits the following salient physiographic units. The east and west coast display
northeast trending ranging up to 870 meters in elevation (Mt. Mayana) that drops steeply to the coast.
These ranges reflect the major structural units of the island. The central (Carmen area) and northernpart of the island (Trinidad) are vast expanses of relatively rolling plains and flat lands.
The development of beautifully-arranged, symmetrically formed “haycock hills” in CarmenBatuan and Bilar - Balilihan area in the east central part of the island is suggestive of well-definedsystem of shears and joints. An elongated cluster of hills of moderate height lies in the northeasternpart of the island (Ubay area).
An east-west ridge connects Alicia with Carmen
The Anda Peninsula and Loon Peninsula strongly suggest elevated plateaus, andAt least five different Plio-pleistocene terrace levels ranging in height from 10 to 300 meters havebeen etched both in Carmen sandstone and shales and Maribojoc limestones.

Fig. 3 The severely degraded upland farms of BoholⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Soil Types
The Bureau of Soils and Water management–Land Resources Evaluation Project (BSW-LREP)
identified 22 soil types within province. Of these soil typologies, the most extensive is Ubay clay
occurring from the central (Carmen and Sierra Bullones) to the north and northeastern (San Miguel to
Alicia) and northwestern areas. Faraon clay predominates at the southern municipalities of Lila,
Dimiao, Valencia and Garcia Hernandez. The other soil types with relatively larger area coverage
include the Batuan - Faraon complex, Ubay clay loam, Sevilla clay and Annam clay.

Fig. 4 Map of soil types of Bohol

Fig. 5 Farmed steep slopes are common sites in the uplands of Bohol
CONCLUSION
Bohol is a limestone province with rolling and hilly terrain and has mountain ranges near the outerareas. The interior part is a large plateau with irregular landforms with the very distinct haycockformation called Chocolate Hills. The province has twenty two (22) soil types with Ubay clay
occurring from the central to the northern part and Faraon clay predominates the southern part of theprovince.

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

ACKNOWLEDGEMENTS
The researcher gratefully acknowledged the generosity of the Agricultural Training Institute (ATI) andthe Office of the provincial Agriculturist (OPA) for the valuable opportunity of collaborative activities
in the upland farms of Bohol and the Barangay Officials for the informal exchange of information andfor the community profiles.
REFERENCESACIAR, Bohol. 2012. Evaluation and adoption of improved farming practices on soil and water resources in
Bohol Island, Philippines.
Bohol Provincial Agricultural Profile. 2011. Department of Agriculture, Regional Field-Unit 7. Agribusiness andMarketing Assistant Division. Mandaue City, Philippines.
Newby, J. and Cramb, R.A. 2007. Economic impacts of the adoption of conservation farming in the Central
Philippines, A Preliminary Report. Australian Agriculture & Resource Economics Society 51 st Conference,
Feb. 13-16, 2007, Queenstown, New Zealand.
Orient Integrated Development Consultancy, Inc. (OIDCI). 2006. Bohol Agricultural Master Plan, CY 2006-2026,
Available online: http//www.bohol.gov.ph/plans/htmlⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Research article
erdInfluence of Dissolved Organic Carbon on the Ecotoxicology of
Copper on Aquatic Biota: Implication for the Revision of
Water Quality Standardization in Cambodia
LYLY SOEUNG
Faculty of Agriculture, Khon Kaen University, Khon Kaen, Thailand
Email: lylysoeung@gmail.com

CHULEEMAS BOONTHAI IWAI*
Faculty of Agriculture, Khon Kaen University, Khon Kaen, Thailand
Email: chulee_b@kku.ac.th; chuleemas1@gmail.com
Received 14 January 2016

Accepted 11 July 2016(*Corresponding Author)

Abstract The Mekong River is one of the world’s greatest river systems and sustains humanlife and ecosystems. The livelihoods of 60 million people who live along the Lower Mekong
Basin (LMB) rely on both the economic resource and the ecological health of the river. In thisstudy, US EPA method was used for the acute toxicity with different water dissolved organiccarbon (DOC) of Mekong River in Cambodia on Chironomus javanus and fish Nile tilapia (O.
niloticus) to modify the effecting of DOC on copper toxicity. Both C. javanus and Nile tilapia
were significantly less sensitive to copper in water high DOC (5.74 mg/L DOC), compared towater low DOC (1.12 mg/L DOC) exposures. The effect of DOC, as humic acid source on theacute toxicity of copper (Cu) to C. javanus and Nile tilapia also was investigated. The
mortalities for both species increase with increasing copper concentration, but LC50 value
decreased as more toxic on Nile tilapia and C. javanus. This gave an order of toxicity of copperin water with low DOC > water with high DOC at the end point of LC50. DOC might provide
protection against Cu toxicity in the freshwater in term of completive between copper form andDOC. The result of the LC50 with 95% confidence limit obtained at 48 hr in tap water on Moina
macrocopa, C. javanus, Grass Carp (Ctenopharyngodon idella) and Nile tilapia were 12 µg/L,
16399 µg/L, 118 µg/L and 1383 µg/L, respectively. This gave an order of toxicity of copper in
tap water with M. macrocopa> Grass Carp > Nile tilapia> C. javanus. Also, it could be notedthat Moina was the most sensitive followed by Grass Carp, Nile tilapia, and C. javanus tocopper. Present study indicated that water chemistry parameters can influence on copper
toxicity to tropical freshwaters biota. Exposures in this series of laboratory experiment will
provides a worst-case scenario and useful for determine the risk assessment of copper on
Mekong tropical freshwater animals.
Keywords copper, water quality, aquatic biota

INTRODUCTION
The livelihoods of 60 million people who live along the Lower Mekong Basin (LMB) rely on both theeconomic resource and the ecological health of the river MRC (2015). However, the development
activities during the past decade and currently, including mining, industries, agriculture, deforestationand household wastes, have caused of extensive soil erosion and contributed increasingly to transfer ofenvironmental levels of heavy metals especially copper (Cu) into the Mekong River (Ti and Facon,
2004; Coates et al., 2006).

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Copper (Cu) is known as the important that all living organisms require its small amounts (5-20µg/g) to survive Solomon (2009). However, too much Cu concentration more than (20 µg/g) will
become toxic Wright and Welbourn (2002) and Bradl (2005). Cu has been documented as one of themost toxic metals to aquatic organism and ecosystem (Bradl, 2005; Carreau and Pyle, 2005; Scudder etal., 1988). Impacts of Cu on an aquatic atmosphere are complex and depend on the physicochemical
characteristics of water as mentioned by Kamunde and MacPhail (2011) and Nadella et al. (2009).
Therefore, the acute toxicity of Cu to fish, invertebrates and other aquatic organisms are influenced bywater quality parameters such as hardness, alkalinity, pH and dissolved organic carbon (DOC) (Linbo
et al. 2009; Santore et al., 2001; U.S.EPA, 2002). And the most effective parameter for reducing of Cu
toxicity to fish is DOC (Linbo et al., 2009). According to Liu and Sheu (2003) and U.S.EPA (2002)
DOC is a vital water quality parameter and it is also a primary food source in the aquatic food web
which supports growth of microorganisms and Complex to the metal form.
Many research papers were designed and conducted on ecotoxicology of Cu worldwide, but mostof them focused on temperate aquatic species. The information on the impact of toxicity effects ofsoluble copper on the tropical aquatic biota is limited. So the ecotoxicology of Cu on aquatic biota with
Mekong River Cambodia compared with dosed distilled and tap water will be a good representative fortropical aquatic species. In the present study, the ecotoxicology of copper on aquatic biota under
different water DOC were investigated in order to help and protect the Mekong River in the future andfor implication for the revision of water quality standardization in Cambodia.
OBJECTIVE
The objective of the study is focus on ecotoxicology of copper on aquatic biota under different water
dissolved organic carbon.
METHODOLOGY
Water sampling: In this study, water samples were collected at two sites in Cambodia's Mekong River,which focus on different water dissolved organic carbon. The site 1 is located in Stung Treng at
13°30'52.50"N/105°55'54.00"E, next to the Lao PDR border. The site 2 is located in the Kampong
Cham at 11°59'18.77"N/105°28'10.26"E, next to the Vietnam border.
Test organisms: The native organisms used in the present study were Moina (Moina macrocopa),
Chironomus javanus, Grass Carp (Ctenopharyngodon idella) and Nile tilapia (Oreochromis niloticus).
These species were provided by the Department of Fisheries, Khon Kaen, Thailand and have been
cultured in at ecotoxicology laboratory of Khon Kaen University, Thailand.
Chemical and test procedure: The standard stock solution (100 mg/L) for studied metals was freshly
prepared by dissolving of copper sulfate CuSO4 5H2O. The test organisms were subjected to different
concentrations of the stock copper solution in each container. The control was kept in experimental
water without adding copper.
Preparation of the standard DOC: The concentration DOC was augmented using a commerciallyavailable humic acid (Aldrich Humic acid (AHA), Sigma-Aldrich, st, Louis, MO, USA). DOC test
water were then diluted to the final concentrations (1 and 5 mg/L DOC) to which the animal were
exposed.
DOC analysis: The dissolved organic carbon concentration in each sample of the filtered (0.45 µm)
exposure water was determined by using a Shimadzu total organic carbon analyzer (model 5050A;
Mandel Scientific, Guelph, ON, Canada). The total organic carbon in each sample was calculated
automatically by subtracting inorganic carbon from total carbon.
Toxicity test: Acute copper toxicity experiments were performed for a 4-d period (96h) using small
fishes at 5 days old, the second instar larva of Chironomus javanus and for a 2-day period for MoinaⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2(Moina macrocopa) at < 1 day old. The number of dead organisms were counted every 24 hours andremoved from aquarium as soon as possible. During the toxicity test, organisms were not fed. The
experimental were performed at room temperature of 25±1C°, with a Photoperiod of 16h light: 18h
darkness. All control result in lower mortality, less than 10% which revealed the acceptability of thetest (U.S.EPA, 2002).
Statistical analysis: Toxicological dose-response data involving quintal response (mortality) following
toxicity of copper on the test species were determined by used of Probit Analysis LC50 Determination
Method (SPSS, version 19 software). The rate response determined at the end of the 96-h for Grass
Carp (Ctenopharyngodon idella) and Nile tilapia (Oreochromis niloticus), and 48-h for Moina (Moina
macrocopa) and Chironomids (Chironomidus javanus). Significance in 95% confidence interval (95%
CI) of detect 48 and 96 hour LC50 value were determined using the Chi-Square technique(Ezeonyejiaku et al., 2011).
RESULTS AND DISCUSSION
Water quality: The water quality parameters measured during the test at site 1 and site 2 were pH 7.77
± 0.02 and 7.83±0.00, Conductivity 191± 1.53 and 192.33±1.03 µS/cm, TDS 45±005 and 50±0.89
mg/L, dissolve oxygen 10.46±0.05 and 8.23±0.04 mg/L, and total hardness (mg2+ and Ca2+) 88±4 and
112±4 mg/L as CaCO3, respectively. The mean value of other water quality parameters such as DOC,
BOD and alkalinity were 5.74±0.08 and 1.12±0.26 mg/L, 541.86±7.39 and 542.86±7.39 mg/L,
1.33±0.20 and 0.4±0.17 mg/L and 118.66±4.61and 113.33±2.30 mg/L, respectively. And a summary ofmeasured heavy metal data for all experiments (e.g., Cu, Zn, Mn, Fe, Pb, Cd, Cr, Mg and Ca) wereshown in (Table 1).
Table 1 Physical- chemical composition of Mekong River in Cambodia
Physical-chemical variable (units)
Site1
Site2
pH
7.83±0.00
7.77±0.01
Temperature (C°)
27.4±0.26
27.38±0.25
DO (mg/L)
8.23±0.04
10.46±0.05
EC (µS/cm)
192.33±1.03
191.66±1.12
TDS (mg/L)
50±0.89
45.66±0.81
Alkalinity (mg/L as CaCO3 )113.33±2.30118.66±4.61
Hardness (mg/L as CaCO3)
112±4
98.66±8.32
BOD (mg/L)
0.4±0.17
1.33±0.20
DOC (mg/L)
1.12±0.26
5.74±0.08
Cu (µg/L)
0.005±4.98
0.005±3.38
Zn (µg/L)
0.003±4.72
0.002±0.14
Mn (µg/L)
0.004±0.13
0.007±0.28
Fe (µg/L)
0.033±0.14
0.022±0.38
Pb (µg/L)
0.005±5.60
0.002±2.85
Cd (µg/L)
0.0002±2.240.0009±0.11
Cr (µg/L)
0.019±1.40
0.017±0.74
Mg (µg/L)>5*>5**
Ca (µg/L)>5>5**: The limitation of analytic is not determined we need to make more dilution, Mean (±SE), n=3

The Effluence of DOC of Mekong River on Copper Sensitivity
A strong relationship between DOC concentration and copper toxicity showed in (Table 2). Both Niletilapia and Chironomid were significantly less sensitive to copper at water high (5.74 mg/L DOC),
compared to water low (1.12 mg/L DOC) water exposures. The protective effect of increasing water
dissolved organic carbon against metal toxicity of copper has been reported in a wide range of aquaticⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

life and thus many water quality regulation are adjusted for water DOC USEPA (1996, 2002). DOC
were found to provide significant protection from acute copper exposure as the LC 50 at water (5.74
mg/L DOC) was more than two-fold higher than (1.12 mg/L DOC) of fish Nile tilapia; and more than
one-fold at water (5.74 mg/L DOC) was higher than (1.12 mg/L DOC) of Chironomid. Although there
has been limited study into the effect of exposure water DOC on copper toxicity in Nile tilapia andChironomid, Gillis et al. (2008) studied the acute toxicity test of copper to glochidia (larvae) offreshwater mussel under different water hardness and dissolved organic carbon reported that theaddition of DOC (as Aldrich Humic Acid) 1.6 mg/L with the soft water was the result of decrease in
Cu sensitive as ten- fold increase in EC50 of E. triquetra. In addition, it is interesting to note that thecopper toxicity was affected by the DOC. The outcomes of the present study come in agreement withthe out finding of Mclntyre et al. (2008) who reported that DOC levels of 1-6 mg/L were found topartially restore olfactory capacity in salmon that were exposed to copper.
Table 2 LC50 with 95 percent confidence interval of copper on Chironomid (Chironomus javanus)
and Nile tilapia (Oreochromis niloticus) of two different DOC of Mekong River
Species

DOC(mg/L)

LC50 with 95% Cl (µg/L)
24h
48h
72h
96h
Nile tilapia
5.74
1228
1052
939
742
(1138-1340)(890-1296)(771-1185)(562-981)
1.12
1236
806
561
397
(1128-1371)(494-1334)(129-1177)(123-761)
Chironomid
5.74
8237
5033
2206
853
(5471-32105)(3035-88359)
(-)
(-)
1.12
2864
2443
983
707
(-)
(-)
(-)
(-)
CL= Confidence limit, LC50= Median lethal concentrations, (-) = 95% Confidence limit (lower-upper value) exposure at 96
hours

The Effluence of DOC from Humic Acid Source on Copper Sensitivity
DOC provided by the addition of Humic Acid alone to test waters significantly decrease copper
toxicity to Both Chironomid and Nile tilapia. The mortalities for both species increased with increasing
copper concentration, and the LC50 values decreased indicating more toxicity on Nile tilapia andChironomid. This gave an order of toxicity of copper in water with low DOC > water with high DOC
at the 96hr LC50. DOC appears to provide protection against Cu toxicity in the freshwater bycompleting between free copper and DOC.
Acute Toxicity with Tap Water
The LC50 48 hrs values for copper were 12 µg/L in Moina, 16399 µg/L in Chironomid, 294 µg/L in
Grass Carp and 1869 µg/L in Nile tilapia, respectively (table 3). This gave an order of toxicity ofcopper in tap water with Moina > Grass Carp > Nile tilapia > Chironomid. The outcomes of the present
study came in agreement with those of Mastin and Rodgers Jr (2000) who reported that D. magna was
the most sensitive of nontarget animals tested for all the tree copper herbicides. In similar toxicity
experiments that exposed a heterogeneous assemblage of test organisms to copper, cladocerans (e.g.,
Ceriodaphnia and Daphnia) were the most sensitive species Schubauer-Berigan et al. (1993) and Dobbs
et al. (1994). According to Pokethitiyook et al. (1987) reported that the mean value 24, and 48 hr LC 50
for copper in Moina macrocopa with water pH 29 were 19 µg/L and 17 µg/L, respectively. However,these reports were higher than the present study, suggesting the different in methodologies. The meanvalue 24, and 48 hr LC50 for CuSO4 5H2O in C. javanus were 24127 and 16399 µg/L, respectively.
Hence, the acute test of 48 and 24 hr showed an opposite relationship between LC50 and exposure time,Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

increase in the concentration reduces the time to kill 50% of C. javanus. Previous studies, the 48 hr
LC50 for CuSO4 was 1073 µg/L in C. ramousus third instar larvae Majumdar and Gupta (2012). Other
outcomes Mastin and Rodgers Jr (2000) reported that 48 hr LC50 of midge larvae C. tentans exposed toClearigate and Cutrine-Plus were 373.5 and 460.9 µg/L, These values were considerably lower thanresponding value in C. javanus, indicating higher vulnerability to Cu.
Table 3 LC50 with 95 % confidence interval of copper to Moina (Moina macrocopa) ,Chironomid(Chironomus javanus), Grass Carp (Ctenopharyngodon idella) and Nile tilapia(Oreochromis niloticus) of tap waterSpecies
Moina (Moina macrocopa)
Chironomid (Chironomus javanus)
Grass Carp (Ctenopharyngodon ldella)

Nile tilapia (Orecochromis nileticus)

Test time
24hr
48hr
24hr
48hr
24hr
48hr
72hr
96hr
24hr
48hr
72hr
96hr

LC50 with 95% Cl (µg/L)
46 (33-68)
12 ( - )24127 (13264-36397)
16399 ( - )330 (293-373)
294 (238-353)
232 (180-293)
188 (126-275)
2388 (2261-2592)
1869 (1157-5235)
1740 ( - )1383 (859-2718)

CL= Confidence limit, LC50= Median lethal concentrations, (-) = 95% Confidence limit (lower-upper value) at exposure time

CONCLUSION
DOC appears to provide protection against Cu toxicity in the freshwater by complexing between freeCu and DOC. The present study indicated that water chemistry parameters can influence Cu toxicity totropical freshwater biota. Exposure of the test species to this series of laboratory experiments has
provided useful data for determine the risk of Cu in Mekong river water compared with dosed distilled
and tap water, and for implication for the revision of water quality standardization in Cambodia.
ACKNOWLEDGEMENTS
I would like to thank to Integrated Water Resource Management Research and Development Center inNortheast Thailand, Khon Kaen University and the research collaboration project between Loyola
University Chicago and Khon Kean University supported by International Copper Association, Ltd.
(ICA).
REFERENCES
Bradl, H. 2005. Heavy metals in the environment, Origin. Interaction and Remediation, Elsevier/Academic Press,
London.
Carreau, N.D. and Pyle, G.G. 2005. Effect of copper exposure during embryonic development on chemosensory
function of juvenile fathead minnows (< i> Pimephales promelas</i>). Ecotoxicology and Environmental
Safety, 61 (1), 1-6.
Coates, D., Poeu, O., Suntornratnana, U., Nguyen, T. and Viravong, S. 2006. Biodiversity and fisheries in the
Mekong River Basin. Mekong Development Series.

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Dobbs, M.G., Farris, J.L., Reash, R.J., Cherry, D.S. and Cairns, J. 1994. Evaluation of the resident-species
procedure for developing site-specific water quality criteria for copper in Blaine Creek, Kentucky. Environ
Toxicol Chem., 13 (6), 963-971.
Ezeonyejiaku, C.D., Obiakor, M.O. and Ezenwelu, C.O. 2011. Toxicity of copper sulphate and behavioral
locomotor response of tilapia (Oreochromis niloticus) and catfish (Clarias gariepinus) species. Online J
Anim Feed Res., 1 (4), 130-134.
Gillis, P.L., Mitchell, R.J., Schwalb, A.N., McNichols, K.A., Mackie, G.L., Wood, C.M. and Ackerman, J.D.
2008. Sensitivity of the glochidia (larvae) of freshwater mussels to copper, Assessing the effect of water
hardness and dissolved organic carbon on the sensitivity of endangered species. Aquatic Toxicology, 88 (2),137-145.
Kamunde, C. and MacPhail, R. 2011. Effect of humic acid during concurrent chronic waterborne exposure of
rainbow trout (Oncorhynchus mykiss) to copper, cadmium and zinc. Ecotoxicology and Environmental Safety,
74 (3), 259-269. doi: http://dx.doi.org/10.1016/j.ecoenv.2010.10.007
Linbo, T.L., Baldwin, D.H., McIntyre, J.K. and Scholz, N.L. 2009. Effects of water hardness, alkalinity, anddissolved organic carbon on the toxicity of copper to the lateral line of developing fish. Environmental
Toxicology and Chemistry, 28 (7), 1455-1461.
Liu, C.P. and Sheu, B.H. 2003. Dissolved organic carbon in precipitation, throughfall, stemflow, soil solution,and stream water at the Guandaushi subtropical forest in Taiwan. Forest Ecology and Management, 172 (2–3),
315-325. doi: http://dx.doi.org/10.1016/S0378-1127(01)00793-9
Majumdar, T. and Gupta, A. 2012b. Acute and chronic toxicity of copper on aquatic insect Chironomus ramosus
from Assam, India. Journal of Environmental Biology / Academy of Environmental Biology, India, 33 (1),
139-142.
Mastin, B. and Rodgers Jr, J. 2000. Toxicity and bioavailability of copper herbicides (Clearigate, Cutrine-Plus,and copper sulfate) to freshwater animals. Archives of Environmental Contamination and Toxicology, 39 (4),445-451.
McIntyre, J.K., Baldwin, D.H., Meador, J.P. and Scholz, N.L. 2008. Chemosensory deprivation in Juvenile Coho
Salmon exposed to dissolved copper under varying water chemistry conditions. Environmental Science andTechnology, 42, 1352-1358.
MRC. 2015. Lower Mekong regional water quality monitoring report 2013, MRC Technical Paper, No. 51,
Mekong River Commission, Vientiane, 63.
Nadella, S.R., Fitzpatrick, J.L., Franklin, N., Bucking, C., Smith, S. and Wood, C.M. 2009. Toxicity of dissolved
Cu, Zn, Ni and Cd to developing embryos of the blue mussel (Mytilus trossolus) and the protective effect ofdissolved organic carbon. Comparative Biochemistry and Physiology, Part C: Toxicology & Pharmacology,
149 (3), 340-348. doi: http://dx.doi.org/10.1016/j.cbpc.2008.09.001
Pokethitiyook, P., Upatham, E.S. and Leelhaphunt, O. 1987. Acute toxicity of various metals to Moina
macrocopa. Nat. Hist. Bull. Saim Soc, 35 (1-2), 47-56.
Santore, R.C., Di Toro, D.M., Paquin, P.R., Allen, H.E. and Meyer, J.S. 2001. Biotic ligand model of the acutetoxicity of metals. 2. Application to acute copper toxicity in freshwater fish and Daphnia. Environmental
Toxicology and Chemistry, 20 (10), 2397-2402.
Schubauer-Berigan, M.K., Dierkes, J.R., Monson, P.D. and Ankley, G.T. 1993. pH-dependent toxicity of Cd, Cu,
Ni, Pb, and Zn to Ceriodaphnoa dubia, Pimephales promelas, Hyalella azteca, and Lumbriculus variegatus.
Environ Toxicol Chem., 12, 1261-1266.
Scudder, B.C., Carter, J.L. and Leland, H.V. 1988. Effects of copper on development of the fathead minnow.
Aquatic Toxicology, 12 (2), 107-124.
Solomon, F. 2009. Impacts of copper on aquatic ecosystems and human health. Environ Commun, 25 (8).
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U.S. EPA. 1996. Ecological effects test guidelines. OPPTS 850.1085, Fish acute toxicity mitigated by humic acid.
EPA 712-C-96-117. Washington, DC, USA.
U.S. EPA. 2002. Methods for measuring the acute toxicity of effluents and receiving waters to freshwater andmarine organisms. Environmental Monitoring Systems Laboratory, Office of Research and Development, US
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Wright, D.A. and Welbourn, P. 2002. Environmental toxicology. 11, Cambridge University Press, UK.

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Research article
erdInfluence of Water Hardness on Ecotoxicology of Copper on
Aquatic Biota: Implication for the Revision of Water Quality
Standardization in Lao PDR.
NAKSAYFONG KHOUNNAVONGSA
Faculty of Agriculture, Khon Kaen University, Khon Kaen, Thailand

CHULEEMAS BOONTHAI IWAI*
Faculty of Agriculture, Khon Kaen University, Khon Kaen, Thailand
Email: chulee_b@kku.ac.th; chuleemas1@gmail.com
Received 14 January 2016

Accepted 11 July 2016(*Corresponding Author)

Abstract The ecotoxicology of copper on freshwater organisms were studied using fieldcollected water from two local sites along Lower Mekong Basin in Lao PDR, which focused on
different water hardness 20±2.83 and 108±0.00 mg L-1 as CaCO3 (water in rainy season),105±3.35 and 140±4.00 mg L-1 as CaCO3 (water in dry season) and distilled water wasreconstituted by adding reagent-grade chemicals which reconstituted water hardness 18±3.58
and 86±4.56 mg L-1 as CaCO3. In this study, the US EPA method was used for the acutetoxicity test to juvenile Cyprinidae (Labeo rohita) and Moina macrocopa at different water
hardness. Mortalities were at 24, 48, 72 and 96 hr for L. rohita and 48 hr for M. macrocopa. At
water hardness of 20±2.83 mg L-1 as CaCO3, the percentage mortality of L. rohita was 100% at
96 hr by Cu 0.13 mg L-1. The mortality was 100% at 96 hr of water hardness 108±0.00 mg/L as
CaCO3 at Cu 0.37 mg L-1. There was a 3-fold increase in water hardness (from 20±2.83 and
108±0.00 mg L-1 as CaCO3) and Cu was highly significantly toxic to L. rohita. The percentage
mortality of L. rohita was 100% at 96 hr by Cu 0.37 mg L-1, on 105±3.35 and 140±4.00 mg L-1
as CaCO3, and both were highly significant difference (P < 0.001). A 8-fold increase in water
hardness (from 105±3.35 and 140±4.00 mg/L as CaCO3) and Cu was significantlytoxic to L.
rohita. At 20±2.83 mg L-1 as CaCO3 hardness, the percentage mortality of M. macrocopa of
100% was very highly significant at 48 hr by Cu 0.07 mg L-1, while percentage mortality was
100% at 48 hr of water hardness 108±0.00 mg L-1 as CaCO3 at Cu 0.13 mg L-1, the difference
was highly significant as well. A 3-fold increase in water hardness (from 20±2.83 to 108±0.00
mg L-1 as CaCO3) had significant toxic effect of Cu to M. macrocopa with overlapping 95%
confidence intervals of LC50 values. The percentage mortality of M. macrocopa of 100% at 48
hr by Cu 0.13 mg L-1, on water hardness of 105±3.35 and 140±4.00 m L-1 as CaCO3, were both
highly significant. A 2-fold increase in water hardness (from 105±3.35 and 140±4.00 mg L-1 as
CaCO3) did not significantly (P > 0.05) have toxic effect of Cu to M. macrocopa. The effects of
Cu on organisms depend on water hardness, i.e., increasing water hardness reduce the toxic
effect of Cu on aquatic organism.
Keywords Water hardness, aquatic biota, copper

INTRODUCTION
The Mekong Basin supports about 60 million people, most of whom depend directly on the natural
resource for their livelihood (MRC, 2010; Snidvongs & Teng, 2006). Moreover, activities that discharge
heavy metals directly or indirectly into natural water systems with little or no treatment may cause serious
environmental effects. Heavy metals are widely used in industries and are common water pollutants; thus
knowledge of their toxicity to aquatic organisms are significance (Rathore & Khangarot, 2003).
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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Cu is a significance trace element to organisms, its often found in industrial wastewaters whichbecome extremely toxic for aquatic animals as their concentration in water increase. The hardness ofwater is a major factor which influences the toxic effects of Cu to aquatic organisms because increase inwater hardness can decrease Cu toxicity due to competition between metal ions and Ca2+ and Mg2+ ions
for uptake sites of organisms (Gary, 1996; Yim, Kim, & Kim, 2006).
The levels of Cu and its distribution in natural water bodies in Lower Mekong Basin are not wellknown. Recent investigations suggest that background levels may be higher than expected. However,data on heavy metal toxicity in Laos is limited. Therefore, research on the ecotoxicology of Cu on
freshwater biota of Mekong River in Laos is important.
METHODOLOGY
The study sites were 2 locations at 2 different seasons (rainy and dry seasons) along Lower Mekong
Basin in Lao PDR with focus on different water hardness; Vientiane (17°58´1.18´´N/ 102°35´1.66´´E),a city of around 692,900 inhabitants with a density of 176 people km-1 (Phonvisai, Coowanitwong,
Shapkota, Pradhan, & Hossain, 2006). Vientiane discharges its municipal sewage into ThatLuang
wetland that discharges into the Mekong River downstream of the city. The other site is Pakxan
District (18°22´23.29´´N /103°39´43.85´´E. The sources of pollution in this site include domestic,
industrial waste, agricultural runoff and mining activities. Those sites were chosen due to theirproximity and are with activities that potentially contribute to pollution of the Mekong River (Table 1).
Table 1 Sampling sites based on different water hardness along the Mekong River parts in Laos
(n=3)
Location and Date

Water hardness(mg L-1 as CaCO3)

Latitude (N) andLongitude (E)Rainy season

Pakxan District (13 July,2014)20±2.83(17°58'1.18"N/
102°35'1.66"E)

Rainy season

Vientiane Capital City (12 July,2014)

108±0.00

Dry season

Pakxan District (22 March,2015)

105±3.35

Dry season

Vientiane Capital City (21 March, 2015)

140±4.00(18°22'23.29"N/
103°39'43.85"E).
(17°58'1.18"N/
102°35'1.66"E)(18°22'23.29"N/
103°39'43.85"E).

Table 2 Distilled water reconstituted by adding reagent-grade chemicals to make its characteristics
similar to that of the Mekong River water (n=3)
Water quality parameterspH
EC (μs cm-1)
TDS (mg L-1)
DO (mg L-1)
Hardness (mg L-1 as CaCO3 )Alkalinity (mg L-1 as CaCO3)

Soft water
7.06±0.1
36±0.018±0.06.97±1.6
18±3.5814±2.2

Reconstituted water hardness
Moderate hardness
7.73±0.1
347±0.0
173±0.0
8.66±0.9
86±4.5686±3.6

Distilled water was reconstituted to make it similar water hardness to Mekong River water byadding NaHCO3, CaSO4x2H2O, MgSO4, KCI that following a USEPA procedure to give reconstituted
water hardness as CaCO3 for 18±3.58 mg L-1 and 86±4.56 mg L-1 (Table 2).

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Statistical Analysis
Acute toxicity dose-response data, involving quintal response mortality following toxicity of copper on
the test species; Cyprinidae (Labeo rohita) and Moina macrocopa were determined by using of
PROBIT Analysis LC50 Determination Method (SPSS Statistics Version 20 software). Mortality
response of organisms were recorded when the animals sank to bottom of the containers and become
motionless. The toxicity response determined at the end of the 96 hr for L. rohita and 48 hr for M.
macrocopa. Significance in 95% confidence interval (95% CI) of detect 48 and 96 hr LC50 value were
determined using Chi-Square technique.
RESULTS AND DISCUSSION
Acute Toxicity of Copper on Local Freshwater Organisms; Cypronidae - Labeo rohita and Moina
Macrocopa under Different Water Hardness of Mekong River in Lao PDR during Rainy Season
in 2014
Acute toxicity of Cu to juvenile fish Cyprinidae (Labeo rohita) during rainy season with water
hardness 20±2.8 mg L-1 as CaCO3 was similar to that reported by (Perschbacher & Wurts, 1999) in his
study on Channel Catfish where they reported 100% mortality in treatments containing magnesiumbased 20 and 400 mg L-1 as CaCO3. These results demonstrate the sensitivity of the organism to Cu
concentrations. However, the present study found that at water hardness of 20±2.8 mg L-1 as CaCO3,
the mortality of L. rohita was 100% at 96 hr with Cu concentration of 0.13 mg L-1 (CV < 20%),indicating very high significant difference. A similar result was obtained at 108±0.0 mg L-1 as CaCO3
at Cu concentration of 0.37 mg L-1. . Comparative LC50 at water hardness 20±2.8 and 108±0.0 mg L-1
as CaCO3 resulted to a significant 3-fold increase in the toxicity of Cu to L. rohita (Table 3).
Table 3 Acute toxicity endpoints (LC50) calculated for juvenile fish Cyprinidae (Labeo rohita)
exposed to Cu (mg L-1) into rainy season based on different water hardnesses (20±2.8
and 108±0.0 mg/L as CaCO3)
Rainy season

Rainy season

LC50 (mg/L) 95% Confidence Limits for conc.
20±2.8 (mg/L as CaCO3)
Hour
Estimate
Lower
Upper
24
0.083
0.069
0.106
48
0.065
0.06
0.071
72
0.055
0.045
0.069
96
0.038*
0.021
0.077

LC50 (mg/L) 95% Confidence Limits for conc.
108±0.0 (mg/L as CaCO3)
Hour
Estimate
Lower
Upper
24
0.271
−
−
48
0.157
−
−
72
0.129
−
−
96
0.106*−−

Note: * = significant at 5% level

Cu effects to different water hardness 20±2.8 mg L-1 as CaCO3, the percentage mortality of Moina
macrocopa was 100% at 48 hr by Cu concentration 0.07 mg L-1, indicating test acceptability highly
significant difference, while percentage mortality was 100% at 48 hr of water hardness 108±0.0 mg L-1
as CaCO3 at Cu concentration 0.13 mg L-1, that has highly significant difference as well, a 3-foldincrease in water hardness (from 20±2.8 to 108±0.0 mg L-1 as CaCO3) was significantly different
toxicity effect of Cu to Moina macrocopa that overlapping 95% confidence intervals of LC50 values(Table 4).

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Table 4 Acute toxicity endpoints (LC50) calculated for Moina macrocopa exposed to Cu (mg/L)
into rainy season based on different water hardnesses (20±2.8 and 108±0.0 mg/L as
CaCO3)
Rainy season
LC50 (mg/L) 95% Confidence Limits for conc.
Hour
24
48

Rainy season
LC50 (mg/L) 95% Confidence Limits for conc.

20±2.8 (mg/L as CaCO3)
Estimate
0.011
0.004*

Lower
0.002

Hour

Upper
0.008

24
48

108±0.0 (mg/L as CaCO3)
Estimate
0.023
0.012*

Lower
0.011
0.009

Upper
0.044
0.015

Note: * = significant at 5% level

Acute Toxicity of Copper on Local Freshwater Organisms; Cyprinidae - Labeo rohita and Moina
macrocopa under Different Water Hardness of Mekong River in Lao PDR during Dry Season in2015
Cu was toxic to Cyprinidae (Labeo rohita) during dry season with water hardnesses as CaCO3
105±3.34 mg L-1 and 140±4.0 mg L-1. Cu toxicity decreases with increasing hardness. Pourkhabbaz etal, (2011) found that Gambusia holbrooki is sensitive to Cu toxicity in soft, more than hard water. A
12-fold increase in water hardness (25 to 350 mg L-1 as CaCO3) substantially reduced the toxicity ofCu (up to 38-fold). In the present study, LC50 for juvenile fish Cyprinidae (Labeo rohita) was 0.092 (00.048) mg L-1 at water hardness of 105±3.4 mg L-1 as CaCO3, compared to LC50 value 0.155 (0.1130.188) mg L-1 at water hardness of 140±4.0 mg L-1 as CaCO3. This is a 2-fold significant increase intoxicity on juvenile fish Cyprinidae (L. rohita) (Table 5).
Table 5 Acute toxicity endpoints (LC50) for juvenile fish Cyprinidae (Labeo rohita) exposed to Cu(mg/L) during the dry season based on different water hardness (105±3.4 and 140±4.0 mg
L-1 as CaCO3)
Dry season
LC50 (mg L-1) 95% Confidence Limits for conc.
105±3.4 (mg L-1 as CaCO3)
Hour
Estimate
Lower
Upper
24
0.145
0.072
0.449
48
0.123
0
0.063
72
0.107
0
0.049
96
0.092*
00.048

Dry season
LC50 (mg L-1) 95% Confidence Limits for conc.
140±4.0 (mg L-1 as CaCO3)
Hour
Estimate
Lower
Upper
24
0.248
0.226
0.273
48
0.176
0.145
0.204
72
0.161
0.126
0.19
96
0.155*
0.113
0.188

Note: * = significant at 5% level

Table 6 Acute toxicity endpoints (LC50) calculated for Moina macrocopa exposed to Cu (mg L-1)
into dry season based at different water hardness (105±3.4 and 140±4.0 mg L-1 as
CaCO3)
Dry season
LC50 (mg L ) 95% Confidence Limits for conc.

Dry season
LC50 (mg L ) 95% Confidence Limits for conc.

-1

Hour
24
48

-1

105±3.4 (mg L-1 as CaCO3)
Estimate
Lower
Upper
0.055
0.031
0.121
0.01*
0.005
0.016

Hour
24
48

Note: * = significant at 5% levelⒸ ISERD15140±4.0 (mg L-1 as CaCO3)
Estimate
Lower
Upper
0.143
0.063
5.711
0.023*
0.003
0.062

IJERD – International Journal of Environmental and Rural Development (2016) 7-2

The percentage mortality of Moina macrocopa was 100% at 48 hr at Cu concentration 0.13 mg L-1,
on 105±3.4 and 140±4.0 mg L-1 as CaCO3 hardness. A 2-fold increase in water hardnesses as CaCO3(from 105±3.4 and 140±4.0 mg/L) did not significantly (P > 0.05) affect Cu toxicity to Moina
macrocopa (Table 6).
Acute Toxicity of Copper on Local Freshwater Organisms; Cyprinidae (Labeo rohita) and Moina
macrocopa on Distilled water with Different Water Hardness
The effects of water hardness as CaCO3 at 18±3.6 mg L-1 and 86±4.6 mg L-1 on acute toxicity of Cu to
on juvenile fish Cyprinidae (Labeo rohita) at water hardness 18±3.6 mg L-1 as CaCO3 was similar tothat reported by Olaifa et al, (2004) who worked on juvenile C. Gariepinus exposed to various Cu
concentrations, e.g., 0.6, 0.71 and 0,70 mg L-1 at 10.42 mg L-1 as CaCO3. Baldwin et al (2003) studied
the influence of water hardness on the inhibitory effects of copper on juvenile coho salmon(Oncorhynchus kisutch). However, in the present study found at 18±3.6 mg L-1 as CaCO3 hardness, thepercentage mortality of L. rohita was 100%, it was found that at 96 hr with Cu concentration of 0.02
mg L-1, the percentage mortality was 100% at 96 hr of water hardness of 86±4.6 mg L-1 as CaCO3 at
Cu concentration 0.16 mg L-1. A 7-fold increase in water hardnesses as CaCO3 18±3.58 and 86±4.56
mg L-1 did not significantly affect Cu toxicity on L. rohita) (Table 7).
Table 7 Acute toxicity endpoints (LC50) of juvenile fish Cyprinidae (Labeo rohita) exposed to Cu(mg L-1) into distilled water hardness (18±3.6 and 86±4.6 mg L-1 as CaCO3)
Soft hardness
LC50 (mg L ) 95% Confidence Limits for conc.
18±3.6 (mg L-1 as CaCO3)
Hour
Estimate
Lower
Upper
24
0.013
0.008
0.087
48
0.008
0.006
0.013
72
0.006
0.004
0.008
96
0.006*
0.004
0.007

Moderately water hardness
LC50 (mg L-1) 95% Confidence Limits for conc.
86±4.6 (mg L-1 as CaCO3)
Hour
Estimate
Lower
Upper
24
0.105
0.042
0.835
48
0.067
0.033
0.121
72
0.052
0.028
0.087
96
0.042*
0.017
0.083

-1

Note: * = non-significant at 5% level

Table 8 Acute toxicity endpoints (LC50) for Moina macrocopa exposed to Cu (mg L-1) at different
water hardness (18±3.6 and 86±4.6 mg L-1 as CaCO3)
Soft hardness
LC50 (mg L ) 95% Confidence Limits for conc.
18±3.6 (mg L-1 as CaCO3)
Hour
Estimate
Lower
Upper
24
0.000797
0.000521
0.0008348
0.000493*
0.000087
0.000965

Moderately water hardness
LC50 (mg L-1) 95% Confidence Limits for conc.
Hour
86±4.6 (mg L-1 as CaCO3)
Estimate
Lower
Upper
24
0.024895
0.004465
0.0632948
0.013725*
0.004918
0.024119-1

Note: * = non-significant at 5% level

The percentage mortality of Moina macrocopa at was 100% at 48 hr by Cu concentration 0.04
mg L-1 had highly significant difference ( P< 0.001), while percentage mortality was 100% at 48 hr of
86±4.6 mg L-1 as CaCO3 at Cu concentration 0.13 mg/L, that has highly significant difference (P <0.001), a 28-fold increase in water hardness (18±3.6 and 86±4.6 mg L-1 as CaCO3) did not significantly(P > 0.05) toxicity effects of Cu to (Moina macrocopa) that overlapping 95% confidence intervals of
LC50 values (Table 8).

Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

CONCLUSIONHigh water hardness could reduce toxic effect of copper on (indicate species tested. As a result of LC50
with 95% confidence interval in water hardnesses as CaCO3 (20±2.8 mg L-1, 108±0.0 mg L-1, 105±3.35
mg L-1, and 140±4.00 mg L-1 were 0.038 (0.021-0.077) mg L-1, 0.106 mg L-1, 0.092 (0-0.048) mg L-1
and 0.155 (0.113-0.188) mg L-1 for L. rohita. Moreover, M. macrocopa were 0.004 (0.002-0.008) mg
L-1, 0.012 (0.009-0.015) mg L-1, 0.01 (0.005-0.016) mg L-1 and 0.023 (0.003-0.062) mg L-1,
respectively.
Distilled water with soft hardness and moderately water hardness were reconstituted water similaras true water of Mekong River (18±3.6 and 86±4.6 mg L-1 as CaCO3), the LC50 with 95% confidence
interval of L. rohita were 0.006 (0.004-0.007) mg L-1 and 0.042 (0.017-0.083) mg/L. and M.
macrocopa were 0.000493 (0.000087-0.000965) mg L-1 and 0.013 (0.0049-0.0241) mg L-1.
The results of this toxicity tests for copper will contribute to ecotoxicology data to manage theaquatic environment for revise environmental quality standard in Lao PDR.
ACKNOWLEDGEMENTS
We would like to acknowledge the Integrated Water Resource Management Research andDevelopment Center in Northeast Thailand, Khon Kaen University and the research collaboration
project between Loyola University, Chicago and Khon Kaen University supported by International
Copper Association, Ltd. (ICA).
REFERENCES
Baldwin, D.H., Sandahl, J.F., Labenia, J.S. and Scholz, N.L. 2003. Sublethal effects of copper on coho salmon,
Impacts on nonoverlapping receptor pathways in the peripheral olfactory nervous system. Environmental
Toxicology and Chemistry / SETAC, 22 (10), 2266–2274. http://doi.org/10.1897/02-428
Gary, M.R. 1996. Fundamentals of aquatic toxicology, Effects, environmental fate and risk assessment.
International Journal of Toxicology. Hemispher, Washington. http://doi.org/10.1177/109158189601500514
MRC. 2010. The Mekong river report card on water quality; Assessment of potential human impacts on MekongRiver wate quality, Vol. 2, Vientiane, Lao PDR.
Olaifa, F., Olaifa, A. and Onwude, T. 2004. Lethal and sub-lethal effects of copper to the African catfish (Clarias
gariepinus) juveniles. African Journal of Biomedical Research, 7, 65-70. Retrieved from http://www.ajol.
info/index.php/ajbr/article/view/54071
Perschbacher, P.W. and Wurts, W.A. 1999. Effects of calcium and magnesium hardness on acute copper toxicity
to juvenile channel catfish, Ictalurus punctatus. Aquaculture, 172 (3-4), 275-280. http://doi.org/10.1016/
S0044-8486(98)00499-2
Phonvisai, P., Coowanitwong, N., Shapkota, P., Pradhan, P. and Hossain, M.M. 2006. Urban wastewater andsanitation situation in Vientiane, Lao PDR. Vol. 2, Vientiane, Lao PDR.
Pourkhabbaz, A., Kasmani, M.E., Kiyani, V. and Hosynzadeh, M.H. 2011. Effects of water hardness and Cu andZn on LC50 in Gambusia holbrooki. Chemical Speciation and Bioavailability, 23 (4), 224-228. http://doi.org/
10.3184/ 095422911X13201685540769
Rathore, R.S. and Khangarot, B.S. 2003. Effects of water hardness and metal concentration on a freshwater, 142,
341-356.
Snidvongs, A. and Teng, S. 2006. Mekong River, GIWA Regional assessment 55. Retrieved December.
University of Kalmar on behalf of United Nations Environment Programme. Retrieved from http://scholar.
google.com/scholar?hl=en&btnG=Search&q=intitle:Global+International+Waters+Assessment+Mekong+Riv
er,+GIWA+Regional+assessment+55#2
Yim, J.H., Kim, K.W. and Kim, S.D. 2006. Effect of hardness on acute toxicity of metal mixtures using Daphnia
magna, Prediction of acid mine drainage toxicity. Journal of Hazardous Materials, 138 (1), 16-21.
http://doi.org/10.1016/j.jhazmat.2005.11.107Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Research article
erdComparison of the Water Footprint of Cassava and Sugarcane
in Northeast, Thailand
NARUEMOL KAEWJAMPA*
Faculty of Forestry, Kasetsart University, Bangkok, Thailand
Email: narue77@gmail.com

NIPAPORN CHAISRI
Surin Land Development Station, Surin, Thailand

CHULEEMAS BOONTHAI IWAI
Faculty of Agriculture, Khon Kaen University, Khon Kaen, Thailand
Received 20 December 2015

Accepted 11 July 2016(*Corresponding Author)

Abstract The water footprint (WF) is an indicator of water use consists of the direct andindirect water use throughout the life cycle of crop produce and it varies on different climate
and agricultural production system. This study aims to assess the water use of cassava andsugarcane cultivation in northeastern, Thailand using WF concept which is a tool forsustainable water analysis and management. The results of this study show the average the WF
of cassava (345 m3/ton) is more than that sugarcane (157 m3/ton). At the provincial level, theWF of cassava is the most highest in Amnat Charoen (378 m3/ton; green WF 44 m3/ton, blue
WF 233 m3/ton and grey WF 101 m3/ton), while Buri Ram has the lowest WF (313 m3/ton;green WF 38 m3/ton, blue WF 181 m3/ton and grey WF 94 m3/ton). For sugarcane, Amnat
Charoen show the highest of WF of 167 m3/ton, which consists of green WF 20 m3/ton, blue
WF 84 m3/ton and grey WF 63 m3/ton. Meanwhile, the lowest WF was 133 m3/ton in Bueng
Kan (green WF 16 m3/ton, blue WF 64 m3/ton and grey WF 54 m3/ton). As a result, thedifferent location, crop, agricultural production systems and yields have an effect on WF.
Therefore, not only developing the efficiency water system to water resources sustainable but
also increased crop productivity and soil fertility are certainly important for decrease theamount of water used in this region.
Keywords Water footprint, cassava, sugarcane, water resource, northeast Thailand

INTRODUCTION
Cassava and sugarcane is an annual crop in tropical region and can be cultivated in almost soil type andlow organic matter such as in Northeastern region, Thailand generally is sandy soil, an average rainfall
30 years is 1,447.70 mm (Meteorological Department, 2009). Cassava and sugarcane is the main cash
crop in northeast region which is a total cassava and sugarcane cultivation area of 4,578,385 and
3,260,700 ha and an average yield is 14,493,229 and 36,978,370 ton, respectively (office ofagricultural economics, 2012). However, high production of cassava and sugarcane depends on not
only their varieties, soil texture, fertility but also water supply still needs for increasing of the
production in Thailand.
Meanwhile, northeast region has a low average rainfall and long dry season. Lack of water may
effect to growth and yield in this region. Sometimes rainfall is insufficient for cultivation must be
supplemental irrigation, surface water and groundwater for produce high crop yield. Therefore, aⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

limited of water resource in Northeast region is should be seriously and carefully to water use andmanagement.
A tool that has been used to estimate water requirement on crop production is the water footprint(WF). The concepts of the WF have been introduced by Hoekstra in 2002 which was an indicator ofwater used for produces the goods and service, by measured through over the full supply chain
considering water use both direct and indirect including by source and polluted volumes in water. The
WF consists of three component which are the green WF refer to the rainwater consumed, the blue WF
refers to the volume of surface and groundwater consumed (evaporated) as a result of the production ofa product and the grey WF refers to the volume of freshwater that is required to assimilate the load ofpollutants based on existing ambient water quality standards (Hoektra et al., 2011). The WF concept is
considered as an alternative toot to improve the water used plan and manage under the existence of alimited resource on the climate change (Hoekstra et al., 2009).
Therefore, the objective of this study was to assess WF of cassava and sugarcane cultivation in
Northeast, Thailand with the findings can be used as a guideline for future water resource management
for cassava cultivation in Northeast, Thailand.
METHODOLOGY
Table 1 Harvest Area, production and yield average on period 2003-2012 of cassava andsugarcane in Northeast, Thailand
Province

Loei
Nong Bua Lum Phu
Udon Thani
Nong Khai
Bung Kan
Sakon Nakhon
Nakhon Phanom
MukdahanYasothon
Amnat Charoen
Ubon Ratchathani
Sri Sa Ket
Surin
Burirum
Mahasarakham
Roi EtKalasin
Khon Kaen
Chaiyaphum
Nakhon Ratchasima

Averageharvested
area (ha)26,518.7
6,866.9
26,855.2
6,753.8
4,113.4
11,731.9
3,017.7
15,920.4
7,639.8
5,265.0
19,490.5
11,192.7
7,039.1
31,498.8
17,461.9
14,925.4
43,352.4
35,243.1
59,413.8
266,674.8

Cassava
Averageproduction(ton/year)
531,095.5
137,659.5
551,312.0
128,970.1
84,256.0
217,621.2
56,545.6
299,082.5
156,861.6
99,356.4
380,353.9
222,623.2
128,947.5
636,715.3
333,141.4
285,697.3
918,329.2
690,881.6
1,183,106.8
5,437,998.3

Total
620,975.4
12,480,554.9
Source: Office of Agricultural Economics (2012)

Averageyield(ton/ha)
20.0
20.0
20.5
19.1
20.5
18.5
18.7
18.8
20.5
18.9
19.5
19.9
18.3
20.2
19.1
19.1
21.2
19.6
19.9
20.4

Averageharvested
area (ha)13,249.2
7,663.4
64,239.0
1,625.3
241.6
4,015.1
1,200.8
14,171.1
1,415.8
1,042.3
1,819.2
834.4
14,679.9
18,148.9
7,777.4
4,215.6
41,621.9
75,477.1
56,839.9
84,747.7

Sugarcane
Averageproduction(ton/year)
803,122.7
479,683.7
3,900,521.0
99,780.8
18,000.0
240,684.7
73,203.3
908,303.3
90,985.6
66,145.6
132,560.0
55,434.3
969,175.3
1,150,709.0
495,478.0
281,601.1
2,714,353.7
5,076,625.0
3,599,376.3
5,232,631.7

Averageyield(ton/ha)
60.6
62.6
60.7
61.4
74.5
59.9
61.0
64.1
64.3
63.5
72.9
66.4
66.0
63.4
63.7
66.8
65.2
67.3
63.3
61.7

392.9

415,025.6

26,388,375.1

1,289.3

Study area and planting design: Data collections were the data of cassava and sugarcane cultivation
areas in Northeast, Thailand during 2003-2012 cover 20 provinces collected from the Office ofⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Agricultural Economics (Table 1). The planting time of cassava is between April through May andharvesting time is between October through November (8 months), while planting time of sugarcane is
October and harvesting time is December (14 months). Climate data of past 30 years from Thai
Meteorological Department and soil type from Office of Soil Survey and Land Use Planning.
Calculation of water footprint of cassava and sugarcane: Water footprint calculated of cassava andsugarcane cultivation use the water footprint concept following the WF assessment manual of Hoekstra
et al. (2011) as showed in equation (1)𝑊𝐹 = 𝑊𝐹𝑔𝑟𝑒𝑒𝑛 + 𝑊𝐹𝑏𝑙𝑢𝑒 + 𝑊𝐹𝑔𝑟𝑒𝑦(1)
3

Green and blue water footprint can be calculated by using crop water use (CWU, m /ha) divided
by cassava and sugarcane yield (Y, ton/ha) as equation (2) and (3)𝑊𝐹𝑔𝑟𝑒𝑒𝑛 =𝑊𝐹𝑏𝑙𝑢𝑒 =

𝐶𝑊𝑈
𝑌

(2)

𝐶𝑊𝑈
𝑌

(3)

Equation (2) and (3) CWU can be calculated by accumulation of daily evapotranspiration (ET,mm/day) using the CROPWAT model as equation (4)𝑙𝑔𝑝

𝐶𝑊𝑈 = 10 × ∑𝑑=1 𝐸𝑇𝑔𝑟𝑒𝑒𝑛, 𝑏𝑙𝑢𝑒

(4)

Where the factor 10 is applied to convert the unit from mm into m3/ha and lgp denotes the lengthof growing period in days which is .244 days for cassava and 426 days for sugarcane.
In this study, evapotranspiration (ET) can be calculated by CROPWAT 8.0 model (FAO, 2009) as
following equation (5) (Hoekstra et al., 2011) which required the spatial data (latitude, longitude ofMeteorological stations and elevation), climate data of each province (maximum temperature (qC),
minimum temperature (qC), humidity (%), wind speed (km/day), sunshine (hours) and rainfall amountof past 30 years (2003-2009)), crop parameters (crop name, planting date, harvest, crop coefficient(Kc), crop development state, the length of growth stage, rooting depth, critical depletion and cropheight) and soil characteristic (soil series, soil texture, total available soil moisture and initial soil
moisture depletion).
ETgreen, blue = Ks × Kc × ET0(5)

Where Kc is the crop coefficient, Ks a water stress coefficient, and ET0 the reference
evapotranspiration (mm/day).
The grey water footprint was calculated by multiplying the chemical application rate per hectare(Appl, kg/ha) with the leaching-run-off fraction (α) divided by the maximum acceptable concentration(Cmax, kg/m3) minus the natural concentration for the pollutant considered (Cnat, kg/m3) and thendivided by the crop yield (ton/ha) (Charoensuk et. al., 2012) as equation (5)𝑊𝐹𝑔𝑟𝑒𝑦 =(𝛼×𝐴𝑝𝑝𝑙)/(𝐶𝑚𝑎𝑥−𝐶𝑛𝑎𝑡)𝑌(5)The leaching-runoff fraction (α) assumed 10% of the chemical application rate (Allen et al., 1998).
In this study considered only the effect of nitrogen fertilizer used. The maximum acceptableconcentration for nitrate (Cmax) reference from surface water and groundwater standard value is 5
mg/litter (Pollution Control Department Thailand, 2011) and the natural concentration for the pollutant
considered (Cnat) is 0 mg/litter (Mokonnen and Hoektra, 2011).
RESULTS AND DISCUSSION
Water Footprint of CassavaⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

The calculation of water footprint (WF) of cassava cultivation for 20 provinces in Northeastern
Thailand showed that the average total WF was 345 m3/ton consist of green, blue and grey WF were 40
m3/ton, 208 m3/ton and 97 m3/ton, respectively (Table 2). At the provincial level, Amnat Charorn (378m3/ton) has higher WF than Mukdahan (375 m3/ton), Ubon Ratchathani (375 m3/ton), Roi Et (370m3/ton), SriSa Ket (369 m3/ton), Mahasarakham (361 m3/ton), Surin (356 m3/ton), Nong Khai (350m3/ton), Yasothon (347 m3/ton), Khon Kaen (346 m3/ton), Sakon Nakhon (346 m3/ton), Chaiyaphum(336 m3/ton), Nong Bue Lum Phu (334 m3/ton), Nakhon Phanom (334 m3/ton), Loei (327 m3/ton),
Udon Thani (326 m3/ton), Bung Kan (322 m3/ton), Nakhon Ratchasima (320 m3/ton), Kalasin (318m3/ton) and Burirum (313 m3/ton) which is the lowest one.
As the result show blue WF higher than grey WF and green WF in all provinces. The highest blue
WF was found in Ubon Ratchathani (235 m3/ton), while the lowest one was 181 m3/ton in Burirum.
Grey WF, Surin is the province where the grey WF is the highest (104 m3/ton), while Kalasin has thelowest grey WF (90 m3/ton). Meanwhile, green WF which is the lowest WF of cassava cultivation was
found Amnat Charoen has the highest green WF (44 m3/ton) and lowest green WF was 37 m3/ton in
Kalasin. These results are consistent with Kongboon and Sampattagul (2012) which reported that theblue WF of cassava in Northern Thailand is higher than green are 232 and 129 m3/ton, respectively.
Water Footprint of Sugarcane
As show in Table 2, sugarcane consists of green, blue and grey WF. The average total WF was 157
m3/ton consist of green, blue and grey WF were 19 m3/ton, 76 m3/ton and 62 m3/ton, respectively. At
the provincial level, the WF increases in the following order: Amnat Charorn and Sakon Nakhon (167
m3/ton), Yasothon and Udon Thani (165 m3/ton), Mukdahan (164 m3/ton), Nong Khai (163 m3/ton),
Nong Bue Lum Phu (161 m3/ton), Loei, SriSa Ket and Mahasarakham (160 m3/ton), Nakhon Phanom(159 m3/ton), Roi Et (158 m3/ton), Kalasin and Chaiyaphum (156 m3/ton), Nakhon Ratchasima (155m3/ton), Burirum and Khon Kaen (149 m3/ton), Surin (146 m3/ton), Ubon Ratchathani (145 m3/ton)and Bung Kan (133 m3/ton).
Besides, the result show that blue WF of sugarcane cultivation was higher than gray WF andgreen WF in all provinces. The highest blue WF, grey WF and green WF were found in Amnat
Charorn (84 m3/ton), Loei and Udon Thani (66 m3/ton) and Amnat Charorn, Yasothon, Loei and Sakon
Nakhon (20 m3/ton), respectively. Whiles, the lowest blue WF, grey WF and green WF was found in
Bung kan with 64, 54 and 20 m3/ton, respectively. During 2003-2012, northeast region was low the
harvested yield and also the low rainfall amount makes the rainwater is not enough for water
consumption. So, the irrigated water was the main water used for sugarcane cultivation and blue WF
was higher than green WF and grey WF. But this study was not similarly with Kongboon andSampattagul (2012) who study WF of sugarcane in northern, Thailand which reported that green WF ofsugarcane was higher than blue WF and grey WF.
The WF of crops varies across of difference crop species, crop yields and region. The WF of
cassava is larger than sugarcane by 2.2 times. So, in this region sugarcane is better than cassava whichis can save more water use for sugarcane production. When compared the WF of cassava andsugarcane in northeast was lower than Thailand and global (Table 3). The green WF, which is therainwater that evaporated during crop growth for Thailand is substantially lesser than the global
average. However, in northeast region not only rainwater but also irrigated water is the main waterused. This is mainly due to the differences in crop yield. The difference of topography, soil
characteristic, yield, crop coefficient, cultivation period and area, evapotranspiration, and waterbalance are influential to the total WF (Sukumalchart et al., 2011).

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Table 2 The water footprint of cassava and sugarcane in Northeast, Thailand
WF of cassava (m3/ton/year)

Province

green

blue

grey

Loei

39

192

Nong Bua Lum Phu

39

201

Udon Thani

38

Nong KhaiWF of sugarcane (m3/ton/year)
green

blue

grey

95

total
327

20

74

66

total
160

95

334

19

78

64

161

195

93

326

19

80

66

165

41

209

99

350

19

78

65

163

Bung Kan

38

191

93

322

16

64

54

133

Sakon Nakhon

42

201

102

346

20

80

67

167

Nakhon Phanom

40

192

101

334

19

75

66

159

Mukdahan

43

231

101

375

19

83

62

164

Yasothon

41

214

93

347

20

83

62

165

Amnat Charoen

44

233

101

378

20

84

63

167

Ubon Ratchathani

43

235

97

375

17

73

55

145

Sri Sa Ket

42

231

96

369

19

80

60

160

Surin

43

209

104

356

18

68

61

146

Burirum

38

181

94

313

18

68

63

149

Mahasarakham

42

219

100

361

19

79

63

160

Roi Et

43

227

99

370

19

79

60

158

Kalasin

37

192

90

318

18

76

61

156

Khon Kaen

40

209

97

346

17

72

59

149

Chaiyaphum

39

201

95

336

18

74

63

156

Nakhon Ratchasima

37

189

93

320

18

72

65

155

40

208

97

345

19

76

62

157

Average

Table 3 A comparisons WF of cassava and sugarcane between Northeast, Thailand
and Global scale
Cassava WF (m3/ton)

Scale

Sugarcane WF (m3/ton)

Green

Blue

Grey

Total

Green

Blue

Grey

Total

Global*

550

0

13

564

139

57

13

210

Thailand*

192

232

85

509

90

87

25

202

Northeast

40

208

97

345

19

76

62

157

* Source: Mekonnen and Hoekstra, 2011

CONCLUSION
The water footprint of cassava and sugarcane in Northeast, Thailand for 20 provinces during 20032012 based on the crop yield over the full life span were 345 m3/ton and 157 m3/ton, respectively
consists of three components: for cassava cultivation; green WF 40 m3/ton, blue WF 208 m3/ton andgrey WF 97 m3/ton. While, sugarcane cultivation; green WF 19 m3/ton, blue WF 76 m3/ton and grey
WF 62 m3/ton. In this region, blue WF higher than grey and green in both crops due to northeast regionⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

is relatively arid and low rainfall amount which affected to low crop yield. The usage of water in bothfrom irrigation and surface water is necessary. The results from this study can be applied to water
resource management guidelines for cassava and sugarcane cultivation which related to increase thecrop yield in Northeast region.
ACKNOWLEDGEMENTS
The author would like to thank Faculty of Agriculture, Khon Kaen Univeristy, Faculty of Forestry,
Kasetsart University. Thankful to Assistant Prof. Dr. Chuleemas Boothai Iwai (Khon Kaen Uinversity)and the Integrated Water Resource Management Research and Development Center in Northeast
Thailand, Khon Kaen University for their support in this research.
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Mekonnen, M.M. and Hoektra, A.Y. 2011. The green, blue and grey water footprint of crop and derived crop
product. Hydrology and Earth System Sciences, 15, 1577-1600.
Meteorological Department. 2009. Climate data 1980-2009.
Sukumalchart, T., Pornprommin, A. and Lipiwattanakarn, S. 2011. Monthly water footprint of maize in major
cultivated areas of Thailand, Proceedings of the first EIT International Conference on Water Resources
Engineering “Water Resources Management under Risk of Natural Hazard and Data Uncertainty”,
Phetchaburi, Thailand.

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Research article
erd

Variation in Storage Temperatures for Foot and Mouth
Vaccine in Cambodia
SOCHEAT SIENG*
Institute for Rural Future, School of Behavioural, Cognitive and Social Sciences,
University of New England, Armidale, New South Wales, Australia
Email: s.socheat2010@gmail.com

STEPHEN W. WALKDEN-BROWN
Animal Science, School of Environmental and Rural Science, University of New England,
Armidale, New South Wales, Australia

JAMES KERR
Institute for Rural Future, School of Behavioural, Cognitive and Social Sciences,
University of New England, Armidale, New South Wales, Australia
Received 15 December 2015

Accepted 11 July 2016(*Corresponding Author)

Abstract Vaccine efficacy may be influenced by pre-use storage condition. This study assesses
vaccine cold storage management and vaccine handling practices at 30 veterinary drug storesspread across the provinces of Pursat (n=10), Kampong Cham (n=9) and Phnom Penh (n=11) in
Cambodia. Electronic data loggers were used to record the temperature in each cold storage
facility every thirty minutes for a period of thirty days. The findings indicated that vaccines
were exposed to freeze temperature for 24-100 hrs (3%-14%) and more than 100 hrs (15%87%) of time recordings in 8 and 9 facilities respectively. Vaccines were exposed to heat for
254-327 hrs (35%-45%) of time recordings in 3 facilities and between 468-7200 hrs (65%100%) in 4 facilities. Most of the refrigerators also contained food and/or drinks, leading to thefrequent door opening. Vaccines were often stored in the bottom drawers and door shelves,
which were the warmest locations within refrigerators in the study. The vast majority of thestudy refrigerators (93.3%) were not equipped with a maximum-minimum thermometer. Daily
refrigerator temperature recording was not practiced in any of veterinary drugstores. This study
also highlighted the considerable temperature fluctuations to which vaccines were exposed to anumber of refrigerators. The frequent power failures which occur in Cambodia contribute tothese temperature fluctuations. This study consequently also investigated the speed and durationof temperature rise in a cold storage facility during a typical power failure in Phnom Penh. The
results suggested that corrective training for vaccine wholesalers/retailers and relevant
government staff may be a useful first step in attempting to improve vaccine storage conditions,hence, improved potency. Maintenance of vaccine potency is likely to improve the success of
vaccination programs in Cambodia. This critical but neglected issue requires improved
practices and ongoing monitoring. The results also highlight the need for improvement andsolutions to avoid ongoing future exposure of vaccines to freezing, too cold and too hottemperatures, particularly in hot tropical countries like Cambodia.
Keywords data logger, veterinary drug store, vaccine, vaccine cold storage, Cambodia

INTRODUCTION
Vaccination is a key control method for foot and mouth disease (FMD) in countries where the diseaseis endemic as is the situation in Cambodia. Immunization is a highly effective way of protectingⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

individuals and communities from infectious disease. However, successful vaccination campaigns
require proper storage, transportation and handling of vaccines, including inactivated FMD vaccines(El-Sayed, El-Din, Rizk, & El-Aty, 2012). The FMD vaccines currently used in Cambodia areinactivated, oil adjuvant purified antigen preparations. Vaccine shelf life is always indicated by the
manufacturer and is usually six to twelve months under the specified conditions of storage. Typicallythese include storage between 2-8 ˚C protected from light and freezing. Typically freezing the vaccineor heating the vaccine will promote emulsion breakdown and destroy vaccine integrity/efficacy overtime (S. Seneque, Merial (Asia), personal communication, September 5, 2014). A study by Bell et al.,(2001) revealed that failure to keep the thermometer in the vaccine storage facilities was associatedwith vaccine storage temperatures outside recommended range (2-8 oC). Cortese and Smith (2004)
reported freezing of vaccine will disrupt the integrity of the antigens and degrade the adjuvant andoverheating can have the same effect. Incorrect handling or storage of vaccine may result in an
ineffective vaccine being administered and failure of protection (Rashid, Rasheed, & Akhtar, 2009). To
remain potent, FMD vaccines should be stored under refrigeration usually at 4r2 oC for the optimal
retention of antigenic potency (Garland, 1999) and should not be used if they have frozen or exposed tohigh temperatures or are outside the use by date (Cortese & Smith, 2004). Weir and Hatch (2004)
suggested that never store vaccines on refrigerator-door shelves, where they are often exposed to warm
air every time the door opens. The vaccine is thought to lose immunogenic potency progressively as
the storage temperature increases above these levels. Thawing frozen vaccines or re-cooling overheated vaccines does not restore vaccine integrity (Cortese & Smith, 2004) and damages theirimmunogenicity (Garland, 1999).
When an inactivated oil adjuvant FMD vaccine was stored at 4 oC for 15 months, no appreciablevaccine potency loss could be detected by the direct challenge testing of vaccinated cattle and specificantibody assay (Doel, 2003; Garland, 1999). Recent research has confirmed that FMD vaccine may
keep their potency for two years at 4 oC, three weeks at 25oC and one week at 37 oC with full
protection against challenge with FMDV O1/Aga/EGY/93 (El-Sayed et al., 2012). Protection was
decreased to 80% when vaccines were stored at 25 oC for 4 weeks and at 37 oC for 2 weeks. The
efficiency of the cold chain is, therefore, a critical factor for optimal vaccine storage (Garland, 1999).
Farmer interviews during the 2010 FMD outbreak in Cambodia suggested very poor protection of
cattle in responses to vaccination administered by government authorities in Kampong Cham province.
The major reasons for this failure were thought to be poor planning, timing and implementation of thevaccination program, as well as improper vaccination technique (under-dosing) and weaknesses in thevaccine cold chain (Sieng & Kerr, 2013). The donated FMD vaccine used was reported not to havebeen stored at the proper temperatures recommended by the manufacturer (District veterinarians andvillage animal health workers, personal communication, October 30, 2010). These allegations require
proper testing as temperature in vaccine cold storage facilities in Cambodia have not previously been
investigated and reported. Consequently, this study represents is first attempt to measure theperformance of government and commercial vaccine cold storage facilities in three regions of
Cambodia.
OBJECTIVE
In this study we aimed to investigate vaccine storage temperatures in veterinary drug stores in two
Cambodian provinces and in the capital city of Phnom Penh.
METHODOLOGY
The main study (Study 1) design involved continuous monitoring of temperatures for 30 days at 30
veterinary drugstores (VDs) spread across the provinces of Pursat (PS, n = 10), Kampong Cham (KC, n = 9),Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

and the capital Phnom Penh (PP, n = 11). All known eligible VDs in the 3 areas was invited toparticipate based on selection criteria including significant vaccine sales and willingness to participate.
The study sites included predominantly vaccine retailers but also government vaccine stores of thestudy sites. In KC almost all vaccine stores in Prey Chhor district (3) and Kampong Cham provincial
town (6) participated in the study. In PS province, six (6) VDS participated in Sampov Meas district, as
well as four (4) from Bakan district. Eleven (11) stores in PP participated in the research study. A totalof thirty refrigerators in 30 VDs located in 3 areas in Cambodia were thus selected for the study. Of
these thirty VDs, 3 were government cold storage facilities, and 27 were vaccine retailers. Of the 27
VDs, 26 used a domestic type refrigerator and one used a cold-box. Two out of 3 government cold
storage facilities used domestic type refrigerator and one (PP) involved a large refrigerated vaccine
storage facility. Temperature recording was via electronic data loggers1 (Thermochron®), programmed
to record temperatures at 30 minute intervals for 30 days, a total of 1,440 readings for each refrigerator.
The recording accuracy was ±1 oC. The performance of the data loggers was tested in a refrigerator
with a known temperature as demonstrated by a thermometer. The precise date of placement of the dataloggers was unknown to participants until immediately before placement. A single data logger wasplaced centrally in the refrigerator or cold box next to vaccines but not placed immediately beside or on
an ice pack or ice. The VDs were visited every week by research assistants to ensure that the datalogger was still in the same position. Each half-hourly temperature recording was classified as‘freezing’ (≤ 0 ˚C), ‘too cold’ (> 0 but < 2 ˚C), ‘recommended range’ (2-8 ˚C) or ‘too hot’ (> 8 ˚C) andthe proportion of samples in each category determined for each data logger.
These data were analyzed within temperature categories by one way analysis of variance (AOV)
to test the effect of province (and the reliability of its power supply) on the proportion of samples ineach category. A separate dataset was created in which the duration of each period spent within eachtemperature category over the 30 days experimental period was recorded. This enabled analysis of themean time spent in each temperature category. This was repeated measures analysis so a mixed
restricted maximum likelihood (REML) model was fitted with data logger as a random effect andprovince, temperature category and their interaction fitted as fixed effects. Analyses were performed
using JMP 122 with a statistical significance level of P < 0.05. Because power failures are a frequentand sometimes prolonged event in Cambodia, an additional small study was carried out to test theeffect of a power failure on temperatures within a vaccine storage facility (Study 2). The study used thedata loggers and ran for a period of 18 days. The government vaccine cold storage facility in Phnom
Penh was chosen for this study because the presence of a 24 hour guard at that facility allowed accurate
recording of the time that the electricity blackout began and ended, so that these times could bematched with the temperatures recorded by the data loggers inside the vaccine cold storage facility
during the same period. The effect of location within a refrigerator on temperature variability was also
investigated in a VD in Phnom Penh (Study 3). The study was carried out for a period of 30 days byusing the same data loggers.
RESULTS AND DISCUSSION
At the completion of study period for Study 1, we received 30 completed data loggers, giving an
overall successful recording rate of 100. Table 1 summarizes the performance of each refrigerator
during the 30 day study period, including mean, median, maximum and minimum temperatures
recorded and time spent in each of the four temperature categories: ‘freezing’ (≤ 0 oC), ‘too cold’ (> 0
but < 2 oC), ‘recommended range’ (2-8 oC) and ‘too hot’ (> 8 oC). The final column in table 1 titled

1

Thermochron® DS1921, Dallas Identification/ALFA-TEK Australia, 7/42-50 Stud Road, PO Box 882, Bayswater, VIC. 3153,
Australia
2
JMP version 12 (SAS Institute Inc., NC, USA, 2015)Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2‘No. of changes’ refers to the number of times that refrigerator moved between temperature categories
during the recording period.

Phnom Penh (PP)
Kampong Cham (KC)
Pursat (PS)No. of changes(%)
Too hot

Temp. range
max-min (˚C)(%)
Correct

Too cold (%)

(%)

no

no

6.40

6.5

0.0

0.0

98.9

1.1

4.5 - 16.0

6

yes

no

13.60

14.0

0.0

0.0

0.0

100.0

8.5 - 26.5

1

PP3

yes

yes

4.04

4.0

0.0

3.0

96.5

0.5

1.0 - 10.5

23

PP4

yes

yes

5.89

5.0

0.6

6.5

71.5

21.4

0.0 - 25.0

127

PP5

yes

yes

0.92

0.5

40.1

35.1

24.4

0.5

-2.5 - 11.5

212

PP6

yes

yes

-1.30

-1.5

86.9

11.2

1.7

0.1

-4.0 - 13.0

32

PP7

yes

yes

2.33

2.5

4.3

23.4

71.9

0.4

-1.0 - 15.0

318

PP8

yes

yes

4.18

4.0

1.4

8.3

84.7

5.6

-1.0 - 24.5

171

Freezing

Food/drinks
also stored

PP1

PP2

a

Median temp
(oC)

vaccines indoor shelf

Site

Mean temp (oC)

Table 1 Details of each of the vaccines storage refrigerators including the cumulative percentageof temperature recordings in each of four temperature categories, and number ofchanges between these categories over a 30 day period

PP9

yes

yes

6.94

6.5

3.2

10.3

51.2

35.3

0.0 - 15.0

224

PP10

yes

yes

8.14

8.0

0.1

0.1

60.1

39.8

0.0 - 15.0

230

PP11

yes

yes

3.54

4.5

15.1

10.5

67.9

6.5

-9.5 - 14.5

61

KC1

yes

yes

-1.30

-2.0

76.4

7.1

11.4

5.1

-8.5 - 20.0

121

KC2

yes

yes

3.28

3.0

7.7

25.5

63.7

3.2

-1.5 - 14.5

160

KC3

yes

yes

3.17

2.5

26.9

16.7

43.4

13.0

-8.0 - 22.5

190

KC4

yes

yes

2.28

2.0

7.2

30.8

61.4

0.7

-1.5 - 12.5

676

KC5

yes

no

1.70

1.5

12.3

45.1

42.4

0.3

-2.0 - 13.5

213

b

KC6

no

yes

1.51

-1.0

73.6

5.1

6.8

14.5

-4.0 - 24.5

45

KC7

yes

yes

4.56

3.5

6.5

17.1

59.2

17.2

-3.5 - 20.5

242

KC8

yes

yes

5.17

5.0

8.0

6.7

65.9

19.4

-3.0 - 19.5

344

KC9

yes

yes

5.63

5.5

4.2

7.2

66.4

22.2

-2.0 - 17.5

187

b

PS1

yes

yes

1.10

1.0

37.8

21.2

40.9

0.1

-3.5 - 10.5

1165

PS2

yes

yes

6.34

6.5

0.0

0.0

94.0

6.0

4.0 - 12.0

26

0.0

0.0

35.0

65.0

2.0 - 19.5

59

PS3

no

yes

9.24

9.5

c

PS4

yes

yes

8.56

7.5

0.0

0.7

53.9

45.4

1.0 - 24.5

80

PS5

yes

yes

1.77

2.0

26.5

22.7

50.7

0.1

-3.5 - 9.0

141

PS6

yes

yes

3.56

3.5

0.0

9.4

90.1

0.5

0.5 - 11.5

185

PS7

yes

yes

4.20

3.0

0.1

17.5

71.7

10.7

0.0 - 22.0

236

PS8

yes

yes

5.94

6.5

19.0

0.3

35.8

44.9

-9.0 - 13.0

58

PS9

yes

yes

9.85

9.5

0.0

0.0

23.7

76.3

6.5 - 14.5

164

PS10

yes

yes

1.96

2.0

3.7

45.2

50.8

0.3

0.0 - 10.0926aDepartment of Animal Health and Production vaccine cold storage, bProvincial Office of Animal Health and Production
vaccine cold storage, cCold box rather than refrigeratorⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

In Phnom Penh, eleven refrigerators were monitored for a median 743 (range 716-750) hours.
Although two of the eleven PP refrigerators were equipped with a maximum and minimum
thermometer, in neither of them was the internal temperature of the refrigerator regularly monitored. In
fact, one of the two refrigerators that was equipped with a maximum and minimum thermometer
nevertheless had 100% of its data-logger temperature recordings at > 8 oC (too hot). Three otherrefrigerators in PP also registered a significant proportion of recordings (21.4%, 35.3% and 39.8%) inthe ‘too hot’ temperature range (> 8 oC), while other 3 refrigerators vaccines were exposed to too cold(> 0 but < 2 oC) and freezing temperature (≤ 0 oC) in 25.6%, 75.2% and 98.1% of recordings. Of the 11
PP refrigerators, 9 were also used to store food and/or drinks. In all refrigerators, vaccines were stored
on door shelves.
In Kampong Cham, nine refrigerators were monitored for a median 743 (range 769-793) hours.
None of the refrigerators were equipped with a maximum and minimum thermometer. Vaccines in one
refrigerator were exposed to both heat temperatures (> 8 oC) for 13.0% of recording and too cold andfreezing temperatures for 43.6% of recordings (Tabel 1). In four refrigerators, vaccines were exposed
to too cold (> 0 but < 2 oC) and freezing temperature (≤ 0 oC) for 33.2%, 57.4%, 38% and 83.5% of thetemperature recordings. The results for the POAHP’s refrigerator are especially significant because
large quantities of donated and government FMD and other types of vaccines are stored there
periodically. The temperatures in that facility were freezing (≤ 0 oC) for approximately three quartersof time (78.6%) and too hot (> 8 oC) in 14.5% of recordings. Of the nine refrigerators, 8 refrigerators
were also used to store food and/or drinks. In 8 of the 9 KC refrigerators, vaccines were stored in thedoor shelves.
In Pursat, nine refrigerators and an ice box were monitored for a median 725 (range 668-743)
hours. None of the vaccine storage facilities were equipped with a maximum and minimum
thermometer. In two refrigerators vaccines were exposed to heat (> 8 oC) for 65.0%, and 76.3% of thetemperature recordings. Vaccines were exposed to too cold (> 0 but < 2oC) and freezing temperatures(≤ 0 oC) in 2 refrigerators for 48.9% and 49.2% of the temperature recordings. The most pronounced
example of temperature variability in Pursat was recorded in refrigerator PS8, which recorded 44.9%
of reading in the ‘too hot’ range (> 8 oC) and 19.0% of readings in the ‘freezing’ category (≤ 0 oC). The
results from the single set of cold box recordings (PS4, Table 1) showed that vaccines were exposed toheat > 8 oC for 45.4% of the temperature recordings. As in Kampong Cham province, the temperaturesin that government facility (PS1) were freezing (≤ 0 oC) for 37.8% of recordings and too cold (> 0 but< 2 oC) for 21.2% of recordings. All 10 monitored refrigerators in Pursat were used to store food and/or
drinks. In all nine refrigerators, vaccines were found to be stored on door shelves.

Fig. 1 Significant interaction between the effects of study area and ownership on temperature
variation (SD, Left) and number of changes between temperature categories (Right)Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

The number of episodes between temperature ranges that each site encountered in all study areas
was described in Table 1. The results from the analysis of the variables showed that there was no
significant effect of Province, Government/Private status or interaction between these two for mean ormedian temperature, or the percentage of time spent in different temperature categories (p > 0.05).
However, for the standard deviation of temperature, and the number of temperature episodes indifferent categories while there was no overall effect of the province (Table 1) there was significant
interaction between the effects of Province and Government/Private status (p < 0.05, Fig 1).
Given the very small number of Government facilities, this should be interpreted with caution.
This demonstrates that most of the variation in these was due to large variation between the
Government sites included in the study. In particular, the vaccine storage facility in POAHP of KC
recorded very high variability in temperature, and the POAHP of PS a high number of transitions
between temperature categories. On the other hand, the POAHP in PP showed very consistentmaintenance of temperature. Indeed, although the study was small, it provides clear evidence of serious
problems with vaccine storage that could jeopardize the success of a vaccination program. Vaccine
damage depends on the ambient temperature and the duration of exposure to adverse temperatures(Wawryk, Mavromatis, & Gold, 1997) and should not be used if they have been frozen or exposed tohigh temperatures (Cortese & Smith, 2004). The vaccine cold storage is critical point for the successful
or failure of the vaccination program (Thakker & Woods, 1992). Those vaccine refrigerators can nolonger maintain temperatures in recommended range (2-8 oC) have to be brought for the services orreplaced (Grasso, Ripabelli, Sammarco, Manfredi Selvaggi, & Quaranta, 1999). Weir and Hatch (2004)
suggest that never store vaccines on the refrigerator-door shelves. Failure to keep the thermometer inthe vaccine refrigerators was associated with vaccine storage temperatures outside recommended range(2-8 oC) (Bell et al., 2001). None of the cold storage facilities were routinely monitored by theowners/managers. Storing vaccines contrary to the manufacturers’ recommendation is likely toadversely affect their potency and consequent efficacy in the field, reducing the effectiveness of
disease prevention programs which rely heavily on vaccination. Even though the study was small, ithighlighted serious problems with 53.3% (n = 16) of the study vaccine cold storage facilities where
56.3% (n = 9) set to freeze and too cold temperatures from 43.6%-98.1% and 43.7% (n = 7) set to too
hot temperatures from 35.3%-100% of the recordings. Moreover, the study results suggest that the
majority of wholesalers/retailers and government officials in charge of cold storage facilities would
benefit from a brief and specific training session on vaccine and cold storage management in order toensure all vaccines are stored at the correct temperature range or avoid the damage of vaccines whilestoring inside their refrigerators. The Study 2 investigating the consequences of power failure on
temperatures within the DAHP’s Phnom Penh vaccine storage facility revealed that the temperature
spike on the day 8 coincided with a 6-hours electricity blackout recorded by the DAHP guard. Ninety
minutes after the blackout began the storage facility temperature had risen above acceptablerefrigeration range (8 oC), and after 6 hours without electricity, the temperature had risen to 16 oC.
After the electricity supply was restored, it took two hours for the temperature within the cold storage
facility to return to the refrigeration range 2-8 oC. The effect on temperature of location within arefrigerator (Study 3) was investigated using the best performing commercial study refrigerator owned
by a private VD in PP (PP3). The refrigerator registered 96.5% of temperature recording the correct
refrigeration range (2-8 oC) during the 30 days study period. Marked variation was recorded dependingon the location within the refrigerator. The mean temperatures of 0.7 (-2.5 - 4.5), 1.5 (-0.8 - 5.0), 0.0 (2.3 - 5.5), 6.8 (4.0 - 8.8) and 5.3 (1.3 - 8.8) were recorded at the top shelf, 2nd shelf, 3rd shelf, bottom
drawer and door shelf within the refrigerator respectively. The temperatures at the bottom drawer anddoor shelf were much warmer than other parts of the fridge.

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

CONCLUSION
Most of the vaccine cold storage facilities in all 3 study areas failed to maintain the recommended
temperature range (2-8 ˚C) where vaccines in 8 facilities were exposed to freeze temperature, ranging
between 24-100 hrs (3%-14%) and 9 facilities (including two from the POAHP) spent more than 100
hrs (15%-87%) of the temperature recordings. In three and four facilities, vaccines were exposed toabove the recommended max temperature for 254-327 hrs (35%-45%) and 468-7200 hrs (65%-100%)of recordings. The practical implications of this on vaccine efficacy cannot be determined withcertainty and are the subject of a separate study. However, they are unlikely to be positive and some
simple measures could be attempted in order to improve vaccine storage conditions in bothgovernmental and commercial facilities. SEACFMD reliance on vaccine to control FMD (FAO controlof Avian Influenza) needs to consider these results and their importance on success of vaccination
programs. The results from this study suggest that training program for government vaccine
responsible staff (DAHP and POAHP) must be developed and recommend that each POAHP holds
training for vaccine retailers. Education of vaccine distributors is a logical step, as lack ofunderstanding about the effects of heating, freezing and temperature fluctuations on vaccine potency is
doubtless part of the problem. The Cambodian government is aware that farmer uptake of vaccination
will be discouraged if vaccines damaged by cold chain failures fail to provide expected protection.
Licensing of vaccine retailers is an option being considered by the Cambodian government so thatgovernment officers can audit commercial vaccine storage conditions. In the interim, vaccine
distributors should be offered training to improve cold storage standards. At a bare minimum, these
operators should be encouraged to use thermometers to check and record the operating temperatures
twice daily in their refrigerators. The effects of repeated door opening should be presented to them,
together with recommendations to store vaccines separately from food and/or drink, or at least to store
them in the colder shelves. Likewise, the effect of power outages on refrigerator temperatures should
be demonstrated, together with the need for them to have an alternative source of power (generator) or
ice in order to keep the vaccine refrigerated in such an event. While it is difficult to supervise
conditions in commercial vaccine outlets, it is within the government’s power to ensure that better
temperature monitoring and management is applied at the government storage facilities responsible formanaging the large quantities of donated and government funded vaccines which underpin disease
control programs against FMD, HPAI and other animal diseases of national significance. All
government vaccine cool rooms or refrigerators should be equipped with max-min thermometers inorder that temperatures can be monitored and controlled. Protocols should be developed whereby
remedial action is initiated by a temperature trigger point during power outages. It is also importantthat critical experimentation to better define the detrimental consequences of improper vaccine storageon vaccine efficacy be supported. This will assist with the development of critical thresholds triggering
discarding of vaccine if they are breached.
ACKNOWLEDGEMENTS
The authors wish to acknowledge the support of the Cambodian DAHP and POAHP for providing us
mission letter to carry out this study. Authors would also like to express our thanks to many field staff
including officials from the POAHP that assisted us to conduct this study. Many thanks are due to
Associate Prof. Ian Patrick, project leader of the ACIAR-AH/2010/046, for providing enormous
support and funding, which enabled us to carry out the research. Last but not least, we would like tothank all vaccine retailers who allowed us to use their refrigerators at their premises for this researchstudy and without their permissions, the research would not be possible to implement.

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

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Cortese, V. and Smith, R. 2004. Proper vaccine handling. Paper presented at the Proceedings of the ThirtySeventh Annual Conference, American Association of Bovine Practitioners, Fort Worth, Texas, USA, 23-25.
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Doel, T. 2003. FMD vaccines. Virus research, 91 (1), 81-99.
El-Sayed, E., El-Din, W.M.G., Rizk, S.A. and El-Aty, M.A. 2012. Effect of different storage temperatures on theefficacy of the bivalent foot and mouth disease oil vaccine. Journal of Advanced Veterinary Research, 2 (3),198-205.
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Grasso, M., Ripabelli, G., Sammarco, M., Manfredi Selvaggi, T. and Quaranta, A. 1999. Vaccine storage in thecommunity, A study in central Italy. Bulletin-World Health Organization, 77, 352-355.
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Research article
erd

Soil Amendments for Maize Cultivation by Crop Rotations in
Upland Cropping Systems of Southeast Cambodia
TARA PIN*
Faculty of Agriculture, Chea Sim University of Kamchaymear, Cambodia
Email: pintara30@gmail.com

KONGKEA PHAN
Faculty of Science and Technology, International University, Phnom Penh, Cambodia

VANNARO PINFaculty of Agriculture, Chea Sim University of Kamchaymear, Cambodia

OEUN HORN
Faculty of Agriculture, Chea Sim University of Kamchaymear, Cambodia

JOHN M. SCHILLER
School of Agriculture and Food Sciences, University of Queensland, Australia
Received 21 December 2015

Accepted 10 September 2016(*Corresponding Author)

Abstract A study was made of the importance of crop rotations on the growth and yield ofmaize in upland cropping systems of Cambodia. Maize (MZ) was grown continuously and in
two-year rotations with cassava (CS), soybean (SB), mung bean (MB) and peanut (PN). Six
different rotations T1, T2, T3, T4, T5 and T6 were designed and studied in the upland cropping
systems in the provinces of Prey Veng and Svay Rieng in southeastern Cambodia. Monocropping with maize (T0) was used as the control treatment in the study. The study was
undertaken in the period 2013 to 2015. The field experiments revealed an increase in crop
yields in the order of T1 > T2 > T3 > T5 > T6. There was no significant difference in crop yield
between T4 and the control (T0) treatment. The analysis of soils data revealed that there wereno significant differences in soil nitrogen and phosphate levels pre-treatment and post–
treatment in each of the rotations (paired samples t test, p > 0.05). However, post-treatment
potassium levels were significantly lower than the pre-treatment levels in all cropping rotations(p < 0.05) except T0. The results of the study suggest that the maize-legume rotation is the mostpromising crop rotation for yield improvement in the upland cropping systems in southeast
Cambodia.
Keywords maize, crop rotation, upland cropping system, Cambodia

INTRODUCTION
It is Cambodian government policy to encourage crop diversification (i.e. to grow cash crops otherthan rice), especially in non-rice upland agro-ecological systems (Chan et al, 2009). Cambodian
farmers, extension workers and researchers, are less familiar with crop rotations than with monocropping, as the focus of the research has been on cassava cultivation for many years on the same land.
Cassava production is also perceived to degrade soil fertility. This is also a major contributing factor to
the relatively low cassava yields in areas where cassava has been cropped over many years.
Maintaining soil fertility is one of the main challenges in agricultural production systems in Cambodia.
Intercropping is one of the options available for more sustainable agricultural production systems.
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Other benefits of intercropping include, spreading of risk (relative to single cropping), improved weed
management, and reduced incidence of insect pest and disease damage. The Government of the 3rdConstitution has adopted a development strategy which is partly based on crop intensification anddiversification (MAFF, 2007). Most farmers in the provinces of Prey Veng and Svay Rieng have tried
to intensify agricultural production through mono-cropping of cassava, reflecting the high demand forthis crop in commercial markets. However, this cropping intensification has been done with little
knowledge of procedures or technologies for maintaining soil fertility.
Soil fertility (and therefore crop yields) has shown a significant decline in areas with a long
history of cassava cropping, as smallholder producers are unable to afford commercial fertilizers to
replace the nutrients removed by successive cassava crops. To date, mono crops in Cambodia are
generally low yielding, with little knowledge and financial information available on the best
management practices for soil fertility maintenance in mono cropping systems, and often unsuitable arebeing grown. Attention to the agronomic aspects of rotation crops, especially soybean and mungbean isrequired. Growers need agronomic advice which will reduce the risk of degradation in soil fertility(Chan et al., 2009). To enhance food security and sustainable livelihoods, improvements are needed inagricultural techniques for enhancing production in upland rural areas of Prey Veng and Svay Rieng
Provinces of Cambodia. A combination of poor soils and a dependence on non-irrigated agricultural
production are the basis of low agricultural production and high levels of poverty in Prey Veng andSvay Rieng Provinces.
OBJECTIVE
The goal of this project was to use an on-farm, farmer participatory approach to study a range ofpotential agricultural technologies for enhancing and sustaining agricultural production and incomes inPrey Veng and Svay Rieng Provinces. The main objectives of the study were to: (1) determine thepromising crop rotation options for improving fertility and food crop production of the Prey Khmer
soil group in upland cropping system of Prey Veng and Svay Rieng provinces; and (2) investigate thechanges in soil chemical and physical properties after crop rotations.
METHODOLOGY
The study was carried out in Prey Veng and Svay Rieng provinces which are located in theSoutheastern part of Cambodia (Fig. 1). The continuous mono-cropping particularly with cassava inthese upland areas has led to a progressive decline in soil fertility. There is an urgent need to identify
alternative agricultural production options capable of economically improving both the soils andproduction, while the same time improving incomes of rural households which are almost 100%
dependent on agriculture.
Six different treatments (combinations of maize (MZ), cassava (CS), mungbean (MB), soybean(SB) and peanut (PN)) T1 (SB-MZ-MB-MZ), T2 (PN-MZ-SB-MZ), T3 (MB-MZ-PN-MZ), T4 (CS-CSCS-MZ), T5 (CS-MB-PN-MZ) and T6 (CS-SB-PN-MZ) were designed to investigate on the growth
performance and crop yield of maize in eight basic production systems (7m × 10m) in the study areasof Prey Veng (n = 4) and Svay Rieng (n = 4) provinces. The mono-cropping of maize was used as acontrol in the present study. Field trials were conducted in the field of farmers and carried out at
appropriate times throughout the growing seasons. The Proposed cropping treatments and timetable ofcropping activities are summarized in Table 1. The plant height (cm), the number of ear per plant, ear
length (cm), ear size (cm), weight (g) per ear and maize yield (dwt) per hectare (t/h) were measured
before the next cycle of ration. Concurrently, soil samples were collected at depth of 10-30cm before
and after each treatment to determine soil properties and measure the changes in their total C, organic
C, N, P2O5, Ca, Mg, Na, K and exchangeable acidity (pHKCl) and actual acidity (pHH2O).
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Fig. 1 Map of the study areas
Table 1 Summary of crop rotations in the upland cropping system in Prey Veng and Svay Rieng
provinces
Treatment
T0
T1
T2
T3
T4
T5
T6

2013
EWS
-

2014
LWS
MZ+F
SB+F
PN+F
MB+F
CS+F
CS+F
CS+F

EWS
MZ+F
MZ+F
MZ+F
MZ+F
CS+F
MB+F
SB+F

2015
LWS
MZ+F
MB+F
SB+F
PN+F
CS+F
PN+F
PN+F

EWS
MZ+F
MZ+F
MZ+F
MZ+F
MZ+F
MZ+F
MZ+F

LWS
-

EWS, early wet season; LWS, late wet season; MZ, maize; SB, soybean; MB, mungbean; CS, cassava; PN, peanut;+F, fertilizer application

All statistical analyses were performed using SPSS for Windows (Version 16.0). The t-test wasapplied to verify significant differences in the growth performance and crop yield between the six
treatment methods with a control and differences in the growth performance and production yield
between the two study areas. One way ANOVA was applied to verify the differences in the growth
performance and crop yields among the six rotation designs. Paired samples t test was applied to verify
the difference of soil physical and chemical properties before and after treatment. The significance wasconsidered in a circumstance where p < 0.05.
RESULTS AND DISCUSSION
Plant height (cm), number of ear per plant, and yield per hectare (t/h) of maize after crop rotation arepresented in Table 2. A comparison revealed that there were no significant differences in plant heightof control (T0) with each treatment (t-test, p > 0.05). However, there was a significant difference in
number of ear per plant among all treatments (One-way ANOVA, F (6, 49) = 12.11, p < 0.01). PostⒸ ISERD34

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hoc Tukey HSD tests showed that there were significant differences in number of ear per plant between
T0 and T1, T2, T3 and T5 (p < 0.05), but T4 and T6 were not significant different in number of ear per
plant with T0 (p > 0.05). A statistically significant difference was found among all treatments on ear
length, F (6, 49) = 11.45, p < 0.01. The ear length of T0 was significantly shorter than that of T1, T2
and T3 (p < 0.05) using Games-Howell post-hoc test. Likewise, ear size were statistically different
among all treatments (One-way ANOVA, F (6, 49) = 11.42, p < 0.01). Ear size of T1, T2 and T3 were
statistically bigger than that of the control using Tukey HSD post doc test. A statistically significant
difference was found among all treatments on weight of ear, F (6, 49) = 8.50, p < 0.01.
Table 2 Summary of growth performance and crop yield of maize crop rotation in the uplandcropping systems in Prey Veng and Svay Rieng provinces
Treatment
T0 (n = 8)
T1 (n = 8)
T2 (n = 8)
T3 (n = 8)
T4 (n = 8)
T5 (n = 8)
T6 (n = 8)

Statistics

Plant height (cm)Number of ear/ plant

Yield (t/h)

Mean
S.D
Mean
S.D
Mean
S.D
Mean
S.D
Mean
S.D
Mean
S.D
Mean
S.D

111.9
27
138.4
26.4
125.8
18.5
135.1
22.2
112.6
18
109.3
16.7
122.9
21.4

1.1
0.1
1.5
0.1
1.4
0.2
1.4
0.2
1.1
0.2
1.4
0.1
1.2
0.1

4.9
0.3
7.9
1.1
6.9
0.7
6.5
0.9
4.9
0.8
5.9
0.7
5.8
0.4

S.D, standard deviation; Yield is on 100% dry weight

Weight of ear of T1, T2 and T3 were significantly heavier than that of T0 using Games-Howellpost-hoc test. Analytical results revealed that there were statistically significant differences in crop
yield among all treatments (One-way ANOVA, p < 0.05). Further comparison indicated that crop yieldof treatment 1 (T1) is statistically significant higher than that of the control (T0) (t-test, p < 0.05).
Likewise, the crop yields of T2, T3, T5 and T6 are statistically significant higher than that of thecontrol (t-test, p < 0.05). It seems like the plant height is associated with crop yield without
consideration of rotation. Concurrently, it is more likely that crop yield is associated with number of
ear per plant, ear length, ear size and weight of ear. The present study showed that maize growth wasbetter in the crop rotation system than mono-cultured soil (control). This result is consistent with theresults of an earlier study by Horst and Härdter (1994) which found that in pot experiments, maize
growth was much better in the soil from the crop rotation than from the mono-cropping plots. Crop
yield of the present study was increased through crop rotation which is consistent to a statement by
Honeycutt et al., (1995).
The physical and chemical properties of soils before and after treatments are presented in Table 3.
Soil before crop rotation composed of sand, silt and clay of 66%, 26% and 8%, respectively. Whenplotting the percentage of all particles in the triangle diagram, the texture of soil was found to be sandyloam. However, the soil texture was not altered after crop rotation. In general, the management
practices do not alter the textural class of a soil on a field scale. Changing the texture of a certain soil
would require mixing it with another soil material of a different textural class. For example, theⒸ ISERD

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incorporation of large quantities of sand to change the physical properties of a clayey soil for use ingreenhouse pots would be considered to change the soil texture (Brady and Weil, 2007).
Table 3 Mean values of the chemical and physical properties of soils before (n = 8) and after(n = 8) treatment
Treatment
T0
T1
T2
T3
T4
T5
T6

Org C
2.4
2.4
2.4
2.4
2.4
2.4
2.4

T0
T1
T2
T3
T4
T5
T6

1.81
2.03
2.11
1.77
2.15
2.05
1.89

Pre-treatment
N
P2O5
1.18
188.691.18
188.691.18
188.691.18
188.691.18
188.691.18
188.691.18
188.69Post-treatment
1.1
178
1.22
152.131.4
148.25
1.14
177.63
1.28
161.5
1.24
162.5
1.1
167.25

Ca
2.59
2.59
2.59
2.59
2.59
2.59
2.59

Mg
1.68
1.68
1.68
1.68
1.68
1.68
1.68

Na
0.18
0.18
0.18
0.18
0.18
0.18
0.18

K
0.25
0.25
0.25
0.25
0.25
0.25
0.25

pH
4.6
4.6
4.6
4.6
4.6
4.6
4.6

3.08
2.99
3.23
3.08
3.21
3.17
3.31

1.27
1.33
1.31
1.35
1.33
1.34
1.41

0.12
0.12
0.11
0.09
0.11
0.1
0.09

0.17
0.15
0.14
0.16
0.17
0.14
0.16

4.71
4.82
4.98
4.89
5.08
4.96
4.82

Org C, N, P2O5, Ca, Mg, Na, K in mg kg-1

A comparison indicated that the total carbon of the post-treatment and pre-treatment in eachrotation were not significantly different (Paired samples t test, p > 0.05), except T2 that total carbon of
post-treatment was significantly higher than that of pre-treatment (t = -2.59, p = 0.036). Likewise, there
were not significant differences in organic carbon between pre-treatment and post-treatment of mostrotation (Paired samples t test, p > 0.05), except T0 and T4. Further analysis revealed that there were
not significant differences in total nitrogen and phosphate between pre-treatment and post –treatment ineach rotation (Paired samples t test, p > 0.05). A paired samples t test indicated that K of posttreatment were significant lower than that of pre-treatment in each rotation (p < 0.05), except T0.
However, Ca of post-treatment was significant higher than that of pre-treatment in each treatment(Paired samples t test, p < 0.05), except T2 and T5. Analytical results revealed that Mg of the posttreatment were significantly lower than that of pre-treatment in all treatment (Paired samples t test, p <0.05). However, Na of the post-treatments was not significantly lower than that of the pre-treatment,
except T3 and T6 (Figure 18). The exchangeable pH of pre-treatment were significantly lower than thatof post-treatment of T1, T2 and T4 (Paired samples t test, p < 0.05); however, there were notsignificant differences in the exchangeable pH of T0, T3, T5 and T6 (Paired samples t test, p > 0.05).
Concurrently, a comparison showed that the actual pH of pre-treatment were not significantly different
from that of post-treatment of T0, T1, T4, T5 and T6 (Paired samples t test, p < 0.05) while marginal
difference was found in T2 and T3. A study of field crop productivity in relation soil properties in
Basaltic soils of Eastern Cambodia found that drought, soil acidity, inadequate N fertilizer were themain factors accounting for the unreliable performance of maize (Seng et ., 2011).

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CONCLUSION
Crop rotation for maize production was successfully implemented in the upland cropping system inPrey Veng and Svay Rieng provinces in Cambodia. Experimental results revealed that crop yield
increased in the order of T1 > T2 > T3 > T5 > T6. Although post-treatment K was significantly lower
than that of pre-treatment, N and P2O5 were not significantly different before and after the treatment.
This study suggested that the rotation of soybean-maize-mungbean-maize T1 (SB-MZ-MB-MZ) was
the most promising crop rotation to increase maize yield in the upland cropping system of Cambodia.
ACKNOWLEDGEMENTS
Authors would like to thank OAE and DOA advisors and student volunteers attached to Chea Sim
University of Kamchaymear (CSUK) for their valuable field assistance. This study was financially
supported by World Bank through HEQCIP project of the Directorate General of Higher Education,
Ministry of Education, Youth and Sport of Cambodia Government.
REFERENCES
Brady, N.C. and Weil, R.R. 2007. The nature and properties of soils. 14th Ed., Prentice Hall.
Chan, P., Bob, M., Bob, F., Ung, S., Pol, C. and Pin, T. 2009. Farmer’s challenge in improving upland farming
systems in Cambodia. Cambodian Journal of Agriculture, 9 (1-2), 8-23.
Honeycutt, C.W., Clapham, W.M. and Leach, S.S. 1995. Influence of crop rotation on selected chemical andphysical soil properties in potato cropping systems. American Potato Journal, 72, 721-734.
Horst, W.J. and Härdter, R. 1994. Rotation of maize with cowpea improves yield and nutrient use of maize
compared to maize monocropping in an alfisol in the northern Guinea Savanna of Ghana. Plant and Soil, 160(2), 171-183.
Ministry of Agriculture, Fisheries and Forestry (MAFF). 2007. Statistics of general crops, 1980-2006. Cambodia.
Seng, V., Bell, R.W., Hin, S. and Touch, V. 2011. Field crop productivity in relation soil properties in Basaltic
soils of Eastern Cambodia. Cambodian Journal of Agriculture, 10 (1-2), 5-19.

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Research article
erd

Improving Upland Rice Production for Sustainability of Rice
Self-Sufficiency in Ratanakiri Province, Cambodia
SOPHAL VAR*
Faculty of Agronomy, Royal University of Agriculture, Phnom Penh, Cambodia
Email: var.sophal@gmail.com

EDNA A. AGUILAR
Department of Agronomy, Crop Science Cluster, University of the Philippines Los Baños,
Philippines

POMPE C. STACRUZ
Department of Agronomy, Crop Science Cluster, University of the Philippines Los Baños,
Philippines
Received 21 December 2015

Accepted 10 September 2016(*Corresponding Author)

Abstract Rice is the major source of carbohydrate, nutrient and income of poor farmers
especially in rural areas in Cambodia, and Ratanakiri Province is one among them. Rice selfsufficiency was threatening while the population dramatically increasing and the riceproduction trend showed the declining. Given primary result showed that a few families werevictims of rice self-insufficiency, notably, who possessed small farm, and large members’
family. But none of those families experienced hunger as they superior to buy food aid from themarket while the other mechanisms were also held. The linear multiple regression models
showed that rice sufficiency of upland rice producer families were strongly depend on rice yieldobtained. Traditional practices carried by many farmers resulting poor rice productivity. Thus,
to meet and sustain rice self-sufficiency several management practices are needed to improve
including increasing seeding rate, wisely select variety and planting method, fertilization while
capacity building are more apparent for the rapidly adopt technological and economic
environment and increasing income.
Keywords rice self-sufficiency, upland rice, upland community, Ratanakiri, Cambodia

INTRODUCTION
Rice is the staple food, source of carbohydrate and nutrient for Cambodian, especially for rural andpoor resource farmers (FAO, 2009; Ros et al., 2011; MAFF, 2012, Work Bank, 2013). By 2012,
Cambodia has covered 2.97 million ha for rice production with an average yield of 3.1 t ha -1 (MAFF,
2012). Cambodia, upland rice plays a key role in maintaining food security for rural areas, and accountfor around 20% of total rice production annually (MAFF, 2012). However, upland rice farming still
follows traditional practices such as slash and burn for ethnic people while some have already adopted
advanced technologies including land preparation, fertilization and pest control. Hence, the country’s
average upland rice production is only 1.2 t ha-1 (MAFF, 2012). Ratanakiri Province, well-known forhighland rice producing in Cambodia, has about 30,000 ha potential for upland rice production. In
2012, MAFF reported the decreasing trend of upland rice yield during the last decade and suggested to
improve rice production nationwide, not only on lowland but as well as upland rice. There is a reported
reduction in wet season rice productivity of rainfed upland rice in Ratanakiri Province, despite theconstant of upland rice production while the population is dramatic increasing from about 70,000 ha in2000 to 191,000 ha in 2012 (NCDD, 2010; RPDA, 2012). Notably, population increasing and low rice
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yield would push toward food crisis in the province, particularly rice sufficiency. Thus, the study was
aimed to determine the rice consumption status of upland rice farmers in Lum Choar commune, Ou Ya
Dav District, Ratanakiri Province, Cambodia, and identified the improvement options.
METHODOLOGY
The study was conducted in the dominantly upland rice production areas of Lum Choar commune, Ou
Ya Dav district, Ratanakiri province where the most number of upland rice producers was reported(RPDA, 2012). Farmer respondents of the study were taken from the total families of rice producers in
Lum Choar commune. The sampling of respondents was determined based on the Slovin’s formulawith ten percent (10%) margin of error. A total of 90 respondents out of 265 upland rice families wererandomly selected. Direct interview (questionnaire survey) was administered describe thecharacteristics of farmer, upland rice production and household rice status. A combination ofqualitative and quantitative, and Multiple Regression analysis using SPSS version 19.0 (SPSS Inc.)was employed.
RESULTS AND DISCUSSION
Level of Household Requirement
Table 1 show that the respondent have an average of 4 members and all of the respondent families are
subsistence rice planting rather than commercial.Weekly plant height (cm) of the plants was taken in
all treatments as shown in Table 1. It was found out that there was a difference of height in alltreatments compared with the Control. However, based on the analysis of variance, it was found thatthe difference was insignificant in all treatments over the control plots.
For instant, based on self-sufficiency equation, we had estimation for the household rice
requirement as in follow. The household survey showed that the requirement for food grains is fixed at
450 grams per person per day for rural areas. This translates into an annual requirement of:Household requirement = 450 g/capita/day x 4 people x 365 days = 657 kg(1)

Thus, to meet the rice self-sufficiency, each household has to produce at least 1,000 kg of paddy ricewhere the conversion ratio from paddy to polished rice was found about 64% (De Datta, 1981), andplus at least 30-40 kg of seed reserve for next planting (Table 1). Hence, rice self-sufficiency would be
not the problem in the study area where the average yield of 1.46 ton per ha (0.93 ton polished) wasrecorded (Table 1).
However, Table 2 showed that about 8 percent of the respondent families were fell into rice
insufficiency. Among those who faced rice insufficiency, majority was rice insufficiency for more than
50 days (85%). Difference in farmland size devoted for planting upland rice, yield and household
member triggered this phenomenon (Table 1). About 10 percent of the respondent families own lessthan 1 ha devoted for rice production and about 8.9 percent got yield less than 1 ton per hectare. While
production area is small and the rice yield is low, these families would fall into rice self-insufficiency.
In addition, none of the rice insufficiency families experienced hunger since they have coping
mechanisms to feed rice to their family and children. All of seven respondents who suffered rice
insufficiency resource to purchasing rice (100%), 85.7% asked from neighbours or their relatives,
28.6% said they sometimes milled some portion of their next cultivation seed in case of emergency.
The result implied that most of farmers could afford to purchase supplementary food from market,
even though majority of them obtained low income (Table 2).

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Table 1 Household member, education attainment, rice production area, yield, seeing rate,
planting purpose and family income of upland rice producer families
Descriptions
Household Member (person)
x =< 3x 4x >= 5
Educational Attainment
x No formal schoolingx Primary school
x Secondary school
Upland Rice farm areas (ha)x <1x 1-2.0
x 2.1-3.0
Yield (ton ha-1)x >1.00
x 1.00-1.50
x 1.51-2.00
x >2
Seeding rate (kg ha-1)
x 20-30
x 31-40x >40Purpose of planting rice*x Consumption
x Income
Family Income (US$/year)- <500- 500-800- 800-1,000- >1,000

Frequency

Percent

Mean+S.E

50
21
19

55.60
23.30
21.10

50
31
9

55.60
34.40
10.00

9
76
5

10.00
82.20
7.80

1.20 ± 0.50

8
49
30
3

8.90
54.50
33.30
3.30

1.46 ± 0.37

66
20
4

73.40
22.20
4.40

30.10 ± 8. 90

9051

100.00
56.70

78
3
7
2

86.70
3.30
7.80
2.20

4 ±1

750 ± 420

Table 2 Household rice sufficiency in Lum Choar Commune, Ou Ya Dav District, Ratanakiri
Province, Cambodia
Descriptions

Frequency

Percentx Surplus

27

30.0

x Sufficiency

56

62.2

x Lacking7

7.8

x 50 days1

14.3

x > 506

85.7

x Purchase from market

7

100.0

x Ask from neighbor/relative

6

85.7

x Milled the seed for next cultivation

2

28.6

Mean+S.E

Rice Status

Duration of Rice shortage

Coping mechanisms to rice shortage** multiple responsesⒸ ISERD40

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Factor Affected Households’ Rice Sufficiency and Improvement Options
A regression analysis was done on the following selected factors to determine which factor influenced
household rice sufficiency: income, household member (social factors), areas of rice production, seed
used rate, and rice yield (production factors). The result shows that there was a significant relationshipbetween the availability of rice for household consumption and the selected variables. However, among
the selected factors only rice yield had positively significantly affected on the availability of rice forhousehold consumption (Table 3). The result indicates that the level of rice sufficiency for household
consumption depend on upland rice yield.
Table 3 Factors affecting household rice sufficiency
Model

Observation number

PR>F

90
90
90
90
90

0.361 ns
0.327 ns0.018 *
0.082 ns
0.906 ns

Seed rate
Area of upland rice production
Rice yield
Household member
IncomeCoefficientvalue-0.1110.103
0.313-0.1820.013* Significant at 0.05 level. R2=0.117 (P=0.002)

Suggesting that increasing rice yield is crucial to meet and sustain rice availability and sufficiency
in upland communities, specifically in Lum Choar commune. On the other words, high rice yieldwould also increase family’s income. This is understandable because Cambodia is well known as an
agriculture country (MAFF, 2012; OECD, 2013; World Bank; 2013). Agriculture sector stands as thirdcontributor to its GDP (MAFF, 2012). However, the scheme to increase upland rice yield per unit
should be in parallel with sustainable development and environment harmony.
Factors Lmiting Rice Production and Options for Yield Improvement
The Linear Regression model was used to represent the effects of selected social factors such as
education level, income and management interventions (rice variety, sowing date, seed used history,
planting methods, seeding rate, fertilization, and weed management) on rainfed upland rice yield.
Table 4 Factors affecting upland rice yield (Regression Model)
Modela

Sowing Date
Planting Methoda
Variety Usea
Seed Use Durationa
Seed Rate Usea
Fertilizationa
Weed Managementa
Education levelb
IncomebaObservation number

PR>F
ns

90
90
90
90
90
90
76
90
90

0.361
0.020 *
0.001**
0.016 *
0.000**
0.000**
0.696 ns0.005**
0.000**

Coefficient
0.065
0.241
0.284
-0.213
0.715
0.448
0.077
0.215
0.285

Management practices factors, b Social factors, * Significant at 0.05; **Significant at 0.01
R2=0.70 (P=0.000)

Significant affected were observed among selected factors (Table 3). Planting methods, rice
variety, seed used history and fertilization were factors limiting productivity while sowing date andⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

weed management was significantly affected. The results indicated that traditional practices carried by
farmers were the major yield’ limiting factors which commendable implied from poor education andlow income. Thus, to improve upland rice yield, farmers have to select variety and planting method
wisely, or change their seed every 3-5 years. This is because after 4-5 years of continued recycling of
the seeds, a decline in rice yield often takes place due to the accumulation of seed pathogens, impurityof genetic and mixed with the weed seed which later results to unhealthy crops and low yield (Seshu etal., 1988). Sehnoy et al (1988) reported that 20% of rice’s yield decline was due to the use of poor seed
quality. Commendably, increasing seeding rate would significantly increase yield.
Over the years, improved rice varieties has been proven to achieve 20% more yield than local
varieties in many countries such as China, India, Vietnam, Philippines, Indonesia, Malaysia, Thailand,
African nation, Australia, and Cambodia (Longping, 2004; Virmani and Kumar, 2004). In 2004,
Longping pointed out that new improved and hybrid rice is a wise and great prospect for commercial
production and would play a key role to ensure the world’s food security. Self-sufficiency in rice is an
important matter as it provides food, income and generates employment opportunities. Additional yieldof rice means high economic profitability to farmers and food security. In the same manner, applicationof additional fertilizer would help to increase rice yield. Results of social profiles both education andincome, played an important role in which way management practices were carried, significantly
influence upland rice production. In rural areas where farming households invested so little ineducation contributed to poor production (FAO, 2009; Ros et al., 2011; MAFF, 2012; OCED, 2013 andWorld Bank, 2013). These authors emphasized that education may enhance productivity directly by
improving the quality of management and labour. Education is an important asset to farm production
in a rapidly changing technological or economic environment. With the rapid spread of technologicalinnovations, the importance of formal schooling and/or training, workshop and farmer field school tofarm production becomes more apparent. On the other hand, increasing upland rice productions withminimum inputs are directly influence the income of the upland rice producer families resulting toenhance rice sufficiency and food security for upland community.
CONCLUSION
Traditional upland rice practices carried by poor and low educated farmers resulting low yield, where
rice served as major carbohydrate and nutrient, and seriously threaten rice sufficiency in uplandcommunities. Hence, improvement management practices including wisely select planting method,change seed use, adopt new rice varieties, increasing seeding rate and additional applied fertilizer will
help to enhance rice production which notably improve rice sufficiency and directly increase theincome. However, increasing family income and knowledge are apparently to improve upland riceproduction such as technological and climate change adaptation.
ACKNOWLEDGEMENTS
The authors would like to express his sincere thankfulness and appreciation to IDRC-SEARCA, for thescholarship and assistance funds, my assistant; selected farmers for supporting and encourage, key
informants and information; your mighty support being my greatest source of motivation andinspiration.
REFERENCES
De Datta, S.K. 1981. Principle of rice production. John Wiley & Sons, Inc., New York, USA.
Longping, Y. 2004. Hybrid rice for food security in the world. Paper presented at the International Year of Rice
Confference, Rome, Italy.
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Ministry of Agriculture, Forestry and Fisheries (MAFF). 2012. Annual report, Summarize activities in 2011-2012
and targeting for 2012-2013. Unpublished. Phnom Penh, Cambodia. 79.
Organization for Economic Cooperation and Development (OECD). 2013. Structural policy for economic
emerging, Country notes. Cambodia in Econmic Outlook for Southeast Asia, China and India 2014, Beyond
the Middle Income, 26.
Ratanakiri Provincial Department of Agriculture (RPDA). 2012. Annual report, Chapter rice production in
Ratanakiri 2011-2012. Ratanakiri, 53, Cambodia.
Ros, B., Nang, P. and Chhim, C. 2011. Agricultural development and climate change, The case of Cambodia (74).
In Cambodia's Leading Independent Development Policy Research Institute (CDRI). Phnom Penh, Cambodia.
Seshu, D.V., Krishnasamy, V. and Siddique, S.B. 1988. Seed vigor in rice. In Rice Seed Health. International
Rice Research Institute, Philippines, 315-329.
Shenoy, S.N., Paris, T.R and Duff, B. 1988. Farm level harvest and post-harvest seed mangement practices offarm women in an irrigated rice system, A case study. In Women in Rice Farming System Network
Orientation and Planning Workshop (held in May, 1988), Philippines.
The National Committee for Sub-National Demoncratic Development (NCDD). 2010. Ratanakiri Province,
commune, district database. Website: db.ncdd.gov.kh. Cambodia.
Virmani, S.S. and Kumar, I.S.H. 2004. Development and use of hybrid rice technology to increase riceproducivity in the tropics. IRRN, 29, 19.
World Bank. 2013. Chapter country pages and key indicator, Cambodia in rebuilding policy buffers,
reinvigorating growth. World Bank East Asia and Pacific Economic Update. 1, 152. Washington D.C., USA.
World Food and Agriculture Organization (FAO). 2009. How to feed the world in 2015. Fact Sheet. Viale delle
Terme di Caracalla, Rome, Italy.

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Research article
erdCurrent Agricultural Conditions and Constraints in Paktya
Province of Afghanistan
ABDUL MALIK DAWLATZAI
Graduated School of Agriculture, Tokyo University of Agriculture, Tokyo, Japan
Email: abduldawlatzai@gmail.com

MACHITO MIHARA*
Faculty of Regional Environmental Science, Tokyo University of Agriculture, Tokyo, Japan
Email: m-mihara@nodai.ac.jp
Received 10 December 2015

Accepted 12 September 2016(*Corresponding Author)

Abstract Agriculture is the backbone of economy of Paktya Province in Afghanistan with morethan 80% people engages in agriculture for their livelihoods. In spite of such a large workforce
involves in this activity, the outcomes are not very satisfied. A survey was conducted to discusscurrent conditions of agricultural sectors and constraints of agriculture in Paktya province.
Survey was done in accordance with a questionnaire sheet on current agricultural condition andconstraints. As per the survey it was found that majority of farmers use traditional farming
methods and have very poor technical knowledge in agriculture. The low productivity andfertility of soils as well as the lack of irrigation water were identified as major factors causing
low agricultural production at the research area. In addition, 32.4% of responded farmers
answered soil erosion happens very severely and 50.0% answered soil erosion happens severely.
It means that more than 80% of farmers require the proper conservation strategies for holding
soil fertility. It was considered that soil degradation caused by erosion phenomena with highintensity rainfall causes low holding capacities of nutrients and water of soils. The developmentof proper conservation strategies as well as farmers education on proper soil management is
indispensable to achieve sustainable agriculture in Paktya Province, Afghanistan.
Keywords Afghanistan, agriculture, constraints, condition, Paktya

INTRODUCTION
Afghanistan is a landlocked country located in the central of Asia. It is bordered by Pakistan to thesouth and the east, Iran to the west, Turkmenistan, Uzbekistan and Tajikistan to the north and China to
the far northeast. The rugged terrain of Afghanistan shares the world’s highest mountain ranges,
Himalayas, Pamirs and Hindukush rising over 7,000 m and running from north east to south west. In
Afghanistan, over 80% of the population relies directly on the natural resources to meet their dailyneeds. However, the United Nations Environmental Programme UNEP (2003) showed that two and ahalf decades of war and continuous drought have resulted in widespread environmental degradation
throughout the country, which also raise a serious threat to the future of Afghan livelihoods.
Afghanistan’s climate is unique. The region is a center of origin for many fruits and nuts.
Afghanistan is not blessed with many riches in resources, but perennial crops and the hard working
Afghan farmers are a superior resource that can correspond to international market. Afghanistan’s
agriculture is the employment engine of the country. About 84% of the country’s population is either
directly involved in or related to farming activities.
Afghanistan has 34 provinces; one of these provinces is Paktya. It is located in the southern regionof Kabul Province and has borders with Logar, Ghazni, Paktika and Khost Provinces, to the north it hasⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

borders with Pakistan as shown in Fig. 1. The total area is 6,259 km2 and 65.1% of the province ismountainous/semi-mountainous terrain while a little more than one third (32.3%) of the area is madeup of flat lands as shown in Table 1 (Harris, 2012). This province is divided to 14 districts; the capital
is Gardez. According to the National Statistical Department, the total population of the province is lessthan one million households with an average of eight members in each household (CSO, 2010).

Fig. 1 Paktya Province map
Paktya has an agricultural based economy. In Afghanistan, the agriculture sector contributes 26%of the country’s GDP (IRACSO, 2010), while the industry sector shares only 25%. Within the industry
sector, mainly products come from very small scale agriculture based industries. It is estimated thatapproximately 94% of population living in the rural areas are engaging in agriculture related activities,
also 80% work as agricultural labors/workforce in farmlands. Most of these agriculture related
activities fall within small scale production systems with only a few farmers being self-sufficient.

Fig. 2 Land cover map of Paktya Province
According to land cover classification of Paktya by FAO (2014), huge areas are covered byrangeland and forests. Similarly, ArcGIS map showed large areas covered by forest and rangeland as
shown in Fig. 2. Wheat is a culturally most significant crop in the province and a staple food for all
Afghans. Wheat is grown on an area of 21,105 ha with a production of 75,203 Mt (MAIL, 2014).
Cereals like barley, maize or rice are the other important food grains. Approximately 90% of wheat isⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

fall-planted and the rest is spring planted, with around 80% produced from irrigated lands and only
20% from rain-fed areas. Although wheat straw has a relatively low nutrition for livestock, it is used
for livestock feeding. Therefore, higher seed rates are recommended to meet the additional need ofstraw to be used as fodder. The lack of irrigation infrastructure in most of the provinces leads to almost
complete failure of the crop cultivated during dry seasons. Due to the undulating topography of theprovince, local farmers have trouble with mechanized land preparation, sowing and irrigation.
OBJECTIVE
The objective of this study is to discuss current conditions of agricultural sectors and constraints ofagriculture in Paktya Province, which is located in southern parts of Afghanistan.
Table 1 General topography of Paktya Province
Flat

Semi flat

Mountainous

Semi mountainous

Not reported

Total

32.3%

1.9%

52.0%

13.1%

0.7%

100%

METHODOLOGY
In order to identify the current agricultural conditions and constrains, in Paktya Province ofAfghanistan, a survey was done in Dawlatzai Village of Paktya Province. The village is located in thecenter of Paktya province and agriculture is the main economic activity in the village. Compared toother parts of the districts, it is safer and provides ample environment to conduct the research. A totalof 34 farmers were randomly selected across the entire study area and interviewed in the survey. The
questions in the questionnaire sheet were on basic information of household, farmland, crop
cultivation, water resource, topography, fertilizer application, agricultural chemicals, soil degradation
and agricultural extension services as shown in Table 2.
Table 2 Questions in the questionnaire sheet
Category

Related question

Details

Basic information of household- Farmer`s information

Name, Age, Gender, Number of family
members, and Address

Farmland- Cultivated area

Size (sq.meter,m2)

Crop cultivated- Kind of crops

Wheat, maize, barely, beans andvegetable

Water resource- Source of irrigation water

Tube well, river and Karez

Topography- Nature of terrain

Flat, semi flat, hilly and mountainous

Fertilization- Type of fertilizers used

Urea, DAP (Diamonium Phosphate),
farm yard manure, compost manure andash

Agricultural chemicals- Type of chemical used

Insecticide, herbicides, fungicides etc.

Soil degradation- Soil erosion effect- Effect soil erosion- Soil conservation measure

Damage level, Nutrient loss and waterpollution, Agronomic and physicalmeasures

Agricultural extension service- Extension service provision

Awareness of agricultural extension
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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Each farmer was requested to fill one form. All forms were filled after all columns were
understood by respondents. The data recorded for various parameters were subjected to statisticalanalysis. Critical Difference (CD) at 1% or 5% level of probability was computed to compare thestatistical significance of different parameters.
RESULTS AND DISCUSSION
Soil Degradation
As shown in Table 2, soil degradation was a key challenge for farmers of Paktya Province.
Environmental stress by the province’s people have drastically altered the landscape and caused
widespread environmental destruction. Since the people lack adequate financial capability to purchasefuel, they mostly cut trees, uproot shrubs and collect animal dung as sources of fuel. This results inextensive soil erosion by both water and wind. Currently, only 6% of the 15% of land in Afghanistan isarable. Due to 3 decades of long civil war, large number of Afghan citizens migrated to neighboring
countries. Therefore, in case if all the refugees were to return, problems of land ownership andadequacy of available land are inevitable. Natural forests have been severely degraded, vast areas are
subjected to soil erosion due to the natural topography and the arid climate. Losses of vegetation andsoil humus have created ever more arid conditions (Saba, 2009). Based on the questionnaire survey,
32.4% of responded farmers answered soil erosion happens very severely and 50.0% answered it
happens severely as shown in Fig. 4. It means that more than 80% of farmers require the proper
conservation strategies for holding soil moisture and fertility. According to the report of Afghanistan
Environmental Protection Agency (2008), more than 80% of the whole land of Afghanistan could be
subject to soil degradation with soil erosion, declining soil fertility, salinization, falling groundwatertable, and de-vegetation.

Fig. 3 Soil region map of Paktya Province (USDA-SCS, 2001)
According to the Global Assessment of Soil Degradation (GLASOD), about 16% of
Afghanistan’s land is severely affected due to anthropogenic activities, whereas the country’s
vulnerability to desertification is one of the highest in the world (3/4 of Afghanistan is vulnerable todesertification). The geological, topographical and meterological features of Afghanistan naturally
increase the country’s susceptibility to the processes of soil erosion, furthermore human activities
significantly intensify them through farming on steep slopes, deforestation and de-vegetation of lands,Ⓒ ISERD

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as well as unsustainable use of shrub and grasslands. Some degradation is too severe to recovery
without human intervention. One of the most threatening impacts arising from loss of soil andvegetation is desertification and increasing floods. Paktya Province is in a mountainous region locatedat an elevation of between 1,500 to 2,300 m above mean sea level with the seasons of warm/dry
summers and cold/chilling winter. The average annual rainfall is below 400 mm. The changes inmonthly amounts of precipitation and average air temperature in Paktya is indicated in Fig. 5.
Precipitation occurs mostly between the months of January to April. From June to October period
Paktya Province receive hardly any rainfall.
60

Responded percentage (%)

50
40
30
20
10
0
Very severe

SevereLess

Very less

NormalFig. 4 Damage level of soil erosion in Dawlatzai Village of Paktya Province
As a result, water shortages frequently occur in the latter part of the cultivating season in August
up-to harvest time in October, causing major difficulties in crop cultivation. Erosion causes a serious
problem affecting the productivity of agricultural lands (Luis et al., 2010). The lack of information on
the factors influencing erosion in the dry regions hampers the formation of proper soil conservationplans. Rainfall in this region is irregular and varies spatially and temporally. Short but intensive
thunderstorms of highly erosive rainfall usually take place early in the rainy season in March and at theend of season in June. Although rainfall amounts are not considered high, the problems of soil erosion
are severe due to high intensity rainfall on steep slopes with sparse or absent vegetation covered in thearid areas.

Fig. 5 Soil degradation observed in Dawlatzai Village of Paktya ProvinceⒸ ISERD

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Water Deficiency and Drought
Paktya is one of the mountainous provinces; it is divided into different valleys and regions. The waterof river resource is from Spin Ghar Mountains, which runs from high latitude to eastern part to Karma
Agency region and the mountains are the main source of irrigation water for Paktya. The quantity ofwater is related to rainfall and snow accumulated in the mountains. Most of the rivers are impermanent
with increased water levels from February to April and usually dry from June to October as shown in
Fig. 6. Zarmal, Patan and Arub are the main rivers flowing through the province. Springs, Karezs andtub wells are also used as water sources. Unfortunately, during the last three decades war, many Karezs
and springs have been destroyed and majority of farmers are now digging the tub wells to get the water
needed as shown in Fig. 7. Fuel is required to run these tube wells, but the higher price of fuel has
caused another acute problem to the farmers of the province. Accordingly, majority of agriculturallands are rain-fed with no alternative methods of artificial irrigation.
70
60

Rainfall (mm)

50
40
30
20
10
0
Jan Feb Mar Apr May Jun

Jul Aug Sep Oct Nov Dec

Fig. 6 Monthly precipitation in Paktya Province

Fig. 7 Water problems in Dawlatzai Village of Paktya Province
About 88% of farmers reported lack of irrigation is a main problem that they are facing as shownin Fig. 8. More than 85% of the land needs artificial irrigation. This has proved as one of the noticeableⒸ ISERD

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factors that are considerably reducing the agricultural productivity. According to the UNEP (2003)
Post-Conflict Environment Assessment Report on Afghanistan, the amounts of water used are less than
one-third of total water potential at 75,000 million m3. Due to three decades political unrest and civil
war, Afghanistan faces many different problems; water scarcity, damaged water infrastructure systems(Habib, 2014).
Shortage of irrigation water (%)

100
90
80
70
60
50
40
30
20
10
0

Lack of irrigation water

Sufficient irrigation water

Fig. 8 Shortage of irrigation water
Agricultural Extension Services
Agricultural extension is one of the powerful forces that are responsible for the growth of crops bytransferring latest and improved technologies to the farmers and ultimately strengthens the national
economy (Sadaf, et al., 2005). Paktya Province has fourteen districts. Unfortunately just one extension
worker has been appointed for six districts while the other 8 districts have none. It is impossible for asingle person to reach the huge number of farmers and to solve their problems. According to thequestionnaire survey, 64.2% of the farmers did not know about the active extension worker. As a result,the farmers lack the modern technical knowledge and still the old age traditional farming is being
practiced, which is in turn hampering the agriculture production and ultimately the life style of people.
Quality of Agricultural Materials
Quality seed is an important asset for quality of production. It affects germination as well as the overall
vigor of the plants, especially for the case of wheat (Barnard and Calitz, 2011). The Department ofAgriculture, Irrigation and Livestock is responsible for seed distribution. But, due to the limited
availability of certified seed and misguidance by many local seed distributors, farmers are forced to use
the low quality uncertified seeds. More than 70% of the farmers were found not to have access toquality seeds. Utilization of poor quality seeds is one of the major problems in agriculture which is
responsible for low crop productivity (DAIL, 2014).
Although Afghanistan Government has claimed that the pesticide contamination and requested todecrease its usage, but still there is continuous use of low quality insecticides. Poor quality insecticides
affect natural environment and also induce some of the serious health issues due to their prolonged
residual effects (Jabbar and Mallick, 1994). Some private agricultural companies and agro-clinics areimporting the low quality insecticide and pesticide from Pakistan, Iran and China (DAIL, 2014). About
31.6% of the farmers are using the pesticides that are not even recommended for application. Thus,
Afghan Government has been unable to completely ban or control such ill practices.
CONCLUSIONⒸ ISERD

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Paktya Province is based on the agricultural economy, but the condition of the farmers is severe.
According to the topographical and climate conditions, modern farming methods employing artificial
irrigation are indispensable. If some alternative sources of irrigation or modern methods of irrigation
are popularized among local farmers, the condition of agriculture would be largely improved. The main
problems that Paktya Province is facing today are those of soil degradation, deforestation, lack ofirrigation water, poor extension services and lack of agricultural inputs. All of these, in turn, contributeto the declining agricultural production. Based on the survey conducted in the study area, 32.4% of the
farmers responded that soil erosion happens very severely and 50.0% answered soil erosion happen
severely. It means that more than 80% of farmers require proper conservation strategies for holding
soil fertility. In addition, 88% of farmers reported lack of irrigation water and that more than 85% ofarable land needs artificial irrigation system.
ACKNOWLEDGEMENTS
The authors would like to express appreciation to Department of Agriculture Engineering, Tokyo
University of Agriculture and Japan International Cooperation Agency (JICA).
REFERENCES
Barnard, A. and Calitz, F.J. 2011. The effect of poor quality seed and various level s of grading factors on theemergence and yield of wheat. South Africa, J. Plant Soil, 28, 56-59.
Central Statics Organization. 2010. Afghanistan agriculture. Statistical Year Book 2009-10. 111-130.
DAIL. 2014. Directorate of agriculture, irrigation and livestock of Paktya Province, Annual report, Afghanistan.
FAO. 2014. In Afghanistan. http://fao.org/soils-portal/soil-survey/soil-maps-and-databases/regional-and-nationalsoil-maps-and-databases.
Favre, R. and Kamal, G.M. 2004. Watershed atlas of Afghanistan. Ministry of Irrigation, Afghanistan.
Habib, H. 2014. Water related problems in Afghanistan. Int. J. Educ. Stud. 1, 137-144.
Harris, W. 2012. The University of Georgia cooperative extension, agricultural development for Afghanistan predevelopment training. California State University, Fresno, USA.
Islamic Republic of Afghanistan Centre Statistics Organization. 2010. Afghanistan statistical yearbook. 20082009, Afghanistan.
Jabber, A. and Mallick, S. 1994. Pesticides and environment situation in Pakistan. Working Paper Series,19, 2140.
Luis, M., González-Hidalgo, J.C. and Longares, L.A. 2010. Is rainfall erosivity increasing in the Mediterranean
Iberian Peninsula? Land Degradation & Development, 21, 139-144.
Ministry of Agriculture, Irrigation and Livestock (MAIL). 2014. Agriculture prospect report. Islamic Republic of
Afghanistan.
National Environmental Protection Agency of the Islamic Republic of Afghanistan, United Nations Environment
Programme. 2008. Afghanistan Environment.
Saba, D.S. 2009. Afghanistan environmental degradation in a fragile ecological setting. International Journal of
Sustainable Development & World Ecology, 8, 279-289.
Sadaf, S., Muhammad, S. and Lodhi, T.E. 2005. Need for agricultural extension services for rural women in Tehil
Faisalabad-Pakistan. J. Agri. Soc Sci, 1, 284-251.
UNEP. 2008. Afghanistan environment. National Environmental Protection Agency of the Islamic Republic of
Afghanistan.
UNEP. 2003. Afghanistan post-conflict environmental assessment. United Nations Environment Program,
Nairobi, Kenya.http://postconflict.unep.ch/publications/afghanistanpcajanuary.
USDA-SCS. 2001. Soil map and soil climate map. Soil Science Division, World Soil Resource. Washington D.C.,
USA. http://soils.usda.gov/use/worldsoils/mapindex/afghanistan-soil.html. Accessed on 14th Nov 2015.

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Research article
erd

The Analyses of Efficiency and Factors Affecting Efficiency ofAgricultural Cooperatives in Lower Northern Region ofThailand
ANUCHA WITTAYAKORN-PURIPUNPINYOO*
School of Agriculture and Cooperatives, Sukhothai Thammathirat Open University,
Nontaburi, Thailand
Email: puanucha@windowslive.com

NAIYANA JULLAPHUN
Pichit Provincial Cooperatives Office, Pichit, Thailand
Received 28 October 2015

Accepted 12 September 2016(*Corresponding Author)

Abstract Agricultural cooperative has been a crucial community business for Thais in the ruralarea of Thailand over 100 years. It is important to analyses of efficiency and factors affecting
efficiency. The research objectives were to (1) analyze the efficiency of agricultural
cooperatives in the lower-northern area of Thailand utilized by the Data Environment Analysis
Model (DEA Model) and (2) study the factors affecting the efficiency and operational
development of agricultural cooperatives in the lower-northern area of Thailand. The research
population comprised of agricultural cooperatives which identified as the general agricultural
cooperatives. The study area covered nine provinces comprise of 196 cooperatives. The
secondary data were collected from Financial Information Data Base of the Department of
Cooperative Auditing, Ministry of Agriculture and Cooperatives. The data were analyzed byusing Data Environment Analysis Model and Ordered Probit Model. The major findings were
(1) the entire efficiency index of agricultural cooperatives in the lower-northern area ofThailand expressed at the medium score index of efficiency. The return to scale of agricultural
cooperative operations in the lower-northern area of Thailand lighted on the Constant Return to
Scale (CRS), Diminishing Return to Scale (DRS), as well as Increasing Return to Scale (IRS)of 15.31, 49.49, and 35.20, respectively. (2) Factors affecting the efficiency and operational
development of agricultural cooperatives in the lower-northern area of Thailand expressed byvalue of total assets and value of credit business. According to the research results, it wassuggested that the cooperative operations should be reached the maximum point of efficiency
and it is necessary for cooperatives to make the operation cost management, the resources ofco-operative operations which comprised of the entire co-operative assets. Moreover; thecooperatives should pay the crucial role on credit business management.
Keywords efficiency analysis, factors affecting efficiency, agricultural cooperatives Ltd.

INTRODUCTION
A cooperative is an autonomous association of people who voluntarily cooperate for their mutual social,economic, and cultural benefit. Cooperatives include non-profit community organizations andbusinesses that are owned and managed by the people who use their services, a consumer cooperative,
or by the people who work there or by the people who live there, hybrids such as worker cooperatives
that are also consumer cooperatives or credit unions, multi-stakeholder cooperatives such as those thatbring together civil society and local actors to deliver community needs, and second and third tiercooperatives whose members are other cooperatives (The World Cooperative Monitor, 2015).
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Cooperative in Thailand was defined by 2 major groups; 1) Agricultural Co-operative sector and 2)
Non-Agricultural Co-operative. The agricultural cooperatives sector was comprised of agricultural
cooperative, land settlement cooperative, and fisheries cooperatives while the non-agricultural sector
was comprised of consumer cooperative, saving cooperative, service cooperatives and credit union
cooperative (The Federal of Savings and Credit Cooperative of Thailand Ltd, 2015).
In Thailand, Agricultural cooperatives were generally organized among the people engaging in
agricultural earning with varying kinds and degrees of need, thus resulting with various agricultural
cooperative types. Basically, the royal Thai government utilized agricultural cooperative as the tool forrural development especially in the agricultural and rural area since Thailand has been agricultural
economy base so the agricultural sector still be the important part in Thai economy. In addition,
agricultural cooperatives have been the biggest proportion among 7 types of Thai cooperatives which
was accounted for 53 percent (The Cooperative Promotion Department, Ministry of Agriculture andCooperative, the Royal Thai Government, 2015).
It is importance to analyses the efficiency of agricultural cooperatives in Thailand especially in theLower Northern region of Thailand which has been and still be the main agricultural area of thecountry. The research also examined factors affecting on their efficiency, and finally find out theguidance to help Agricultural Co-operatives to improve their operational efficiency.
OBJECTIVE
The objectives of this study are as follows.
1. To analyze the agricultural cooperatives Ltd. efficiency in the lower northern region of Thailand.
2. To find out the factors affecting on agricultural cooperatives efficiency and develop agricultural
cooperatives’ operation in the lower northern region of Thailand.
METHODOLOGYThe Study Population was comprised of agricultural cooperatives Ltd. which operated in 9 provinces in
the lower northern region of Thailand which include Kampangpet, Tak, Nakhonsawan, Pichit,
Pitsanulook, Petchabul, Sukhothai, Utaradit Provinces, and Uthaithani Province which accounted for
196 cooperatives.

Fig. 1 Map of lower northern region of ThailandⒸ ISERD

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The data was collected by secondary data from the information data base of Department of Cooperatives Audit, Ministry of Agriculture and Cooperatives, The Royal Thai Government which
comprised of the inputs data; cooperatives operational capitals, cooperatives’ debt, expenditures, thenumbers of officers, output data which comprised of total revenues, and number of cooperatives‘members. The data analysis was utilized Data Envelopment Analysis Model (DEA) to find out theindex of efficiency. The DEA is a relatively new data oriented approach for evaluating the performanceof a set of peer entities called Decision Making Units (DMUs) which convert multiple inputs into
multiple outputs (W. Cooper, 1984). This concept could be expressed as the following diagram.
Inputs
1. Cooperatives operational
capitals

Process

Outputs

DEA

1. Total revenues

2. Cooperatives’ debts

2 Number ofcooperatives ‘members

3. Expenditures
4. The numbers of officers

Fig. 2 Concept of inputs to outputs through Data Envelopment Analysis Model
The Analysis of factors affecting on Agricultural Co-operatives Ltd efficiency, was exploited by
Ordered Probit which was expressed by the following equation:
Efficiency = f (X1, X2 , X3, X4 , X5 , X6, X7)( 1)

Where: X1, = The Value of Agricultural Cooperatives Assets
X2 , = The Numbers of Agricultural Cooperatives Officers
X3, = The Value of Agricultural Cooperatives Deposit
X4 = The Value of Agricultural Cooperatives Credits
X5 = The Value of Agricultural Cooperatives Selling Business
X6 = The Value of Agricultural Cooperatives Collecting Business
X7= The Value of Agricultural Cooperatives Processing Business
RESULTS AND DISCUSSION
In order to answer the first research objective, the research results could be expressed as the efficiency
of agricultural cooperatives Ltd. in the Lower Northern region of Thailand as shown in Table 1.
Table 1 Agricultural Co-operatives Ltd. efficiency in the Lower Northern region of Thailand
The Level of Efficiency
Score
Meaning
0.81 – 1.00
The Highest Efficiency
0.61 – 0.80
The High Efficiency
0.41 – 0.60
The Medium Efficiency
0.21 – 0.40
The Small Efficiency
0.00 – 0.20
The Minimum Efficiency
Total

Agricultural Co-operatives Ltd.
Numbers
Percentage
The Average TE
133
68.88
0.926
33
16.84
0.725
17
8.67
0.523
9
4.59
0.311
2
1.02
0.150
196
100
0.527

Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

According to Table 1, the 133 out of 196 Agricultural Cooperatives Ltd. received the highest
efficiency which accounted for 68.88 percent, with the 0.926 or 92.60 percent of Technical Efficiency(TE). This mean that majority of Agricultural Cooperatives Ltd in the Lower Northern region ofThailand performed their operation in the good shape. There were only 2 Agricultural Cooperatives
accounted for 1.02 percent faced with the minimum efficiency which would be improved.
In order to answer the second research objective for factors affecting on efficiency, the results
could be expressed as Tables 2 and 3.
Table 2 Factors affecting on agricultural cooperatives Ltd. efficiency
Variables Coefficients Standard Error
Intercept
X1
X2
X3
X4
X5
X6
X7

29152.10607
0.029905614-152661.379-0.00717676
0.029655875-0.01626762-0.01106485-0.86824247

t StatP (Y=0)343926.6336 0.08476257 0.93254034
0.0040159 7.44680323 3.3542E-12
52791.37576 -2.8917863 0.00428213
0.005729983 -1.2524932 0.21194601
0.007794125 3.80490123 0.00019177
0.006648256 -2.4469003 0.01532823
0.013729747 -0.8059036 0.42131665
0.235262534 -3.6905259 0.00029302

Marginal Effects
P (Y=1)P (Y=2)-649299.13 707603.345
0.0219836 0.03782763-256800.96 -48521.802-0.0184801 0.00412656
0.0142807 0.04503105-0.0293824 -0.0031529-0.038149 0.01601931-1.3323361 -0.4041488

P (Y=3)P (Y=4)-649299.13 707603.345
0.0219836 0.03782763-256800.96 -48521.802-0.0184801 0.00412656
0.0142807 0.04503105-0.0293824 -0.0031529-0.038149 0.01601931-1.3323361 -0.4041488

Table 3 Results of Ordered Probit Model for analyzing factors affecting on
agricultural cooperatives Ltd. efficiency
Model

Unstandardized
Coefficients
B

1(Constant)Standardized
Coefficients

Std. Error

29152.106

Beta343926.634

t
0.085

Sig.
0.933

x1

0.03

0.004

0.841

7.447

0

x2

-152661.379

52791.376-0.278-2.8920.004

x3-0.0070.006-0.127-1.252

0.212

x4

0.03

0.008

0.398

3.805

0

x5

-0.0160.007-0.147-2.4470.015

x6-0.0110.014-0.034-0.8060.421

x7-0.8680.235-0.156-3.6910

According to factors affecting on agricultural cooperatives efficiency, there were 5 factors that
had affected on efficiency which were 1) the numbers of agricultural cooperatives officers, 2) the valueof agricultural cooperatives deposit, 3) the value of agricultural cooperatives credit, 4) the value ofagricultural cooperatives selling business, and 5) the value of agricultural cooperatives processing
business.
The research could be concluded that the majority of agricultural cooperatives Ltd. in the lower
northern region of Thailand performed in the highest efficiency. This indicated that agricultural
cooperatives Ltd. in the lower northern region of Thailand have been the main and crucial way to get
into economic development since cooperatives would be the only one community business for people
who live in the rural area that get along with the study of Chuamauengphan, (2003) and Kaewthip S.
Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2(2014). The Royal Thai Government could have the program to promote the agricultural cooperatives
business.
CONCLUSION
Majority of agricultural cooperatives Ltd. in the lower northern region of Thailand performed in thehighest efficiency. This means that in lower northern region of Thailand, agricultural cooperatives has
been the crucial community business to help people for their better standard of living in Thailand.
Moreover, the Royal Thai Government would take this research result to utilize the agricultural
cooperatives Ltd. as the tool for community development.
ACKNOWLEDGEMENT
I, personally, thank to my Father and mother who gave me their love all my life. Who support me inevery way of my needs. I would like to extend my thanks to my beloved family-Wittayakorn,
Puripunpinyoo, all of my heritages-my grandfather and grandmother.
REFERENCES
Chuamauengphan, A. 2003. The economic and social development of saving groups under the Thai Royal Project,
Journal of Economics, Chiang Mai University, 6 (1), 27-36.
DeeChin, T. 2013. The measurement of store cooperatives in Thai University by DEA model, Faculty of
Economics, Chiang Mai University, Thailand
Guzman, I. and Arcas, N. 2008. The usefulness of accounting information in the measurement of technicalefficiency in agricultural cooperatives. Annuals of Public and Cooperative Economics. 79, 107-131.
Kaewthip, S. and Pukdee, K. 2014. The study of agricultural cooperatives Ltd. efficiency in the upper northernpart of Thailand, Research Report, Maejo University, Thailand.
Maltz, Alan C. 2000. Defining and measuring organizational success, A multi-dimensional framework. Doctoral
Dissertation. Stevens Institute of Technology. USA.
Ngayvichit, U. 2005. Factors affecting on agricultural cooperatives Ltd. success in the upper northern part ofThailand. Master Thesis, Faculty of Economics, Chiang Mai University, Thailand.
Onwan, D. 2010. Factors affecting on community business success in Thailand. Research Report, Kasetsart
University. Bangkok, Thailand.
Prasuthon, P. and Takarnthaleangsak, P. 2014. The evaluation of agricultural cooperatives Ltd. efficiency inPetchaburi Province. Thailand.
Subpongskorn, U. 2012. The methodology of data envelopment analysis model. Journal of Economics, 16 (1),Chiang Mai University, Thailand.
The International Co-operatives Alliance. 2015. The world cooperatives monitor. www.ica.org.
The Federal of Savings and Credit Cooperative of Thailand. 2015. Saving cooperatives in Thailand.
www.fsct.com.
The Co-operatives Audit Department, Ministry of Agriculture and Cooperatives. 2015. The evaluation ofagricultural cooperatives Ltd. efficiency. Thailand.
The Co-operatives Audit Department, Ministry of Agriculture and Cooperatives. 2015. The financial informationof cooperatives and agricultural groups. Thailand.
The Co-operatives Promotion Department, Ministry of Agriculture and Cooperatives. 2015. The knowledge ofcooperatives in Thailand. http://www.cpd.go.th/ web_cpd /know_ coop02.htm, Thailand.
The Co-operatives Promotion Department, Ministry of Agriculture and Cooperatives. 2015. The information ofcooperatives promotion in Thailand. Thailand.
The Co-operatives Promotion Department, Ministry of Agriculture and Cooperatives. 2014. Information and lawsof cooperatives Ltd. in Thailand. Thailand.
Utthong, U. 2010. Efficiency and ratio gap of operational technology under the different atmosphere. Journal ofApplied Economics, 20 (2), 37-54.
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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Research article
erd

Diversity of Aquatic Insects in the Organic and Conventional
Rice Fields in Khon Kaen Thailand
DUANGRAT THONGPHAK*
Entomology Section, Department of Plant Science and Agriculture Resources,
Faculty of Agriculture, Khon Kaen University, Khon Kaen, Thailand
Email: duathg@kku.ac.th

CHULEEMAS BOONTHAI IWAI
Department of Plant Science and Agriculture Resources,
Faculty of Agriculture, Khon Kaen University, Khon Kaen, Thailand
Received 15 December 2015

Accepted 19 September 2016(*Corresponding Author)

Abstract Water quality has significant effects toward the diversity and distribution of aquatic
insect. The application of fertilizer and pesticides may degrade water quality and affect todiversity of aquatic insects. Aquatic insect in rice fields was surveyed to compare the diversity
between organic and conventional rice fields in Khon Kaen province during June to October
2015. Three replication of sampling by aquatic sweep net were conducted at sampling sites. The
result showed that aquatic insect was represented by 17 species belongs to 16 families of 6orders. The order Hemiptera was the highest in abundance groups in the fields (5 families)
followed by Odonata (3 families), Diptera (3 families), Coleoptera (2 families), Ephemeroptera
was the lowest in abundance (2 families) and Collembola (unidentified family). The richness ofaquatic insects in the organic rice field was found slightly higher than the conventional one. The
species diversity index (H') was 0.427 in organic site and conventional site was 0.401. This
study is considered to have no significant in diversity or abundance of aquatic insects between
organic and conventional rice field. Order Hemiptera was found abundant and dominant among
other orders.
Keywords aquatic insect, organic rice field, conventional rice field

INTRODUCTION
Rice production is one of the main agricultural activities in Thailand. Mostly, there are two types ofrice cultivation include organic and conventional methods (Kenji et al., 2005). For the convention ricecultivation, synthetic chemicals such as fertilizer and pesticides are generally applied while thesechemicals are not used in the organic rice cultivation. Aquatic insects play an important role in aquatic
ecosystem functioning (Dunbar et al., 2010). They are an important component of invertebrate
assemblages in aquatic ecosystem where they are a controlling group in food webs. At the larval stage,
they constitute the principal nutritive fauna for fish. Diversity of aquatic insects in rice field can bedivided into two groups: beneficial and insect pests (Bambaradeniya, 2000; DOA, 2010). The
beneficial insects are usually known as natural enemies Natural enemies are also known as biologicalagents in biological control for minimizing the population of insect pests. In paddy field, some of the
predators in rice fields are associated with water. Improper agronomic practices in rice field such as theextensive used of fertilizers and pesticides may degrade the disturbance of water quality. The diversityand distribution of aquatic insect communities, considering that some species of insects are very
sensitive to pollution and prefer to live in good environment with good quality water (Mohd Rasdi etal., 2012). Thus, the objective of this study is to compared diversity of aquatic insects between organicand conventional rice cultivation in Khon Kaen province northeastern Thailand.
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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

METHODOLOGY
The study was carried out in irrigation rice fields at the Khon Kaen province, north-eastern Thailand
during June to October 2015. Study site was divided into two plots; organic cultivation (no chemical
pesticides and chemical fertilizers applied) and conventional cultivation (applied chemical pesticides
and chemical fertilizers). The samples were taken two2 periods including early period (30 days after
transplanting, DAT) and mid period (60 days after transplanting, DAT). Aquatic insects were collectedin three replications at each sampling areas. The insects were randomly collected using sweeping net
dragged about one meter. The samples were preserved in 70% ethyl alcohol and were identified at least
up to taxonomic order using the identification guides of Dudgeon (1999), McCafferty (1983), Yule andSen (2004). The specimens were also compared with the reference collections at the Insect Museum,
Faculty of Agriculture, Khon Kaen University. The Shannon-Wiener’s diversity index (Krebs, 1999),
was used to calculate the diversity of aquatic insects. The formula of the Shannon-Wiener’s diversity
index (H´) used is presented as followsH´ = Σ (pi)(lnpi)
i=1
Where H’ is species diversity index, s is number of species and pi is proportion of the total sample
belonging to i th species. The evenness index (J´) (Krebs, 1999) was calculated to determine the equal
abundance of aquatic insects in each study site as follows:
J´ =

H´
H´MAX

Where H´ is observed index of species diversity and H´MAX is maximum possible index ofdiversity. Shannaon-Wiener Index (H’) which accounts for both abundance and evenness was used tocharacterize species diversity. Diversity values may very directly with water quality and low diversity
may indicate an unstable community (Chiangthong and Phalaraksh, 2007).
RESULTS AND DISCUSSION
A total of 951 individual of aquatic insects from six orders (Hemiptera, Diptera, Coleoptera, Odonata,
Ephemeroptera and Collembola) and twenty-three different families were recorded in this study. The
order Hemiptera was the highest in abundance groups (8 families included Hydrometridae
Mesoveliidae Micronectidae Notonectidae Veliidae Nepidae Gerridae and Pleidae) followed by
Coleoptera (5 families included Dytiscidae Norteridae Hydraenidae Hydrophilidae and Scirtidae),
Diptera (4 families included Ceratopogonidae Chironomidae Culicidae and Stratiomyidae), Odonata (3families included Coenagrionidae Libellulidae and Protoneuridae) Ephemeroptera (2 families of
Baetidae and Caenidae) and Collembola was the lowest in abundance (1 unidentified family). Table 1
shows the insect composition for two sampling periods of two studied sites. The most abundance ofaquatic insect was found in mid period than the early period. The richness of aquatic insects in theorganic site was found slightly higher than the conventional site. The dominant aquatic insects found in
this study were from the Micronectidae with 21 percentage of abundance followed by Baetidae(18.30%) and Coenagrionidae (6.73%). In organic rice field, the Order Hemiptera was found highest in
number of taxa followed by Odonata and Diptera in early period (30 DAT). Order Hemiptera was also
the highest of number taxa in the mid period (60 DAT) followed by Ephemeroptera and Diptera
respectively. Meanwhile, order Collembola was found only in mid period (Fig. 1). In conventional rice
field, order Odonata was found highest of number taxa in early period followed by order Hemiptera
and Diptera respectively while order Ephemeroptera was found highest of number taxa in mid periodⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

followed by order Coleoptera and Hemiptera respectively. In this study, order Collembola was foundonly in mid period similar to the organic rice field. The Collembola is dominant group of scavenger inthe rice field. They are known as an important source prey for predator insect (Alvarez et al., 1997)
The collembolan are more abundant in moist rice soil rich in organic matter and may decreaseabundant in rice field after pesticide application. Moreover, the different species react differently to thechanging conditions as the plant grows and canopy close (Takagi et al., 1996).

OdonataOrder of insect

Hemiptera
Ephemeroptera
Mid period

Diptera

Early period
Collembola
Coleoptera
0

20

40

60
80
100
Number of taxa

120

140

Fig. 1 Taxonomic of aquatic insects in conventional rice field
OdonataOrder of insect

Hemiptera
Ephemeroptera
Mid period

Diptera

Early period
Collembola
Coleoptera
0

20

40

60

80

100

no. of taxa

Fig. 2 Taxonomic of aquatic insects in the conventional rice fieldⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Table 1 Relative proportion of aquatic insects in the organic rice field (ORG) andthe conventional rice field (CON) at Khon Kaen province Thailand
Early Period

Mid Period

total%abundance

6

13

1.37

0

1

24

2.52

1

8

10

1.05

0

1

0

1

0.11

0

7

0

16

1.68

1

0

0

0

1

0.11

unknown

0

0

2

2

4

0.42

Hydrocanthus sp.

0

0

0

1

1

0.11

Hydraenidae

Hydraena sp.

2

0

0

1

3

0.32

Hydrophilidae

unknown

1

2

0

31

34

3.58

Coleoptera

Hydrophilidae

Hydrobiomorpha sp.

0

1

0

4

5

0.53

Coleoptera

Scirtidae

unknown

0

0

8

12

20

2.10

0

0

38

5

43

4.52

Order

Family

Genus

ORG

CON

ORG

CON

Coleoptera

Dytiscidae

unknown

20

5

Coleoptera

Dytiscidae

Hydaticus sp.

0

23

Coleoptera

Dytiscidae

Hydrovatus sp.

1

0

Coleoptera

Dytiscidae

Hydroporus sp.

0

Coleoptera

Dytiscidae

Hyphydrus sp.

9

Coleoptera

Dytiscidae

Eretes sp.

Coleoptera

Norteridae

Coleoptera

Norteridae

Coleoptera
Coleoptera

Collembola
Dipteraunknown

0

0

1

0

1

0.11

DipteraCeratopogonidae

Bezzia sp.

1

0

23

1

25

2.63

Diptera

Chironomidae

Chironominae

12

0

22

4

38

4.00

Diptera

Chironomidae

Tanypodinae

8

21

6

0

35

3.68

Diptera

Culicidae

unknown

12

8

0

17

37

3.89

DipteraStratiomyidae

Odontomyia sp.

1

3

4

0

8

0.84

Ephemeroptera

BaetidaeCloeon sp.

26

0

57

91

174

18.30

Ephemeroptera

Caenidae

Caenodes sp.

0

26

1

2

29

3.05

Hemiptera

Hydrometridae

Hydrometra sp.

0

0

2

1

3

0.32

Hemiptera

Mesoveliidae

Mesovelia sp.

0

0

1

7

8

0.84

Hemiptera

Micronectidae

Micronecta sp.

105

1

90

10

206

21.66

Hemiptera

Notonectidae

Notonecta sp.

0

3

5

0

8

0.84

Hemiptera

Notonectidae

Aphelonecta sp.

7

0

0

0

7

0.74

Hemiptera

Notonectidae

Nychia sp.

0

0

9

0

9

0.95

Hemiptera

VeliidaePseudovelia sp.

0

0

0

1

1

0.11

Hemiptera

Nepidae

Ranatra sp.

3

0

0

0

3

0.32

Hemiptera

Nepidae

Laccotrepes sp.

1

1

0

0

2

0.21

Hemiptera

GerridaeAmemboa sp.

0

2

0

0

2

0.21

Hemiptera

pleidaeParaplea sp.

1

0

0

0

1

0.11

Odonata

Coenagrionidae

unknown

0

0

5

22

27

2.84

Odonata

Coenagrionidae

Agrionemis sp.

63

0

1

0

64

6.73

Odonata

Libellulidae

Brachythemis sp.

1

33

0

0

34

3.58

Odonata

Libellulidae

Crocothemis sp.

24

0

0

0

24

2.52

Odonata

Libellulidae

Orthemis sp.

0

24

0

0

24

2.52

Odonata

Libellulidae

sympetum sp.

0

1

0

0

1

0.11

Odonata

Protoneuridae

Prodasineura sp.

4

1

0

0

5

0.53

total

285

150

289

227

951

100

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

The highest Shannon-Weiner Index in organic rice fields which was 2.02 in mid period. The
lowest indexes were found in conventional rice fields and organic rice which was 1.92 in early period(Fig. 3). In this study the diversity index of aquatic insects is no different between organic andconventional rice field were similar to those recorded by Rozilah and Ali (1998), where no significant
in diversity or abundance of aquatic insects when insecticide treated and untreated rice fields werecompare. This study showed that the number of families in aquatic insects from organic cultivation (15families) was less than conventional cultivation (16 families) in mid period, but found that ShannonWeiner Index average score was higher in organic site than conventional site and found the populationsof aquatic insects were higher in the fields. Roger (1996), maintain that the dominance of faunalassemblages by one or two taxa and lowered species richness is likely to indicate community
disturbance by agrochemicals in rice field environments. In this study, the insect samples taken fromthe organic rice field in mid period assemblages with greater richness and slightly higher Shannon
diversity indices than those collected from the conventional rice field. The major distinction between
these management regimes was the application of agrochemicals exclusively to the conventional rice
fields. According to Settle et al., (1996) demonstrated that the loss of species richness and decreased
faunal assemblage evenness after pesticide applications.
(A)

(B)
2.50

2.00

H'

1.92

J'

2.02
1.92

1.50
0.87

0.87

1.00
0.50

Shannon index(H')

Shannon index (H')

2.50

0.00

H'

J'

2.00

2.00
1.50
0.92

1.00

0.91

0.50
0.00

Org

Con

Org

Rice fieldCon
Rice field

Fig. 3 Comparison between Shannon index and Evenness of aquatic insects in organic rice field(org) and conventional rice field (Con): (A) early period, (B) mid period
CONCLUSION
This study concluded that the organic cultivation method was recommended to apply in rice fields.
Although, Shannon-Wiener diversity index showed no significantly difference between two ricecultivation practices. The interesting point arising from this study is that the aquatic insects
representative of the Coleoptera, Hemiptera and Odonata were all beneficial insects as predator of rice
pest. The result from this study indicates that the aquatic insect communities are important factors forcheck and balance in rice fields thereby controlling increase in insect pest populations. This condition
is important in understanding ecological rice pest management. For the further work, the waterparameters should be included.
ACKNOWLEDGEMENTS
This research was supported by the Integrated Water Resource Management Centre in Northeast,
Thailand.

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REFERENCES
Alvarez, T., Frampton, G.K. and Goulson, D. 1997. Population dynamics of epigeic Collembola in arable fields,
The importance of hedgerow proximity and crop type. Pedobiologia, 41, 110-114.
Bambaradeniya, C.B.N. 2000. Ecology and biodiversity in an irrigated rice field ecosystem in Sri Lanka. Ph.D.
thesis. University of Peradeniya, Sri Lanka.
Chiangthong, K. and Phalaraksh, C. 2007. Use of aquatic insects as bioindicators of water quality of Mae Kham
Watershed, Chaing Rai Province. KKU. Res J., 12 (3), 277-288.
Department of Agricultural, DoA, Malaysia. 2010. Buku Maklumat Jabatan Pertanian. pp. 44, Malaysia.
Dunbar, M.J., Warren, M, Extence, C., Baker, L., Cadman, D. and Mould, D.J. 2010. Interaction between
macroinvertebrates, discharge and physical habitat in upland rivers. Aquatic Conservation and Marine andFreshwater Ecosystem, 20, 31-44.
Dudgeon, D. 1999. Tropical Asian stream, Zoobenthos, Ecology and Conservation. Hong Kong University Press.
Hong Kong.
Hamasaki, K., Tanaka, K., Nakatani, Y., Yoshitake, H. and Tabata, J. Effect of organic cultivation practices onarthropod assemblages in paddy fields in Tochigi prefecture, National Institute for Ago-Environment
Sciences, Japan.
Krebs, C.J. 1999. Ecological methodology, Addison-Educational Publishers, California, 581.
McCafferty, W.P. 1983. Aquatic entomology. Jones and Bartlett Publishers Inc., Boston.
Mohd Rasdi, Z., Fauziah, I., Ismail, R., Mohd Hafezan, S., Fairuz, K., Hazmi, A.D. and Che Salmah, M.R. 2012.
Diversity of aquatic insects in Keniam River, national park, Pahang, Malaysia. Asian Journal of Agriculture
and Rural Development, 2 (3), 312-328.
Rozilah, I. and Ali, A.B. 1998. Aquatic insect populations in the Muda rice agroecosystem. In Rice
Agroecosystem of the Muda Irrigation Scheme Malasia, Eds. Nashriyah, B.N., Ho, N.K., Ismail, B.S.,
Ahyaudin, B.A. and Lum, K.Y. Malaysian Institue of the Nuclear Technology Research (MINT) and Muda
Agricultural Development Authority (MADA).
Settle, W.H., Ariawan, H., Astuti, E.T. and Cahyana, W. 1996. Managing tropical rice pests through conservationof generalist enemies and alternative prey. Ecology, 77, 1975-1988.
Tanagi, M., Sugiyama, A. and Maruyama, K. 1996. Effect of rice plant covering on the density of mosquito andother insects in the rice field. Applied Entomology & Zoology. 31 (1), 75-90.
Yule, C.M. and Sen, Y.H. 2004. Freshwater invertebrates of the Malaysian region. Aura Productions Sdn. Bhd.
Selangor, Malaysia.
.

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Research article
erd

Variation in Grain Morphology of Upland Rice Varieties from
Luang prabang Province Lao PDR
VUA XIONGSIYEENorthern Agriculture and Forestry College, Luang prabang, Lao PDR
Division of Agronomy, Faculty of Agriculture, Chiang Mai University, Thailand
Email: vuaxiongsiyee@yahoo.com

CHANAKAN PROM-U-THAI*Division of Agronomy, Faculty of Agriculture, Chiang Mai University, Thailand
Lanna Rice Research Center, Chiang Mai University, Thailand

Email: chanakan15@hotmail.com; chanakan.p@cmu.ac.th
Received 13 November 2015

Accepted 19 September 2016(*Corresponding Author)

Abstract Luang prabang province is recognized as a major area of the diversity of Oryza sativa
L. in Lao PDR. Grain morphological characteristics can be used as the primary informationof genetic variation among different rice varieties in the local germplasm which can be asource of value adding traits for rice breeding programs. The purpose of this study wasevaluated variation in grain morphological characteristics of upland rice varieties from Luang
prabang province, Lao PDR. The samples were collected from three districts, Ponxay (PX), Pak
Ou (PO) and Xieng Ngeun (XNg), two villages each. Grain morphological characteristics were
measured including grain size (length, width, and thickness), weight, shape, and endosperm
type and pericarp color. The total of 60 samples were collected which was separated into 26, 10,
and 24 samples from PX, PO, and XNg, respectively and among these samples 42 and 18
samples were glutinous and non-glutinous endosperm types, respectively. The 51 samples were
found in non-pigmented, 4 in red and 5 in black pericarp colors. There was variation of grain
size among 60 samples. Grain length, width and thickness were ranging from 8.61-11.63, 2.674.27 and 1.97-2.47 mm, respectively. Grain shape was determined by using the ratio of grain
length/width and most samples (58 varieties) were distinguished as large grain type and the rest
in slender type. One hundred grain weight was also varied from 2.05-4.04 g among brown riceof 60 samples. The grain weight was varied with grain length, width and thickness in multiple
regression of y = 0.39 (grain length) + 0.53 (grain width) + 1.42 (grain thickness) – 5.52 at R2 =0.89 (p < 0.05). This study demonstrated the variation in grain morphological characteristics of
upland rice varieties from Luang prabang province, Lao PDR. The variation of nutritional
quality was subjected to evaluate in the further investigation which can be used as the basic
information for the selection traits of rice varieties in the further breeding program.
Keywords Luang prabang, rice varieties, rice grain morphological characteristics, color, weight,
village

INTRODUCTION
Grain morphological characteristics especially size and shape is an important component of grain yieldand quality which have been used as the criterion of selection since cereals were first domesticated(Wang et al., 2012). Preferences for grain size and shape vary from one group of consumers to another.
Some ethnic groups prefer short bold grains, some prefer medium-long grains, and other highly prize
long slender grains. In general, long grains are preferred in the Indian subcontinent, but medium tomedium-long rice are preferred in Southeast Asia (IRRI, 2002).
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Globally, improving quantity and quality of rice grain have been approached to solve several
problems among the world population such as decreasing the number of hidden hunger andmalnutrition (Burchi et al., 2011). Breeding for high yielding and nutritional quality has beensuggested as strategy to solve the problems (Marie and Howarth, 1997), especially in Laos where
malnutrition problems are wide spread among the population due to consumption of low nutritional
value rice (WHO, 2011). On the other hand, rice is an important source of energy, iron, calcium,
vitamins, and protein in the diet of the Asian population, including Laos (IRRI, 1993). However, awide variation of grain morphological characteristics will be required as source of genetic materials in
breeding for some specific traits as it would be effect on consumer’s acceptance at the end of processes.
Luang prabang is one of the provinces in the northern of Lao PDR and it has been reported to berich in genetic diversity among rice germplasms. A total of 13,192 samples of traditional varieties werecollected in Lao PDR since 1995 to 2000, it was found the largest germplasm of 5,915 (44.8%)
varieties in the northern region and Luang prabang had 1,243 samples (9.4% of the total) and 85.5% of
the collected samples were glutinous rice (Appa Rao et al., 2002). Therefore, Luang prabang has beenrecognized as rice diversity areas in Lao PDR and it is approximately 25% of the total upland riceproduction area of the country, where rice is cultivated on sloping land using slash-and-burn methods
without tillage and input fertilizers (World Bank, 1995). However, there has not been reported yet indetail on variation of some useful traits among this germplasm and grain morphology are the charactersthat easy and rapid to determine.
Previous studies reported that seed of local rice varieties maintained by farmers are geneticallydiverse (Dennis, 1987). Different varieties can be given similar names and different names can beapplied to the same varieties (Harlan, 1992). Diversity analyses may be based on morphologicalcharacteristics such as shape, size and pigmentation of plant parts that local farmers use to distinguishdifferent rice varieties (Morishima et al., 1980). Molecular techniques such as AFLP, ISSR and SSR(Saini et al., 2004) allow variation to be evaluated between individual plants. Grain morphologicalcharacteristics can be used as the primary information of genetic variation among different rice
varieties in the local germplasm.

Pak OuPonxayXieng Ngeun

Fig. 1 Map of Luang prabang province, Lao PDR and the detail location of 3 districts(Ponxay, Pak Ou and Xieng Ngeun), where the upland rice samples were collectedⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

OBJECTIVE
This study was attempted to identify grain morphological characteristics of upland rice varieties
collected from different locations at Luang prabang province, Lao PDR.
METHODOLOGY
Rice samples were collected among 3 districts, Ponxay (PX), Pak Ou (PO) and Xieng Ngeun (XNg)
with 2 villages each from Luang prabang Province, Lao PDR (Fig. 1). The totals of 60 rice samples
were collected from farmers. Grain morphological characteristics were determined among each sampleof the total collection. Seed size (grain length, width, and thickness) of the unhusked seed wasmeasured by digital Vernier caliper (50 seeds for each sample). The unhusked seeds were dehusked
manually by hand to separate between the husk and brown rice. The 100 grains weight of unhusked
and brown rice grains was weighed in 3 independent replications. The color of hull and pericarp was
also recorded. The analysis of variance was used to determine the significant difference of eachmorphological characteristic among rice varieties at p<0.05 by statistical analysis software
STATISTIX 8.0. The Least Significant Difference was used to indicate the difference of grain size,
weight and shape among varieties.
RESULTS AND DISCUSSION
The total of 60 upland rice samples (42 glutinous and 18 non-glutinous endosperm types) werecollected from three districts with 2 representative villages each of Luang prabang province, Lao PDR.
26 samples from PX (14 in Chomchieng (CC) and 12 in Houameuang (HM)), 10 samples from PO (6in Hoi-Oth (HO) and 4 in Hoi-Loh (HL)) and 24 samples from XNg (10 in Phasanine (PSN) and 14 inPhouthat (PT)). Luang Prabang has been designated as one of the center diversity of Oryza sativa L. in
Laos (Appa Rao et al., 2002). Even though many characteristics have not been evaluated the variation
yet, but genetic diversity among the germplasm has been declared in this area. The variation ofendosperm type is depending on the usual consumption and traditional preference among consumers ineach area. It has been reported that Hmong ethnic group preferred to consume non-glutinous rice rather
than glutinous rice, while Khamu ethnic group preferred glutinous rice (Sengxua, 2006; Roder et al.,1996).
Grain Morphological Characteristics
51 samples found in off white pericarp color (non-pigmented color) (33 in glutinous and 18 in nonglutinous), 4 in red and 5 in black color (glutinous). This suggests that the highland rice germplasm ismostly in white pericarp color which may not depend on the satisfying on the demand market, but theirconsumption preference. However, special quality rice, e.g. varieties with pigmented pericarp withblack and red color has been found and recognized as high antioxidative properties which can protect
against oxidative damages in a range of diseases such as cardiovascular and cancer diseases (Cicero
and Derosa, 2005). Unlike grain shape and size, these properties can be varied according to theinteraction between rice varieties x growing condition which should carefully pay attention when
dealing with these properties in the future (Nkori Kibanda and Luzi-Kihupi, 2007).
Grain weight and size of brown rice was varied among different rice samples collected (p < 0.05)(Table 1). 100-grain weight was ranged from 2.05-4.04 g. The grain weight was varied with theheaviest and lightest grains weight found in varieties Mai-hoke (4.04 g) from HM and Kao siew (2.05g) from HL, respectively. The grain length ranged from 8.61-11.63 mm with the average of 10.00 mm.
The shortest and longest grains were found in varieties Chao khao 2 (8.61 mm) from PSN and LeumⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

poua (11.63 mm) from HM, respectively. The grain width ranged from 2.67-4.27 mm with theaverage of 3.51 mm. The narrowest and widest grains found in varieties Kao siew (2.67 mm) from HL
and Luang leuang (4.27 mm) from HM, respectively. The thickness of individual unhusked grain
ranged from 1.97-2.47 mm. The thinnest and thickest grains found in Kao siew (1.97 mm) and Niew
mad-deng (2.47 mm) from PSN, respectively. Grain size and shape are associated with milling quality,
grain weight and proportion of the main growth axes of the grain (Gegas et al., 2010). The grain sizeand shape can be effectively used to improve yield and grain quality (Wang et al., 2012), and areamong the first quality characteristics considered in developing new commercial varieties (Webb,
1980). Therefore, breeding for specific grain weight together with some other useful traits shouldcarefully consider of grain size as it was found in this study. Thus, a diverse range of grain size andshape among these germplasms will be useful in breeding program as source of genetic materials when
dealing with specific shape for consumer’s demand.
Table 1 Grain morphological characteristics of the collected 60 rice samples
Collection
place

Chomchieng
villageHouameuang
village

Hoi-Othvillage

Variety
ParkerHom-ma-li
Bor-taKam leuang-yao
Kao peing
Chao dam
Kam mad-dam
Kam leuang-dam
Kao dinNiew mad-pom
Chao khoon
Chao deng
Kao wai
Chao leuang
Kao paie
Kam khao-dam
Kao ngeun
Ki-kung
Pa-ya
Leum-poua
Kao Chuk
Mai-hokeKao hoke
Chao leuang 2
Kai-noi
Luang leuang
Kam dor
Chao khao
Niew valee
Niew leuang
Chao peak-peing
Kao ying

Type of
rice
G
NG
G
G
G
NG
G
G
G
G
NG
NG
G
NG
G
G
G
G
G
G
G
G
G
NG
G
G
G
NG
G
G
NG
G

Length
(mm)
11.23
11.20
11.09
10.43
10.15
9.73
10.07
9.14
9.08
9.90
9.62
9.46
11.02
10.45
9.50
9.89
10.27
9.82
10.48
11.63
9.45
11.52
8.67
10.12
10.49
9.28
9.40
9.56
10.95
10.10
9.17
10.17

Grain Morphological Characteristics
Width
Thickness
L/W
100-grain
(mm)
(mm)
ratio
weight
3.86
2.36
2.92
3.77
2.99
2.11
3.75
2.82
3.73
2.35
2.97
3.32
3.59
2.18
2.91
2.76
3.59
2.29
2.83
3.25
3.19
2.19
3.06
2.82
3.90
2.22
2.58
2.79
3.73
2.18
2.46
2.42
3.30
2.12
2.75
2.48
3.82
2.37
2.60
3.36
3.32
2.12
2.90
2.77
3.18
2.16
2.98
2.36
3.34
2.28
3.32
3.07
3.41
2.27
3.07
3.27
3.24
2.20
2.94
2.33
3.79
2.32
2.61
2.88
3.72
2.32
2.77
3.33
3.87
2.38
2.54
3.35
4.02
2.39
2.61
3.41
3.90
2.33
2.99
3.78
4.08
2.37
2.32
3.40
3.81
2.44
3.03
4.04
3.68
2.24
2.36
2.70
3.32
2.09
3.06
2.77
3.23
2.17
3.26
2.74
4.27
2.42
2.18
3.55
3.68
2.18
2.56
2.48
3.26
2.09
2.94
2.68
3.57
2.25
3.08
3.24
3.22
2.15
3.15
2.76
3.43
2.20
2.68
2.75
3.21
2.15
3.17
2.84

Ⓒ ISERD

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pericarp
color
white
white
white
black
white
white
black
black
white
white
white
white
white
white
red
black
white
white
white
white
red
white
white
white
white
white
black
white
white
white
white
white

IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Chao valee
Chao mad-pom
Mak-kheua
Kao Siew
Leuak-yai
Chao khao 2
Kao yuakSia-chaLuang deng
Chao dam 2
Kao peing 2
Niew mad-dengChao-leuang 3
Kao din 2
Kao tamKa-yoke
Kao Kang
Niew leuang 2
Nam-manh
Niew peak-peing
Poua-mia
Kao peing 3
Ma-ma
Niew mad-deng 2
Chao khao 3
Leuak-yai 2
Leuak-noi
Kao yai

NG
NG
G
G
NG
NG
G
NG
G
NG
G
G
NG
G
G
G
G
G
G
G
G
G
G
G
NG
NG
NG
G

10.87
3.02
2.12
3.61
2.85
white
9.22
3.50
2.15
2.64
2.53
white
Hoi-Lohvillage
8.76
4.14
2.34
2.12
2.99
white
10.33
2.67
1.97
3.88
2.05
white
9.50
3.07
2.06
3.10
2.61
white
8.61
3.09
2.14
2.79
2.47
white
11.59
3.71
2.26
3.14
3.63
white
9.26
3.11
2.09
2.98
2.43
white
9.21
4.17
2.42
2.22
3.56
white
Phasaninevillage
9.72
3.16
2.21
3.08
2.80
white
10.14
3.51
2.31
2.90
3.12
white
9.56
4.13
2.47
2.32
3.36
red
10.03
3.26
2.12
3.09
2.63
white
9.56
3.18
2.08
3.03
2.51
white
8.92
3.51
2.39
2.55
2.53
white
11.33
3.61
2.28
3.16
3.55
white
10.86
2.97
2.16
3.68
2.82
white
9.36
3.42
2.30
2.76
2.87
white
9.36
3.99
2.40
2.35
3.23
white
9.27
3.68
2.35
2.53
2.86
white
10.07
3.50
2.27
2.89
2.75
white
Phouthatvillage
10.95
3.66
2.37
3.01
3.31
white
10.24
3.62
2.24
2.84
2.92
white
9.39
3.93
2.40
2.41
3.18
red
9.70
3.03
2.12
3.21
2.60
white
10.20
3.13
2.20
3.27
2.75
white
9.61
3.06
2.12
3.15
2.61
white
11.32
3.73
2.44
3.04
3.89
white
n
60
60
60
60
60
min
8.61
2.67
1.97
2.12
2.05
max
11.63
4.27
2.47
3.88
4.04
mean
10.00
3.51
2.24
2.88
2.96
SD
0.78
0.36
0.12
0.38
0.43
CV (%)
1.47
1.59
2.05
1.68
1.36
F-test
**
**
**
**
**
LSD (0.05)
0.24
0.09
0.07
0.08
0.07
** Significant difference at p< 0.01; CV= coefficient of variation; SD= standard deviation; n= number of sample;
min= minimum; max= maximum; LSD= least significant difference at p< 0.05; G: Glutinous; NG: Non-glutinous
The value of grain size in each sample is averaged from 50 grains.

The ratio of grain length/width was used to separate grain shape of unhusked rice. Most samples(58 varieties) were distinguished as large grain type and the others 2 samples are slender type (Fig. 2).
Grain weight was varied with grain length, width and thickness in multiple regression of y = 0.39
(grain length) + 0.53(grain width) + 1.42(grain thickness) – 5.52 at R2 = 0.89 (p < 0.05).

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Length (mm)Grain shape
11.50
11.00
10.50
10.00
9.50
9.00
8.50
slender type
8.00
7.50
7.00
6.50
2.50
3.00

CC
HM
HO
HL

large type
PSN

round type
PT

3.50
4.00
Width (mm)4.50

Fig. 2 The grain shapes of unhusked grain among rice samples
CONCLUSION
A wide variation of grain morphological characteristics has been found among the local upland rice as
it was expected among the collected samples.
Most of rice samples are in a large grain shape with only few samples are slender type. Grain
weight is an important characteristic in commercial networks as it is used to determine the production
and price of rice. In this germplasm, Grain weight was varied with grain length, width and thickness in
multiple regression of y = 0.39 (grain length) + 0.53(grain width) + 1.42(grain thickness) – 5.52 at R2 =0.89 (p < 0.05). The results of this study can be used as the basic database of rice germplasm in Luang
prabang province for the selection of rice varieties in further breeding program. However, other usefultraits of nutritional qualities such as iron, zinc, protein, silicon and antioxidant properties should befurther evaluated.
ACKNOWLEDGEMENTS
The authors are grateful for the financial supported by International Development Research Center(IDRC) and Southeast Asian Regional Center for Graduate Study and Research in Agriculture(SEARCA) and the National Research University Program of Thailand’s Commission on Higher
Education.
REFERENCES
Appa Rao, S., Bounphanousay, C., Schiller, J.M. and Jackson, M.T. 2002. Collection and classiﬁcation of rice
germplasm from the Lao PDR between 1995 and 2000. Ministry of Agriculture and Forestry, Lao-IRRI
Project, Vientiane, Laos, 576.
Burchi, F., Fanzo, J. and Frison, E. 2011. The role of food and nutrition system approaches in tackling hidden
hunger, Res. Public Health Int. J., 8 (2), 358-373.
Cicero, A.F.G. and Derosa, G. 2005. Rice bran and its main components, Potential role in the management ofcoronary risk factors, Curr Top Nutraceut Res., 3, 29-46.
Dennis, J.V. 1987. Farmer management of rice variety diversity in northern Thailand. Ph.D. Thesis, Cornell
University. USA.
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Gegas, V.C., Nazari, A., Griffiths, S., Simmonds, J., Fish, L., Orford, S., Sayers, L., Doonan, J.H. and Snape, J.W.
2010. A genetic frame work for grain size and shape variation in wheat. Plant Cell, 22, 1046-1056.
Harlan, J.R. 1992. Crops and man. Second Edition. American Society of Agronomy, Madison, USA.
IRRI (International Rice Research Institute). 1993. IRRI rice almanac, 1993-1995. Manila Philippines. 142 .
IRRI (International Rice Research Institute) 2002. Discussion paper, No. 44. A proposal for IRRI to establish agrain quality and nutrition research center (ISBN 971-22-0177-5).
Marie, T.R. and Howarth, E.B. 1997. Plant breeding, A long-term strategy for the control of zinc deficiency in
Vulnerable populations.
Morishima, H., Sano, S. and Oka, H.I. 1980. Observations on wild and cultivated rices and companian weeds inthe hilly area of Nepal, India and Thailand. Report of a Study Tour in Tropical Asia, 1979. National Instituteof Genetics, Mishima, Japan.
Nkori Kibanda, J.M. and Luzi-Kihupi, A. 2007. Influence of genetic and genotypic x environment interaction on
quality of rice grain. African Crop Sci. J., 15 (4), 173-182.
Roder, W., Keoboulapha, B., Vannalath, K. and Phouaravanh, B. 1996. Glutinous rice and its importance for hill
farmers in Laos. Economic Botany, 50 (4), 401-408.
Saini, N., Jain, N., Jain, S. and Jain, R.K. 2004. Assessment of genetic diversity within and among Basmati andnon-Basmati rice varieties using AFLP, ISSR and SSR markers. Euphytica, 140, 133-146.
Sengxua, P. 2006. Rice-base traditions and beliefs of the Hmong. In Rice in Laos, Edited by Schiller, J.M.,
Chanphengxay, M.B, Linquist, B. and Appa Rao, S., 107-112.
Wang, S., Wu, K., Yuan, Q., Liu, X., Liu, Z., Lin, X., Zeng, R., Zhu, H., Dong, G., Qian, Q., Zhang, G. and Fu,
X. 2012. Control of grain size, shape and quality by OsSPL16 in rice. Nature Genetics, 44, 950-954.
doi:10.1038/ng.2327.
Webb, B.D. 1980. Rice quality and grades. In Rice Production and Utilization, Edited Luh, B.S. AVI publ. Co.,
Inc., Westport, Connecticut., 543-565.
WHO (World Health Organization). 2011. Who country cooperation strategy for the Lao People’s Democratic
Republic 2012-2015. Lao PDR.
World Bank. 1995. Lao PDR agricultural sector memorandum, An agricultural sector strategy. Report No.
13675-LA. World Bank, Washington, DC.

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Research article
erdInfluence of Coral Nursery Units on Fish Assemblage
JESRELLJANE AARON-AMPER*
College of Fisheries and Marine Sciences, Bohol Island State University Candijay Campus,
Cogtong, Candijay, Bohol, Philippines
Email: jesrelljane@gmail.com

SAMUEL J. GULAYAN
College of Fisheries and Marine Sciences, Bohol Island State University Candijay Campus,
Cogtong, Candijay, Bohol, Philippines

JOSUEH M. GULAYAN
University of the Philippines Visayas, Miagao, Iloilo, Philippines
Received 14 January 2016

Accepted 11 October 2016(*Corresponding Author)

Abstract Since 2012, the Department of Science and Technology-Philippine Council for
Agriculture and Natural Resources Research and Development (DOST-PCAARD) has beenfunding a coral reef restoration project, conducted by different universities in the Philippines.
As part of this project, coral nursery units (CNUs) have been deployed to supply high quality
coral nubbins aimed at reducing the dependence of coral fragments from wild coral populations.
Changes in the reef fish assemblage were assessed after four months to find out whether fishes
are attracted to and produced at the CNUs. Six CNUs were deployed at 30 m apart from eachother. Fishes were counted and identified using the fixed-point technique. Fish density andspecies richness were compared before and after CNU installation. Both production andattraction of reef fishes were evident, notably, by the abundance of Apogonidae. The highconcentrations of secondary consumers are the main evidence for the attraction of the CNUs.
Our results indicate that CNUs can be used as an effective management and restoration tool for
improving the local fishing yields.
Keywords coral cover, fish assemblage, marine protected areas, nursery

INTRODUCTION
The Philippines is one of the world’s centers of marine biodiversity and multi-taxa marine endemism(Roberts et al., 2002). However, the country’s marine resources are also experiencing the highest levelof anthropogenic and climatic threats. The anthropogenic threats include fishing overcapacity;
overfishing and destructive fishing practices; increased domestic, agricultural, and industrial runoff
from a burgeoning population; poor land use; and increased sedimentation from forest deforestation
and un-regulated mining activities (Cabral et al., 2014).
One of the ecosystems in the Philippines that are in serious deterioration-suffering massive, longterm declines in abundance and diversity of species are the coral reefs. In order to save our reefs, theDepartment of Science and Technology-Philippine Council for Agriculture and Natural Resources
Research and Development (DOST-PCAARD) provided funds for different universities in thePhilippines to implement a coral reef restoration project which started in the year 2012. One of its
objectives is to establish demonstration for coral nursery units (CNUs). The main purpose of
establishing and deploying CNUs is to supply high quality coral nubbins for transplantation and to
reduce the dependence of coral fragments from wild coral populations (Pub. Project 6: Pilot Testing,2014). As the project proceeded, projects staff, volunteers, and project implementers observed fishesⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

that were not around in the area in the past. CNUs have literally become an artificial reef for these
species. In general terms, the artificial reefs are man-made habitats placed at the sea bottom thatprovide a framework for marine life to develop. Such habitats have several benefits including:providing food, shelter, protection, and spawning areas for fish and marine life, as well as, relieving
natural reefs from user pressure by providing alternative recreational areas (Bohnsack and Sutherland,1985). Intrigued by the observed fishes around the CNUs, we proposed this study in order to assess theinfluence of the CNU’s on fish assemblage.
OBJECTIVESThis study investigated the influence of coral nursery unit (CNUs) deployed in the Roll-out Coral
Restoration Project in Anda, Bohol on fish assemblage. Specifically, this study compared the fishabundance and species richness before and four months after installation of the CNUs by determining
the occurrence, frequency, and abundance of fish species by trophic levels.
METHODOLOGYThis study was conducted in the Marine Protected Area (MPA) of Suba, Anda, Bohol (Fig. 1) to ensure
safety of the CNUs. Six CNUs (dimension = 3 m L x 1 m W x 0.5 H), made up of ropes andreinforcing bars, were deployed in the sandy portion of the MPA at 30 m apart from each other toavoid overlapping. Fishes in the CNUs were counted and identified visually using the fixed-point
technique (Hackradt et al., 2011) every month. Observations were made within an imaginary cylinderthat has a radius of 3 m. There was a 5-min interval before and after census to minimize interference.
The census was done for 10 minutes at each CNU. Monthly dive was done to remove foulingorganisms (Aaron-Amper et al., 2015).
The fish assemblages were characterized in terms of: 1) fish abundance and species richness, 2)four classes of frequency occurrence of species (permanent 75-100%, frequent 50-75%, scarce 25-50%,
and rare < 25%), 3) and trophic level of each fish species following the procedures described by
Romanuk et al. (2011) wherein an omnivore was assigned to trophic positions between 2.2 and 2.79,
secondary consumer to > 2.8, and tertiary consumer to > 4.
Statistical analysis was performed using Systat 12. The data were log transformed based on thepaired t-test.

Fig. 1 Map of Bohol, Philippines showing the CNU siteⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

RESULTS AND DISCUSSION
Overall, 41 species belonging to 12 families were recorded from the two sampling periods combined(Table 1). Of these, 38 (93% of the whole species pool) were recorded four months after deployment of
the CNUs.
Table 1 Fish species composition, abundance, and richness before and four months
after deployment of coral nursery units
FamilyAcanthuridae
Apogonidae

Blenniidae
Chaetodontidae

Labridae

Mullidae
Ostraciidae
Pomacanthidae
Pomacentridae

Serranidae
Scorpaenidae
Tetradontidae

Abundance

SpeciesAcanthurus grammoptilus
Apogon bandanensis
Apogon griffini
Apogon moluccensis
Apogon monospilus
Apogon perlitus
Apogon quadrifasciatus
Apogon sealei
Archamia melasma
Cheilodipterus singapurensis
Centropyge multifasciatus
Chaetodon ocellicaudus
Chaetodon selene
Chaetodon vagabundus
Heniochus acuminatus
Petroscirtes breviceps
Coris dorsomacula
Coris pictoides
Halichoeres leucoxanthus
Halichoeres scapularis
Oxycheilinus bimaculatus
Thalassoma lunare
Upeneus moluccensis
Ostracion cubicus
Genicanthus watanabei
Altrichthys curatus
Amblypomacentrus clarus
Amphiprion polymnus
Chromis analis
Chrysiptera parasema
Chrysiptera springeri
Dascyllus aruanos
Dascyllus reticulatus
Dascyllus trimaculatus
Dischistodus perspicillatus
Pomacentrus philippinus
Pomacentrus proteus
Pseudanthias huchti
Pterois volitans
Canthigaster solandri
Canthigaster valentini

Total abundance
Total no. of
speciesⒸ ISERD

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before
0
0
5
40
70
30
10
110
0
0
0
0
0
0
0
70
2
0
12
0
0
0
1
0
0
5
6
0
0
11
5
0
1
5
1
16
0
5
2
0
0
407

after 4 months
2
400
0
260
365
100
265
380
115
40
1
2
1
2
1
16
17
1
7
6
11
12
0
1
1
0
15
5
1
45
2
6
6
11
1
30
5
70
7
5
2
2217

20

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Percentage composition (%)

Only 20 species were common and the Apogonidae dominated the community. During the second
survey, four species were not found while 21 species were recorded. The total abundance of fish
assemblage showed a highly significant increase (p = 0.001). The experimental results indicate thecomplex role of the CNUs as an effective way in increasing species richness and abundance of fish
assemblage, and corroborate with the statement of Charbonnel et al. (2002) that habitat complexity has
a prominent role on the ecological effectiveness of artificial reefs.
Changes in the frequency of occurrence demonstrate the relationship between habitat complexity
and temporal variability in the fish assemblage (Fig. 2). Four months after the deployment of CNUs,
the contribution of the permanent species (11% vs. 5%), frequent (13% vs. 10%), and scarce (50% vs.
26%) increased while the rare species decreased (26% vs. 60%). The “new” frequent species included
Oxycheilinus bimaculatus and Thalassoma lunare of Labridae. This result may suggest higher
temporal stability of the species assemblage.
120
100
80
rare
60

scarce40

frequent

20

permanent0
beforeafter 4 months

Deployment of CNUs

Fig. 2 Percentage composition of frequency of occurrence classes of the fish species
before and four months after deployment of coral nursery units
Regarding the trophic levels, secondary consumers represented the greatest part of species
composition and have increased after deployment of the CNUs (Fig. 3). Food availability, one of themain constraints to the optimal foraging of the predators (Simon et al., 2011) will not become alimiting factor within the CNUs, at least for some species. This may explain the increase of tertiary
consumers during the second survey because these predators can encounter food at lower cost of search.

Totlal abundance

2500
2000
1500
tertiary consumers
1000

secondary consumers
omnivores

500
0
beforeafter 4 months

Deployment of CNUs

Fig. 3 Total abundance of fish species by trophic levelsⒸ ISERD73

IJERD – International Journal of Environmental and Rural Development (2016) 7-2

CONCLUSION
The deployed CNUs undoubtedly offer suitable habitats to a number of fishes. In such habitats, thesefishes can find food in abundance and this hypothetically would benefit their reproductive output andspillover. The sea is continuously subjected to stressors. Thus, even if the CNUs have not been planned
for sustaining fisheries, they still need shelter and protection against undesirable impacts.
ACKNOWLEDGEMENT
We are grateful to Christopher Olavides, Edlin Rene Handugan, Robert Curay, and Regie Tutor for
their active participation in this research.
REFERENCES
Aaron-Amper, J., Gulayan, J.M., Olavides, C. and Gulayan, S.J. 2015. Growth rate of Acropora nobilis attached
to table type framework. International Journal of Environmental and Rural Development, 6 (1), 108-113.
Bohnsack, J.A., and Sutherland, D.L. 1985. Artificial reef research, A review with recommendations for futurepriorities. Bulletin of Marine Science, 37 (1), 11-39.
Cabral, R.B., Aliño, P.M., Balingit, A.C.M., Alis, C.M., Arceo, H.O., Nañola, C.L., Geronimo, R.C. and MSN
Partners. 2014. The Philippine marine protected area (MPA) database. Philippine Science Letters, 7 (2), 300308.
Charbonnel, E., Serre, C., Ruitton, S., Harmelin, J.G. and Jensen, A. 2002. Effects of increased habitat
complexity on fish assemblages associated with large artificial reef units (French Meditteranean coast). ICES
Journal of Marine Science, 59, S208-213.
Hackradt, C.W., Félix-Hackradt, F.C. and García-Charton, J.A. 2011. Influence of habitat structure on fish
assemblage of an artificial reef in southern Brazil. Marine Environmental Research, 72 (5), 235-247.
Pub. Project 6, Pilot Technology Demonstration on Coral Reef Restoration in Panglao, Bohol. Retrieved
September 11, 2015, from https://uscmarineres.wordpress.com/2014/05/15/project-6-pilot-technologydemonstration-on-coral-reef-restoration-in-panglao-bohol/
Roberts, C.M., McClean, C.J., Veron, J.E., Hawkins, J.P., Allen, G.R., McAllister, D.E., Mittermeier, C.G.,
Wells, F., Vynne, C. and Werner, T.B. 2002. Marine biodiversity hotspots and conservation priorities fortropical reefs. Science, 295 (5558), 1280-1284.
Romanuk, T.N., Hayward, A., and Hutchings, J.A. 2011. Trophic level scales positively with body size in fishes.
Global Ecology and Biogeography, 20, 231-240.
Simon, T., Pinheiro, H.T. and Joyeux, J.C. 2011. Target fishes on artificial reefs, Evidence of impacts overnearby natural environments. Science of the Total Environment, 409, 4579-4584.

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Research article
erd

Utilization of Corncob as Feedstuff on Growth Performance,
Feed Utilization and Carcass Composition of Nile Tilapia(Oreochromis niloticus L.)
RUNGKAN KLAHAN*
Faculty of Agricultural technology, Phetchaburi Rajabhat University, Phetchaburi, Thailand
Email: rukiirun@windowslive.com

PANUPHONG YOTHA
Faculty of Agriculture and natural resource, University of Phayao, Phayao, Thailand

MONTREE PUNYATHONG
Faculty of Agriculture, Chiang Mai University, Chiang Mai, Thailand
Received 18 December 2015

Accepted 11 October 2016(*Corresponding Author)

Abstract The utilization of corncob as feedstuff was investigated to examine the diet contained
corncob in the fingerling Nile tilapia (Oreochromis niloticus L.). The initial weight of Niletilapia fingerlings ranged from 14.66 – 16.66 g/fish. The experiment was divided into fourgroups by the levels of corncob of 0%, 2%, 8% and 15% and conducted for 120 days. At theend of experiment, the results showed that the growth performance and feed utilization eachgroups were not significant different (P > 0.05). In addition the carcass composition andcomposition of edible flesh have no difference (P > 0.05). On the other hand, the feed cost was
decrease by variation with the level of corn cob in diet were 0.14, 0.56 and 1.05%, respectively.
Moreover, the water qualities of fish fed with feed contained corncob at different levels were in
range of water quality standard. The study indicated that the diets containing corncob at 15% offiber no negative effect on growth, feed utilization, carcass composition and edible flesh quality.
Moreover, it’s affected on cost - effectiveness.
Keywords Nile tilapia, corncob, feed, growth performance

INTRODUCTION
Corn production of Thailand is revived up significantly to 4.9 million metric tons in 2014. The averagecorn yield is estimated to increase to approximately 700 kilogram per rai (4.38 metric tons per hectare),up 2 to 3 percent from the previous year due to favorable weather conditions (Prasertsri and Santella,2014). High yield of corn followed with the great corncob that is agriculture waste which eradicated byburned in Thailand. In addition, yield of corncob in each country are prodigious. The tremendous
corncob is used for many things such as; carbon adsorbent (Tsai et al., 2001), bacterial cellulose(Huang et al., 2015) carbon fuel cell (Jinshuai et al., 2014) and Acetone-Butanol (Kumar et al., 2014).
The corncob composition are a lignocellulosic material composed of cellulose, hemicellulose andlignin were detected: cellulose: 38.8%, hemicellulose: 44.4% and lignin: 11.9% (Pointner et al., 2014)
protein, fat, moisture and ash were 4.10, 9.96, 5.42 and 4.46%, respectively (Olagunju et al. 2013).
Cellulose, hemicellulose and lignin are embedded in a complex matrix which is very resistant toenzymatic degradation (Mosier et al., (2005); Menon and Rao, (2012); Pointner et al., (2014) andaffected on fish digestion because it lack of the enzymes to degrade cellulose, and lignin (Halver andHardy, 2002). Nevertheless, fiber resist digestion property is benefit to control rate of food in digestion
tract to slow down that improve the digestion. Moreover, some species of fish have specialized forⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

herbivorous and many species for instance Cichlidae (Nile tilapia) are able to ingest and digest
quantities of plant material. Because the intestine of herbivorous fish are longer relative to organismal
size than are those of omnivours and carnivorous fish. The capacity for carbohydrate digestion shows acertain plasticity, particularly in omnivorous fish. Tilapia modify their secretion of digestive enzyme
when their diet is valid (Halver and Hardy, 2002; Jobling, 1995; Klahan et al., 2009).
OBJECTIVES
The aim of this study were to apply the corncob as the feedstuff to improve the cost effectiveness ofculturing Nile tilapia (Oreochromis niloticus L.) and reducing the environment pollution from corncob
burning.
METHODOLOGY
Experimental Fish
Nile tilapia (O. niloticus, L.) were obtained from commercial farm at Phayao province, Thailand. Fishwere acclimated in net cage on earth pond for 1 week by control diet containing 30% crude protein(CP) (no corncob contain) before start the experiment. Fingerling (14 – 16 g) were randomly stocked
into 1*1*1.5 m3 net cages at a density of 50 fish per net cage.
Experimental Diet
The corncobs were collected from the local farm in Phayao province, Thailand. Corncobs (Fig. 1a)
were blended to small pieces with grinding machine (Fig. 1b). Take small piece of corncob (Fig. 1c) tomixed with other feedstuff of feed formula. Four isonitrogenous (30% crude protein (CP)) andisocaloric (3000 KcalKg-1) diets were formulated and contained corn cob that effected on the fiberlevel at 0, 2, 8 and 15% (Table 1). The feedstuff of each diet were mixed together for 20 minutes withhorizontal mixing and took to extruder for floating pellet feed. The diets were dried at room
temperature for 12 hours and stored in plastic bags at room temperature.

a

b

c

Fig. 1 Corncob (A), grinding machine (B) and small piece of corncob (C)Experimental Procedure
The experiment design was completely randomized design (CRD) included 4 treatments. Each of the 4experimental diets was randomly assigned to triplicate groups of fish and all the groups were fed with
their respective diet at 3% body weight day twice daily for 120 days. Also, water is changed for every
two - three days for 30% throughout the study.
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Table 1 Feed formulation of the experimental diets (on dry matter basis)
Feedstuff (g/100)
Fishmeal
Soybean meal
Rice bran
Corncob
Cassava
Vegetable oil
Fish oilPremix1
D - starch
Total
Chemical analysis (%)
Moisture
Protein
Fat
Fiber
Ash
GE (Kcal100g-1)2

0
25
32
19
0
15
3.5
3.5
1
1
100

Dietary corncob contain (%)
2
8
25
25
32
32
17
11
2
8
15
15
3.5
3.5
3.5
3.5
1
1
1
1
100
100

15
25
32
4
15
15
3.5
3.5
1
1
100

2.26
30.48
9.59
3.69
9.42
292.25

2.37
30.29
9.56
5.20
9.35
295.07

3.06
29.10
9.38
14.98
8.94
303.40

2.69
29.74
9.48
9.71
9.16
303.53

1premix: each 0.5 kg contain vitamin A 500,00 IU, Vitamin D3 100,000 IU, Vitamin E 10,000 IU, Vitamin K 800 mg ,Vitamin
B1 250 mg, Vitamin B2 200 mg, Vitamin B2 750 mg ,Vitamin B12 5 mg ,pantothenic acid 3,000 mg, niacin 2,150 mg , folicacid 300 mg, inositol acid 25,000 mg, biotin 25 mg, selenium 30 mg, iron 20,000 mg, zinc 32,000 mg, copper 2,000 mg andfeed preservative 50 mg
2
GE (gross energy): calculated followed NRC =(% protein x 5.64 )+ (% lipid x 9.44 )+ (% NFE x 4.11)

Analytical Method
During experiment, the mortality was recorded daily and fish in each tank were counted and weighed
individually at a monthly. Growth rate were monitored to determine the final weight, weighed gain,
specific growth rate (SGR), average daily gain, survival rate, feed intake, feed conversion ratio (FCR)
and protein efficiency ratio (PER) were calculated according to Castell and Tiews (1980). At the startof experiment, 10 fish randomly were dried for the determination of body proximate composition. At
the end of the feeding trial, 5 fish from each group (n = 15 fish/group) were collected blood for blood
analysis of red blood cell, heamatocrit and hemoglobin with auto blood cell count and analyzed forfinal whole body proximate composition. Proximate composition of body was analyzed following
AOAC (2002) methods.
Statistical Analysis
In the experiment, all data were assessed by one-way analysis of variance (ANOVA) followed by
Duncan's multiple range tests. A significance level of P < 0.05 was used.
RESULTS AND DISCUSSION
Growth Performance
The result of the growth trial showed that all groups were not significantly different (P > 0.05) (Table2). The mean final weight, weigh gain, ADG and SGR of different experimental diets ranged between
68.86 - 75.00 g/f, 53.19 - 59.00 g/f, 0.59 - 0.65 g/f/d and 1.59 - 1.74% respectively. In addition,
survival rate in all groups were not significantly different also (P > 0.05). Feed utilization of NileⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

tilapia fed with contain corncob diet at different level for 120 days showed that not significantly
different (P > 0.05). The feed intake. feed conversion ratio and feed conversion efficiency of different
experimental diets ranged between1.05 - 1.10 g/f/day, 1.65 - 1.79 and 57.62 - 60.53%, respectively.
Table 2 Growth performance of Nile tilapia fed with corncob contain diet at 120 days
Growth performance
Initial weight )g/f(
Final weight )g/f)
Weight gain )g/f(
Average daily gain )g/f/day(Specific growth rate (%/day(Survival rate ( % )Feed utilization
Feed intake )g/f/day)Feed conversion ratio
Feed conversion efficiency (%)

Dietary corncob contain (%)
0
16.00 ± 2.00
75.00 ± 0.87
59.00 ± 2.18
0.65 ± 0.02
1.72 ± 0.14
98.66 ± 1.15

2
16.66 ± 1.15
74.15 ± 0.77
57.49 ± 1.50
0.64 ± 0.02
1.66 ± 0.07
98.00 ± 2.00

8
15.33 ± 2.30
72.99 ± 4.01
57.66 ± 1.78
0.64 ± 0.02
1.74 ± 0.10
98.66 ± 1.15

15
16.66 ± 1.15
69.86 ± 6.10
53.19 ± 7.09
0.59 ± 0.08
1.59 ± 0.16
94.00 ± 8.71

1.10±0.02
1.68±0.08
59.57±2.86

1.07±0.02
1.68±0.02
59.54±0.97

1.06±0.06
1.65±0.04
60.53±1.81

1.05±0.09
1.79±0.10
57.62±0.19

The growth performance of fish depend on two systems; digestion and absorption. The
digestibility of corncob diets of Nile tilapia from the previous study showed curtailing while thedigestibility and absorption of other feedstuff or nutrients were in normal stage by observation fromfeed utilization data ie. feed intake, feed conversion ratio and feed conversion efficiency. These data
were not significant different among groups that effected on growth performance not difference also.
Furthermore, the prebiotic attribute of corncob that is the one of reasons make the not difference on
growth performance. The property of prebiotic are a nondigestible food ingredient that beneficiallyaffects the host and resistance to gastric acidity and to gastrointestinal absorption (Gibson et al., 2004;
Yousefian and Amiri, 2009( The result from this study was the same line with Ren et al. (2015) who
found that the growth performance and survival rate of blunt snout bream (2 g/f) fed with dietcontained different carbohydrate sources namely wheat flour, maize flour, dextrin, maltose, glucose
and cellulose for 3 months were not different. Additionally, this is in agreement with the finding ofDalsgaard et al., (2012) that supplementation of β – glucanase and protease in juvenile rainbow trout
diet increased the feed utilization.
Carcass Composition
Table 3 Carcass composition of Nile tilapia fed with corncob contain diet at 120 days
Carcass composition (%)
Edible flesh
Bone and skin
Viscera and fat
a,b,c

0
35.17 ± 0.69
45.10 ± 0.26
7.44 ± 0.48c

Dietary corncob contain (%)
2
835.05 ± 2.71
35.00 ± 2.07
47.74 ± 3.47
45.99 ± 1.25
8.84± 0.58b
9.07 ±0.69a

15
32.07 ± 0.71
47.78 ± 1.88
9.79 ± 0.31a

Means within a row with common superscript are significantly different (P<0.05). n = 30

The effect of different corncob contained on carcass composition of fish showed in Table 3. The results
showed that there was no significant difference on percentage of bone and skin and edible (P > 0.05)
but it effected on percentage of viscera and fat (P < 0.05) that showed the highest on 8 and 15% ofcorncob in diet and control group. For HSI of control group were highest but lowest in 15% corncobⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

contained in diet group (P > 0.05). The similar data of carcass composition among groups is meaningthat the nutrient intake and nutrient deposit in muscle between groups of fish were close.
Blood Analysis
The result of blood analysis of Nile tilapia fed with contain corncob diet at different level for 120 days
showed that not significantly different (P > 0.05). The red blood cell, hematocrit and hemoglobin ofdifferent experimental diets ranged between 2.0 - 2.43 cell x106/µl, 32.25 - 37.60% and 10.75 - 12.40
g/dl, respectively (Table 4). These data were all in normal range of healthy Nile tilapia.
Table 4 Blood analysis of Nile tilapia fed with corncob contain diet at 120 days
Carcass composition (%)
Red blood cell (cell*106/µl)
Hematocrit (%)
Hemoglobin (g/dl)

02.19 ± 0.16
32.95 ± 1.20
11.05 ± 0.06

Dietary corncob contain (%)
282.24 ± 0.34
2.14 ± 0.55
34.10 ± 3.95
34.30 ± 5.93
12.30 ± 0.14
11.85 ± 0.21

15
2.00 ± 0.18
34.150 ± 2.61
11.45 ± 0.77

Corncob is the toxic without feed stuff that no effected on fish health. This reason made the blood
data showed no difference. These blood data according to Rungkan (2009), the red blood cell,
hematocrit and hemoglobin were 2.78 x106/µl, 21.11% and 11.82 g/dl, respectively. The comparison of
red blood cell, hematocrit and hemoglobin with other fish were in normal range were 0.973 - 2.75
x106/µl, 20 - 51% and 5.46 - 101.33 g/dl, respectively (Duy et al., 2008; Min and Kang, 2008; Pérez etal., 2008). Hence, the wide range depends on the varity of size, type and strain of fish.
CONCLUSION
The corn cob can be as feed stuff for Nile tilapia diet by contained in feed formula 15%. These no
negative effected on growth performance, feed utilization and fish health including the flesh quality
also. Moreover, the feed cost of 15% corncob group was cheaper than control group about 1.50
Baht/Kg feed (0.04 USD/kg feed).
ACKNOWLEDGEMENTS
This research was supported by the grant of NSTDA Northern Region.
REFERENCES
AOAC. 2002. Official methods of analysis. Virginia, Association of Official Analytical Chemist, Inc.
Castell, J.D. and Tiews, K. 1980. Report on the EIFAC, IUNS and ICES. Working group on the standardizationof methodology in fish nutrition research, Hamburg, Federal Republic of Germany. 2123 March, EIFAC
Technical Paper, 26.
Dalsgaard, J., Verlhac, V., Hjermitslev, N.H., Ekmann, K.S., Fischer, M., Klausenand, M. and Pedersen, P.D.
2012. Effects of exogenous enzymes on apparent nutrient digestibility in rainbow trout (Oncorhynchus
mykiss) fed diets with high inclusion of plant-based protein. Animal Feed Science and Technology, 171 (2-4),
181-191.
Duy, A.T., Schrama, J.W, Dam, A.V. and Verreth, J.A.J. 2008. Effects of oxygen concentration and body weighton maximum feed intake, growth and hematological parameters of Nile tilapia, Oreochromis niloticus.
Aquaculture, 275, 152-162.

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Gibson, G.R., Probert, H.M., Van Loo, J. Rastall, A.R. and Roberfroid, M. 2004. Dietary modulation of thehuman colonic microbiota: updating the concept of prebiotics. Nutrition Research Reviewer, 17, 259-275.
Halver, J.E. and Hardy, R.W. 2002. Fish nutrition. Third edition, Academic Press, USA.
Jinshuai, Y., Yicheng, Z. and Yongdan. L. 2014. Utilization of corn cob biochar in a direct carbon fuel cell.
Journal of Power Sources, 270, 312-317.
Klahan, R., Areechon, N., Yoonpundh. R. and Engkagul, A. 2009. Characterization and activity of digestive
enzymes in different sizes of Nile tilapia (Oreochromis niloticus L.). Kasetsart J. (Nat. Sci.), 43, 143-153.
Kumar, M., Kumar, D. and Singh, B. 2014. Utilization of agro residue corncob for production of acetone-butanolusing clostridium acetobutylicum and process optimization through RSM. J Microb Biochem Technol,
S8:005. doi:10.4172/1948-5948. S8-005.
Menon, V. and Rao, M. 2012. Trends in bioconversion of lignocellulose, Biofuels, platform chemicals andbiorefinery concept. Progress in Energy and Combustion Science, 38 (4), 522-550.
Min, E. Y. and Kang, J.C. 2008. Effect of waterborne benomyl on the hematological and antioxidant parametersof the Nile tilapia, Oreochromis niloticus. Pest. Biochem. Physiol, 92, 138-143.
Mosier, N., Wyman, C., Dale, B., Elander, R., Lee, Y.Y., Holtzapple, M. and Ladisch, M. 2005. Features ofpromising technologies for pretreatment of lignocellulosic biomass. Bioresource Technology, 96 (6), 673-686.
Huang, C., Yang, X.Y., Xiong, L., Guo, H.J., Luo, J., Wang, B., Zhang, H.R., Lin, X.Q. and Chen, X.D. 2015.
Utilization of corncob acid hydrolysate for bacterial cellulose production by Gluconacetobacter xylinus. Appl
Biochem Biotechnol. 175 (3), 678-88. doi: 10.1007/s12010-014-1407-z. Epub 2014 Nov 26.
Olagunju, A., Onyike, E., Muhammad, A., Aliyu, S. and Abdullahi, A.S. 2013. Effects of fungal (Lachnocladiumspp.) pretreatment on nutrient and antinutrient composition of corn cobs. African Journal of Biochemistry
Research, 7 (11), 210-214.
Pointner, M., Kuttner, P., Obrlik, T., Jäger, A. and Kahr, H. 2014. Composition of corncobs as a substrate forfermentation of biofuels. Agronomy Research, 12 (2), 391-396.
Prasertsri, P. and Santella, R. 2014. Thailand Grain and Feed Annual. [homepage on the Internet]. Gain report:
Bangkok, Global Agricultural Information Network. [cited 2014 Nov 12]. Available from: http://
gain.fas.usda.gov/Recent%20GAIN%20Publications/Grain%20and%20Feed%20Annual_Bangkok_Thailand_3-7-2014.pdf
Pe´rez, M.I.G., Lo´pez, M.M., Ramıírez, L.A.G., Banùelos. C.A.R. and Marenco. M.L.R. 2008. Effect of sublethal concentrations of endosulfan on phagocytic and hematological parameters in Nile tilapia (Oreochromis
niloticus). Bull. Environ. Contam. Toxicol. 80, 266-269.
Ren, M., Habte-Tsionb, H.M., Xie, J., Liu, B., Zhou, Q., Ge, X., Pan. L. and Chen, R. 2015. Effects of dietarycarbohydrate source on growth performance, diet digestibility and liver glucose enzyme activity in bluntsnout bream, Megalobrama amblycephala. Aquaculture, 438, 75-81.
Rungkan Klahan. 2009. The digestive enzymatic activity, apparent digestibility coefficients and effect of enzyme
supplement on feed utilization in Nile tilapia (Oreochromis niloticus L.). Ph.D. Dissertation, Department of
Aquaculture, Kasetsart University, Thailand.
Tsai, W.T., Chang, C.Y., Wang, S.Y., Chang, C.F., Chien, S.F. and Sun, H.F. 2001. Utilization of agricultural
waste corn cob for the preparation of carbon adsorbent. J Environ Sci Health B, 36 (5), 677-686.
Yousefian, M. and Amiri, M.S. 2009. A review of the use of prebiotic in aquaculture for fish and shrimp. African
Journal of Biotechnology, 8, 7313-7318.

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Research article
erdCharacteristics of Transformation of Traditional Upland
Farming System in Cambodia: A Case Study of Snuol
Commune, Kratie Province
SHINOBU YAMADA*
Research Center, Institute of Environmental Rehabilitation and Conservation, Tokyo, Japan
Email: sinobun4022@gmail.com

MACHITO MIHARA
Faculty of Regional Environment Science, Tokyo University of Agriculture, JapanKUMIKO KAWABE
Extension Center, Institute of Environmental Rehabilitation and Conservation, Tokyo, Japan
Received 31 November 2015

Accepted 11 October 2016(*Corresponding Author)

Abstract The main objective of this study is to compare the characteristics between the local
farmers who conduct traditional upland farming without chemical fertilizer and the local
farmers who depend on chemical fertilizer. The results of the analysis are summarized asfollows. 1) According to the results of Multiple Correspondence Analysis, it was clear that thepreference divisions of the local farmers who depend on chemical fertilizer were “Gender”,“Age”, “Family number”, “Duration of residence”, “Irrigation facility” and “Multiple cropping”
as important characteristics for the classification. 2) The results from the Biological andChemical Technology Method indicated that chemical fertilizers were applied intensively infarmlands with low soil fertility. Therefore, it was considered that the contribution of thecurrent capital, such as chemical fertilizer, was not effectively conducted. 3) In the research site,
the estimated value of technical efficiency showed the existence of technical inefficiency inupland farming systems.
Keywords traditional farming system, chemical fertilizer, biological and chemical technology,
production function

INTRODUCTION
In Cambodia the amounts of applying agricultural chemicals, such as chemical fertilizer and pesticide,have rapidly been increasing in recently years (Fujimoto and Miyaura, 1966). Although it contributed
to increase the agricultural productivity, the amounts of applying agricultural chemicals caused
environmental disruptions, such as soil and water quality degradation, and decreased land productivity
in the long term. Based on the above mentioned backgrounds, the main objective of this study is tocompare the characteristics between the local farmers who conduct traditional upland farming withoutchemical fertilizer and the local farmers who depend on chemical fertilizer. At first, the approach was
to clarify the characteristics of the local farmers who depend on chemical fertilizer through evaluating
factor inputs by the estimated production function based on the Biological and Chemical Technology
Method. In addition, the technical efficiency is evaluated by the estimated stochastic frontier
production function.
METHODOLOGYⒸ ISERD

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The research site is the Snuol Commune, Kratie Province. The research site is a well-known area
where a variety of upland crops are produced in Cambodia. The urgent expansion of a variety of
upland crop production creates an issue of environmental disruptions, such as soil and water quality
degradation, and decreases land productivity by the amounts of agricultural chemicals which areapplied. In addition, in this site, the Institute of Environmental Rehabilitation and Conservation carriedout the project “study on sustained utilization of the natural resource” (3/2015 – 4/2016). The firstproblem is to clarify the characteristic of the farm household using agricultural chemicals. The second
problem is to clarify factor input structures by estimated the production function that was based on the
Biological and Chemical technology (Egaitu and Shigeno, 1983). In addition, the third problem is toclarify technical efficiency by estimating the stochastic frontier production function.
Kratie Province is located in the northeastern part, where development is the slowest, in
Cambodia, and the compared difference with other areas is large. In Snuol village, Snuol district,Kratié Province, 170,000 ha, equal to 65%, is used in the total area, 260,000 ha is forest, and 14,000 ha,
equal to 5%, is used as agricultural land. The questionnaire survey was entitled “Baseline investigation
for sustainable rural development in Snuol village, Snuol district, Kratié Province (2011, April)”. The
target area of the questionnaire survey consisted of six villages: Kbal Snuol, Thpong, Snuol Kert,
Snuol Lech, Kathdai and Prek Kdey. The numbers of useful responses received per area are as follows:
Kbal Snuol Village: 46 respondents (25.0% of the total respondents), Thpong Village: 42 respondents(22.8%), Snuol Kert Village: 23 respondents (12.5%), Snuol Lech Village: 33 respondents (17.9%),
Kathdai Village: 21 respondents (11.4%) and Prek Kdey Village: 19 respondents (10.3%). There were
184 respondents in total.
RESULTS AND DISCUSSION
Table 1 shows the respondent profiles. Almost 51% were “male” and about 48% were “female.” About
the age of the respondents, the majority of respondents were between the ages of “More than 50 years”(41.0%), followed by “40-49” years (27.5%) and “30-39” years (18.0%). The lowest percentage wasaged “Less than 20 years” old. About the number of family members, the majority of respondents had
a family number of “3-5” people (55.0%), followed by “6-8” people (34.3%) and “Less than 2 people”(5.3%). The lowest percentage was “More than 10 people.” About the residing number of years, themajority of respondents had resided in the area “More than 41 years” (54.7%), followed by “36-40”
years (9.4%) and “31-35” years (8.8%). The lowest percentage was “Less than 20 years” old.
Table 1 Demographic Information of Respondents
GenderAge
Numbers of family persons
numbers of
numbers of
numbers of
responses
responses
responses(n) (%)(n) (%)(n) (%)
Male
95 51.6 Less than 20 years
2
1.1 Less than 2 persons
9
5.3
Female89 48.4 20 - 29 years
22 12.4 3-5
93 55.0
30 - 39 years
32 18.0 6-8
58 34.3
40 - 49 years
49 27.5 9-1053.0
More than 50 years
73 41.0 More than 10
4
2.4

Total
184 100.0 Total
Source:Survey Data

178 100.0 TotalⒸ ISERD

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Family living years in this village
numbers of
responses(n) (%)
Less than 2 years
1
0.6
3-5
6
3.5
6-10
3
1.8
11-15
5
2.9
16-20
13
7.6
21-25
9
5.3
26-30
9
5.3
31-35
15
8.8
36-40
16
9.4
More than 41 years 93 54.7
169 100.0 Total
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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Table 2 shows the using of the chemical fertilizer and the organic fertilizer becoming the core of
the BC technology with land. About using chemical fertilizer, almost 76% were “No” and about 27%
were “Yes.” About using chemical pesticide, almost 64% were “Yes” and about 36% were “No”.
About using organic fertilizer, almost 50% were “No” and about 50% were “Yes.” About usingorganic pesticide, almost 97% were “No” and about 3% were “Yes”. The inhabitants continue
Cambodian-style traditional lifestyle depending on natural resources.
Table 2 Using of the chemical fertilizer and the organic fertilizer
Using chemical fertilizer
numbers of
responses
(n)
(%)
Yes
37 23.6
No
120 76.4
Total
157 100.0
Source:Survey Data

Using chemical pesticide
numbers of
responses
(n)
(%)
Yes
98
64.5
No
54
35.5
Total
152 100.0

Using organic fertilizer
numbers of
responses
(n)
(%)
Yes
78 49.7
No
79 50.3
Total
157 100.0

Using organic pesticide
numbers of
responses
(n)
(%)
Yes
4
2.6
No
152 97.4
Total
156 100.0

In the Snuol District, Kratie Province, this area uses a high level of chemical fertilizer andpesticide. However, there are many local farmers which apply fertilizers without knowing the usage ofappropriate chemical fertilizers and pesticides. Using an attribute from Table 1, this part clarifies thecharacteristic of the local farmers using the chemical fertilizer and the local farmers not using chemicalfertilizer. In this analysis, Multiple Correspondence Analysis was employed. According to the resultsof Multiple Correspondence Analysis, it was clear that the preference divisions of the local farmers
who depend on chemical fertilizer were “Gender”, “Age”, “Family number”, “Duration of residence”,“Irrigation facility” and “Multiple cropping” as important characteristics for the classification.

Fig.1 The result of Answer Pattern for using of chemical fertilizer andorganic fertilizer by Correspondence AnalysisⒸ ISERD

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Figure 1 shows the result of the answer pattern for “Not using chemical fertilizer”, as well as“Using chemical fertilizer”. The answer pattern of “Using chemical fertilizer” is similar to the answer
pattern of family number of 9-10 persons, more than 10 persons, duration of residence of 6-10 years,
11-15 years, 16-20 years, and using pesticide. Also, the answer pattern of “Not using chemicalfertilizer” is similar to the answer pattern of female, aged more than 50 years old, family number ofless than two persons, duration of residence of 26-30 years, 31-35 years, irrigation not improved, andsingle-crop farming.
BC process production technology functional model for the estimation is shown by Model 1 andModel 2.
Model 1: Yn = AX1^αX2^βModel 2: Yn = AX2^βWhere Yn is the average annual income from agricultural activity (riel), X1 is the total chemicalfertilizer inputs, and X2 is the upland area (ha). At the same time, A, α, β is the estimation parameter.
The estimation sample is the unit of the farm. Model 1 is the farmers using chemical fertilizers, andModel 2 is the farmers not using chemical fertilizers. The estimated parameter introduces a dummy
variable of OID and VDn. OID is organic input dummy (input: 1, no input: 0) and VDn is village
dummy, n is each village (Thpong: 1, Snuol Kert: 2, Snuol Lech: 3, Kathdai: 4, Prek Kdey: 5). The
ordinary least squares (OLS) method was employed in the estimation of regression model.
Table 3 Estimation results of BC process production technology function
Chemical Input：Model 1 (N=33)
Variable

Coefficient t-value

Non Chemical Input：Model 2 (N=86)
Coefficient t-value

Constant： C
12.44 23.77 ***14.39 76.92 ***Chemical Inputkg
X1 ： α0.425.59 ***
Upland and Paddy field
Area (ha) X2 ： β
0.54
3.44 ***
0.61 5.99 ***Organic Input
Dummy OD1 ： γ
-0.43
-0.15
-0.10 -0.61
ThpongDummy VD1 ： δ
1.09
2.72 ***
0.34 1.23
Snuol Kert
Dummy VD2 ： ε
0.38
0.60
0.53 1.92 *Snuol Lech
Dummy VD3 ： ζ
0.68
1.62 *
0.22 0.81
Kathdai
Dummy VD4 ： η
0.79
1.66 *
0.51 1.75 *Prek Kdey
Dummy VD5 ： θ
1.15
1.90 **-0.11 -0.30
R2
0.68
0.46
Adj.R20.57
0.42
F-value
6.28
9.65
p-value0.00
0.00
Note:***1% level of significance,**5% level of significance,*10% level of significance
Source:Survey Data

In Table 3, the estimation results are shown of the BC process production technology function of
upland farming systems in the research-site area.
Estimation results of Model 1 and Model 2 are as follows. According to the measuring results ofModel 1, indicating the farmer using the chemical fertilizer inputs, the value of production elasticity ofchemical fertilizer inputs (α) is 0.3596. Moreover, the value of production elasticity of the land area (β)
is 0.6060. The statistical significances of the value of α, β are satisfactory. Adjusted R-squared asstatistical goodness-of-fit shows 0.6190. In the estimation results of Model 1, no statistical significanceis recognized of the estimation parameter of the organic input dummy (OID) (γ) and village dummy of
Snuol Lech (VD2) (ε). The value of α+β is 0.9656. BC process production technology in Model 1 hasdiminishing returns to scale. Furthermore, the value of α/β shows 0.5933. This means that the land useⒸ ISERD

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and the chemical fertilizer inputs saving technology have been applied in BC process production
technology.
According to the measuring results of Model 2 indicating the farmers not using the chemicalfertilizer inputs, the value of production elasticity of the land area (β) are 0.6123. The statisticalsignificance of the value of β is satisfactory. Adjusted R-squared as statistical goodness-of-fit shows
0.4413. In the estimation results of Model 1, the statistical significance is not recognized of theestimation parameter of the organic input dummy (OID) (γ) and village dummy of Thpong (VD1)(δ),
Snuol Lech (VD3)(ζ) and Prek Kdey (VD5)(θ).
From these estimation results, observation facts of the BC process production technology function
are as follows.
First observation fact, the BC process production technology have diminishing returns to scale(α+β<0).
Second observation fact, when examining routine charge wealth (α) and land area (β), element
contribution for the production of the element was not a high value.
Third observation fact is related to the value of land area (β). The values of β are mode 1:0.541
and mode 2:0.612. The contribution degrees of the land as the agricultural production inputs are morethan 0.5 with both models. With the value of β being high, regardless of having chemical fertilizer in
use or not, farmers performed the agricultural production which depended on the land. Regarding thevalue of land area (β), even if the land’s fertile soil under the present conditions was a high level, insuch condition of land area, the current inputs were intensively utilized. Therefore, element
contribution of current inputs to production became a low level. It gradually strengthens a tendency as
the productivity of the land is a low level. This tendency occurs if the soil fertility is a low level andsoil erosion is a high level.
Fourth observation fact did not recognize a statistically significant recurrence relation in theorganic input dummy (OID) (γ). This means that the introduction of the sustainable farming system
based on natural resource circulation for the purpose of a decrease in chemical fertilizer and thedecrease in chemical pesticide is difficult.
At first the estimation of the technical efficiency is as follows. Difference of the technology
efficiency defines the residual from the actual value and estimated value. Difference of the technology
efficiency is as follows with the index. Difference of technology efficiency index of the average annual
income from an agricultural activity base:
EFFICIENCY = (income actual value / income estimated value) × 100
This means that EFFICIENCY is the technology efficiency of a high level in the time over 100, and thetechnology efficiency is a low level in times fewer than 100.
Table 4 The results of estimated of EFFICENCY
Using chemical fertilizer
numbers of
responses
(n)
(%)
Yes
37 23.6
No
120 76.4
Total
157 100.0
Source:Survey Data

Using chemical pesticide
numbers of
responses
(n)
(%)
Yes
98
64.5
No
54
35.5
Total
152 100.0

Using organic fertilizer
numbers of
responses
(n)
(%)
Yes
78 49.7
No
79 50.3
Total
157 100.0

Using organic pesticide
numbers of
responses
(n)
(%)
Yes
4
2.6
No
152 97.4
Total
156 100.0

In Table 4, the results of the estimated EFFICIENCY by analysis of variance (Multiple Range
Tests: Modified LSD (Bonferroni) test with a significance level 0.05), in the villages Kbal Snuol,Ⓒ ISERD

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Thpong, Snuol Kert, Snuol Lech, Kathdai, and Prek Kdey, the difference of the mean of the index of
EFFICIENCY is not confirmed statistically.
Therefore, it confirms the influence that EFFICIENCY gives to agriculture income (Y: theaverage annual income from agricultural activity (riel)). The results of the regression model by
estimation are as follows.
［Using chemical fertilizer of farmer］
Y = -233,717 + 55,438.94 EFFICIENCY R2 = 0.6377［Non-using chemical fertilizer of farmer］
Y = -1,357,258 + 48,388.51 EFFICIENCY R2 = 0.7671
With both farmers using chemical fertilizers and those which do not, EFFICIENCY shows that it
has a positive influence on agriculture income. It also shows that the existence of the technicalinefficiency has a negative influence on agriculture income at the same time. The growth of technicalefficiency of farm productivity rises and realizes an increase in agriculture income.
CONCLUSION
The main objectives of this study are tp clarify the character of the upland farming system in Snuol
village, Snuol district, Kratié Province. The first objective is to clarify the characteristic of the farmhouseholds using agricultural chemicals. The second is to clarify factor input structures by estimating
the production function that was based on the Biological and Chemical technology. In addition, thethird objective is to clarify technical efficiency by estimated the stochastic frontier production function.
The results of this analysis are summarized as follows.
According to the results of Multiple Correspondence Analysis, it will be clear for the preferenceof the farm household using the agricultural chemicals, the divisions of “Gender,“ “Age,“ “Family
number,“ “Duration of residence,“ “Irrigation facility“ and “Multiple cropping“, as importantcharacteristics for the classification.
The Biological and Chemical technology process is a condition of the diminishing returns to scale.
The technology process intensively utilizes the agricultural chemicals in farms with low soil fertility.
Therefore, contribution to the current capital such as chemical fertilizer is not high. Under the
traditional cultivation method, depending on soil fertility, the upland farming system of the
productivity has been realized by lands using chemicals and the agricultural chemicals saving
production technology.
The estimated value of the technical efficiency shows existence of the technical inefficiency inupland farming systems of the research site.
As a result of the analysis, in the future, introduction of the environmental preservation farming
systems are necessary for the sustainable development of the upland farming system.
Toward realization of the environmental preservation farming systems, it is suggested that agricultural
education be part of life-skill education and networking for promoting sustainable agriculture.
REFERENCES
Egaitu, F. and Shigeno, R. 1983. Rice production function and equilibrium level of wage and land rent in postwar
Japan. Journal of Rural Economics, 54 (4), 167-174.
Fujimoto, A. and Miyaura, R. 1996. An ecological and economic assessment of vegetable, Cultivation inhighland areas in Southeast Asia. Journal of Agricultural Science, 40 (4), 248-263.

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Research article
erdComparison of Rice Plant Development with Different
Transplanting Density under SRI Practices in the Lysimeter
ISHWAR PUN*
Graduate School of Frontier Science, The University of Tokyo, Chiba, Japan
Email: punisr@gmail.com

EIJI YAMAJI
Graduate School of Frontier Science, The University of Tokyo, Chiba, Japan

SOPHY CHES
Graduate School of Frontier Science, The University of Tokyo, Chiba, Japan
Received 15 November 2015

Accepted 12 October 2016(*Corresponding Author)

Abstract Transplanting a single young rice seedling is one of the common methods in SRI
practices. However, farmers in some lowland areas hesitate to apply this method due to thethreats such as seasonal floods, birds and pests. Most of the farmers are more comfortable withtransplantation of two or more seedlings per hill. Thus, an experiment was conducted in thelysimeter at the rooftop of the University of Tokyo in 2015 to compare the rice plantdevelopment with different transplanting density. As an experimental design, two sets of single
seedling transplantation were applied with alternative wetting and drying irrigation as
replications; the same irrigation condition was applied to other transplantations with two, threeand four seedlings per hill. The plant height, number of leaves and tillers, dry biomass, andgrain yields were selected as the main factors for the comparison of rice plant development. As
a result, no difference was observed for the development of height across all transplantation
density treatments during the vegetative phase. However, during the reproductive and ripening
phases, single-seedling transplantation reached greater height. For the development in numberof tillers and leaves, three and four seedlings produced more tillers and leaves than one and twoseedlings. We found that the grain yield is significantly higher in three and four seedlings rather
than one seedling.
Keywords system of rice intensification, young seedling, transplanting density, plantdevelopment

INTRODUCTION
Rice is a major staple crop in the world. About 90% of all rice production and consumption takes placein Asian countries (FAO, 1998). Moreover, rice is also an important food in these areas, interconnected with culture and eaten in festivals and other important events. While both the world
population and the food demand is increasing, rice production is fluctuating due to the climate change
and shifts in rice cultivation methods. Varieties of rice with high yield and climate tolerance have been
discovered in recent years according to the International Rice Research Institute (IRRI, 1998). The
varieties of rice and its cultivation differ by the climatic differences from region to region. The use of
inorganic fertilizer in the paddy field is a common agricultural practice today in order to achieve highyields, but the excessive use of inorganic fertilizer have had negative impacts on the environment(Gimeno-Garcia et al., 1995). As a result, concerns with human health and interests in organic farming
have risen. A new method of plant management, organic fertilizer application, water management, andⒸ ISERD

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resultant high yields in rice production was found in Madagascar in 1983 by Father Henri de Laulanı´e,a French Jesuit priest, and later disseminated worldwide by the Cornell International Institute for Food,
Agriculture and Development. This method, called the system of rice intensification (SRI) today, isconsidered to save water yet achieves high-yield compared to the conventional method (Thakur et al.,2010; Chapagain and Yamaji, 2009). Stoop et al. (2002) reviewed the SRI method practiced around theworld explaining how high yields are achieved through SRI’s key principles through a range ofenvironmental factors and agronomic management practices including variety selection.
There are several definitions of SRI based on the climatic features of the countries. We applied theirrigation management called alternative wetting and drying irrigation (AWDI), which is also known as
the intermittent irrigation. SRI method is considered as a water-saving method with high yields. At thesame time, water management by AWDI reduces the methane gas emission from rice cultivation (Punand Yamaji, 2014), which is one of the major contributors to the potential global warming. With
respect to the worldwide dissemination of SRI, there are nonetheless many issues with regards to its
method of application. One such issue is the farmers' hesitation to transplant single rice seedling per
hill, which is considered a key principle of SRI, due to the concerns over threats from floods, pests andbirds to name a few. Instead, these farmers prefer to transplant two or more seedling per hill. Suchtendency among the farmers and their challenges in protecting young seedlings in lowland areas is oneof the reasons why the dissemination of SRI as a single-seedling transplantation method has been
limited.
The experiment conducted in lysimeter 2014, transplanting single seedlings were cultivated underboth AWDI and continuous flooding conditions. The plant development was significantly higher in
non-SRI method than in SRI method. But there was no significant difference between the two methods
in terms of grains produced. It is because of same transplanting density of rice seedling. In this study,
we investigated the rice plant development with different transplanting density under SRI practices.
The aim of this study is to find adequate recommendations to farmers who hesitates to transplant single
seedling in lowland areas as well as some uplands.
MATERIALS AND METHODS
The lysimeter experiment was conducted in the University of Tokyo Kashiwa campus, Chiba
Prefecture, Japan during the rice growing season in 2015. The study aimed to verify the difference inrice plant development by different transplanting density. The size of lysimeter was 495 cm in lengthand 158 cm in width. The lysimeter consists of a drainage valve on the right border and an irrigation
facility from tap water on the left border (Fig. 1). The soil was puddled homogeneously for two weeks
before transplanting. The organic fertilizer (2,200 gram) was also mixed homogeneously into the entire
soil. The composition of organic fertilizer was 1.3% nitrogen 0.6% phosphorus, and 1.8% potassium,with C/N ratio of 22. We also installed a water tube with 13.5 cm diameter and 25 cm length tomeasure the ponding depth. Ponding depth was measured using data logger LR5042 (Hioki E.E.
Corporation, Japan) over the course of the experiment. The water depth sensors inside the water tube
were fixed at 15 cm deep from the soil surface. Data logger LR5042 measures water pressure involtage ranging from -5.000 V to 5.000 V which is converted to the height of water in lysimeter with acalibrated equation. Water pressure data was collected every sixty minutes. The transplanted rice in thenursery was a 24-days old Japanese rice variety koshihikari. A total of 160 rice nurseries weretransplanted on May 12, 2015. A single factor experiment method was utilized for this experiment, inwhich a single factor varied (density of rice seedlings while other factors remained constant (e.g.
fertilizer, water management). The experiment followed the completely randomized design (CBD) withfour treatments (number of rice seedlings per hill) with two replication. The randomization was done asshown in Fig. 1. The numbers indicated in Fig. 1 are a) SRI method with one seedling per hill, 2) SRIⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

method with two seedlings per hill, 3) SRI method with three seedlings per hill, and 4) SRI methodwith four seedlings per hill.
Rice plant height and the number of tillers and leaves were recorded once in a week during thevegetative phase. During the reproductive phase, the plants were covered with a net to protect frombirds, and were measured twice a month. The water management applied was AWD (alternative
wetting and drying) irrigation. Water was drained by using a hand pump when there was the excess
rainfall.
The collected data was tested by ANOVA (Analysis of Variance) using R statistical software (RCore Team, 2014). Later, Tukey’s HSD test was conducted to identify the differences in development
among different treatments.
2

3

4

5

6

7

8

9

10

11

12

13

1 4 15

16

5

1

2

1

3

2

3

4

4

2

3

158 cm

4

1

10 cm

1

10 cm

495 cmWater depth sensor
Water depth logger

Water Tube

Rice Nursery

Fig. 1 Schematic diagram of the experimental setup
RESULTS AND DISCUSSION
Water Management and Climatic Condition
There are four seasons in a year in Japan. Paddy is cultivated only in summer seasons. Japanese rice
farmers prepare the paddy field in late spring by flooding the field and applying fertilizers. Likewise,
lysimeter was also prepared with flooding and fertilizer application at the end of April. The first rice
was transplanted on the 12th of May. The method of water management was alternative wetting anddrying irrigation (AWDI). We maintained the shallow ponding condition above the soil surface startingfrom the day of transplantation to 26th may until the rice plant became stronger. The maximum waterlevel was 7.59 cm and minimum level was 0.24 cm from the soil surface (Fig. 2). The drainage valve
was opened to reduce the water level in the lysimeter down to -13.10 cm from 27th May to 5th June.
AWDI method was also applied based on the rainfall event in the study area (Fig. 2). The maximum
rainfall in the study area occurred during the first 10 days of September at 249 mm (Japan
Meteorological Agency, 2015). The comparison of rainfalls by 10-day intervals (start- first 10 days,
mid-second 10 days, end-last ten days) during rice cultivation period revealed that the minimum
rainfall (4 mm) was recorded at the start of August (10 days). Maximum temperature was also recorded
during the cultivation period (36.7°C). If there was no rainfall event, tap water was used for irrigation.
During the ripening phase, lysimeter was kept dry to prepare for the harvest.
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Rice Plant Development
The rice plant height and the number of tillers and leaves were measured once in a week during thevegetative phase. However, measurements were taken only once a month during the reproductive phase,because the lysimeter was covered with a net to protect the rice plants from birds.

Fig. 2 Water management during the rice cultivation in the lysimeter

Fig. 3 Rice plant height development in all treatments

Fig. 4 Rice tillers development in all treatments

Fig. 5 Rice plant leaves development in all treatmentsⒸ ISERD

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After the rice was transplanted on of May 12, the first height was measured on May 22, by ameasuring tape. Fig. 3 shows that the average height in centimeters for two, three, and four seedlings
per hill were 16.34 ± 1.21, 16.03 ± 1.34 and 16.03 ± 1.53, respectively, but the average height for one
seedling per hill was only 15.69 ± 2.26. Fig. 4 shows the development of tillers, which was observed inevery seedling density after the May 29. Fig. 5 shows the development of rice plant leaves counted
altogether, where the maximum number of leaves was counted in four seedlings, followed by three,
two, and one seedling. During the vegetative phase, numbers of leaves were similar in three and four
seedlings. Number of tillers and leaves were also higher in three and four seedlings than one and twoseedlings. The rice was harvested on September 23. Maximum height across all four treatments wereobserved in one and two seedlings, while the heights for three and four seedlings were similar to eachother but less than that of the one and two seedling densities. The number of leaves decreased because
lower leaves decayed. Some leaves decayed and dried but were not included in the count. The numberof tillers increased at the end of the vegetative phase because of the emergence of small branches.
However, formation of panicles was not observed for the small branches.
Table 1 Details of the rice plant development
Measured Variables

1 T (One Seedling)

2 T (Two Seedlings)

Mean

Mean

SD

SD

3T (Three Seedlings)
Mean

SD

4 T (Four Seedlings)
Mean

SD

Height (Centimter)

92.13

2.88

91.00

89.25

89.25

2.63

88.56

2.19

Stem (Number)

10.38

2.36

12.88

2.15

13.06

1.45

15.25

2.41

Green Leaves (Number)

29.69

7.21

34.63

6.44

36.50

4.64

43.25

6.69

Dead Leaves (Number)

13.44

2.26

19.56

2.99

20.13

3.52

20.81

3.40

Panicle (Number)

9.75

1.67

11.94

2.35

11.94

1.32

13.25

2.62

Dry Stem (Gram)

9.61

0.89

13.04

0.74

13.39

2.35

14.39

2.04

Dry Leaves (Gram)

4.14

0.41

5.55

0.51

5.76

0.86

5.84

0.73

Good Grain (Number)

647.75162.97798.0064.39

752.8885.18

681.1375.21

Bad Grain (Number)

8.50

1.08

16.75

8.45

15.75

1.50

13.00

9.88

Dry Spikelet (Gram)

0.95

0.15

1.03

0.15

0.98

0.13

1.07

0.20

Grain Weight (Gram)

15.89

2.31

18.20

3.15

19.83

2.55

20.49

4.39

SD: Standard Deviation

Table 2 Comparison between indicators using T-test

Grain Yield and Biomass
The rice was harvested on September 23. To study the grain yields and total biomass development
within four treatments, four rice plants were selected from the middle of each treatment. Height, thenumber of stems, green leaves, dead leaves, and panicles were measured for a total of 64 rice plants.
Moreover, to study the details of rice plants, the number of grains (good and bad), dry stems and leaves,and spikelets were counted from selected 32 plants. The grain weight at 14% moisture level wasⒸ ISERD

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measured from all rice plants (Table 1). The result of height among the treatments showed the meandifference is higher in one seedling but without significant difference. In case of stems, one seedling
was lower than the two, three, and four seedlings. The number of green leaves at the time of the harvest
were counted, but the number was lower for one seedling case.
The dead leaves were recorded just after the harvest. In comparison with other treatments, threeseedlings showed a significantly higher level of dead leaves compared to one seedling treatment, asshown in Table 2 (p < 0.05). The four seedlings also had a greater number of dry leaves than one andtwo seedlings (p < 0.001 for comparison with one seedling treatment; p < 0.01 for comparison with
two seedling treatment). The number of dry stems and leaves were higher for four seedling treatment
than for one seedling treatment (p < 0.05). For other comparisons, differences in dry stems and leaves
were not significant. The spikelets without grains were also higher for two, three, and four seedlingtreatments. The grain weight at 14% moisture level was measured. The grain weight (i.e. yield) was
significantly higher for three and four seedlings compared to one seedling treatment (p < 0.05).
However, there was no significant difference in grain weight (yield) among the two, three, and four
seedling treatments.
CONCLUSION
We conducted the lysimeter experiment to clarify the difference in rice plant development by different
transplanting density under the SRI practices. The common method of rice transplanting by SRI is
single young rice seedling. However, famers in some lowland areas hesitate to transplant single
seedlings by the SRI method because of the threats from birds, flood, and insects, causing a dilemma
for the farmers over the implementation of the SRI method. We found that the grain yield issignificantly higher for transplantation treatment with three and four seedlings rather than one seedling,validating the farmers’ confidence in their way of applying the SRI method. This study thus suggeststhat farmers can transplant more than one seedling in lowland areas. The study used a Japanesekoshihikari rice nursery. It is highly recommended to test with the local rice variety, climatic condition,
and agronomical practices for a more precise confirmation of optimal seedling densities.
REFERENCES
Chapagain, T. and Yamaji, E. 2009. The effects of irrigation method, age of seedling and spacing on crop
performance, productivity and water-wise rice production in Japan. Paddy Water Environ., 2010, 8, 81-90.
FAO. 2002. FAO rice information. Vol. 2. Rome.
Gimeno-Garcia, E., Andrew, V. and Boluda, R. 1995. Heavy metals incidence in the application of inorganic
fertilizers and pesticides to rice farming soils. Environmental Pollution, 92 (1), 19-25.
IRRI. 1998. Report of the fifth external program and management review of international rice research institute.
Phillipines.
Pun, I. and Yamaji, E. 2014. Comparative study of the structural development of rice, Plants by SRI and non-SRI
methods in a lysimeter experiment. Unpublished manuscript.
Stoop, W.A., Uphoff, N. and Kassam, A. 2002. A review of agricultural research issues raised by the system ofrice intensification (SRI) from Madagascar, Opportunities for improving farming system of resource-poor
farmers. Agricultural System, 71, 249-274.
Thakur, A.K., Rath, S., Patil, D.U. and Kumar, A. 2010. Effects on rice plant morphology and physiology ofwater and associated management practices of the system of rice intensification and their implication for crop
performance. Paddy Water Environ., 2011, 9, 13-24.

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Research article
erd

Adaptation Strategies to Changing Environment by an
Organic Farm in Laguna, Philippines
NINA SHIMOGUCHI *Tokyo University of Agriculture, Tokyo, Japan
Email: n3nocon@nodai.ac.jp

LOIDA MOJICA
University of the Philippines Los Banos, Laguna, Philippines
Received 22 December 2015

Accepted 12 October 2016(*Corresponding Author)

Abstract With the increasing awareness of consumers for an alternative lifestyle and theenactment of the Organic Agricultural Act of 2010, more and more farmers are expected to shift
to organic farming (OF) in the Philippines. However, shifting to OF and maintaning an organic
farm are not easy tasks due to various issues such as lack of knowledge on suitable production
technologies, unstable supply, lack of markets, intensive labor inputs and difficulty incontrolling weeds, pests and diseases to name a few. Despite these issues, some organic farms
were able to sustain operations. This study aims to determine different farm business strategies
that enabled C Farm (CF) to remain in business and continue to grow given the changing
business environment. This paper does not limit its scope to the strategies adopted by CF tocope with climate changes, but this also focuses on the changes in business strategies despite
the challenges in the economic, technological and socio-cultural environment. The case study
approach is done through in-depth interviews with company owners, multiple site visits andobservations. Furthermore, evaluation of the opportunities and threats in a businessenvironment was also done to identify suited strategies implemented by CF. This study is asignificant tool for potential OF investors in determining best practices in the OF business.
Farm visits and key informant interviews revealed that CF was able to adopt innovative
production, marketing, financing and community relationship strategies, which are the key
factors in business survival and growth. Positioned as an agritourism farm, it was able to deal
with the presssures of the external environment by integrating farm operations; crafting
strategies to increase and sustain production through ecological means; adopting keen market
sensing strategies; increasing financing through joint ventures and strengthening community
relations by involving them in the various financing and operations activities.
Keywords organic farming, investment strategies, extension services, Philippines

INTRODUCTION
Conversion to organic farming (OF) has become a prevalent trend all over the world due to increasing
market awareness, growing demand for organic products, and support of the government throughgovernment policies and push for organic agriculture. In addition, more stakeholders of the food chain,including the farmers have become involved. However, Gliessman (2009) explains that success inconversion is based on ability of the farmer to operate the farm and to adjust to other factors (e.g.
extension, market development, prices) of the food system, which are often beyond his/her control. In
other words, it is more than just changing the inputs. This also entails changes in strategies in the foodchain and compliance with regulatory and certification policies. In the case of the Philippines, organic
certification is not an easy process. Amekawa (2013) adds that certification does not generallyⒸ ISERD

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guarantee market access. In most cases, access to market is ensured even before organic farms apply
for certification.
OF has been practiced in the Philippine since early 60s, however, the advent of Green Revolution
in the mid 60s has successfully influenced many farmers to use chemical fertilizers and pesticides toincrease farm productivity. Renewed OF interest started in the 1980s initially by NGOs, farmers, andacademe (Nakanishi, 2014). Since then, increased number of small-scale farms have been developed.
This has caught the attention not only of the health enthusiasts but also the government, which
recognized the importance of OF. With the recent enactment of the Organic Agricultural Act of 2010,
more and more farmers are expected to shift to OF. According to the National Organic Agriculture
Program (NOAP), organic agriculture covers about 40,000 has, which are managed by about 76,500
farmer-beneficiaries in 2013 (Caneda, 2014). Although the scale is still considered small, NOAP addedthat its main targets are to increase total area, increase production volume, expansion in markets,
increase number of certified farms and processors, and increase number of organic agriculture adopters.
However, shifting to OF and maintaining an organic farm are not easy tasks due to various issues suchas lack of knowledge on suitable production technologies; unstable supply; lack of markets; intensive
labor input; and difficulty in controlling weeds, pests and diseases. Another issue related to shifting to
OF is the availability of the organic farm to sustain operations and be resilient given the demands andchallenges of the new business environment. According to Milestad and Darnhofer (2003), resiliency
will highly depend on the learning and adaptation ability from current issues and conditions.
OBJECTIVE
This study aims to determine how an organic farm business was able to cope with the various
challenges in term of the implemented strategies to sustain operations despite changes in the businessenvironment. It should be noted that the environment refers not only to natural factors but also includes
socio-cultural and economic aspects, which affect the farm (Fujimoto, 2014). Lessons from theseexperiences may help other farmers to attain growth and resilience in their OF business. Moreover,this study is a potential tool useful for future OF investors to determine the best practices in the OF
business. It should be noted that this paper may not be able to thoroughly explain all aspects, but aims
to provide an outline for further research.
METHODOLOGYThis study used the case study approach based on the collected qualitative and quantitative data. Thisfocuses on the experience of C Farm (CF), which has been operating in the town of Majayjay, Laguna
Philippines since 2006. The town of Majayjay, which is located about 120 km South of Metro Manila,
is endowed with characteristics that are favorable for vegetable production. Primary data weregathered from farm visits and key-informant interviews conducted in February and May 2014. The
May 2014 interviews were recorded using an IC recorder, and transcribed in order to fully capture thedetails.
RESULTS AND DISCUSSION
Profile of C Farm
Table 1 shows the development of CF, which was initially established in 2006 as a hobby farm towards
achieving an alternative lifestyle. Located near the Majayjay falls, CF started in a 0.77 ha farm lot.
Without any knowledge and experience on farming, the family initially planted fruit bearing trees suchⒸ ISERD

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as santol (Sandoricum koetjape), makopa (Syzygium samarangense), bayabas (Psidium guajava),
dalandan (Citrus aurantium), mangosteen (Garcinia mangostana), langka (Artocarpus heterophyllus)
and sampalok (Tamarindus indica) among others.
While waiting for the trees to bear fruit and so as not waste the time and space, CF started
producing traditional vegetables and herbs for home consumption. The vegetables produced then (e.g.
eggplant, okra, squash, bitter gourd) were mainly used for Ilocano dishes such as pinakbet (i.e. mixed
vegetables sauteed/steamed with shrimp or fish paste), which is highly preferred by the household head,
who hails from the province of Ilocos located in Northern region of the Philippines.
By 2008, the farm also started planting salad greens (e.g. lettuce) initially for home consumption
but expanded towards commercial farming for all its farm produce in response to the demand.
Relatives, friends and aquaintances frequently visited the farm and it is through these visits that thecompany owner of a group of restaurant chains became CF’s first partner in 2009. This initial
partnership involved supplying four (4) branches of its Italian restaurant for the vegetables and herbs
demand. By 2010, CF was able to penetrate and establish a market in Mercato Central, Taguig City,
Metro Manila. In the same year, CF was also duly accredited by the Department of Tourism as theFirst Agritourism Destination in the Philippines, since they also have been offering recreational
activities (e.g. pick-and-pay, fish-and-pay, feeding the animals) and accommodation facilities. These
have resulted to more partnerships with other hotel, restaurant and catering service (HORECA) outlets
and other initiatives (e.g. life at the farm tour, wellness tour).
Currently, CF has expanded to 5 hectares, and more expansion is on the way to keep up with theincreasing demand. It produces 20 tons of vegetables and herbs per month, 80% of which is lettuce . It
is a common practice of CF to produce vegetables based on the contract with the clients. In otherwords, there is assured market for whatever they plant. Production is planned for each client. However,
CF also reserves about 20% of production as buffer for new clients. With regards to organic
certification, CF is duly certified by the Negros Island Organic Certification Services (NICERT).
Table 1 Highlight on the development of C Farm
Year
2006
2008
2009
2010
2012

EventsEstablished as a hobby farm
Started commercial production of organic produce
Supplied a restaurant for the first time (4 branches to 18 branches in 2014)
Achieved "Zero-Waste Farming"
Started marketing at Mercato Central, Global City, Taguig
Accredited as the First Agritourism Destination in the Philippines
Ventured on more partnerships with other HORECA outlets
Established a website
Started the "Building a Greenhouse" programAwarded as the Most Outstanding Farm in the Philippines by President Aquino

Source: Key informant interview, May 2014

Adaptation Strategies
Since its establishment, CF has been facing a series of opportunities and threats that it has successfully
responded to. It has been able to adapt to its environment, hence its growth, sustainability andresilience through the years.
Integrated Farming Operations
CF meets market demands, and grows and sustains its business through integrated farming operations.
This is also a way of dividing risks and keeping costs to a minimum since all businesses in the farmⒸ ISERD

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support each other. The farm does not incur logistics and transaction costs in sourcing organic
fertilizers because this is also produced in the farm. Some raw materials for organic fertilizers comefrom the crops and animals that the farm grows. It was observed that the output of one business group(organic fertilizer) is used as inputs to another business group (crop production). The integrated farmconsists of high value crop production, culinary herbs, free-range poultry and livestock, aquaculture,vermiculture and orchard. It also has service facilities such as restaurants, training rooms and lodging
areas, which support their tour and private extension activities. Fig. 1 shows the organizational
structure showing the different businesses.
ChairmanNursery and Seedling
Department

President

Plant and Maintenance
Department

Vice- President

Post-Harvest Department

Packing Section

Livestock, Poultry and
Aquaculture Department

Fertilizer Section

Agritourism Department

Housekeeping Section

Office Administration
Department

Tour Guide Section

Kitchen Section

Fig. 1 Organizational structure of C Farm
Source: Key informant interview, May 2014

Market Networking Strategies
One of the challenges in the OF business is keeping connected with good markets. CF is able tomaintain good relationships with a group of restaurants chain-company, which is its first institutionalbuyer. CF also formed a marketing partnership with a high-end retail chain store selling organic
products. CF exclusively supplies organic pork, chicken and eggs to this company. Aside from these
two big buyers, they also serve prominent hotels and other smaller regular buyers in Metro Manila.
Keeping connected with these markets and continuous search for future markets are some advantagesof CF.
Sharing of Information and Technologies
Traditionally, Filipino farms do not often share trade-secrets such as farm technologies and otherinformation. This is not the case for CF as this farm openly shares their OF experience and business.
CF builds relationships with communities and potential organic farmers by sharing technologies andmarket information. Seminars and trainings are conducted in the farm where OF as a business andlifestyle is showcased. This is a farm extension activity where CF as a private entity actively takes partsince 2010. With this strategy, CF is also able to source agricultural produce from these new farmers
during times when the farm produce cannot meet the volume requirements of the market. Moreover,Ⓒ ISERD

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CF is creating notable impact in the community as increasing number of local and foreign people learn
the OF processes and their long-term benefits to health and the ecology as a whole.
In addition, with its accreditation as the private extension service provider of the Agricultural
Training Institute (ATI) under the Department of Agriculture (DA), CF is in the position to also further
expand its networks with the government, educational institutions and other agencies interested in the
OF system.
Investment Partnering through Joint Venture Arrangements
Majayjay Town, where the farm is located, has approximately 10 months of rain. This kind of weather
adversely affects vegetable production. To meet the increasing demand for vegetables, CF realized theneed to find alternative ways to adapt to the condition of the natural environment by putting up
greenhouses. However, the family was not financially capable due to limited capital. One growth andsustainability strategy that they implemented at this point is to encourage partnership and investment
into the farm.
In 2012, CF initially targeted and invited Overseas Filipino Workers (OFWs) to be business
partners for its "Building a Greenhouse" program under joint venture (JV) arrangements. CF assumed
that OFWs have the capital, the willingness to invest and the interest in organic production, but do nothave the time and knowledge to engage in farming. In this JV arrangement, investors fund the buildingof greenhouses within the farm, while CF does the actual production and marketing operations. CF
and the investors share the profit 50:50 every quarter. The advantage of this arrangement aside fromprofit share is that the investor does not do actual farming operations while CF does not need to invest
in greenhouse facilities. In six (6) months after the announcement in its official website, CF was able
to fill up its farm with greenhouses. The first venture partners were an engineer in Africa and a doctor
in USA, both of whom, the owners do not know personally. Investment partnering, an innovation
strategy adopted by CF, is now being practiced by other organic farms.
Recent JV offerings are agritourism development and multi-purpose hall project in response to theneed for expansion of the farm and agritourism operations, and establishing a training center,
respectively. Through investment partnering, organic farms are able to cope with the financial
challenges in business operations.
Capitalizing and Promoting Health Consciousness
The trend towards a healthy and alternative lifestyle is what prompted CF to invest in OF. It isprojected that this trend will continue on a long term. Consumers are realizing the importance of good
health and are more conscious of the negative effects of synthetic chemicals used in agricultural
production. The green revolution that was previously seen as the solution to food crisis is now being
associated with many health issues. This is also demonstrated in India where the Green revolution
increased productivity and export potential to the degradation of the ecosystem. It has caused
irreversible poisoning of the environment and is seen to adversely affect future generations (Vaarst,2010). CF continuously promotes health consciousness among its network of buyers and the larger
community as well. Health consciousness campaign is part of the overall OF showcase, which isemphasized in the seminars and farm tours that CF is conducting.
Positioning the Farm as an Agritourism Farm
The change in the positioning of CF from just an organic farm to an agritourism farm has provided
opportunities for the farm to widen its reach and serve more people through community activities. CFⒸ ISERD

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is able to showcase its OF model, which it willingly shares with its visitors. As an agritourism farm, it
offers tour and learning packages for OF enthusiasts.
CONCLUSION
An organic farm’s growth and sustainability is determined by its ability to adapt to the challenges ofthe external environment. A key adaptation strategy implemented by CF is integrating farm business
operations. Small organic farmers may not be able to adapt this strategy but there is always thatpossibility that they can connect with CF or similar farms by participating in their farm extension
program. An innovation that CF adapted to enable the farm to grow and respond to its increasing
demand is through investment partnering. CF as an agritourism farm has a strategic advantage, sincetrend towards ecology-based farming and health consciousness will continue in the next several
decades.
ACKNOWLEDGEMENTS
This paper is partly funded by a 4-year JSPS project (2013-2017) entitled “Support System for Rural
Innovation Towards Human Development and Knowledge Creation” with Prof. Dr. Hiroki Inaizumi as
project leader.
REFERENCES
Amekawa, Y. 2013. Can a public GAP ensure safety and fairness? A comparative study of Q-GAP in Thailand. J.
Peasant Stud., 40 (1), 189-219.
Caneda, L. 2014. Personal Interview, National Organic Agriculture Program Coordinator. 2 May 2014.
Fujimoto, A. 2014. What is biobusiness environment? In Inaizumi, H., Nibe, A. and Yamada, T. (Eds)
Biobusiness, 12, Ie no Hikari Association. 158-168. Japan.
Gliessman, S. 2009. The framework for conversion. In Gliessman, S. and Rosemeyer, M. (Eds) The Conversion
to Sustainable Agriculture, –Principles, Processes and Practices. CRP Press, Taylor and Francis Group, 3-14.
USA.
Milestad, R. and Darnhofer, I. 2003. Building farm resilience, The prospects and challenges of organic farming, J.
Sust. Agric., 22 (3), 81-97.
Nakanishi, T. 2014. Piripin no yuki nogyo ni manabu (Lessons from Philippine Organic Agriculture in Japanese).
Noson To Toshi Wo Musubu, 748, 55-58. Japan.
Vaarst, M. 2010. Organic farming, Who are interested and who are no? J. Sust. Dev., 3 (1), 39-50.

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Research article
erd

Diversity of Plant Growth Promoting Rhizobacteria
Communities Associated with Thiamethoxam in Cassava
Production Systems
PHRUEKSA LAWONGSA*
Department of Plant Science and Agricultural Resources, Land Resources and Environment Section,
Agricultural Biotechnology Research Center for Sustainable Economy: (ABRCSE),
Faculty of Agriculture, Khon Kaen University, Khon Kaen, Thailand
Email: phrueksa@gmail.com

PIMUPSORN PANOMKHUM
Department of Plant Science and Agricultural Resources, Land Resources and Environment Section,
Faculty of Agriculture, Khon Kaen University, Khon Kaen, Thailand
Received 26 October 2015

Accepted 12 October 2016(*Corresponding Author)

Abstract The use of chemical pesticide always leaves chemical residues on soil and may affectthe population, function and diversity of soil microorganisms. Therefore, the aim of the study
was to determine the effect of thiamethoxam, pesticide in the group of neonicotinoid to control
insect pest, on diversity of plant growth promoting rhizobacteria (PGPR) communities incassava production systems. Bacteria were isolated from rhizosphere of cassava grown in thefield of 5 treatments, including cassava production system without thiamethoxam and fertilizer
application, cassava production system with thiamethoxam application, cassava production
system with thiamethoxam and organic fertilizer application, cassava production system withthiamethoxam and chemical fertilizer application, and cassava production system withthiamethoxam, organic and chemical fertilizer application, and then screened for plant growthpromoting traits. The genotypic diversity of isolates was determined on a basis of amplified
rDNA restriction analysis (ARDRA). The findings of this study indicated that the majority ofbacteria were found to belong to the genera of Bacillus, Ochrobactrum, and Brevibacillus.
Interestingly, the application of thiamethoxam in cassava production system has no effect on
PGPR diversity.
Keywords Plant Growth Promoting Rhizobacteria (PGPR), Thiamethoxam, Cassava

INTRODUCTION
Plant growth promoting rhizobacteria (PGPR) represent numerous species of soil bacteria which, whengrown in association with a host plant, result in stimulation of growth of their host. PGPR are used as
inoculants for biofertilization, phytostimulation, biocontrol (Bloemberg and Lugtenberg, 2001) andbioformulation (Prathap and Ranjitha Kumari, 2015). PGPR can directly benefit plant growth by fixing
nitrogen, which can subsequently be used by the plant, thereby improving plant growth when theamount of nitrogen in the soil is limited (Vessey and Buss, 2002), produce phytohormone such asindole-3-acetic acid (IAA) (Ahemad and Khan, 2012; Sachdev et al., 2009) and phosphorus uptake)Rodriguez and Fraga, 1999(. Indirectly, by increase resistance to pathogen, PGPR may suppress plant
pathogens by producing antimicrobial metabolites )Duffy et al., 2004( as well as by producing
enzymes and/or fungicidal compounds (Bloemberg and Lugtenberg, 2001; Haas and Défago, 2005). In
addition, PGPR can produce siderophore induced disease resistance, which can be enhanced by thesimultaneous activation of induced systemic resistance (ISR) and systemic acquired resistance (SAR)Ⓒ ISERD

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pathways (Duffy and Défago, 1999). However, accumulation of chemical pesticides into the soils
beyond certain threshold levels due to its frequent application in the fields to overcome plant pests
damages the rhizosphere microorganisms and their activities (Wani et al., 2005) and may alter diversityof the microorganism. Nowadays, thiamethoxam, pesticide in the group of neonicotinoid, was normallyused for cassava stake soaking to control aphids. However, the data of whether thiamethoxam affects
soil microorganism diversity remains scarce.
OBJECTIVE
The purpose of this study was to investigate the influence of chemical pesticide (thiamethoxam) on thediversity of PGPR communities in cassava production systems.
METHODOLOGY
Study Sites and Soil Sampling
Study sites used in this study were selected from Kalasin province )N16°38'3", E 103° 15 '15"(,
Thailand. This experiment has been designed as the randomized complete block design (RCBD). A
sampled area was set up at 5m x10 m for each block. Soil samples were collected from rhizosphere of
cassava cultivar Kasetsart 50 (KU50) at a spacing of 1m x 1m with three replications at 0, 15, 30, 45
and 60 days after planting (DAP). Thiamethoxam 25 WG was used in this study for cassava stakesoaking at the rate 4g/20 liters of water. Five treatments used in this study, including cassava
production system without thiamethoxam and fertilizer application (T1), cassava production systemwith thiamethoxam application (T2), cassava production system with thiamethoxam and organic
fertilizer application (T3), cassava production system with thiamethoxam and chemical fertilizer
application (T4), and cassava production system with thiamethoxam, organic and chemical fertilizer
application (T5). Organic fertilizer used in this study is chicken manure mixed with rice husk, 1000
kg/1,600 m2 and chemical fertilizer used in this study is formula 15-7-18, 50 kg/1,600 m2. The
rhizosphere samples were placed in plastic bags and stored at 4°C for further microbial analysis.
Isolation of PGPR from Cassava Rhizosphere
Bacterial strains were isolated from cassava rhizosphere by serial dilution plate technique on nutrient
agar medium (NAM). The bacterial colonies were isolated and maintained on NAM slants at 4°C. One
hundred isolates obtained from serial dilution plate technique of each treatment were screened for theirplant growth promoting factors included production of indole-3-acetic acid (IAA), phosphatesolubilizing activity and their ability to grow in N-free medium. In addition, their biocontrol activity
included protease enzyme production as well as siderophore production was investigated.
Assays for Growth Promoting Abilities of Isolates
Indole-3-acetic acid (IAA) production: IAA production was determined using the method describedby Lawongsa et al. (2008) with slight modification. Bacterial isolates were cultured in Tris-TMRT (Dmannitol 10 g, yeast extract 0.2 g, CaCl2.2H2O 0.2 g, MgSO4.7H2O 0.25 g, tris-base 1.21 g, pH 6.8)
supplemented with tryptophan 0.5 mM for 48 h. The measurement of IAA was done by adding 2 ml of
0.01 M FeCl3 in 35 % HClO4 into 1 ml of Tris-TMRT culture broth. The mixture was incubated in thedark at 30 °C for 30 min. The detection of IAA was determined by the development of pink color.
Phosphate solubilizing assay: Solubilization of tricalcium phosphate was detected in national
botanical research institute’s phosphate growth medium (NBRIP) agar plate supplemented with 1.5 %Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2(w/v) agar (Nautiyal, 1999). Five microliters of each bacterial culture was dropped on NBRIP agar
plates. Plates were incubated for 7 days at 28°C. The development of halo zone around the bacterialcolony was considered as positive for phosphate solubilizing activity.
Nitrogenase activity: For rapid determination, nitrogenase activity was assayed after bacterial strains
were streaked onto N-free minimal medium supplemented with 1.5 % (w/v) agar and incubated at 28 ±2 °C for 3 days (Desnoues et al., 2003). Bacterial growth indicated nitrogenase activity.
Protease assay: Bacteria were isolated for protease enzyme (casein degradation) using a method
described by Sjödahl et al. (2002(. Samples were inoculated on Luria-Bertani (LB) agar plates
containing skim milk (20 %(, then incubated at 28 ± 2 °C for two days (Uyar et al., 2011(. The
development of clear zone around the bacterial colony indicated protease enzyme activity.
Siderophore assay: Siderophore was determined by chromazurol sulphonate agar (CAS) using themethod described by Clark and Bavoil (1994). Bacterial inoculum was spotted into the center of a CAS
agar plate. After incubation at 28°C for 5 days, siderophore production was assayed by clear zone
formation around the cell.
Total Genomic DNA Isolation
PGPR isolates were grown in a nutrient broth at 28°C overnight and then were harvested bycentrifugation at 5,000xg for 5 min and washed twice in 500 µl of TEN buffer (0.1 M Tris-Cl, 0.01 M
ethylenediaminetetraacetic acid (EDTA), and 1 M NaCl, pH 8.0). Cell lysates were prepared by mixing
the cell pellet with 200 µl of 20% (w/v) sucrose in TEN buffer to this 20 µl of 2 mg/ml of lysozyme
and 20 µl of 10 mg/ml of RNase was added. Cell mixtures were incubated at 37°C for 60 min. Then 75µl of 5 M NaCl and 100 µl of 10% Sodium dodecyl sulfate (SDS) were added before gentle mixing.
The solution was purified twice by using phenol:chloroform:isoamyl-alcohol (25:24:1, by volume).
The upper phase was collected and precipitated by using isopropanol and 3 M sodium acetate. The
DNA pellet was resuspended in sterilized deionized-water and total genomic DNA was kept at -20°C
before use (Sambrook and Russell, 2001).
Amplified rDNA Restriction Analysis (ARDRA)
The 16S rDNA universal primers fD1 (5’-AGAGTTTGATCCTGGCTCAG-3’) and rP2 (5’AAGGAGGTGATCCAGCC-3’) (Weisburg et al. 1991) were used to amplify a 1.5-kb internal regionof the 16S rRNA gene. An initial denaturation at 95°C for 5 min was followed by 35 cycles withdenaturation at of 95°C (30 s), annealing at 58°C (1 min) and extension at 72°C (2 min), and a final
extension at 72°C for 7min. Restriction analysis was performed with 5 µl of amplified product and 10µl of restriction buffer containing 2 U of either the restriction enzymes AluI. After a 4 h digestion at theappropriate temperature, the enzyme was inactivated by heating the preparations at 65°C for 20 min.
For each isolate, PCR amplification and restriction analysis were performed at least three times.
Calculation of the pair-wise coefficients of similarity was based on the presence or absence of bands. A
cluster analysis with the UPGMA algorithm was performed with the NTSYS-pc numerical taxonomy
and multivariate analysis system. Then, Representatives of each group were selected for cloning andpartial 16S rRNA gene sequencing to retrieve sequence similarity and bacterial identity from
nucleotide sequence databases.
RESULTS AND DISCUSSION
Plant Growth Promoting Properties of Bacterial StrainsⒸ ISERD

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A total of 100 cultivable bacterial isolates of each treatment obtained after serial dilutions werescreened for plant growth promoting traits. Subsequently, community of representatives of PGPR
genera/species of each treatment was distinguished by ARDRA analysis. Detailed data of thephenotypic characterization of these isolates are shown in Fig. 1. Ninety five percentage of PGPR
isolates obtained from ARDRA cluster I showed the ability to solubilize phosphate and 85% of PGPR
isolates showed the ability to produce IAA. In ARDRA cluster II, 100% of PGPR isolates obtained
from ARDRA cluster I showed the ability to solubilize phosphate and 90% of PGPR isolates showed
the ability to produce IAA. In ARDRA cluster III, 100% of PGPR isolates obtained from ARDRA
cluster I showed the ability to solubilize phosphate, 80% of PGPR isolates showed the ability to
produce IAA and 80% of PGPR isolates showed the ability to grow in N-free medium. Meanwhile, in
ARDRA cluster IV, PGPR isolate showed the ability to produce IAA, protease can solubilize
phosphate and be able to grow in N-free medium but did not show the ability to produce siderophore.
ARDRA Analysis and 16S rRNA Gene Partial Sequencing on PGPR Isolates
The cluster dendogram of ARDRA analysis of PGPR isolates obtained from cassava rhizosphere isillustrated in Fig. 1. Digestion of amplified 16S rDNA with AluI revealed four main clusters of
ARDRA dendogram. Cluster I and II of ARDRA dendogram showed representative of genera/species
from all treatment. Cluster III contained representative of PGPR genera/species from T1 (cassava
production system without thiamethoxam and fertilizer application), T2 (cassava production systemwith thiamethoxam application) and T4 (cassava production system with thiamethoxam and chemicalfertilizer application) while, cluster IV showed representative of PGPR genera/species only from T2.

*The different isolates were designated KU followed by the time after planting (0, 15, 30, 45 or 60),
treatment number and by progressive numbers of PGPR isolation.

Fig. 1 Dendogram of PGPR isolates representing each ARDRA group and plant growthpromotion characteristics presented by bacterial isolates and their ARDRA groupsⒸ ISERD

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Interestingly, no representative of PGPR genera/species isolated at 60 DAP was observed incluster I of ARDRA dendogram. In addition, no representative of PGPR genera/species isolated from 0
DAP was observed in cluster II of ARDRA dendogram. In ARDRA cluster III, no PGPR
genera/species isolates at 0 and 15 DAP was obtained. Moreover, In ARDRA cluster IV, only PGPR
genera/species isolates at 60 DAP from T2 was found. Additionally, PGPR isolates from treatment
applied with organic fertilizer were not found in ARDRA cluster III and IV.
On the basis of the 16S rRNA gene sequence analysis, in excess of 1 kb fragments weresequenced for most of isolates, with similarities ranging between 95 and 99%. Six isolates wereidentified as Ochrobactrum anthropi, three as Ochrobactrum ciceri, One as Ochrobactrum
intermedium, fifteen as Bacillus spp., one as Bacillus silvertri, four as Bacillus thuringiensis, two as
Bacillus megeterium and four as Brevibacillus reuszeri (Table 1). Interestingly, Brevibacillus spp. was
not found at 0, 15, 30 and 45 DAP, but was only obtained at 60 DAP.
Table 1 Similarity analysis based on 16S rRNA gene partial sequences of PGPR isolates bycomparing to the GenBank and their ARDRA groups
ARDRA group

Isolates
Homology% identity
Accession No.
KU0T1, KU0T2.1,
KU15T2.1, KU15T3,
Ochrobactrum anthropi DJ3
97
KC992296.1
KU30T2, KU45T1.1
KU0T2.2, KU0T3,
KU0T4, KU0T5,
KU15T1.1, KU15T4,
Bacillus sp. SGE119
99
HM566648.1
I
KU15T5, KU30T5,
KU45T1.2, KU45T2.1
KU15T1.2, KU45T3,
Ochrobactrum ciceri L2296
JX646649.1
KU45T5
KU45T2.2
Ochrobactrum intermedium SYF-18
98
JN048652.1
KU15T1.3
Bacillus sp. DoB56
98
JQ359104.1
KU15T2.2
Bacillus sp. SGE39
99
HM566736.1
KU45T1.3
Bacillus silvestris SAFN-010
95
AY167818.1
II
KU60T1.1, KU60T2.1,
Bacillus sp.YY-13
99
JX575604.1
KU60T2.2
KU30T3, KU30T4,
Bacillus thuringiensis Ou2
98
KP128698.1
KU60T3, KU60T5
KU30T1
Bacillus megaterium H2
99
JQ579631.1
KU45T4
Bacillus megaterium ML257
98
KC692200.1
III
KU60T1.2, KU60T2.3,
Brevibacillus reuszeri NBRC15719
99
AB680946.1
KU60T4IV
KU60T2.4
Brevibacillus reuszeri BCX-22
98
KM378576.1*The different isolates were designated KU followed by the time after planting (0, 15, 30, 45 or 60), treatment number andby progressive numbers of PGPR isolation.

These findings clearly showed that thiamethoxam had no effect on PGPR diversity as ARDRA
cluster 1, 2 and 3 shared the same soil bacterial ribotypes including PGPR isolated from T1 and PGPR
isolated from T2. This could be certified to the fact that certain soil bacteria can degrade pesticides.
Bacillus spp., Ochrobactrum spp. and Brevibacillus spp. are common soil bacteria easily cultured frommost agricultural soils. The previous study showed that Bacillus megaterium has potential applicationin bioremediation of contaminated soil and water system (Sogani et al., 2014). Ochrobactrum spp. isalso found to be able to degrade pesticide in neonicotinoid group such as imidacloprid (Hu et al., 2013).
In addition to species of the Ochrobactrum genus, many individual isolates have been found to be able
to degrade pesticide in neonicotinoid group, such as Bacillus spp. and Brevibacterium spp.
(Sabourmoghaddam et al., 2015). Moreover, certain soil bacteria might have utilized pesticide asenergy sources as well (Ahemad and Khan, 2011).
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CONCLUSION
In this study, thirteen bacterial strains isolated from cassava KU50 were characterized. Most of thebacteria were member of the Bacillaceae, Brucellaceae and Paenibacillaceae families. The bacterial
communities were dominated by Bacillus spp. (61.11%), Ochrobactrum spp. (27.78%) andBrevibacillus spp. (11.11%). Interestingly, the findings of diversity analysis of thirty six bacterial
isolates selected at random but representing each field site by ARDRA suggested that thiamethoxam
had no effect on PGPR diversity as application of thiamethoxam was not be able to distinguish soil
bacterial ribotypes.
ACKNOWLEDGEMENTS
This work was supported by a grant from National Science and Technology Development Agency andAgricultural Biotechnology Research Center for Sustainable Economy, Khon Kaen University.
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Pseudomonas putida under insecticide-stress. Microbiol. J., 1, 54-64.
Ahemad, M. and Khan, M.S. 2012. Productivity of greengram in tebuconazole-stressed soil, by using a tolerant
and plant growth promoting Bradyrhizobium sp. MRM6 strain. Acta Physiol. Plant., 34, 245-254.
Bloemberg, G.V. and Lugtenberg, B.J.J. 2001. Molecular basis of plant growth promotion and biocontrol byrhizobacteria. Curr. Opin. Biotechnol., 4, 343-350.
Clark, V.L. and Bavoil, P.M. 1994. Methods in enzymology. London, Academic Press.
Desnoues, N., Lin, M., Guo, X., Ma, L., Carreno-Lopez, R. and Elmerich, C. 2003. Nitrogen fixation genetics
and regulation in a Pseudomonas stutzeri strain associated with rice. Microbiol., 149, 2251-2262.
Duffy, B. and Défago, G. 1999. Environmental factors modulating antibiotic and siderophore biosynthesis by
Pseudomonas fluorescens biocontrol strains. Appl. Environ. Microbiol., 65, 2429-2438.
Duffy, B., Keel, C. and Défago, G. 2004. Potential role of pathogen signaling in multitrophic plant-microbe
interactions involved in disease protection. Appl. Environ. Microbiol., 70, 1836-1842.
Haas, D. and Défago, G. 2005. Biological control of soil-borne pathogens by fluorescent pseudomonads. Nature
Rev. Microbiol., 3, 307-319.
Hu, G., Zhao, Y., Liu, B., Song, F. and You, M. 2013. Isolation of an indigenous imidacloprid-degrading
bacterium and imidacloprid bioremediation under simulated In situ and Ex situ conditions. J. Microbiol.
Biotechnol., 23, 1617-1626.
Lawongsa, P., Boonkerd, N., Wongkaew, S., O’Gara, F. and Teaumroong, N. 2008. Molecular and phenotypiccharacterization of potential plant growth-promoting Pseudomonas from rice and maize rhizospheres. World J.
Microbiol. Biotechnol., 24, 1877-1884.
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microorganisms. FEMS Microbiol. Lett., 170, 265-270.
Prathap, M. and Ranjitha Kumari, B.D. 2015. A critical review on plant growth promoting rhizobacteria. J. Plant
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Rodriguez, H. and Fraga, R. 1999. Phosphate solubilizing bacteria and their role in plant growth promotion.
Biotech. Adv., 17, 319-339.
Sabourmoghaddam, N., Zakaria, M.P. and Omar, D. 2015. Evidence for the microbial degradation of
imidacloprid in soils of Cameron Highlands. J. Saudi Soc. Agric. Sci., 14, 182-188.
Sachdev, D.P., Chaudhari, H.G., Kasure, V.M., Dahavale, D.D. and Chopade, B.A. 2009. Isolation andcharacterization of indole acetic acid (IAA) producing Klebsiella pneumoniae strains from rhizosphere ofwheat (Triticum aestivum) and their effect on plant growth. Indian J. Exp. Biol., 47, 993-1000.
Sambrook, J. and Russell, D.W. 2001. Molecular cloning: a laboratory manual. Cold Spring Harbor Laboratory,
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Sjödahl, J., Emmer, Å., Vincent, J. and Roeraade, J. 2002. Characterization of proteinases from Antarctic krill(Euphausia superba). Protein Express. Purific., 26, 153-161.
Sogani, M., Bakre, P.P., Mathur, N., Sharma, P. and Bhatnagar, P. 2014. Acetamide hydrolyzing activity ofBacillus megaterium F-8 with bioremediation potential: optimization of production and reaction conditions.
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Research article
erd

Impact Assessment of Land Use Change on Ecosystem Services
and Livelihood Security of Rural Highland Communities in
Saysathan District, Sayaboury Province, Lao PDRBOUAVONH BIACHAMPAH*
Department of Agriculture and Forestry, Ministry of Agriculture and Forestry,
Vientiane Capital, Lao PDR
Email: bouavonh@gmail.com

PANOMSAK PROMBUROM
Center for Agricultural Resource Systems Research, Faculty of Agriculture,
Chiang Mai University, Thailand

BUDSARA LIMNIRANKUL
Department of Agricultural Economy and Development, Faculty of Agriculture,
Chiang Mai University, Chiang Mai, Thailand
Received 10 November 2015

Accepted 17 October 2016(*Corresponding Author)

Abstract It is widely recognized that land use changes are affecting provision of ecosystemservices as well as people’s livelihoods, especially in rural areas where people are highly
dependent on local ecosystem services. This study developed an integrated methodologicalframework by combining a diversity of corresponding frameworks and concept, such as DriverPressure-State-Impact-Response (DPSIR), Ecosystem Services (ES), Sustainable Livelihood
Framework (SLF) and Agro-Ecosystem Analysis (AEA). This integrated framework was used
together with a combination of Participatory Rural Appraisal (PRA) method and spatiotemporal
analysis. The objectives of this study aimed at detecting land use change and identifying its
drivers; and assessing the impact on provisioning ES and livelihood security of rural highlandcommunities in Saysathan district, Sayaboury province, Lao People’s Democratic Republic(Lao PDR). Land use change analysis highlighted a large decrease in forest areas during thepast decade. The reduction of forest cover was associated with significant decline ofprovisioning ES, and the decline in provisioning ecosystem services also influenced the state oflivelihood security of the local communities, especially natural capital. By taking the trajectoryof forest cover change and the importance of provisioning ES into account, it is essential for
stakeholders to integrate ES indicators into land use management planning as well as socioeconomic development to maximize benefits from natural resources to the communities.
Keywords land use change, ecosystem services, livelihood security, integrated methodologicalframework, rural highland communities, Lao PDR

INTRODUCTION
In the Lao PDR land use change has been recognized for several decades which mostly driven byrelated government policies, such as Land and Forest Allocation (LFA), land concession, and others(Thomas, 2003; Saphangthong and Kono, 2009; Baird, 2010). Consequences of land use change haveresulted in degradation of natural resources i.e. changes in ecosystems causing negative impacts not
only on agricultural land and livelihood but also on forest covers and long-term environmental
degradation (PEI, 2012). For instance, a reduction of shifting cultivation land and shortened fallow
period, increased weed population, depleted soil fertility, and reduced crop productivity as well asⒸ ISERD

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labor productivity (Takahashi and Liang, 2010), and a continuous reduction of forest cover from 70%of the national land in 1940 to 64% in the 1960s, to 49.2% in 1982, to 47.1% in 1992, 41.5% in 2002
and 40.29% in 2010 (UNEP, 2001; World Bank, 2001; Bouahom, 2009; DOF, 2003; 2005; 2011).
Although impacts of land use changes have been widely studied, there is still a need to investigate
drivers that have led to change in land use, and how ecosystem services (ES) and livelihood security(LS) are affected by land use change, especially at local level in rural context.
OBJECTIVE
This study aimed at (1) detecting land use change and identifying its drivers during 2005 to 2014; and(2) assessing the impacts of land use change on provisioning ecosystem services and livelihood
security of local community.
METHODOLOGY
Study Site
Saysathan is a rural highland district of Sayaboury province, located in the north-central part of the Lao
PDR between latitudes 19°13’12”N and 19°33’15”N and longitudes 101°11’11”E and 101°31’47”E,with elevations ranging from 324 to 2,061 meters above sea level. In order to get insight information ofthis area, two villages (Doykao and Paklong) with a diversity of agroecosytem and livelihood contexts(traditionally relying on shifting cultivation and natural resources as for maintaining their livelihoods;
being in the transition of land use, natural resources and livelihood, and facing land use management
problems; and others) were selected for this study.
Data Collection
This study developed an integrated methodological framework from various frameworks and concepts,
such as DPSIR, ES, SLF and AEA, which have been effectively applied in rural research perspectives.
This integrated framework was used to support the data collection process so that all activities could be
conducted systematically and logically. PRA method with a series of activities, for example, key
informant interview, focus group discussions (FGDs), resource mapping, livelihood analysis, historicalprofile, etc., and spatiotemporal analysis were also used to conceptualize, diagnose and synthesize theinterconnectedness of land use change, ES and livelihood security of the local communities.
A total of thirty-three indicators of livelihood security (ten of provisioning ES, the italicized texts)
were collectively developed and categorized into five main groups as follows:x Human capital: (1) health; (2) children’s school enrollment; (3) adult literacy; (4) labor availabilityx Natural capital: (5) land holding size; (6) soil fertility; (7) rice yield; (8) timber; (9) bamboo; (10)firewood; (11) broom grass; (12) bamboo shoots; (13) wild mushroom; (14) wild vegetables; (15)wildlife (e.g. bird, rat, squirrel, etc.); (16) aquatic species (e.g. fish, frogs, crab, etc.)
x Financial capital: (17) household income; (18) land ownership; (29) cattle holding; (20) house
quality; (21) access to creditx Physical capital: (22) access to clean water; (23) access to road; (24) access to school; (25) access to
hospital/healthcare center/dispensary; (26) access to electricity; (27) access to market; (28) access to
information and communication services
x Social capital: (29) capacity of village authority; (30) community participation; (31) woman’ role invillage organization; (32) woman’ role in household decision-making; (33) traditional worshipingⒸ ISERD

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The majority of indicators were determined using critical values representing three different
degrees, including 0.33, 0.66 and 1 to replace, for example, “Poor”, “Average” and “Good”,
respectively (Muangkaew and Shivakoti, 2005). Another form of “Yes” and “No” answers, the valuesof 1 and 0 were used respectively. Two temporal Landsat images, including Landsat 5 Thematic
Mapper (TM) and Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) acquired
on February of 2005 and 2014 respectively were used for land use change analysis. In addition,
household survey with a total of 70 sampled households (purposively selected using on a quota
sampling method), were also conducted in December, 2014.
Data Analysis
Landsat imageries were classified, analyzed and visualized using a combination of remote sensing (RS)and geographical information system (GIS) techniques. The developed indicators were standardized
into the values ranged from 0 to 1 using the min and max normalization method. Ranking and scoring
methods were applied to reflect the importance of indicators. The capital index values were also
aggregated for the “Composite Index” which was used to imply states of livelihood security of thestudied communities. The normalized and weighted data were then analyzed, and the asset pentagon(DFID, 1999) was created to visualize various aspects of livelihood assets. Finally, the aggregatedcapital values as well as the composite index were interpreted using the rating scale of “0-0.33”, “0.340.66” and “0.67-1” for “Poor”, “Average” and “Good” conditions, respectively.
RESULTS AND DISCUSSION
Changes in Land Use between 2005 and 2014
2005

2014

Fig. 1 Land use classification of Doykao village in 2005 and 2014
2005

2014

Fig. 2 Land use classification of Paklong village in 2005 and 2014
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The results of this study (Tables 1 and 2) assert that, in both Doykao and Paklong villages, forest area
and upland rice field were obviously decreased between the year 2005 and 2014. In contrast, the results
also reveal significant increases in fallow and urban areas similarly in the two villages (Figs. 1 and 2).
The decreases in forest area are consistent with the study of Eickhoff et al., (2012) that highlights
a continuous reduction of forest cover in this area. However, when considering with a reduction of
upland rice field, these results seem to disagree with other findings which mostly reveal that upland
rice agriculture is the major cause of deforestation. Nevertheless, the results are consistent with CPI(2005) which notes that a reduction of shifting cultivation and a decrease in forest area occurredconcurrently.
In this regard, the finding from the Focus Group Discussions (FGDs) addressed that a reduction of
upland rice field was mainly related to recognition of village boundary which encourages farmers tocultivate specifically in their village areas unlike years ago that anyone could farm anywhere they
preferred. The decrease in forest area was associated with upland rice farming. The forest wastransformed into upland rice field (at the time the upland rice area increased), then most of them wasleft fallow due to the land use policy particularly LFA, and the farmers had to cultivate in the limited
allocated land.
Table 2 Land use change matrix for Doykao village from 2005 to 2014
From land use 2005 (ha)Total

2,629.26

Type
Loss into Land use Area net changes
changeFallow Forest Upland rice Urban 2014 (ha) 2014 (ha)(ha)(%) rate (%)
402.092.34
110.918.75
122.00 1,330.11 806.02 59.11
23.28
Into land use 2014 (ha)Fallow

524.09Forest

1,388.34

571.77615.84167.1234.01

772.91670.66-717.68-52.63

55.67

Upland rice712.19356.2552.99

248.2154.85

463.98530.87-181.32-13.30

65.15

Urban

4.64

-

-

4.64

-

4.64

97.61

92.98

6.82

100.00928.0255.23

282.6797.61

1,363.53

2,629.26

Gain into 2014 (ha)Source: Data analysis

Table 3 Land use change matrix for Paklong village from 2005 to 2014
From land use 2005 (ha)Total

5,753.63

Fallow

Fallow

1,667.47

Forest2,069.92

Upland rice

2,006.74

1,041.58

9.50

Gain into 2014 (ha)Source: Data analysis

Urban

Type
Loss into Land use Area net changes
changeForest Upland rice Urban 2014 (ha) 2014 (ha)(ha)(%) rate (%)
28.32
279.560.52
308.40 3,012.99 1,345.52 60.87
18.50

Into land use 2014 (ha)1,359.07

609.19 1,353.02

107.030.69

716.91 1,511.24-558.69-25.2834.63

129.11825.7010.36 1,181.04 1,212.29-794.45-35.94

58.85

3.15

0.79

-

7.62

0.34

41.56

1,653.92

158.22386.59

5.55

3.95

17.11

11.56 2,210.30 5,753.63

Responses from the FGDs and the household survey (Fig. 3) indicate that these changes in land
use have been primarily driven by the government's policies, increasing population and forest fire
which actually caused by human’s activity, specifically upland rice farming.

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100.00

85.00

80.00
60.00

60.00

57.14

40.00

31.43

31.43

20.00

11.43

15.00

8.57

5.00

-

DoykaoPaklong

Govt. policy

Local officials

Population growth

Forest fire

Fig. 3 Drivers of land use change in the study area given by different stakeholders
Changes in Provisioning ES and Livelihood Security
Index Values of Provisioning ES
Figure 4 illustrates an obvious decline of provisioning ES in both Doykao and Paklong villages froman overall index value of 0.921 and 0.892 in 2005 to 0.426 and 0.450 in 2014 respectively. The broom
grass was considered with a slight increase only in Paklong because villagers have gradually
maintained and planted this grass in their upland fields.
Paklong

DoykaoRice yield

Rice yield

1.000
0.800
0.600
0.400
0.200
-

Wildlife

1.000
0.800
0.600
0.400
0.200
-

TimberWildlife

BambooWild…

Firewood

Wild…

Broom grass
Bamboo…

2005

BambooWild…

Firewood

Wild…

TimberBroom grass
Bamboo…

2014

2005

2014

Fig. 4 Index values of provisioning ES of the selected communities
Index Values of Provisioning ES
Paklong

Doykao

Human

Human

Social

1.000
0.800
0.600
0.400
0.200
-

PhysicalSocialNaturalPhysicalFinancial

2005

1.000
0.800
0.600
0.400
0.200
-

2014

NaturalFinancial

2005

2014

Fig. 5 Index values within five capitals of the selected communitiesⒸ ISERD

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The results illustrated in the Figs. 4 and 5 indicate that in 2005 both studied communities had
good states of natural and human capitals but poor in financial and physical accesses, while social
assets were at average condition. By 2014, there were predominant increases in physical, financial andhuman capitals in both communities. However, natural capital was significantly decreased, while social
capital was not much changed. These results reveal that the five livelihood capitals of the selected
communities were changed in a similar direction.
Composite Index of Livelihood Security
Table 3 illustrates that composite indices of both villages were slightly increase from 0.567 and 0.579
in 2005 to 0.757 and 0.740 in 2014, respectively. In general, the results indicate that the condition of
livelihood security of the selected communities have considerably improved from “Moderate” to“Good” during the past decade.
Table 3 Composite indices of livelihood security of the selected communities
Capitals
1)
2)
3)
4)
5)

Human
NaturalFinancial
PhysicalSocialComposite index
Source: household survey, 2014

Doykao
2005
0.563
0.779
0.305
0.367
0.742
0.567

Paklong
2014
0.882
0.357
0.676
1.000
0.854
0.757

2005
0.533
0.737
0.384
0.510
0.721
0.579

2014
0.894
0.394
0.728
0.942
0.834
0.740

CONCLUSION
Results from land use change analysis and household survey reveal that land uses in both studied
communities have highly changed during the past decade. The main drivers of this change weregovernment policies together with population growth and forest fires. Land use change, specifically adecrease in forest area which is the fundamental stock of ES, has led to a dramatic degradation ofprovisioning ES. The decline of provisioning ES highly influenced the condition of natural capitalwhich also contributed to an alteration of livelihood security of the local communities. Although thestatus of livelihood security of Doykao and Paklong villages have improved from “Moderate” to“Good”, natural capitals which are mainly made of provisioning ES have dramatically declined during
2005 to 2014. By taking the trajectory of forest cover change and the importance of provisioning ES
into account, it is essential for stakeholders to integrate ES indicators into land use management
planning as well as socio-economic development to maximize benefits from natural resources to thecommunities.
ACKNOWLEDGEMENTS
The authors would like to acknowledge the International Development Research Centre of Canada andthe Southeast Asian Center for Graduate Study and Research in Agriculture (IDRC-SEARCA) for thefinancial support. We are also express a grateful thank to Saysathan district administration and its
relevant sectors as well as communities’ authorities and villagers for their cooperation and participation.

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Research article
erd

Investigation of Vibration Characteristics of a Hand Tractor
using MEMS Sensor
PHON SOVATNA*
Faculty of Agriculture, Kyushu University, Fukuoka, Japan
Email: ruasovatna@yahoo.com

EIJI INOUE
Faculty of Agriculture, Kyushu University, Fukuoka, Japan

MUNESHI MITSUOKA
Faculty of Agriculture, Kyushu University, Fukuoka, JapanZHEN LI
Faculty of Agriculture, Kyushu University, Fukuoka, Japan
Received 20 December 2015

Accepted 21 October 2016(*Corresponding Author)

Abstract The increase of agricultural mechanization, especially hand tractors has beenremarkably emerged in the last decade. It is known as well that agricultural mechanization not
only facilitated timely completion of operations but also increased production, labor savings,
energy efficiency, productivity, and profitability. With high degree of hand tractor use,
providing a safe and comfortable working environment to operators became an importantconsideration, specifically vibration that is a main cause of early fatigues. In this study focus on
measuring translational acceleration and rotational angular velocity at various locations ofhand-tractor under stationary and driving modes. Root-mean-squares (RMS) and powerspectrum-density (PSD) were used to investigate vibration magnitude and dominant frequencies,and effective measurements were finally suggested. Results showed that under stationary mode
largest vibration acceleration appeared at handgrip in vertical axis of about 8.5m/s2 followed byengine top, gearbox and chassis, respectively. In driving mode, the main vibration magnitude
occurs in vertical axis at about 11.8 m/s2. Within 50Hz frequencies, predominant acceleration
occurred in longitudinal axis at about 10Hz frequencies at first peak and about 18Hz
frequencies at next peak at engine top. Whereas, at handgrip predominant acceleration appearedhugely in vertical axis at about 10Hz frequencies, and at the same frequency was found in pitch
axis of rotational angular velocity under stationary mode. However, it appears clearly at about
9Hz frequencies in vertical axis in driving mode. Both conditions, vibration exposures are muchhigher than that in health risk limitation standard that operators should be prevented effectively;
otherwise, to suffer from early fatigue.
Keywords agricultural tools, vibration magnitude of translational acceleration and rotational
angular velocity, hand-arm vibration, and future development

INTRODUCTION
Agriculture employs almost 80% of Cambodian rural labor forces. It is considered to strongly support
Cambodian people in ensuring food security (Ngo and Chan, 2010) and constitutes a main source ofincome (Ros et al., 2011). It is the main driver of poverty reduction (Ngo and Chan, 2010), and it has a
29% contribution to the GDP (Chao, 2009; Chan, 2013).

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The enhancement of agricultural production through agricultural tools, the use of agricultural
mechanization has gradually increased, specifically over the last decade (Chan, 2013). It is evident thatthe agricultural mechanization not only facilitated timely completion of operations but also increased
production, labor savings, energy efficiency, productivity, and profitability (Singh et al., 2011). In
Cambodia; therefore, many farmers sold animals to buy mechanized tools for field operations,especially hand tractors (Chao, 2009). Multipurpose uses of mechanization meant that time operation
to hold handgrip became longer that induce to vibrated discomfort known as early fatigue. Tiwari et al.,(2006) explained that machine vibration was detrimental to agricultural users. Many researchers also
confirmed that vibration would be very harmful to health induced such as early fatigues that may cause
physical, physiological and musculoskeletal disorders after long-time exposure over months and years(Salokhe et al., 1995, Sam et al., 2006).
This study measures vibration magnitude and vibration transmissibility at various locations ofhand tractors such as engine top, chassis, gearbox and handgrip, hand-arm vibration exposure andsuggests effective intervention for future development.
METHODOLOGY
Experimental Hand Tractor
A 12Hp hand tractor as shown in Fig. 1, under stationary and driving modes in a duration of 30
seconds with the idling speed (5 km/h) was employed in these experiments using MEMS sensor.

Fig. 1 Transportation-type hand tractor
Experimental Instrumentation
A

D

engineC
gear

B

A- engine top
C- gearbox

B- chassis
D- handgrip

Fig. 2 Locations of experiment specification and MEMS sensorⒸ ISERD

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Vibration transmission measurement at various locations of hand tractor had been carried out by many
researchers, and strain gage were mostly employed for the experiments (Salokhe et al., 1995,
Taghizadeh et al., 2007). However, strain gage were complicate in manipulation such as Strain
Amplifier, Chanel-Data-Tape Recorder, Autonomous Data Acquisition Unit and Microcomputer with alimited connected cord. In a modern society; however, a MEMS sensor is very compact, light and easy
to use. So it was chosen for this study. The wireless sensor can detect signal within 50 meters, and theoutput is easy to convert and calculate (Choe et al., 2013).
Data Outputting and Processing
The characteristics of hand tractor vibration are described in RMS, PSD and dominant frequencies,
derived from output generation equations, Eq. (1) and Eq. (2). Vibration transmission is a proportion
between engine top, main source of vibration, and connecting parts.
𝑮=(𝑽−𝟏.𝟔𝟓) × 𝟗.𝟖
𝟎.𝟏𝟗

(1)

𝑽−𝟏.𝟑𝟓𝑾 = 𝟓.𝟔×𝟎.𝟎𝟎𝟎𝟔𝟕(2)

Where V: voltage output when translational acceleration and rotational angular velocity are in G
and W, respectively (Choe et al., 2013).
Root Mean Square and Power Spectrum Density
The RMS was used to obtain vibration magnitudes, and the PSD was employed using Fast Fourier
Transform (FFT) function of mathematical computation and signal processing software package toobtain frequency domain (Salokhe et al., 1995). The PSD was plotted against frequency of the signal;
therefore, the dominant frequency of vibration was received from the plot.
Hand-arm vibration exposures
A quantity of three combination axes was recommended by ANSI S2.70-2006 to evaluate hand-arm
vibration exposures as expressed in Eq. (3) and Eq. (4).
𝒂𝒉𝒘(𝒓𝒎𝒔) = √∑𝒊(𝑾𝒉𝒊 𝒂𝒉𝒊(𝒓𝒎𝒔) )𝟐(3)

𝒂𝒉𝒗(𝒓𝒎𝒔) = √𝒂𝟐𝒉𝒘𝒙 + 𝒂𝟐𝒉𝒘𝒚 + 𝒂𝟐𝒉𝒘𝒛(4)Where 𝑎ℎ𝑤(𝑟𝑚𝑠) : vibration in each direction 𝑎ℎ𝑣(𝑟𝑚𝑠) : vibration combined value, 𝑊ℎ𝑖 : correction
coefficient,𝑎ℎ𝑤𝑥 , 𝑎ℎ𝑤𝑦 , 𝑎ℎ𝑤𝑧 : each direction value.
RESULTS AND DISCUSSION
RMS of Stationary Hand Tractor
Vibration magnitudes of the 12Hp hand tractor using MEMS sensor are described in Fig. 3. It can beseen that RMS values at handgrip in vertical axis was the biggest followed by those at gearbox, engineⒸ ISERD

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top and chassis, respectively. The high vibration magnitude at handgrip in vertical axis was given that
handle acts like a cantilever beam (Salokhe et al., 1995, Bahareh et al., 2013).
At engine top, magnitude is observed higher in longitudinal axis given that it responses to thecorresponding of engine power stroke. The excitation of power stroke induces the rotating engines tovibrate in the same direction (Mehta et al., 2000). At the same location, extreme vibration signals
predominantly in roll axis. It would be reasonably that engine is the main source of vibration excitationthat vibration is movably parallel to the displacement of piston.
As engine is a main source of vibration, the relationship between engine top and other connecting
parts were observed. It revealed that engine transmitted vibration slightly to chassis of 0.4 m/s2, andgearbox of about 0.4 m/s2, but largely to handgrip 1.1 m/s2.
18

15
12
7.9

9
6

8.5
5.8

3.9

3

2.9

2.5

1.5

2.5

1.6

2.1

2.2

2.5

0

Engine top

ChasisLongitudinal

Gearbox

LateralHandgrip

Rotational velocity of angle (m/s2)

Translational acceleration (m/s2)

18

15

13.9

13.6

12
9
6

6.0

5.8
3.7

3.6

3

2.6

4.0

3.3

2.5

3.4

1.5

0

Engine top

VerticalChasisRoll

Gearbox

Pitch

HandgripYaw

Fig. 3 RMS of translational acceleration and rotational angular velocity (stationary)
RMS of Driving Hand Tractor
Figure 4 represents the RMS of translational acceleration and rotational angular velocity at idling speed.
Of the translational acceleration, peak magnitude appears in vertical axis of around 12 m/s2, and it aswell occurred hugely at roll axis of about 11 m/s2. The predominant vibration may be caused bycantilever beam the hand tractor acts (Salokhe et al., 1995, Bahareh et al., 2013).
18

11.8

12
8.8

9
6

5.5

3

Translational acceleration (m/s2)

Translational acceleration (m/s2)

18

15

15

12

0

11.1

10.2

9
6.1

6
3

0

Longitudinal

LateralVertical

Roll

Pitch

Fig. 4 RMS of driving hand tractor at handgripⒸ ISERD

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Power Spectrum Density at Stationary and Driving Modes

3,000

3,000

2,500
2,000
1,500

10 Hz,
Longitudinal

1,000
500
0
0

10

20

30

40

50

PSD of translational acc. (N2/Hz)

PSD of translational acc. (N2/Hz)

The results of PSD on the engine top and handgrip were partly represented in Figs. 5 and 6. The
sensitivity vibration at 2, 5 or 20Hz may cause severe discomfort or injury but will not produce thenausea, vomiting and color changes so characteristic of motion sickness (M. J. Griffin, 1990).
It is seen in stationary condition that predominant magnitude at the engine top occurred largely atabout 10Hz frequencies in longitudinal axis while at about 11Hz frequencies dominantly emerged athandgrip in vertical axis. These may be due to the corresponding to the movement of engine piston andmovement of cantilever beam that the handle acts (Salokhe et al., 1995).

2,000
1,500

1,000
500

0
0

Frequency (Hz)Longitudinal

Lateral

11 Hz
Vertical

2,500

10

Vertical

20

Longitudinal

Fig.5 PSD at engine top (stationary)30

Lateral40
50Frequency (Hz)Vertical

Fig.6 PSD at handgrip (stationary)In driving mode, dominant frequency is found at about 3Hz frequencies first in longitudinal axis
and about 9Hz frequencies next in vertical axis. The first frequencies would cause by movement ofengine piston and the second peak would cause by cantilever beam that these results also confirmed by
Salokhe (1995) and Bahareh et al., (2013).
PSD of translational acc.(N2/Hz )

700
600

9Hz
Vertical

500
400
300
200
100

0
0

10

20

30

40

50

Frequency (Hz)Longitudinal

LateralVerticalFig. 7 PSD at handgrip (driving)
Hand-arm Vibration Exposures
The hand-arm vibration exposures were conducted based on RMS of engine vibration magnitude under
hand-gripped modes to observe the severity of vibration from hand tractor to the operators, and apicked up frequencies were experimentally needed to compute exposure.

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Results appeared that in stationary and driving modes the RMS of hand-arm vibration exposures
were extremely higher than those stated in health guidance zone. This means that operators shall betechnically advised to stop their operation; otherwise, it would be longer-sooner risky to health.
1817.1 m/s2

15
12

10.4 m/s2

9.9 m/s2

96

30Free handle-gripped

handle-gripped

Hand-arm vibration

RMS of vibration magnitude (m/s2)

Root-Mean-Squares (m/s2)

18

15.7 m/s2

15
12.1 m/s2
12
9
6
3

0

handgripped

hand-arm vibration

Fig.8 RMS of hand-arm vibration exposure in stationary and driving modes

Fig.9 Health Guidance Zones (Sayed M.E. et al., 2012)
Future Development
To prevent from health risky, an effective interventions such as isolator dampening sleeves, splitting
handle arm installed on some locations in between engine and base frame and between handle andgearbox. Some researchers applied successfully with isolators dampening sleeves, splitting handle arm
on some locations (Chavan et al., 2013, Charturvedi et al., 2012).
CONCLUSION
The demand to improve agricultural production through enhancing agricultural mechanization was
important for country development, Cambodia. However, with multipurpose uses of mechanization,
especially hand tractors, long-time operation would cause discomfort to operator through handgrip
vibration. Experiment results showed that the large vibration occurred at the handgrips in vertical axes.
The RMS of hand-arm vibrations exposure at the handgrip of the 12Hp hand tractor were much higher
than that in health risk limitation standard. Therefore effective intervention should be developed toprevent operator’s health.

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ACKNOWLEDGEMENTSFirst, I thank to the Japanese Grand Aid for Human Resource Development Scholarship Program (JDS)
and Coordinators and Royal Government of Cambodia, who have supported me so far. Second, myprofound appreciation extends to my professors, who have supervised, encouraged, and inspired me somuch through experimental research and good opportunities in Japan. Third, my warm appreciation
goes to all lab-mates and friends for their assistance and for together sharing our knowledge andexperience. Finally, I pay gratitude to my host family and wonderful family.
REFERENCES
Bahareh, H., Seyed, R.H. and Barat, G. 2013. Investigating a power tiller vibration transmissibility using dieselbiodiesel fuel blends on stationary con. 3 (10), 877-884.
Chan, S. 2013. Cam perspective on rice production and mech. in Cambodia. Dept. of Agri. Eng.
Chao, L. 2009. Agri.al mach. and agri. dev. strategies in Cambodia, submitted to the 5th session of the technicalcommittee of UNAPCAEM, 14-15 October 2009, Los Banos, Philippines.
Choe, J.S., Mitsuoka, M. and Inoue, E. 2013. Measuring inclination angle of semi–crawler tractors using MEMS
sensor. Journal of the Faculty of Agriculture, Kyushu University, 58 (1), 79-85.
Charturvedi, V., Kumar, A. and Singh, J.K. 2012. Power tiller, Vibration magnitudes and intervention
development for vibration reduction. 43, 891-901.
Chavan, V.S., Sanap, S.B. and Askhedkar, R. 2013. Analysis of anti-vibration mounts for vibration isolation indiesel engine generator set. In’t Journal of Engg Res and App (IJERA), 3 (3), 1423-1428.
Mehta, C.R., Shyam, M., Singh, P. and Verma, R.N. 2000. Ride vibration on tractor-implement system. Appliedergonomics, 31 (3), 323-328.
Griffin, M.J. 1990. Handbook of human vibration. Human Factors Research Unit, Institute of Sound andVibration Research, The University, Southampton, UK.
Ngo, S. and Chan, S., 2010. Agri. sec financing and serv. for small hold farm. MAFF and MOWRAM. Phnom
Penh, Cambodia.
Ros, B. et al. 2011. Agri.l development and climate change, A case in Cambodia. 65, CDRI, Cambodia.
Salokhe, V.M., Majumdar, B. and Islam, M.S. 1995. Vibration characteristics of a power tiller. Journal of
Terramechanics, 32 (4), 181-197.
Sam, B. and Kathirvel. K. 2006. Vib. Chara. walking and riding type power tillers. Biosys Eng, 95 (4), 517–528.
Sayed, M.E., Habashy, S. and Adawy, M.E. 2012. Evaluation of whole-body-vibration exposure to Cairo Subway(Metro) passengers. In’t Journal of Computer App (0975-8887), 55, No.8.
Singh, T.V., Kumar, R.M. and Viraktamath, B.C. 2011. Selective mech. in rice cultivation for energy saving andenhancing profitability. Rice Knowledge Management Portal (RKMP). India.
Taghizadeh, A. et al. 2007. Evaluation of vibration in power tiller on the asphalt surface. Asian Association for
Agricultural Engineering.
Tiwari, P.S. and Gite, L.P. 2006. Evaluation of work-rest schedules during operation of a rotary power tiller.
International Journal of Industrial Ergonomics, 36, 203-201.

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Research article
erd

Policy Analysis for Biodiversity Conservation in Cambodia:
The Protected Areas System
SOALY CHAN*
General Secretariat of National Council for Sustainable Development/
Ministry of Environment, Cambodia
Email: somalychan.ca@gmail.com
Received 1 January 2016

Accepted 21 October 2016(*Corresponding Author)

Abstract The Government of Cambodia recognizes the importance of biodiversity
conservation. Following broad consultation and collaboration with stakeholders, it has creatednational policies and legislation for environmental and natural resources management over the
next decade and also to compliance with country’s obligations under relevant international
treaties and conventions. This paper sets out the existing national environmental and natural
resources management’s policies and legislation, focusing on the protected areas systemmanagement in Cambodia. The specific objective is to analyze policy gaps in biodiversity andnatural resources conservation; and assess its’ effectiveness implementation. There are threephases in the assessment process: 1) gathering, listing and reviewing existing policies andlegislations to highlight the significant contents in competences to natural resources
conservation and management; 2) analyzing and identifying content gaps and opportunities toimplement “Protected Areas Law” and relevant legislation in contribute to biodiversity
management; 3) reviewing and examining national legislations, the provisions reflect on
Cambodia’s obligations under the UN Convention on Biological Diversity. Among 9 specificlaws and some relevant policies and strategic plan there is approximate one third are found they
have specific provisions related to biodiversity management and relevant to the protected areas
system management. The analysis of “Protected Areas Law” shown a significant gap forunmanageable of protected areas that are not designated by Royal Decree on 1 November 1993
and neither financial mechanism nor guideline for zoning identification and management. The
analysis showed that lack of specific policy on biodiversity management lead to challenges forsustainable use of natural resources with no return monitory benefits from ecosystem services.
In conclusion, this paper will present opinions and recommendations to address policy gaps andenhance the implementation of existing laws.
Keywords policy, analysis, biodiversity, conservation, Cambodia

INTRODUCTION
Biodiversity is referred to the variability living organisms from all course including, inter alia,
terrestrial, marine and other aquatic ecosystems and the ecological complexes of which they are part;
this including diversity within species, between species and ecosystem (CBD, 1992). It has beenrecognized as an important and essential asset that significantly contributes into national and global
economics. According to Sukhdev et al (2014), around 70% of the world’s poor live in rural areas
satisfy as much as 90% of their needs from biodiversity and its services such as food, fuel, medicine,
shelter, and income generation. However, the global population growth increases demand of natural
resources for improved living condition and development. The destruction of biodiversity and natural
resources including habitat loss and degradation of ecosystem are among key global concerned. Likeelsewhere, Cambodia depends mainly on rich natural resources and biodiversity for its socio-economic
development that cause many challenges for country biodiversity conservation. Aware of theseⒸ ISERD

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challenges and the biodiversity’s values, the Royal Government of Cambodia (RGC) has been engaged
in establishing Protected Areas Systems (PAS) including 23 Protected Areas, 6 Forest Protection, and 8
Fish Sanctuary, aim to conserve, protect, and manage of natural resources, biodiversity, and its
components for sustainable use, along with introduced various national policies and legislations to
support and guide responsible institutions.
OBJECTIVE
This paper aims to analyze the existing national policies and legislations relevant to biodiversity
conservation within the protected areas system in Cambodia in order to identify opportunity, gap andoverleaping areas. Based on key findings, various recommendations are proposed to bridge the gap
between policy and practice, reduce overlapping and overcome policy challenges.
METHODOLOGYThis study has collected relevant policies and legislations including Cambodian Rectangular Strategy;
Sectoral Policies such as land, forest, and fisheries; and existing laws. The review process focus oncontent, purpose and objective of those legislations, while analyzed process examine the most relevant
provisions and articles of Protected Areas Law that articulate on Natural resources management andBiodiversity Conservation in Cambodia in line with the program of work and strategic objective of the
UN Convention on Biological Diversity (UN-CBD). The final analysis focuses on opportunity,
overlapping, and gaps of Biodiversity Conservation. However, this paper mainly reviews on three
specific policies: a protected area law, law on forestry, and law on fisheries, in with details on Protected
Areas Law. The analysis has focus on three aspects: structure and provisions on natural conservation,
implementation and compliance measure, and financial mechanism provision.
RESULTS AND DISCUSSION
The RGC tries to implement a coordinated set of laws, programs, action plans, and institutionalarrangements regarding natural resources which are directed toward enabling the achievement of
national goals of environmental protection, biodiversity conservation, poverty reduction, socioeconomic development, and good governance, as described in table 1 on National Policies. The RGC
sets national goals directed to the sustainable development of the Nation that provides the overall
development framework for the conservation and management of Cambodian natural resources, andconsiders the ecologically, socially and economically viable conservation and management of
biological resources as a major pillar for public welfare directly contributing to environmental
protection, poverty reduction and socio-economic development.
Overview of National Policy and Legislation
This section describes overview of national policy, law, and strategic plan that are relevant to natural
resources and biodiversity conservation in Cambodia.
National Policy
This study selected only 5 policies on land, forestry, and fisheries to review in the context of
biodiversity conservation for sustainable management. Land Policy (2001) has objective to ensure
management, protection and use of land and natural resources with transparency and efficiency in orderⒸ ISERD

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to preserve environmental sustainability and equitable socio-economic development in rural and urban
areas as well as to prevent disputes over land use by regulating land development, land conversion,
land readjustment, construction, and resettlement. While National Forest Sector Policy (2002) provides
mandate to the Forestry Administration (FA) of Ministry of Agriculture Forestry and Fisheries(MAFF) to conserve and manage forest resource with five objectives to conserve and sustainable
manage of the country’s forest resources for sustainable social-economic development; to consider
remaining forest resources as Permanent Forest Estate; to engage private sector and local population toensure food security, poverty reduction and socio-economic development; to coordinate multistakeholder to enable the harmonization of the different perceptions, interests and objectives of thevarious forest interest groups; and to support forestation of arable land and to protect those trees for thedevelopment of forest resources. To achieve the objective of Forest Sector Policy, MAFF hasdeveloped a long term National Forest Programme 2010-2029 (NFP, 2010) that aims to attainsustainable forest management and reduce poverty in the country with specific objectives and goals ofenvironmental protection, biodiversity conservation, economic development and good governance. The
programme has identifies the four tasks on forest resources conservation, good governance, social
economic development, and poverty reduction, that need to achieve by 2029. Furthermore, Fisheries
sector also developed 20 years Strategic Planning Framework for Fisheries 2010-2029 (SPF, 2010) to
guide Fisheries Administrative in effective implementing the National Strategic Development Plan,
and compliance with the Law on Fisheries.
Table 1 National Policy related to Biodiversity Conservation
Date
2001
2002

2010

2010

PolicyThe Declaration on Land Policy
Focuses on three sub-sectors: land administration, land management, and land distribution, underresponsible of Ministry of Land Management, Urban Planning and Construction (MoLMUPC)
National Forest Sector Policy
To conserve and sustainable manage of the country’s forest resources for sustainable socialeconomic development and to ensure that the management and exploitation of forests generates
benefits for government entities, local communities, the private sector and individuals.
National Forest Programme (NFP) 2010-2029
NFP is developed to replace and implement National Forest Sector Policy. It identifies REDD+ as
important source of sustainable forest financing in targeting to register 1,000 community forestry
groups nationally, and for community forest programmes to cover 2.0 million hectares by 2030.
The Strategic Planning Framework for Fisheries: 2010-2019
To support the achievement of Cambodia’s MDG and implement National Strategic Development
Plan with compliance with Law on Fisheries to be benefit of the Cambodian people.

National Law related to Natural Resource Conservation
Cambodia has adopted a number of laws to support natural resources management in which thesepolicies are directly and indirectly used to manage Protected Area System. Nine relevant laws related
to Biodiversity conservation and protected areas management has been selected to review and descriptin this section. However, only three laws (Protected Area Law, Law on Forestry, and Law oh Fisheries)
are directly responded to protected areas system management and establishment of conservation
communities as shown in table 2. The “Law on Environmental Protection and Natural Resource
Management” of 1996 (LEPNRM, 1996) intends to protect and promote environmental quality andpublic health through the prevention, reduction, and control of pollution, to assess the environmental
impacts of all proposed projects prior to the issuance of the decision by the Royal Government, toensure the rational and sustainable conservation, development, management, and use of the natural
resources, to encourage and enable the public to participate in environmental protection and naturalⒸ ISERD

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resource management, and to suppress any acts that cause harm to the environment. The objective of
the “Land law” 2001 (LL, 2001) is to determine the regime of ownership for immovable properties in
the Kingdom of Cambodia for the purpose of guaranteeing the rights of ownership and other rights
related to immovable property, according to the provisions of the 1993 Constitution of the Kingdom of
Cambodia. This law provides legal basis to government institutions to manage state land such asprotected areas, public land, and community land. The “Law on Water Resources Management” 2007
(LWRM, 2007) emphasize management and development of water and water resources based on an
integrated water resources management (IWRM), in which requires to coordinated multi-sectoral water
use planning including the need for conservation of biodiversity and ecosystems. Article 23 of this law
authorizes the Ministry of Water Resources and Meteorology (MOWRM) to declare any watershed asa protected "water use" zone if it is prone to degradation by human activities or natural factors. Besides,“Law on Biosafety” 2008 (LBS, 2008) has been developed in 5 years after Cambodia become a party of
the Cartagena Protocol on Biosafety. The purpose of the law is to respond with Cambodia’s obligationand commitment to implement the Biosafety protocol of the Convention on Biological Diversity that
Cambodia becomes a party in 1995. This law aims to prevent adverse impact on the conservation of
biodiversity and natural resources caused by the trans-boundary movement, development, handling,transfer, use, storage, and release of living modified organisms resulting from modern biotechnology;
and ensure effective conservation of biodiversity and sustainable use of biological resources, taking
also into account risks to human health. At the same year RGC also adopted “Law on Seed
Management and Plant Breeder’s Right” (LSMPBR, 2008) that serves as legal instrument to manage
and control the breeding, release for use, production, processing, registration, distribution, import andexport of seeds. This law has objectives to protect new plant varieties, to secure the management andsustainable development of varieties, and to encourage the development thereof for social, economic,
and environmental benefits. One year later, the RGC endorsed “Law on Tourism” 2009 (LT, 2009) toallow the Ministry of Tourism (MOT) to govern the tourism sector in a sustainable manner for poverty
reduction. This law aims to protect and conserve the natural resources, culture and customs, which
serve as the foundation of the tourism sector, with its optimal benefits (Article 2).
In addition to the above laws, three specific laws are directly defended legal framework for
Biodiversity Conservation within Protected Area System in Cambodia. The “Law on Forestry” 2002
(LF, 2002) defines framework for management, harvesting, use, development and conservation of theForests in the Kingdom of Cambodia. The objective of this law is to ensure sustainable management ofthese forests for their social, economic, and environmental benefit, including conservation biologicaldiversity and cultural heritage. The “Law on Fisheries” 2006 (LFi, 2006) aims to ensures fisheries andfishery resource management, enhance aquaculture development, the management of production andprocessing, and to promote the livelihood of people in local communities for the social-economic andenvironmental benefits, including the sustainability of the conservation of biodiversity and natural
culture heritages. The “Protected Area Law” 2008 (PAL, 2008) defines the framework of management,
conservation and development of protected areas to ensure the management, conservation of
biodiversity, and sustainable use of natural resources in protected areas.
National Strategy
The National Strategic Development Plan and its Update 2009-2013 (NSDP, 2010) contains policy
priorities that support the establishment of protected areas and protected forests with the objectives toconserve biodiversity and improve the livelihoods of people living in rural areas and contribute toeconomic growth. It covers all aspects of sustainable development, including chapters on enhancementof the agricultural sector for improving agricultural productivity and diversification. While National
Strategic Development Plan 2014-2018 has been formulated for implementing the Rectangular
Strategy Phase III (RS, Phase III, 2010): Growth, Employment, Equity, & Efficiency, to ensure
development sustainability and poverty reduction and sustainable management of natural resources,Ⓒ ISERD

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Cambodia Climate Change Strategic Plan 2014-2023 (CCCSP, 2013) is a continuation of national
policy response, in providing a framework for climate change responses and guiding the transition to
low-carbon and climate resilient development. It supports national preparedness in responding toclimate risks and disaster management, and in capitalizing on emerging opportunities such as green
growth, mobilizing climate funds from bilateral and multilateral sources, and enhancing effective
participation in international dialogues and negotiations on climate change, and biodiversity. National
Biodiversity Strategy and Action Plan (NBSAP, 2015) sets its vision to use, protect and manage
biodiversity for sustainable development in Cambodia. To ensure this, biodiversity issues and values
are mainstreamed in national development and sectoral policies, plans and programmes; biodiversity,
our natural capital, is protected by reducing the various direct and indirect pressures causing its loss ordegradation, and is used wisely so as to enhance the benefits from it to the people of Cambodia,
particularly in rural areas; and the enabling environment for effective and efficient implementation ofthis mission is strengthened.
Policy Analysis: Protected Areas Law
The Protected Areas Law established by Royal Decree dated on 15 February 2008, defined the
management, conservation, and establishment of new and existing protected areas, which identified in
Royal Decree of 1 November 1993. This law composed of 11 chapters with the objective to ensure themanagement, conservation of biodiversity, and sustainable use of natural resources in protected areas.
Article 2 of this law sets scope of application in protected areas defined by the provisions of the Law
on Environmental Protection and Natural Resources Management, which was promulgated by Royal
Decree No NS/RKM/1296/36 of December 24, 1996, Royal Decree on the Establishment and
Designation of Protected Areas of November 01, 1993, Royal Decree on the Establishment andManagement of Boeung Tonle Sap Biosphere reserve No NS/RKT/0401/070 of April 10, 2001, andother relevant standard documents. Chapter II has defined responsibility of the Ministry ofEnvironment (MoE) for management of protected areas with full participation from local communities,
indigenous ethnic minorities and the public to participate in the decision-making on the sustainable
management and conservation of biodiversity. This law provides legal framework and opportunity toconserve and manage biodiversity resources in line with Cambodia obligation to implement UN
Convention on Biological Diversity (UN-CBD) and its protocol. Article 5, 6, and 38 sets the rights andduties of MoE to monitor national resource of all kinds in the protected areas including the right tocontrol export and import of wild flora and fauna, seeds and samples, cross-breeding of wild species orfish of all species from/into the protected areas based on scientific research. These articles are mostly
relevant to the control measures set in Nagoya Protocol on access and benefits sharing of the UN-CBD,
and MoE duty to develop strategic plans, action plans, and technical guidelines for managing theprotected areas. Article 9 & 10 states that RGC may establish provincial/municipal protected areas andmodify any protected area that already designate as world or regional heritage site shall be comply withnational legislations to ensure its management and conservation consistent with procedures andrelevant regulations. The article 15, 16 and 19 determines the needs for development of national
strategic and action plan (NSAP) for protected area management with introduce the process andinstruction for NSAP. Article 22 recognizes and secures access to traditional uses, local customs,
beliefs, and religions of the local communities, and indigenous ethnic minority groups residing within
and adjacent to the protected areas and allow to Access to traditional uses of natural resources andcustomary practices on family scale within sustainable use zone and conservation zone subject toguidelines. This article responds to the implementation of article 8(j) of the UN-CBD. Articles 32, 33,& 34 define the establishment of “Protected Area Trust Fund”, the sources for this fund, and the use offund to support activates. Chapter 10 defines procedure and mechanism on penalties of natural resource
offenses. However, the procedure for penalties in this law is not capturing all forest offenses, so thatneed for using provisions of law of forestry to complain at the court in some cases.
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Provisional Gap of Protected Area Law
Although Protected Area Law has many strength provisions, it is still some gaps to achieve the goal fornatural resources management and biodiversity conservation for sustainable development. Those gaps
are described in table 2.
Besides provision gaps in PA Law, there is policy gap such as no environmental policy, nobiodiversity policy/law that limit functions of responsible institution in biodiversity conservation andbenefits values of biodiversity and its ecosystem for social economic development.
Table 2 Provision Gap Analysis of PA Law
Provision
Article 2
Article 11
Article 12
Article 16
Article 19
Article 25
Article 41

Gap Description
This Law has a scope of application in 23 Royal Decree on 1 November 1993 only. However,Protected Area System includes Forest Protection, Fish Sanctuary and Community Conserve
Area that should cover by this law.
Identify 4 zoning for PA management, but it does not include cultural and heritage zone under
Apsara authorities.
Set only criteria for zoning identification, not introduce procedure and guideline.
No guideline or mechanism for implementing National PA Strategic Management Plan.
No financial mechanism to implement action plan.
This law not covers any part of Community PA outside PA boundary.
Missing to include rare, endangered species, and threaten species in the prohibited practices
considered destructive and harmful.

Overlap responsibility of Protected Area Law with Laws on Forestry and Fisheries
The RGC has endorsed sectoral laws: PA Law,
Law on Forestry, Law on Fisheries, Land Law,
and Law on Water Resources Management todirect and indirect manage and conserve natural
Law onPA Law
resources for sustainable development. These laws
ForestryMOEcreate overlapping responsibilities among
MAFF
Naturalgovernment sectors for natural resource
Resource
management (Fig. 1).
Management
PA Law aims to manage and conserve
biodiversity within the 23 Protected Areas underLaw onjurisdiction of MOE, while MAFF has responsible
Fisheries
to biodiversity conservation outside the PA. The
MAFF
conservation of biodiversity within Forest
Protected is under jurisdiction of FA and within
Fish Sanctuary is under jurisdiction of Fisheries
Fig 1. Overlapping Areas of PAL, LF, & LFi
Administration. Moreover, Law on Forestry
emphasized that the areas of Forest Protection and all kind wildlife species are under the management,
research and conservation of the Forestry Administration, except for fish and animal that breed inwater. Chapter 4, Chapters 5 and 6 in the 2006 Law on Fisheries present approaches to protect andconserve fisheries in inland and marine waters, in general, and more specifically in inundated forestsand mangrove forests as shown in Table 3. Overlapping jurisdictions among key ministries for such as
MoE, MAFF, MOWRM, and Ministry of Land Management, Urban Planning and Construction(MLMUPC), have often led to ambiguity as to which ministry has the key role in managing which
resources.

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Table 3 Comparison Protected Area Law with Laws on Forestry and fisheries
PolicyInstituteOverlapping Responsibility

PA LawMOE

Law onForestry

MAFF

Law onFisheries

MAFF

Management, conservation and development of protected areas to ensure themanagement & conservation of biodiversity & natural resources for sustainable use.
Management, harvesting, use, development and conservation of the forests toensure the sustainable management of forests for social, economic andenvironmental benefits, including conservation of biological diversity and cultural
heritage.
Ensures fisheries and fishery resource management, enhance aquaculture
development, the management of production and processing, and to promote thelivelihood of people in local communities for the social-economic andenvironmental benefits, including the sustainability of the conservation of
biodiversity and natural culture heritages.

CONCLUSION
In general, there are many national policy and legislations established by RGC for manage andconserve of biodiversity within or outside the protected areas system. However, based on this study,
the results showed that almost sectorial policy and law are developing in ad hoc based on individual
sectors and institutional circumstance. Almost all of sectorial laws are excluded financial mechanism
and implementation measure, and resources needs. This gap limits law enforcement and participationfrom all relevant stakeholders. Learning from the gap finding, it appears that there is a need forestablishment and strengthen of coordination mechanism, mobilize adequate resources, and enhancecapacity to review and amend some laws to be coherence, consistent, and clear mandate for individual
institution. To achieve biodiversity conservation, the national biodiversity policy and laws should beestablished as urgent needs. Fortunately, in February 2016, Prime Minister announce on jurisdiction
reform to give mandate to MoE in environmental protection within PAS including 23 Protected Areas(PAs) and MAFF has responsible for production forest and Economics Land Concession (ELC) areas,and protection and management of fisheries. Therefore, soon sectorial policies have been amendment
within this new reform.
ACKNOWLEDGEMENTS
The author would like to thank the General Secretariat of National Council for Sustainable
Development of Ministry of Environment for encouraging and providing legal documents for thisstudy. Also thanks to colleagues from Biodiversity Department for their supports in collecting
information/data to conduct this study. Finally, the author would like to give sincere thanks to Prof. Dr.
Machito MIHARA, Institute of Environmental Rehabilitation and Conservation / Tokyo University ofAgriculture, for his support and professional guidance on this paper.
REFERENCES
Ministry of Agriculture, Forestry and Fisheries. 2002. Law on forestry. Ministry of Agriculture, Forestry and
Fisheries, Cambodia.
Ministry of Agriculture, Forestry and Fisheries. 2002. National forest sector policy. Ministry of Agriculture,
Forestry and Fisheries, Cambodia.
Ministry of Agriculture, Forestry and Fisheries. 2006. Law on fishery. Ministry of Agriculture, Forestry and
Fisheries, Cambodia.
Ministry of Agriculture, Forestry and Fisheries. 2008. Law on seed management and plant breeder’s right.
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Ministry of Agriculture, Forestry and Fisheries, Cambodia.
Ministry of Agriculture, Forestry and Fisheries. 2010. National forest program, Ministry of Agriculture, Forestry
and Fisheries, Cambodia. (ttp://www.4cmr.group.cam.ac.uk/filecab/redd-law-project)
Ministry of Agriculture, Forestry and Fisheries. 2010. National strategic planning for fisheries 2010-2029. FiA,
Ministry of Agriculture, Forestry and Fisheries, Cambodia.
Ministry of Environment. 1996. Law on environmental protection and natural resource management. Ministry ofEnvironment, Cambodia.
Ministry of Environment . 2008. Law on biosafety. Ministry of Environment, Cambodia.
Ministry of Environment. 2008. Protected area law. Ministry of Environment, Cambodia.
Ministry of Environment. 2010. The rectangular strategy phase III. Ministry of Environment, Cambodia.
Ministry of Environment. 2010. National strategic development plan, update 2009-2013. Chapter IV. Ministry ofEnvironment, Cambodia.
Ministry of Environment. 2013. The Cambodia climate change strategic plan. Ministry of Environment,
Cambodia.
Ministry of Environment. 2014. The national protected areas system strategic management framework. P.1.
Ministry of Environment, Cambodia.
Ministry of Environment. 2015. The national biodiversity strategic and action plan. Ministry of Environment,
Cambodia.
Ministry of Land Management, Urban Planning and Construction. 2001. Land policy. Ministry of Land
Management, Urban Planning and Construction, Cambodia.
Ministry of Land Management, Urban Planning and Construction. 2001. Land law. Ministry of Land
Management, Urban Planning and Construction, Cambodia.
Ministry of Tourism. 2009. Law on tourism. Ministry of Tourism, Cambodia.
Ministry of Water Recourses and Meteorology. 2007. Law on water resources management. Ministry of Water
Recourses and Meteorology, Cambodia.
Sukhdev, P., Wittmer, H., and Miller, D. 2014. The economics of ecosystems and biodiversity (TEEB),
Challenges and responses, In D. Helm and C. Hepburn (eds), Nature in the Balance: The Economics ofBiodiversity. Oxford: Oxford University Press.
The Cambodian National Sustainable Development Strategy. 2009.
The Convention on Biological Diversity (CBD). 1992. The Article 2, Use of term on biological diversity. CBD.

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Research article
erd

Peanut Yield and Changes of Soil properties by Intercroppingin Upland Cropping Systems of Southeast Cambodia
TARA PIN*
University of Heng Samrin Thbongkhmum, Thbongkhmum, Cambodia
Email: pintara30@gmail.com

KONGKEA PHAN
Faculty of Science and Technology, International University, Phnom Penh, Cambodia

VANNARO PIN
University of Heng Samrin Thbongkhmum, Thbongkhmum, Cambodia

OEUN HORN
Faculty of Agriculture, Chea Sim University of Kamchaymear, Cambodia

JOHN M. SCHILLER
School of Agriculture and Food Sciences, University of Queensland, Australia
Received 21 December 2015

Accepted 21 October 2016(*Corresponding Author)

Abstract Successive monocropping with cassava in upland areas of Cambodia has led to a
progressive decline in soil fertility. The aim of the present study was to investigate the changeof soil properties and examine the growth and yield of peanut in intercropping cultivation in the
upland cropping systems of Cambodia. Seven intercropping treatments were studied: T1(cassava + mungbean + fertilizer rotation with fallowing); T2 (cassava + peanut + fertilizer
rotation with fallowing); T3 (cassava + fertilizer rotation with fallowing); T4 (cassava + no
fertilizer); T5 (mungbean + fertilizer rotation with cassava + mungbean + no fertilizer); T6(peanut + fertilizer rotation with cassava + peanut + no fertilizer) and T7 (stylo + fertilizer
rotation with cassava + no fertilizer) were designed and conducted in the fields of farmers in
Prey Veng and Svay Rieng provinces. Field data indicated that peanut yield increased in theorder of: T2 > T7 > T1 > T6 > T5 > T3 > T4. Analysis revealed there were significant
differences in peanut yield among all seven treatments, with the yield of T4 being significantly
lower than that of T2 and T7. The mean of the peanut yields were greater than 2.1t h-1 for all
treatments. The total N, K and phosphate of the pre-treatment analysis did not significantly
differ from those of the post-treatment analysis. This study suggests that intercropping
cultivation could provide a sustainable harvestable yield of peanut in the upland cropping
system in Cambodia.
Keywords peanut, intercropping, upland cropping system, Cambodia

INTRODUCTION
The challenges of farmers in improving upland farming systems in Cambodia were identified, in whichsoil fertility was one of the main challenges in agricultural production systems in Cambodia (Chan etal., 2009). Soil factors affecting crop suitability for upland crops in Cambodia have been documented(Seng et al., 2009). Previous studies revealed that upland areas are widespread throughout Cambodia,
thus there was a considerable scope in developing upland crops and cropping technologies in
Cambodia (Seng et al., 2011). The continuous mono-cropping particularly with cassava in upland areasⒸ ISERD

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has led to a progressive decline in soil fertility. There is an urgent need to identify alternative
agricultural production options capable of economically improving both the soils and production, whileat the same time improve the incomes of rural households, which are almost 100% dependent on
agriculture. Important upland crops in Cambodia are maize, rubber, soybean, mungbean, cassava,
sesame, peanut and sugarcane (Bell et al. 2005). Inter-cropping is one of the options available for moresustainable agricultural production systems. Most farmers in the provinces of Prey Veng and Svay
Rieng have tried to intensify agricultural production through mono-cropping of cassava, reflecting thehigh demand for this crop in commercial markets. However, this cropping intensification has been
done with little knowledge of procedures or technologies for maintaining soil fertility.
Some farmers have reported that soil fertility shown a significant decline in areas with a history of
cassava cropping because smallholder producers like them are unable to afford commercial fertilizers
to replace the nutrients removed by successive cassava cultivation. In this study, a number of different‘systems of production’ are being evaluated on the Prey Khmer soils in Prey Veng and Svay Rieng
provinces. Crop growth and yield performance, together with issues of soil fertility sustainability, fromdifferent combinations of maize and cassava with selected legumes were investigated.
OBJECTIVE
The objectives of the present study are to (1) examine growth and yield of peanut in intercropping
cultivation in the upland cropping system of Cambodia and (2) investigate the changes in soil chemicaland physical properties after intercropping cultivation.
METHODOLOGYThis study was carried out in Prey Veng and Svay Rieng provinces which are located in theSoutheastern Cambodia (Fig. 1). Prey Veng is located on the east bank of the Mekong River and is oneof the largest rice producing regions in Cambodia and other crops while Svay Rieng is located on
Cambodia’s South-Eastern border with Vietnam, 125km from Phnom Penh capital.

Fig. 1 Map of the study areasⒸ ISERD

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Field trials of intercropping cultivation of peanut were conducted in eight basic production
systems (7m × 10m) of farmers in the study areas of Prey Veng (n = 4) and Svay Rieng (n = 4)
provinces. The detailed design of field trials is presented in Table 1. The plant height (cm), weight perhill (g), number of fruit per hill, grain weight per 100 seeds (g), peanut yield per hectare (t h-1) were
determined. Concurrently, soil samples were collected before and after each treatment, to determine
soil properties and the changes in total C, organic C, N, P2O5, Ca, Mg, Na, K and exchangeable acidity(pHKCl) and actual acidity (pHH2O).
Table 1 Summary of intercropping of peanut cultivation in the upland cropping system inPrey Veng and Svay Rieng provinces
Treatment
T1
T2
T3
T4
T5
T6
T7

2014
EWS
CS+MB+F
CS+PN+F
CS+F
CS-F
MB+F
PN+F
Stylo+F

2015
LWS
–
–
–
–
CS+MB-F
CS+PN-F
CS-F

EWS
PN+F
PN+F
PN+F
PN+F
PN+F
PN+F
PN+F

LWS
–
–
–
–
–
–
–

EWS, early wet season; LWS, late wet season; MZ, maize; SB, soybean; MB, mung bean; CS, cassava; PN, peanut;+F, fertilizer application; -F, No fertilizer application

All statistical data analyses were employed using SPSS for Windows (Version 16.0). One-way
ANOVA test was applied to verify the differences in plant height, weight per hill, number of fruit perhill, peanut yield among all treatments. Paired samples t testing was performed to certify thedifferences in soil pH, total C, organic C, total N, P2O5, K, Ca, Mg and Na between pre-treatment andpost-treatment of each treatment. Significance is considered in a circumstance where p < 0.05.
RESULTS AND DISCUSSION
Peanut Yield
A summary of growth and yield of intercropping cultivation of peanut are presented in Table 2. The
comparisons revealed that there were no significant difference in plant height at flowering andharvesting stages among all treatments (One-way ANOVA, p > 0.05). However, there were significant
differences in weight per hill of peanut among all treatment (One-way ANOVA, p < 0.05). The weight
per hill of T2 was significantly higher than that of T3, T4, T5 and T6 using post hoc Tukey HSD test (p< 0.05). Likewise, the number of fruit per hill significantly differed among all treatments (One-way
ANOVA, p < 0.05). The post hoc Tukey HSD test revealed that number of fruit per hill of T2 wassignificantly greater than that of T3, T4, T5 and T6 (p < 0.05). Grain weights per 100 seeds weresignificantly different among all treatment (One-way ANOVA, p < 0.05). A previous study on fieldcrop productivity in relation to soil properties revealed that peanut was the most reliable crop withsuccessful establishment in the early wet season and harvestable yield at 80% of sites (Seng et al.,2011). The present study showed that peanut yield increased in an order of T2 > T7 > T1 > T6 > T5 >T3 > T4. A comparison revealed that there were significant differences in peanut yield among all
treatments (One-way ANOVA, F (6, 49) = 3.18, p = 0.01). Post hoc Tukey HSD test indicated that
peanut yield of T4 was significantly lower than that of T2 and T7 (p < 0.05). According to Seng et al(2011), peanut yield was between 2.1 to 3.4t h-1 on Kampong Siem soils. Peanut yield of the presentⒸ ISERD

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study (Table 2) was comparable to that of Kampong Siem soil. Peanut yield varied with site and season
in which about 43% of peanut crops yielded 1.5t h-1 or less (Seng et al., 2011). The mean of peanut
yield in all treatments in the present study were greater than 2.1t h -1. These data suggested thatintercropping cultivation could provide a harvestable yield of peanut in the upland cropping system of
Cambodia.
Soil chemical and physical properties before and after intercropping are presented in Table 3. The
soil texture that applied to soil sample was determined using the triangle (Brady and Weil, 2007). Soil
particle analysis revealed that field soils were sandy loam. A comparison revealed that there were no
significant differences between total C of pre-treatment and post-treatment in all treatment; however,
the total C of post-treatment was significant lower than that of pre-treatment of T6 (Paired samples ttest, p < 0.05). Likewise, organic C of pre-treatment and post-treatment of all treatments, except T6 (p= 0.013), are not significantly different (Paired samples t test, p > 0.05). There were not significant
differences in total N and phosphate between pre-treatment and post-treatment in all treatments (Paired
samples t test, p > 0.05).
Table 2 Plant growth and crop yield after intercropping in the upland cropping systems ofPrey Veng and Svay Rieng provinces

Treatment

T1
T2
T3
T4
T5
T6
T7

Statistics

Plantheight atflowering(cm)

Plant heightatharvesting(cm)

Weight/Hill(g)Numberoffruit/Hill

Weight/
100 seeds
(g)

Yield
(th-1)

Mean
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD

13.01
2.35
13.88
2.68
13.65
2.97
11.69
1.72
11.17
0.96
12.18
2.40
11.61
3.30

40.40
8.58
39.40
7.06
40.88
6.97
38.08
8.49
37.48
9.09
35.68
10.41
38.15
8.76

48.90
5.95
52.80
6.58
42.68
4.52
40.93
4.88
43.50
5.44
44.15
5.06
50.65
5.32

46.48
2.83
50.20
3.50
42.23
3.51
40.53
4.20
42.73
3.92
43.85
4.63
48.08
2.23

171.855.97
177.883.76
165.435.03
161.869.74
170.806.11
171.757.40
177.58
6.33

2.47
0.33
2.72
0.38
2.31
0.41
2.12
0.38
2.39
0.20
2.44
0.29
2.69
0.30

S.D, standard deviation

Further analysis revealed that soil Ca levels of pre-treatment did not significantly differ from thatof the post-treatment in all treatments (Paired samples t test, p > 0.05). However, soil Mg and Na levelsof post-treatment of T5, T6 and T7 was significantly lower than those of pre-treatment (Paired samples
t test, p < 0.05). A comparison indicated that there were no significant differences in soil K levels of
pre-treatment and post-treatment in all treatment (Paired samples t test, p > 0.05). Concurrently, theexchangeable pH and actual pH of soil in the pre-treatment did not significantly differ from those thepost-treatment (Paired samples t test, p > 0.05).
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Table 3 Mean values of the chemical and physical properties of soils before (n = 8) and after(n = 8) intercropping
Pre-treatment
Treatment
T1
T2
T3
T4
T5
T6
T7

C
10.32
10.32
10.32
10.32
10.32
10.32
10.32

Org C
1.77
1.77
1.77
1.77
1.77
1.77
1.77

T1
T2
T3
T4
T5
T6
T7

9.04
9.04
8.92
9.49
9.62
7.78
9.53

1.55
1.55
1.51
1.63
1.65
1.33
1.63

N
P2O5
1.18
144.251.18
144.251.18
144.251.18
144.251.18
144.251.18
144.251.18
144.25
Post-treatment
0.93
145.880.95
142.630.94
156.630.95
146.130.94
143.130.88
150.63
1.09
139.75

Ca
3.40
3.40
3.40
3.40
3.40
3.40
3.40

Mg
1.40
1.40
1.40
1.40
1.40
1.40
1.40

Na
0.12
0.12
0.12
0.12
0.12
0.12
0.12

K
0.16
0.16
0.16
0.16
0.16
0.16
0.16

pH
4.73
4.73
4.73
4.73
4.73
4.73
4.73

4.06
2.71
2.69
2.70
2.79
2.74
3.08

1.49
1.24
1.24
1.20
1.11
1.15
1.22

0.11
0.11
0.11
0.12
0.09
0.08
0.11

0.18
0.17
0.17
0.16
0.17
0.17
0.16

4.78
4.70
4.49
4.55
4.59
4.58
4.76

C, Org C, N, P2O5, Ca, Mg, Na, K in mg kg-1

CONCLUSION
Intercropping of peanut cultivation has been successfully implemented in the upland cropping system
of Prey Veng and Svay Rieng provinces. Field data revealed that there were not significant differencesin peanut height at flowering and harvesting stages among all treatments. However, weight per hill,number of fruit per hill and 100 grain weight significantly differed among the treatments. Peanut yield
increased in the order of T2 > T7 > T1 > T6 > T5 > T3 > T4. The mean of peanut yield were greaterthan 2.1t h-1 in all treatments. There were no significant differences in total N, phosphate, and K before
and after intercropping cultivation. This study suggests that intercropping could provide a harvestablesustainable yield of peanut in the upland cropping systems of southeast Cambodia.
ACKNOWLEDGEMENTS
Authors would like to thank OAE and DOA advisors and student volunteers attached to Chea Sim
University of Kamchaymear (CSUK) for their valuable field assistance. This study was financially
supported by World Bank through HEQCIP project of the Directorate General of Higher Education,
Ministry of Education, Youth and Sport of Cambodia Government.
REFERENCES
Bell, R.W., Seng, V., Schoknecht, N., Vance, W. and Hin, S. 2005. Assessing land suitability for crop
diversification in Cambodia. In Proceedings of the Land Resource Assessment Forum, held at CARDI, 23-26
September 2004, Cambodia.
Brady, N.C. and Weil, R.R. 2007. The nature and properties of soils. 14th Ed. Prentice Hall.
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Chan, P., Bob, M., Bob, F., Ung, S., Pol, C. and Pin, T. 2009. Farmer’s challenge in improving upland farming
systems in Cambodia. Cambodian Journal of Agriculture, 9 (1-2), 8-23.
Seng, V., Bell, R.W., Hin, S., Schoknecht, N., Vance W. and White, P.F. 2009. Soil factors affecting crop
suitability for upland crops in Cambodia. Cambodian Journal of Agriculture, 9 (1-2), 24-37.
Seng, V., Bell, R.W., Hin, S. and Touch, V. 2011. Field crop productivity in relation soil properties in Basaltic
soils of eastern Cambodia. Cambodian Journal of Agriculture, 10 (1-2), 5-19.

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Research article
erd

Systems Analysis and Modelling of Pollution Loading forManagement of Calumpang River in Batangas City,
Philippines
DIANE CARMELIZA N. CUARESMA*
University of the Philippines Los Baños, Laguna, Philippines
Email: dncuaresma@up.edu.ph

BEN PATRICK U. SOLIGUIN
University of the Philippines Los Baños, Laguna, Philippines

ROWENA A. JAPITANA
University of the Philippines Los Baños, Laguna, Philippines

RUBY A. ABAO
University of the Philippines Los Baños, Laguna, Philippines

JESUSITA O. COLADILLA
University of the Philippines Los Baños, Laguna, Philippines
Received 14 December 2015

Accepted 31 October 2016(*Corresponding Author)

Abstract The whole stretch of Calumpang River in Batangas province, Philippines is being
considered for ecotourism development by the Batangas City government. Water quality of thisriver, however, falls under the Philippine Department of Environment and Natural Resources’(DENR’s) classification as Class D – suitable only for agricultural and industrial purposes.
Restoration to Class B is needed for the river to qualify for Recreational Water Use. This
resource management concern needs to be addressed by the involved local government units(LGUs). Using systems analysis and modeling, a study on pollution loading of Calumpang
River is conducted to generate information that will aid policymakers in crafting management
options for the restoration. Factors, relationships, and processes involving people, land uses,
and management practices that led to its current polluted state are identified and analyzed using
the conceptual framework of the river system. Pollution contributions are identified andquantified. Analytical Hierarchy Process (AHP) and Geographic Information System (GIS) areused in determining who should be responsible and accountable for the restoration andmanagement of this water resource. Results showed that agricultural activities are the major
contributor to the degradation of water quality in Calumpang River. Swine production, inparticular, loads as much as 16,990 kg of solid waste daily. Using the physico-chemical andsocio-economic characteristics and their pollution loading contribution as a basis in determining
the degree of accountability, results showed that Batangas and Lipa cities have the highest levelof accountability with an AHP value of 0.24, followed by Rosario (0.15), Ibaan (0.14), and San
Jose (0.10). Establishment of a governing body as a management option can be recommended
using the results of the study as a basis for determining the financial contribution of theaccountable municipalities and the number of their representatives in the governing body.
Keywords systems analysis, Calumpang, watershed, swine, water degradation

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The Batangas City Government acknowledges the vital role of ecosystem services provided by the
Calumpang Watershed, and the need for rehabilitation, protection, and conservation of the river to push
forth its ecological tourism plan. This recognition led to the formulation of the Calumpang Watershed
Rehabilitation and Conservation Strategic Development Program for 2013-2023 which is now in its
third phase of implementation. Phase-1 focuses on socio-environmental preparations, education,
information, communication (EIC), institutional mobilization and strengthening multi-stakeholder
collaboration. Phase-2 focuses on watershed rehabilitation, resources, and technological investments.
Phase-3 covers the feasibility analysis of river restoration and ecotourism hotspot development. This
Phase requires cooperation and collaboration of all municipalities located within the watershed forthough the Calumpang River is located within Batangas City, its tributaries cover six municipalities(Cuenca, Padre Garcia, Rosario, San Jose and Taysan) and two cities (Batangas City and Lipa City)(Fig. 1).

Fig. 1 Calumpang Watershed map
One major constraint in the proposed development is its water quality. In 2013, the group of
Arboleda found the river to have high fecal coliform content (2 000- 130 000 MPN/100 mL), highlevel of Biological Oxygen Demand (BOD) (9-23 mg/L), and low level of Dissolved Oxygen (DO)(0.53-4.71 mg/L). In 2014, Cinco reported that Calumpang River was classified as Class D by thePhilippine Department of Environment and Natural Resource (DENR), indicating that the water is not
fit for any recreational activities and only fit for agricultural and industrial use. Identified potential
cause of pollutants includes inflow of untreated domestic sewage and animal wastes from poultries andpiggeries in the watershed. According to the Office of Provincial Planning and Development
Coordinator, in 2010 there are approximately 870,000 people residing in the watershed, with only
about 13.14% residing in Batangas City. Swine population is about 325,344 heads at any given time,
mostly found in Lipa City (28.72%).
River rehabilitation and water quality restoration from Class D to Class B are challenges that the
local government has to face as they pursue their plans for development. Batangas City can modify thepolluting factors within their jurisdiction using physical, economic, and/or political approaches.
However, since the watershed encompasses several municipalities and cities, baseline information as abasis for cooperative and collaborative river restoration is needed.

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DRIVING FORCE
Industrialization
Urban development
Agriculturalactivities

PRESSURE
Agricultural
pollutant and Urban
sewageloading

STATE
Eutrophic water
Polluted water
Class D water

IMPACT

Low aquatic diversity
Low productivity
Not suitable for ecotourism
Not suitable for fish
production

RESPONSE
Development plan
Scenario building
Policy development
River restoration
Ecotourism

Fig. 2 DPSIR framework of Calumpang Watershed
Coming up uses Systems Analysis to study the Watershed and to pinpoint the heaviest contributorof pollution. This study can be used to justify that even though Calumpang River falls within the
territorial jurisdiction of Batangas City, the restoration and management of the River can be made as a
combined effort of all municipalities and cities in the Watershed. Fig. 2 summarizes theabovementioned discussion.
OBJECTIVESThis study aims to describe the effect of swine production and human population within the watershedto the pollution of Calumpang River; and to roughly quantify the extent of contribution of eachmunicipality or city to serve as basis for restoration and rehabilitation accountability.
METHODOLOGYThis study was conducted from July to December 2014 as part of a commissioned project by the Local
Government of Batangas City to the School of Environmental Science and Management of the
University of the Philippines Los Baños. Primary and secondary data gathering was conducted in thearea (Fig. 1) using the DPSIR framework shown in Fig. 2 as a guide for data requirement. Systemanalysis approach was applied to analyze the state of Calumpang River system, the contributing factors
to its current state, its impact to the people and environment, and the government responses to address
the identified problems. Analysis was conducted using tools such as Geographic Information Systems(GIS), systems modelling and Analytical Hierarchy Process (AHP). GIS was used to generate
information on loading process based on the amount of pollutants at source and proximity of pollutant
sources to the river. The absence of data on the rate of flow of the tributaries is offset by estimating theamount and flow of water as affected by the soil, slope and elevation. This method was used toestimate the flow of pollutants from the source and the amount that reached the water. Lastly, adecision criterion, employing AHP, is set up to determine which municipality(ies) is/are accountable inthe current state of the river and their level of participation that is crucial in the management andrestoration of Calumpang River.
RESULTS AND DISCUSSIONⒸ ISERD

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System Analysis of Calumpang Watershed

WASTES
Domestic
Agricultural

FLOW OFWASTE
Runoff affected byproximity, soil type,elevation, slope andrainfall amt.

ENVIRONMENTALSTATUS OFCALUMPANG
RIVER

SUSTAINABILITY
OF ECOTOURISM
PROJECTECONOMIC, DEVELOPMENTAL AND ENVIRONMENTAL POLICIESFig. 3 Framework of Calumpang Watershed
Analysis of the Calumpang river system based from observations and data gathered in the area showedthat though households typically have septic tanks or sanitation facilities, there are piggeries with nowater treatment facilities and a few households with no septic tanks. The combined wastes of theresidents and pigs from all municipalities will be received by a catchment point in Batangas City. The
flow of water is not constant from each municipality; rate of flow is usually affected by elevation,slope, soil type, proximity to the area, and rainfall. The state of the water in the River will determine
how successful the proposed ecotourism project will be. Initial analysis of the Calumpang river systemshows that sustainability of ecotourism project is dependent on the environmental status of Calumpang
River. The River is polluted due to the wastes coming from the different municipalities and cities
within the Watershed which are using the tributaries as sink of domestic and agricultural waste (Fig. 3).
To achieve a Class B, restoration of the River must be done. This can be done by introducing policies
either at the waste source, such as reduction in number of pigs per farm; or at the River by dredging of
the River; etc.
Computation of Total Wastes Received by Calumpang River
Using the above framework as a conceptual model of the Calumpang river system, quantification of therelationship was done. This can be used by policy makers as aid in crafting policies for the restorationand management of Calumpang River.
Table 1 Summary of parameters that affect the flow of water to Calumpang River
Proximity(m)Elevation(m)
Slope*
Soil Type

Batangas
City
0

Ibaan

1-100

21-500Flat to steep

Very steep

5,851

Lipa
City
16,511

CuencaTaysan

San jose

Rosario

12,745

10,965

9,051

12,099

Padre
Garcia18,187101500Flat tohilly

201-975

51-500101-500

51-200101-200

Dominantly
hilly
Ibaan
Loam,
Ibaan
Loam
(Gravelly
Phase)

Flat to hilly

Rolling tohilly

Flat torolly

Flat to hilly

Hydrosol,
Ibaan Loam Ibaan
Ibaan Loam Ibaan
Ibaan Clay
Taal Sandy(Gravelly
Loam,(Gravelly
Loam,
Loam,
Loam,
Phase),
Ibaan
Phase),
Ibaan
Guadalupe
Calumpang
Ibaan Clay
Clay
Guadalupe
Loam
Clay Loam
Clay, Ibaan
Loam,
Loam,
Clay Loam,(Gravelly
Loam, Ibaan Guadalupe
Lipa
Ibaan Clay
Phase)
Clay Loam
Clay Loam
Loam
Loam*Flat= 0-3%, Rolling= 3-6%, Hilly= 6-15%, Steep= 15-30%, Very Steep= >30% measured near the riverⒸ ISERD137

Lipa Loam,
Guadalupe
Clay Loam,
Ibaan ClayLoam

IJERD – International Journal of Environmental and Rural Development (2016) 7-2

For the quantification, this study uses the value derived by Agbisit et. al. on swine daily waste
generation which is at 0.26 kg, and the average daily human solid waste generation which is about 0.5
kg. Daily waste generation of each municipality and city were computed and the amounts of wastes
that will end up in the Calumpang River were estimated. Due to lack of data on the amount of rainfall
received per municipality or city, it is assumed that each municipality or city receives the same amountof rainfall per month or year. Also, only wastes produced by the residents and swine are included in theanalysis since they are the highest waste generator. Table 1 summarizes the parameters that affect theflow of wastes to Calumpang River, while the summary of human and swine population can be foundin Table 2.
Figure 4 shows the pollution loading of each municipality within the Calumpang Watershed.
Results showed that Batangas City (7951.95 kg) is the greatest polluter of Calumpang River, followedby Ibaan (2707.74 kg), Lipa City (2204.94 kg) and San Jose (1583.25 kg). This result is expected sinceBatangas City is the nearest municipality to the catchment area, and the municipality that has thehighest number of residents and second in number of swine. For the case of Lipa City, though this area
is one of the farthest from the catchment point, its elevation, and its high number of residents andswine caused it to contribute more to the pollution. However, for Ibaan and San Jose, despite the low
number of residents in the municipality, its proximity to the area, and the high number of swine caused
the high amount in waste contribution. Meanwhile, Cuenca (1165.68 kg), Taysan (908.01 kg), Rosario(391.13 kg) and Padre Garcia (79.03 kg) are the least polluter of Calumpang River.
Calumpang River receives approximately 16,991 kg of wastes daily. If no intervention will be
introduced in the area, the water will continue to be polluted: this may result to poor water quality inthe region, which can then result to loss of biodiversity, loss of livelihood (fishery), illness such as
diarrhea and other related diseases, the failure of the proposed ecotourism project, etc. This situation,
if not solved, will make Batangas City’s efforts to develop Calumpang River into an ecotourism site
futile.

Fig 4. Summary of pollution loading ofmunicipalities or cities in Calumpang
Watershed

Fig 5. Summary of weights computed

Decision Criterion on Selection of Participants to Restoration and Management Project
Given that the river has many sources of pollutant which could exacerbate the declining water quality,
the proposed ecotourism would not be successful. However, the problem is that Batangas City cannot
be expected to clean up all wastes contributed by other municipalities and cities. If a governing bodywill be established to craft policies and implement restoration and rehabilitation program based on theirⒸ ISERD

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contribution and accountability in the water pollution, a basis for decision making is needed. For thispurpose, AHP was used to determine which among the municipalities surrounding the River is moreaccountable and should be responsible for the restoration and management of the River.
Land area, population of residents, population of swine, and the area’s contribution to pollution
has been chosen as the criteria for joining this governing body. Land area is chosen since the larger theland area occupied, the higher its use of the Watershed. Population of residents and total swine units
are chosen since the higher the number of these two factors will result to higher amount of taxes paid
to the municipality or the city, which will result to the municipality or the city having more money tofund the project. Lastly, pollution loading is chosen since the higher this is, the higher the
responsibility of the area to the pollution of the River.
Data used for these criteria are based on the study by Morales (2011). Table 2 summarizes thecriteria together with the corresponding value per municipality. Note that the population of residents istaken in 2007, while the population of the swine is taken in 2011. Comparison of municipality or city isdone pair-wise and the one that presents the higher value is given the higher point.
It has been found that Batangas City (0.24), Rosario (0.15), Ibaan (0.14), Lipa City (0.24), and
San Jose (0.10) present the highest weights. Expectedly, these five municipalities are the ones with thelargest land areas in the Watershed, the largest population, the most number of swine, and the greatest
polluter of Calumpang Watershed. On the other hand, Padre Garcia (0.06), Taysan (0.09), and Cuenca(0.07) present the lowest weights.
Table 2 Criteria for joining the restoration and management project
BATANGAS
CITY
6546

IBAAN

RESIDENTS
SWINE
POLLUTION
LOADING (kg)

LAND AREA (ha)CUENCATAYSAN

6881

LIPA
CITY
5024

ROSARIO

4971

SAN
JOSE
5510

6550

PADRE
GARCIA
893

956

29523145649

260568

65498

34961

93452

28581

33454

61307

95785

42942

2720

17722

28600

74410

7981

7951

2708

2205

1165

908

1583

391

79

CONCLUSION
Calumpang River is predicted to be polluted, and the results show that every municipality contributes
to it in different extents. Restoration and management program should be done to realize the proposed
ecotourism project in Calumpang River. However, Batangas City government will need help fromother municipalities and cities since each of them contributed in the pollution and, because ofjurisdiction issues, Batangas City’s restoration program cannot go beyond their administrative
boundaries. Quantification of each municipality’s contribution can be used as basis for determining theextent of accountability and responsibility in the restoration and management programs that will be
introduced. An option to ensure rehabilitation and restoration of Calumpang River could be a creationof consortium or a governing body composed of municipalities contributing to river pollution. The
members of such body must be proportionate to its contribution based on the results of this study. In
terms of financial contribution or otherwise, further study should be conducted to determine its
feasibility.
ACKNOWLEDGEMENTS
This study was conducted by the ENS 211 class of 1st Semester, AY 2014-2015 contributing to theproject commissioned by the Local Government Unit (LGU) of Batangas City to the University of theⒸ ISERD

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Philippines Los Banos School of Environmental Science and Management (UPLB-SESAM). Maps
were generated using the licensed version of ArcMap 9.2 of the SESAM.
REFERENCES
Catelo, Ma Angeles O., Dorado, Moses A. and Agbisit, E., et al. 2001. Backyard and commercial piggeries in thePhilippines, Environmental consequences and pollution control options. EEPSEA Research Report.
Arboleda, M., et al. 2013. EIA dredging project. University of the Philippines Los Banos. Unpublished.
Bibal, A., Cabrera, E., Copaquiyan, J., Joven, J., Ladia, A., et al. 2014. Badjao indigenous peoples and of
Batangas City Calumpang River rehabilitation and ecotourism development, Prospects and trade-offs.
University of the Philippines Los Banos. Unpublished.
Boongaling, C. 2014. Modelling run-off and sediment yield in Calumpang Watershed, Philippines and its
response to landscape pattern. University of the Philippines Los Banos. Unpublished.
Cinco, Maricar. 2014. Coliform prompts Batangas to River rehab. http://newsinfo.inquirer.net/619305/coliformprompts-batangas-River-rehab
Hamilton, D., Luce, William G. and Heald, Aimee D. n.d. Production and characteristics of swine manure.
Oklahoma State University, USA.
Morales, L.R. 2011. Effect of swine waste pollution on water quality and fish productivity at a different sectionof Calumpang River Watershed, Batangas, Philippines. Ph.D. Dissertation. University of the Philippines.
Unpublished.

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Research article
erd

Differences in Benthic Cover and Fish Assemblage Inside andOutside Marine Protected Areas
JESRELLJANE AARON-AMPER*
College of Fisheries and Marine Sciences, Bohol Island State University Candijay Campus,
Cogtong, Candijay, Bohol, Philippines
Email: jesrelljane@gmail.com

SAMUEL J. GULAYAN
College of Fisheries and Marine Sciences, Bohol Island State University Candijay Campus,
Cogtong, Candijay, Bohol, Philippines
Received 14 January 2016

Accepted 31 October 2016(*Corresponding Author)

Abstract Marine protected areas (MPAs) are being used increasingly to manage and protect
marine resources. Most studies of MPAs have only focused on either benthic cover or fish
assemblage. In this study, the influence of MPA protection on both parameters in two areas at
Bohol (Badiang, Anda and Baybayon, Mabini) was investigated. At each MPA, three 50-mtransect lines at 10 m interval were permanently established inside and outside at 5-8 m depth.
The systematic point intercept method was used in determining the benthic cover and fishvisual census method for fish assemblage. In Badiang, the protected area had significantly
higher live hard coral cover than the general use area. Dead coral with algae covered the generaluse area in both Badiang and Baybayon. Fish species richness were significantly different in
Baybayon with moderate condition in protected area and poor condition in the general use area.
Fish density inside the protected area and general use area were not significantly different but
were in moderate condition. The high levels of hard coral cover and fish species richness in theprotected areas may be a result of their protection status.
Keywords coral, coral nursery unit, fish assemblage, restoration, management

INTRODUCTION
A part of the world’s population lives along the coastal plain comprising the coasts, seas, oceans, rivers
and estuaries. Humans deal with the coastal and aquatic ecosystems as food resources and a large
proportion of the people in most countries are dependent on aquatic resources to provide their dailyneeds. Unfortunately, many of these natural ecosystems have been indiscriminately harvested or evendevastated due to over fishing, physical and chemical destructions arising from industrial activities,
untreated sewage of nearby cities and factories, oil and gas contamination from refineries and passing
vessels and oil rigs. All these factors have caused the destruction and/or degradation of marine
ecosystems, especially decrease in the population of many kinds of aquatic biota (Azhdari et al., 2012).
One of the solutions being used to address the threats plaguing marine resources is theestablishment of marine protected areas (MPAs). They are “clearly defined geographical spaces,
recognized, dedicated and managed, through legal or other effective means, to achieve the long-term
conservation of nature with associated ecosystem services and cultural values” (IUCN definition by
Dudley, 2008). This is one of the most achievable modes of protection particularly in the Philippines inrelation to Coastal Resource Management (CRM) (White et al., 2002). In the Philippines, MPAs can be
categorized into two governance levels: nationally established and locally established MPAs. In
general, they take four forms: 1) Marine sanctuary or no take marine reserve, where all forms ofⒸ ISERD141

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extractive activities are prohibited; 2) Marine reserve, where extractive and non-extractive activities are
regulated; 3) Marine parks, where uses are designated into zones; and 4) Protected landscape andseascape, where protection may include non-marine resources (Miclat and Ingles, 2004, White et al.,2014). The most common objectives of MPAs establishment are biodiversity conservation, fisheries
sustainability, and tourism and recreation, among others.
In a recent review of 112 independent empirical measurements of 80 different reserves, it was
found that average values of all biological measures were strikingly higher inside marine reservescompared to the general use areas (Halpern, 2003). Relative to general use sites, population densities
were 91% higher, biomass was 192% higher, and average organism size and diversity were 20–30%
higher in reserves. Furthermore, these values were independent of reserve size, indicating that evensmall reserves can produce high values.
There are only a few reports that determine the biological response of the reserve protection in
Bohol (Pollnac et al., 2001). Thus, this study investigated the benthic characteristics condition of thegeneral use and protected area as well as reef fish status based on the diversity and density of fishes. In
addition, we tried to determine if there is a significant difference between these parameters in thegeneral use and protected areas.
METHODOLOGY

Baybayon, Mabini
Badiang, Anda

Fig. 1 Map showing the locations of the two MPAs in Bohol as survey sites
Site Selection
This study was conducted in the MPAs at Badiang, Anda, and Baybayon, Mabini, located in theeastern part of Bohol (Fig 1). Badiang, Anda MPA known as Badiang Fish Sanctuary was establishedin 2003 with a total area of 0.701 km2 while Baybayon, Mabini known as Lumayag Islet Marine Parkwas established in 1995 with a total area of 0.265 km2.The river water quality was monitored at 37
sampling points located on the main stream (nos. 1-17) and each tributary (A-T) of the Tokachi Riverbasin in June, either August or September and October from 2007 to 2011 under base flow conditions.
Water samples were analysed for pH, BOD, SS and EC.

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Benthic Survey Technique
The benthic cover at each location along three randomly established transect lines at 5 m depth (during
highest high tide) were assessed using the systematic point intercept method. Each transect was 50 m
in length. Photographs were taken using an underwater camera at .25 m intervals and at a height of .50
m above the substrate of each transect. To examine the condition of the coral reef, we grouped thecoral cover into 16 categories: branching, table, digitate, encrusting, foliose, mushroom, massive, submassive, soft, macroalgae, seagrass, other fauna, dead coral, rubble, hard rock, and sand. Coral reef
status were categorized using the criteria of Gomez et al. (1994).
Fish Species Richness and Density
Divers recorded the density and diversity of fish in 250 m2 area demarcated by a 50 m transect line
(laid during the benthic survey) an hour after the benthic survey. The number of individuals per species
was noted. The families surveyed are those that are diurnal only. Reef fish status was determined basedon fish density (individuals/1,000 m2) and diversity (mean number of fish species/250 m2), using thecategories by Hilomen et al. (2000).
Statistical Analysis
The data were arcsine transformed to pass the assumptions. T-tests were used to determine if there is asignificant different between each biological component measured in the general use and protectedareas.
RESULTS AND DISCUSSION
Living structures excluding dead corals covered an average of 51% and 33% of the substrate in theprotected areas of Badiang and Baybayon, respectively, and 10% and 29% in the general use areas (Fig.
2). Live hard coral, rubble, and sand and silt were among the benthic categories which have highpercentage cover in both protected areas of the study sites. Dead coral with algae, sand and silt, andrubble were among those which have high percentage in the general use areas. Soft corals, sponges,
and fleshy algae combine contributed less than 3% to total benthic cover in both protected and generaluse. In Badiang, the protected area had significantly higher live hard coral cover compared to thegeneral use area (p < 0.05). Its live hard coral, which had the highest coral percentage cover observed,
was classified as ‘good’. The general use in Badiang was ‘poor’ while the coral status in Baybayon inboth general and protected areas was ‘fair’.
The 1950’s were typically regarded as the start of the demise with the introduction of dynamite
fishing during the Second World War and other illegal practices in the subsequent decades, such as
cyanide fishing and trawling (Marcus et al., 2007). Green et al. (2002) conducted a survey on illegal
fishing in Bohol Province and they found out that out of 11 out-lawed fishing gears and activities,
dynamite was the most widely used. Though the areas examined in this study are not listed as dynamite
and cyanide hotspots in Bohol by Green et al. (2002), we suggest that the use of cyanide, and local
plant poisons such as tubli and lagtang were the most likely reason for the high percentage cover ofdead coral with algae in the general use areas since this kind of destructive fishing practices do notdirectly result in physical breakage of hard corals (McManus et al., 1997). The presence of rubble in
the protected and general areas also indicates incidence of dynamite fishing.

Ⓒ ISERD

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Percentage Cover

IJERD – International Journal of Environmental and Rural Development (2016) 7-2

90
80
70
60
50
40
30
20
10
0

General Use

Protected

Live hard Soft coral Sponges Other
Fleshy Seagrass Sand and Rubble Rock and Dead
coral
Animals Algae
siltblock coral with
algae
90
80
70
60
50
40
30
20
10
0

Live hard Soft
coral
coral

Sponges

Other Fleshy Seagrass Sand and Rubble Rock and Dead
Animals Algae
silt
block
coral
with
algae

Density (1000 m2)

Fig. 2 Benthic composition in the general and protected areas at Badiang and Baybayon
Protected

2000
1800
1600
1400
1200
1000
800
600
400
200
0

Badiang

General Use

BaybayonMarine Protected Areas
Fig. 3 Fish density in the two marine protected areas
Fish diversity were significantly different in Baybayon with a moderate condition in protectedarea and poor condition in the general use area (Table 1). However, fish density in the protected andgeneral use areas of both Badiang and Baybayon showed no significant difference (Fig. 3). This is anindication that they were under more or less of the same condition. Based on the classification ofⒸ ISERD

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Hilomen (2000), the density of fishes in all study areas were in moderate condition. The most dominantfamilies in both Badiang and Baybayon came from Pomacentridae and Pomacanthidae. Higher densityof these species was probably due to the lack of top predators which declined following intense fishingpressure (Corrales et al., 2015).
Table 1 Species richness in the marine protected areas at Badiang and Baybayon
FamilyAcanthuridae
Apogonidae
Balistidae
Caesionidae
Chaetodontidae
Centriscidae
Haemulidae
Holocentridae
Labridae
Lethrinidae
Lutjanidae
Monacanthidae
Mullidae
Ostracidae
Ogcocephalidae
Nemipteridae
Pempheridae
Plotosidae
Pomacanthidae
Pomacentridae
Scaridae
Scorpaenidae
Serranidae
Siganidae
Synodontidae
Tetraodontidae
Zanclidae
Total

Protected
x
x
x
x
x
x
x
x

Badiang
General Use
x
x
x
x
x
x
x

x

x
x
x

x
x
x
x
x
x

x
x
x
x
x

x
x

x
x

x
x
19

x
18

Protected
x
x
x
x
x
x
x
x

Baybayon
General Use
x
x
x

x

x
x
x
x
x
x

x

x
x
x
x
x
x
x
x
x
x
24

x
x

x
x

x
x
x

12

CONCLUSION
The MPAs the study sites have played an important role in fishery conservation and this is evident in
the higher levels of hard coral cover and fish species richness within the areas. However, they still needlong-term protection and good management to improve fish population.
REFERENCES
Cabral, R.B., Aliño, P.M., Balingit, A.C.M., Alis, C.M., Arceo, H.O., Nañola Jr, C.L. and Partners, M.S.N. 2014.
The Philippine marine protected area (MPA) database. Philippine Science Letters, 7 (2), 300-308.
Corrales, C.M., Delan, G.G., Rica, R.L.V., Piquero, A.S. and Monte, I.A. 2015. A baseline study on coral reef
fishes in the marine protected areas in southern Cebu, Philippines. Tropical Technology Journal, 1 (19), 1-8.
Dudley, N. 2008. Guidelines for applying protected area management categories. IUCN.

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Green, S.J., Alexander, R.D., Gulayan, A.M., Migriño III, C.C., Jarantilla-Paler, J. and Courtney, C.A. 2002.
Bohol Island, Its coastal environment profile. Report, Bohol Environment Management Office, Bohol andCoastal Resource Management Project, Cebu City, Philippines.
Halpern, B.S. and Warner, R.R. 2002. Marine reserves have rapid and lasting effects. Ecology Letters, 5 (3), 361366.
Hilomen, V.V., Nañola Jr, C.L. and Dantis, A.L. 2000. Status of Philippine reef fish communities. Gomez (eds.).
Philippine Coral Reefs, Reef Fishes, and Associated Fisheries: Status and Recommendations to Improve their
Management. Global Coral Reef Monitoring Network (GCRMN).
Marcus, J.E., Samoilys, M.A., Meeuwig, J.J., Villongco, Z.A.D. and Vincent, A.C.J. 2007. Benthic status ofnear-shore fishing grounds in the central Philippines and associated seahorse densities. Marine Pollution
Bulletin, 54 (9), 1483-1494.
McManus, J.W. 1997. Tropical marine fisheries and the future of coral reefs, A brief review with emphasis on
Southeast Asia. Coral Reefs, 16 (1), S121-S127.
Miclat, E. and Ingles, J. 2004. Standardized terms and definitions for use in marine protected area management in
the Philippines. In Proceedings of the Workshop Toward the Formulation of the Philippine Marine Sanctuary
Strategy (pp. 3-8). Quezon City: Marine Science Institute, University of the Philippines.
Pollnac, R.B., Crawford, B.R. and Gorospe, M.L. 2001. Discovering factors that influence the success ofcommunity-based marine protected areas in the Visayas, Philippines. Ocean & Coastal Management, 44 (11),683-710.
Roberts, C.M., McClean, C.J., Veron, J.E., Hawkins, J.P., Allen, G.R., McAllister, D.E. and Vynne, C. 2002.
Marine biodiversity hotspots and conservation priorities for tropical reefs. Science, 295 (5558), 1280-1284.
White, A.T., Courtney, C.A. and Salamanca, A. 2002. Experience with marine protected area planning andmanagement in the Philippines. Coastal Management, 30 (1), 1-26.
White, A.T., Aliño, P.M., Cros, A., Fatan, N.A., Green, A.L., Teoh, S.J. and Venegas-Li, R. 2014. Marine
protected areas in the coral triangle, Progress, issues, and options. Coastal Management, 42 (2), 87-106.

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Research article
erdInfluence of Meteorological Variable Combinations on
Reference Evapotranspiration Estimated by the FAO56
Penman-Monteith Method
HIROMU OKAZAWA*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Email: h1okazaw@nodai.ac.jp

YASUSHI TAKEUCHI
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Received 29 Decemberber 2015

Accepted 31 October 2016(*Corresponding Author)

Abstract An estimate of potential evapotranspiration (PET) is typically required for rainfall
runoff modeling, and such as estimate of PET is often determined from use of the PenmanMonteith (PM) method using air temperature, humidity, wind speed, solar radiation andsunshine hours data. This method is recommended by the FAO and used widely across theworld. The estimated PET is known to vary depending on the combination of meteorological
data used in the PM equation. For example, PET can be estimated by using wind speed and airtemperature data only, or by using all five meteorological data. There have been no cases thatwere examined regarding how combinations of the five data influence estimated PET for the
Asian Monsoon region. Air temperature, wind speed, solar radiation, sunshine hours andhumidity were measured and recorded at ten-minute intervals for three years at a weather
station in the Minami-Soma City, Fukushima Prefecture, Japan. The daily PET was estimatedfor the 13 combinations of the five data. It was found that PET is overestimated when the solar
radiation is not included in the combination. The above results show that data on the solar
radiation are indispensable for PET estimation that uses the PM equation in the Asian Monsoon
region.
Keywords hydrological model, potential evapotranspiration, FAO, Penman-Monteith method

INTRODUCTION
In recent years, there have been hydrological hazards such as floods and landslides due to heavy
precipitation and metrological hazards such as storms and extreme temperature that have occurred inmany areas of the world. Particularly in the Asia-pacific region including the Asian monsoon region,hydrological and metrological hazards were the most frequent disasters in 2014. Furthermore,
economic losses due to those disasters were estimated in more than 50 billion USD (ESCAP, 2014).
Therefore, river development and watershed management for mitigating flood damage have beencalled for. In planning projects for river development and watershed management for natural disastermitigation, it is necessary to simulate the effectiveness of the project by using a rainfall runoff model,
with which it is possible to predict the changes in the river discharge in relation to the rainfall in thewatershed scale.
For such a rainfall runoff model to be used, data on potential evapotranspiration (PET) is required.
Measured PET data is not generally used for the model. The PET data is determined from the fivemeteorological data of air temperature, intensity of solar radiation, humidity, wind velocity andsunshine hours and by using a FAO-56 Penman-Montieth (PM) method, which was described in the
FAO Irrigation and Drainage Paper No 56 “Crop Evapo-transpiration” in 1998 by the Food andⒸ ISERD

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Agriculture Organization (FAO) of the United Nations, to revise guidelines for computing crop waterrequirements (Allen et al., 1998). The most common equation for estimating PET, which isrecommended by the FAO and is used widely in the world, is the Penman-Monteith (PM) equation.
OBJECTIVE
The estimated PET is known to vary depending on the combination of meteorological data used in thePM equation (Todorovic et al, 2013; Pereiraa et al. 2015). For example, PET can be estimated by using
wind velocity and air temperature data only, or by using all five meteorological data. There have beenno cases that were examined regarding how combinations of the five data influence estimated PET for
the Asian Monsoon region. In this study, comparisons between measured and estimated values were
performed for atmospheric pressure, vapor pressure, and solar radiation by using the root mean squared
error (RMSE), and the accuracy of the estimation method recommended for use in the PM method was
examined. The influence of the estimation accuracy of these three items on the estimated PET wasclarified.
1
̂
𝑅𝑀𝑆𝐸 = √ ∑𝑁
𝑖=1 𝑃𝐸𝑇𝑖 − 𝑃𝐸𝑇𝑖

(1)

𝑁

Where N is number of calculation data, 𝑃𝐸𝑇𝑖 is computing value by using all five meteorological̂𝑖 is computing value by using 2 to 4 meteorological variables.
data, 𝑃𝐸𝑇METHODOLOGY
Meteorological observation was done for the 22 months from November 2011 to September 2013. A
weather station was installed at a location 2km inland from the sea coast of Minami-Soma City,
Fukushima Prefecture (Fig.1 and Photo.1), during those 22 months. The observation items wereprecipitation (P), wind direction (WD), wind speed (WS), temperature (T), relative humidity (RH), solar
radiation (RS), and actual hours of sunshine (AH). These were measured at 10-minute intervals. The
daily average, daily lowest, and daily highest values for these seven items were determined.
Atmospheric pressure (P) could not be measured at the observation site. Instead, the atmosphericpressure observed by the Japan Meteorological Agency at Sendai City, 60 km from the observation
station, was used.
In calculating the daily potential evapotranspiration (PET), the Penman-Monteith (PM) method,which is recommended by the FAO, was used. The equation used for the PM method is shown below.
𝐸𝑇0 =0.408Δ(𝑅𝑛 −G)+𝛾

900
𝑢 (𝑒 −𝑒𝑎 )𝑇+273 2 𝑠

(2)

Δ+𝛾(1+0.34𝑢2 )Where ETo is the reference evapotranspiration (= PET) (mm/d), Rn is the net radiation at the crop
surface (MJ m-2 d-1), T is the air temperature at 2 m height (OC), u2 is the wind speed at 2 m height (m s-1)
es is the saturation vapour pressure (kPa), ea is the actual vapour pressure (kPa), Δ is the slope vapour
pressure curve (kPa OC-1), γ is the psychrometric constant (kPa OC-1) G is the soil heat flux density (MJ
m-2 d-1). For day and ten-day periods, as the magnitude of the day or ten-day soil heat flux beneath thegrass reference surface is relatively small, it was ignored.
In using the PM method to determine the PET, it is necessary to obtain several variables: Rn, T, u2,es, ea, Δ, γ, and G. The meteorological data, including T, RH, Rs or AH, and P are used to determine thevariables. The PET can be determined even without data such as Rs (or AH), RH, or P. The flows of
calculation for the items relevant to the PM method are shown in Fig. 2. The P can be estimated fromⒸ ISERD

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the elevation. To determine the vapor pressure ea, RH and T are used; however, when the RH data areunavailable, it is possible to estimate ea by using the T data. When the Rs data are not available, Rs canbe estimated from the AH.

Sendai

Fukushima
M inami- soma

Fukushima prefecture
Iwaki

0

20

40km

Fig. 1 Investigation site (Red point)

Photo. 1 Weather station

Wind speed (u)Height of wind speed (h)Attitude (z)Dew point temperature (TDEW )Psychometric data

Wind speed at 2.0m (u2.0)* P can estimate by attitude (z).
Atmospheric pressure (P)Psychrometric constant (γ)

Clear-sky solar radiation (RSO)

Soil heat flux (G=0)
In the case of cpmputing dairy ETo,
It maybe ignored* ea can estimate by RH, T, T DEW or Psychometric data.
Actual vapour pressure(ea )Vapour pressure deficit (eS-ea)

Relative humidity(RH mean, RH min, RH max)Slope vapour pressure curve (Δ)
Air temperature (Tmin, Tmax)

Saturation vapour
pressure (eo)Mean saturation
vapour pressure (eS)Net radiation (Rn)

* Rs can estimate either T or AH.
Solar radiation (Rs)

Net longwave radiation (Rne )Actual duration of sunshine (AH)
Number of day in the year (n)Net solar or shortwave radiation (Rns)Daylight hour (N)Albedo (a=0.23)

Latitude (j)Reference evapotranspiration(ETo )

Extraterrestrial radiation
for dairy period (Ra )Fig. 2 Flow diagram of potential evapotranspiration calculation by the PM methodⒸ ISERD

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As shown in Table 1, when determining the PET by using the meteorological data such as T, RH,
Rs (or AH), and P as variables, there are 13 combinations of data items, here designated A to M (Table1). The estimated PET differs according to what combinations of meteorological data items are used.
However, no previous reports have investigated how combinations of the meteorological data influence
estimation of the PET for the Asian monsoon region.
Table 1 Thirteen patterns of meteorological data set for calculating PET by the PM method

RESULTS AND DISCUSSION
Weather Characteristics of Minami-Soma City
The meteorological data obtained during the 22 months is shown in Fig. 3. The daily data for the 22months are shown in the graphs for the monthly data. The daily average temperature was the highest in
August and the lowest in February. The annual temperature difference was 25°C. The humidity washigh in summer (July), at 70% or greater, and low in winter (Jan., Feb., March), at 60%. The windspeed ranged between 1.0 and 1.5m/s. The wind speed in this area was extremely low throughout theyear. The variation in atmospheric pressure was small; it ranged between 1000 and 1010 hPa. The solar
radiation and sunshine hours were the greatest in June and the smallest in December. These changed
with an annual cycle. The precipitation was great in spring (April, May) and fall (September, October).
This area has little snowfall. There is no snow cover during winter.
When P data were unavailable, P was estimated by using the elevation in the PM method. Here,the measured and estimated P are compared and the estimation accuracy is examined. Fig. 4 shows therelationship between the measured and estimated daily data for P during the 22 months. As there wasonly one elevation reference location, the P estimated from that elevation was 100kPa. The estimatedvalues varied between 97kPa and 103 kPa. The RMSE was an extremely small value of 0.71kPa. The
above result clarified that the P could be accurately estimated from the elevation, even when the P data
were unavailable.
The actual vapor pressure (ea) is determined as a function of the daily average RH and daily
highest and lowest T. The value of ea can be determined from the daily lowest T even when the RH
data are unavailable. Here, ea determined by using the RH and T data was compared to that determinedby using only the T data. The estimated values determined in the two methods were compared (Fig. 6).
The comparison revealed a high correlation between the two values. The RMSE was an extremely
small value of 0.16kPa. Based on the above, it was thought that ea can be accurately estimatedirrespective of the use of the RH data.
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Fig. 3 Meteorological data obtained during the 22 months

Fig. 4 Relationship between the Fig. 5 Relationship between the Fig. 6 Relationshipobserved and the calculated
calculated data by RH & T
between the observed
daily data for P
and the calculated data by T
and the calculated
daily data for RsⒸ ISERD

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Estimation Accuracy of Atmospheric Pressure, Vapor Pressure and Solar Radiation
When the Rs (net radiation) data were unavailable, the Rs was estimated from the AH or T. Here, theobserved solar radiation is compared with the values estimated from the AH and the values estimatedfrom the T (Fig. 7). The values estimated from the AH and the values estimated from the T show apositive correlation with the observed values. However, the RMSE is the great value of 6 MJ m2 d-1 forboth types of estimated values. The Fig. 7 shows that the difference between the observed andestimated values is small in the areas near the highest and lowest observed values. The estimatedvalues were 20, 25 and 25 MJ m2 d-1, while the observed values were 5, 10, 15 and 20 MJ m2 d-1. The
estimated values overestimated the observed values by a factor of 4, 2.5 and 1.25, respectively. This
comparison found that Rs is unable to be accurately estimated from the AH or T.
The Influence of Combinations of Meteorological Data Items on the Estimation of the PET
Figure 7 shows the daily average of the PET determined from the data obtained during the 22 months.
The error bar indicates the standard deviation. The graph shows the 13 patterns of combinations ofmeteorological data items. J shows the PET (2.07mm/d) that was determined by the estimation
calculation using T, WS, RH, Rs, and P, which is recommended in the PM method. The discussion will
be done using the J value as the standard. For the combinations of meteorological data items A to I, in
which Rs was not used, the PET values (2.51 - 2.27) are overestimated and are higher than those of J
(1.21 - 1.10). For the combinations of meteorological data items K to M, in which the Rs was used but
one or more data were not used, the PET was between 1.98 and 2.07, which are small values equal toor 0.96 times that of J. From the above, it was clarified that the PET can be accurately estimated byusing the PM method when Rs data are available, even when the RH or P data are unavailable. It wasalso clarified that when the PM method is used in the Asian monsoon region, Rs is an importantvariable in addition to WS and T.

Fig. 7 Daily average of the PET determined from the data obtained during the 22 months
CONCLUSION
In this study, examination was done on the use of the PM method for estimating the PET of therelatively warm regions with small precipitation. As the results, the potential evapotranspiration can be
accurately estimated by using the Penman-Monteith method when solar radiation data are available,
even when the relative humidity or atmospheric pressure data are unavailable. It was also clarified thatwhen the Penman-Monteith method is used in the Asian monsoon region, solar radiation is an
important variable in addition to wind speed and air temperature.

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However, the climatic divisions are varied even in the Asian monsoon region. It is necessary to
conduct an examination that is similar to the one done in this study in areas with heavy rain and in cold
areas. It is also necessary to conduct an examination in which the year is divided into quarters so thatthe accuracy of PET estimation in seasons with small or great solar radiation can be examined.
ACKNOWLEDGEMENTS
This research was supported by the Grant-Aid from Tokyo University of Agriculture (TUA), Japan.
REFERENCES
Allen, R.G., Pereira, L.S., Raes, D. and Smith, M. 1998. Crop evapotranspiration, Guide-lines for computing
crop water requirements. In: FAO Irrigation and Drainage Paper No. 56, FAO, Rome, Italy, 300.
Pereiraa, L.S., Allenb, R.G., Smithc, M. and Raesd, D. 2015. Crop evapotranspiration estimation with FAO56,
Past and future. Agricultural Water Management, 147, 4-20.
Todorovic, M., Karic, B. and Pereira, L.S. 2013. Reference evapotranspiration estimate with limited weather data
across a range of Mediterranean climates. Journal of Hydrology, 481, 166-176.
Economic and Social Commission for Asia and the Pacific (ESCAP). 2015. Disasters in asia and the pacific,
2014 year in review, 3-4.

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Research article
erd

Determining C Factor of Universal Soil Loss Equation (USLE)
Based on Remote Sensing
KUANG TING KUO
Graduate School of Agriculture, Tokyo University of Agriculture, Tokyo, Japan
Email: kuokuangting0507@gmail.com

AYAKO SEKIYAMA
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan

MACHITO MIHARA*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Email: m-mihara@nodai.ac.jp
Received 4 December 2015

Accepted 31 October 2016(*Corresponding Author)

Abstract Soil erosion is a serious environmental problem which causes degradation of soil andwater environment. Thus, soil conservation is necessary for the areas where accelerated erosion
occurs. At early stages of soil conservation, certain strategies should be implemented based on
predicted soil erosion rate of the area. Soil erosion rate has been calculated using erosion
models, such as Universal Soil Loss Equation (USLE), Revised Universal Soil Loss Equation(RUSLE), Water Erosion Prediction Project (WEPP), etc. However, the most common model iseither Universal Soil Loss Equation (USLE) or Revised Universal Soil Loss Equation (RUSLE),
as they are easy in handling by users. Attention has been paid to Cropping Management, factor
C of USLE or RUSLE, since it is challenging to determine. The factor depends on the type ofcrop and the growing stage, however growing conditions would change locally and harvestingtime are unpredictable. Also, vegetation could be changed unpredictably due to weather or
farming conditions. Approaches based on remote sensing technology which has less temporaland spatial restrictions on detection of vegetation were applied to determine C factor using
vegetation indices. However, it is not always successful in field application. Therefore, theobjective of the study is to improve determination of C factor using vegetation indices. For
clarification, experiments for identifying the relationship between C factor and vegetation
indices such as Normalized Difference Vegetation Index (NDVI) and Soil-Adjusted Vegetation
Index (SAVI) were carried out under several types of soil. Furthermore, the accuracy ofdetermination of C factor using vegetation indices was discussed through an erosion modelexperiment. The results showed SAVI is more strongly correlated with C factor than NDVI.
Estimation of C factor based on NDVI and SAVI have 30% and 36% of relative error in field
application. Therefore, it was concluded that vegetation indices have high potential todetermine C factor of USLE or RUSLE. Also, estimation of field C factor based on SAVI ismore recommendable for determination of C factor in the field where there are several types ofsoil.
Keywords soil erosion, soil conservation, USLE, C factor, remote sensing, NDVI, SAVIINTRODUCTION
It is well known that accelerated erosion results in serious form of soil degradation, and pollutes thewater environment with component of nitrogen and phosphorous. Thus, soil conservation is necessary
for protecting soil and water areas, where accelerated soil erosion happens. At the early stage of soil
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conservation planning, soil erosion predicting model is employed for evaluating condition of local soil
erosion rate, before and after soil conservation strategies are applied. Many models have beendeveloped for predicting water-induced soil erosion rate. Especially, Universal Soil Loss Equation(USLE) and Revised Universal Soil Loss Equation (RUSLE) have been used to calculate annual soil
erosion rate (Wischmeier and Smith, 1978; Renard, 1997). USLE is empirical model, originallydeveloped to predict soil erosion rate, mainly in agricultural land. RUSLE is an advanced version withless limitation on application area. However, more details about field are required. Both USLE and
RUSLE have the same mathematic structure which can be written as follows:(1)

A= RKLSCP

Where A is soil erosion rate (ton/ha yr.), R is rainfall and runoff erosivity factor (MJ mm/ha h yr.),
K is soil erodibility factor (t ha h/ha MJ mm), LS is topographic factor comprised of slope length andslope gradient-slope steepness, C is Cropping Management factor, P is soil conservation practice factor.
(Revised) Universal Soil Loss Equation is most common model for soil conservation planning.
Determining LS factor and C factor is always challenging when applying (Revised) Universal Soil
Loss Equation in field. Complicated topographic feature causes difficulties in initial field datacollection for computing LS factor. Several proposed ideas indicate remote sensing has high potential
in estimating LS factor, in terms of high speed of execution and computing in topographic complex(Desmet, et al., 1996; Winchell, et al., 2008). Efforts linking LS factor and remote sensing have beensuccessfully carried out by processing topographic function in Geographic Information system (GIS)
with raster database of Digital Elevation Model (DEM). However, determining C factor still remains achallenge. C factor is defined as relative impact of vegetation reducing on soil erosion rate.
Determining C factor requires one to know about vegetation which is difficult to identify manually.
Remote sensing technology which has less temporal and spatial restrictions on detection of vegetation
were widely applied to determine field C factor using vegetation indices such as Normalize Difference
Vegetation Index (NDVI) (Van der Knijfff et al., 2000; Lin et al., 2002). However, it is not always
successful in field application (Alejandro, et al., 2007).
OBJECTIVE
Accordingly, the objective of the study is to improve determination of C factor using vegetation indices.
METHODOLOGY
Estimation of C Factor Based on Vegetation Indices
Required materials such as experimental plots, soil samples, canopies, portable spectroradiometer (MS720E), and white panel were prepared. Soil physical properties were analyzed and classified based on
IUSS method (Table 1). For each plot, same amount of soil samples was used and were randomly
planted canopies with coverage approximately ranging from 0% to 70%. In total, there were threedifferent kinds of treatments; (a) Andosol (1) + Ophiopogon japonicus (b) Ultisol + Ophiopogonjaponicus (c) Andosol (2) + Lolium perenne. At the beginning, white panel was used for calibrating
effect of shadow and spectra reflectance of red light and near-infrared red were measured in each plotby spectroradiometer outdoor (Fig.1). After reflectance spectra data of each plot was acquired,vegetation index was calculated as in Eq. (2) proposed by Deer (1978).
NDVI= (NIR-Red) / (NIR + Red)

(2)Ⓒ ISERD

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Where NDVI is Normalized Difference Vegetation Index calculated with function of reflectancedifferences between red and near infrared red (NIR), Red is reflectance of red light (630 nm - 690 nm)
and NIR is reflectance of near-infrared red (775 nm - 900 nm). Secondly, experiment of soil erosion
was conducted under artificial rainfall simulator for evaluating C factor (Fig. 2). Plots were placed on
slope of 8 degree under rainfall simulator. At each trial of rainfall simulation, rainfall intensity wasvaried from 36 to 120 mm/hr. for 30 minutes. Soil loss was collected after rainfall-simulation andmeasured by oven-drying for 24 hours. The weight of soil loss was used for computing C factor basedon the ratio of soil loss between the plots with bare soil and vegetation cover. Finally, the graph of therelationship between C factor and vegetation index was drawn. Besides, equation of C factor based onvegetation index was established by statistical regression analysis.
Table 1 Soil physical properties
Soil

Specific
gravity

Pacticle size distribution (%)
Gravel Coarse sand

Ignition

Fine sand

Silt

Clay

loss (%)

Soil texturea. Andosol (1)b. Ultisol

2.64
2.73

1.2
0.1

17.9
0.9

16.7
15.5

31.8
49.6

32.4
34.0

15
8

Sandy Clay Loam
Clay Loamc. Andosol (2)

1.53

2.4

4.2

9.9

27.0

56.5

64

Clay

Fig. 1 Experiment for evaluating
vegetation index

Fig. 2 Slope model experiment for evaluating
C factor

Field Measured C Factor
In this procedure, field C factor was measured in study area. Study area is located in Linkou distinct,
north part of Taiwan. It lies in 25°3′ to 25°9′ N latitude 121°17′ to 121°25′ E longitude (Fig. 3). Total
area of study is 54.15 km2. Forest and agriculture are main dominant land use pattern in Linkou distinct.
Annual average rainfall is about 2500 mm. Degree of soil erosion is influenced by changes ofvegetation and land use pattern. Main species of canopy in the field is Eremochloa ophiuroides(Munro).
To determine field C factor , parameters such as amount of annual soil erosion (A), rainfall andrunoff erosivity factor (R), soil erodibility factor (K), topographic factor (LS), Soil conservation
practice factor (P) were measured in the field. In addition, field measured C factor are computed basedon Eq. (3).
(3)

C= A / RKLSPAs the arrangement for measuring annual soil erosion (A) was illustrated in Fig.4, two poles wereinserted into ground surface tightly and deeply in the field. Initial difference of height for both sides ofⒸ ISERD

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the pole was 17.5 cm. Both side of the pole was connected with a baseline of 14.9 m long and wasgiven a mark at every 10 cm interval. After equipment was installed in the field, the height frombaseline to the ground was measured and recorded at interval of 10 cm. Experiment was conductedfrom 13 September, 2014 to 5 September, 2015. Changes of soil surface and dried density of soil wasmeasured to calculate total amount of soil erosion (A) in the field. Data of hourly rainfall from 2004 to2013 was collected from local weather station for calculating rainfall and runoff erosivity factor (R).
Soil erodibility factor (K) and topographic factor (LS) was computed based on field measurements andexperimental analysis. Soil conservation practice factor (P) was assumed as 1.

Fig. 3 Study area

Pole

Baseline

Eroded soil
2014/9/13

2015/9/14

Fig. 4 Observation of soil erosion in the field
Validation of Determination of C Factor Using Vegetation Indices
By comparing with field measured C factor, estimated C factor based on vegetation indices could bevalidated. Estimated C factor was derived by substituting monthly field vegetation index into C factor
equation based on NDVI. Moreover, monthly vegetation index was calculated as in equation (2) withdata of satellite-image of Landsat 7 from 2014 to 2015. The satellite-image was first downloaded fromwebsite of NASA and calibration of atmospheric effect was done by following instruction of Landsat 7
Handbook.
RESULTS AND DISCUSSIONⒸ ISERD

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Estimation of C Factor Based on Vegetation Indices
The estimation of C factor of USLE or RUSLE becomes challenging as land use pattern and vegetation
change (Alejandro, et al., 2007). It was thought that determining C factor using vegetation indices is
promising technology for responding to fast land use and vegetation changes. Lin (2002) stated that
there is linear correlation between C factor and NDVI. Moreover, Van der Knijfff (2000) presented
exponential C factor equation based on NDVI, which is applicable for environmental condition in
Europe. As results of experiments shown in figure 5, it shows linear correlation (R2 = 0.69) between C
factor and NDVI. The result is similar to approach of Lin (2002). Nevertheless, it was observed thatNDVI is highly variable as C factor equals to 1. It would decrease accuracy of estimation of C factor.
Therefore, Soil-Adjusted Vegetation Index (SAVI) presented by Huete (1988) was applied to improve
estimation of C factor. Equation of Soil-Adjusted Vegetation Index (SAVI) can be expressed asfollows.
(4)

SAVI= (NIR-Red) (1+L)/ (NIR+ Red+ L)

Where L is an adjustment length and it was assumed as 0.5. In Fig. 6, the relationship between
SAVI and C factor was shown. The results indicated SAVI is more strongly correlated with C factor
than NDVI. Correlation R2 increases from 0.69 to 0.73. Huete (1988) indicated estimation ofvegetation based on SAVI is less affected by soil background. It means estimation of C factor based on
SAVI is more accurate than NDVI in the field where there are several types of soil. Besides, it wasobserved that there is less variation in SAVI than NDVI under bare soil (Table 2). Moreover, it wasobserved that equation established by statistical regression analysis (Figs. 5 and 6) has similarmathematic structure which could be defined as follows:(5)

C= -a VI + 1; VI <0, C=0

Where C is cropping management factor, VI is vegetation indices which represents vegetation
signal response of canopy, and a is defined as efficiency of vegetation in reducing soil erosion rate.
The a is equal to 0.82 when VI is NDVI, and a is equal to 1.18 when VI is SAVI. It was consideredthat the value of a may decrease as height of vegetation increases because higher vegetation has lower
efficiency in reducing soil erosion rate (Wischmeier and Smith, 1978; Renard, 1997). In the case of
study, heights of vegetation were about 5 cm to 15 cm.
Table 2 Comparison of NDVI and SAVI under bare soil
Bare
soil

Max.
0.30

NDVI
Min.
0.06

Sd.
0.07

Max.
0.16

SAVI
Min.
0.03

Sd.
0.03

Sd. is standard deviation

Field Measured C Factor
About 72 ton/ha/yr. of soil loss (A) was observed in the field (Fig. 8). Moreover, field measured C isequal to 0.56 which is calculated by following parameters summarized in Table 3.
Validation of Determination of C Factor Using Vegetation Indices
The results of monthly NDVI and SAVI (Fig. 7) are shown. Moreover, estimated C factor based on
different approaches were summurized in table 4. It was observed that estimated C factor based on bothⒸ ISERD

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NDVI and SAVI are higher than field C factor. Moreover, although SAVI is more strongly correlatedwith C factor than NDVI (Figs. 5 and 6), estimation of C factor based on NDVI is most accurate with
30 % of relative error. It was considered that estimation of C factor based on SAVI becomes accurate
as different types of soil is existed in the field. However, only single type of soil (Ultisol) was found in
the field. Furthermore, it was observed that both estimated C factor based on NDVI and SAVI are
more accurate than appoach of Lin (2002).
1.00
y = -0.8158x + 1
R = 0.69**

0.80
C factor

0.60
0.40
0.20
0.00
0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

NDVI
Andosol (1) + Ophiopogon japonicus

Ultisol + Ophiopogon japonicus

Andosol (2) + Lolium perenne

C factor

Fig. 5 Relationship between C factor and NDVI
1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00

y = -1.175x + 1
R = 0.7321**

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

SAVI
Andosol (1) + Ophiopogon japonicus

Ultisol + Ophiopogon japonicus

Andosol (2) + Lolium perenne

Fig. 6 Relationship between C factor and SAVI
Table 3 Parameters for calculating C factor in the field
A

R

K

L

S

P

Field measured C factor

72

8135

0.02

0.82

0.96

1

0.56

Table 4 Comparison of field C factor with different C factor approaches
C factor

C factor

Relative

C factor

Relative

C factor

Relative(Field)(NDVI)

error %(SAVI)

error %

(Lin, 2001)

error %

0.56

0.73

30%

0.76

36%

0.33

45%

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0.50
0.45
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00

NDVI
SAVI

9

10

11

12

1

3

5

8

10

Date (2014-2015)

Length from baseline to ground(cm)

Fig. 7 Variation of vegetation indices from 2014 to 2015
60
50
40

2014/9/13
2015/9/14

30
20
10
0
0

100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400

Distance (cm)Fig. 8 Changes in heights from baseline for evaluating annual soil loss in the field
CONCLUSION
Therefore, it was concluded that (1) vegetation indices have high potential to determine C factor of
USLE or RUSLE, (2) estimation of field C factor based on SAVI is more recommendable fordetermination of C factor in the field where there are several types of soil. For the future research plan,
the experiment for evaluating the relationship between C factor and vegetation indices will be
conducted in other different kinds of vegetation and soil. Also, more field erosion model experiments
will be conducted for validating determination of C factor using vegetation indices.
ACKNOWLEDGEMENTS
We would like to thank Prof. Dr. Shimada Sawahiko for his invaluable research advices and equipment
rentals. Our sincere gratitude is also accorded to Mr. Kuo Mingchi and Watanabe Motohiro for theirkind assistance in initial data collection in the field and experimental supports.

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REFERENCES
Alejandro, M.de Asis and Omasa, K. 2007. Estimation of vegetation parameter for modelling soil erosion using
linear spectral mixture analysis of landsat ETM data. ISPRS Journal of Photogrammetry & Remote Sensing,62, 309-324.
Desmet, P.J.J. and Govers, G. 1996. A GIS procedure for automatically calculating the USLE LS factor on
topographically complex landscape units. Journal of Soil and Water Conservation, 51, 427-433.
Huete, A.R. 1988. A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25, 295-309.
Jackson, R.D. and Huete, A.R. 1991. Interpreting vegetation indices. Prev. Vet. Med., 11, 185-2000.
Lin, C., Lin, W. and Chou, W. 2002. Soil erosion prediction and sediment yield estimation, The Taiwan
experience. Soil & Tillage Research, 68, 143-152.
Renard, K.G., Foster, G.R., Weesies G.A. and Porter, J.P. 1991. RUSLE, revised universal soil loss equation.
Journal of soil and water conservation, 46 (1), 30-33.
Van der Knijfff, J.M., Jones, R.J.A. and Montanarella, L., 2000. Soil erosion risk assessment in Europe. Officeand Official Publications of the European Communities, Luxembourg, 1-32.
Winchell, M.F., Jackson, S.H., Wadley, A.M. and Srinivasan, R. 2008. Extension and validation of a geographic
information system-based method for calculating the revised universal soil loss equation length-slope factor
for soil risk assessment in large watershed. Journal of Soil and Water Conservation, 63 (3), 105-111.
Wischmeier, W.H. and Smith, D.D. 1978. Predicting rainfall erosion losses, A guide to conservation planning,
USDA Agriculture Handbook No. 537.

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Research article
erd

Factors Affecting Householders’ Acceptance to Adopt Reduce,
Reuse and Recycle - 3Rs Program in Domestic Waste
Management in Mekong Delta, Vietnam
NGO THI THANH TRUC*
Can Tho University, Can Tho, Vietnam
Email: ntttruc@ctu.edu.vn

NGUYEN THI THU TRANG
National Taiwan University, Taipei, Taiwan
Received 12 January 2016

Accepted 3 November 2016(*Corresponding Author)

Abstract Reduce, reuse and recycle (3Rs) is one of the elements contributing to the success oflaunching the integrated solid waste management recommended by the United Nations
Environment Program. A survey of 360 urban and suburban household respondents was
conducted in the Mekong Delta, Vietnam to understand how domestic solid waste managed athousehold level, to experience respondents’ knowledge, awareness and their acceptanceparticipating 3Rs program if it is introduced in the Mekong Delta. Results show that 78%
respondents sold recyclable waste and listed activities meaning reducing, reusing and recycling
solid domestic waste. More than 70% respondents supported this program when it is launched.
The results of the logit model reveal the significant difference in factors affecting urban andsuburban respondents’ acceptance this program. Age, gender and educational attainment ofrespondents, household income, respondents’ knowledge on reduce, reuse and recycle theirsolid domestic waste and community participation are factors affecting household acceptanceinvolving in 3Rs. They also propose how to organize successful 3Rs program, namely thecollaboration between household and local community in organizing this program, upgrading
households’ awareness on environmental protection and the support in propaganda of local
authorities and social media.
Keywords domestic solid waste, 3Rs, reduce, reuse, recycle, Mekong Delta

INTRODUCTION
Domestic solid waste has increased rapidly in Vietnam and other Southeast Asian countries (Rathi,
2006; Visvanathan and Tränkler, 2003; Bai and Sutanto, 2002). However, it has not been managed
properly, especially in Vietnam (Trang, 2012; Hoang and Viet, 2011 and Thanh et al., 2010). In the
Mekong Delta, Vietnam, solid waste increases about 10 - 16% annually and about 5,3 million tons ofdomestic solid waste is generated per day in the Mekong Delta (about 0.3 kg per capita per day)
(Hoang and Viet, 2011 cited from MONRE, 2010). However, only 65 -72% of them is collected thatmost of them are dumped at the landfill.
Reduce, reuse and recycle – 3Rs is one of the suggested solutions for the integrated solid waste
management recommended by the United Nations Environment Program (Bernstad, 2014; Tai et al.,2011; Uyen and Hans, 2009). The purpose of 3Rs is to minimize waste generation or disposal and it isa waste hierarchy, the first step, in managing domestic solid waste at source. However, 3Rs has notbeen widely propagandized and practiced in the Mekong Delta, Vietnam. Thus, this case study was
conducted in the Mekong Delta, Vietnam to understand how domestic solid waste is managed at a

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household level to experience respondents’ knowledge, awareness and their acceptance participating
3Rs program if it is introduced in the Mekong Delta, Vietnam.
METHODOLOGY
Study Sites and Methods of Data Collection
A survey of 360 respondents was conducted in six urban and suburban wards/town in four provinces
and cities in the Mekong Delta, Vietnam (Fig 1). Domestic solid waste in those urban sites have beencollected for many years while solid waste collection service has just been provided in three suburban
areas recent 2-3 years. The respondents are the persons in the households that fully understand how
their domestic waste generation and management. Purposive sampling technique was applied with theguide of the head of each ward/town to avoid bias.

Fig. 1 Map of study sites in Mekong Delta, Vietnam
Note: Red is urban sites and pink is suburban sites

Data Analysis
The surveyed data were analyzed descriptively using frequency, descriptive and cross tabulation, T-test
and chi-square to describe the socio-demographic characteristics of respondents and households,
households’ solid waste generation and management, respondents’ awareness and acceptance 3Rs in
the urban and suburban areas in the Mekong Delta, Vietnam.
Model to Identify Factors Affecting Respondents’ Acceptance 3Rs ProgramAn assumption was created that 3Rs program will be launched to those six urban and suburban sites in
the Mekong Delta. Full introduction about the meaning and examples how householders practice 3Rs
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adopt this program when would be launched. The follow-up questions were the reasons why they
accepted or not to adopt this program and how to organize successfully this program.
The binary logistic regression model was applied to find out the factors affecting respondents’
acceptance to practice 3Rs program. The model is as follows.
ln

Yi

Pi
1  Pi

EiXi  D

Where Yi is respondents’ acceptance to apply 3Rs program when it is introduced to their sites. Y i= 1: accepted and Yi = 0: not accepted). i =1 is represented for 360 respondents i= 2 and 3 are urban
and suburban sites respectively (180 respondents). βi are the coefficient of the explanatory variables(Xi). The explanatory variables are defined in Table 1. The explanatory variables were based onhouseholds’ socio-demographic characteristics, respondents’ knowledge and awareness how to practice
3Rs at household solid waste management are major factors influencing 3Rs practices (Bernstad, 2014;
Miafodzyeva and Brandt, 2014; Singhirunnusorn et al., 2012; Banga, 2011; Farley, 2011; MoEF, 2010;
Uyen and Hans, 2009; Shafeeqa et al., 2009; Gamba and Oskamp, 1994).
Table 1 Description of variable in the logit model
Var.

Description

X1

Area of survey, X1 = 1: urban area, otherwise,
X1 = 0: rural area
Age of respondents (years)
Gender of respondents, X2 = 1: male, otherwise
X2 = 0: female

X2
X3

Expected
signs+/-

Characteristics
50% urban area++/-

45.2±11.9 years
40% male respondents

X4

Educational attainment of respondents,
X4 = 1: attended high school (grade 10) or
higher, otherwise X4 = 0+/-

64% respondents’ educational attainment
equal or higher high school (grade 10)

X5

Gross household income(VND/month)
Aware using friendly products means reducing
waste, X6=1: yes, otherwise X6=0
Reuse carton boxes means reuse waste,
X7=1: yes, otherwise X7=0
Household selling recycle waste, X8 = 1: yes,otherwise X8 = 0
The participation of the local community andgovernment contribute to the success of 3Rs
program, X9 = 1 yes, otherwise X9 = 0+/+

10±8 million VND/month~ 450±374 USD/month
44% respondent’s awareness of reduce+

58% respondent’s awareness of reuse

X6
X7
X8
X9

78 % household selling recycle waste+

49% respondents reveal that collaboration
between local community and government
will contribute to the success of 3Rs program

RESULTS AND DISCUSSION
Respondents and Households’ Characteristics in the Mekong Delta, Vietnam
Among 360 respondents, 50% of them is from urban areas and 40% of them is male (Table 1). The
average age is 45.2 ± 11.9 years and 64% reach high school or higher. There are 4.2 ± 1.4 members ina household with 2-3 members are in the working age. The average gross household income is about
10 million VND per month (~ 450 USD/month).

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Management of Households’ Domestic Waste in the Mekong Delta, Vietnam
The waste quantity is generated about 1.9 ± 1.0 kg per household per day and more waste is disposedin the urban than in the suburban areas (Table 2). The persons who dispose their household waste to
the common trash bin or waste truck are more female (61%) than male (16%) and 23% both male andfemale in the household takes turn to dispose their waste. Plastic bags and trash bins are the most used
for waste containers. Each household has 1-3 trash bins and place them in the kitchen or back-yard.
About 78.3% household sell recycle waste. The most recycle waste is used bottles or jars, carton boxes,
cans and books or newspapers. They earn about 79,000 ± 83,000 VND per quarter (~3.6 ±3.7 USD).
Table 2 Current situation and management of domestic waste of household in Mekong Delta
Urban

Characteristics

n=180
Waste generation (kg/day/household)
2.0± 1.1% of HH selling recycle waste
79.4
Recycle trash (%)
n=139
Used bottles or jars
73.4
Used carton boxes
59.7
Beer cans
58.3
Used books or newspapers
45.3
Others39.6
Return from selling recycle trash (thousand VND/quarter)
89± 90Note: ***, ** and * mean significant different at 1%, 5% and 10%, respectively

Suburbann=1801.7± 0.9
77.2
n=143
90.2
56.6
45.5
29.4
18.9
105± 90

Total
n=360
***
1.9±1.0
78.3
n=282
81.9 ***
58.2 *
51.8 **
37.2 ***
29.1 ***
79±83 ***

Respondents’ Awareness on Reuse, Reduce and Recycle (3Rs) in Domestic Waste Managementin the Mekong Delta, Vietnam
Most of respondents listed activities meaning to reduce, reuse and recycle waste (Table 3). Even theirunderstanding is simple, it would contribute to the success of introducing this 3Rs program to the
public. The presence of plastic bags and containers are the main causes of increasing waste generation.
Table 3 Respondents’ awareness on 3Rs in domestic waste managementin the Mekong Delta, Vietnam
Respondents’ awareness on 3Rs
How to reduce waste generation (%)
Only buy necessary goods
Buy endurable products
Buying in bulk rather than individuals
Use environmental friendly products
Bring reusable bags when shopping
Use reusable food containers
Use glasses or bottles for buying drinks
How to reuse waste (%)
Reuse used plastic bags
Reuse used bottles
Reuse used rubber and plastic bands
Donate used clothes, shoes or notebooks
Rese carton box to keep things
OthersHow to recycle waste (%)
Recycle is selling recycle trash
Recycle is to recreate useful things from trash
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Urban(n=180)Suburban(n=180)Total(n=360)

71.7
75.0
57.2
43.3
42.2
36.1
27.8

96.1
89.4
60.0
45.6
44.4
25.6
27.8

83.9
82.2
58.6
44.4
43.3
30.8
27.8

71.7
62.2
66.7
71.1
53.3
31.7

86.1
77.2
61.1
49.4
61.7
5.0

78.9
69.7
63.9
60.3
57.5
18.3

56.7
51.7
34.4

75.6
64.4
40.6

66.1
58.1
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People do not bring containers or reusable bag when go shopping or buy food and drink. The
convenience of small containers also causes more waste. Providing plastic bags to buyers is perceived
politeness and care by sellers as results from our study.
The results indicate that respondents often reuse plastic bags, bottles, rubber bands, clothes,notebooks, shoes and carton boxes (Table 3). More people in suburban reuse those things than in theurban areas. The reuse practice is not only mean saving, but it is also a habit of care users. The
convenience and household wealth restrict people to reuse things. That is important point that needs toupgrade residents’ behavior in reuse things to reduce waste generation and environmental protection.
The same with the first two Rs – reduce and reuse, recycle is more popular for poor people.
Respondents often sell recycle waste and recreate useful things from trash (Table 3). More residents inthe suburban sell recycle waste than in the urban areas. Price of recycle waste and household wealthalso restrict recycle behavior. Due to the goods cost is low and mostly is not included cost of the waste
disposal, their price is lower and thus it leads people lazy to sell recycle waste. Residents recycle waste
due to the economic benefit rather than to reduce waste generation or environmental protection.
Factors Affecting Respondents’ Acceptance to adopt 3Rs program in the Mekong Delta, Vietnam
After receiving information about the proposed 3Rs program, 72% of the respondents accept topractice this program. More suburban residents (79%) prefer this program than urban residents (66%).
The result of the logit models is presented in Table 4.
Table 4 Factors affecting respondents’ acceptance to adopt the 3Rs program in the Mekong
Delta, Vietnam
Variables
Total
Urban
Regions-0.118 ***Ages of respondents-0.031 **-0.024
Genders of respondents-0.349-1.114
Educational attainment of respondents
0.727 **
1.226 ***
Gross household income per month
0.000 *
0.000
Aware on reduce waste generation
0.262
0.428
Aware on reuse waste generation
0.396
0.675 ***
Practice selling recycle waste
0.547
0.587
Community
0.020 ***
0.011
Constant
0.406-0.596
No. of observation
360
180
Percentage of acceptance (%)
72
66
Log likelihood-303.033-195.057
R2
0.279
0.251
Note: Number in the table is the coefficient of the logit model***, ** and * indicate statistical significance at 1%, 5% and 10% levels, respectively
X1
X2
X3
X4
X5
X6
X7
X8
X9

Suburban-0.056 **-1.165 **-0.0660.000-0.146
0.675 ***
0.587
0.011
-0.596180
79-94.714
0.247

There are differences in the results in three logit models. More suburban respondents accepting
this program if it is introduced. The significant factors of these models confirm the characteristics of
respondents and households (age, gender, educational attainment of respondents and householdincome) affecting the acceptance of this program (Banga, 2014; Miafodzyeva and Brandt, 2013).
Besides, the awareness of reduce and reuse waste generation also affect their acceptance (Banga, 2014;
Miafodzyeva and Brandt, 2013; Farley, 2011; Uyen and Hans, 2009; Shafeeqa et al, 2009). Lastly, thecollaboration between the local residents and the government is the factor affecting for the success ofthe 3Rs program (Challcharoenwattana and Pharino, 2015; Miafodzyeva and Brandt, 2013; MoEF,
2010).

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Besides, respondents recommend that the collaboration between the local residents andgovernment, residents ‘awareness on environmental protection and preserve the environment for the
future as well as the propaganda for the program are factors contributing to the success when 3Rs
program is launched. The most effective modes of communication for this 3Rs program are television,
local propaganda, radio/radio station. Besides, local information exchange, newspapers, internet andproviding 3Rs information through the basic schools.
CONCLUSION
3Rs program should be introduced and propagandized widely in the Mekong Delta as well as the whole
Vietnam. It will be the start hierarchy to improve domestic solid waste management in the Mekong
Delta through minimizing waste generation and make use of waste before disposal and dumping. The
3Rs program should incorporate the linkage of individual – community performance and social media
to upgrading households’ awareness on environmental protection and successfully launch this programin the Mekong Delta and Vietnam.
ACKNOWLEDGEMENTS
The authors are grateful to Le Thi Thuy Duyen, Lam Nguyen Nguyen Hanh, Dinh Van Nghia, Le Thi
Bich Ngoc, Le Thu Trang for their participation and contribution in this study.
REFERENCES
Bai, R. and Sutanto, M. 2002. The practice and challenges of solid waste management in Singapore. Waste
Management, 22 (5), 557-567.
Banga, M. 2011. Household knowledge, attitudes and practices in solid waste segregation and recycling, Thecase of Urban Kampala. Zambia Social Science Journal, 2 (1), 27-39.
Bernstad, A. 2014. Household food waste separation behavior and the importance of convenience. Waste
Management, 34, 1317-1323.
Farley, F. 2011. Information for primary school teachers. Environmental Awareness, Deutsche Gesellschaft fürInternationale Zusammenarbeit (GIZ) GmbH.
Gamba, R.J. and Oskamp, S. 1994. Factors influencing community residents' participation in commingled
curbside recycling programs. Environment and Behavior, 26 (5), 587-612.
Hoang, N.X. and Viet, L.H. 2011. Solid waste management in Mekong Delta. Journal of Vietnamese
Environment, 1 (1), 27-33.
Miafodzyeva, S. and Brandt, N. 2013. Recycling behaviour among householders, Synthesizing determinants via a
meta-analysis. Waste and Biomass Valorization, 4 (2), 221-235.
Ministry of Environment and Forests (MoEF). 2010. National 3 R strategies for waste management. Governmentof the People’s Republic of Bangladesh.
Rathi, S. 2006. Alternative approaches for better municipal solid waste management in Mumbai, India. Waste
Management, 26 (10), 1192-1200.
Shafeeqa, F., Jaleel, M., Glen, E., Seddon, G. and Shazna, M., 2009. Waste awareness resource kit, Community,
environment research centre and live & learn environmental education.
Singhirunnusorn, W., Donlakorn, K. and Kaewhanin, W. 2012. Contextual factors influencing household
recycling behaviours, A case of waste bank project in Mahasarakham Municipality. Procedia-Social and
Behavioral Sciences, 36, 688-697.
Tai, J., Zhang, W., Che, Y. and Feng, D. 2011. Municipal solid waste source-separated collection in China, A
comparative analysis. Waste Management, 31 (8), 1673-1682.
Thanh, N.P., Matsui, Y. and Fujiwara, T. 2010. Household solid waste generation and characteristic in a Mekong
Delta city, Vietnam. Journal of Environmental Management, 91 (11), 2307-2321.
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Trang, T. 2012. Solid waste management, Difficult problem of Vietnam. Journal of Techonology. Term 1.
Septmber, 2012. 44-45. (in Vietnamese). Retrieved from http://www.vjol.info/index.php/bct-cn1/article/view/9983, 20/10/2015.
Uyen, N.N. and Hans, S. 2009. Sustainable solutions for solid waste management in southeast Asian countries.
Waste Management, 29, 1982-1995.
Visvanathan, C. and Tränkler, J. 2003. Municipal solid waste management in Asia, A comparative analysis.
Workshop on Sustainable Landfill Management.
Challcharoenwattana, A. and Pharino, C. 2015. Co-benefits of household waste recycling for local community’ssustainable waste management in Thailand. Sustainability 2015, 7, 7417-7437.

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Research article
erdEarthworm Communities and Activities in Rice Ecosystem
under Different Soil Salinity Levels in Northeast Thailand
AJCHARAWADEE KRUAPUKEE
Land Resources and Environment Division, Faculty of Agriculture, Khon Kaen University,
Khon Kaen, Thailand

CHULEEMAS BOONTHAI IWAI*
Integrated Water Resource Management Resource and Development Center in Northeast Thailand,
Khon Kaen University, Khon Kaen, Thailand
Email: chulee_b@kku.ac.th

NARUMOL KAEWJAMPA
Faculty of Forestry, Kasetsart University, Bangkok, Thailand
Received 16 January 2016

Accepted 10 November 2016(*Corresponding Author)

Abstract Soil salinity is one of the most serious agricultural problems. This problem generates
low soil productivity and soil ecosystem. Earthworms are one of the most important soilorganisms in soil ecosystem (maintaining soil structure and the fertility of soil). Soil salinity has
become one of the major determinants of crop productivity in Northeast Thailand. The aim ofpresent study was size and composition of earthworm communities on related soil properties
and rice growth under different soil salinity; 2 levels 1) low soil salinity (EC 2-4 dS/m) and 2)
moderate soil salinity (EC 4-8 dS/m). Soil and earthworm cast were collected to analyze for soil
chemical properties. The results showed that there was significant difference between density
and size of different species of earthworms in different level of soil salinity. In rice ecosystem
in moderate salt-affected area the earthworm species Drawida beddardi was the only one foundat 95 days after rice sowing, while in low salt affected area the earthworm species, Glyphidrilus
chiensis and Drawida beddardi were the most common species found at 45 days after ricesowing. Earthworms improve soil properties and rice growth rate. Oryza sativa L. (Khao Dawk
Mali 105 and RD6) growth decreased with increasing levels of soil salinity.
Keywords earthworm, rice ecosystem, salt-affected area

INTRODUCTION
Increasing soil salinity is a serious land degradation issue worldwide. Thailand salinization is amongst
the major degradation processes endangering the potential use of Northeast Thailand soils. Despite of
the naturally occurring salinization, deicers for removal from salt-bearing rocks (Land Development
Department, 1991) in the Nakhon Ratchasima, Khon Kaen, Roi-Et and Mahasarakham provinces(Department of Mineral Resources, 1982). Salts have negative effects on ecosystem and environments
have appeared increasingly. Sodium chloride (NaCl) from salt-bearing rocks is responsible for theincreased salinity of soil surface and ground waters. Chloride accumulation can compromise soil
structure and increase soil erosion, reduce soil fertility, and have an effect on soil chemistry. Salts
negatively affect environmental ecosystems crop yield (Grewal, 2010; Li et al. 2010; Zhang et al.
2010), soil microorganisms (Yuan et al., 2007; Ibekwe et al., 2010), plants (Gadallah and Ramadan,
1997; Joutti et al., 2003; Ruhland and Krna, 2010), and soil organisms (Owojori et al., 2008). There
has been a growing concern of the environmental effects resulting from deicing.
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Earthworms are soil engineers, they have potential to improve soil properties, physical, chemical,
and biological (Jouquet et al., 2009). Earthworm cast is usually chemical and physically protected andstabilizes aggregate and SOM in soil and (Bossuyt et al., 2005; Jouquet et al., 2008a; Chutima et al.,2010). There is also the positive influence of earthworms on soil structure (Mackay and Kladivko,
1985; Ketterings et al., 1997) and plant growth and yield (Scheu, 2003; Eisenhauer et al., 2009).
Although, most of the published works which reported earthworm aerobic ecosystems, very few
studies were carried out in partially or totally flooded environments, such as paddy fields. Flooding
events are considered as adverse periods limiting the activity of macrofauna such as earthworms(Schütz et al., 2008; Chutima et al., 2010).
OBJECTIVE
The aim of this paper was to monitor the diversity and size of earthworm species in rice ecosystem andinfluences of earthworm on soil properties and rice growing in salt-affected area.
METHODOLOGY
Study Site
Studied in paddy field salinity area Phai district, Khon Kaen province during rainy season 2014, wereselected area from map of the distribution of saline soil Land Development Department 5 Khon Kaen,
two levels salinity, 1) low soil salinity (EC 2-4 dS/m) and 2) moderate soil salinity (EC 2-4 dS/m).
These are areas sowing jasmine rice 105 and sticky rice RD 6, samples of soil rice growing andearthworms in three replicates.
Statistical Analyses
The data collected were statistically analyzed using analysis of variance techniques. Statistical analysis
was performed employing Statistics 8.0 (Analytical Software, 2003). Mean comparisons of different
treatments were done by least significant difference (LSD) and standard error of the difference (SED).
RESULTS AND DISCUSSION
Distribution of Earthworm
Distribution of earthworm population is highest on low salinity area (EC 2-4 dS/m-1) about 280(Juvenile and Adult) earthworm number per m2 (Table 1), found earthworm activities Glyphidrilus
chiensis and Drawida beddardi species (Fig. 1) at 45 days after rice sowing. Moderate soil salinity (EC2-4 dS/m) D. beddardi is found only specie in this area about 20 (Adult) earthworms per m2, they had
activity at 95 days after rice sowing. Chanaban et al. (2013) have discovered a new earthworm species
in the genus Glyphidrilus in paddy fields Northeast of Thailand. Earthworm species is most commonly
found in paddy soil. Ivask and et al. (2007) study of earthworm’s community in coastal areas andgrasslands, flooded areas has lower earthworm’s species. Thibaud et al (2003) reported factors thathave influence on earthworm diversity environmental conditions, physical and chemical properties ofsoil, topography, climate and humans (agriculture and pollution).

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Table 1 Diversity of earthworms in rice ecosystem under different soil salinity levels in Banpai
district, Khon Kaen province
Rice ecosystem under different soil
salinity levels

Stage of earthworm
Juvenile
Adult)Number/ m2(

Species

Low soil salinity- found earthworm activities at 45 days
after rice sowing
Moderate soil salinity- found earthworm activities at 95 days
after rice sowing

Glyphidrilus chiensis
Drawida beddardi

196 ±13.2
48 ± 4.4

28 ±3.1
8 ±2.1Glyphidrilus chiensis
Drawida beddardi-

20 ±2.1

Mean (n=3)

Drawidabeddardi
Glyphidrilus
chiensisFig. 1 Earthworm species Glyphidrilus chiensis and Drawida beddardi
in rice ecosystem under different soil salinity levels
Earthworm Activities on Soil Properties
The results of earthworm activities on soil chemical properties showed OM, pH, total N, available P
and K in cast were increased. Earthworm activities have decreased soil EC (Table 2). Soil salinity
reduces soil fertility, to have an effect on soil chemistry. Salts negatively affect environmental
ecosystems crop yield (Grewal, 2010; Li et al. 2010; Zhang et al. 2010), soil microorganisms (Yuan etal., 2007; Ibekwe et al., 2010), plants (Gadallah and Ramadan, 1997; Joutti et al., 2003; Ruhland andKrna, 2010) and soil organisms (Owojori et al., 2008). Earthworms decompose organic matter andrelease plant nutrients into the soil such as ammonium nitrate, exchangeable potassium etc. and plant
growth hormones and vitamins.
Table 2 Earthworm cast properties in rice ecosystem under different soil salinity levels in
Banpai district, Khon Kaen province
Rice ecosystem under
different
soil salinity levels
low soil salinity)EC = 2-4 dS/m)moderate soil salinity)EC = 4-8 dS/m)
Mean (n=3)

soil
cast
soil
cast

OM

pH

EC

Total N

Avai P

K

%

(1:5)

(dS/m)

%

ppm

ppm

0.84
2.08
0.78
1.88

6.6
7.5
6.4
7.1

0.29
0.11
0.65
0.46

0.1
0.4
0.1
0.4

5.39
11.58
2.62
5.12

42.83
139.6831.17
100.37

Earthworm activities on rice growth under different soil salinity levels
Statistical analyses showed that the influence of earthworm activity with earthworm cast and salinity
levels on rice number per m2 and height of rice (Table 3) Jouquet et al. (2008b) showed that casts
produced by Glyphidrilus sp. can be considered as patches of nutrients in paddy fields in NortheastⒸ ISERD

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Thailand. In Africa, Owa et al. (2003) also observed faster rice development and greater productivity
when earthworm casts were associated to rice plants.
Table 3 The growth of rice ((Oryza sativa L.) KhaoDawk Mali 105 and RD6) under different
soil salinity levels
Number of plant
Height of plant(m2)
flowering stage (cm)Low soil salinity growing KhaoDawk Mali 105
35.32
92.13 abc
Low soil salinity growing RD6
30.00
103.07 aModerate soil salinity growing KhaoDawk Mali 105
19.00
81.63 cModerate soil salinity growing RD6
24.64
97.20 abF-testns*
C.V. (%)
48.11
8.11
Remark: Mean (n = 3) in the same column followed by the same lower case letters are not significantly different
at |p| ≤ 0.05 (LSD)
Rice ecosystem under different soil salinity levels

CONCLUSION
Within the rice ecosystem in low salt affected area (EC 2-4 dS/m), the earthworm species, Glyphidrilus
chiensis and Drawida beddardi were the most common species found at 45 days after rice sowing (280
earthworms per m2), while in moderate salt-affected area (EC 4-8 dS/m) the earthworm species G.
chiensisis was the only specie found at 95 days after rice sowing (20 number of earthworm per m2).
Oryza sativa L. (Khao Dawk Mali 105 and RD6) growth decreased with increasing levels of soil
salinity. Soil salinity influences the distribution of earthworm and rice growth. In salt-affected area
earthworms play a main role on maintaining soil fertility, soil chemical properties, soil microbialcommunities and soil physical properties.
ACKNOWLEDGEMENTS
This study is supported by Integrated Water Resource Management and Development Center inNortheast, Thailand, Khon Kaen University, Thailand. Special thanks to the Research Developing and
Learning Centre on Earthworm for Agriculture and Environment for facilities provided. Thanks, areextended to the Division of Land Resource and Environment, Faculty of Agriculture, Khon Kaen
University for the support of equipment for laboratory testing.
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Research article
erd

Spatial Analysis of Ecosystem Disservice via Disamenity ofMosquitoes – A Case Study in Nagoya City, Japan
KIICHIRO HAYASHI*
Nagoya University, Nagoya, Japan
Email: maruhaya98--@imass.nagoya-u.ac.jp

AKIRA SUGIYAMA

Nagoya Women’s University, Nagoya, Japan

MAKOTO OOBANational Institute for Environmental Studies, Miharu, Japan
Received 16 November 2015

Accepted 10 November 2016(*Corresponding Author)

Abstract Nature provides many benefits to human society, known as ecosystem services (ESs),
and also has negative impacts on human society, known as ecosystem disservices (EDSs).
Mosquitoes contribute to EDSs, such as the risk of disease, the disamenity of mosquito bites.
The purpose of this study was to understand the factors of EDSs caused by mosquitoes,
employing a case study in Nagoya City, Japan. Mosquitoes were collected by CDC (Center for
Disease Control) CO2-baited traps. Also a questionnaire survey of Nagoya citizens was
conducted to assess the disamenity level of mosquitoes. Many variables, such as land use type,were developed by geographical information system (GIS). Statistical analyses were conducted
to identify the main factors of mosquito abundance and disamenity. Important factors wereidentified for both mosquito abundance and its disamenity. Further studies, including multipoint trap surveys and more detailed spatial studies, are required to elucidate these aspects.
Keywords ecosystem service, ecosystem disservice, mosquito, biodiversity, GIS

INTRODUCTION
Nature provides many benefits to human society, known as ecosystem services (ESs), which include
carbon absorption, water regulation, timber supply, and water cycling, among others (Millennium
Ecosystem Assessment, 2005). Nature also has negative impacts on human society, known as
ecosystem disservices (EDSs), which include agricultural pests and vectors of diseases, etc. (Lyytimäki
and Sipilä, 2009; Escobedo et al., 2011). The use of the concept of EDSs is relatively limited (Ango etal., 2014). Mosquitoes (MQs) are considered an EDS because they are disease vectors and also becauseof their disamenity effect. Numerous studies have already been conducted on MQs as a public healthissue (Eshita and Kurihara, 1978; Kobayashi et al., 2002; Tsuda et al., 2006; Tsuda 2011, 2013).
According to Tsuda (2011), the main purpose of MQ studies in Japan was to establish the distribution
status of MQ species to assess the risk of diseases caused by them, as opposed to developing countermeasures for potential diseases. Kamimura (1968) reported that Aedes albopictus (Skuse) was one ofmain MQ species appearing in residential areas in Japan. In Nagoya City, the third largest city in Japan,
the most abundant MQ species were Culex pipiens group and Ae. albopictus (Sugiyama, 2007; Yokoi,
et al., 2014; Nagoya City, 2015). To date, many studies, especially from a public health perspective,
have been conducted on Ae. albopictus (Takagi et al., 1995; Tsuda et al., 2003; Tsuda and Kim, 2012).
With the technological advancement in the geographical information system (GIS) and remote sensing,studies on the relationship between land use and MQ distribution is an emerging area of researchⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2016) 7-2(Johnson et al., 2008; Yonejima et al., 2011; Landau and van Leeuwen, 2012). However, there arelimited studies on the EDSs of MQs, e.g., the level of disamenity, because disamenity depends on the
citizens’ subjective assessment. The GIS studies and factor analyses of MQ’s EDSs, especially Ae.
albopictus have been limited to urban areas in Japan.
OBJECTIVE
The aim of this study was to understand the main factors of EDSs, focusing on the disamenity of MQs(especially for, Aedes albopictus (Skuse)), using MQ traps and a questionnaire survey of the subjective
assessment by citizens in Nagoya City, Japan.
METHODOLOGY
Nagoya City (the city hall: 35.181°N, 136.906°E) is located in the central part of Japan (Fig.1 (a)). The
average annual temperature in 2014 was 16.1°C, and the average precipitation was 1506 mm (Japan
Meteorological Agency, 2015: http://www.data.jma.go.jp/obd/stats/etrn/index.php). The city has anarea of about 326 km2 and a population of 2.3 million as of April 1, 2014 (Nagoya City, 2015:
http://www.city.nagoya.jp/shisei/category/67-5-0-0-0-0-0-0-0-0.html). The study area for the trap
survey was the east part of the city, including an urban residential area, universities, and a forest park
(Fig.1 (b)).

(c)

Trap points(b) Nagoya city
(a)

Japan

Trap points
50m radius
100m radius
150m radius
ForestGrassland
Agricultural land
Water area

Fig. 1 Maps of the study area: (a) Japan with Nagoya City circled, (b) Nagoya City outlined inblue, with trap points indicated by star symbols, (c) trap points in east-Nagoya
Source: Land use map was developed by Nagoya City (2010)

A two-step approach was employed to assess the disamenity of MQs in the urban area. In the firststep, MQs were collected by CDC (Center for Disease Control) CO2-baited traps (Inokuchi-Tekko,
Nagasaki, Japan) in Nagoya City, Japan. The traps were set at approximately 1.5 m height under tree
branches or equivalent height of structures. The traps were equipped with a small, battery-driven fan,and 1 kg of dry ice wrapped with newspaper in a styrofoam cooling box, was set at approximately 10–
15 cm above the fan. In total, 13 traps were set within an area of approximately 9 km2. Traps were set
in a relatively large secondary forest located on the east hill of the city, on the edges of forests, and inresidential areas in flat locations for five nights from July to September of 2013 (Fig. 1 (c)). The
candidate trap points were decided after conducting a pre-survey in 2012. These sites were selected to
study the relationship between land use type and MQ abundance. The elevations of the sites were
between around 15 m and 70 m. The traps were set between 12:15PM and 16:40PM on the first day of
period1, and collected between around 9:00 AM and the afternoon on the next day (Table 3). In theother days, the traps were set between 11:00AM to 15:00PM, mostly. At that time most cakes of dry iceⒸ ISERD

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had already melted. After collecting the traps, the samples were stored in a refrigerator. Several data
points were missing in this survey due to technical issues of sample collection (Table 3) and theaverage number of trapped MQs was determined for each of the points. Species identification was
conducted, focusing on Ae. albopictus and Cx. pipiens group by several research assistants as well as
two of the authors.
Table 1 Variable development and selected variables (#) for the trap statistical analysis
Variables
Description
Hitosuji_T
Trapped number of Ae. albopictus in average in each point
Hitosuji_ln (Dependent variable)ln(Hitosuji_T+0.5)
Land use potential variables
Forest50, Forest100, Forest150% of forest within 50m, 100m and 150m radii from each trap
Grass50, Grass100, Grass150% of grassland within 50m, 100m and 150m radii
Agri_land50, Agri_land100#, Agri_land150 % of agricultural land within 50m, 100m and 150m radii
Water50, Water100#, Water150% of water area within 50m, 100m and 150m radii
Urban50, Urban100, Urban150% of urban area within 50m, 100m and 150m radii
RoadW2_50#
Each way not less than two lanes within 50m from each trap
Slope potential variables
Slope1
Slope situation1 (1: in a middle of slope, 0: other)
Slope2#
Slope situation2 (1: edge of slope with flat area, 0: other)
Source: （1）by the trap survey, (2) developed by ArcGIS based on Nagoya City(2010), (3)author's assessment on site

(1)

(2)

(3)
(3)

Next, the identification of explanatory variables was performed using a GIS and data collected onsite (Table 1). By analyzing the Green coverage GIS data (Nagoya City, 2010), the percentage of fiveland use types (forest, grassland, agricultural land, water area, and urban area) were calculated in 50
m, 100 m and 150 m radii. According to Tsuda (2013), the individual range of Ae. albopictus waswithin several hundred meters. Using this as a reference, the three ranges of radii were employed. The
other variables are listed in Table 1. The “Hitosuji_ln” was used as the dependent variable, calculated
from “Hitosuji_T”. The correlations among the potential explanatory variables were checked by
Pearson correlation coefficients with avoiding multi-collinearity by checking the variance inflation
factor (VIF). The high correlated variables were excluded. Finally the variables (“#” in Table 1) wereselected for multiple regression analysis (MR). Each variable was selected for the proxy of land use
types including road, and slope. Because several studies have included land use parameters for the
analysis of the distribution status of MQ species (Johnson et al., 2008; Yonejima et al., 2011; Landau
and van Leeuwen, 2012). Also the slope variable was selected as a still water parameter which could be
used for nursery ground for MQ larva based on Tsuda (2013).
Lyytimäki and Sipila (2009) indicated that the same ESs can be understood to be positive or
negative, depending on the person questioned. Therefore, subjective assessment of the people wasconducted as a secondary step. An internet-based questionnaire survey was conducted from September
to the beginning of October in 2013 for Nagoya citizens by Rakuten Research Inc. The survey requests
were sent out to the monitor registrants of the company. The respondents could get small amount of
rakuten points after the answer. At the first screening stage, 39,340 requests were sent out to themonitors and received 5,272 responses which could be used as a stock of the subsequent survey. Thenrequests were sent to each monitor from the stock. Before sending the requests, the targets of collected
number of samples in each gender and age range were decided based on population data as of July
2013 (Nagoya City: http://www.city.nagoya.jp/shisei/category/67-5-5-0-0-0-0-0-0-0.html). Once atarget was fulfilled, the collection of relevant samples was stopped by each gender and age range
category. However after collecting the samples, we noticed sampling errors. After the examination ofthis issue, finally we decided to conduct additional collection of samples to complement 171 samples
in the middle of October 2013 to the same monitor pool by the same company. Finally in total 1,400Ⓒ ISERD

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samples were collected. Among them, a total of 565 samples were weightedly collected close to thetrap points: the Chikusa, Showa, Meito and Tenpaku wards of the city. The samples took into
consideration gender and age range balances for each ward, as much as possible, and the remaining
835 samples covered the other 12 wards, which were treated as one region from the perspective ofgender and age ranges.
Table 2 Questionnaire contents and selected variables (#) for the EDS statistical analysis
Questions/ variables
Disamenity of MQs(mosquitoes)

Detailed
1.no; 2.a bit; 3. either; 4.a bit; 5.very strong disamenity. This was converted to two-scale.
New "1" means old "1" to "3", and new "2" means old "4" and "5".
Individual attributes and subjective assessment by questionnaire survey
Forest_preference#
1.do not prefer - 3.rather prefer - 5.very prefer: in 5-level
Nature_vs._development
Priority on 1.nature; 2.rather nature; 3.either; 4.rather development; 5. development
Number of MQs near home#
1.few; 2.not many; 3.normal; 4.a bit large number; 5.large number
Source of MQs near home#

1.trees, garden#; 2.gutter, drain#; 3.forest, park, cemetery; 4.river, pond, water area; 5.other

Most noxious things(two choices)
1.MQs; 2.insects; 3.birds; 4.fallen leaves and branches; 5.others: 1st & 2nd choices
Gender
1.male; 2.female
Age range
20s, 30s, 40s, 50s, 60s, 70years ≦Under junior high school children#
Are there any children in the family? 1: Yes, 2: No
Others: Distance and visiting frequency of important forest or frequent visit forest, Appearance_of_MQs, Distance from source of MQs,
Occupation, Education, Family number, Income, Zip code, etc.
Land use potential variables developed by ArcGIS
Pond_zip#, River_zip#, Agri_zip#, Forest_zip% of each land use type area in each zip code area (1)Build_zip
Road_zip#
Slope potential variables developed by ArcGIS% of building area in each zip code area (2),% of road area (width ≧10m) in each zip code area (3)Difference_DEM#
Difference between max and minimum elevation values in each zip code area (4)Source: (1): Nagoya City (2010), (2): Nagoya City (2011), (3): digital map by MLIT, (4): DEM by GIA-J

The questionnaire contents, including zip codes to roughly identify the geographical location ofeach sample, were summarized in Table 2. Two types of data sets were developed. One aimed tounderstand the general tendency of the city average; therefore, randomly adjusted resampling (1,080
samples) was conducted to reflect a total population balance (gender and age ranges) of the city, except“women 70years ≦” samples which was compensated from “women 60s”, because in 1,400 samples
there were some shortages of the number of samples in some slots of age ranges and the five ward
samples were collected weightedly.
The other set focused on Ae. albopictus, targeting the surveys with the answer “MQs appearing
frequently during the day”, for further analysis (141 samples). Because the most frequently trapped
MQs in the city were Ae. albopictus which is common during the day, and Cx. pipiens group(Sugiyama, 2007; Yokoi, et al., 2014; Nagoya City, 2015). Parameters related to land use typeincluding road, slope, and building shade were also developed using a GIS. Variables in Table 2 wereused to check the Pearson and Spearman correlation coefficients to avoid multi-collinearity. As small
scale MQ source information, “source of MQs near home” parameters were considered based on thequestionnaire survey even if these were subjectively assessed. Also EDS might have a relation withpersonal way of thinking so the subjective assessment of nature (such as, “forest_preference”), andindividual attributes including, age range, gender, education, income, children, etc. were examined.
The selected variables (“#” in Table 2) were chosen for the binary logistic regression (BLR) analysis.
Statistical analyses were conducted using SPSS statistics ver.22 (IBM). ArcGIS10.2.2 (ESRI
Japan) was used for GIS analysis.

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RESULTS AND DISCUSSIONIn Table 3, the basic results of the trap
Table 3 Trap points and collected number of MQs
survey were presented. The NO4 which
Average number of trapped MQs
was located at the edge of forest near
Site
Site description
Ae. albopictus Cx. pipiens group Other
agriculture land was the highest in the
NO1 Forest
3.6
0.2 1.2
number of Ae. Albopictus. On the other, NO2 Forest
4.8
1.2 0.2
forest (NO1, 2 and 5) and urban area
NO3 Edge of forest*
18.8
2.5 0.0
near a big road (NO10, 11 and 12) were
NO4 Forest edge near agriculture land
58.4
6.4 0.4
relatively low in the number of trapped
NO5 Forest**
5.6
1.8 0.2
12.0
16.4 0.2
MQs. Next the MR results were NO6 Edge of forest**
12.8
24.8 0.0
summarized in Table 4. As for land use NO7 Edge of forest**
NO8 Urban residential area**
12.8
9.4 0.0
variables, agriculture and urban related NO9 Urban residential area
1.2
1.6 0.2
variables, namely, Agri_land100 and NO10 Urban area near a big road
1.0
0.4 0.0
NO11 Urban area near a big road
1.4
2.0 0.0
RoadW2_50, were the significant
0.3
1.8 0.0
variables (p < .10). Agri_land50 was NO12 Urban area near a big road***NO13 Urban residential area****7.6
41.4 0.0
also significant (p < .10) instead ofNote1: period1: July 31to Aug. 1, period2: Aug. 7-8, period3: Aug. 20-21, period4:
Agri_land100 in the Model 1.
Sep. 11-12, period5: Sep. 25-26 in 2013. The cakes of dry ice in NO1, 2 and 3 only
According to Tsuda (2013), Ae. were stored in steal small cages requested by the government for security reason.
albopictus normally does not breed from Note2: The time difference between the first and the last settings of the traps in eachpaddy field. One explanation for day were 4h25m, 3h15m, 2h3m, 2h14m and 1h17m, for period 1 to 5, respectively,
agriculture factor was as follows. except NO13. The traps of NO13 were set at 15:00PM except period5 at 16:00PM.
*: Data missing in period2, and as for period4 the trap NO3 was set again on Sep.13Agricultural site near the traps was 14 instead of Sep. 11-12 by technical issues; **: in a university campus; ***: Data
limited, namely, NO4. The paddy field
missing in period3 by technical issues, in a temple; ****: in a different university
near NO4 was located in a university
campus, in which the trap was set almost every week but period1 to 5 data only used
this paddy
study. field and many artificial small containers, suchcampus with a small water reservoir tank forintheas, bowls and planters, for university research purposes, which could be used for the container habitats
by Ae. Albopictus. Also there was small wetland close to NO4.
Forest was not recognized as a significant factor, which was similar to the results of Tsuda (2013).
Water100, also same with Water150 instead of Water100 in the Model 1, and Slope2 were notsignificant in this study. Thus further studies are required with increasing the number of traps to study
spatial structure of abundance of MQs.
There were several issues remaining. One was that the setting time of each trap was different.
Most traps were set around noon to 14:00. But some were set around 15:00-16:00 even if the trap
settings were conducted by three separate teams with the effort to minimize the setting time differences.
In the future it is better to set all traps almost same time because Ae. Albopictus is mostly appearing in
the day time. Also at the trap setting, the effect of wind should be considered in detailed, such as, daily
monitor of wind. And the sky openness factor should also be considered and treated as one parameterof the analysis.
Regarding the questionnaire survey in Table 5, MQs were recognized as the “most noxious things”
compared to other environmental pests claimed by nearly 76.9% in the 1,080 sample survey. Also themajority of citizens felt that the “disamenity of MQs” was high, concentrating on level 4 and 5. The“5.very strong disamanety” reached to 46.9%. These showed that, especially in urban areas like
Nagoya, the disamenity of MQs could be identified as one of the most important targets for EDS
analysis. Also the “source of MQs near home” was high in “1.trees, garden (34.6%)” and “2.gutter,drain (38.7%)”. Then the public assessment on “number of MQs near home”, which might be related to
MQ abundance by the trap survey, was the highest at level 3 (41.3%).
Focusing on Ae. albopictus, the citizen’s subjective assessment of MQs was studied in Table 6 (N= 141). The number of MQs near home was negatively correlated with Road_zip by the Spearman's
rank correlation coefficient, which was similar result with the Model 1 for the trap survey. Then road
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variables were identified as one of theimportant factors of MQ abundance for Table 4 MR result for the trap survey: Model 1 (N=13)
MR Model 1 for the trap survey
both the trap and questionnaire surveys.
Unstandardized
Also the source of MQs near homeStandardized
Coefficients
Variablestp
VIF
Coefficients(trees, garden) was significantly
B
Std. Error
correlated with the number of MQs near(Constant)
1.827
.264
6.906
.000
home. The source of MQs variable
Agri_land100
.199
.090
.407
2.199
.059
1.273
Water100
-.842
.889
-.183
-.948
.371
1.385
represented small scale land situation
RoadW2_50-1.311.556-.472-2.360.046
1.490
including tree and green distributions
Slope2
.540
.527
.194
1.024
.336
1.341
even if these were subjectively assessed
Note1:
Dependent
Variable:
Hitosuji_ln,
by the citizens. The number of MQs
Note2: R 2 = .785, adjusted R 2 = .677 (model evaluation test: p = .009)
might be impacted by small scale land
usage.
Table 5 Basic results of questionnaire survey (%)
Next, to analyze the main factors
Questions12345of the disamenity of MQs, the BLR was
Most noxious things
76.9
7.5 13.2
0.5
1.9
conducted for 141 samples, focusing on
Number of MQs near home
4.4 16.4 41.3 20.9 17.0
Ae. albopictus. After checking theDisamenity of MQs
1.6
8.1 13.5 29.9 46.9
correlation coefficients, the selected
Source of MQs near home*34.6 38.7 14.5 15.6
1.7
variables (“#” listed in Table 2) were
Note: each choice of 5-level(1 to 5) is presented in Table 2
used for the analysis. Finally, two types*: multiple answer questions. In addition, "do not know" answer was
23.6%.
(N=1,080)
of models were developed in Table 7.
As a full model, Model 2 included all
potentially related variables: land use, Table 6 Correlations with Number of MQs near homeslope, the number of MQs near home,
Spearman's rank correlation coefficient(N=141)the source of MQs, the subjective
RD
S_TG
-.235
.346
assessment of nature, and individual
correlation
Number of MQs near home
sig.
.005
.000
attributes, referring to the trap survey-.147
correlation
results and above mentioned correlation.
Road_zip(RD)
sig.
.082
Model 3 was developed by a variable
S_TG:
Source
of
MQs
near
home
(treesandgarden)reduction step wise method by Wald (p≦ .20 (in), p ≧ .25 (out) ) from Model 2.
The R2 values for both wererelatively low; however, three significant variables were identified in both models (Table 7). The
citizen’s subjective assessment on MQs, such as, the number of MQs near home (p < .01) and thesource of MQs near home (trees, garden and gutter, drain) (p < .05) were significant variables.
However, all land use variables developed by GIS were not recognized as significant variables.
One reason for that was that these GIS based land use variables were the percentage of each land use
type within each zip code area so the assessment scale of the variables were relatively large comparedwith land use parameters impacted on MQ appearance which might be much smaller scale such as trees,garden, gutter and drain existences. In this study each questionnaire sample location was roughly
identified by the coordinates of the center of gravity for each zip code. Concrete coordinate point data
are required for detailed analyses reflecting the specific land use situation in the future.
Regarding individual subjective assessment on nature and its attributes, all the variables tested inthis study were not identified as significant variables. As mentioned above, MQs were recognized as
the most noxious pests so the most of citizen feel MQ’s disammenity might be high.

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Table 7 BLR models for disamenity of MQs (N=141)
Model 2 (full model) and Model 3(variable reduction step wise (Wald): p ≦ .20 (in), p ≧ .25 (out))
95% C.I.for
Std.
Std.
Model
B
Wald
p
Exp(B ) 95% C.I.for EXP(B)B
Waldp
Exp(B )
EXP(B)
Error
Error
Model 2Model 3
Agri_zip
5.096 8.749.339 .560
163.370 .000 4.577E+09
Pond_zip and River_zip
7.834 12.368.401 .526 2.525E+03 .000 8.504E+13
Road_zip3.530 4.649.577 .448
34.131 .004 3.093E+05
DifferenceDEM
.025
.020
1.596 .206
1.025 .986
1.065.024 .019 1.620 .203
1.025 .987 1.064
Number_of_MQs_near_
1.008.287 12.307 .000
2.740 1.560
4.812.983 .284 12.015 .001
2.673 1.533 4.661
home
Source of MQs near
1.634
.592
7.605 .006
5.124 1.604
16.366 1.547 .573 7.276 .007
4.697 1.526 14.452
home(trees, garden)
Source of MQs near
1.157
.511
5.129 .024
3.179 1.168
8.650 1.111 .479 5.384 .020
3.038 1.188 7.768
home(gutter, drain)
Forest_preference
-.037
.198
.036 .850.963 .654
1.419
Under junior high school
.297
.525
.320 .572
1.346 .481
3.770
children(Constant)-3.519 1.268
7.703 .006
.030
-3.152 .949 11.033 .001
.043
Note 1: Dependent variable: Disamenity of MQs (1, 2, 3 level →0; 4, 5 level →1)
Note 2 for model 2: -2 Log likelihood=135.44, Cox&Snell R 2 = .227, Nagelkerke R 2 = .322, model evaluation test p = .000, Hosmer & Lemeshow test p =.434
Note 3 for model 3: -2 Log likelihood=137.17, Cox&Snell R 2 = .217, Nagelkerke R 2 = .309, model evaluation test p = .000, Hosmer & Lemeshow test p =.586, VIF for DifferenceDEM(1.021), Number_of_MQs_near_home (1.166), Source of MQs near home(trees, garden) (1.151), Source of MQs nearhome(gutter, drain) (1.017)

CONCLUSIONThe EDSs, focusing on the disamenity of mosquitoes and its abundance, was studied based on datafrom trap survey as well as the questionnaire survey. According to the trap survey, agricultural androad parameters were identified as significant factors. One possibility for the agricultural factor wasthat the paddy field near a trap was located in a university with a small water reservoir tank and manysmall containers which could be used for container habitats by Ae. Albopictus. However, the number oftraps was limited, therefore an increase in the number of traps should be considered to further study on
the relation between mosquito abundance and land use. As for the disamenity, subjective assessment ofmosquito numbers, and source of mosquitos might be important factors. Land use parameters impacted
on mosquito appearance might be much smaller scale such as trees, garden, gutter and drain existences
than those developed by GIS. Concrete coordinate point analysis is required for detailed analyses
reflecting small scale land use situation in a future study.
ACKNOWLEDGEMENTS
We thank Nagoya City Greeniﬁcation and Public Works Bureau (Showa and Higashiyama park
offices), Maeyama post office, Koshinji-temple, Showa ward office, Nagoya University Museum
Botanical Garden and S. Inoue for giving us the permission of setting traps. Also the authors thank to
Y. Yonekura, Y. Hasegawa, A. Dhakal, T. Ota, Y. Kato and others to support setting and collecting thetraps. This research was supported by the fund ‘NEXT Generation World-Leading Researchers’ from
JSPS and MEXT, Japan.
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Johnson, M.F., Gómez, A. and Pinedo-Vasquez, M. 2008. Land use and mosquito diversity in the Peruvian
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Ministry of Land, Infrastructure, Transport and Tourism (MLIT). 2006. Road data digital map 25,000. (J)Nagoya City. 2007. Nagoya land use metric survey GIS data. (J)Nagoya City. 2010. Green coverage GIS data. (J)Nagoya City. 2011. Land and building use report. (J)Nagoya City. 2015. Mosquito generation dynamics research. Nagoya City office web site: http://www.city.
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Nagoya Women's University, Home Economics･Natural Science, 53, 105-109. (J)Takagi, M., Tsuda, Y., Suzuki, A. and Wada, Y. 1995. Movement of individually marked Aedes albopictus
females in Nagasaki, Japan. Trop. Med., 37 (2), 79-85.
Tsuda, Y., Maekawa, Y., Saita, S., Hasegawa, M. and Takagi, M. 2003. Dry ice-trap collection of mosquitoes
flying near a tree canopy in Nagasaki, Japan, with special reference to Aedes albopictus (Skuse) and Culex
pipiens pallens Coquillett (Diptera: Culicidae). Med. Entomol. Zool., 54 (4), 325-330.
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Aedes albopictus and laboratory estimations of the residual longevity. Med. Entomol. Zool., 63 (3), 223-230.
Tsuda, F. 2013. Observation of mosquito and ecological survey. Hokuryukan Publications, Tokyo, Japan. (J)Yokoi, H., Kamite, Y., Kodaira, A., Yokoshima, R. and Shibata, S. 2014. Surveillance of mosquitoes for west
Nile virus in Nagoya City (2013). Ann. Rep. Nagoya City Public Health Res. Inst., 60, 35-37. (J)Yonejima, M., Watanabe, M., Nihei, N., Kobayashi, M. and Nakaya, T. 2011. Relation between land use patternaround trap location and the number of Culex tritaeniorhynchus collected by dry ice baited traps. Med.
Entomol. Zool. 62 (1), 13-22. (J)Ⓒ ISERD

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Research article
erdSocio-Economic and Spatial Evaluation of Ecosystem Services
in Nagoya, Japan
MAKOTO OOBA*National Institute for Environmental Studies, Tsukuba, Japan
Email: ooba.makoto@nies.go.jp

HIDEYUKI ITO
Nihon University, Funabashi, Japan

KIICHIRO HAYASHI
Nagoya University, Nagoya, Japan
Received 25 November 2015

Accepted 10 November 2016(*Corresponding Author)

Abstract In recent years, the value of urban green spaces and parks in Japan has begun to bereevaluated. In particular, attention is being paid to easily accessible and routinely available
urban green spaces and parks, where many people benefit from cultural services such asrecreation and relaxation. However, these spaces are facing the threat of destruction by urban
development. Thus, to assess the recreation function of the small- to medium-scale urban parks
and green spaces routinely used by many people, this study aimed to evaluate their economic
value using the travel cost method (TCM). To expand the results from the TCM, suggestions
were made with regard to prioritizing ecosystems in urban areas for conservation. The potential
supply of ecosystem services was estimated using five categorized proxy variables andweighted by the TCM results. This assessment can be applied to any city whose social andnatural statistics are not well-managed.
Keywords conservation priorities, land use, travel cost method, urban green space

INTRODUCTION
The Millennium Ecosystem Assessment (MEA) performed the organization of the concept of
ecosystem services. These refer to a variety of services, from concrete services that human society
receives from ecosystems (carbon storage, soil formation) to related subjective cultural services(landscape, leisure). However, integrated quantitative evaluation tools that would encompass all
ecosystem service concepts are still at the research and development stage.
In addition, in recent years, urban green spaces and parks in Japan have been increasing in area,and many people can use such places to engage in recreation and relaxation. However, they are facing
the threat of disappearing due to urban development. Therefore, it is important to economically assess
their utility values and the values of their ecosystem services.
With regard to the literature on recreation function assessment, Kuriyama (2001) calculated therecreation values of Yakushima Island and Mt. Fuji in Japan by using the travel cost method (TCM)
and the contingent valuation method. Maeda (2004) economically assessed the recreation value ofKushiro Marsh and then proposed new environmental conservation measures based on the economic
assessment results. Hein et al. (2006) estimated the total economic value of a wetland’s ecosystemservices based on the assessment results using the TCM. Thus, there are many previous studies
assessing recreation functions. However, these studies focused on nationally famous tourist sites andⒸ ISERD

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facilities, and tended to deal less with assessing the economic value of the small- to medium-scaleparks and urban green spaces that are used by citizens on a daily basis.
In addition, within a certain management scope, there is also demand to rank ecosystems in orderto prioritize their conservation such that important ecosystem services are not lost. There are several
conservation planning support softwares that use GIS to conserve certain specified species. Based on
certain restrictive conditions (costs, etc.), they obtain the optimum spatial plan, which can be applied todetermine conservation priorities in order to maximize ecosystem services.
OBJECTIVE
The study is proposing a method for the integrative evaluation of the supply potential of the various
ecosystem services that urban ecosystems provide. This study estimated ecosystem services andbiodiversity conservation using the relatively simple method developed by Ooba et al. (2014, 2015),
which assumes that land use transforms ecosystem services. The economic values of cultural services
in small and medium urban green spaces in Nagoya were assessed through the TCM using an internet
survey and estimating the economic value of each ecosystem service. Further, this web questionnairealso asked for the importance of each ecosystem service, and based on the results, weighted andperformed integrated evaluations of the ecosystem services that were individually estimated. Finally,
conservation software was used to calculate conservation priorities and determine where importanturban ecosystems were located.
METHODOLOGY
Study Area
Aichi prefecture in Japan, the venue of the ordinary meeting of the Conference of the Parties (COP10)
to the Convention on Biological Diversity in 2010 and a prefecture eager to preserve urban green
spaces, was selected for study. The four selected small and medium urban parks and green spaces used
on a daily basis by citizens in Aichi pref. are the Idaka green space (60.4 ha), Aioiyama park (84.9 ha),Chayagasaka park (6.18 ha), and Meitoku park (15.4 ha) (Fig. 1).
Estimation of Ecosystem Services
Outline of questionnaire survey: To estimate the economic values of the recreation functions of theurban green spaces and parks, the TCM was adopted based on the travel costs and numbers of visitors
for each green space and park obtained through the internet survey (Rakuten Research, Japan). In
December of 2014, a screening survey was first conducted with a sample of 20,000 monitor members
across Aichi pref. who intended to answer the questionnaire. Then, in consideration of the regional
population, age distribution, and sex distribution in the pref., 2,800 samples were collected throughpseudo-random sampling in January of 2015. The question items explored the following: whether
respondents had visited the selected parks and green spaces within the past five years; the number ofvisitors in the past five years; the purposes of the visits (multiple choice from 21 items); modes oftransportation employed; travel times for each mode of transportation; visit durations; and average
number of visitors. Then, the ecosystem services of the general urban green spaces were explained sothat respondents could rate the importance of cultural services on a five-point scale. Finally, questions
about individual attributes (occupation, annual income, and educational background) were asked.
Analysis by the TCM: Generalized round-trip costs per capita (total cost) were calculated based onrequired costs such as transportation and facility usage costs (e.g., train fare, cost of gasoline, andadmission fee) and the product was found by multiplying required time, i.e., the sum of travel time andⒸ ISERD

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visit duration, by the time value. Following the method of Cesario (1976), the time value was set to989 yen, which is equivalent to 33% of the average hourly income of 2,967 yen (data from the Ministryof Internal Affairs and Communications in 2012). In addition, demand curves were estimated throughregression analyses of the annual average visit times and generalized costs. Then, recreation values
were calculated by multiplying the consumer surpluses per visitor by the annual numbers of visitors(Eq. (1)). Finally, the annual recreation values were divided proportionally according to the importancelevels of the ecosystem services to determine the economic value of each ecosystem service.
RV = (−AT/I) × AV

(1)

Where RV is the recreation value, ID is the slope of the demand curve, and AT is the annual
average visiting number of a visitor, and AV is annual numbers of visitors.
(a)

130E

140E

(b)

40N

Nagoya City

Fig. 1 Location (a) and study sites (b) including economic evaluation for cultural service
Spatial evaluation of ecosystem services: Based on the four MEA categories, ecosystem services
were categorized. These services are conceptual, so the carbon storage rate quantified based on proxyvariables, food supplies, prevention of soil erosion, recreation, etc., were estimated. Biodiversity wasestimated based on habitat continuity (see also Ooba et al., 2015). Detailed Digital Information for
Urban Landuse (Geospatial Information Authority and Japan Map Center) was used in relation to landuse. The latest version of the product was provided for only map at 1997. Nagoya City has beendeveloped well and then slight change between the current and 1997 was assumed at 1-km grid size.
The 17 land use subdivisions were reclassified into five types: water area, cities, roads, agriculturalland, and forestland. "Parks" and "green belts" were classified as forestland. This simplification oflanduse is aimed to application for developing country where landuse map may be limited andmethodology of estimating ecosystem services is also limited. For elevations and slopes, a Digital
Elevation Model (DEM) was used provided by the Geospatial Information Authority. For this study,
the national third mesh system (approximately 1 km meshes) was used to calculate the total supply of
ecosystem services.
Carbon storage and food supply were estimated using agricultural statistics (Table 1). For soil
erosion prevention, the USDA's Revised Universal Soil Loss Equation (RUSLE) was employed. The
results of the TCM were used to estimate the economic values of cultural services. The economic value
V (1 million yen /ha y) per unit of area was estimated as follows.
V = aAb(2)

Where A is area (ha) and a and b are parameters obtained by a regression calculation (b < 1). For agreen space of 1 ha or greater, respective services were evaluated. With regard to habitat continuity, thecontinuity of green spaces with a radius approximating 2 km was calculated using GIS based onⒸ ISERD

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previous research (Li, 2014). The estimated quantities of services are shown by different unit systems,
so for inter-comparison purposes, values were compared after normalization based on the averagevalues and standard differentials through logarithm conversion.
Integrated evaluation of ecosystem services: To perform the integrated evaluation of ecosystemservices, Zonation, which calculates conservation priorities (Moilanen et al., 2012), was employed.
Zonation divides the region of focus into meshes and identifies the mesh with the greatest overall loss
when one mesh is removed (for example, if it is species diversity, then the diversity of species, or if it
is ecosystem services, then the value of integrated ecosystem services). Conservation priority isdetermined by repeatedly removing the mesh that was identified and searching among the remaining
meshes for the cell with the maximum loss.
As a calculation method, the Core Area Zonation that minimizes loss by assigning high rank tospatial continuous and high weight ecosystem services was used. This study used the average value ofimportance obtained through the web questionnaire. The costs were all assumed to equal one. The
other Zonation parameters were set to the default values.
Because of technical restrictions on data entered into Zonation, the national 3rd mesh system ofJapan was converted into 500 m meshes to calculate conservation priority.
Table 1 Methods used to estimate ecosystem services (see also Ooba et al., 2015)
Service category
Support
Provision
Regulation

Proxy variable
Basic units, method details*
Carbon sequestration
3.09(F)
Food supply
2.98(A)
Inverse of soil erosion S = 65.41sin2Ɵ+ 4.56sin Ɵ + 0.065
coefficient
C = 1 (U), 0.33(A), 0.0085(F)CultureEconomic value of Value per unit area as green belt area
green spaceA(ha) V = 3.0184A-0.437
HabitatContinuity of green
ArgGIS tool (Focal statistics)
space
proximity as 2 km radius* Land-use codes—U: Roads and urban areas, F: Forestland, A: Agricultural land

Unitt/y hat/y haReference
Ogawa et al.(2002)
Aichi Pref.(2012)-

Renard et al. (1997)
6

10
JPY/y

This study-

Li (2014)

RESULTS AND DISCUSSION
Table 2 shows the purposes of visits to the four urban parks/green spaces. Representing about half of
responses, the first and second purposes were seeing a landscape and enjoying a walk, respectively.
Regarding the characteristics of each park and green space, Meitoku park has a campsite and people
who visit this park to use the campsite accounted for 9% of respondents. The Idaka green space has a
sports ground and visiting this facility accounted for 7% of responses, whereas seeing the Hotaria
parvula (species of firefly) in the Aioiyama green space and represented 10% of responses.
Table 2 Purposes of visits (%)
Seeing a landscape
Enjoying a walkLight exercise
Forest bathing
Enjoying playing tool*
Other

Chyagasaka
44
19
7
8
5
17

Meitoku
26
28
7
7
9
21

*Firefly viewing only at Meitoku park

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Idaka
30
18
7
13
7
25

Aioiyama
37
12
8
7
10
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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Also shown is the importance of the four types of ecosystem services as estimated on a five-point
scale (Table 3). The cultural services obtained high scores for many parks and green spaces, with valueof 4.15 on the five-point scale. The supply services obtained low scores, with average value 3.59.

Fig. 2 Estimated demand curves of the parks from TCM
Table 3 Importance level and economic value
Total number of visitor (1/y)
Number of visit time (1/y)
Regulating ES
Providing ES
Importance level*
Cultural ES
Supporting ES
Biodiversity
Regulating ES
Providing ES
Economic value
Cultural ES(Million JPY)
Supporting ES
Biodiversity*Five grade scale

Chyagasaka
445,569
1.14
4.15
3.61
4.15
3.95
4.09
8.77
7.63
8.77
8.35
8.64

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Meitoku
155,200
0.95
4.01
3.51
3.97
3.89
3.88
11.97
10.48
11.85
11.61
11.58

Idaka
571,161
1.05
4.23
3.63
4.30
4.05
4.19
51.84
44.49
52.70
49.63
51.35

Aioiyama
442,646
0.97
4.13
3.60
4.17
4.07
4.16
24.05
20.96
24.28
23.70
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IJERD – International Journal of Environmental and Rural Development (2016) 7-2

Figure 2 and Table 3 shows the estimated demand curves and their economic values. The annual
average number of visits was about 1.0 for each park and green space, representing a low frequency.
The correlation between the generalized costs and the numbers of visits was not very strong. The
estimated recreation values correspond to the values of the cultural service, and the economic values
vary significantly according to the annual numbers of visitors. In the analysis of importance, all fourparks and green spaces exhibited the highest scores for cultural services and the lowest scores for
supply services. The reason for this could be that citizens greatly enjoy cultural benefits such as
playing and seeing beautiful landscapes but do not care as much about receiving supply services suchas food.
Spatial Evaluation of Ecosystem Services
Cultural services were estimated based on the value of four parks by a power function such as Eq. (2),a = 3.0184, b = −0.437 (R2 = 0.63). If the area increases, the value per unit area decreases, but because
this is multiplied by the area, the area and value of the cultural services increases gradually. Figure 1b
shows the part of the green space of 1 ha or greater used for this study and the value of the estimatedcultural services. Like Itaka and Aioiyama, the values for the Higashiyama and the western part ofNagoya City were high.
The results of the total and converted estimated ecosystem services for each national 3rd mesh are
shown in Figs. 3a to e.
(a) Support(e) Habitat(b) Provision(c) Regulation(f) Rank with equal weight(d) Culture(g) With weights from the survey result

Fig. 3 Distribution of Ecosystem Services (a-e) and Conservation Priority (f and g)
This study performed estimations through a simple method related to land use, so places high inecosystem service supply were arranged to be relatively easily identifiable. Carbon storage (Fig. 3a)
was high in Eastern Nagoya City and Moriyama, where there are many woodland areas. Food
production (Fig. 3b) was high in western Nagoya, where there are relatively large areas of paddy andfarmland. Cultural services and habitat quality (Figs. 3d and e) tend to be low in the central area but
higher in the surrounding areas.
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Results that relatively display the conservation priority (where 1 is the top priority) are shown in
Figs. 3f and g. Priority tends to be high in the surrounding areas, where individual ecosystem services
were high, and in Higashiyama, Moriyama, and western Nagoya City. Atsuta, which is isolated inside
the city, and green spaces in the Nagoya region also earned high priority.
The difference between Figs. 3f and g resulted from weighting: equal weights (every weight was
assumed to be 1.0) and weighting based on the results of the questionnaire survey. The priority of theeast side of Nagoya was lower in the weighted case (Fig. 3g) than the equal weights case (Fig. 3f) due
to the low weight of provisioning services. It is assumed that this is because this area has few nearlynatural ecosystems.
CONCLUSION
The results show that among urban green spaces and parks, differences are observed in the
purposes of use according to the availability of accompanying facilities such as playground equipment
as well as urbanization around forest areas. Many visitors simply enjoy the scenery of green spaces,
which shows that relaxing by seeing beautiful landscapes and walking in the woods is of great value.
Regarding green spaces, the correlation between the generalized cost and the number of visits is notvery high. However, the economic value of greenery-related recreation estimated in this survey isshown to be extremely high due to a very large number of visitors per year, despite the small andmedium size of the evaluated green spaces and parks.
In the analysis of importance, all four parks and green spaces exhibited the highest scores for
cultural services and the lowest scores for supply services. This could be because citizens greatly enjoy
cultural services, such as playing in parks and green spaces and seeing beautiful landscapes, whereas
they do not care as much about supply services, such as food. However, the respective ecosystemservices are not independent, and it is likely that the economic value is overestimated. The authors arereviewing spatial estimation methods about cultural services, and in a future study more reliable
methodology can be proposed.
Ecosystem services at the 1 km mesh level were estimated using a simple method related to land
use and the survey results. In the area surrounding the city, relatively high services were exhibited dueto the presence of agricultural land and green spaces including secondary forests. The conservation
rankings also showed the same trend; however, the conservation priority of agricultural land isrelatively lower than that of the other green spaces due to the low weight of provision services in thesurvey results.
The implementation that have been carried out in this study was limited (few landuse types andsimple estimation methods). These limitation of landuse are resulted from the aim to application of ourframework in developing country where usually data and estimation methods is limited. However theselimitation may be easily replaced by more detailed landuse map and complicated methods.
ACKNOWLEDGEMENTS
This study was supported by the funding program for next generation world-leading researchers(MEXT, Japan) and the Environment Research and Technology Development Fund (1-1401, 2-1404,
MOE, Japan).
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Cesario, F.J. 1976. Value of time in recreation benefit studies. Land Economics, 5 (2), 32-41.
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Ooba, M. and Hayashi, K. 2014. Comparative assessments of ecosystem services between rural and urban areas.
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Ooba, M., Hayashi, K., Suzuki, T., Li., R. 2015. Analysis of urban ecosystem services considering conservation
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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 publish the International Journal of Environmental and Rural Development, 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.
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

IJERD – International Journal of Environmental and Rural Development

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
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. Jeeranuch Sakkhamduang, Institute of Environmental Rehabilitation and Conservation,
Southeast Asia Office / Association of Environmental and Rural Development, Thailand
Dr. Junaid Alam Memon, Pakistan Institute of Development Economics, Pakistan
Dr. Julian Torillo, Jr., Bohol Island State University, Philippines
Dr. Carlos Onan Tovar Mendoza, Honduras Embassy in Japan, Japan
Treasurer
Dr. Lalita Siriwattananon, Rajamangala University of Technology Thanyaburi, Thailand
Regional Vice Presidents
Prof. Dr. Robert J. Martin, University of New England, Australia
Dr. Sinisa Berjan, University of East Sarajevo, Bosnia and Herzegovina
Prof. Dr. Mom Seng, Royal University of Agriculture, Cambodia
Prof. Dr. Dieter Trautz, University of Applied Sciences, Germany
Dr. Siaw Onwona-Agyeman, African Program on Field Oriented Leaders in Environ. Sectors, Ghana
Dr. Sri Wahyuni, Islamic University of Riau, Indonesia
Dr. Hiromu Okazawa, Tokyo University of Agriculture, Japan
Dr. Junaid Alam Memon, Pakistan Institute of Development Economics, Pakistan
Prof. Dr. Regucivilla A. Pobar, Bohol Island State University, Philippines
Dr. Chuleemas Boonthai Iwai, Khon Kaen University, Thailand
Prof. Dr. Murari Suvedi, Michigan State University, USA
Dr. Vo Quang Minh, Cantho University, Vietnam
ISERD Secretariat:
Institute of Environmental Rehabilitation and Conservation (ERECON)
2987-1 Onoji Machida-Shi, Tokyo 195-0064, Japan
Tel/Fax: +81-42736-8972
E-mail: iserd.secretariat@gmail.com
Webpage: www.iserd.net
Collaborated with

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

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