ISSN 2185-159X

erd

International Journal ofEnvironmental and Rural Development

Volume 11 Number 2

December 2020

International Society of Environmental and Rural Development

IJERD – International Journal of Environmental and Rural Development

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

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

IJERD – International Journal of Environmental and Rural Development

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

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

IJERD – International Journal of Environmental and Rural Development (2020) 11-2

Contents
Methods for Improving the Performance of Paddy Soil-Used Sediment Microbial Fuel Cells
Narong Touch and Takahiko Nakamura

1

Risk Assessment of Pesticide Use in Chinese kale Cultivation of GAP and Conventional Practice by
EIQ in North-East Thailand
Jarupong Prasopsuk, Arunee Promkhambut,
Suwit Laohasiriwong and Chuleemas Boonthai Iwai

7

Farmers’ Perceptions on Soil Degradation and their Criteria to Adopt Soil and Water Conservation
Strategies in Ovche Pole Region in North Macedonia
Ognen Onchevski and Machito Mihara

12

Combination of Entomopathogenic Fungi with Essential Oil for Controlling Bean Fly,
Ophiomyia phaseoli Tryon (Agromyzidae: Diptera)
Malee Thungrabeab and Patcharin Krutmuang

20

Agronomic and Yield Performances of Three Rice Cultivars (Oryza sativa L.)
under Water Regimes in Dry Season
Savoeurn Lang, Sophaonarith Ro, Siranet Roeurnand Lyhour Hin

25

Applicability of Tank Model in Mid-Sized Catchments in Eastern Uganda
Emmanuel Okiria, Hiromu Okazawa, Yuri Yamazaki,
Yukimitsu Kobayashi and Shinji Suzuki

31

Effect of Excavated Small Drainage Channels on Desalinization in Northeastern Thailand
Naho Nohara, Tadao Yamamoto, Takashi Kume,
Katsuyuki Shimizu and Chuleemas Boonthai Iwai

38

Farmer’s Perception of Ecosystem Services for Lowland Rice Cropping Systems
in Battambang Province, Northwest of Cambodia
Raksmey Phoeurk, Kimchhin Sok and Malyne Neang

46

Improvements in Agricultural Education at Secondary Schools in Nepal:
A Case Study in Mustang District
Yusuke Kurata, Kazuki Adachi, Sirjana Kafle,
Kazuhiro Nemoto and Mitsuru Hamano

53

Treatment of Wastewater from Dyeing Process of Weaving Workshop in Inle Lake by Using
Lotus Stalk and Coconut Shell Charcoal
Chaw Su Hlaing, Nan Noe Noe Oo and Ah Mar Yi

62

Diversity of Arthropod Natural Enemy Species in Intensive Monsoon Rice Growing Area,
Nay Pyi Taw, Myanmar
Wai Zin Phyu, Moe Hnin Phyu and Thi Tar Oo

71

Profitable Management Styles of Small-Scale Pig Farming in Rural Areas of Cambodia
Mitsuru Hamano, Naoki Nakano, Socheat Nak
and Kasumi Ito78

Selection Index for Yield and Yield Contributing Traits in Improved Rice Genotypes
Nyo Mar Htwe, Myint Aye and Chan Nyein Thu

86

Production and Quality of Biogas from Pilot Biodigesters using Cow Manure
Lytour Lor, Machito Mihara, Bunthan Ngo, Lyhour Hin,
Dyna Theng, Chanmakara Mean and Bart Frederiks

92i

IJERD – International Journal of Environmental and Rural Development (2020) 11-2

Efficiency Evaluation of Solar Pumping System for Wadi Agriculture in Djibouti
Makoto Shinozaki, Sawahiko Shimada, Ayako Sekiyama,
Kiyoshi Tajima and Hassan Ali Barkad

98

Growth and Yield Performance of Different Potato Varieties under Upland Condition in Cambodia
Kheang Song, Sophal Var, Savry Poeng, Kimyee Orng,
Chantha Seng, Sophoanrith Ro, Siranet Roeunand Hong Cheang

104

Reaction of Different Rice Varieties to Bacterial Blight
Han Su Yin, Seint San Aye, Htay Htay Oo, Yi Yi Mon
and Tin Aye Aye Naing

109

Study on the Factors of Awareness for the Production and Development of Vegetables
by Farmers in Cambodia
Shinobu Yamada, Machito Mihara and Kumiko Kawabe

116

Yield and Yield Components of Potato Response to Various Planting Date in Cambodia
Kheang Song, Sophal Var, Sovanborey Oy, Seangly Kheang,
Sophoanrith Ro, Siranet Roeun and Hong Cheang,

123

Economic Impact of Rice Tractor and Combine Harvester Custom Services in Northwest Cambodia
Dalin Sun, Tomohiro Uchiyama and Nina N. Shimoguchi

128

Coping Strategies of Japanese Farmers to Recent Challenges in K City, Chiba, Japan
Nina N. Shimoguchi, Jennica Amielle M. Moraand Eliza C. Aquino

134

The Abundance of Hemiptera and Diptera fauna on Monsoon Rice at Nay Pyi Taw, Myanmar
Nwe Ni Win, Moe Hnin Phyu, Thi Tar Oo and Kyaw Kyaw Win

140

Changes in Soil Physical and Chemical Properties with Depth due to Megascolicidae Movements
Takanori Kaneko, Tomonori Fujikawa and Machito Mihara

146

Postharvest Management Options to Improve Tomato Value Chain in Cambodia
Tong Socheath, Borarin Buntong and Antonio Acedo Jr.

154

Assessing the Yield of a High Yielding Rice Variety, Byaw Htun, Planted Using the Cut-stem
Transplant Method and Cultivated in a Deep-water Area, Bago Region, Myanmar
Yu Mon, Yoshinori Yamamoto and Mie Mie Aung

163

Physiological Variables Associated with Yield of Improved Rice (Oryza sativa L.) Genotypes inNormal and Late Growing Seasons
Zun Phoo Wai, Nyo Mar Htwe and Su Latt Phyu

170

ii

IJERD – International Journal of Environmental and Rural Development (2020) 11-2

Research article
erd

Methods for Improving the Performance of Paddy Soil-Used
Sediment Microbial Fuel Cells
NARONG TOUCH*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Email: nt207118@nodai.ac.jp

TAKAHIKO NAKAMURA
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Received 5 December 2019

Accepted 1 July 2020(*Corresponding Author)

Abstract Sediment microbial fuel cells (SMFCs) have received considerable attention for
remediating sediment and wastewater while providing electricity. This technology offers
many benefits for rural regions, particularly for those in developing counties. SMFCs cantreat agricultural wastewater, household sewage, and organic waste while providing
electricity to households. However, the performance of SMFCs remains low and must be
improved. It has reported that mixing steelmaking slag (SS) with littoral sediment improves
SMFC performance. The present study examines the use of SS to potentially improve theperformance of a SMFC that uses paddy soil as its fuel (PS-SMFC). Moreover, we examinechanges in the performance of a SS-SMFC (the PS-SMFC that the anode chamber is filledwith SS) that uses lactic acid bacteria (LAB) and BN strain of Bacillus subtilis (BNB)
solution-mixed paddy soil as its fuel. In laboratory experiments, paddy soil was poured into
the SS layer (the anode chamber) of a SS-SMFC. LAB or BNB were added to the SS-SMFC
anode by mixing a bacteria solution with the paddy soil. The SMFC performance was
evaluated by measuring the polarization (current–voltage relation) and power density. The
power density of the SS-SMFC was observed to be 152 mW.m−2, which is approximately
twice than that observed without using SS (80 mW.m−2, as reported in previous studies). Thisshows that the performance of a paddy soil-used SMFC increases after mixing SS with the
paddy soil. Furthermore, the SS-SMFC power density increased from 66 to 191 mW.m−2
after adding BNB and to 247 mW.m−2 after adding LAB. Thus, adding LAB or BNB to
paddy soil is shown to improve SMFC performance. In comparison with BNB, LAB has
greater potential for increasing SMFC performance.
Keywords sediment microbial fuel cell, performance, paddy soil, steelmaking slag,
lactic acid bacteria, BN strain B. subtilis

INTRODUCTION
Recently, sediment microbial fuel cells (SMFCs) have received considerable attention for improving
sediment and water quality. Numerous studies have reported that when using SMFCs, the amountand variations in the state of the organic matter present in sediment-applied SMFCs decrease and theredox potential of the sediment increases (Sacco et al., 2012; Sajana et al., 2013; Touch et al., 2014).
Furthermore, SMFCs have been proven to be effective in preventing the deterioration of water quality
due to ion diffusion from sediment (Touch et al., 2017a) and improving the benthic habitat
environment in highly reduced sediment (Touch et al., 2018a). Moreover, Touch et al. (2017b)
showed that using SMFCs is effective for removing hydrogen sulfide from sediment and fixing
phosphate in them; they showed that the oxidation of reduced substances at the SMFC anode plays
an important role in improving the sediment quality and the benthic habitat environment. As such,
SMFCs were employed into the sediment deposited near a sewage outlet (Touch et al., 2018b) andan oyster farm (Touch et al., 2018c) to improve the quality of the sediment and water.

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

Households

Farmlands
Agricultural wastes➢ water➢ biomass➢ Sewage➢ kitchen waste

SMFC system
Electricity

Resources➢ nutrients➢ treated water➢ treated sludge

Fig. 1 Benefits of using SMFCs in rural regions
The achievements reported in previous studies suggested that SMFCs offer many benefits forrural regions, particularly those in developing counties. For example, SMFCs can treat agricultural
wastewater, household sewage, and organic waste while providing electricity to households andrecycled resources to farmlands (Fig. 1). However, the performance of SMFCs remains low and must
be improved. Kouzuma et al. (2014) reported the maximum power and short-circuit current densities
of SMFCs in rice paddy fields are only 80 mW.m−2 and 550 mA.m−2, respectively (based on the
projected anode area). Many methods have been proposed for improving the SMFC performance,such as adding mediators to the sediment (Lovley et al., 2004) and the activation of organisms onelectrode (Wang et al., 2009). It has been showed that adding steelmaking slag (SS) to littoral
sediment could improve the SMFC performance (Nishimura et al., 2018). In the present study, we
focus on using SS to improve the performance of a SMFC that uses paddy soil as its fuel (PS-SMFC);
further, we examine the applicability of lactic acid bacteria (LAB) and the BN strain of Bacillus
subtilis (BNB) to improve the performance of a SS-SMFC (the PS-SMFC that the anode chamber isfilled with SS).
OBJECTIVE
The first objective of this study was to examine the changes in the performance (current and power)of a PS-SMFC after adding SS to the anode chamber, i.e., the performance of SS-SMFC. The second
objective of this study was to examine the applicability of LAB and BNB to improve the performanceof SS-SMFC.
METHODOLOGY
Experimental Device and Materials
The experimental device comprised a cylindrical bottle with an inner diameter and height of 120 mm
and 150 mm, respectively. The bottle was filled with SS (diameter range of 5–40 mm) to a depth of
20 mm, and the anode electrode was placed on the SS layer. Then, 20 mm of the SS layer was placedon the anode electrode. The wet paddy soil was mixed with deionized water in a soil-to-water weightratio of 1:2; subsequently, the mixture was slowly poured into the bottle until it reached a height of
50 mm from the bottom of the bottle. Finally, tap water was poured over the soil layer, and thecathode electrode was submerged near the surface of the water (Fig. 2a).
The paddy soil was collected from a rice filed (Ebina, Kanagawa, Japan) during the agriculturaloff-season. Approximately 150 mm of the surface soil was collected and transported to the laboratory.
The paddy soil was mixed with deionized water to facilitate its easy pouring into the SS layer.
Solutions of LAB or BNB were used instead of the aforementioned deionized water to examine theireffects. Either 50-g Natto or 75-g yogurt (commercial products) was mixed with 3-L tap water andⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

fermented for 7 days at ambient temperature. Then, the supernatant was extracted and mixed withthe paddy soil.
<Cathode electrode>(100*100) mm2 –brush type
120 mmExternal resistance

100 mmTap water

20 mm

50 mm

Paddy soil

R

V

External resistance

CathodeCathodeFor a fixedcathode potentialof 0.3 V

R

V

Anode

Anode

<Anode electrode>
Steelmaking slag
(100*100) mm2 –brush type(b) Current(a) SS-SMFC
measurements

Potentiostat(c) Polarization measurements

Fig. 2 Experimental device and measurement methods
The electrode material used was carbon cloth (News Company, PL200-E), which was heated at
500 °C for 1 h to improve its performance before being used as the electrode material according to
Nagatsu et al. (2014). The heated carbon cloth, with a surface area of 10000 mm2 (100-mm widthand 100-mm long), was separated into carbon fibers to make the brush-type anode or cathode (Fig.
2a). Plastic-coated copper wire was used for all the connections in the SS-SMFC and operating
circuits.
Operations and Measurements
The experiments were conducted by following the operations and measurements as shown in Fig. 3.
All SS-SMFCs were put into an open circuit (without electrical current flow) mode until their
voltages stabilized (~7 days), after which the polarization was measured using the circuit shown in
Fig. 2b. An external resistance was loaded between the anode and cathode and varied over 2.2 Ω–10
kΩ. The cell voltage was recorded 1 min after each external resistance was loaded. The recorded
voltage was used to calculate the current according to the Ohm’s law, namely, I = U/Rex, where U[V] is the voltage, I [A] is the current, and Rex [Ω] is the external resistance; further, the power P was
calculated according to P = IU. The current and power densities were obtained by dividing thesevalues by the surface area of the electrode, i.e., 0.01 m2. To understand the long-term performanceof SS-SMFCs, an external resistance of 20 Ω was loaded between the anode and the cathodeelectrodes (Fig. 2b), after the polarization measurement.

SS-SMFCs
creation

Anode potential➢Bacterial effects

Open circuit(no current flow)

Stable voltage

Performance➢Current density➢Power density

Polarization measurement➢0.3 V of cathode potential➢2.2 Ω to 10 kΩ of external
resistance
20 Ω-external resistance(current generation)

Performance➢Current density➢Power density

Polarization measurement➢2.2 Ω to 10 kΩ of external
resistanceFig. 3 Operation conditions and measurements during experimentsⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

To calculate the circuit current, the voltage across the external resistance was measured every
30 min using a voltmeter (Graphtec, midi LOGGER GL840-M). After long-term current generation,
the SS-SMFCs were put into an open circuit mode again until their voltages stabilized. To evaluate
the effects of LAB or BNB in the SS-SMFCs, the polarization was measured by fixing the cathodepotential at 0.3 V versus Ag/AgCl using a potentiostat (Hokuto, HB-151B) (Fig. 2c). This value wassourced from the study conducted by Nagama et al. (2018), who noted that the potential of sea water
is approximately 0.3 V. After fixing the cathode potential, an external resistance was loaded between
the anode and cathode and varied over 2.2 Ω–10 kΩ. The cell voltage was recorded 1 min after
loading each external resistance.
RESULTS AND DISCUSSION
Improved Performance of Paddy Soil-Used SMFCs by Steelmaking Slag
Fig. 4 shows the polarization curves of the SS-SMFCs before they generate electrical current. As
shown in Fig. 4a, the maximum power and current densities of the SS-SMFCs were approximately
150 mW.m-2 and 1600 mA.m-2, respectively. Kouzuma et al. (2014) reported the maximum powerand short-circuit current densities of SMFCs in rice paddy fields were only 80 mW.m−2 and 550 mA.
m−2, respectively. Comparison with the two latter shows that the performance of a PS-SMFC
increases when SS is used in the anode chamber of the PS-SMFC.

200
Cell voltage (V)Power density (mW.m-2)

250

150
100
50

(a)
0
0

200 400 600 800 100012001400160018002000
Current density (mA.m-2)

1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0

SS-SMFC
SS-SMFC with BNB
SS-SMFC with LAB(b)0

200 400 600 800 100012001400160018002000
Current density (mA.m-2)

Fig. 4 Polarization curves of SS-SMFCs before generating electrical current
The results of the present study agree well with those of Nishimura et al. (2018), who suggested
that mixing SS with littoral sediment increases SMFC performance. They argued that the reductionof iron compounds in the SS and its dissolution could make sediment into a higher reduced condition.
Furthermore, the SS might play an important role in supporting electron transfer in the sediment. Our
results suggest that mixing SS with either littoral sediment or paddy soil can improve SMFC
performance.
Effects of Lactic Acid Bacteria (LAB) and BN stain of Bacillus subtilis (BNB) in SS-SMFCs
Fig. 4 (the polarization without fixing the cathode potential) shows that the differences in the powerand current densities of a SS-SMFC with and without BNB were unclear; this occurs because the
SMFC performance depends on the performance of the cathode and anode electrodes. Thus, we must
fix the cathode electrode at the same potential to obtain a better understanding the anode electrode
performance, i.e., the effects of either LAB or BNB in the SS-SMFC anode.
Fig. 5 depicts the polarization curves for a fixed cathode potential of 0.3 V. The maximum
power density was 66 mW.m−2 in the case of using paddy soil alone; it increased to 190 mW.m−2 (athreefold increase) after adding BNB to the paddy soil and to 247 mW.m−2 (an increase of 3.74 times)Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

after adding LAB (Fig. 5a). This suggests that adding either BNB or LAB improves SS-SMFC
performance, with LAB improving the performance more. A Similar conclusion is reached bycomparing the current density of each SS-SMFC (Fig. 5).
300
250
Cell voltage (V)Power density (mW.m-2)

(a)
200
150

100
50
0

0

200

1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0

400 600 800 1000 1200 1400
Current density (mA.m-2)(b)

SS-SMFC
SS-SMFC with BNB
SS-SMFC with LAB

200

400 600 800 1000 1200 1400
Current density (mA.m-2)

Fig. 5 Polarization curves for a fixed cathode potential of 0.3 V
40

(a)

35
30

(b)

400

SS-SMFC with BNB

Current density (mA.m-2)

Power density (mW.m-2)

450

SS-SMFC

SS-SMFC with LAB

25
20

15
10
5

350
300

250
200
150
100

Cathodeexposed to air

50

0

0
0

10

20
30
Opertation time (day)

40

50

0

10

20
30
Opertation time (day)40

50

Fig. 6 Long-term variations of power and current densities of SS-SMFCs
A SMFC experiences various potential losses that decrease the cell voltage during electricity
generation (Touch et al., 2019). In other words, the cell voltage of a SMFC with higher performanceis less reduced for a given generated current. For a current density of 400 mA.m-2, Fig. 5b shows thatthe cell voltage decreased by approximately 0.70, 0.45, and 0.35 V for the basic SS-SMFC, SSSMFC with BNB, and SS-SMFC with LAB, respectively. From this, it can be said that adding either
BNB or LAB can improve the SS-SMFC performance. The improvement may be partly due to theenhanced electron transfer to the anode and the accelerated decomposition of organic matter by thebacteria; unfortunately, those reasons could not be examined in the present study.
In addition, having continuously generated electrical current for 40 days, the power densities
were 7, 16, and 25 mW.m-2 for the basic SS-SMFC, SS-SMFC with BNB, and SS-SMFC with LAB,
respectively (Fig. 6a), and the current densities were 180, 280, and 350 mA.m -2, respectively (Fig.
6b). These results suggest that the bacteria will continue to affect the SS-SMFCs during long-term
operations.
CONCLUSION
In this study, laboratory experiments were conducted to examine changes in the performance of the
PS-SMFC when using SS in the anode chamber and the applicability of LAB and BNB for improving
SS-SMFC performance. A twofold increase in the power density was observed, suggesting that theutilization of SS in the anode chamber improves the PS-SMFC performance. Furthermore, the powerⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

density increased by 2.9 times after adding BNB and 3.7 times after adding LAB to paddy soil,
thereby indicating that adding either LAB or BNB improves the SS-SMFC performance; further,adding LAB was shown to increase the SS-SMFC performance more. It was considered that thesebacteria enhance the electron transfer to the anode and accelerate the decomposition of organic matter.
ACKNOWLEDGEMENTS
The authors gratefully acknowledge the students of the Rural Environmental Engineering Laboratory,
Tokyo University of Agriculture, for their efforts in collecting data.
REFERENCES
Kouzuma, A., Kaku, N. and Watanabe, K. 2014. Microbial electricity generation in rice paddy fields: Recent
advances and perspectives in rhizosphere microbial fuel cells. Appl. Microbiol. Biotechnol, 98, 9521-9526.
Lovley, D.R., Holmes, D.E. and Nevin, K.P. 2004. Dissimilatory Fe (III) and Mn (IV) reduction. Adv. Microb.
Physiol, 49, 219-286.
Nagama, K, Yamaji, S, Miyatsu, T., Touch, N. and Hibino, T. 2018. Electrode potential-measured method andits practicality for monitoring the formation of hypoxic water. J. Jpn. Soc. Civ. Eng. Ser. B2 (Coast. Eng.),
74 (2), 1189-1194 (in Japanese).
Nagatsu, Y., Tachiuchi, K., Touch, N. and Hibino, T. 2014. Factors for improving the performance of sedimentmicrobial fuel cell. J. Jpn. Soc. Civ. Eng. Ser. B2 (Coast. Eng.), 70 (2), 1066-1070. (in Japanese)
Nishimura, k., Yamaji, S., Touch, N. and Hibino, T. 2018. Usable output of sediment microbial fuel cell under
the use of steel slag mixed-sediment as a fuel. J. Jpn. Soc. Civ. Eng. Ser. B2 (Coast. Eng.), 74 (2), 11831188 (in Japanese).
Sacco, N.J., Figuerola, E.L.M., Pataccini, G., Bonetto, M.C., Erijman, L. and Cortón, E. 2012. Performance ofplanar and cylindrical carbon electrodes at sedimentary microbial fuel cells. Bioresour. Technol., 126, 328335.
Sajana, T.K., Ghangrekar, M.M. and Mitra, A. 2013. Application of sediment microbial fuel cell for in situ
reclamation of aquaculture pond water quality. Aquacult. Eng., 57, 101-107.
Touch, N., Hibino, T., Kinjo, N. and Morimoto, Y. 2018a. Exploratory study on improving the benthic
environment in sediment by sediment microbial fuel cells. Int. J. Environ. Sci. Technol., 15, 507-512.
Touch, N., Hibino, T., Morimoto, Y. and Kinjo, N. 2017b. Relaxing the formation of hypoxic bottom waterwith sediment microbial fuel cells. Environ. Technol, 38 (23), 3016-3025.
Touch, N., Hibino, T., Nagatsu, Y. and Tachiuchi, K. 2014. Characteristics of electricity generation andbiodegradation in tidal river sludge-used microbial fuel cells. Bioresour. Technol, 158, 225-230.
Touch, N., Yamaji, S., Hiroki, T. and Hibino, T. 2017a. Solar cell-combined sediment microbial fuel cell forpreserving sediment and water environments. Int. J. Environ. Prot., 7 (1), 37-45.
Touch, N., Yamaji, S., Nagama, K., Miyatsu, T. and Hibino, T. 2018c. Improvement of sediment and water
quality with solar-cell combined sediment microbial fuel cells in oyster farms. Int. J. Environ. Prot., 8 (1),32-37.
Touch, N., Yamaji, S., Nishimura, K., Sunada, Y. and Hibino, T. 2018b. Remediation of sediment depositednear sewage outlet with solar cell-combined sediment microbial fuel cells. Int. J. Environ. Prot., 8 (1), 1824.
Touch, N., Yoshimura, K., Nishimura, K. and Hibino, T. 2019. Electrochemical method for treating excess
accumulated sediment on the riverbank of tidal rivers. J. Jpn. Soc. Civ. Eng. Ser. B2 (Coast. Eng.), 75 (2),1063-1068 (in Japanese).
Wang, X., Feng, Y., Ren, N., Wang, H., Lee, H., Li, N. and Zhoa, Q. 2009. Accelerated start-up of twochambered microbial fuel cells: Effect of anodic positive poised potential. Electrochem. Acta, 54 (3), 11091114.

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Research article
erd

Risk Assessment of Pesticide Use in Chinese kale Cultivationof GAP and Conventional Practice by EIQ in North-East
Thailand
JARUPONG PRASOPSUK
Office of Agricultural Research and Development Region 3,
Ministry of Agricultural and Cooperatives, Khon Kaen, Thailand

ARUNEE PROMKHAMBUT*
Faculty of Agriculture,Khon Kaen University, Khon Kaen, Thailand

SUWIT LAOHASIRIWONG
Faculty of Agriculture, Khon Kaen University, Khon Kaen, Thailand

CHULEEMAS BOONTHAI IWAI*
Faculty of Agriculture,Khon Kaen University, Khon Kaen, Thailand
Email: chuleemas1@gmail.com
Received 10 September 2019

Accepted 21 July 2020(*Corresponding Author)

Abstract This study reports the pesticide application and environmental impact in Chinese
kale cultivation under Good Agricultural Practice (GAP) and conventional practice in NorthEast, Thailand. The Environmental Impact Quotient (EIQ) model was applied in this study.
The data were collected by using semi-structured interviews and observation. GAP farmers(farmers in GAP's system) and conventional cultivation farmers (non-GAP farmers) were
purposive selected, 10 per each group with a total of 20 farmers. Data from farmer interviewson pesticides application, type of substances, application rates, frequency, and plot size wereused in the EIQ Field Use equation to assess environmental risks between the two practices.
The criteria are EIQ Field Use; <25 = very low risk <50 = low risk 50-99 = moderate risk
100-199 = high risk and> 200 = very high risk. The results showed that 15 active ingredientsin pesticide were found in GAP farms and 19 active ingredients in pesticide use were foundin non-GAP farms. The GAP Chinese kale has a lower level of impact on environmental
risks than the conventional one (Average EIQ Field Use: GAP = 87.4, non-GAP = 136.87).
This data indicates that the GAP system could reduce the risk of pesticides in the environmentof commercial vegetable-growing village.
Keywords environmental impact quotient, pesticide risk, good agricultural practice

INTRODUCTION
The increasing rate of pesticides application poses enormous challenges to manage the associatedrisks to people and ecosystems (Schreinemachers et al., 2017; Harnpicharnchai et al., 2013). In
conventional agricultural practice, the application of pesticides is a common practice among
vegetable grower due to the prevalent pest and disease problems. Pesticides are products that
improved agricultural productivity, although their inherent toxicity and misuse have led to various
adverse effects on important ecosystems and human health (Páez et al., 2013). Although nowadays
consumers are increasingly concerned about food safety and looking for safer food (Schreinemachers
et al., 2012). To reduce potential food hazards and increase the good image of Thai horticultural
products abroad, the Thai government introduced public standards of Good Agricultural Practice(GAP). This has been shown that the application of pesticides in a GAP system is a production
strategy that ensures sustainability and competitiveness. An environmentfriendly agriculturalⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

production and a contribution to the health of workers, consumers and other stakeholders in the foodchain, facilitate trade and international opportunities (Páez et al., 2013).
The long-term strategies to manage risks in the GAP system, farmers can pesticide to control
weeds, pests, and diseases following the principles of Integrated Pest Management (IPM) because
Good Agricultural Practice will be decided on interventions following consideration of all possible
methods and their short and long-term effects on-farm productivity and environmental implications
in order to minimize the use of agrochemicals, in particular, promote IPM (FAO, 2004). However,some growers and pest management practitioners did take into account the effect of the pesticides on
the applicator or beneficial natural enemies such as predatory mites when making pesticide
recommendations, but no formal method was available to assist them in making environmentally
based pesticide choices. Because there is no easy method to assess pesticide impacts, each individual
had to rely primarily on their own judgment to make these decisions (Kovach et al.1992).
The Environmental Impact Quotient (EIQ) is a formula created to provide growers with data
regarding the environmental and health impacts of their pesticide options, so they can make better
informed decisions regarding their pesticide selection. (Cornell University, 2018) The formula helps
to calculate the environmental impact of most common fruit and vegetable pesticides (insecticides,
acaricides, fungicides and herbicides) used in commercial agriculture. The values obtained fromthese calculations can be used to compare different pesticides and pest management programs toultimately determine which program or pesticide is likely to have the lower environmental impact.
The method addresses a majority of the environmental concerns that are encountered in agricultural
systems including farm worker, consumer, wildlife, health and safety (Kovach et al., 1992). Since
2000, the EIQ has been used in several IPM projects in Asia for different purposes ranging from
impact assessment to pesticide selection (FAO, 2008).
Chinese kale is one of the main vegetable growing in Khon Kaen province in North-East,
Thailand and is one of the major vegetable consumed in the region (National Bureau of Agricultural
Commodity and Food Standards, 2016). The vegetable is also susceptible to a substantial number ofarthropod pests and plant diseases, which farmers need a lot of pesticides to prevent crop damage.
For the commercial vegetable village in this study area, GAP farmers have used pesticides less than
non-GAP farmers because they were supported to pesticides used in accordance with IPM. However,there are no indicators that GAP can reduce the risk of pesticides used. Therefore, the EIQ impact
assessment will show the risk levels of both Chinese kale cultivation (GAP and non-GAP). This will
be answered that whether GAP compliance can reduce the risk of pesticides on environmental andhealth impacts or not. Moreover, it is expected that the results of the study can also be used to help
governmental agencies to implement better GAP programs in this region.
OBJECTIVE
To assess pesticide risk and environmental impact in Chinese kale cultivation among GAP andconventional practices.
METHODOLOGY
Data Collection
The commercial vegetable growing village in Muang District, Khon Kaen Province, Thailand was
purposively selected as a study site in this research. This village is a large vegetable production in
the area which farmers continue to grow vegetables for more than 30 years as it is the main sourceof their incomes. At the same time, this village is one of the pilot GAP vegetable production areasby the government. Since it is a voluntary scheme, there are both GAP farmers and non-GAP farmers
in the village. In this study, Chinese kale plots were purposively collected from 10 GAP and 10 nonGAP plots, as their farms scattered across the village. Pesticide application data were collected byusing a semi-structure interview and making observations, during January to October 2018. Data ofⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

pesticide compound, common name, active ingredient, % active ingredient, rate of application,
frequency of application and plot size were collected from sample plots.
Risk Assessment of Pesticide used by EIQ
The EIQ value for a particular active ingredient is calculated according to a formula that includes
parameters of toxicity (dermal, chronic, bird, bee, fish, and beneficial arthropod), soil half-life,
systemicity, leaching potential, and plant surface half-life are considered. The formula for
determining the EIQ value of individual pesticides is listed below and is the average of the farmworker, consumer, and ecological components. The EIQ Equation as in Eq.(1) (Kovach et al., 1992).
EIQ={C[(DT*5)+(DT*P)]+[(C*((S+P)/2)*SY)+(L)]+[(F*R)+(D*((S+P)/2)*3)+(Z*P*3)+(B*P*5)]}/3(1)

Where DT = dermal toxicity, C = chronic toxicity, SY = systemicity, F = fish toxicity, L =leaching potential, R = surface loss potential, D = bird toxicity, S = soil half-life, Z = bee toxicity, B= beneficial arthropod toxicity, P = plant surface half-life.
Field Use EIQ is calculated by multiplying the table EIQ value for a specific chemical by thepercentage of active ingredient in the formulation and its dosage rate per hectare, as in Eq. (2)Field Use EIQ = EIQ value x % active ingredient x Dosage rate

(2)

The risk level according to the EIQ Field Use Rating Levels; when EIQ Field Use less than 25= very low risk, less than 50 = low risk, 50-99 = moderate risk, 100-199 = high risk, over than 200= very high risk (Cornell University, 2018).
RESULTS AND DISCUSSION
Pesticide Applied in Chinese Kale Cultivation
In each crop production, different frequencies of different types of pesticides were found applied inboth GAP and non-GAP plots. The insecticides that commonly applied in all production cycle in bothplots indicating that insect damage in Chinese kale production in this area was critical and approaches
to reduce the infestation of insect must be seriously taken in to account. The types of pesticides
applied by farmers (GAP and non-GAP) were not different because most farmers buy pesticides at
the agro-chemicals shops in the village. For example, imidacloprid was commonly used for control
worms and aphids because this product is inexpensive, and easy to obtain from shops in the village.
In the rainy season, during the high pest epidemics, farmers will use pesticides with higher toxicity
levels, such as tolfenpyrad, profenofos and cypermethrin. However, considering number ofchemicals used, GAP farmers used less than non-GAP farmers (Table 1).
Based on a survey of pest control in the field, GAP farmers tried to use integrated pest
management methods, which were bio pesticide such as azadirachtin, Baciluss thuringiensis,
Trichoderma harzianum and Steinernema sp. Moreover, they also applied insect net for protection
against pests with government support, which non-GAP farmers do not have. This may be the reasonof fewer number of pesticides applied by GAP farmers and also indicate the important of intervention
form government agencies in terms of production and reducing pesticide application. However,factors affecting farmers' decision to apply pesticides include labor, market motivation, disease andinsect outbreaks, and size of vegetable plots.
Risk Assessment of Pesticide Applied in Chinese Kale Cultivation
The EIQ Field Use values were calculated by using data of pesticide applied in farmlands. The results ofⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

calculated EIQ Field Use for assessing pesticide risk revealed that EIQ Field Use (n =10) of GAP
farmers was in the range of 28-131 and the average EIQ Field Use values is 87.42 (Ratinglevel=moderate risk). Although the EIQ Field Use (n =10) of non-GAP farmers was in the range 30–393
and the average EIQ Field Use values is 136.87 (Rating levl= high risk). This data shown in Table 2.
Table 1 Pesticide application of GAP and non-GAP farmers in Chinese kale plots

Pesticides%ActiveingredientTypeabamectin
acetamiprid
alachlor
carbarylchlorfenapyr
chlorantraniliprole
chlorpyrifos+cypermethrin
cypermethrin
diazinondichlorvos
dinotefuranemamectin benzoate
haloxyfop-p- methyl
imidacloprid
indoxacarb
mancozeb
oxadiazon
profenofos
spinetoram
tolfenpyrad

I
I
H
I
I
I
I
I
I
I
I
I
H
I
I
F
H
I
I
I

1.8%W/V EC
20% SP
48%W/V EC
85%WP
10%W/V EC
5.17%W/V SC
50%+5%W/V EC
35%W/V EC
60% W/V EC
50%W/V EC
10% WP
5% WG
10.8%W/V EC
70% WG
15%W/V EC
85%WP
25%W/V EC
50%W/V EC
12% W/V SC
16% EC

Application rate per 20 L
water

Frequency of
application per crop

GAP
20-30 ml
5g
150 ml
20 g
40 ml
40 ml
10-20 ml
40 ml
50 ml
5g
50 g
100 ml
20 ml
15 ml
20 ml

GAP

non-GAP
20-30 ml
5g
100-175 ml
30 g
40 ml
20 ml
10-30 ml
40 ml
10-60 ml
10-15 g
10 g
50 ml
10 g
10 ml
40 g
100 ml
10 ml
10 ml
40 ml

3-6
2
1

1
1
2
1-6
3
1
2

1

1
3
3
1

non-GAP
3-6
2
1
3
1
6
3
1
2-6
1-4
2
1
2
1
6
1
4
4
1-5

Remark: Collected samples (N=20) from 10 GAP and 10 non- GAP farmers interviews in March to May 2018 of Muang
District Khon Kaen Province Thailand. I= Insecticide, H=Herbicide, F= Fungicide, Application rate per 400 m2 plot size.

Table 2 EIQ Field Use of GAP and non-GAP Chinese kale cultivation
Type of Chinese
kale cultivationEIQ Field Use(Min-Max)

Average
EIQ Field Use

S.D.

Risk rating

GAP (N=10)
non-GAP (N=10)28-13130-39387.42
136.8731.38
115.76Moderate risk
High risk

Remark: when EIQ Field Use less than 25 = Very low risk, less than 50 = Low risk, 50-99 = Moderate risk,
100-199 = High risk, over than 200 = Very high risk (Cornell University, 2018).

The numbers of GAP and non-GAP Chinese kale farms classified by EIQ Field Use rating arepresented in Fig.1. The result of calculated EIQ Field Use risk assessment of pesticide application
revealed that in 10 GAP farms there are4 farms with high risk levels (40%), 5 farms with moderaterisk levels (50%) and 1 farm with low risk levels (10%). Within the 10 non-GAP farms, there are 3very high risk levels (30%), 2 farms with high risk levels (20%), 4 farms with moderate risk levels(40%), and 1 farm with low risk levels (10%).

Ⓒ ISERD10umber of farmers

IJERD – International Journal of Environmental and Rural Development (2020) 11-2

Risk
ratingFig.1 Number of GAP and non-GAP Chinese kale farms classified by EIQ Field Use rating
CONCLUSIONGAP Chinese kale cultivation has a lower level of impact on environmental risks than that ofconventional one (Average EIQ Field Use: GAP = 87.4, non-GAP = 136.87). This data indicates that
the GAP system could reduce the risk of pesticides application in the environment of commercial
vegetable-growing village.
ACKNOWLEDGEMENTS
This study was funded by The Agricultural Research Development Agency (Public Organization)
Bangkok, Thailand. The authors would like to thank the Office of Agricultural Research andDevelopment Region 3, Department of Agriculture, Ministry of Agriculture and Cooperatives,
Thailand for participating in this research.
REFERENCES
Cornell University. 2018. A method to measure the environmental impact of pesticides. Environmental Impact
Quotient: An Introduction. https://nysipm.cornell.edu/eiq.
FAO. 2004. Good agricultural practices a working concept background paper for the FAO internal workshop
on good agricultural practices, FAO Agriculture Department. FAO GAP Working Paper Series 5. Foodand Agricultural Organization of the United Nation. Rome, Italy.
FAO. 2008. IPM impact assessment series. Review use of environmental impact quotient in IPM programmed
in Asia. Food and Agricultural Organization of the United Nation, Rome, Italy.
Harnpicharnchai, K., Chaiear, N. and Charerntanyarak, L. 2013. Residues of organophosphate pesticides usedin vegetable cultivation in ambient air, surface water and soil in Bueng Niam Subdistrict, Khon Kaen,
Thailand. Southeast Asian J. Trop. Med. Public Health, 44, 1088-1097.
Kovach, J., Petzoldt, C., Degnil, J. and Tette, J. 1992. A method to measure the environmental impact ofpesticides. New York's Food and Life Sciences Bulletin. New York, Cornell University, New York, USA.
National Bureau of Agricultural Commodity and Food Standards. 2016. Food consumption data of Thailand.
Bangkok, Thailand.
Paez, M., Sánchez, R. and Castro, R. 2013. Environmental impact quotient (EIQ) as an indicator for thesustainability in tomato crops with traditional and GAP’s systems. Department of Caldas. Colombia.
https://www.york.ac.uk/conferences/yorkpesticides2013/pdfs/134.pdf.
Schreinemachers, P., Chen, H., Nguyen, T.T.L., Bontong, B., Bouapao, L., Guatam, S., Le, N. T., Pinn, T.,
Vilaysone, P. and Srinivasan, R. 2017. Too much to hand? Pesticide dependence of smallholder vegetable
farmers in Southeast Asia. Sci. Total Environ., 593-594, 470-477.
Schreinemachers, P., Schad, I., Tipraqsa P., Williams, P. M., Neef, A., Riwthong. S., Sangchan, W. andGroverman, C. 2012. Can public GAP standards reduce agricultural pesticide use? The case of fruit andvegetable farming in northern Thailand. Agric. Hum. Values, 29, 519-529.
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Research article
erd

Farmers’ Perceptions on Soil Degradation and their
Criteria to Adopt Soil and Water Conservation Strategies in
Ovche Pole Region in North Macedonia
OGNEN ONCHEVSKI
Graduate School of Agriculture, Tokyo University of Agriculture, Japan
E-mail: ognenoncevski@hotmail.com

MACHITO MIHARA*
Faculty of Regional Environmental Science, Tokyo University of Agriculture, Japan
E-mail: m-mihara@nodai.ac.jp
Received 22 January 2020

Accepted 11 September 2020(*Corresponding Author)

Abstract Ovche Pole is a region in Macedonia where the main economic activity of people
is agriculture. Moderate-continental-sub-Mediterranean climatic conditions are prevalent in
the area. However, based on the data for average annual precipitations (P) and potential
evapotranspiration (PET), the region has aridity index of 0.64, thus it is classified as dry subhumid and vulnerable to desertification. The region is dominated by agriculture land whichtakes 62% of total area, followed by forests and pastures that takes 22.55% and 14%
respectively. Vertisols are the dominant soil type, taking 51.24% of total area in the region.
Climatic conditions, together with the unsustainable agricultural practices highly influence theprocess of land degradation, especially soil degradation in the region. The key for success ofany land restoration activity is the involvement of local communities. Understanding thefarmers’ perceptions on this issue is crucial for development and implementation ofsustainable resource management strategies. Therefore, the objectives of this study are to: (i)assess farmers’ perceptions on different types of soil degradation and (ii) examine farmers’
perception and motivation for adopting new SWC practices. A semi-structured questionnaire
was developed and distributed to farmers to gather primary data. Out of total population of
375 registered farmers, following convenience sampling method, 102 farmers took a part in
the questionnaire survey. Secondary data on climate/weather, land use, soils, demography was
obtained from published or unpublished sources. The results of the study show that farmers
could observe different soil degradation process on their land. Most of the farmers perceived
decline in soil moisture retention as most intense and most significant problem. For majority
of interviewed farmers, the main criteria to adopt SWC are the increased financial benefits andgains from the new measure and financial incentives provided by government institutions.
Keywords farmers’ perceptions, questionnaire survey, soil degradation, soil and water
conservation

INTRODUCTION
The Land Degradation Assessment in Drylands (LADA) project (2011) reported that “Soildegradation occurs as a result of adverse changes in the soil biological, chemical, physical and/orhydrological properties. Such changes can increase the vulnerability of the soil to further degradation”.
Although, soil degradation is influenced by local environmental conditions such as climate,topography, soil type etc., farmers with their land management practices can exacerbate degradation
processes too. Therefore, adoption of SWC measure is required to prevent or revers degradation ofnatural resources. However, achieving success in SWC programs is difficult because many constrainsplay a role. Deciding to adopt SWC measures is complicated process influenced by many factors
such as the agro- ecological conditions, socioeconomic and cultural characteristics of the farmers’
population (Calatrava et al., 2011; Pulido and Bocco, 2014). Decision to adopt SWC measures drivenⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

by intrinsic factors can promote long lasting behavioral change, while decisions made only becauseof extrinsic motivation factors, such as financial incentives provide less stable changes.
Understanding the motivation factors that influence farmers to implement new SWC will help
policymakers to design more effective SWC strategies and manage conservation programs more
successfully. Top-down oriented projects in general are not so successful; Development
organizations focus more on participatory methods emphasizing the importance of beneficiaries’commitment and engagement in activities (Kessler, 2006).
OBJECTIVE
The objectives of this research are (i) to assess farmers’ perceptions of different types of soil
degradation and (ii) to examine farmers’ perception and motivation for adopting new SWC practices.
METHODOLOGY
Study Area Description
The region of Ovche Pole is a plain located in the east central part of Macedonia and takes an areaof 649 km2 (Fig. 1). Administratively, the region is divided into two municipal units, Sveti Nikole
and Lozovo. According the last census municipalities together had population of 21.355 people (State
Statistical Office, 2002). Highest point is on 856 m above sea level, however the average elevationof the region is between 200 and 400 meters. Three characteristically different landscape types canbe distinguished in the region. Agricultural flatland landscape on saline ground takes the flat areas
up to elevation of 350 m. specific for this area is the presence of halomorphic soils. Lowland rolling
agricultural landscape, which are the areas found up to elevation of 500 m.a.s.l. represented by hills
with mild slopes. The third specific landscape type is the lowland rolling agricultural landscape withwind hedges. Specific for this area is the presence of man-made corridors of trees and shrubs that
protect the agriculture land from the prevailing winds (Melovski et al., 2015).

Fig. 1 Geographical position of the research area (in red borders of the right picture)
The climate in the region is modified warm continental with Mediterranean influence (Zikov,
1995; Filipovski et al., 1996). Specific for this region is the occurrence of strong winds coming fromthe north-west, north, south-east direction present most of the time of the year. Analysis of climatic
data for the period between 1950 and 2000 showed that the average annual precipitation is 471.1 mm
and the average annual evapotranspiration is 734.4 mm, with an aridity index of 0.64. According to
the UNCCD this classifies the region as dry sub-humid and vulnerable of desertification (Blinkov etal., 2005; Miladinovc et al., 2006). The region is dominated by vast areas under arable fields andcroplands. Although, agriculture land takes 40 183 ha (62 % of the total land), much of the arable
land is not irrigated (Fig. 2). Forests cover 14 619 ha (22.5%) of which 2/3 are degraded, whereas
9134.38 ha (14%) are pastures (CORINE LC/LC, 2012). Vertisols are the dominant soil type in theⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

region, almost entirely distributed in areas where agriculture is intensively practiced. This soil typeis distributed on 33 422 ha or 51.24 % of the land (MASIS). Farmers mainly produce grains such as
wheat and barley, however there are areas where tobacco, alfalfa, melons, and vegetables arecultivated.

Fig. 2 Agriculture landscape in the research area
Data Collection and Analysis
The study was conducted from 7th of September to 7th of October 2019. Semi-structured questionnaire
was developed and distributed to farmers to gather primary data. Using convenience sampling
method, 102 farmers took a part in the questionnaire survey, out of a population of 375 registeredfarmers (MAFWM, 2019). The interviews with the farmers were done at any place they were met,
usually in the field, local bars and shops in the villages or in their homes. Part of the questions were
designed in a 5-point liker-type scale, ranging from “strongly not agree” to “strongly agree”, however
some information were gathered through ranking questions. The question statements were put in
simple language, however in case when person could not understand some part additional
explanation were given to them. The questionnaire was designed to have three sections. The firstsections, contained questions related to socioeconomic characteristic of farmers as well as the land
management practices. Second section, captured farmers’ perceptions on soil degradation. Questionsin the third section captured farmers’ perceptions on SWC and their drivers of motivation to adopt
new SWC measures. Simple descriptive statistics such us frequency distribution and percentage wereused to interpret and present data. Secondary data on climate/weather, land use, soils, demography
was obtained from published or unpublished sources. The number of registered farmers was provided
by The Ministry of Agriculture, Forestry and Water Management (MAFWM). Data on land use/landcover was obtained from the CORINE Land Cover (CLC2012) data set from 2012, program
coordinated by European Environmental Agency (EEA). Data from The Macedonian Soil
Information System (MASIS) was used to analyze characteristics and distribution of the soil in the
research area.
RESULTS AND DISCUSSION
Farmers’ Perceptions on Soil Degradation Processes
Questionnaire results showed that 89% of the respondents noticed some negative changes related tosoil quality. Table 1 outlines farmers’ perceptions on the degree of intensity of soil degradation
processes on their land. The farmers could choose one response on an intensity scale with five levelsof degree ranging from no presence of soil degradation to extreme intensity of soil degradation. The
results showed that water logging and salinization and/or alkalinisation were not present at all forⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

91% and 82% of the farmers, respectively. However, majority of farmers reported some degree ofdegradation, for the other investigated soil degradation processes. Decline of soil moisture retention
was perceived as most insensitively present problem; 77% of the farmers reported strong and 6%
extreme degree of this type of soil degradation. For loss of fertility and loss of soil structure, majorityof the respondents’ answers ranged between light, moderate and strong. Regarding, loss of topsoil
and erosion 46% of the farmers reported light intensity, 31% reported no presence and 20% moderateintensity. However, for loss of life and biodiversity the results showed two tendencies in the response.
A group of 39% of respondents that did not notice this problem and a group of 32% reports strong
intensity of loss of soil life and biodiversity.
Regarding the perception for the time of beginning of these issues, 12% of respondents answeredthat the soil degradation issues started in the past 5 years, 35% said in the past 10 years, 25% in thepast 15 years, 15% said in the past 20 years and 13% told they don’t know. In addition, 69% of
farmers said that now they use more fertilizers compared to the past 10 years. Farmers were asked torank the soil degradation processes by the degree of significance for their farming activities. The
results from the data analysis are visually presented in Fig. 3. The sample group gave consistentanswers when ranked the 1st and 2nd most significant soil degradation issues. Decline in soil
moisture retention capacity was ranked as the most significant problem by 89% of the respondents.
The loss of soil fertility was ranked 2nd most significant issue by 75% of farmers. Loss of soil
structure and loss of topsoil and erosion were ranked 3rd and 4th most significant issues, respectively.
Loss of life and soil biodiversity was ranked 5th most significant issue. These results can be explained
if we have in mind the climatic conditions and properties of Vertisols-the dominant soil type in theregion.
Table 1 Farmers' perception on soil degradation intensity degree
Type of degradation

Intensity of soil degradation process
Not present

Light

Moderate

StrongExtremeLoss of topsoil and erosion.

31%

46%

20%

3%

0%

Loss of soil fertility

3%

17%

44%

34%

2%

Loss of soil structure

4%

24%

48%

24%

1%

Water logging of soil

91%

7%

1%

1%

0%

Loss of life and soil biodiversity

39%

14%

9%

32%

6%

Salinization and/or alkalinisation

82%

16%

2%

0%

0%

Decline in soil moisture retention

4%

4%

2%

77%

13%

Own Source: Data provided by questionnaire survey, 2019

The World Soil Resource Report (2015) notes that “the physical properties and the soil moistureregime of Vertisols represent serious management constraints. The heavy soil texture and dominationof expanding clay minerals result in a narrow soil moisture range between moisture stress and water
excess” (IUSS Working Group WRB, 2015). According to Alvaro-Fuentes et al. (2008) “Soil organic
matter (SOM) is a key factor in semiarid agrosystem production” (Álvaro-Fuentes et al., 2008). In
their study on effects of soil organic matter on soil productivity, Bauer and Black (1994) concluded
that loss of fertility explained loss of productivity due to a depletion of soil organic matter.
Soil and Water Conservation Practices among Farmers
The results from the questionnaire showed that 77% of the farmers practice some measure for SWC
conservation and 23% did not. Fig. 4 shows information on the different SWC practices implemented
by farmers. Farmers practice only traditional conservation measure such as manuring, crop rotationand fallow. Except drip irrigation which is integrated by 5% of respondents, no other new
technologies or practices are implemented. The involvement of government institutions or otherⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

organization to support and encourage farmers in implementation of SWC is absent. The results ofthe survey showed that 96% of farmers are not familiar with government programs aimed to support
SWC. In addition, 98% of farmers have never been contacted by any institution or organization on
SWC and issues related with soil degradation.
89%
75%

52%
44%

41%

38%

16%
6%
1% 3%

12%

6%

1%

3%

36%

33%

4%

1% 2% 3%

11%
7%
2% 2%

7%

4%

1%

1st most significant 2nd most significant 3rd most significant 4th most significant 5th most significant
1- erosion and soil loss

2- loss of soil ferility

3- problem with soil structure

4- water logging

5- loss of life and bidiversity of soil

6- salinization/alkalinisation

7- decline in soil moisture retention

0- didn't answer

Fig. 3 Ranking of soil degradation issues by significanceRespondents (%)

82%

56%
48%
40%
36%

33%

17%
3%

6%

9%

12%

11% 10%
2%

8%

1%

3% 3%

4%

8%
1%

2%

4% 2%

1st most relevant criterion 2nd most relevant criterion 3rd most relevant criterion 4th most relevant criterion

To reduce inputs and costs for land management
To ensure conservation and sustainability of the natural environment
Time and labor consuming aspects
Not to take additional economic resources for implementation.
To guarantee an income for the farm in the short term
To guarantee better soil health/quality and climate change resilience
Didn't answer

Fig. 4 Distribution of different soil and water conservation practices among farmers
Farmers’ Motivation for Adopting New Soil and Water Conservation Practices
On the question if there is an interest in adoption of SWC measures among farmers, 61% answered
affirmative, 19% said that there is no interest and 20% did not know how to answer. Perception ofexisting a future risk can be a driver for behavioral change, in this case adoption of SWC measure.
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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

Therefore, farmers were asked if they believe that soil degradation issues would increase, stay sameor decrease in future. Out of all, 95% answered that the soil degradation processes will increase in
future and only 3% and 2% believed that issues will stay same and decrease, respectively. In thisstudy respondents were asked to rank relevant criteria expected when adopting new SWC measure.
The results presented in Fig. 5 show that the three most relevant criteria are related to the economic
benefits of the farmers. Better soil quality and climate change resilience is on the fourth place ofimportance.
No SWC measure
Manure(Ma)30%

Fallow(Fa)23%

Respondents (%)

Crop rotation (Cr)Manure + Crop rotation
Manure + Drip irrigation
12%
6%

7%

8%

Manure + Fallow

7%

Manure + Fallow + Crop rotation

4%
1%

1%

1%

Manure+Fallow+Crop rotation+Drip irrigation
Fallow+Crop rotation

Soil and water conservation (SWC) measures

Fallow+Crop rotation+Drip irrigation

Fig. 5 Farmers' ranking of relevant criteria for adoption of SWC measure
91%

85%
77%
1-Financial supportand incentives
2-Education andtraining
3-Technical support

15%
8%

14%

8%

1%
1st most relevant need1%
2nd most relevant need

3rd most relevant needFig. 6 Ranking of relevant need for adoption of SWC measure
To extract information on what farmers need to adopt new soil and water conservation measure
they were asked to rank among: education and training, technical support and financial incentives.
Participants in the survey ranked financial support and incentives as most relevant need for adoptionof new SWC measure, technical support was ranked 2nd whereas education and training 3th most
relevant need for adoption of new SWC measure. The results are presented in Fig. 6 of thismanuscript. A study that compared results of independent research projects in five developing
countries showed that factors that motivates farmers are always context-specific and generalization
is not possible. However, in general profitability and financial benefits are common factors that
influence farmers to adopt SWC measures (de Graaff et al, 2008). Other authors had similar
conclusion that resource conservation should be accompanied by short-term economic benefits forfarmers (Pulido and Bocco, 2014). However Calatrava et al. (2011) in their study on policy measures
for agricultural soil conservation in semi-arid Mediterranean areas noted that “stakeholders statedⒸ ISERD

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that the most important and effective measure is to provide technical education and information tofarmers to convince them of the benefits of conservation practice.”
CONCLUSION
General perception among the participants in the study is that biggest issues come from the decline
in soil moisture retention, decline of soil fertility, soil structure and soil erosion. Soil degradation is
induced as a result of combination of factors such as climatic conditions in the region and theproperties of the dominant soil type, however problems are exaggerated by the land management
practices. Although, 76% of the farmers of Ovche Pole region implement one or more SWC measure,most farmers execute only some traditional and very basic land management practices, new SWC
practices have been rarely or not adopted at all. Extending of the traditional measures andintroduction of new practices is needed, however this would require education, technical andfinancial support for farmers. Results of this study point out that SWC needs to be followed by shortterm financial benefits through improved production and reduced costs, which are primary interestof farmers. Therefore, as a way to promote and encourage conservation agriculture, government must
provide direct or indirect subsidies for farmers that implement SWC measures. In addition,
institutions should provide financial support and incentives for farmers in the initial phase of
implementation so they can overcome the initial investment constrains that they usually face. So far,the engagement of relevant government or non-governmental agencies to support farmers in adoptionof new SWC strategies is very low. Therefore, development of capacity of institutions andorganizations to conduct SWC programs and support farmers to implement measures on their landis needed. Commitment should be on a long term and project interventions need to have longer
project cycle. Establishment of research and demonstration sites where farmers can directly see thebenefits of SWC and be trained should be considered as appropriate strategy for long term results.
Local solutions and innovations, as well as farmer-to farmer knowledge dissemination should be
encouraged.
REFERENCES
Álvaro-Fuentes, J., López, M., Cantero-Martinez, C. and Arrúe, J. 2008. Tillage effects on soil organic carbon
fractions in Mediterranean dryland agroecosystems. Soil Science Society of America Journal, 72 (2), 541547.
Bauer, A. and Black, A. 1994. Quantification of the effect of soil organic matter content on soil productivity.
Soil Science Society of America Journal, 58 (1), 185-193.
Blinkov, I., Vasilevski, K. and Miladinovic, M. 2005. An analyze of some particular conditions referred to lenddegradation and desertification processes in the Republic of Macedonia (preliminary results), Scientific
Conference Youndula 5-8.X 2005, Bulgaria.
Calatrava, J., Barberá, G. and Castillo, V. 2011. Farming practices and policy measures for agricultural soil
conservation in semi-arid Mediterranean areas: The case of the Guadalentín basin in southeast Spain. Land
Degradation & Development, 22 (1), 58-69.
FAO. 2011. Land degradation assessment in drylands: Manual for local level assessment of land degradationand sustainable land management. Part 1: Planning and methodological approach, analysis and reporting.
Food and Agriculture Organization of the United Nations, Rome, Italy, 28.
Filipovski, G., Rizovski, R. and Ristevski, P. 1996. Characteristic of the climate–vegetation–soil zones(regions) in the Republic of Macedonia. Macedonian Academy of Sciences and Arts, Skopje.
Graaff, J. de., Amsalu, A., Bodnár, F., Kessler, A., Posthumus, H. and Tenge, A. 2008. Factors influencing
adoption and continued use of long-term soil and water conservation measures in five developing countries.
Applied Geography, 28 (4), 271-280.
IUSS Working Group WRB. 2015. World reference base for soil resources 2014, update 2015. Internationalsoil classification system for naming soils and creating legends for soil maps. World Soil Resources
Reports No. 106. FAO, Rome, 18.
Kessler, C. 2006. Decisive key-factors influencing farm households' soil and water conservation investments.
Applied Geography, 26 (1), 40-60.

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Melovski, Lj., Jovanovska, D. and Avukatov, V. 2015. Landscape diversity in Bregalnica Watershed. Finalreport of the project “Ecological Data Gap Analysis and Ecological Sensitivity Map Development for the
Bregalnica River Watershed”, Book 3, Skopje, 18-21.
Mitkova, T. and Mitrikeski, J. 2005. Soils of the Republic of Macedonia: Present situation and future prospects.
European Soil Bureau, 225-234.
Pulido, J. and Bocco, G. 2014. Local perception of land degradation in developing countries: A simplified
analytical framework of driving forces, processes, indicators and coping strategies. Living Rev. LandscapeRes, 8.
State Statistical Office. 2002. Census of population, households and dwellings in the Republic of Macedonia,
2002 - Book XIII.
Zikov, M. 1995. Climate and climate regionalization in Republic of Macedonia. Geographical consideration,
Skopje 30, 13-21.

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Research article
erd

Combination of Entomopathogenic Fungi with Essential Oil
for Controlling Bean Fly, Ophiomyia phaseoli Tryon(Agromyzidae: Diptera)
MALEE THUNGRABEAB
Agricultural Technology Research Institute, Rajamangala University of Technology Lanna,
Lampang, Thailand

PATCHARIN KRUTMUANG*
Department of Entomology and Plant Pathology, Faculty of Agriculture, ChiangMai University,
ChiangMai, Thailand
Email: patcharink26@gmail.com
Received 6 March 2020

Accepted 12 October 2020(*Corresponding Author)

Abstract The objective of this study was to evaluate the compatibility of entomopathogenic
fungi with repellants to control bean fly, Ophiomyia phaseoli Tryon (Agromyzidae: Diptera).
Nine isolates of entomopathogenic fungi belonging to 3 genera and 5 species were screened
for pathogenicity against bean fly. The results found that Beauveria bassiana isolate Bff andMetarhizium anisopliae isolate Mff caused 100% mortality to both its larval and adult stages.
The repellency of 7 essential oil was also evaluated against adult bean fly in the laboratory.
The results showed significant differences in repellency among essential oil andconcentrations. Essential oil extract from pomelo peeling was the strongest repellant followed
by eucalyptus and sweet basil. However, essential oil extract from camphor was the weakest
repellant. On the other hand, these seven essential oils (pomelo, zingiber, citronella grass,
eucalyptus, camphor, kaffir lime and sweet basil) at a concentration of 0.1% had no effect on
the viability of conidia, but at higher concentrations it was found that citronella grass andzingiber reduced viability of B. bassiana. The results on the effect of essential oils on colony
growth showed the same tendency as the one on the viability of conidia.
Keywords bean fly, entomopathogenic fungi, essential oil, repellent

INTRODUCTION
Phaseolus vulgaris L., French bean is a herbaceous annual plant in the Fabaceae family, it grows to
between 20-60 cm high; and twining, climbing vines up to 2-5m long. The stems of bushy types arerather slender, pubescent with many branches (Chávez-Servia et al., 2016). In twinning types, thestems are prostrate for most of their length and rise toward the end. The leaves, borne on long green
petioles, are green or purple in colour and trifoliate. Leaflets are 6-15 cm long and 3-11 cm broad.
The inflorescences are axillary or terminal, 15-35 cm long racemes. The flowers are arranged in pairs
or solitary along the rachis, white to purple and typically papillonaceous. Once pollinated, eachflower gives rise to one pod. Pods are slender, green, yellow, black or purple in colour, sometimes
striped (Caproni et al., 2019) . They can be cylindrical or flat, straight or curved, 1-1.5 cm wide andup to 20 cm in length. The pods may contain 4 to 12 seeds. The seeds are 0.5-2 cm long, kidneyshaped and highly variable in colour depending on the variety: white, red, green, tan, purple, gray or
black.
French bean is a major plant of Royal Project Foundation for the growers of organic vegetablesystem in Thailand. However, the problem of French bean plantation is bean fly, Ophiomyia phaseoli
Tryon (Agromyzidae: Diptera) (Ojwang et al., 2010) .They lay eggs in the leaf tissue or directly on
the stem. Early signs of attack are egg laying punctures on the primary leaves which tend to beconcentrated around the leaf base (Letourneau, 1994). Eggs hatch into small white maggots which
migrate down the stem to the root zone where they pupate into brown puparia. Severe damage isⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

indicated by wilting and dying of seedlings. The attack disrupts nutrient transportation, causing thetap root to die (Ssekandi et al., 2016). The plant attempts to recover by forming adventitious roots
above the damaged area (Ojwang et al., 2010). Young seedlings under stress wilt and die within ashort time. Older and more vigorous plants may tolerate the damage but become stunted and will
have reduced yield. Control strategies for grower to use were as follow: application of botanicalpesticides, natural enemies, sticky trap and also chemical seed dressing with systemic insecticides.
Plutachis sp. Eulophid, Biosteres sp. Pteromalid sp. nematode and Oecophylla smaragdina Fabricius
were effective against bean fly by 52% but bean fly still serious pest of French bean plantation(Jaramillo et al., 2013).
OBJECTIVES
The objectives of this study were: firstly to screen promising entomopathogenic fungi against bean
fly and secondly to evaluate plant-based insect repellants and their compatibility with theentomopathogenic fungi in controlling bean fly.
MATERIALS AND METHODS
Selection of Entomopathogenic Fungi from Collection
Nine isolates of entomopathogenic fungi consisting of 3 different genera and 5 different species wereselected from Agricultural Technology Research Institute, Rajamangala University of Technology
Lanna, Lampang 52000, Thailand. These were screened for their efficacy against bean fly underlaboratory condition.
Selection of Plants as Repellants Against Bean Fly
Selection of plants that have potential to repel bean fly was conducted according to the literature
reviewed that hinted on the plants that have essential oils that repel invertebrates (Showler, 2017 andAbtew et al., 2015). Extraction of essential oil was done using the Steam-distilled method(Mcguinness, 2003). After that, Study on the efficacy of essential oil that repel bean fly at difference
concentration was conducted. Moreover, study on effect of essential oil to germination ofentomopathogenic fungi and study effect of essential oil to growth of entomopathogenic fungi wasalso conducted (Liu, 2012).
Efficacy of Formulation of Entomopathogenic Fungi Combine with Repellant
This was conducted with the aim to produce an efficient formulation of entomopathogenic fungi forcontrolling bean fly. The formulation was produced by mixing 20% of entomopathogenic fungi +1% of Tween 80 at a concentration of 10% + 1% of Glycerin + 5% vegetable oil + 3% Propylene
glycol (Malee, 2015). This was then applied on French bean leaves to assess the spore viability andefficacy of formulation of entomopathogenic fungi against bean fly. The experiments were carriedout in 3 treatments: formulation 1 (Beauveria bassiana), formulation 2 (Metarhizium anisopliae) andcontrol. Suspension was directly sprayed on to the bean fly.
RESULTS AND DISCUSSION
Efficacy of Entomopathogenic Fungi to Infected Bean Fly
Nine isolates of entomopathogenic fungi belonging to M. anisopliae, B. bassiana Isaria
fumosoroseus, Isaria tenuipes and Isaria farinosus were selected for this study. The results forpathogenicities of 9 isolates of these entomopathogenic fungi showed high virulence against larvalⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

and adult stage of bean fly. It was observed that B. bassiana isolate Bff and M. anisopliae isolate
Mff caused 100% mortality to both larval and adult stages of bean fly as shown in Table 1. This wasa very impressive result and is in agreement with several studies (Letourneau, 1994). The otheradvantage of these entomopathogenic fungi is that they offer endophytic advantages as well to theplanted when they are inoculated (Mantzoukas and Eliopoulos, 2020).
Table 1 Percent mortality of entomopathogenic fungi to bean fly (larval stages)
Entomopathogenic fungi*
Metarhizium anisopliae

Beauveria bassiana

Isaria fumosoroseus
Isaria tenuipes
Isaria farinosus

Isolates

Percent mortality

Ma.4849
Ma.7965
Mff
Bb.5335
Bb.4591
Bff
Pfu.2507
Pt.6073
If 2549

80.00
93.33
100.0
80.00
80.00
100.0
60.00
46.67
40.00

*Fungus isolates from Agricultural Technology Research Institute, Rajamangala University ofTechnology Lanna, Lampang

Efficacy of Plants as Repellants Against Bean Fly

Repellents (%)

The repellency of 7 essential oil was evaluated against adult bean fly in the laboratory. The results
showed significant differences in the repellency among essential oils in different concentrations.
Essential oil extract from peel of pomelo was the strongest repellent followed by eucalyptus andsweet basil. Essential oil extract from camphor was observed to be the weakest repellent as indicatedin Fig. 1. In addition, the seven essential oils (pomelo, zingiber, citronella grass, eucalyptus,
camphor, kaffir lime and sweet basil) a concentration of 0.1% had no effect on the viability ofconidia, but in higher concentrations, it was observed that citronella grass and zingiber reduced
viability of B. bassiana. The results on the effect of essential oils on colony growth showed the sametendency as shown in the viability of conidia (Fig. 2). These results did not deviate much from otherstudies (Liu, 2012). Compatibility of these EPFs is known to be of paramount effect on theireffectiveness and hence cannot be omitted (Neves et al., 2001).

Fig. 1 Percent efficacy of plants as repellents against bean flyⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

0.10% Beaveria

0.10% Metarhizium

1% Beaveria

1% Metarhizium

Inhibition (%)

Inhibition (%)

zingiber

eucalyptus

sweet basil

camphorcitronella grass

kaffir lime

pemeloFig. 2 Percent inhibition of plant repellent to Beauveria spp. and Metarhizium spp.
Efficacy of Formulation of Entomopathogenic Fungi Combine with Repellent
Concerning the potentiality of formulation of entomopathogenic fungi in combination with essential
oils against bean fly, it was observed that when entomopathogenic fungi combine with essential oil
there was increased effectiveness in controlling bean fly. This is an interesting finding as they would
complement without adverse effects. Ali et al (2018) also worked with eucalyptus andentomopathogenic fungi observed remarkable potential in their compatibility and the resultant
efficacy.
CONCLUSIONSOut of 9 isolates, 2 isolates i.e., B. bassiana isolate Bff and M. anisopliae isolate Mff showed thehighest mortality against both larval and adult stages of bean fly. Formulation of entomopathogenic
fungi took time to ablate from French bean leave which was very impressive. Essential oil extractfrom peel of pomelo was a stronger repellent followed by eucalyptus and sweet basil. However,essential oil extract from camphor was a weaker repellent. It was also observed that a concentrationof 0.1% had no effect on the viability of conidia, but at higher concentrations it was found thatcitronella grass and zingiber reduced viability of B. bassiana. The results on the effect of essential
oils on colony growth showed the same tendency as the one on the viability of conidia.
Entomopathogenic fungi combined with essential oil had high potential in controlling bean fly.
ACKNOWLEDGEMENTS
This research was funded by Highland Research and Development Institute (Public Organization).
REFERENCES
Abtew, A., Subramanian, S., Cheseto, X., Kreiter, S., Garzia, G. T. and Martin, T. 2015. Repellency of plant
extracts against the legume flower thrips Megalurothrips sjostedti (Thysanoptera: Thripidae). Insects, 6(3), 608-625.
Ali, S., Farooqi, M.A., Sajjad, A., Ullah, M.I., Qureshi, A.K., Siddique, B. and Asghar, A. 2018. Compatibilityof entomopathogenic fungi and botanical extracts against the wheat aphid, Sitobion avenae (Fab.)(Hemiptera: Aphididae). Egyptian Journal of Biological Pest Control, 28 (1), 4-9.
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Caproni, L., Raggi, L., Ceccarelli, S., Negri, V. and Carboni, A. 2019. In-depth characterisation of common
bean diversity discloses its breeding potential for sustainable agriculture. Sustainability (Switzerland), 11(19), 1-20.
Chávez-Servia, J.L., Heredia-García, E., Mayek-Pérez, N., Aquino-Bolaños, E.N., Hernández-Delgado, S.,
Carrillo-Rodríguez, J.C., Gill-Langarica, H.R. and Vera-Guzmán, A.M. 2016. Diversity of Common Bean
(Phaseolus vulgaris L.) Landraces and the Nutritional Value of their Grains. Intech, (Grain Legumes), 135.
Jaramillo, C.M., Celeita, J.J. and Sáenz, A. 2013. Suceptibility of Delia platura to seven entomopathogenic
nematode isolates from the central andes region of Colombia. Universitas Scientiarum, 18 (2), 165-172.
Letourneau, D.K. 1994. Bean fly, management practices, and biological control in Malawian subsistence
agriculture. Agriculture, Ecosystems and Environment, 50 (2), 103-111.
Liu, W. 2012. Compatibility of essential oils with the biocontrol fungus, Beauveria Bassiana. Master's Thesis,
University of Tennessee, https://trace.tennessee.edu/utk_gradthes/1418.
Malee Thungrabeab. 2015. Research and development of myco - insecticide and repellent for controlling bean
fly, Ophiomyia phaseoli Tryon (Agromyzidae: Diptera), 62-66 In Proceeding of Research of Royal ProjectFoundation and Highland Research and Development Institute (Public Organization), 3 September, 2015.
Chaing Mai, Thailand.
Mantzoukas, S. and Eliopoulos, P.A. 2020. Endophytic entomopathogenic fungi: A valuable biological control
tool against plant pests. Applied Sciences (Switzerland), 10 (1), 1-13.
McGuinness, H. 2003. Aromatherapy therpy basic. 2nd ed., Hodder & Stoughton, London, UK
Neves, P.M.O. J., Hirose, E., Tchujo, P.T. and Moino, A. 2001. Compatibility of entomopathogenic fungi withneonicotinoid insecticides. Neotropical Entomology, 30 (2), 263-268.
Ojwang, P.P.O., Melis, R., Songa, J.M. and Githiri, M. 2010. Genotypic response of common bean to natural
field populations of bean fly (Ophiomyia phaseoli) under diverse environmental conditions. Field Crops
Research, 117 (1), 139-145.
Showler, A.T. 2017. Botanically based repellent and insecticidal effects against horn flies and stable flies(Diptera: Muscidae). Journal of Integrated Pest Management, 8 (1), 15.
Ssekandi, W., Mulumba, J.W., Colangelo, P., Nankya, R., Fadda, C., Karungi, J., Otim, M. De Santis P. andJarvis, D.I. 2016. The use of common bean (Phaseolus vulgaris) traditional varieties and their mixtureswith commercial varieties to manage bean fly (Ophiomyia spp.) infestations in Uganda. Journal of Pest
Science, 89 (1), 45-57.

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Research article
erd

Agronomic and Yield Performances of Three Rice Cultivars(Oryza sativa L.) under Water Regimes in Dry Season
SAVOEURN LANG*
Faculty of Agronomy, Royal University of Agriculture, Phnom Penh, Cambodia
Email: savoeurnlang@gmail.com

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

SIRANET ROEURN
Faculty of Agronomy, Royal University of Agriculture, Phnom Penh, Cambodia

LYHOUR HIN
Faculty of Agricultural Engineering, Royal University of Agriculture, Phnom Penh, Cambodia
Received 31 December 2019

Accepted 12 Otober 2020(*Corresponding Author)

Abstract Rice (Oryza sativa. L) is widely cultivated in Cambodia, but it consumes
considerably more water than any other crops. In the context of water scarcity due to global
climate change, rice cultivation in Cambodia has been worsened by the effect of drought.
Development of a cultivation technique to minimize yield loss under drought stress or/and
limited water resource in rice production is of great strategic value. Therefore, the present
study aims to investigate growth and yield performances of three rice genotypes, namely
CAR 14, CAR 15 and CAR 16 under different water regimes including drought (at flowering
stage), alternative wet and dry (AWD), and flooded conditions. The experiment was
conducted from January to October 2019, at the Tonle Bati Agricultural Development Center,located in Bati District, Takeo Province, Cambodia. The soil is clay loam and is classified as
Toul Samrong (Soil Classification for Rice Production in Cambodia). Two-way ANOVA was
utilized to determine interaction between the genotypes and the water regimes. As a result,the genotype-water regime interaction was detected for grain yield. Water regimes affectedgrain filling percentage and yield, whereas rice genotypes affected plant height, 50%
flowering days, 100% flowering days, number of unfertile grains, grain yield, and 1000 grain
weight. Nevertheless, plant density, panicle length, and straw biomass were not affected byeither of the factors. In any water regimes, CAR16 grew the tallest at 94.4 cm and blossomed
2 to 4 days later than any other cultivars. In contrast, CAR 15 had the highest yield, observedin permanent flooding and in AWD. Although 27% of irrigation water was saved in AWD,
permanent flooding produced more yield. In short, drought conditions affected total yield.
Despite that, Car 15 was observed to be more suitable for any water regimes.
Keywords Rice cultivars, AWD, drought, rice yield, straw biomass

INTRODUCTION
Rice belongs to the genus Oryza sativa L. and is known as a remarkable semi-aquatic plant which
has been cultivated in tropical and subtropical regions for about 10,000 years (IRRI, 2013; Sivapalan,2015). Maintaining proper water level in paddy fields is critical for rice production, but rice plants
will die or suffer yield loss when the water is too deep (Eckardt, 2017). International Rice ResearchInstitute (2013) reported that rice alone provides food for nearly half of the world population that has
increased remarkably. Irrigated rice accounts for 55% of the world’s harvested rice area and increases
by 25% in the next 20 years. Inadequate irrigation causes agronomic problems for intensive ricecultivation (Sivapalan, 2015). It is reported that drought adversely affects rice production by limiting
growth and reducing yield by 25.4%, posing a serious threat to global food security (Zhang et al.,Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

2018). The problem is even exacerbated when the demand for clean water is not fulfilled because
competition between irrigation and household use has formed.
In Cambodia, rice is grown in both wet and dry seasons depending on availability of water
sources. However, prolonged drought has been considered one of the main affecting factors that limit
annual rice planting areas. In 2015, severe drought occurred in the country, resulting in dire water
shortages and affecting several million people, while in 2012, thousands of hectares of rice fields
were destroyed (Climate Change Adaptation, 2019). In response, new rice varieties are studied andbred in hopes of producing drought tolerability. As a result, several varieties such as CAR 14, CAR
15 and CAR 16 have been released, but they are not yet widely available. Besides that, recognizing
their effectiveness is still unclear (CARDI, 2019). To address these issues, a proper irrigation
technique is required to maintain the yield although drought-tolerant rice varieties are used. A
promising solution to rice cultivation with water scarcity is alternative wetting and drying (AWD)
designed to irrigate paddy fields when needed, to save water. Large numbers of research results showthat AMD significantly reduced water use while maintaining yield (Howell et al., 2015). Therefore,
testing different irrigation methods may be beneficial for sustainable rice production within the
country.
OBJECTIVE
The research aims to investigate growth and yield performances of the three rice genotypes under
different water regimes classified as drought (at flowering stage), alternative wetting and drying
irrigation (AWD), and flooded conditions, known as flooding in three rice varieties: CAR 14, CAR
15 and CAR 16.
METHODOLOGY
The experiment was conducted at the Tonle Bati Agricultural Development Center, located in Bati District,
Takeo Province, Cambodia, starting from January to October 2019. Three rice cultivars were planted onclay loam, classified as Toul Samroang based on the Cambodian soil classification for rice production.
Those cultivars were CAR 14, CAR 15, and CAR 16, and they were planted under three different water
regimes designed for drought conditions at flower stage, alternative wetting and drying irrigation (AWD),
and flooded conditions, known as flooding. The experimental plots were neatly prepared, bunded, andlined in polythene plastic at the depth of 30 cm. Rice seeds were broadcasted at rates of 125 kg ha-1, withurea and DAP fertilizer applied at rates of 50 kg ha-1 each after land preparation and at 100 kg ha-1 at thevegetable stage.
In drought conditions, the water level was maintained at 5.0 cm above the ground, but the plots werecompletely drained at the flowering stage. Draining activities were repeated in case of rain to ensure nowater was left in the field. In AWD, PVC tubes were placed in the plots at 40 cm underground and at 20
cm above the ground. The tubes were 40.0 cm in length and 15.0 cm in diameter, perforated with 0.5 cm
diameter holes spaced 2.0 cm apart and covered in cloth to prevent clogging. The water level in the AWD
plots was maintained at 5.0 cm above the ground and repetitive irrigation was needed when it decreased
5.0 cm below the ground. This practice was discontinued at the flowering stage. In flooding, the paddy
fields were kept submerged at 3.0 - 5.0 cm above the ground and then at 5.0 - 7.0 cm until the booting
stage. At milking stage, the plots were completely drained.
Three months after planting, the plant height was measured from 10 randomly selected plants withineach plot, while plant density was evaluated from 3 random locations within each plot using a 1.0-m-2
frame area. In addition, 50% and 100% flowering was evaluated by counting the number of days required
from planting to half-full and full blossom. In each plot, panicle length and the number of grains per
panicle were measured from 10 randomly selected plants and rice yield from 3 locations using a 4.0-m-2
square frame area. Manual threshing was done to collect grains for drying and weighing to calculate therice yield in all treatments. Then the straw biomass left was dried using an oven at 800C for 48 hours.
Grain weight was measured based on 1000-grain quantity (Tian et al., 2017). Firstly, grains were dried toreach 140C. Then 1000 grains from each plot samples were randomly taken and weighed. Afterwards,
grains were split into categories, full or imperfect, and then counted for comparison.
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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

Fig. 1 Experimental plots arranged in RCBD and placed under three water regimes
The experiment arranged for this study was a randomized complete block design comprising threerice cultivars grown in three different water regimes. This combination constituted 6 treatments replicatedthree times, generating 27 plots. Each plot was 4.0 m by 4.0 m and had spacing of 1.0 m. Two-way
ANOVA was performed to determine the interaction between the varieties and the water regime used.
Statistical differences were stated by using LSD-test with an error of 5%.

RESULTS AND DISCUSSION
Plant height and Plant density
No significant interactions between the varieties and the water regimes were observed for plant height(P=0.086). The water regimes (p=0.200) also had no effects on plant height, but there were significant
differences among the varieties (p<0.001). CAR 16 varieties had significantly higher stems, whencompared to CAR 14 and CAR 15, regardless of irrigation techniques. In contrast, CAR 14 had theshortest stems. In addition, the plant height was significantly greater in AWD than in flooding anddrought conditions. In Flooding, the plant height for CAR 14, CAR 15, and CAR 16 was 91.0, 90.6,
and 96.8 cm, respectively. In AWD, they were 93.5, 91.7, and 98.1 cm, respectively. In drought, theplant stems for different rice cultivars were the shortest, averaging less than 93.0 cm. In short, drought
affected rice growth, stunting the stems. Regarding plant density, there were no interactions between
the varieties and the water regimes. In addition, no significant differences were found among the two
factors. Regardless of the varieties and the irrigation technique used, the plant density ranged from61 to 73 plants m-2.
Flowering Stage
Days to flowering were counted in this experiment starting from the day of sowing until 50% and100% blossom. However, no signification interactions between the varieties and the water regimes
were observed. Different water regimes also had no significant effects on flowering days, but there
were significant differences among the varieties, which means that different rice cultivars started toblossom at different days. It was observed that CAR 14 started to flower faster, when compared toother varieties. In addition, CAR 16 produced flowers at the slowest pace. In all regimes, CAR 14began to flower 50% at day 64 after planting, followed by CAR 15 and CAR 16 that produced 50%Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

blossom at days 67 and 68. Full blossom was observed 2 days after 50% flowering. In short, drought
did not have effects on flowering dates, and but different varieties did.
Panicle Length
In the experiment, the panicle length of the different varieties was measured at harvest time. There
were no significant interactions between the varieties and the water regimes used. In addition, neitherof the two factors affected the panicle. These mean that the tested varieties had similar panicle length.
Regardless of the water regimes used, the panicle length was observed to lie within the range of 24.8
to 25.9 mm
Table 1 Comparison of vegetative and reproductive growth in three seed varieties plantedin three water regimes (Different alphabets mean statistical difference at 5% error)
Water Regime(WR)
Drought

AWD

Flooding

Seedvariety(SV)
Car 14Car 15Car 16Car 14Car 15Car 16Car 14Car 15Car 16SE
F-test probabilities
WRSV
WR x SV

Plant height
(cm)

Plant
density(plants/m2)

50%
flowering
days

100%
floweringdays

Paniclelength (cm)89.1 cd
92.3 b
92.9 a89.1 d91.7 bc
93.5 b
91.0 bcd
90.6 bcd
96.8 b
19.87

64.3
61.2
64.9
65.9
66.6
65.0
70.9
68.0
73.6
4.81

64.7 c67.0 b68.0 a65.0 c67.0 b68.0 a64.7 c67.3 ab68.0 aN/A

66.7 c69.0 b70.0 a68.0 c69.0 b70.0 a67.5 c70.0 ab70.3 a
N/A

24.8
25.3
24.9
25.9
25.6
25.8
24.9
24.9
25.0
2.1

0.200
<0.001***0.086300.054
0.61670.760400.721<0.001***
0.52150

0.831<0.001***
0.52450

0.113
0.990
0.965

*Significantly different p at 0.05; **significantly different p at 0.01; and ***significantly different p at 0.001

Table 2 Comparison of vegetative and reproductive growth in three seed varieties plantedin three water regimes (Different alphabets mean statistical difference at 5% error)
Water Regime(WR)
Drought

AWD

FloodingSE
F-test probabilities
WRSV
WR x SV

Seed
variety(SV)
Car 14Car 15Car 16Car 14Car 15Car 16Car 14Car 15Car 16

Yield(Ton/ha)1000-grain
weight (g)Strawbiomass(Ton/ha)Harvestindex (%)

Water used
(m3 ha-1)

2.47 e2.96 cde2.62 de3.12 bcde
4.00 a2.72 de3.45 abc
3.70 ab3.18 bcd
0.42

25.0 c28.4 ab29.8 a24.8 c27.9 b
28.9 ab25.6 c28.8 ab30.0 a
7.80

6.80
6.98
6.90
5.94
7.85
5.51
8.80
7.92
7.85
0.72

26.8
29.8
30.7
35.1
33.9
32.9
28.2
31.8
29.0
2.18

4,824

<0.001***<0.001***
0.021*

0.175<0.001***
0.980

0.066
0.527
0.517

0.093
0.730
0.807

*Significant different p at 0.05; **significant different p at 0.01; and ***significantly different p at 0.001Ⓒ ISERD

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4,968

6,768

N/A

Number of grain per panicle

IJERD – International Journal of Environmental and Rural Development (2020) 11-2

160
140
120
100
80
60
40
20
0
Car 14 Car 15 Car 16 Car 14 Car 15 Car 16 Car 14 Car 15 Car 16
Drought

AWD

Flooding

Water regimes

Fig. 2 Comparison of full and imperfect grains for each rice cultivars grownin different water regimes (mean ± SD; n = 30).
Weight in 1000 Rice Grains
After harvest, the grain was sun-dried until they arrived at 14% moisture. Then, 1000 grains wererepeatedly taken from the different varieties, weighed and compared. Statistically, no interactions
between the varieties and the water regimes were observed (p=0.980). Significant differences in
1000-grain weight were not detected among the water regimes (p=0.175). However, there weresignificant differences in the weight among the varieties (p<0.001). Regardless of the irrigation
conditions, 1000-grain weight was similar between CAR 15 and CAR 16 but was the lowest in CAR
14. On average, 1000 grains of CAR 15 and CAR 16 weighed 28 to 30 g, whereas the same amountof CAR 14 weighed only 25 g.
Number of Panicle Grains
Effects of drought were detected based on separation of full and imperfect grains. No interactions
between the varieties and the water regimes were observed for imperfect grains (p=0.377) and forfull grains (0.360). Significant differences in imperfect grains were found among the varieties used
(p<0.001), but not the water regimes (p=0.081). In contrast, full grains were significantly affected by
the water regimes (p=0.001), not by the varieties (p=0.222). Among the varieties planted, CAR 14
had greater numbers of full grains in AWD and drought, compared to other varieties. Likewise, CAR
16 was seen to have more full grains in flooding. Both of these varieties had few imperfect grams
than CAR 15 did. Regarding the total grain number, CAR 15 had the most and CAR 16 had the least,
while CAR 14 was in the middle.
Rice Yield, Straw Biomass, Harvest Index, and Water Use
Significant interactions between the varieties and the water regimes were observed in rice yield(p=0.021), and these two factors also affected the yield (p<0.001). It can be seen that the yield
harvested in the drought treatment was significantly lower than in other treatments, regardless of thevarieties used. Similar rice yield was obtained both in AWD and flooding treatments. In drought
condition, the yield for the three varieties was less than 3 tons ha-1. Drought reduced the yield was
reduced by 28 % for CAR 14, 20% for CAR 15, and 17% for CAR 16. The result was similar in thestudies by Zhang et al. (2018), which identified the effect of drought by 25.4%. Besides that, the rice
yield of CAR 14 and CAR 15 was lower in this study than in the report by CARDI (2018a & 2018b).
Straw biomass was also collected from all treatments for comparison and for calculating harvest
index. Significant interaction between the varieties and water regimes was not observed (p=0.517),
nor were there significant differences in straw biomass (p=0.066; p=0.527). It was found that drought
had no effects on biomass that varied from 5.5 to 8.8 tons ha-1 among all treatments. SignificantⒸ ISERD

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interaction between the varieties and water regimes were not detected for the harvest index (p=0.093).
There were also no significant differences among the two factors (p=0.730; p=0.807). In alltreatments, the harvest index averaged 31%. Regarding the water use, it can be seen that the flooding
treatment consumed considerably more water than other treatments, while the amount of water usedin the drought condition and AWD was quite similar. In this research, the amount of water consumed
was 4,824 for drought, 4,968 for AWD and 6,768 m3 ha-1 for flooding. When compared, flooding
consumed 26.6% more water than AWD, but the rice yield between these treatments was not muchdifferent. Likewise, CGIAR (2014) also mentioned in a report and Kumar and Rajitha (2019) in theirstudies that using AWD could save water up to 25%.
CONCLUSION
In this research, three different rice cultivars CAR 14, CAR 15, and CAR 16 were planted in threedifferent water regimes, namely drought, AWD, and flooding, to find out their effects on rice growthand yield, as well as aiming to select the most suitable varieties. In the results, CAR 16 produced thegreatest plant length among the experimented cultivars, but began to flower a bit late, when comparedto other varieties. However, they had similar panicle length. CAR 15 and CAR 16 produced higher
yield, regardless of the water regimes although the straw biomass and harvest index among thetreatment were not different. In conclusion, drought conditions tend to affect total rice yield, while
flooding and AWD were more favorable for rice plants. For drought tolerance, CAR 15 and 16 should
be selected for cultivation. For flooded conditions, all of the varieties were suitable and for AWD,CAR 14 and CAR 15 were better.
REFERENCESCARDI. 2018a. Early-duration rice variety CAR 14. Cambodian Agricultural Research and Development
Institute, Phnom Penh.
CARDI. 2018b. Early-duration rice variety CAR 15. Cambodian Agricultural Research and Development
Institute, Phnom Penh.
CARDI. 2019. Rice service. Cambodian Agricutural Research and Development Institute, http://www.
cardi.org.kh/?page=productlist&pcateid=5&menu1=10&ctype=article&id=10&lg=en&paginate=2.
CGIAR. 2014. New irrigation technique can ease drought effects for rice farmers. Consultative Group forInternational Agricultural Research, https://ccafs.cgiar.org/fr/blog/new-irrigation-technique-can-easedrought-effects-rice-farmers#.Xe-Dx5Mza00.
Climate Change Adaptation. 2019. Cambodia, looking to the horizon, prepares for drought. United Nation
Development Program, https://www.adaptation-undp.org/cambodia-looking-horizon-prepares-drought.
Eckardt, N. 2017. How rice thrives in flooded fields. The plant cell. In a Nutshell, https://plantae.org/
research/how-rice-thrives-in-flooded-fields/.
Howell, K.R., Shrestha, P. and Dodd, I.C. 2015. Alternate wetting and drying irrigation maintained rice yields
despite half the irrigation volume, but is currently unlikely to be adopted by smallholder lowland rice
farmers in Nepal. Food Energy Secur, 4 (2), 144-157.
IRRI. 2013. Rice almanac, 4th Ed., International Rice Research Institute. Manila, Philippines, Global Rice
Science Partnership, http://books.irri.org/9789712203008_content.pdf.
Kumar, K.A. and Rajitha, G. 2019. Alternate wetting and drying (AWD) irrigation, A smart water saving
technology for rice, A review. International Journal of Current Microbiology and Applied Sciences, ISSN:
2319-7706 8 (03).
Sivapalan, S. 2015. Water balance of flooded rice in the tropics. In 98 Irrigation and Drainage - Sustainable
Strategies and Systems, 92-118. Frank Wise Institute of Tropical Agriculture, Department of Agriculture
and Food, Kununurra, Australia, IntechOpen, http://dx.doi.org/10.5772/59043.
Tian, Z., Li, J., He, X.,Jia, X., Yang, F. and Wang, Z. 2017. Grain yield, dry weight and phosphorus (Oryza
sativa L.), Varieties as affected by salt-alkali and phosphorus. Sustainability, (9), 1461. doi:10.3390/su
9081461.
Zhang, J., Zhang, S., Cheng, M., Jiang, H., Zhang, X., Peng, C., Lu, X., Zhang, M. and Jin, J. 2018. Effect ofdrought on agronomic traits of rice and wheat, A meta-analysis. Int. J. Environ. Res. Public Health, 15 (5),839. doi: 10.3390/ijerph15050839.

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Research article
erdApplicability of Tank Model in Mid-Sized Catchments inEastern Uganda
EMMANUEL OKIRIA
Graduate School of Agriculture, Tokyo University of Agriculture, Tokyo, Japan

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

YURI YAMAZAKI
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, JapanYUKIMITSU KOBAYASHI
Graduate School of Agriculture, Tokyo University of Agriculture, Tokyo, JapanSHINJI SUZUKI
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Received 27 January 2020

Accepted 29 October 2020(*Corresponding Author)

Abstract Long-term stream discharge data is indispensable in irrigation and drainage design.
However, in Uganda, this data is poor and insufficient, limiting irrigation system design.
Conversely, the rainfall monitoring network is denser than the river flow monitoring network.
Therefore, we attempt to build a model that calculates river discharge from input of rainfall.
In this study, the lumped parameter Tank Model was applied. The model was applied to the
Namatala River catchment (155 km2) in Eastern Uganda. The study sought to ascertain theapplicability of a lumped parameter model to a mid-sized catchment. Specifically, theobjectives were: 1) To calibrate the numerical values of Tank Model parameters, 2) To verify
the Tank Model parameters. This Tank Model required daily rainfall, evapotranspiration andriver discharge data during calibration. Data for years 2015 and 2016 was used for calibrationand validation respectively. During calibration, Monte Carlo simulation was used to find thenumerical values of 16 Tank Model parameters. The best performing calibration parameterset had Nash-Sutcliffe (NS) efficiencies of 0.608 and 0.257 in calibration and validation
respectively. However, among the 2015 calibration parameter sets, the one with a calibration
NS of 0.502 performed best in validation (NS = 0.526). Equifinality was observed during
parameter calibration. By using Tank Model, simulated discharge was divided into its surface
runoff, interflow and base flow components. Tank Model was adaptable to Namatala River
catchment.
Keywords Equifinality, lumped model, Monte Carlo simulation, parameter, Tank Model

INTRODUCTION
To buttress the vulnerable agricultural systems in Uganda, the government plans to promote
irrigation (MWE, 2013). Irrigation and drainage planning requires long-term observed hydrometeorological data. However, Uganda has a scarcity of this data. Numerous Ugandan rivers areungauged, and worse, only about 33% of installed water level gauging stations are operational (MWE,2013). Comparatively, the state of rainfall monitoring is better than that of the hydrologicalmonitoring. Further, Kobayashi et al. (2018) explored the accuracy of satellite rainfall observations
and found their detection accuracy to be acceptable. Satellite observed rainfall data is therefore apromising source of rainfall data.

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Since rainfall data is more readily available, it is attempted to build a hydrological model tocalculate river discharge from inputs of rainfall. Tank Model (Sugawara, 1995) and TOPMODEL(Beven and Kirkby, 1979), are some of the successful hydrological models. Okiria et al. (2019)
applied the semi-distributed TOPMODEL to the Atari River catchment in Eastern Uganda. In thisstudy, an attempt will be made to represent the hydrological response of the Namatala River
catchment (NRc) using Tank Model. Whereas TOPMODEL is semi-distributed, and has fewer
parameters, it is comparatively complex, and separates the predicted hydrograph into only two
components, i.e., surface runoff and subsurface flow. On the other hand, Tank Model is simpler andseparates the predicted hydrograph into four components, i.e., surface runoff, inter flow, sub-baseflow and base flow. A weakness of Tank Model is that it is a lumped parameter model, with many
unknown parameters (16 parameters for a 4-tank Tank Model). Because it is lumped, it cannot
represent the heterogeneity in catchment characteristics. And due to the many unknown parameters,a more pronounced equifinality is expected. This equifinality might be caused by the interdependence
among parameters reported in Beven (1997).
Whereas Tank Model has been successful in the continuously wet soils in humid sub-tropicalclimates (Suryoputro et al., 2017; Xiong et al., 2009), its behaviour in tropical climates, with soils
that undergo both wet and dry periods, is not widely documented. Onyutha (2016) applied Tank
Model to the Blue Nile Basin in Ethiopia. In East Africa, Tank Model was applied to a catchment in
Rwanda (JICA, 2014). To date, the authors have not found published evidence of the application of
Tank Model in Uganda. Therefore, the novelty of this study is to pioneer the development of Tank
Model for a catchment in Eastern Uganda.
Before hydrological models are applied to ungauged catchments, they require calibration andvalidation. Model calibration involves the determination of unknown parameters and their predictive
performance. On the other hand, validation involves testing the predictive performance of thecalibrated parameters in a period other than that of calibration. Being one of the well gauged
catchments in Uganda, the NRc was chosen for the calibration of Tank Model.
The lumped parameter model assumption of a catchment scale homogeneous hydrologicalresponse is likely to fail for medium to large catchments. Therefore, the purpose of the study is toascertain the applicability of a lumped parameter model (Tank Model) to mid-sized catchments inEastern Uganda. The specific objectives are: 1) Calibration of Tank Model parameters; and 2)
Validation of the model parameters. In so doing, we strive to build a Tank Model that successfully
predicts daily stream discharge from inputs of daily rainfall and evapotranspiration.
METHODOLOGY

Study Area
The study area is the Namatala River catchment (NRc), a headwater catchment of Mt. Elgon in
Eastern Uganda, with a drainage area of 155 km2 at the stream gauging station. Its topography iscomprised of mountainous areas from where the Namatala River originates and flows to the relatively
flat plains. From ASTER GDEM, the difference in height between the lowest and the highest point
is 1,262 m. Of the 155 km2, 73% is agriculture, 24% is forest, 2% is built up areas and 1% is rangeland.
Under the Project on Irrigation Scheme Development in Central and Eastern Uganda (PISD)(JICA, 2017), hydro-meteorological monitoring equipment were set up in the NRc, viz., a mid-stream
rain-gauge to detect catchment rainfall, a downstream meteorological station to measureevapotranspiration parameters and a water level logger at a control section of the Namatala River.
Tank Model Concept
One version of Tank Model comprises of four tanks laid out vertically in series, so named tanks 1, 2,
3 and 4. Rainfall is added to the topmost tank while evapotranspiration is subtracted from it. If tank
1 is empty, evapotranspiration is deducted from tank 2. If both tanks 1 and 2 are empty, thenevapotranspiration is subtracted from tank 3 and so on. The storage tanks have side outlets, fromⒸ ISERD

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which runoff flows. Side outlets of tanks 1,2,3 and 4 release surface runoff, interflow, sub-base flow
and base flow respectively. Tanks 1,2 and 3 have bottom outlets as well, through which infiltration
to a lower tank occurs. Tank Model is calibrated to determine the value of 16 unknown parameters,
namely; A1 (coefficient of top side out let of tank 1), A2 (coefficient of lower side outlet of tank 1),
B1 (coefficient of side outlet of tank 2), C1 (coefficient of side outlet of tank 3), D1 (coefficient ofside outlet of tank 4), A0 (coefficient of bottom outlet of tank 1), B0 (coefficient of bottom outlet oftank 2), C0 (coefficient of bottom outlet of tank 3), AH1 (height of top side outlet of tank 1), AH2(height of lower side outlet of tank 1), BH (height of side outlet of tank 2), CH (height of side outletof tank 3), SA0 (initial height of water in tank 1), SB0 (initial height of water in tank 2), SC0 (initialheight of water in tank 3) and SD0 (initial height of water in tank 4), as in Fig. 2. The simulated riverdischarge is the sum of runoff from all the side outlets. Details of Tank Model are in Sugawara (1995).

ARc

SRc
NRc
Fig. 1 Location of Namatala River catchment(NRc) relative to Atari River catchment(ARc) and Sironko River catchment (SRc)

Fig. 2 Schematic of Tank Model

Computational Procedure of Tank Model
Evaluation of tank 1:
𝑆𝐴𝑡 = 𝑆𝑍𝐴𝑡 + 𝑅𝑡 − 𝐸𝑇0𝑡

(1)
SAt is water depth in the tank during calculation (mm), SZAt is water depth in the tank at the start andend of each time step calculation (mm), R is observed rainfall (mm/day), ET0t is potential
evapotranspiration (mm/day), and the subscript t is the time step of calculation (day).
𝐴 × (𝑆𝑍𝐴 − 𝐴𝐻𝑥 )𝑄𝐴𝑥𝑡 = { 𝑥0 𝑓𝑜𝑟 𝑆𝑍𝐴 < 𝐴𝐻𝑥(2)

QAxt is runoff from side outlet (mm/day), Ax is discharge co-efficient of side outlet, AHx is height ofside outlet (mm), and subscript x is side outlet under consideration (1 or 2).
𝑄𝐴0𝑡 = 𝐴0 × 𝑆𝐴𝑡(3)
QA0t is infiltration from tank 1 to tank 2 (mm/day), A0 is discharge co-efficient of tank 1 bottom
outlet.
𝑆𝑍𝐴𝑡 = 𝑆𝐴𝑡 − 𝑄𝐴1𝑡 − 𝑄𝐴2𝑡 − 𝑄𝐴0𝑡

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Evaluation of tank 2:
𝑆𝑍𝐵0 + 𝑄𝐴0𝑡 − 𝐸𝑇0𝑡 for day 1, and an empty tank 1
𝑆𝐵0 = {𝑆𝑍𝐵0 + 𝑄𝐴0𝑡 for day 1 and non − empty tank 1(5)

SB0 is water depth in the tank during calculation (mm), SZB0 is water depth in the tank at the startand end of each time step calculation (mm).
𝑆𝐵𝑡 = {𝑆𝑍𝐵𝑡 + 𝑄𝐴0𝑡 − 𝐸𝑇0𝑡 after day 1, and an empty tank 1
𝑆𝑍𝐵𝑡 + 𝑄𝐴0𝑡 after day 1 and non − empty tank 1(6)

SBt is water depth in tank during calculation (mm), SZBt is water depth in the tank at the start andend of calculation (mm).
𝐵 × (𝑆𝐵𝑡 − 𝐵𝐻)
𝑄𝐵1𝑡 = { 10 for 𝑆𝐵𝑡 < 𝐵𝐻

(7)

QB1t is runoff from tank 2 side outlet (mm/day), B1 is discharge co-efficient of tank 2 side outlet,
BH is height of tank 2 side outlet (mm).
𝑄𝐵0𝑡 = 𝐵0 × 𝑆𝐵𝑡(8)
QB0t is infiltration (mm/day) from tank 2 to tank 3, B0 is discharge coefficient of tank 2 bottom
outlet.
𝑆𝑍𝐵𝑡 = 𝑆𝐵𝑡 − 𝑄𝐵1𝑡 − 𝑄𝐵0𝑡

(9)The calculations for tanks 3 and 4 follow the same logic as the calculations for tank 2. Also, these
conditions must be met: 𝐴0 > 𝐵0 > 𝐶0 and 0 > 𝐶 > 1 where C is discharge coefficient.
Evaluation of Parameter Predictive PowerNash and Sutcliffe efficiency (NS), (Nash and Sutcliffe, 1970) and Root Mean Square
Error (RMSE) are the indices for evaluating model efficiency as in Okiria et al. (2019).
Novel Concept for Managing Competing Parameter Sets
Calibration of model parameters is an uncertain process with uncertainty increasing with increasing
number of unknown parameters. The Generalised Likelihood Uncertainty Estimation (GLUE)
framework was developed to eliminate competing parameter sets (Beven, 1997). To augment thisconcept, the authors suggested another method to manage uncertainty, i.e.: 1) Use the competingparameter sets to simulate the hydrograph for a period outside the calibration period (verification ofcompeting parameter sets). The parameters that perform poorly in validation are then rejected; 2)Plot hydrograph components predicted using non-rejected parameter sets and choose the most likelyhydrograph based on the depiction of the shape of the base flow component, which is supposed to be
fairly constant. The authors attempted to use 1) and 2) in combination, to eliminate competingparameter sets.
Data Requirement
The input data for Tank Model is rainfall (R), river discharge (Q) and evapotranspiration (ET0).
Table 1 Tank Model input data
Purpose

PeriodR (mm)ET0 (mm)

Q (mm)

Calibration

2015-Feb-27 to Oct-22 (238 days)

1,376

866

517

Validation

2016-Apr-27 to Dec-31(249 days)

1,004

921

467

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RESULTS AND DISCUSSION
Like findings by Beven (1997), competing parameter sets were observed, making it impossible toidentify with certainty the optimum parameter set for Tank Model.
Table 2 shows two parameter sets from the calibration in 2015 as well as their calibration andvalidation performances. During calibration, the best performing parameter set had an NS value of0.608. However, during validation, its predictive power reduced to an NS of 0.257. On the other hand,the parameter set with the calibration NS of 0.502 had the best performance during validation, witha validation NS of 0.526. The difference between calibration and validation NS values could be
evidence that parameter sets are dependent on rainfall characteristics as reported in Okiria et al.
(2019). It can also be attributed to the obscurity in setting the initial condition during validation.
Figure 3 shows the best performing Tank Model parameters. Based on the new method to manage
uncertainty, the parameter set with calibration and validation NS of 0.608 and 0.257 respectively ispreferred since it has a very good calibration NS and a sufficient validation NS, and it also yields a
reasonable base flow curve – the classification of NS as good or sufficient is in Foglia et al. (2009).
Fig. 4 shows the observed and simulated hydrographs for 2015 during calibration while Fig.6
shows the observed and simulated hydrographs for 2016 during validation of 2015 parameters. In
2015, the trend of the simulated hydrograph was quite similar to that of the observed hydrograph.
However, in 2016, the trends between observed and simulated hydrographs were less similar. The
dissimilarity in 2016 could be attributed to input data error or in an ability of the model to accurately
represent the rainfall-runoff response of 2016. In both years, majority of the peak discharges were
underestimated. This could be attributed to under estimation of catchment rainfall and or the overestimation of evapotranspiration.
In Fig. 5 the components of the simulated hydrograph for 2015 during calibration are shown
while Fig.7 shows the components of the simulated hydrograph for 2016 during validation by 2015
calibration parameters. The simulated discharge was separated into its surface runoff, inter flow, subsurface flow and base flow components. Surface runoff was dominant during the rainy period whilebase flow was the dominant component in the dry period. In addition, base flow was generally stable
and showed delayed response to rainfall.

Fig. 3 Best performing parameters for Namatala River
catchment (NRc) calibrated in 2015

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B1

B0

.040

0.011

0.004

0.005

Fig. 5 Hydrograph components for 2015 during calibration

A0

1.108

A2

1.387

RMSEv

st parameter set from calibration in 2015 and their validation performance in 2016

Fig. 7 2016 Hydrograph components during validation by 2015

IJERD – International Journal of Environmental and Rural Development (2020) 11-2

C0

D1

SAinitial

SBinitial

SCinitial

SDinitial

AH1

AH2

BH

CH

NSc

RMSEc

NSv

0.026

0.001

0.013

31

690

759

78

98

89

664

952

0.608

1.141

0.257

C1

0.008 0.010 0.002 0.006 0.069 0.004 0.005
124
100
528
51
63
7
55
502 0.502
1.285
0.526
Note: NSc and RMSEc are NS and RMSE values respectively during calibration, and NS v and RMSEv are NS and RMSE values respectively during validation

0.257
1.141
0.608
952

NSv
NSc
CH

RMSEc

.008 0.010 0.002 0.006 0.069 0.004 0.005
124
100
528
51
63
7
55
502 0.502
1.285
0.526
e: NSc and RMSEc are NS and RMSE values respectively during calibration, and NS v and RMSEv are NS and RMSE values respectively during validation

Fig. 5 Hydrograph components for 2015 during calib

IJERD – International Journal of Environmental and Rural Development (2020) 11-2



664
89
98

BH
AH2
AH1

Table 2 Best parameter set from calibration in 2015 and their validation performance in 2016

IJERD – International Journal of Environmental and Rural Development (2020) 11-2

served and simulated hydrograph for best parameter of 2015

A2

0.041

0.040

0.011

B1

B0

C1

C0

0.004

0.005

0.026

0.001

D1

SAinitial

SBinitial

SCinitial

0.013

31

690

759

SDinitial

AH1

AH2

BH

CH

NSc

RM

78

98

89

664

952

0.608

1

Ⓒ ISERD

0.040
0.041

0.028

A2

Note: Qobs is observed discharge, Qsim is simulated discharge

36

36

36

Fig. 5 Hydrograph components forFig. 7 2016 Hydrograph components duⒸ ISERD

0.011

A0

Fig. 6 2016 Observed and simulated hydrograph using 2015 parametersNote: Qobs is observed discharge, Qsim is simulated discharge

0.001
0.026
0.005
0.004

36

Fig. 6 2016 Observed and simulated hydrograph using 2015 parameters

31
0.013

690

SAinitial
D1
B0
B1

C1

C0

Fig. 4 Observed and simulated hydrograph for best parameter of 2015

A1

RD

SBinitial

ote: Qobs is observed discharge, Qsim is simulated discharge

Fig. 4 Observed and simulated hydrograph for best parameter of 2015

759

0.008 0.010 0.002 0.006 0.069 0.004 0.005
124
100
528
51
63
7
55
502 0.502
1valuesrespectively
during calibration,
NS v Hydrographand RMSEv are NS
and RMSE values
respectively
duringbv
c and RMSE
c are NS and RMSE
Fig. 7and2016
components
duringvalidation
016 ObservedNote:and NS
simulatedhydrograph
using
2015
parameters
SCinitial

0.028

A0

78

A1

SDinitial

Table 2 Best parameter set from calibration in 2015 and their validation performance in 2016

IJERD – International Journal of Environmental and Rural Development (2020) 11-2

CONCLUSION
Tank Model was successfully applied to the Namatala River catchment to simulate its rainfall-runoff
process. However, due to equifinality, the model should be applied with caution. In addition, more
research needs to be done to better understand the shortcomings of the model. Acquisition of finer
spatial resolution input data is recommended. Studies on other catchments in Eastern Uganda could
be useful in confirming the applicability of lumped parameter models.
ACKNOWLEDGEMENTS
The study was done during graduate studies at Tokyo University of Agriculture, Tokyo, Japan,
courtesy of scholarship from Japan International Co-operation Agency (JICA), Japan. It goes without
thanking NTC-International Co., Ltd for the opportunity to advance my career.
REFERENCES
Beven, K. 1997. TOPMODEL: A critique. Hydrol. Process, 11, 1069-1085.
Beven, K.J. and Kirkby, M.J. 1979. A physically based, variable contributing area model of basin hydrology.
Hydrological Sciences Bulletin, 24 (1), 43-69.
Foglia, L., Hill, M.C., Mehl, S.W. and Burlando, P. 2009. Sensitivity analysis, calibration, and testing of a
distributed hydrological model using error-based weighting and one objective function. Water Resources
Research, 45 (6).
Japan International Cooperation Agency (JICA). 2014. The preparatory survey report on land-husbandry,water-harvesting and hillside-irrigation project in the Republic of Rwanda.
Japan International Cooperation Agency (JICA). 2017. The project on irrigation scheme development in central
and Eastern Uganda, Final Report, 1, Main Report.
Kobayashi, Y., Watanabe, F., Suzuki, S., Okiria, E. and Kanyike, T. 2018. Verification of availability of
GSMaP rainfall data based on the comparison of observed rainfall data in Africa. Journal of Arid Land
Studies, 28 (S), 85-88.
Ministry of Water and Environment (MWE). 2013. Uganda national water resources assessment, Kampala:
Directorate of water resources management. Ministry of Water and Environment, Uganda.
Nash, J.E. and Sutcliffe, J.V. 1970. River flow forecasting through conceptual models part I, A discussion ofprinciples. Journal of Hydrology, 10 (3), 282-290.
Okiria, E., Okazawa, H., Kobayashi, Y., Yamazaki. Y. and Suzuki, S. 2019. Identifying the minimum numberof observed rainfall events required for optimal TOPMODEL parameters in mid-sized equatorial
catchments. International Journal of Environmental and Rural Development, 10 (2), 113-119.
Onyutha, C. 2016. Influence of hydrological model selection on simulation of moderate and extreme flow
events, A case study of the Blue Nile Basin. Advances in Meteorology, 2016.
Sugawara, M. 1995. Tank model. In Singh, V.P. (Ed.) Computer models of watershed hydrology, U.S.A, Water
Resources Publications, 165-214.
Suryoputro, N., Suhardjono, Soetopo, W. and Suhartanto, E. 2017. Calibration of infiltration parameters onhydrological tank model using runoff coefficient of rational method. AIP Conference Proceedings, 1887
(September).
Xiong, J., Ohnish, Y., Takahashi, K. and Koyama, T. 2009. Parameter determination of multi-tank model withdynamically dimensioned search. Proc Symp Rock Mech Jpn, 38, 19-24.

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

Research article
erd

Effect of Excavated Small Drainage Channels on
Desalinization in Northeastern Thailand
NAHO NOHARA
Hokkaido University, Sapporo, JapanTADAO YAMAMOTO*
Hokkaido University, Sapporo, Japan
Email: tady@env.agr.hokudai.ac.jp

TAKASHI KUME
Ehime University, Matsuyama, JapanKATSUYUKI SHIMIZU
Tottori University, Tottori, JapanCHULEEMAS BOONTHAI IWAI
Khon Kaen University, Khon Kaen, Thailand
Received 27 January 2020

Accepted 29 October 2020(*Corresponding Author)

Abstract Salt-affected soil is a serious problem in Thailand, and most of this soil is found in
the northeastern part of Thailand. The total area of saline land in Northeast Thailand is 2.85
million ha, which accounts for about 17% of this area (Land Development Department,2011).
The objective of this study is to evaluate the effect of desalinization by digging drainage
channels in salt-affected fields during rainfall. The study was conducted on a high salinity
field in Khon Kaen, Thailand. In April 2019, the main drainage channel of a depth of 1 m,
was excavated across the center of the field in the south-to-north direction. Additionally, side
ditches were installed along the circumference of the west part of the field. We constructeddrainage channels to promote field drainage and effectively induce salt leaching with rainfall.
Field observations were conducted eight times, especially in the rainy season, from August
2018 to September 2019. Soil apparent electricity conductivity (ECa) was measured using anelectromagnetic induction meter in three distinct depth ranges, i.e., 0.375 m, 0.75 m, and 1.5m, from the soil surface. Soil salinity was represented as contour maps based on spatiallyinterpolated data and spatial distribution and temporal changes were analyzed. The soil ECa
in the field gradually increased from upstream to downstream. Moreover, it was higher near
the surface and lower deep underground. By comparing the soil salinity observed in the laterpart of the rainy season in both the years, ECa was observed to have decreased by 20% from
August 2018 to September 2019. The ECa values at depths of 0.375 m and 0.75 m in the west
part of the field, which had side ditches, were significantly lower than those in the east partof the field two months after the drainage channels were constructed. However, a contrary
result was obtained after a heavy flood. These results indicate that drainage channels
contribute to salt leaching with rainfall. Our results suggested that excavating drainage
channels could effectively reduce soil salinity during the rainy season under good drainage
conditions.
Keywords saline soil, desalinization, leaching, drainage, electric conductivity

INTRODUCTION
Soil salinization is a major global problem limiting crop productivity. Urgency exists to prevent andimprove soil salinization for sustainable agriculture. Salt-affected soils are found in more than 100Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

countries and typically occur in arid and semi-arid regions (Rengasamy, 2006). The Food andAgriculture Organization (FAO) estimated that globally the total area of salt-affected soils is 831
million ha. Salt-affected soils have also been developing in monsoon zones in South and Southeast
Asia. Thailand is one of the countries where improving saline soil is an urgent need.
Salt-affected soil is a serious problem in Thailand, and most of this soil is found in thenortheastern part of Thailand. The total area of saline land in Northeast Thailand is 2.85 million ha,which accounts for about 17% of this area (Land Development Department,2011). The potential
source of salt in this area is halite in the Maha Sarakham Formation (Wongsomsak, 1986). Apartfrom its geographical environment, human activities such as deforestation associated with
agricultural development and traditional salt making have contributed to accelerating soil salinization(Arunin et al., 2015; Löffler et al., 1988). People in this area are impoverished because of low
agricultural productivity resulting from infertile land and salt-affected soil. To combat this problem,the mechanism of reducing soil salinization was elucidated, and studies using various approaches tomitigate soil salinity have been attempted from more than 30 years (Miura et al., 1991;
Patcharapreecha et al., 1990). However, the people in this area are still suffering from salt-affectedsoil. In other words, these desalinization approaches do not have widespread application. Some
farmers abandoned their farmlands and gave up farming because with salt-affected soil being formed
opportunities to expand farmlands did not exist. To enhance agricultural development and encourage
the agricultural community, ameliorating salt-affected soil and develop them for farmlands are necessary.
One of the common strategies for combating salt-affected soil is leaching salts from upper tolower soil depths (Qadir et al., 2000). To effectively facilitate the leaching process, an open or
subsurface drainage system is commonly adopted (Ritzema, 2016). This approach is generally
considered to decrease the saline groundwater table and removes leaching water from the soil profile.
However, installing a drainage system to control salinity is a costly proposition (Datta et al., 2000)
and raises concerns about high salinity drainage water. In this study, a conceptual model of the
Cascading Salt Using System (CSUS) (Kume et al., 2019a, 2019b) has been considered. This model
focuses on water and salt flow and proposes to reconsider salt as a useful resource. In this system,
different types of crop cultivation are practiced considering feasible salinity levels. For instance, ricepaddies can be cultivated upstream and halophilic crops can be cultivated downstream where the salt
concentration is higher. Moreover, table salt can be made from high salinity discharge water that isobserved at the lowest downstream level. Production of halophilic crops and salt are expected to raise
farmers’ income.
This study is the first step of the CSUS project to decrease soil salinity in a large salt-affected
field by excavating small drainage channels. Open drainage channels that are currently installed in
the field considered in this study are not aimed towards completely removing salts from the field andmitigating soil salinity for low salt-affected levels. These drainage channels are not large; therefore,
they are inexpensive and easy to install for farmers. The objective of this study is to evaluate theeffect of desalinization by digging small drainage channels.
METHODOLOGY
Study Area
The study was conducted in a high saline soil field in Ban Phai district (16°03′ , 102°69′ E), Khon
Kaen (Fig. 1). This area experiences a tropical savanna climate (Köppen climate classification Aw)
with marked alternation of the rainy season (from May to October) and dry season (from ovember
to April). The range of annual precipitation is from 1,100 mm to 1,500 mm, and the mean annual
temperature is 27°C. The overview of the field under consideration in this study is shown in Fig. 2.
This field with an area of approximately 0.8 ha has no vegetation because of high soil salinity;
however, the upper area of the field is used for rice cultivation in the rainy season. For improving thesaline soil in the field, a strategy to install small drainage channels was adopted by the Land
Development Department. The drainage channels are expected to promote field drainage and induce
salt leaching with rainfall. In April 2019, a main drainage channel with a 1-m depth was excavatedⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

across the center of the field in the south-to-north direction. Additionally, side ditches with a depthof 1 m were installed along the circumference of the west part of the field. The gradient of thedrainage channels was approximately 2.5 / 1000. The water flow is in the direction of the arrow in
Fig. 2. The drainage ultimately runs downstream through the hume pipe under the road lying on thenorth side of the field. Daily precipitation data (Fig.3) in the urban area in Khon Kaen was obtained
from the Japan Meteorological Agency website.
Field Survey
Soil salinity was measured using an electromagnetic induction meter, EM38-MK2 (Geonics Limited),
which measured apparent soil electrical conductivity (ECa) in units of millisiemens per meter (mS/m).
This instrument has two receiver coils, each of which, are separated by 1 m and 0.5 m from thetransmitter providing data from effective depth ranges of 1.5 m and 0.75 m, respectively, when
positioned in the vertical dipole orientation, and 0.75 m and 0.375 m respectively, when positioned
in the horizontal dipole orientation. We measured soil salinity in vertical and horizontal dipole
orientation in 1-m intercoil spacing as well as in horizontal dipole orientation in 0.5-m intercoil
spacing, thereby obtaining three distinct depth ranges of data, i.e., 0.375 m, 0.75 m and 1.5 m, fromthe soil surface. The measurement interval was about 10 m. Field observations were conducted eighttimes, especially in the rainy season, from August 2018 to September 2019 and three times in the dry
season, i.e., February, March, and December 2019.

Fig. 1 Location of the study area

Fig. 2 Overview of the study area

Fig. 3 Daily precipitation in Khon KaenⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

Data Analysis
The soil ECa data obtained from EM38-MK2 in the field were used as a database for mapping the
distribution of the field soil salinity. They were interpolated using the Inverse Distance Weighted
method with 1-m intervals and represented as contour maps to analyze spatial and temporal
distributions. Because ECa measured using EM38-MK2 affects soil moisture, data under similar
groundwater level conditions were used for comparing soil salinity changes. The observation datesof the data used for this analysis are shown in Fig. 3 in blue (in the rainy season) and red (in the dry
season) dots. Moreover, averages of field ECa were calculated based on the interpolated data.
RESULTS AND DISCUSSION
Spatial Distribution and Temporal Changes of Soil Salinity in the Field
Soil salinity in the field was represented as contour maps. Fig. 4 shows field soil salinity at a depth
range of 0.75 m in August 2018 as well as September 2019 before and after excavating the drainage
channels. The soil ECa gradually increased from upstream to downstream in the field associated withwater flow. Identical results were obtained at the other measurement dates as well as the other two
depths, i.e., 0.375 m and 1.5 m. Comparison of both the figures showed that the soil ECa in September
2019 was lower than that in August 2018 in the entire field. Table 1 shows the average EC a in thefield at three different depth under similar groundwater level conditions in the rainy season. The soil
ECa has a tendency to be higher near the soil surface and lower deep underground. In the rainy season
in 2019, the soil ECa gradually decreased from the early part of the rainy season in May to the endof the rainy season September. The specific decrease was from 1398 mS/m to1290 mS/m, 1367 mS/m
to 1205 mS/m, and from 1106 mS/m to 944 mS/m at the depths of 0.375 m, 0.75 m, and 1.5 m,
respectively. The total rainfall in this period was 655.4 mm. Leaching is considered to haveprogressed during rainfall.

Fig. 4 Distribution of soil salinity in the field at a depth of 0.75 m before the installation ofdrainage (left) and after the installation of drainage (right) in the rainy season
Moreover, the soil ECa decreased after excavated drainage channels. The soil ECa in September
2019 was 20% lower than that in August 2018, even though both these periods were the later part of
the rainy season. This result indicates that installing drainage channels promotes salt leaching by
rainfall in the rainy season.
Additionally, soil salinity was compared before and after excavating drainage channels in thedry season. Fig.5 shows field soil salinity at a depth range of 0.75 m in March 2019 as well as
December 2019 before and after excavating the drainage channels. The averages of the soil ECa in
the dry season are also shown in Table 1. After installing drainage, the soil ECa in December 2019
Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

was lower than that in March 2019, before installing drainage. Additionally, Fig. 5 clearly shows thatthe soil ECa decreases after excavating the drainage channels. Miura, K., and Subhasaram, T. (1991)
indicated that accumulation of salt on the soil surface in the dry season was associated with theelevation of the groundwater table to a critical level at the end of the rainy season and continuity ofcapillary pores above the groundwater level. In this study, comparing the soil ECa under similar
groundwater level conditions, this continuity of capillary pores should be prevented due to thegroundwater level after excavating the drainage channels was relatively lower than before that. This
result agrees with the earlier result in the rainy season and supports the assumption that drainage
channels effectively function as a desalinization method.
Table 1 Averages of field ECa (mS/m) at three depths
Depth (m)Rainy season
May 2019 June 2019
1398
1277

September 20191290

Dry season
March 2019
December 2019
1133
944

0.375

August 2018
-

0.75

1470

1367

1286

1205

1109

954

1.5

1155

1106

1077

944

947

840

Fig. 5 Distribution of soil salinity in the field at a depth of 0.75 m before installing drainage(left) and after installing drainage (right) in the dry season
Comparison of Salinity Changes under Different Drainage Intensity
In the field under consideration in this study, the intention of drainage channels is different between
the west and east parts of the field. The west part of the field is surrounded by a side ditch; therefore,drainage and leaching efficiency in the west part are expected to be better than those in the east partof the field. To compare the desalinization effect on both the sides, we compared the soil ECa in thewest part to that in the east part of the field. Fig. 6 shows the average soil ECa at a depth of 0.75 m
in the west and east parts of the field. The error bars show the standard deviation. The average of thesoil ECa before the introduction of drainage was higher in the west part of the field than that in theeast part of the field, i.e., 1498 mS/m and 1442 mS/m, respectively. However, the soil ECa was lower
in the west part than that in the east part of the field two months after the drainage installation, i.e.,
June 2019. The average field ECa was 1205 mS/m and 1340 mS/m in the west and the east part of
the field, respectively. Moreover, significant difference (Mann-Whitney U test; p <0.01) with thesame result was obtained at a depth of 0.375 m, while no significant difference between the west andthe east parts of the field was observed at a depth of 1.5 m. This result indicates that intensive drainage
enhanced salt leaching in the west part of the field. However, in September 2019, the soil ECa in thewest part was higher than in the east part of the field. Before measurement in September 2019, thisarea experienced heavy flooding, and some parts of the drainage system were broken; therefore,Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

excess water in the field could not be immediately removed. This may have caused higher salinity inthe west part of the field in September 2019. In December 2019 after the flood, the same tendency
was observed as that before the flood even though it was the dry season.

Fig. 6 Averages of the soil ECa in the west andthe east part of the field at a depth of
0.75 mFig. 7 Divided five areas depend on the
distance from drainage channels

Fig. 8 Changes of the average ECa in five areas in the rainy season
Subsequently, we compared the soil ECa near the drainage channels and far from them toconduct a detailed examination of the field salinity changes. The field was divided into five areas(Fig. 7) based on the distance from the drainage channels, i.e., the area 0-10 m from the main drainage
channel in the west part of the field (area A), the area 0-10 m from the side ditch in the west part of
the field (area B), the middle area of the west part of the field (area C), the area 0-10 m from the main
drainage channel in the east part of the filed (area D), and the area 10-25 m from the main drainage
channel in the east part of the field (area E). We compared the values of the soil ECa in the five areasat three depths during the rainy season under a similar groundwater level condition. Fig. 8 shows theaverage soil ECa in each of the five areas at depths of 0.375 m and 1.5 m as an example. The soil ECa
generally decreased in all the areas and at all the depths from August 2018 to June 2019. However,in September 2019, after the flood, the soil ECa suddenly increased in areas A and B at a depth of
0.375 m, while it slightly decreased in area C, which was surrounded by A and B,. This result
indicates that salt was supplied from the soil surface layer in C to the A and B areas. Alternatively,
this may suggest that salt reaccumulated from the drainage water after the flood. Conversely, at a
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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

depth of 1.5 m, the soil ECa in areas A, B, and D near the drainage channel, considerably decreasedin September 2019 in contrast with small changes before that. The drainage and leaching effect wasconsidered to be less at a depth of 1.5 m because the groundwater level was over 1.5 m in theordinarily rainy season, but the depth of the excavated drainage channels was 1.0 m. However, thegroundwater level in the field was low in July and August 2019 because low rainfall was experienceduring this period. Therefore, a large amount of rainfall caused by the flood infiltrated deep
underground in an instant and this made the salt leach away, especially from near the drainage
channel and deep underground. These results indicate that drainage channels contribute to saltleaching during rainfall and drainage systems operating in a satisfactory manner are important fordesalinization.
CONCLUSION
We evaluated the effect of small drainage channels during rainfall on desalinization in the highsalinity field in Khon Kaen, Thailand by measuring field soil ECa using an electromagnetic induction
meter. After analyzing the spatial distribution and temporal changes of the field soil salinity, we
found the following results. The soil ECa gradually increased in the field from upstream todownstream. The soil ECa was higher near the surface and lower deep underground. In 2019, the soil
ECa gradually decreased from the early part rainy season to the end of the rainy season. By comparing
the soil salinity before and after excavating the drainage channels in the same season, the soil ECa
was observed to have decreased after drainage installation. Moreover, the soil ECa in the west part of
the field, where drainage was more intensive, was significantly lower than that in the east part of the field
two months after the drainage channels were constructed. However, later in the rainy season in 2019,the value of the soil ECa in the west part of the field was higher than that in the east part of the field.
The drainage channels were considered to have not worked well after the heavy flood. The same
holds true of the result obtained by comparing the ECa changes based on the distance of the drainage
channels. Our results suggest that the excavated drainage channels can effectively reduce soil salinity
during the rainy season. Overall, the desalinization effect could be observed in the field soil ECa
throughout the year. Additionally, desalinization is assumed to continue to progress by repairing thedrainage channels.
It was estimated that heavy flood in September 2019 would be equivalent to once in 50 years
scale from local interviews. Due to such heavy flood, several collapses of the channel slope,
sedimentation in the channel, and damage to the Hume concrete pipe at the most downstream point
occurred. In order to restore the drainage function and leaching effect, it is necessary to repair themurgently.
ACKNOWLEDGEMENT
This work was supported by Grant-in-Aid for Scientific Research (KAKENHI; No.17H04630) (B)from the Japan Society for the Promotion of Science (JSPS) and The Mitsui & Co. Environment
Fund (Grant No. R17-0039).
REFERENCES
Arunin, S. and Pongwichian, P. 2015. Salt-affected soils and management in Thailand. Bull. Soc. Sea Water
Sci., Jpn., 69, 319-325.
Datta, K.K., De Jong, C. and Singh, P.O. 2000. Reclaiming salt-affected land through drainage in Haryana,
India, A financial analysis. Agric. Water Manage., 46, 55-71.
Kume, T., Iwai, B., C., Srihaban, P., Yamamoto, T., Shimizu, K., Matsuda, H. and Ubukata, F. 2019a. The
cascading salt using system for adaptive environmental governance to sustain rural areas in Khon Kaen
Province, Thailand. The Book of Abstracts 10th ICERD, 126.
Kume, T., Yamamoto, T. and Shimizu, K. 2019b. Research on adaptive environmental governance to convert
salts into resource material by the cascading salts using system in agricultural field. Proc. JSIDRE, 360361.
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Land Development Department. 2011. Reclamation of saline soil in the Northeast. https:// www.ldd.go.th/
web_eng56/Soil_Resource/Soil_reclamation_techniqes/Reclamation%20of%20saline%20soil%20in%20
the%20Northeast.htm. 1 Nov. 2020
Löffler, E. and Kubiniok, J. 1988. Soil salinization in North-East Thailand. Erdkunde, 42 (2), 89-100.
Miura, K. and Subhasaram, T. 1991. Soil salinity after deforestation and control by reforestation in Northeast
Thailand. Trop. Agric. Res. Ser, 186-196.
Patcharapreecha, P., Topark-Ngarm, B., Goto, I. and Kimura, M. 1990. Studies on saline soils in Khon Kaenregion, Northeast Thailand. III. Effects of amelioration treatment on physical and chemical properties ofthe saline soil. Soil Sci. Plant Nutr, 36 (3), 363-374.
Qadir, M., Ghafoor, A. and Murtaza, G., 2000. Amelioration strategies for saline soils: A review. Land Degrad.
Develop., 11, 501-521.
Rengasamy, P. 2006. World salinization with emphasis on Australia. Journal of Experimental Botany, 57 (5),1017-1023.
Retzema, P.H. 2016. Drain for gain: Managing salinity in irrigated lands- a review. Agric. Water Manage. 176,
18-28.
Wongsomsak, S. 1986. Salinization in Northeast Thailand. Southeast Asian studies, 24 (2), 133-153.

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Research article
erd

Farmer’s Perception of Ecosystem Services for Lowland
Rice Cropping Systems in Battambang Province,
Northwest of Cambodia
RAKSMEY PHOEURK*
Ecosystem Services and Land Use Research Center, Division Research and Extension,
Royal University of Agriculture, Phnom Penh, Cambodia
Email: praksmey@rua.edu.kh

KIMCHHIN SOK
Ecosystem Services and Land Use Research Center, Division Research and Extension,
Royal University of Agriculture, Phnom Penh, Cambodia

MALYNE NEANG
Ecosystem Services and Land Use Research Center, Division Research and Extension,
Royal University of Agriculture, Phnom Penh, Cambodia
Received 25 January 2020

Accepted 2 November 2020(*Corresponding Author)

Abstract Rice is significant in Cambodian food security. The main cultivated area is incentral plain and floodplain of Tonle Sap Lake (TSL). TSL provides importantly bothprovisioning and regulating services to rice cultivations in its floodplain such natural floodfor irrigation, soil fertility from sediment and aquatics animals specifically fish and snakes
which regulated and improve the rice cropping system naturally. However, changes of the
Mekong River (flood pulse) and climate change impact on changes of rice cropping systems(RCS) observed recently. The objective of the study aims at carrying out farmer’s perception
on ecosystem services (ES) in comparison with two sites of Low-water-land (LWL) andmiddle-water-land (MWL) in Sangkae district, Battambang province. An agrarian systemanalysis and diagnosis method applied for whole implementation with 120 rice farmers forthis survey. Flood-pulse of TSL have change to lower and lower which led some part offloodplain became infertility, so farmers have changed their traditional rice cropping systems(floating rice and long-term rice) to high-yield rice; shifted from traditional techniques tomodern systems by adopting new innovations, inputs and technology, chemical fertiliser andmodern machineries. Nevertheless, from our study, the new rice cropping systems seem tobe less sustainable, inadequate use of new technologies or inputs in the study areas. Rice
cropping systems in MWL is more profitable than LML site. Farmers in both sites are awareof the ecosystem services provided by TSL, but not all of them perceived the same importanceamong the RCS because of agroecosystem differentiation. The poor farmers, who lived inand closer to the TSL basin relied the most on traditional rice; floating and long-term rice,
were vulnerable to food insecurity and insufficient household’s income, changes of theecosystem services in their regions. They reported the ES are more importance to their RCS
than other medium and large farmers. Adaptive RCS and irrigation system should promotecorresponding to the dynamic changes, ecosystems of Tonle Sap Lake.
Keywords rice cropping system, agrarian system and diagnosis, ecosystem services,perception, economic analysis, Tonle Sap Lake

INTRODUCTION
Tonle Sap lake (TSL) is known as a complex ecosystem, which provides a substantial hydrological,
biological, nutritional, cultural value and the productive operations as natural floodwater reservoir inthe lower Mekong region offering flood protection and assuring dry season flow to the Mekong Delta(Arias et al., 2014; Kummu et al., 2014). The TSL floodplain system plays a critical role not only inⒸ ISERD

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providing necessary water resources and other environmental services for the entire country, but it
also represents a global biodiversity hotspot supporting the remarkable productions of fishery andagriculture, mainly rice (Keskinen et al., 2013).
The lowland areas are largely cultivated in TSL floodplain, which accounts for almost 90% of
the total rice cultivation fields as well as for 77% of total rice production (Chea, 2015; MAFF, 2016).
Particularly RCS are enormously dependent on the natural resources provisioning. Battambang
province is the major producer of rice called “rice bowl” located in northwest of Cambodia, wheremore than 70% of the population depend on agriculture as their main job and almost half of themcultivate rice (provincial department of planning, 2016). However, the extreme flooding occurred
which damaged more than one tenth of rice cultivated area in 2011 in the country, but the total areasof rice affected by these floods reached more than 30% in this province, while damages in Sangkae
district itself represented 70% of the total cultivated area (Kamoshita and Ouk, 2015). With thesechanges especially flood pulse of TSL, farmers have changed their RCS by adapting new innovations
and technologies in the purpose of increasing their rice production. In floodplain areas of TSL,
floating rice (FR) or long-term rice (LTR) areas dramatically shifted to high-yield rice, particularly
EWSR and/or RR practices (Keskinen et al., 2013).
OBJECTIVES
The overall objective of this study aims at understanding farmer’s perception on ecosystem services(ES) in comparison with two sites of LWL and MWL in Sangkae district, Battambang province withrespect to recent dynamics in TSL floodplain ecosystems.
Based on the interactions of these changes of TSL ecosystem sand RCS, the study discusses on
the advantages and disadvantages of the changes in RCS as well as to document the perception of
ES of TSL affecting the livelihood of households in different agroecosystems. Moreover, there arestill lack of scientific studies on such topic from Cambodia which would deeply analyse the changesof agricultural land-use systems of RCS in the floodplains in/around TSL whereas the ES of TSL
altered by the changes of its flood pulse. The study proposes to conduct a research on theseinteractions between ES of TSL and RCS in lowland area in Battambang province.
The limitation of the study did not access to measure economic comparation neither between
RCS in both MWL and MWL, nor the household’s livelihood diversity provided by provisioning andregulating services of ES from TSL
METHODOLOGY
Agrarian System Overview
The study was adopted agrarian system concept in order to achieve the objective of the study. Thisis an all-encompassing concept, capable of making sense of agricultural and livelihood activities at
a regional scale in a way that accounts for both ecological and socio-economic dimensions (Cochet,2012). The historical changes study helps to identify and understand the main dynamics ofdifferentiation among farming families and thus help define current farming systems (Barral et al.,2012).
Sample Selection and Data Collection
120 rice producing farmers (60 farmers from each site) were randomly selected in both different
agro-ecological systems in Sangkae district. Baset, Oumuni and Rorkar in Middle-water-land(MWL) site, Samdach, Svay Sar, and Boeng Tuem from low-water-land (LWL) site.

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Data Analyses
SPSS version 20 (Social Package for Social Sciences) was performed by specific tools basicallydescriptive statistic, such as frequencies, means and standard deviations. Likert scale, a psychometricresponse scale primarily used in questionnaires to obtain participant’s preferences or degree ofagreement with a statement or set of statements, was also used. The order scaling was set as 4 levels
scoring from 1 to 4 which represents from ―Strongly agree‖ to ―Disagree‖ (1=strongly agree,
2=agree, 3= somewhat disagree, 4= disagree) while the scoring from 1 to 6 representing from
―Strongly decrease‖ to ―Don‘t know‖ (1=strongly decrease, 2=somewhat decrease, 3=the same,
4=strongly increase, 5=somewhat increase and 6=don‘t know), and other scoring for awareness wasfrom 1 to 4 (1=strongly aware, 2=aware, 3=somewhat aware, 4=not aware).
Study Area
The study was conducted at floodplain areasin Sangkae districts of Battambang province.
The Fig. 1 visualised the layout and locationin red of TSL in Cambodia. The hydrologicalregime of this province supports anunnoticeable support to national economic
development contribution of Cambodia byproviding a wide range of ecosystems suchas high biodiversity and productivity, mainly
fish, plant communities, and wildlife.
Almost half of the Cambodian population
uses resources of TSL (Arias et al., 2014).
Two Ago-ecological zones of theFig. 1 Map of Cambodia and study area
Sangkae distinct were selected for this study(Arias et al. 2014)(Fig. 2), the This area from 0 -1 m unlessthere is flooding. Agricultural land is cultivated RCS such as long-term rice (LTR), early season rice
(ESR), and dry season rice (DSR). There are not many fruit trees or vegetable grown in this area.
There are available supplementary irrigation systems in this zone, which suitable for cultivating
short-term RCS.

Zone 2: Middle-water- land or middle field

Zone 1: Low-water-land or low field

Note:

Fig. 2 Landscape during wet season (November - April)
RESULTS AND DISCUSSION
Rice Cropping Practices in Two-zones
Fig. 3 shows rice cropping systems cultivated in low-water land and middle-water land. Only floating
rice (FL) is existing in LWL while there is no any farmers in MWL cultivated this rice cropping
system.

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Number ofhouseholds

50
Low-water
land
0
RR

ESR

DR

FL

LTR

Fig. 3 Rice cropping systems in different agroecology
As a result, majority of farmers (>60%) in both sides have adopted this innovation by changing
their old RCS, which practised with traditional techniques and mainly relied on natural resources
provisioning, to the new RCS which confirmed by keskinen (2013). Farmers have low adaptive
capacity while the climate and ES (flood pulse) variability have occurred in their areas which similar
to the studies rainfed upland in Cambodia (Yusf and Francisco, 2009). Insufficient supplementary
irrigation systems and depending on unreliable rainfalls and floodwater from TSL led to low
productivity improvement while they have shifted to cultivate high-yield RCS in their areas which
consistent with Sophea’s study (2012).
Farmer’s Perceptions of Ecosystem Services

Percentage (%)

Most of the farmers in both areas have similar perceptions of ES such as floodwater, wildlife, fish
and forest. They perceived that those ES dramatically declined and changed. The amount of fish wasindicated by more than 50% of farmers in the MWL as strongly decrease while 60% in the LWL. On
the contrary, among the interviewed farmers had a different opinion of floodwater. They havementioned that floodwater was strongly increased which more than 5% of them in both areas
perceived while more than 2% of farmers in the MWL was found somewhat increase as shown in
Fig. 4.
70%
60%
50%
40%
30%
20%
10%
0%

Strongly decrease
Somewhat decrease
The same
Strongly increase
Somewhat increase
Water

Wildlife

Fish

ForestWater

Wildlife

Low-water land

Fish

ForestDo not know

Middle-water land

Fig. 4 Farmer's perceptions of ES changed in TSL
FR cropping system was, traditional system, required low cost of production compared to highyield RCS. Additionally, farmers exercised this RCS with lower labour and cost of inputs, farmers
did not apply chemical fertilisers and obtained approximately 900kg/ha. Farmers practice FR for
mainly household’s consumption which similar to Sarkkula et al. (2003), who stated that FR issignificant for the poorest households on floodplain area due to its cost-efficiency. Therefore, thestudy found that farmers perceive that ES from TSL not only the water for their RCS, but also
provided other fishy research for their livelihood system. The result of analysis indicated that thefarmers in LWL valued the ES more importantly to the resources from TLS rather than the farmers
in MWL site. From this over-view, the study assumes that farmers who lived in and closer to the
TSL basin are aware of and depended directly on the ES of TSL.
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Farmers provided different information of awareness evaluation as shown in Fig. 5. The respondents
in the LWL is higher than who in the MWL, 80% of farmers in the LWL aware the ES in their RCS
annually while 60% in the MWL. In contrast, 40% of farmers in the MWL are not aware ES while
20% in the LWL. Additionally, farmers provided their level of awareness on four specific ES suchas water, wildlife, fish, and forest contributed in their RCS.
100%

80%

Percentage (%)

60%
40%

50%

20%

0%

Aware

Not aware

Low-water land

Middle-water land

Fig. 5 Farmer's awareness of ES for rice cropping systems in both sites
The Importance of Ecosystem Services
Figure 6 shows the farmer’s perceptions of the importance of ES in TSL for their RCS. As the results,
more than 80% of local farmers show that the ES are necessary for their RCS particularly floodwater.
Meanwhile, 7% of farmers in LWL mentioned not all of the ES are important while 2% of farmers
in the MWL also mentioned. Additionally, among those farmers,10% of farmers in LWL and 17%
in the MWL, also did not know whether these ES are important or not.
Percentage(%)

100%

83%

80%

66%

60%
40%
20%

7%

18%

10%

17%

0%
Not imporant

Imporant

Low-water land

Do not know

Middle-water land

Fig. 6 Farmers’ perceptions of the importance of ES for rice cropping systems
Most of the households in the both agro-ecosystems were aware of a wide range of ES
provisioning from TSL for their RCS such as freshwater, wildlife, flooded forest, and fish. Thisawareness was higher among the farmers from LWL with 80%, compared to 60% in MWL,
respectively. However, both values were lower compare to 90% observed in Nigeria (Zhang et al.,2016). It explicitly explained that farmers in the LWL might be closely interacted and depended on
the ES from TSL for their RCS while farmers in the MWL did not which relatively similar to a study
conducted in Philippines (Lasco et al. 2016) and main areas of European grasslands (Lamargue et al.
2011).
Correspondents in the LWL were more likely to be aware the causes of changing while farmers
in the MWL were not widely aware. The linkages between their livelihood and ES in TSL also mighthighlight their different perceptions of ES. Due to the LWL located very closed to TSL, most of them
actively and directly relied on those ES which led them to well recognising the causes of changes.
CONCLUSION
Land-use systems in floodplain of Tonle Sap Lake (TSL) were changed resulting particularly in vast
deforestation and replacing traditional rice varieties practices in past decades, then to modern rice
cropping systems mainly for the household’s improvement and Cambodian country’s economy. Suchchanges also affected the TSL’ES and profitability of particular systems. ES variation affected thehouseholds’ livelihood particularly the poorest households in the floodplains. Changing of the RCSⒸ ISERD

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provided highly negative impacts on ecosystems in TSL, using high chemical fertilisers, pesticides
and herbicides among inputs. Farmers were more vulnerable and prone to high risk for their RCS
due to low adaptive capacity, lack of supplementary irrigation systems and explicit reliable sourcesof metrological information to confront with ES and recent climate change. Majority of farmers inboth study sites perceived ES of TSL as important directly to their RCS and other fishery resources
provisioning to their livelihood. The more closer people to TSL basin, the more they relied on the
ES. However, not all of them perceived that ES provided by TSL are important to them while those
ES changed particularly flood pulse which in particularly year their RCS were seriously damaged byflooding. Moreover, they were aware about the changes in freshwater, fish, wildlife, and flooded
forest, but farmers in LWL were aware the causes of change of ES higher than farmers in MWL due
to their closely interaction between ecosystems in TSL.
ACKNOWLEDGEMENTS
The authors are grateful for supports and cooperation from AFABET scholarship program (20152018) funded by EU, the villagers and relevant sectoral department governors/authorities, Ecosystem
Service and Land Use Research Center (ECOLAND) at the Royal University of Agriculture (RUA)
in Cambodia, Dr. Vladimir Verner, Faculty of Tropical AgriSciences of Czech University of Life
Sciences Prague, Czech Republic, and Dr. Kimchhin SOK’s Ph.D. project.
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Impacts of hydropower and climate change on drivers of ecological productivity of Southeast Asia's mostimportant wetland. Ecological modelling, 272, 252-263.
Arias, M.E., Piman, T., Lauri, H., Cochrane, T.A. and Kummu, M. 2014. Dams on Mekong tributaries as
significant contributors of hydrological alterations to the Tonle Sap Floodplain in Cambodia. Hydrology
and Earth System Sciences, 18 (12), 5303.
Barral, S., Touzard, I., Ferraton, N., Rasse-Mercat, E. and Pillot, D. 2012. Assessing smallholder farming.
Diagnostic analysis of family-based agricultural systems in a small region. Los Banos: Southeast AsianRegion Center for Graduate Study and Research in Agriculture, Philippines.
Chea, S. 2015. Evaluating cropping system options for farmers in the lowland rice-based systems of Cambodia,
Cambodia.
Cochet, H. 2012. The systeme agraire concept in francophone peasant studies. Paris Institute of Technology
for Life, Food and Environmental Sciences (AgroParisTech), Comparative Agriculture and Agricultural
Development Research Unit. Paris, France.
Kamoshita, A. and Ouk, M. 2015. Field level damage of deepwater rice by the 2011 southeast asian flood in aflood plain of Tonle Sap Lake, Northwest Cambodia. Paddy and Water Environment, 13 (4), 455-463.
Keo, S. 2015. The impact of climate change on agricultural production in north-west Cambodia. In Conferenceon International Research on Food Security.
Keskinen, M., Kummu, M., Salmivaara, A., Someth, P., Lauri, H., Moel, H., Ward, P. and Pech, S. 2013. Tonle
Sap now and in the future? Final Report of the Exploring Tonle Sap Futures study, Cambodia.
Kummu, M., Tes, S., Yin, S., Adamson, P., Józsa. J., Koponen, J., Richey, J. and Sarkkula, J. 2014. Water
balance analysis for the Tonle Sap Lake-floodplain system. Hydrological Processes, 28 (4), 1722-1733.
MAFF. 2016. Annual report on agricultural sector in Cambodia. Ministry of Agriculture, Forestry and Fisheries,
Phnom Penh, Cambodia.
Malyne, N. 2015. Maintaining ecosystem services provided by rice production systems in Cambodia:
Identifying costs for farmers and consumers' preferences. The University Clermont Auvergne, ClermontFerrand, France.
Provincial Department of Planning. 2016. Profile on economic and social of Battambang province in year 2015.
Based on commune and district databases, Cambodia.
Sarkkula, J., Kiirikki, M., Koponen, J. and Kummu, M. 2003. Ecosystem processes of the Tonle Sap Lake. In
Ecotone II-1 Workshop, Phnom Penh and Siem Reap, Cambodia.
Yusuf, A.A. and Francisco, H. 2009. Climate change vulnerability mapping for Southeast Asia. Economy andEnvironment Program for Southeast Asia (EEPSEA), Singapore, 10-15.
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Zhang, W., Kato, E., Bhandary, P., Nkonya, E., Ibrahim, H.I., Agbonlahor, M., Ibrahim, H.Y. and Cox, C.
2016. Awareness and perceptions of ecosystem services in relation to land use types: Evidence from ruralcommunities in Nigeria. Ecosystem Services, 22, 150-160.

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Research article
erd

Improvements in Agricultural Education at Secondary
Schools in Nepal: A Case Study in Mustang District
YUSUKE KURATA
Faculty of Agriculture, Shinshuu University, Nagano, JapanKAZUKI ADACHI
Faculty of Agriculture, Shinshuu University, Nagano, JapanSIRJANA KAFLEAST Foundation, Kathmandu, Nepal

KAZUHIRO NEMOTO
Faculty of Agriculture, Shinshuu University, Nagano, Japan

MITSURU HAMANO*
Faculty of Agriculture, Shinshuu University, Nagano, Japan
Email: hamano_m@shinshu-u.ac.jp
Received 25 January 2020

Accepted 9 November 2020(*Corresponding Author)

Abstract The Nepal government introduced Technical Vocational Education to secondary
schools nationwide in 2014 as part of its School Sector Reform Plan (running from 2009
through to 2015). The purpose of agricultural education in secondary schools is to develop aworkforce to support the nation’s agricultural development and alleviate poverty. This casestudy analyzes the current status of and issues with agricultural education at a secondary
school in epal’s Mustang District. First, the curriculum and syllabi of the Plant Science
Stream program were reviewed. Second, the school’s teaching activities were analyzed andcompared with the teaching methods in use at a Japanese agricultural high school in the
Nagano Prefecture. The head of the school and a teacher of agriculture conducted
observations and interviews regarding the Japanese high school’s teaching practices in
September 2017. After observing the Japanese high school, focus group discussions wereconducted with five other agriculture teachers at the targeted school in Nepal. The discussions
found that the content of the lectures did not adequately explain local farming practices. It
was determined that the study program should conduct cultivation trials of local products inthe school farm. Students could interview local farmers and observe their crop production,agro-processing, livestock rearing, and natural resource managements. Students could
practice farming to use the products for their own consumption or sales at school and local
markets. These activities can strengthen students’ understanding of agricultural informationand techniques. The suggested activities would also allow the teachers to learn what
information to include in the lectures and practices to support students’ knowledge of farming
practices relevant to the local area.
Keywords Nepal, mountain area, rural development, practical education

INTRODUCTION
A quarter of epal’s total population of 27 million falls below the poverty line. More than 80% of
the population lives in rural areas, and 73% are engaged in agriculture. Agriculture accounts for 33%
of epal’s gross domestic product (World Bank, 2017). epal’s ational Strategy Plan (13th threeyear plan) aimed to improve living standards and reduce poverty to 18% by 2020 (National Planning
Commission, 2013). Furthermore, the Ministry of Agriculture Development (MoAD) (2016)prioritized the strengthening of agricultural education to improve agricultural productivity and reduceⒸ ISERD

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poverty. However, public agricultural extension services have been limited to reach the rural farmers
due to lack of the budget, infrastructure and qualified extension workers. In addition, the supply
driven extension approaches rather than demand driven have been failing to cater the needs of the
farmers (Dhital, R.P. 2017). Technical and Vocational Education and Training (TVET) program
under the Council of TVET have allocated 175 training centers in different areas of Nepal but they
are mainly in urban areas. Agricultural training service are also limited in only 20 training centers(Asian Development Bank, 2015).
In 2013, as a part of epal’s School Sector Reform Plan (2009-15), the Ministry of Education(MoE) established a technical and vocational education (TVE) program in secondary schools,
covering the 9th, 10th, 11th, and 12th grades (MoE, 2009; MoE, 2016). The TVE program includes
Plant Science, Animal Science, Civil Engineering, Electrical Engineering, and Computer
Engineering. The aim of introducing the TVE program was to promote technical studies and facilitate
the development of practical engineers who could contribute to epal’s economic development andpoverty alleviation (MoE, 2016; Santwona Memorial Academy Pvt. Ltd., 2017). The Plant Science
Stream program aims to attract students to pursue higher education in the subject who can then workin agricultural organizations or companies and promote the role of local agricultural businesses andfarming within the overall economy (MoE Curriculum Development Center, 2015; MoAD, 2016).
In 2014, the MoE introduced five TVE program in 99 model schools nationwide (MoE, 2015;
Santwona Memorial Academy Pvt. Ltd., 2017). As of 2017, 284 schools had adopted a TVE programin secondary school, including 94 which introduced the Plant Science Stream, the largest among all
the programs (MoE, 2018).
The Plant Science Stream in secondary schools is expected to enhance the capacity developmentof national human resources to promote agricultural and rural development in Nepal. However, there
is no study, yet which clarifies the current situation since agricultural education has only recently
been introduced in secondary schools.
OBJECTIVE
This study analyzes the current status of agricultural education, focusing on Plant Science Stream insecondary schools in Nepal, and identifies issues and ways to improve the program.
METHODOLOGYThis study employed action research which involved both the researchers and targeted beneficiaries,
agricultural teachers in this case, to address the existing issues together (Greenwood and Levin, 1998).
Education research has often utilized action research for not only teachers’ learning to develop
teaching methods and skills but also the solutions of significant problems in classrooms and schools(Gregory S. C. Hine. 2013). A teacher or a group of teachers try to identify the issues in their classes
and come up with causes and possible solutions with a concrete action plan to apply to the actual
lessons as trials. The trial results are monitored and evaluated to ascertain the effectiveness of thesolutions. This process is often repeated until addressing the issues and the findings can be sharedwith other teaching staff and researchers as a valuable reference for further developments(Greenwood and Levin, 1998; Gregory S. C. Hine. 2013.).
This study tried to identify the issues of the teaching methods and other related environmentsof the surveyed school through the observation of those in Japan for comparison, and several focus
group discussions to identify the issues and necessary action plans to solve them with the researchers’
facilitation. A targeted secondary school for this study was selected in a mountainous area where thealtitude is around 2,600 m in the Mustang district of Nepal (MP RC, 2017). The school introduced
the Plant Science Stream in 2014 when the TVE program had just started in Nepal (MoE, 2016).
Observations were conducted in December 2016 and again in August 2017, a survey was first
conducted comprising observations of lectures and practices; interviews with teachers on theirteaching methods; and reviews of the curriculum, syllabi, and teaching materials in a Plant ScienceⒸ ISERD

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Stream at the targeted school. A questionnaire survey was conducted with the students to record theirbackground, the agricultural experiences of their family, and their career expectations.
Second, in September 2017, to identify the educational issues, joint observations wereconducted in a Japanese agricultural high school in the Nagano Prefecture with the head of thetargeted school, an agriculture teacher at that school, an MoE officer, and the researchers. The
observation team compared their own education at the targeted schools in Nepal with the education
system and teaching practices at the Japanese agricultural high school. Thereafter, in November andDecember 2017, the teachers led several focus group discussions with five other teachers ofagriculture at the targeted school, through the facilitation of the researchers.

Fig. 1 Target area in Nepal
RESULTS AND DISCUSSION
Teachers and Students of the Surveyed School
As of August 2017, the targeted secondary school had seven teachers in charge of agriculturalsubjects and six teachers for general subjects. The agriculture teachers came from areas that were all
located at altitudes much lower than that of the Mustang district. The school had 29 students in the
9th grade, 16 in the 10th grade, 20 in the 11th grade, and 16 in the 12th grade. The 12th-grade students
were the first group to join the Plant Science Stream of the targeted secondary school.
Table 1 indicates the results of a questionnaire completed by the 12th-grade students in
December 2016, when they were in the 11th grade. The students originated primarily from the samevillage development committee (VDC) area of the surveyed school and neighboring VDCs. Somestudents came from areas far away from the school or urban areas. The school offered dormitories,
kitchen facilities, and dining rooms for out-of-area students. The parents of 13 out of the 14
respondents were engaged in agriculture. The chief crops cultivated as staple foods were maize,
potatoes, buckwheat and legumes. Most families grew vegetables and fruits such as carrots, radishes,cabbages, cauliflowers, apples, walnuts, and potatoes are planted as cash crops in the region to be
sold to markets in the urban areas. Certain staple foods were generally grown on farmlands using aseasonal crop rotation system. Vegetables and fruits were generally grown in small fields near homes,
or in backyards. Regarding students’ plans after graduation, seven students aimed to study agriculturein university and seven students planned to work in agriculture.

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Table 1 House business and expected careers of the students (December, 2016)
House business

Agriculture: 13 (Maize, Barley, Wheat, Buckwheat, Potato, Common bean, Wildbean, Carrot, Radish, Cabbage, Cauliflower, Apple, Walnut)/ Non agriculture: 1

Expected career
after graduation

Agriculture: 7 (4 males and 3 females) , Study in university: 7 (6 males and 1
female) Expected faculty to be enrolled: Agriculture 6, Other 1

Note: Respondents were 14 (Male: 10, Female: 4) out of 16 students in the 12th grade

Curriculum and Syllabus
The curriculum for the Plant Science Stream at the targeted school included general subjects, suchas Nepali, English, Mathematics and Science subjects, as well as agricultural subjects which are
shown in Table 2 (MoE CDC, 2015; Higher Secondary Education Board, 2015). Each subject has asyllabus covering the course content including the teaching times, objectives, study outcomes,
content of theory and practice, and evaluation criteria and methods. Agricultural subjects
encompassed a step-by-step learning process from basic knowledge and techniques required in the
9th grade to more specific and subdivided subjects in the 10th to 12th grades. The curriculum also
required 3,100 hours of practical work in four years.
Table 2 Agricultural subjects of Plant Science Stream in the surveyed school
Grade

Subjects

9

Principle of Agronomy / Principles and Practices of Fruit Crop / Plant Protection / Soil and Soil
Fertility Management / Extension and Community

10

Vegetable and Medical Plant / Floriculture and Nursery Management / Crop Protection / FarmManagement and Marketing / Aquaculture and Fisheries / Industrial Entomology and Mushroom

11

Commercial Fruit Production and Orchard Management / Food Crops Production and Food
Security / Participatory Agriculture Extension and Marketing

12

Commercial Vegetable Production and Marketing / Sustainable Integrated Nutrient and Pest
management / Commercial mushroom production and marketing

Table 3 Syllabus “Principles and Practices of Fruit Crop Production” in the 9th Grade[Theory] 1. Introduction: 1.1 Meaning & definition of horticulture and branches. 1.2 Importance & scopeof horticulture. 1.3 Types of fruit crops (tropical, subtropical, and temperate) found in Nepal.
2. Climate: 2.1 Environmental factors affecting fruit production. 2.2 Role of climate on fruit distribution.
3. Home garden, 4. Orchard management, 5. Plant growth, 6. Plant growth regulators, 7. Cultivation offruit crops, 8. Harvesting and post-harvest handling of fruits.
[Practical] 1.1 Identify fruit / plantation crops. 1.2 Identify horticultural tools / equipment. 2.1 Lay-out
orchard / tea garden. 2.2 Perform digging and filling of pits and planting of fruits. 2.3 Perform training andpruning of fruit and plantation crop. 3.1 Fertilize / manure fruit trees. 3.2 Prepare Bordeaux mixture / paste.
3.3 Practice cutting / layering / grafting. 4.1 Study the equipment/tools used for preservation. 4.2 Study
ripening of banana. 4.3 Perform dehydration and water loss of different fruits. 4.4 Prepare jam / jelly /ketchup / juice / squash / pickles. 4.5 Prepare green coffee.

On completion of the first agricultural course, Principles of Agronomy, which covers the basic
knowledge of agronomy and cultivation environments, including plant physiology, soil management,
cropping systems, water management, and post-harvest management, students undertook Principles
and Practices of Fruit Crop Production which was conducted in the same year. As Table 3 illustrates,
the syllabus focused on the basic knowledge of fruit production, and on commercial fruit production
and orchard management, which focused more specifically on all kinds of existing Nepalese fruits
from tropical, subtropical, and temperate areas. The class included practical and applied knowledgeⒸ ISERD

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on production skills, farm management, and marketing and distribution systems. Teachers covered
tropical and subtropical fruits in lectures, and temperate fruit crops were introduced later. Practicalactivities offered the experience of identification of fruit crops, the orchard setting, field preparation,
fertilization, grafting, pest control, harvesting, and processing (MoE CDC, 2015).
Teaching Methods in Nepal and JapanAt the surveyed school in Nepal at the time of this study, textbooks or teaching manuals were yet tobe created for the Plant Science Stream. Therefore, as Fig. 2 shows, teachers had to prepare teachingnotes based on the reference books recommended in the syllabi. Moreover, the students studied laterfrom their lecture notes. In class, the teacher explained the content of the teaching notes orally andby writing on the whiteboard. Additionally, cultivation practice was conducted in the school farm.
At the beginning of agricultural education in 2014, one hectare of school farmland had beendeveloped, and cultivation practice was conducted each year.

Fig. 2 Teaching environments in the surveyed school
On September 5th, 2017, teaching activities in the subject Agriculture and the Environment
were observed in a Japanese agricultural high school. As Fig. 3 shows, the teacher first explained in
the classroom about rice grain maturity and the appropriate timing of harvesting based on the
moisture content of the rice. Second, the teacher guided students to conduct field observations on
differences in rice maturity, depending on the varieties. Students sampled the rice stalks with paddy
from different varieties to measure the moisture. After returning to the classroom, the students drew
diagrams of the rice stalks and measured the moisture of the paddy to prepare a report. The classes
covered the entire production process and growing stages of rice, including the preparation of the
paddy fields, seeding, transplanting, growth, and harvesting. The theory and practice wereinterconnected, as Fig. 4 shows.

Fig. 3 Integration of teaching methods, lectures, field practices, and teaching material
at the Japanese agricultural high school
Issues and Improvement Plan Based on the Focus Group Discussions(1) Prioritizing local products in lectures and connecting theory with practice:In the focus group discussion, the teachers suggested focusing more on local agricultural products,
although they recognized the importance of knowledge of Nepalese agriculture in tropical,
subtropical, and temperate areas. These teachers felt that local farming practices should be integrated
into the cultivation practices on the school farm and into the teaching of theory in lectures.
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Fig. 4 Integration of the lecture and field practice at the Japanese agricultural high school
The discussion indicated that the teaching content in the lectures and practices did not appear to
be integrated. A teacher who had visited Japan emphasized issues based on learning points observedin the Japanese teaching method which connected comparative cultivation trials on rice varieties withlecture contents. These points included observation, measurement of the product’s growth and yieldcomponents, and report writing relating to the farming practice season by season.
Teacher in charge of Principle of Agronomy in the 9th grade suggested connecting the contentsof the lecture and the farming practices with popular local crops such as barley. The field practice
could then include a comparison of cultivation among the different varieties of barley. Duringlectures on germination, for example, the teacher could use the barley cultivation practices to teachthe practice of determining germination rate.
Furthermore, the characteristics of plant growth and flowering time could be observed andrecorded in the field when the same contents were explained in the lectures. The harvest season could
offer the opportunity to observe different maturity timing and to collect yield data for comparisons.
The timing of the teaching content in the lectures should thus be matched with the instruction content
in the practice activities.
(2) Introducing comparative research:
In the situation at the time of this study, cultivation at school farms was rather limited in offering theexperience of farming practices. The teacher in charge of “Industrial Entomology and Mushroom”
in the 10th grade also emphasized the necessity of introducing a research context in lectures andpractice. The appropriate varieties of mushroom which were easily grown in the school area could
be produced in the school farm, allowing for several research topics such as variety comparisonsregarding growth and yield. The mushroom beds were available in the agricultural research center inthe region and were easy to obtain.
Comparative research could also be introduced to compare apples in different areas. Even if
apple trees were not grown in the school farm, the school practice could be conducted on apple farms
outside of the school. Teachers and students could visit apple farmers in different areas. The same
variety of apple could be collected from different village and the sugar contents of the fruits could
be compared.
As a plan for cultivation practices and comparative cultivation trials, the teachers suggested thatthe school farm be divided into 20 plots for the 9th and 10th grades and another 20 plots for the 11thand 12th grades. In the school farm, crops and vegetables could be cultivated as experimental fieldpractices. Comparative experimental cultivation could provide opportunities for scientific research
into different treatments and could also develop knowledge and skills regarding data collection,
analysis, and report writing.
It was thus felt that the idea of research should be introduced in lectures and practices. Local
products and varieties of each crop, in addition to local cultivation practices, could be used as
research targets and prepared for cultivation experiments under the supervision of the agriculture
teachers. The experience and knowledge thus gained would later be useful for students, both in higher
education and when or if they engage in agriculture.
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(3) Learning from farming and processing practices at students’ homes and on local farms:
At the time of this study, the families of most students were farmers who cultivated crops, vegetables,and fruits on their own farms or in their home gardens. There were hence many opportunities forstudents to learn from their own agricultural practices. Additionally, students could learn about
natural resources and water management from the real farming practices by local farmers.
Many farmers around the school grew fruit trees, including apple and walnut. The teacher incharge of Principles and Practices of Fruit Crop in the 9th grade suggested that the subject could belinked to the local apple farming and processing which were practiced in the areas around the school
and in the neighboring villages. Apples were processed into dry fruit, alcoholic beverages, juice, andjam. It was suggested that these local production processes should be learned through student visitsand experienced by the students in the practices in school.
(4) Utilizing the school farm more efficiently and effectively for learning and school
management:
The school farm consists of five hectares, including the field and building; however, only one hectare
has been used for farming practices since 2014. Thus, the agricultural field could be extended for
greater production.
Since apple and walnut are popular as cash crops, it was suggested that the plantations on theschool farm be increased for cultivation and research opportunities. These practices could be
integrated into the teaching content of the Principles and Practices of Fruit Crop in the 9th grade.
Moreover, it was suggested that cauliflower, cabbage, radish, ginger, garlic, onion, and several leaf
vegetables be grown as a part of students practice in the school farm. These cultivation practices
should then be connected with Vegetable and Medical Plant in the 10th grade and Commercial
Vegetable Production and Marketing in the 12th grade.
If apples were to be harvested at the school, agro-processing such as the production of dried
apple and apple jam could be practiced in the school kitchen. It was suggested that the learning
opportunities arising from existing local processing businesses should be increased by taking
students to visit the processers.
More than 20 students who came from the villages or cities far from the school stayed in theschool dormitory. The school financially supported the students who stayed at the school dormitory
by purchasing food supplies from local markets or farmers. However, it was proposed that if theaforementioned farming activities could be increased, students could produce food for their own
consumption. Some harvested and processed products could also be sold in the school or to the local
residents. These activities could assist the school management financially, as well as increase
learning opportunities regarding farming and business management.
(5) Accumulating the teaching content of lectures and practices:
Since the training and licensing system for teaching agriculture has yet to be established, the subject
teachers have not been professionally trained. Most agriculture teachers came from other areas andwere not familiar with the farmers’ practices and local products grown at an altitude of 2,600 m. The
teachers therefore also suggested that each teacher should create teaching notes which could be filed
and provided as instructional notes for new teachers. It is important to accumulate teachingknowledge so as to operate efficient schools that incorporate local agriculture.
Relevance of the Results of the Focus Group Discussions
These results identified the issues in agricultural education in the targeted secondary school in Nepal
while TVE in secondary school has just been introduced in secondary schools nationwide since 2014.
Among five discussion points, the essential issue to be improved is strengthening the links between
the educational contents, and regional agriculture and livelihoods with related businesses.
The implementation of the Technical and Vocational Education and Training (TVET) programby Council of TVET has resulted in a low employment rate of graduates largely due to the mismatch
between the market needs and program content (ADB, 2015; Bagale, 2018). ADB (2015) argued thatthe involvement of industry and business is necessary to a market that is responsive in assessing thejob market’s demand to enhance the employability and productivity of the workforce. InformationⒸ ISERD59

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sharing between industry and technical institutions is essential to connect the training content with
the necessary skills and knowledge of the targeted businesses to close the gap between educational
content and learning outcomes which are far from what the market demands (Nepal, 2015; Bagale,2018).
In the case of the technical education in agriculture (Plant Science Stream) at the surveyedschool, a limited connection of the teaching content with local agricultural practices is recognized as
the primary issue as argued by the studies cited above. As the TVET experiences indicate, it is a
critical situation with a high risk of mismatching between teaching content and the real need for
agricultural development in the region. Also, teaching new agricultural techniques, material,
equipment, and economic system without understanding local and traditional farming practices runs
the risk of the students uncritically adopting those new technologies which sometimes ruin the naturalenvironment and unexpectedly change the socio-economic situation in the region.
The rural people’s knowledge and practices on agriculture and natural resources use have been
already appropriate and reasonable in many cases. The traditional livelihoods including farming
system in developing countries are generally complex and diversified so that rural people can reduce
vulnerability and enhance security and ensure long term well-being and sustainability. These
traditional rural practices should be appropriately evaluated and outsiders’ and rural people’sknowledge could combine their strengths and neutralize the weaknesses (Chambers, 1983; Chambers,
1997).
The main purpose of technical education should be to develop the human capacity to improveor optimize the old practices through obtaining the new information, technologies, business strategies,
and even lifestyles without environmental and cultural distraction.
Thus, the learning process from real agricultural practices of local farmers could be fundamental
for agricultural education. Comparative research can provide the opportunities to enhance thestudents’ capacity for critical thinking with a verification (evaluation) method on the traditional
practices and newly introduced techniques. The farming practices through cultivation experiments
and crop–fruit–vegetable production in the school farm can not only give meaningful farming skills
and learning opportunities of the regional agricultural practices but also trial practices of newtechniques and material including seeds and equipment. Crop–fruit–vegetable production forstudents’ consumption in the school can also provide the experiences of processing, storing, andselling the products which enhances the students’ knowledge and skills in agricultural management
and business development.
The record of research process and outputs including the collected data and students’ reports
can be accumulated to utilize as teaching materials and learning references. Kanel (2015) emphasizes
the importance of the TVE in secondary schools to enhance capacity development of the teaching
staff of technical education. The accumulation of the information through the research and practices
in and out of the school can be the teaching contents and manual for the teachers. This practicalinformation can be utilized as effective teaching material during the daily lectures in the classes.
Combining the theory and practical information based on real farming practices in the daily lectures
can synergistically lead to effective and understandable teaching methods in each agricultural subject.
CONCLUSION
This study identified the existing issues and possible action for the improvement of agricultural
education in the surveyed secondary school in Nepal through observations of the Japanese school forcomparison and discussions by the teachers with researchers’ facilitation. The effectiveness of theseideas should be monitored and evaluated through the implementation of the action plan for the
improvements.
ACKNOWLEDGEMENTS
This study was conducted under the implementation of JICA partnership project on Enhancement ofAgricultural Education in Higher Secondary School in Nepal (2016-2018). We thank Kami-inaⒸ ISERD

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Agricultural High School (Nagano Prefecture, Japan), AST Foundation, and Curriculum
Development Center of MoE (Nepal) for their cooperation for the project implementation.
REFERENCES
Asian Development Bank. 2015. Innovative strategies in technical and vocational education and training foraccelerated human resource development in south Asia Nepal. Asian Development Bank, 79.
Bagale, S. 2018. Necessity of linkage of TEVT with industry in Nepal. International Journal of Social Sciences
and Management, 5 (4), 237-242.
Chambers, R. 1983. Rural development: Putting the last first. Longman, Harlow, UK.
Chambers, R. 1997. Whose reality counts? Putting the first last. ITDG Publishing, London, UK.
Dhital, Pankaj Raj. 2017. Agricultural extension in Nepal: Experiences and issues. Journal of Advances inAgriculture, 7 (3), 1071-1082.
Government of Nepal, Ministry of Agriculture Development. 2016. Agriculture development strategy 2015 to2035. Nepal, 135.
Government of Nepal, Ministry of Education. 2009. School sector reform plan 2009-2015. Nepal, 128.
Government of Nepal, Ministry of Education. 2015. Status report 2014/015, School sector reform program(SSRP)- District school sector reform program (SSRP). Center Education for All Shishu VikashKaryakram Community School Capacity Development Program. Nepal, 282.
Government of Nepal, Ministry of Education. 2016. School sector development plan 2016/17-2022/23. Nepal,
184.
Government of Nepal, Ministry of Education. 2018. Numerical concise information of TVET schools. Nepal.
Government of Nepal, Ministry of Education, Curriculum Development Centre. 2015. Secondary level school
curriculum technical and vocational stream class 9 to 10, Plant science. Nepal, 95.
Government of Nepal, National Planning Commission. 2013. An approach paper to the thirteenth plan 20132016. Nepal, 175.
Greenwood, D.J. and Levin, M. 1998. Introduction to action research: Social research for social change. SAGE
Publication (California), 274.
Gregory, S. and Hine, C. 2013. The importance of action research in teacher education programs. Issues in
Education al Research, 23 (2).
Higher Secondary Education Board Curriculum and Training Division. 2015. Curriculum of technical subject
group higher secondary level (grade XI and XII), Plant science. Nepal, 53.
Kanel, C.H. 2015. Introducing technical and vocational education and training (TVET) in the secondary
schools in Nepal: Opportunities and challenges. Journal of Training and Development, 1 (1), 3-8.
Mega Publication and Research Centre. 2017. National and district profile of Nepal 2016/2017. Nepal, 884
Nepal, P.H. 2015. Exploring the gap between content and learning outcomes in Nepalese technical education.
International Conference on Emerging Trends in Technical and Vocational Education and Training Vision
2025, Bhopal, India.
Santwona Memorial Academy Pvt. Ltd. 2017. A study on technical and vocational education in secondary
school as a separate stream: Required policies, strategic measurers, implementation arrangement andimprovements needed in teaching learning to enhance program effectiveness. Nepal, 139.
World Bank. 2017. https://data.worldbank.org/country/nepal? (derived on 14th February 2017).

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Research article
erdTreatment of Wastewater from Dyeing Process of Weaving
Workshop in Inle Lake by Using Lotus Stalk and Coconut
Shell Charcoal
CHAW SU HLAING*
Department of Chemistry, Taunggyi University, Taunggyi, Myanmar
Email: chaw88@gmail.com

NAN NOE NOE OO
Department of Chemistry, Taunggyi University, Taunggyi, Myanmar

AH MAR YI
Department of Chemistry, Taunggyi University, Taunggyi, Myanmar
Received 30 January 2020

Accepted 12 November 2020(*Corresponding Author)

Abstract Inle Lake is the second largest natural lake in Myanmar. It has a population of some
150,000 people, many of whom live on floating islands of vegetation. About half of thepeople who live in Inle Lake work the traditional hand weaving business. It is now facing theenvironmental degradation of its area due to human activities. Direct discharging ofwastewater containing contaminants (especially azo dyes and heavy metals) from dyeing
process into its environment impairs the soil and water qualities and causes a series ofproblems in living beings. In this research, the treatment of wastewater of dyeing processfrom silk, lotus and cotton hand weaving workshops in Inle lake was performed by sorption
technique using local available waste, lotus stalk and coconut shell charcoal as the major
sorbent materials. The results obtained from dyed wastewater treatment using activatedcoconut shell charcoal (5 g), activated lotus stalk (5 g), and a combination effect of activatedlotus stalk and activated coconut shell charcoal at a 4:1 ratio for appropriate time taken
treatment indicated that the highest color removal efficiency (94%, 95%, 100%) respectively.
Therefore, a combination of sorbent materials (4:1) might be the best choice for the dyed
wastewater treatment. The resultant data of before and after treatment of wastewater werecompared with WEPA standard for public health. Some tested heavy metals andphysicochemical properties of treated water were within the WEPA standard. However, longterm disposing of wastewater without proper treatment causes a serious problem. Therefore,
treatment of wastewater before discharging into its environment is necessary for theconservation and sustainability of Inle Lake.
Keywords coconut shell charcoal, cotton, dyeing wastewater, Inle Lake, lotus stalk, silk

INTRODUCTION
Water pollution has become one of the most dangerous threats to the environment in today’s world.
The negative effects of water pollution are not just limited to human beings, but it is fatal for theentire ecosystem. Water comes from many sources like ground water, surface water such as lakewater, pond water, river water, etc., which is why the causes of its pollution are different dependingon the source. Chemical, textiles, tannery industries etc. cause high rate of pollution (Vijaya, 2014).
The effluent containing heavy metals, chemicals, such dyes, oils and many other harmful materials
are discharged by the industries into the water bodies without proper treatment, thus leading tocontamination of said water bodies. All the wastes of the colorant category produced from various
types of industries might have injurious impacts on microbial flora and fauna and may be unhealthyand sometimes even fatal to mammals. At low concentrations, dyes have an adverse effect on the lifeof marine animals and therefore, the food cycle. As per their design, dyes are relatively very steadyⒸ ISERD

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molecules, created to fight against the deterioration by light, biological, chemical and other naturalmodes of degradation (Qada, 2008).
The most widely methods for removing dyes from wastewater systems include physicochemical,
and biological methods, such as flocculation, coagulation, precipitation, adsorption, membrane
filtration, electrochemical techniques, ozonation and fungal decolorization (Sotelo et al., 2002).
Amongst the numerous techniques of removal of dye, adsorption is an effective and useful process.
Adsorption is considered to be superior in comparison with the other techniques of dyeing
wastewater treatment due to low cost, easy availability, simplicity of design, high efficiency, ease ofoperation, biodegradability and the ability to treat dyes in more concentrated form which can mix thewastewater and the porous material powder or granules, such as activated carbon and clay, or let thewastewater through its filter bed composed of granular materials (Zongping, 2011).
But the use of one individual process may often not be sufficient to achieve complete
decolorization. The present study is to explore the feasibility of natural waste materials, lotus stalkand coconut shell charcoal as a low cost and local available sorbent materials in Inle Lake,
Nyaungshwe Township, Taunggyi District of Southern Shan State in Myanmar. The lake has 22 kmlong and 10 km across. It is famous for its scenic beauty and the unique leg-rowing of the Inthas, thenative lake dwellers. It is one of the main tourist attractions in Myanmar. Moreover, the hand weavingwith lotus fiber is also a well-established part of the tourist trail. But, the dyeing wastewater and fiber
extracted lotus stalks which discharged from these hand weaving workshops were adverse effectfrom ecosystem of Inle Lake. Therefore, through this research the potential of treatment of indigo
color dyeing wastewater by the use of new waste matter (lotus stalk) which is handily available inabundance of Inle area has been explored. The used indigo color dye powder is the Bayer trademark.
The chemical formula of indigo is C16H10N2O2 (Wouten, 1991) and its molecular structure is asshown in fig. 1.

Fig. 1 Molecular structure of indigo dye
OBJECTIVES
The aim of this research is to reduce the adverse effect of wastewater from dyeing process on Inle
Lake area by using the treatment with local available waste sorbent materials such as lotus stalks andcoconut shell charcoal, and to protect the environmental deterioration of the lake caused by dye
pollution.
METHODOLOGY
An experimental process of this research was done to evaluate the removal capacity of lotus stalkand coconut shell charcoal with respect to various parameters such as color adsorbent capacity ofmaterial with initial concentration at different doses, time and pH on indigo color dyeing-wastewater.
In all the investigations, the methods and techniques involved both conventional and modern
methods. All observations and measurements except scanning electron microscope (SEM) analysis
were performed in laboratory of Chemistry Department, Taunggyi University, Southern Shan State,
Myanmar. SEM analysis was performed in laboratory of Chemistry Department, Western University
of Yangon.
Collection of samples: The fiber extracted residual lotus stalks, coconut shells and indigo color
dyeing wastewater were collected from one of the silk, lotus and cotton hand weaving workshop in
Inle area in December, 2018. The chemicals used in the experimental work were purchased fromlocal chemical store. All chemicals were of reagent grade.
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Preparation of sorbent materials (non-activated and activated lotus stalk): The fiber extracted
residual lotus stalks were cleaned with tap water and distilled water to remove dust particles andwater-soluble impurities. After that, these were cut into small pieces, dried in sunlight for 2 days
until the stalks became crisp. Then using a mortar the stalks were crushed until uniform size particle
was obtained and sieved to desired particle size in order to produce the non-activated lotus stalks.
In the preparation of activated sorbent material, non-activated lotus stalk powder was washedthoroughly with distilled water to remove the dust particles, then soaked overnight in 0.1 M NaOH
solutions and again washed with double distilled water. Then they were soaked in 0.1 M CH3COOH
for a period of 2-3 hours to remove the traces of NaOH. It was thoroughly washed again with double
distilled water till the wash water became colorless and then filtered, air dried, powdered and sieved
before use.
Preparation of non-activated and activated coconut shell charcoal: The coconut shells wereseparated and cleaned from other materials, such as coconut fiber or soil and then dried in sunlight.
The dried coconut shells were burned at burning sink or drum at 200 to 550C for 3-5 hours to getcharcoal. Some charcoal was soaked in chemical solution (25% H3PO4) for 24 hours to become
activated charcoal. The obtained activated charcoal was washed with distilled or clean water andspread on tray at room temperature to be drained. Then, it was dried in oven at temperature 110Cfor 3 hours. These non-activated and activated charcoal were ground and sieved to get the size rangeof 50-100 mesh. The prepared sorbent materials are shown in Fig. 2 (a) and (b).
Characterization of the surface function of prepared sorbent materials: The prepared sorbent
materials were examined by Fourier-transform infrared spectroscopy (FTIR) analysis and scanningelectron microscope (SEM) for a visual inspection of surface morphology.
Determination of maximum wavelength absorbed by indigo dyeing wastewater: The maximum
wavelength, max is the wavelength at which the highest absorbance of the solution has. At thiswavelength, the solution is most sensitive to concentration changes. To determine the λmax ofcollected dyeing wastewater sample, the absorbance versus wavelength graph was constructed byexamining the absorbance of a certain concentration of collected dye sample using UltravioletVisible (UV-VIS) spectrophotometer. The resulted graph was showed in Fig. 6 (a).
Determination of molar absorptivity of indigo dyeing wastewater: The four indigo dyeing
wastewater with the various concentrations of 0.25%, 0.5%, 1%, and 1.25% were prepared and theirabsorbance were examined by UV-VIS spectrophotometer at 530 nm (λmax of collected dye sample).
Then the calibration curve of absorbance versus concentration was constructed and the molar
absorptivity () of indigo dyeing wastewater was determined from the slope of the trend line. The
resulting data are described in Fig. 6 (b).
Treatment of indigo dyeing wastewater: In each twenty separate flasks, 100 mL of 1% originaldyeing wastewater was mixed with the varying masses of 1-5 g of non-activated lotus stalk, activatedlotus stalk, non-activated coconut shell charcoal, and activated coconut shell charcoal respectively
and allowed to stand for 1 day at room temperature. Moreover, the varying amount of 1-5 g of nonactivated coconut shell charcoal, and activated coconut shell charcoal were added in five separate
flasks and allowed to stand for 2 hours. Then the mixtures were separately filtered through filter
paper Whatmann No.1 and the absorbance of each filtrate was determined by UV-VIS
spectrophotometer at 530 nm.
Furthermore, the 100 mL of 1% original dyeing wastewater was mixed with prepared sorbent
materials (non-activated and activated lotus stalk) of various masses ranging from 1 g to 5 g wereadded to this solution in each separate flasks and the mixtures were allowed to stand for 1 day. After
that, the mixtures were separately filtered through filter paper Whatmann No.1. To the filtrates, thedesired amount of various masses (1-4 g) of non-activated coconut shell charcoal and activatedcoconut shell charcoal were separately added and allowed to stand for 2 hours. After sufficient time,the mixtures were filtered again and the pH of each filtrate was adjusted to 7 using 0.1 M citric acid.
Finally, the absorbance of dye solutions before and after treatment were determined by UltravioletVisible (UV-VIS) spectrophotometer at 530 nm. From the observed absorbance of each dye solution,Ⓒ ISERD

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the concentrations and removal percent were calculated using Beer- Lambert’s law and the equation(1) respectively. The resulting data are presented in Tables 2, 3 and 4.
Assessments of quality of dye treated water: The parameters analysed to assess the treated water
qualities were pH, chemical oxygen demand (COD), biochemical oxygen demand (BOD), dissolved
oxygen (DO), total hardness, total alkalinity and some heavy metals. BOD, COD and total hardness
were determined by titration methods. pH, DO and total alkalinity were examined by pH meter, DO
probe (AMT-07) and alkalinity test kit, respectively. Arsenic and heavy metal contents were analysed
by Palintest arsenator and atomic absorption spectrophotometer (SHIMADZU AA-7000). The
resulting data are presented in Table 5.
RESULTS AND DISCUSSION
Fig. 2 (a) and (b) show the prepared lotus stalks and coconut shell charcoal.

Fig. 2 (a) Lotus stalk (b) Coconut shell charcoal
FTIR Analysis
Fourier transform infrared (FTIR) was used to provide structural and compositional information on
the functional groups presented in the solid sorbent materials. Figure 3 shows the infrared spectrumof prepared lotus stalk. The band assignments are tabulated in Table 1.

Fig. 3 FTIR spectrum of lotus stalk
The characteristic peaks of O-H stretching and C-H stretching bands were observed at 3396.64
cm and 2922.16 cm-1. The band at about 875.68 cm-1 shows the characteristic of the deformation of
the glycosidic linkage in cellulose. Furthermore, some peaks in the 600 to 900 cm-1 region associatedwith the aromatic ring C–H out of plane bending vibration were found in the spectrum, corresponding
to the aromatic skeletal vibration in lignin. A dominant absorption bands at 1629.85 and 1431.18 cm1, representing the stretching of symmetric and asymmetric C=O groups of hemicelluloses which
present in the lotus stalk. The band at 1035.77 cm-1 corresponded to C-OH represents the stretchingof alcoholic group-1Ⓒ ISERD

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Table 1 FTIR spectrum assignments for lotus stalkExperimental
Frequency (cm-1)
3396.642922.16
1629.85
1431.181035.77875.640*Literature
Frequency (cm-1)
3200-3600
2800-3000
1600-1950
1400-1470
1000-1200
450-1000*Band assignments
(OH) stretching
(C-H) aliphatic, CH2 , CH3
 asy (C=O) (carbonyl) sym (C=O) (carbonyl)(C-O) (alcohol)(C-H) aromatic*Silverstein (1981)

From the information which found in FTIR analysis, it may be confirmed that lotus stalkprincipally consists of cellulose, pectin, hemicellulose, lignin and chlorophyll pigments.
SEM Analysis

(b)

(a)

Fig. 4 SEM photograph of non-activated coconut shell charcoal
and activated coconut shell charcoal
Fig. 4 (a) and (b) show the surface morphology of non-activated coconut shell charcoal and activatedcoconut shell charcoal. Since micro and meso pores are observed on the surface of the sorbent
materials, significant adsorption is likely to occur. SEM image of the activated coconut shell charcoal
revealed that a more cluster form of aggregate with cavitated pores than the non-activated one.
Therefore, the activated charcoal may be responsible for the more enhanced specific sorption
properties than non-activated one.
Lotus stalk has spongy like and porous structure. Fig. 5 (a) and (b) show surface morphology
of lotus stalk before and after treatment of indigo dyeing-wastewater. After treatment of indigo dye
is very different from surface morphology of before treatment. The significant changes of foam likeand porous structure of the lotus stalk before treatment of indigo dye waste were observed in surface
morphology of the lotus stalk after treatment of dye waste materials. It is one way to explain thenature of images that sorption of dye waste materials on the surface of lotus stalk may take place.

Fig. 5 SEM photographs of lotus stalk before treatment andafter treatment of indigo dyeing-wastewaterⒸ ISERD

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Determination of  max and Molar Absorptivity of Indigo Dyeing Wastewater
Fig. 6 (a) shows absorbance versus wavelength plot of indigo dyeing wastewater to determine  max.
It is found that the max is at 530 nm. Fig. 6 (b) shows the calibration curve of absorbance versus
concentration of indigo dyeing wastewater. The molar absorptivity, ε, was determined from the slopeof the line. The observed value of molar absorptivity, ε, of indigo dyeing wastewater was found tobe 0.5054 cm-1mol-1L by Beer-Lambert’s Law, A = ε c l, A = absorbance of the sample,c = concentration of the sample, l = optical path length.
0.45

AbsorbanceAbsorbance

0.40
0.35
0.30
0.25
0.20

0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0

y = 0.5054x
R² = 0.9823

0400420440460480500520540560580600

0.25

0.5

0.75

1

1.25

1.5

Concentration (%)

Wavelength (nm)

(b)

(a)

Fig. 6 (a) Absorbance versus wavelength plot of indigo dyeing wastewater and(b) Absorbance versus concentration plot of indigo dyeing wastewater
Effect of Prepared Sorbent Materials on Treatment of Dyeing Waste Water
In this research, dye color in collected sample was not completely removed by using only one
prepared sorbent material at fairly time and dosage. Only if the combination effects of prepared twosorbent materials, discharge of dye color was found to be high activity.
Table 2 shows the removal efficiency of indigo dye color by each of the prepared four types ofmaterials. It is found that the removal efficiency of the use of non-activated lotus stalk and nonactivated coconut shell charcoal were not so good on indigo dye color by the use of increase dose of
non-activated lotus stalk and decrease dose of non-activated coconut shell charcoal. Although theoriginal indigo dye color is discharged, the pale yellow color which produced from lotus stalk was
remained. But, the removal efficiency of activated lotus stalk and activated coconut shell charcoal
were found to be fairly high.
Table 2 Removal activity of indigo dye’s color by four types of sorbent materials
Time
taken
Materials (hour)

Concentration of 1% original dyeing
Removal percent (%)
wastewater (mol L-1)
Pr
BeforeAfter treatment (ce)valuetreatment
1g
2g
3g
4g
5g
1g 2g 3g 4g 5g
(co)
NALS
24
0.084 0.048 0.040 0.056 0.078 0.081 43 52 33
740.906*
0.034
ALS
24
0.084 0.034 0.032 0.017 0.005 0.004 59 62 80 94 95
0.963** 0.008
NACSC
20.084 0.049 0.044 0.041 0.038 0.039 42 48 51 55 54
0.935*
0.020
ACSC
20.084 0.037 0.024 0.020 0.013 0.005 56 71 76 85 94
0.988** 0.002
NALS = Non-activated lotus stalk, ALS = Activated lotus stalk, NACSC = Non-activated coconut shell charcoal,
ACSC = Activated coconut shell charcoal, Volume of 1% original dyeing wastewater = 100 mL, Wavelength = 530 nm
r = Pearson correlation coefficient, P-value = probability of obtaining result, * = significant correlation𝑐 𝑐Percent removal of dye = 𝑜− 𝑒 × 100(1)
𝑐𝑜

Where, co = initial concentration (mol L-1),
ce = equilibrium concentration (mol L-1)

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Table 3 shows the removal efficiency on indigo dyeing wastewater by the combination effectof non-activated lotus stalks with non-activated and activated coconut shell charcoal. From theseresults, it is found that the dye removal efficiencies of activated coconut shell charcoal is superior to
the non-activated coconut shell charcoal. Activation of prepared sorbent materials has more effectover non activation. Therefore, the treatment of dyeing wastewater was continually performed by
activated sorbent materials to achieve high efficacy.
Table 3 Comparison of removal efficiency on the indigo dyeing wastewater by the
combination effect of non-activated lotus stalk with non-activated and activatedcoconut shell charcoal
Absorbance of 1% original
Concentration of dyeing
Removaldyeing wastewater
wastewater (mol L-1)
Materials
Percentr
P-value
BeforeAfter
BeforeAfter(%)
Treatment
Treatment Treatment
Treatment
NALS (1g) and NACSC (1g)
0.424
0.242
0.084
0.048
42.9
NALS (2g) and NACSC (1g)
0.084
0.424
0.323
0.064
23.8
-0.998*0.04
NALS (3g) and NACSC (1g)
0.084
0.424
0.436
0.086
0
NALS (1g) and ACSC (1g)
0.424
0.235
0.084
0.050
44.6
NALS (2g) and ACSC (1g)
0.424
0.261
0.084
0.052
33.4
-1.000** 0.005
NALS (3g) and ACSC (1g)
0.424
0.331
0.084
0.065
21.9
NALS = Non-activated lotus stalk, NACSC = Non-activated coconut shell charcoal,
ACSC = Activated coconut shell charcoal, Volume of 1% original dyeing solution = 100 mL, Wavelength = 530 nm
r = Pearson correlation coefficient, P-value = probability of obtaining result, * = significant correlation

Table 4 shows the removal activity of the combination effect of activated coconut shell charcoal
and activated lotus stalk. It was found to be more effective on the discharge of indigo dye color. The
combination effects of various masses (1 g, 2 g, 3 g, 4 g) of activated lotus stalk and activated coconut
shell charcoal were found to be (68.9, 80.7, 91.3 %, 94.1% ) removal efficiency respectively. The
dye removal efficiency increases with increasing usage of the amount of activated sorbent materials.
But the combination effect of 4 g of activated lotus stalk and 4 g of activated coconut shell charcoal
was found just a little high efficacy than 3 g combination of each type of sorbent material. This isdue to the 4 g of each type of activated sorbent material only has high efficiency. The combination
effect was seemed to be need to fix amount of one sorbent material and another with variable dose.
Thus, the investigation was continually performed by the use of reduced mass of one of the activatedsorbent materials. In this study, the main attention is to explore the effect of lotus stalk materials on
the discharge of color of dyeing wastewater. Therefore, the observation was performed by the use of
lotus stalk as major sorbent material. The optimum condition was found to be the combination effectof 4 g of activated lotus stalk with 1 g of activated coconut shell charcoal (100%).
Table 4 Removal efficiency on the indigo dyeing wastewater by the combination effect ofactivated lotus stalk and activated coconut shell charcoal
Materials

Absorbance of 1% originaldyeing wastewater
BeforeAfter
Treatment
Treatment

Concentration of dyeing
wastewater (mol L-1)
BeforeAfter
Treatment
Treatment

RemovalPercent (%)

r

ALS (1g) and
0.424
0.132
0.084
0.026
68.9
ACSC (1g)
ALS (2 g) and
0.424
0.082
0.084
0.016
80.7
ACSC (2g)
ALS (3g) and
0.424
0.037
0.084
0.007
91.3
0.976**ACSC (3g)
ALS (4g) and
0.424
0.025
0.084
0.004
94.1
ACSC (4g)
ALS (4g) and
0.424
0.000
0.084
0
100
ACSC (1g)
ALS = Activated lotus stalk, ACSC = Activated coconut shell charcoal
Volume of 1% original dyeing solution = 100 mL, Wavelength = 530 nm
r = Pearson correlation coefficient, P-value = probability of obtaining result, * = significant correlationⒸ ISERD

68

P-value

0.004

IJERD – International Journal of Environmental and Rural Development (2020) 11-2

Statistical analysis of observed results were performed with Pearson correlation analysis. The
results were significant correlated for non-activated sorbent materials and highly significant
correlated for activated sorbent materials.
Table 5 shows the assessments of quality of dyed wastewater before and after treatment process.
By comparing the resulted data with the WEPA wastewater discharge standards for public area, thetested parameters of dye treated water were within the desirable range for ecosystem of Inle Lake.
Table 5 Assessments of Quality of Dye Treated Water
Parameters(ppm, except pH)

1 % original
dyed wastewater

Treated water

pH
BOD
COD
DO
Total alkalinity (as CaCO3)
As
Cd
Cu
Fe
Pb

8.2
13.8
54
3.97
300
ND
0.06180.14502.81850.0307

7
10.0
22
3.04
70
ND
0.01800.04570.42990.0154

Wastewater discharge standards for
public area
(WEPA, 2013)
6-9.5
30
120
600
0.25
0.03
0.5
2.0
0.2

CONCLUSION
From this study, it may be concluded that the removal of dyeing wastewater from Silk and Lotus
Hand Weaving Workshop in Inle Lake area by activated lotus stalk and activated coconut shellcharcoal has been found to be useful for controlling water pollution caused by dyes. From thisexperiment, it is clear that the removal of color of dyes is influenced by the amount of adsorbents
and contact time. The completely destruction of dye color, the highest removal (100%) was favorable
for the combination effect of activated lotus stalk (4g) and activated coconut shell charcoal (1g) in
100 mL of 1% original indigo dyeing wastewater. Thus, with the experimental data obtained in thisstudy, it is possible to design and optimize an economical treatment process by recycling local wastematerials for the dye removal from Silk, Lotus and Cotton Hand Weaving Workshop effluents in Inle
area.
ACKNOWLEDGEMENTS
The authors would like to express special gratitude to Rector Dr Mu Mu Myint, Taunggyi University
and our Ministry of Education for giving us the opportunity to present this research paper. I also
thanks to Professor and Head, Dr Ah Mar Yi, Department of Chemistry, Taunggyi University, ourco-workers and friends for their guidance, helpful and encouragements during this field. We wish to
express our grateful thanks to Shan State Young Entrepreneurs Association (SSYEA) in Taunggyi
City for their kind help and financial support throughout this research paper. Moreover, we also thankthe reviewers of IJERD for their help in improving the quality of our research paper and their criticalreviews.
REFERENCES
Qada, E.A. 2008. Adsorption of basic dyes from aqueous solution onto activated carbons. Chemical
Engineering Journal, 135, 174-184
Silverstein, R.M. 1981. 4th Edition, Jhon Wiley & Sons, Inc. N.Y. 306-311.
Sotelo, J.L., Ovejero, G., Deiado, M.J.A. 2002. Adsorption of lindane from water on GAC: Effect of carbon
loading on kinetic behavior. Chemical Engineering Journal, 87 (1), 113-120.
Vijaya, L. 2014. Removal of malachite green dye from water using orange peel as an adsorbent. 4-34
http://ethesis.nitrkl.ac.in/6030/1/E-178.pdfⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

WEPA (Water Environment Partnership in Asia). 2013. Environmental quality standards for water and effluent
standards.
Wouten, J.V.A. 1991. High-performance liquid chromatography of blue and purple indigoid natural dyes.
Journal of the Society of Dyers and Colorists’, 107, 266-269.
Zongping, W. 2011. Textile dyeing wastewater treatment, advances in treating textile effluent. 100. derived
from https://en.wikipedia.org/wiki/Beer Lambert lawⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

Research article
erd

Diversity of Arthropod Natural Enemy Species in Intensive
Monsoon Rice Growing Area, Nay Pyi Taw, Myanmar
WAI ZIN PHYU*
Yezin Agricultural University, Myanmar
Email: waizinphyu209@gmail.com

MOE HNIN PHYU
Yezin Agricultural University, Myanmar

THI TAR OO
Yezin Agricultural University, Myanmar
Received 20 January 2020

Accepted 27 November 2020(*Corresponding Author)

Abstract This study was conducted to investigate the species diversity of arthropod natural
enemy species structure in intensive monsoon rice cultivation areas during 2018. The studysite is Kyee Inn village, Pyinmana Township, Myanmar, and over 550 ha. Data collectedfrom (300 m x 300 m) grid pattern and 56 grid points (G) using a D-Vac vacuum suctionmachine. This study identified eight orders, 30 families, 57 genera, and 28 arthropod natural
enemy species. The highest species richness occurred in Order Hymenoptera, followed by
Order Coleoptera and Order Hemiptera. The diversity of natural enemy was varied widelywith different grid points. The recorded equitability (evenness) was equally abundant in mostgrid points, but some have high single-species dominance. The highest number ofCyrtorhinus lividipennis (Order Hemiptera) found in G18, even though G18 displayed amedium diversity index and low equitability. The population of Cyrtorhinus lividipennis washigher than other species in all grid points. It may due to food sources are abundant during
the growing season. Fortunately, we observed many natural enemy species, and it should
conserve for natural balance to maintain the pest population.
Keywords natural enemy community, species diversity, equitability,
intensive monsoon rice

INTRODUCTION
Rice (Oryza spp.) is the most important and widely cultivated crop globally. It is the staple crop for
more than 60 percent of the world population. Rice is a dietary staple throughout all Myanmar. In
Myanmar, paddy sown total area is 7.28 million hectares (monsoon and summer rice), and riceproduction is 28.32 million metric tons (MOAI, 2014). Arthropods are the most diverse and dominantconstituent of biodiversity in terrestrial ecosystems. It is the largest animal phylum constituting about
85% of all known animals in the world (Odegaard, 2000).
In agricultural fields where pesticide use is minimized, crop production commonly depends onnatural controls provided by a pest's natural enemies. These have an important role in regulating pest
populations (Barbosa, 1998). The importance of natural enemies is particularly highlighted when apest resurgence takes place (Dent, 2000). Indiscriminate use of agrochemicals, such as insecticides,
harms these natural enemies and causes a loss in such beneficial organisms' biodiversity. Agrobiodiversity performs several ecosystem services (Dudely et al., 2005).
The biodiversity of beneficial natural enemies may be a pivotal resource to improve productivity
and sustainability in agriculture (Schmitz, 2007). The arthropods, natural enemies of rice insect pests,
include a wide range of predators and parasitoids such as carabid beetles, aquatic and terrestrial
predatory bugs, and dragonflies. Parasitoids include many hymenopteran wasp species and some
dipteran flies (Bambaradeniya and Amerasinghe, 2003). Beneficial insects provide regulating
ecosystem services to agriculture such as pollination and the natural regulation of plant pestsⒸ ISERD

71

IJERD – International Journal of Environmental and Rural Development (2020) 11-2

(Getanjaly, 2015). Although most of the farmers are familiar with some rice insect pests in Myanmar,
they don't know the important role of arthropod natural enemies and are not familiar absolutely. Thus,
it is crucial to study the species richness of natural enemies in their habitat and conserve them toimprove biological control.
OBJECTIVE
This research investigates the species richness and diversity of natural enemies on monsoon rice tosupport farmers' valuable information.
METHODOLOGY
Study Site
The study was conducted in 56 farmers' fields during the monsoon rice season at Kyee Inn village,
Pyinmana Township, Nay Pyi Taw, which lies between 19°70'66''-19°72'62'' N and 96°22'43''96°25'73'' E from July to November 2018. The sampled area is 2.4 Km wide by 3.9 Km long (550ha). The Manawthukha rice variety is grown in the study fields using farmers' usual practices.

Nay Pyi Taw

Kyee Inn
VillagePyinmana TownshipFig. 1 Study areas at Kyee Inn Village, Pyinmana Township, Myanmar
Species Sampling
Arthropod natural enemies were collected on a 300 m by 300 m grid pattern, resulting in 56 grid
points started at 20 days after sowing until harvest time. Five samples were taken at random fromeach rice field. All samples were collected near the center of the plot, at least 5m from the edge, toreduce edge effects using D- Vac Vacuum Insect et - Hand Carry Model 122S (made by Rincon –Vitova Insectaries). The collection from 4-5 hills of rice plant after sowing, but only 2-3 hills after
the rice plant reached maximum tillering at the fortnightly interval. Sampling duration was fixed at
1 to 2 min, depending on the rice's growth stage, and each sampling repeated three times. All samples
inside the enclosure were collected and transferred to plastic bottles containing ethyl acetate withcotton wool, with species identification conducted in the laboratory for identification. All thecollected samples were stored in 90% methylated spirit.
Identification of Species
Species identification was made in the JICA-ELB1 Laboratory, Department of Entomology andZoology, Yezin Agricultural University. All the collected samples were stored in 90% methylated
spirit. Morphospecies identification was made by using the textbooks of Insects of Australia (CSIRO,
1970), Manual of Nearctic Diptera, Volume 1, 2, 3 (McAlpine et al., 1981), and Pests of rice andⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

their natural enemies in Peninsular Malaysia (Vreden and Ahmadzabidi, 1986) with OLYMPUS SZ
61 camera attached microscope (10x × 45x).
Data Analysis
The abundance and species richness of arthropod natural enemies were measured by the ShannonWiener function (Krebs, 1978). Shannon-Wiener function was used to measure the index of species
diversity by the following formula:
𝑆

𝐻= −∑

(𝑃𝑖 ) (𝑙𝑜𝑔2 𝑃𝑖 )𝑖=1

Where;
H = index of species diversity or information content of sample (bits/individual)
S = number of species
Pi = proportion of total sample belong to ith species (Krebs, 1978)
More even or equitable distribution among species will also increase species diversity measured by
the Shannon-Wiener function (Krebs, 1978). Equitability (evenness) measured in;
𝐸 = 𝐻/𝐻𝑚𝑎𝑥
Where;
E = equitability (range 0 – 1)
H = observed species diversity
Hmax = maximum species diversity = log2S
RESULTS AND DISCUSSION
Species Diversity and Abundance of Natural Enemy Species
There were eight orders, 30 families, 57 genera, 28 species identified in this study (Table 1). The
observed arthropod orders are Araneae, Coleoptera, Dermaptera, Diptera, Hemiptera, Hymenoptera,
Odonata, and Orthoptera. In 2014, 44 species from seven orders of natural enemy species wereobserved in Nyaungbingyisu, Nay Pyi Taw (Khin Ngu War Thant, 2016). May Thet Hlaing (2017)
surveyed 118 species in Nyaungbingyisu (Pobbathiri Township), 62 species in Kyarku,
Dekkhinathiri Township, and 105 species Zalaung, Oattarathiri Township, and 103 species in Yezin
Agricultural University Campus. Hurlbert et al., (1989) found that the numbers of species andindividuals and the diversities and evenness values were distinctly different according to habitat, typeof field, and rice growth stage. The criterion used by (Rahayu et al., 2006) holds that species
biodiversity is high when the value is greater than 3, a medium between 1 and 3, and low when lessthan 1. In our study, high diversity index occurs at 11 grid points and a medium at 44 grid points.
The remaining grid points displayed a low level of diversity. Therefore, the overall species diversity
index was considered in the medium criterion (Fig. 2.a, b).
Alatalo (1981) devised an index of species abundance (evenness or equitability) typically on ascale ranging from near 0, indicating low evenness or high single-species dominance, to 1, whichmeans an equal abundance of all species, or maximum evenness. According to the results, therecorded equitability (evenness) of 19 grid points show a low index of evenness, while 37 grid points
are approaching equal abundance (≥ 0.5) (Fig. 3.a, b). According to the results, the recorded
equitability (evenness) of most grid points in the study area was nearly equally abundant, and someare high single-species dominant. The highest diversity index (3.44) is in G31 and the most evenness(0.82) in G32 (Fig. 2.b and Fig. 3.b).
On the other hand, the lowest diversity index (0.99) and least equitability (0.22) occurs in G46(Fig 2.b and Fig 3.b). Therefore, the diversity of natural enemy species varied widely according todifferent grid points due to adjacent habitats, cropping patterns of the area, farmers' practices such as
irrigation, pesticides, fertilizers, and pests.
Ⓒ ISERD73

IJERD – International Journal of Environmental and Rural Development (2020) 11-2

Table 1 Recorded natural enemy species from the study area,
Kyee Inn Village, Pyinmana Township, 2018
No.
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
55.
56.

Order
Araneae
Araneae
Araneae
Araneae
Araneae
Araneae
AraneaeColeoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Dermaptera
Dermaptera
DipteraHemiptera
Hemiptera
Hemiptera
Hemiptera
Hemiptera
Hemiptera
Hemiptera
HemipteraHymenoptera
Hymenoptera
Hymenoptera
Hymenoptera
Hymenoptera
Hymenoptera
Hymenoptera
Hymenoptera
Hymenoptera
Hymenoptera
Hymenoptera
Hymenoptera
Hymenoptera
Hymenoptera
Hymenoptera
Hymenoptera
Hymenoptera
Hymenoptera
Hymenoptera
Hymenoptera
Hymenoptera
Hymenoptera

FamilyTetragnathidae
Araneidae
Oxyopidae
Linyphiidae
Lycosidae
Lycosidae
Lycosidae
Staphylinidae
Coccinellidae
Anthicidae
Staphylinidae
Carabidae
Carabidae
Coccinellidae
Coccinellidae
Carabidae
Carabidae
Carabidae
Staphylinidae
Carabidae
Carabidae
Hydrophilidae
Staphylinidae
Anisolabididae
Forficulidae
Pipunculidae
Miridae
VeliidaePentatomidae
Reduviidae
Mesoveliidae
Reduviidae
Reduviidae
Reduviidae
Dryinidae
Eulophidae
Dryinidae
Braconidae
Pteromalidae
Formicidae
Eulophidae
Formicidae
Eurytomidae
Diapriidae
Platygastridae
Diapriidae
Braconidae
Formicidae
Formicidae
Formicidae
Formicidae
Halictidae
Ichneumonidae
Braconidae
Formicidae
Ichneumonidae

Genus
Tetragnatha
Araneus
OxyopesAtypena
Hippasa
Trochosa
LycosaBledius
Micraspis
Anthicus
Paederus
Bembidion
Casnoidea
Harmonia
Menochilus
Clivina
Ophionea
Eucolliuris
Lathrobium
AnillusAnoplogenius
Berosus
StenusEuborellia
Doru
Tornosvaryella
Cyrtorhinus
Microvelia
Zicrona
Polytoxus
Mesovelia
Peregrinator
Rhynocoris
Zelus
Aphelopus
Elasmus
Gonatopus
BraconTrichomalopsis
Dorymyrmex
Tetrastichus
Myrmecocystus
Eurytoma
Trichopria
Macroteleia
Trichopria
Phanerotoma
Leptothorax
Pheidole
LasiusManicaSpeciesmaxillosasp.
sp.
formosana
sp.
sp.
sp.
filipescroceasp.
ripariussp.
indicaoctomaculata
sexmaculatus
fossornigrofasciata
fuscipennis
sp.
sp.
sp.
sp.
sp.
annulipes
sp.
oryzaetora
lividipennis
douglasisp.
fuscoviftatus
vittigera
biannulipes
sp.
sp.
sp.
sp.
zealandicus
sp.
sp.
sp.
sp.
mexicanus
sp.
basalissp.
drosophilae
sp.
sp.
sp.
sp.
sp.

CharopsSpathius
Solenopsis
Xanthopimpla

brachypterumsp.
sp.
flavolineataⒸ ISERD

74

Mean
18.29
8.60
3.40
3.20
2.40
0.67
0.43
12.40
1.57
1.33
1.33
1.00
0.71
0.50
0.40
0.33
0.33
0.20
0.20
0.17
0.17
0.14
0.14
1.00
0.29
2.57
199.20
3.00
0.71
0.50
0.43
0.33
0.20
0.14
15.60
15.00
7.14
7.00
4.43
4.40
3.67
3.00
1.17
1.00
0.57
0.50
0.40
0.33
0.29
0.20
0.20
0.20
0.20
0.17
0.17
0.17

SE (±)
4.83
3.46
3.16
3.20
1.29
0.49
0.43
12.40
1.41
0.72
0.88
1.00
0.47
0.50
0.24
0.33
0.21
0.20
0.20
0.17
0.17
0.14
0.14
1.00
0.18
1.93
133.46
1.90
0.71
0.50
0.43
0.33
0.20
0.14
15.35
11.66
4.72
5.05
2.36
4.15
2.08
3.00
1.17
0.82
0.20
0.34
0.40
0.33
0.29
0.20
0.20
0.20
0.20
0.17
0.17
0.17

IJERD – International Journal of Environmental and Rural Development (2020) 11-2

Table 1 (contd.)
No.
57.
58.
59.
60.

Order
Odonata
Odonata
Orthoptera
Orthoptera

FamilyCoenagrionidae
Coenagrionidae
Gryllidae
Gryllidae

Genus
Agriocnemis
Agriocnemis
Anaxipha
MetiocheSpeciespygmaeafeminalongipennis
vittaticollis

Mean
5.50
3.29
3.17
0.17

SE (±)
5.50
2.65
1.40
0.17

These results were consistent with the finding of several authors have concluded that theabundance and diversity of predators and parasitoids within a field are closely related to the natureof the vegetation surrounding the field (Hopper, 1989). There is wide acceptance of the importanceof vegetation surrounding the field margins as the reservoirs of crop pests' natural enemies.

(a)

(b)

Fig. 2 Diversity index of natural enemies on rice during monsoon season
in study area (a) grid points 1 to 28 (b) grid points 29 to 56

(a)

(b)

Fig. 3 Equitability in distribution of natural enemies on rice during monsoon season
in study area (a) grid points 1 to 28 (b) grid points 29 to 56
The highest species richness of natural enemies occurs in the Order Hymenoptera, which
includes ten families, 20 genera and six species identified. The second highest species richness from
Order Coleoptera consists of five families, 16 genera and nine identified species. Order Hemiptera
has the third-highest species richness includes five families, eight genera and five identified species.
In Order Araneae, family Tetragnathidae, the highest mean number of Tetragnatha maxillosa(18.29 ± 4.83 individual) occurs at G10. Tetragnatha maxillosa is a spider species that is very active
during the night and preys upon brown planthopper (Nilaparvata lugens), leafhopper (Nephotetteixsp.), and some other insect pest species (Betz and Tscharntke, 2017). Spiders are used as a biologicalcontrol agent of rice pests instead of chemicals (Khan, 2013). In Coleoptera, the highest mean number
of Bledius filipes (12.40 ± 12.40 individual) from the family Staphylinidae occurs in G16. It might
feed on algae and detritus (Mark, 2006). The mean number of Anthicus sp. (1.33 ± 0.72 individual)
from family Anthicidae occurs in G43. Ant-like flower beetles are mainly saprophagous, somespecies being predaceous or anthophilous (feeding on flowers) (Telnov, 2008). Insects are directly
beneficial to humans by producing honey, silk, wax, and other products. Indirectly, they areimportant as pollinators of crops, natural enemies of pests, scavengers, and food for other creatures(Hoffmann and Frodsham, 1993). Under Order Dermaptera, the highest mean number of Euborellia
annulipes (1.00 ± 1.00 individual) from the family Anisolabididae is observed in G56. In Order
Diptera, the highest mean number of Tornosvaryella oryzaetora (2.57 ± 1.93 individual) from thefamily Pipunculidae is in G22. In Order Hemiptera, the highest mean number of Cyrtorhinus
lividipennis (199.20 ± 133.46 individual) belongs to the family Miridae in G18. Predators are mainlyⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

from Order Heteroptera include Cyrtorhinus lividipennis (Miridae) and Microvelia douglasi(Veliidae), being the most abundant species (Heong et al., 1991).
Under Order Hymenoptera, the highest mean number of Aphelopus sp. (15.60 ± 15.35
individual) belongs to the family Dryinidae and occurs in G7. Noyes (2008) reported that several
species of Eulophidae are important in biocontrol programs throughout the world. Hymenoptera is
the most important insect order due to many insect species that are potential pollinators andparasitoids. Its ecological specialist species are also being used widely for habitat quality assessment(Trevis, 1996). In Order Odonata, the highest mean number of Agriocnemis pygmaea (5.50 ± 5.50
individual) belong to the family Coenagrionidae and occur at G43. In Order Orthoptera, the highest
mean number of Anaxipha longipennis (3.17 ± 1.40 individual) belongs to the family Gryllidae from
G29. Among them, the observed dominant rice natural enemy species is Cyrtorhinus lividipennis
belonging to Order Hemiptera. This result was consistent with the finding of Heong et al., (1990),
who stated that the mirid bug Cyrtorhinus lividipennis was found to predate on the eggs and nymphsof both leafhoppers and planthoppers, preferring mainly BPH eggs. The population density of
Cyrtorhinus lividipennis increase in the abundance of the BPH and WBPH. Brown planthopper andWhiteback planthopper provide a broader range of food sources for an extended period during thegrowing season.
CONCLUSION
This study indicates that, arthropod natural enemy species diversity is medium in most of the grid
points for the study period. Sample results yielded eight orders, 30 families, 57 genera, and 28 speciesof arthropod natural enemies in the study. According to the results, the observed species diversity
index was considered in the medium criterion. The recorded equitability (evenness) of most grid
points was nearly equally abundant, and some are high single-species dominance. The population of
Cyrtorhinus lividipennis was higher than other species in all grid points. Therefore, the diversity ofnatural enemy species varied widely according to different grid points due to adjacent habitats,
cropping patterns of the area, farmers' practices such as irrigation, pesticides, fertilizers, and pests.
Therefore, it may be assumed that the Brown planthopper and Whiteback planthopper populations
are abundant in this and previous year and found vegetation near the field in this study area. Brown
planthopper and Whiteback planthopper provide a wider range of food sources for an extended period
during the growing season. Some insects such as Bledius filipes, Anthicus sp., Berosus sp. from Order
Coleoptera and Manica sp. from Order Hymenoptera are found as beneficial insects because ofvegetation near the field. Proper identification and understanding of natural enemies, as well as
beneficial insects, is the first step in implementing biological control and enhancing pollination
activity. Therefore, Natural enemies and beneficial insects in rice fields play an important role inagriculture. Suppose we create a better environment for natural enemies by using non-chemical
control methods at different rice growth stages. In that case, many natural enemies may suppress pest
populations, which may benefit the farmers. The present study's findings may help provide valuable
information for farmers to improve biological control techniques. Additionally, further studies should
be undertaken to establish the abundance and different natural enemies present in this area.
ACKNOWLEDGEMENTS
The authors would like to thank the generous financial and technical training support provided by
the Japan International Cooperation Agency (JICA) Project for Capacity Development of Yezin
Agricultural University (YAU-JICA TCP). We are also appreciative of the authorized persons fromthe Department of Agriculture (DoA) for facilitating the farmers’ participation in this project.
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Research article
erdProfitable Management Styles of Small-Scale Pig Farmingin Rural Areas of Cambodia
MITSURU HAMANO
Faculty of Agriculture, Shinshu University, Nagano, Japan.

NAOKI NAKANO
Faculty of Agriculture, Shinshu University, Nagano, Japan.

SOCHEAT NAK
Faculty of Animal Science, Royal University of Agriculture, Phnom Penh, Cambodia.

KASUMI ITO*
International Center for Research and Education in Agriculture, Nagoya University,
Aichi, Japan.
Email: kasumito@nagoya-u.ac.jp
Received 15 January 2020

Accepted 29 November 2020(*Corresponding Author)

Abstract For years, farmers in rural Cambodia have practiced small-scale pig farming mainlywith family-based production. However, in recent years, there has been an increasing inflow
of imported pigs grown with a lower production cost in neighboring countries. In addition,
the share of products from domestic large-scale pig farming using commercial production
systems has been increasing. This situation has led to price fluctuations in Cambodia’s highly
competitive pig and pork meat market, which affect family-based small-scale pig farming inrural areas. This study aimed to identify various management styles of small-scale pig
farming and analyze their business status to discuss the profitable management styles under
low sale price conditions. To grasp the pig farming styles, key informant interviews wereconducted with government officers, middlemen, and pig farmers in the Treang and Tramkak
districts of Takeo Province and in urban markets of Phnom Penh. The economic statuses of
pig farming were clarified by interviewing the pig farmers and observing their rearing
practices in the same areas to compare the profitability of different management styles. As aresult, three pig farming styles were identified: fattening, breeding, and both. On the other
hand, some farmers fed their pigs mainly with rice liquor residues with compound feeds,
while some did not use rice liquor residues at all but mainly compound feeds. The
comparative analysis of their economic statuses clarified that combining the fattening andbreeding operations and feeding the pigs with both compound feeds and rice liquor residues
effectively decreased the production costs and yielded comparatively high profits.
Keywords small-scale pig farming, import, by-product, agro-processing, animal feed

INTRODUCTION
In Cambodia, which is positioned as one of the least developed countries in the world, about 80% of
the population of about 15.57 million people (WB, 2015) lives in rural areas (MOP, 2013). Amongthe working population, 64.3% are engaged in the agriculture sector (ADB, 2015) and account for
28.2% of the gross domestic product of the country (WB, 2015). The Cambodian government hasprioritized the sector for poverty alleviation through increased income from agriculture, including
crop and livestock production (MOP, 2014). Due to recent economic and population growth, thedemand for meat has increased and this can enhance livestock production (MAFF 2015). Since then,pork has been the most consumed meat in Cambodia, and small-scale farmers have supplied about
70% of the pigs consumed (Huynh, et al., 2006). However, the importation of pigs and pork meatfrom Vietnam and Thailand has been increasing (Tornimbene and Drew, 2012). Cambodian domesticⒸ ISERD

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pig production peaked in 2006, before starting to decrease (FAO, 2020). Since mid-2015, the priceof pigs has been decreasing due to increasing pig imports, and local farmers cannot meet their daily
expenses (Phnom Penh Post, 2016). Tornimben and Drew (2012) argued that the increase of lower
priced imported products has discouraged Cambodian farmers from raising pigs and in extreme cases,
abandon their business. Vathana and Takeya (2006) clarified the advantageous conditions of thathave resulted in lower production costs in those neighboring countries compared to small-scale
Cambodian pig production. In addition, in 2012 the Association of South East Asian Nations signed
a free trade agreement to lift the tariff barriers of all items within the region (FAO, 2012). This lossof protection could greatly impact small-scale pig farmers under more severe business environmentsin the near future. Moreover, as large-scale pig companies with commercialized production systems
have increased their supply share in Cambodia, the family-based small-scale pig farming faces morechallenges competing with cheaper and higher quality pigs from both imported and commercialized
products (Thai, 2018). Strom et al (2017) clarified that small-scale pig farmers recognized the main
constraints to pig-keeping were high feed costs and pig diseases as well as low pig sales prices.
Recently, the high cost of compound feed and high labor requirement make it less attractive forfarmers to continue this business (Ashley et al., 2018).
Previous studies on pig farming in Cambodia discussed the advantages of utilizing agricultural
by-products as pig fattening feeds (Vathana and Takeya, 2004). Yagura et al (2010) suggests that theby-products of rice milling and rice liquor production can be used as pig fattening feeds whenavailable in appreciable quantities. However, no research has been found that gives a detailed
situation on how small-scale pig farmers in Cambodia are coping with the declining price of pigs dueto the increasing pig importation.
This study aimed to identify various management styles for small-scale pig farming and analyze
their business statuses to discuss the profitable management styles under low sales price conditions.
METHODOLOGYThis study consisted of three field studies, including key informant interviews, semi-structured
interviews, and structured interviews with small-scale pig farmers on their management styles andbusiness statuses to determine the more profitable management styles for pig farming in the rural
areas of Cambodia. The key informant interviews aimed to determine the necessary information forfurther field studies, including the location and recent situation and issues of pig farmers in the survey
area. In order to identify existing management styles of pig farming, semi-structured interviews wereconducted with all the available pig farmers in the survey area according to the result of key
informant interviews. Finally, semi-structured interviews were conducted with pig farmers who had
different management styles to analyze their business status, including all the necessary costs andsales to calculate their profit. Then, a profitable management style and its characteristics werediscussed through a comparative analysis among the business status of different management styles.
Target Area and Data Collection
The surveys for this study were conducted in Tramkak and Treang districts of Takeo Province (Fig.
1) which are in rural regions where the numbers of small-scale pig farming were confirmed with therice liquor production (Hamano, et al., 2013). Takeo Province is located between Phnom Penh
(capital city) and the Vietnam border, which are connected by the National Roads.
The key informant interviews were conducted to understand pig farming management styles
and its distribution system in the survey areas in August 2016. The key informants selected for the
study were government officers at animal husbandry offices, the district office under the provincial
Department of Agriculture, the merchants at the local markets, slaughterers, middlemen, and several
pig farmers.
Semi-structured interviews and observations to collect data on the economic status of pig
farming were conducted in August and September 2016. First, the simple survey to understand thefarmers’ management styles, which could be breeding or/and fattening, as well as their feedingⒸ ISERD

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operation and main material, was conducted with 21 farmers in the two districts. Five of these farmers
with different management styles took part in the detailed survey through semi-structured interviewson their economic status and observation of their operations. The data on the production costs onrevenue were collected, including the cost of piglet, feeding in several growth stages, facility andhealth care, growth periods and weight increases of pigs, the weight of sold a pig and its sales price,and profit from the various management styles.

Fig. 1 Target areas for the survey
An analysis of the profitability was conducted by comparing the profit per pig (head) and thefarmers’ monthly income from pig farming. The monthly incomes were also simulated under the
lower sales prices than those at surveyed time, -1,000 Riel (4,000 R = 1.00 USD), -2,000 Riel, and 3,000 Riel to examine which management styles can survive under a fluctuating pig market.
RESULTS AND DISCUSSIONManagement Styles of Pig Farming
Pig farmers were targeted and interviewed to grasp their operation styles in the areas. As a result, 21
farmers were interviewed and three styles of operation were confirmed: only breeding (2 farmers),
breeding and fattening (8 farmers), and only fattening (11 farmers). Their feeding operations werealso confirmed. Fifteen farmers fed the pigs mainly with rice liquor residues and compound feeds,
while 6 farmers mainly used compound feeds without rice liquor residues (Table 1).
Table 1 Identified management styles of pig
farming

Management
style
Breeding
Breeding +fattening
Fattening
Total

No. of interviewed pig farmers
Main feed material
Rice liquor
residue andCompoundcompound
feeds
feeds
1
1

Breeding
farmers

Breeding
and fattening
farmers

Fattening
farmers

Growing sow
Stud and farrow
Growing piglets

Total
2

3

2

5

11
15

3
6

14
21

Selling piglets tomiddlemenorfattening farmers
Buy piglets
Fattening pigs
Sellingtomiddlemenorlocal markets

Fig. 2 Chain of pig production systemⒸ ISERD

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Fig. 2 shows the distribution flows of the piglets and fattened hogs according to the results of
key informant interviews and semi-structured interviews with the 21 pig farmers. Three types of pig
farmers, only breeding, breeding and fattening, and only fattening, were identified. The farmers who
breed and fatten the pigs obtained all piglets from their own breeding. One breeding cycle is generally
about 5 months. The farmers who only fattened the pigs purchased the piglets directly from breeders
or from middlemen. The fattened pigs were sold through middlemen or transported by pig farmers
themselves to the local markets in the surveyed areas, where they were marketed either by aslaughterer in the same district, by a middleman, or sometimes by the farmer himself.
Business Status in Different Management Styles
To conduct semi-structured interviews on production cost and sales revenue and observe the pig
farming practices, five of the 21 interviewed farmers were selected for the survey. The farmers
included: two farmers (A and B) who focused only on fattening using rice liquor residues andcompound feed; one farmer (C) who focused only on fattening using compound feeds without rice
liquor residues; and two farmers who managed both fattening and breeding, one (D) of which usedliquor residues and compound feeds while the other (E) only used compound feeds. There was nochance to interview the farmers of animal breeding in detail.
The farmers were asked about their production costs and sales revenue for one fattening cycle
for farmer A, B, and C, and one cycle of breeding and fattening for farmer D and E. Table 2 shows
compares the profitability of different management styles based on the production costs including
feeding and piglet costs, sales revenue, fattening periods, and increase in weight.
Farmer A focused on pig fattening by feeding them mainly with rice liquor residues andcompound feeds. The rice bran from a neighboring miller and water convolvulus from her garden
and pond were used as feeds. Farmer A bought 17 piglets, each of which weighed about 7 kg. Three
piglets died from a disease in the very beginning, and the remaining 14 pigs were sold at a weight of
79 kg each after 5 months of fattening. Feeding costs were the highest proportion at 63.3% of thetotal costs at 5,268,000 R. The piglet cost was the second highest proportion at 32.3% of total
expenses. Health and facility cost shared 4.4%. The sales of 14 pigs at a price of 8,000 R/kg earned
a profit of 3,532,000 R.
Farmer B focused on pig fattening by feeding them mainly with rice liquor residues, compound
feeds, and rice bran. Three pigs weighed about 35 kg each; they were fattened for 3 months after
purchase, and all of them were sold at a weight of 105 kg each. Farmer B only purchased pigs that
had been grown for 2–3 months since the risk of managing them is low compared to piglets with ahigher risk of disease and death. The pigs can also be fed with rice liquor residues from the starting
point, while piglets, after weaning, require a different compound feed for about a month. The pig
cost was almost as high as the feeding cost, making up 48.0% and 49.5% of the total production cost
(2,012,000 R), respectively. Farmer B sold the three pigs at a price of 8,500 R/kg and made a profitof 666,000 R.
Farmer C managed pig fattening operation by feeding the pigs with only compound feed andrice bran without rice liquor residues. The feeding cost shared the highest ratio at 68.6% of total costs
at 1,921,000 R. Subsequently, piglet cost for 5 piglets which weigh around 5 kg each shared 26.0%of the total cost. All 5 piglets were fattened to 65 kg/head on average and sold at a price of 8,000
R/kg gaining the profit of 679,000 R.
Farmer D managed both the breeding and fattening operations. The farmer fed pigs with rice
liquor residues, rice bran, and compound feed. Table 3 shows the production costs and sales in thebreeding stage. Farmer D grew a total of 28 piglets from 3 mother pigs (sows). Nine of them weresold as piglets; 11 were fattened as hog for sales; 2 females were grown to be sows, while 6 died
before weaning. For the breeding stage, the feeding cost for sows and piglets shared 77% of the total
breeding cost at 744,000 R. The sales of 9 piglets gained a profit of 801,000 R in breeding stage. In
the fattening stage (Table 2), the total cost of farmer D was 2,783,000 R for 11 fattened pigs. In
addition, for the feeding cost and piglet cost were 85.9% and 13.4% respectively of the total cost. No
medicines and vaccines were used during the fattening stage. All 11 fattened pigs were sold at 7,800
R/kg with 63 kg of each body weight and generated a profit of 2,638,000 R.
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Farmer E also managed both the breeding and fattening operations. The pigs were not fed withrice liquor residues. As shown in Table 2, 20 piglets were grown by farmer E from two sows. Thirteenof them were sold as piglets, while the remaining seven were fattened. The feeding cost at thebreeding stage was 83.1% of the total breeding cost of 1,423,000 R. The profit from the 13 piglets
sold was 1,677,000 R. The breeding cost per head could be considered as the piglet cost per head at
the fattening stage in Table 2. The total cost of Farmer E was 3,104,000 R for 7 fattened pigs for 4
months fattening period. The feeding cost and the piglet cost were 83.6% and 16.0% respectively of
the total cost. The 7 pigs were sold at 8,500 R/head with 5 kg body weight and gained a profit of393,000 R.
Profitability among Different Management Styles
Farmer A and farmer C were compared based on their differing feed management systems, as far as
using rice liquor residues, on the similar conditions of the piglets, at 5 to 7 kg/head and around 1
month old, for fattening initiation. The feeding cost per pig for farmer A was 9.8% lower than thatfor farmer C. The feeding cost to increase 1 kg weight in famer A’s pigs was 24.2% lower than thatof farmer C. The fattened pigs were sold at the same price, therefore farmer A’s sales revenue per
pig was 21.0% higher than farmer C, based on the weight of pig sold. Therefore, the profit per pig of
Farmer A was 85.3% higher than that of farmer C. The monthly income per pig of farmer A was
47.1% higher than that of farmer C. Using rice liquor residues in the feed resulted in improving thecost effectiveness per 1 kg of weight gain, contributing to lowering the feeding cost per pig andachieving a lower total cost and higher profit per head. As a result, the monthly income per pig was
also higher even though farmer A’s system took 1 month longer than farmer C’s. Although farmer B
fed the pigs with rice liquor residues and compound feeds, the initial cost for purchasing bigger pigs,
feeding cost per pig, and feeding cost to gain 1 kg weight were 39.5% and 42.5% higher, respectively,
than those of farmer A. As a result, production cost per pig for farmer B was 78.5% higher than forfarmer A. Profit per pig for farmer B was 11.9% lower than for farmer A. However, farmer B took
only 3 months to build 70 kg weight in the pigs while famer A took 5 months to build 72 kg, andcontributed to farmer B’s attainment of a higher monthly income per pig that was 48.0% higher thanthat of farmer A.
The main difference between farmer D and E was the feeding operation of either using rice
liquor residues or not using them for both breeding and fattening management. The feeding cost per
sow and per piglet of farmer D were 51.7% and 49.1% lower, respectively, than the feeding cost forfarmer E. As a result, the production cost per piglet of farmer D was 52.1% lower than that of farmer
E. Additionally, the feeding cost per pig and feeding cost to gain 1 kg of body weight for farmer D’s
pigs were 41.5% and 45.5% lower, respectively, than those of farmer E. As a result, the production
cost per pig was 43.0% lower than that of farmer E. Profit per pig for farmer D amounted to about
4.3 times that of farmer E’s pigs. Monthly income per pig for farmer D was 3.4 times of that forfarmer E.
The profitability between only fattening management and both breeding and fattening
management can be compared between farmer A and farmer D under the same feeding operation ofusing rice liquor residues, compound feeds, and rice bran (Table 2). The feeding cost per pig and thefeeding cost to increase 1 kg weight on the pigs of farmer A at 238,000 R and 3,328 R, respectively,
are similar to those of farmer D at 217,000 R and 3,439 R, respectively. However, the piglet cost perhead for farmer D is 34,000 R, which is 66.0% lower than that for farmer A.
As a result, the production cost per pig for farmer D is 32.7% lower than that for farmer A.
Since the body weight of farmer A’s sold pig was 79 kg, which is 16 kg heavier than that of Farmer
D’s sold pig, the sales revenue per pig for farmer A is 27.6% higher than that for farmer D. Profit per
pig and monthly income per pig for farmer A were 252,000 R and 50,000 R, respectively. This was
similar to price per pig and monthly income per pig for farmer D at 240,000 R and 48,000 R,
respectively, and were higher than those for farmer C and farmer E.

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Table 2 Comparisons of profitability in different management styles
Farmers
Management styles
Compound feeds
Rice liquor residue
Pigs for starting
Pigs marketed
Death loss
Growing period (month)
Feed cost (‘000 R)
Piglet cost (‘000 R)
Facility cost (‘000 R)
Health cost (‘000 R)
Total cost (‘000 R)
Total weight of sold pigs (kg)
Average starting weight (kg)
Average sold weight (kg)
Unit price of sold pig (R/kg)
Revenue (‘000 R)
Profit (‘000 R)
Profitability (fattening) (%)
Feed cost/pig (‘000 R)
Feed cost to gain 1 kg weight (R)Piglet cost/pig (‘000 R)
Production cost/pig (‘000 R)
Sales revenue/pig (‘000 R)
Profit/pig (‘000 R)
Monthly income/pig (‘000 R)
Monthly fattening income (‘000 R)
Monthly income from piglet sales (‘000R)A
Fatten
Use
Use
17
14
3
5
3,335
1,700
83
150
5,268
1,100
7
79
8,000
8,800
3,532
40.1
238
3,328
100
376
629
252
50
706
-

B
Fatten
Use
Use
3
3
0
3
996
966
50
0
2,012
315
35
105
8,500
2,678
666
24.9
332
4,743
322
671
893
222
74
222
-

C
FattenUse
Not use
5
5
0
4
1,318
500
3
100
1,921
325
5
65
8,000
2,600
679
26.1
264
4,393
100
384
520
136
34
170
-

D
Fatten
Breed
Use
Use
11
11
0
5
2,390
372
21
0
2,783
695
63
7,800
5,421
2,638
48.7
217
3,439
34
253
493
240
48
528
160

E
FattenBreed
Use
Not use
7
7
0
4
2,595
498
11
0
3,104
412
59
8,500
3,498
393
11.2
371
6,306
71
444
500
56
14
98
335

Note:
・The feeding cost included feed material and purchased feed price and amount during the several stages of fattening
period. Feeding cost using the rice liquor residues were accounted at zero cost since rice liquor earned incomes.
・Piglets cost consisted of the unit price per head and the numbers purchased for fattening operators. Piglet cost for boththe fattening and breeding operators consisted of numbers of sows and piglets with breeding costs included the feeding
cost of sow and piglets, as well as the facility and health management costs.
・The facility cost accounted with 10 years of pig house depreciation and health management cost.
・The labor cost was not included in the calculation since all the respondents operated with only family members.

Profitable Management Style under the Low Sales Price
Fig. 3 simulates the change in the monthly income per fattened pig under declining sales prices.
Farmers reported that lower pig sales price per kg of weight in the past were in the range of 5,000 R7,000 R which were 1,000 R-3,000 R lower than the current sales prices at around 8,000 R-8,500 R.
Farmers C and E who fed the pigs with compound feed without rice liquor residues faced a deficit
when sale prices decreased 2,000 R and 1,000 R respectively.
On the other hand, farmer A and D, who feed the pigs with both rice liquor residues andcompound feed, can remain profitable with sales price decreasing 3,000 R. The amount farmer B
generated on a monthly basis as income per pig was around 1.5 times that of farmer A and D at thesales price during the survey. However, if the sales price went down by 2,000 R, farmer B would run
into a deficit due to the higher production cost per pig compared to Farmer A and D. The comparison
between farmer A and D also shows that farmer D can keep advantageous income during the sales
price declines due to a lower production cost than farmer A.
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Table 3 Comparisons of economic statusesof breeding managements
Farmers
D
E
Mother pigs
3
2
Born piglets
28
20
Sold piglets
9
13
Fattened piglets
11
7
Grown as sow
20
Dead piglets
60
Production cost (‘000 R)
Feed: sows
518
1,073
Feed: grown piglets
56
110
Facility
42
15
Health128
226
Total cost
744
1,423
Cost/ piglet
34
71
Sales, cost, profit: Sold piglets (‘000 R)
Unit price for sales
123
200
Sales revenue
1,107
2,600
Production cost306
923
Profit801
1,677
Monthly income
160
335

Monthly income per head (Riel)

IJERD – International Journal of Environmental and Rural Development (2020) 11-2

80000

Farm A
Farm B

60000

Farm C

40000

Farm D
Farm E20000
0-20000-40000Price
Dcreasedduring the 1,000R
surveyDcreased
2,000R

Dcreased
3,000R

Fig. 3 Monthly incomes per fattened pig

The comparison of the feeding operations between rice liquor residues and/or compound feeds
shows that rice liquor residues contributed in lowering the feeding cost. The feed management offarmers A and D with rice liquor residues, compound feeds, and rice bran showed a higher feed cost
efficiency to increased body weight relationship than those of farmers C and E who used only
compound feeds and rice bran. Comparing farmers who deal with breeding and/or fattening
operations revealed that an integrated management of both can contribute to a decrease in piglet costs
for fattening. The total cost of breeding sows by feeding them with rice liquor residues can produce
piglets at a lower cost than the purchasing price in the market, which includes the margin of breeders
and middlemen. As a result, the initial fattening cost can decrease, and it can contribute to thedecrease in the total cost. Additionally, breeding can generate income from piglet sales.
CONCLUSION
This study aimed to identify the management styles of small-scale pig farmers in Cambodia and to
discuss the profitability of each style by comparing their economic statuses. The results of theinterviews and observations to farmers indicated the effectiveness of integrated pig farming
operations with breeding and fattening stages and feeding management with rice liquor residues andcompound feeds to decrease the production costs. The results showed possible challenges for smallscale farmers to sustain a profitable status despite the lower sales prices of pig markets in Cambodia.
The integrated management requires more skills and knowledge on both fattening and breeding
management, including mating and taking care of small piglets that could easily die from diseases.
Wider spaces to take care of sows and piglets are also necessary. To feed pigs with rice liquor residues,
a farmer needs to manage rice liquor production and sales activities, which require equipment andstable operations and sales. Thus, further studies are necessary to understand how the farmers obtainand accumulate the information and experiences of the production techniques and business
managements, how they cope and optimize their businesses within the limited resources in labor,
finance, land, equipment, and materials in family-based small-scale productions, and what kind of
external interventions are necessary and effective.
ACKNOWLEDGEMENTSⒸ ISERD

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We thank Faculty of Animal Science, Royal University of Agriculture, Cambodia, for supporting
this survey. This study was supported by Grants-in Aid for Scientiﬁc Research ( o. 16714767) from
the Ministry of Education, Culture, Sports, Science and Technology of Japan.
REFERENCES
Ashley, K., Harrison, H., Hok Chan, P., Sothoeun, S., Robert young, J., Andrew Windsor, P. and David Bush,
R. 2018. Livestock and livelihoods of smallholder cattle-owning households in Cambodia: The
contribution of on-farm and off-farm activities to income and food security. Tropical Animal Health andProduction, 50, 1747-1761.
Asian Development Bank. 2015. Key indicators for Asia and the Pacific 2015 (46th Ed.). Asian Development
Bank, Retrived from https://www.https://www.adb.org/sites/default/files/publication/175162/ki2015.pdf
Food and Agricultural Organization/AGAL. 2005. Cambodia: Livestock sector brief. Food and Agriculture
Organization, Retrived from http://www.fao.org/ag/againfo/resources/en/publications/sector_briefs/lsb_
KHM.pdf
Food and Agricultural Organization. 2012. Regional trade agreements and food security in Asia. Food andAgriculture Organization of the United Nations, Regional Office for Asia and the Pacific, Bangkok.
Food and Agricultural Organization. 2020. FAOSTAT data. Food and Agriculture Organization, Rome.
Hamano, M., Matsumoto, T. and Ito, K. 2013. Technical modifications for the quality improvement of rice
liquor (Sraa Sar) in Cambodia. Tropical Agriculture Development, 57 (4), 126-137.
Huynh, T., Aarnink, A., Drucker, A. and Verstegen, M. 2007. Pig production in Cambodia, Laos, Philippines,
and Vietnam. A Review. 69-90.
Ministry of Agriculture, Forestry and Fisheries. 2015. Strategic planning framework for livestock development
2016-2025. Department of Animal Health and Production, Ministry of Agriculture, Forestry and Fisheries,
Cambodia.
Ministry of Planning. 2014. National strategic development plan 2014-2018. Ministry of Planning, Cambodia.
Phnom Penh Post. 2016. Pig sellers say prices in a trough. Publication Date 26 February 2016, Retrived fromhttps://www.phnompenhpost.com/business/pig-sellers-say-prices-trough
Ström, G., Andersson Djurfeldt, A., Boqvist, S., Albihn, A., Sokerya, S., San, S., et al. 2017. Urban and periurban family-based pig-keeping in Cambodia, Characteristics, management and perceived benefits andconstraints. PLoS ONE, 12 (8), e0182247.
Thai, R. 2018. Agri-food system transformation, A case study of the effects on Cambodian pig value chain
actors. Master Thesis, Agri-Commerce, Massey University, University of New Zealand. 142.
Tornimbene, B. and Drew, T. 2012. Characterisation of swine production systems in the Cambodia Mekong
lowland region. Retrived from https://agrocambodia.files.wordpress.com/2011/05/characterisation-ofswine-production-systems-in-the-cambodian-mekong-lowland-region1.pdf.
Vathana, T. and Takeya, H. 2004. Economic evaluation of local feed resources in fattening pigs in Cambodia.
Journal of Agricultural Development Studies, 15, 69-79.
Vathana, T. and Takeya, H. 2006. The international cost competitiveness of the Cambodia’s small and medium
scale swine industry. Japanese Journal of Farm Management, 44 (1), 24-33.
Word Bank. 2015. Agriculture, forestry, and fishing, value added (% of GDP) – Cambodia. World Bank Open
Data, Retrived from http://data.worldbank.org/indicator/NV.AGR.TOTL.ZS?locations=KH.
Yagura, K., Nishimura, Y., Keo, S. and Matsumoto, T. 2010. Roles and obstacles of agro-processing industries
in rural Cambodia. Journal of Agricultural Development Studies, 20, 1-8. (in Japanese with English
summary).

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Research article
erd

Selection Index for Yield and Yield Contributing Traits in
Improved Rice Genotypes
NYO MAR HTWE*
Yezin Agricultural University, Nay Pyi Taw, Myanmar
Email: dr.nyomarhtwe@yau.edu.mm

MYINT AYE
Yezin Agricultural University, Nay Pyi Taw, Myanmar

CHAN NYEIN THU
Yezin Agricultural University, Nay Pyi Taw, Myanmar
Received 15 January 2020

Accepted 29 November 2020(*Corresponding Author)

Abstract To select improved rice lines according to a selection index, a field experiment was
conducted using fifty improved rice genotypes, during the dry season of 2017 at the
Department of Plant Breeding, Physiology and Ecology, Yezin Agricultural University,
Myanmar. The examination used a Randomized Complete Block Design with three
replications. Days to 50% flowering, plant height, number of effective tillers per hill, filled
grain percentage, 1000 seed weight, number of spikelets per panicle, harvest index and yield
per plant exhibited highly significant differences indicating the existence of genetic
variability among the improved rice lines. There was not much variability in panicle length.
Seed yield per plant was positively and significantly correlated with days to reach 50%
flowering, plant height, the number of effective tillers per hill, filled grain percentage, numberof spikelets per panicle and the harvest index at phenotypic and genotypic levels. This showsthat indirect selection on these traits would be effective in improving grain yield. At the
genotypic level, path coefficient analysis shows that number of spikelets per panicle, the 1000
grain weight, filled grain percentage, number of effective tillers per hill, plant height andharvest index has a positive influence on seed yield. The selection index based on the
combination of number of effective tiller per hill, filled grain percentage, number of spikelets
per panicle and seed yield per plant (ETPP+FGP+SPP+SYPP) has the highest genetic
advance and relative efficiency. This indicated that indirect selection via these traits would
be more efficient than direct selection using yield alone. Therefore, the genotypes; YAU1215-S-S-S-41-1-1, YAU-1211-9-3-1, YAU-1211-71-1-1, YAU-1211-118-2-1 and YAU1201-151-1-1 could be selected based on multiple traits selection for further evaluation.
Keywords correlation, genotypic, path analysis, phenotypic, selection index

INTRODUCTION
Improving grain yield is one of the main objectives of many breeding programs. Seed yield is linked
to a complex inheritance and it is an ultimate expression of different factors. It is highly affected byenvironmental variations. The knowledge of the interrelationship among various yield and yieldcomponent traits is necessary for an effective breeding program (Sarwar et al., 2004). Path coefficient
analysis can estimate the causes and measurement of the relative importance of each of the yieldcomponents can also separate the direct effects from the indirect ones that are due to other characters(Ibrahim et al., 2012). Moreover, the effectiveness of a plant breeding programs depends on theability of a breeder to select superior individuals or families for many traits of interest (Strefeler andWehner, 1986a).
The economic value of a plant depends on the value of its different traits, therefore, plant
breeders should consider simultaneous selections for several traits to maximize the economic valueof a plant (Rabiei et al., 2004). Moreover, breeding and selection programs often incorporate severalⒸ ISERD

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characters simultaneously (Hill et al., 1998). It is necessary to choose individuals with the best
combination of desirable traits when considering several traits. The basis for this selection is aselection index, which is a combination of traits to select, according to their relative weighting. Gainsfrom selection for any given trait is expected to decrease as additional traits are included in the index,
therefore the choice for traits to be included must be done accurately (Hallauer and Miranda, 1981).
The Smith Hazel index is considered the optimum index when accurate estimates of variancesand covariance are available (Hazel, 1943; Strefeler and Wehner, 1986b). However, this index
requires a quantitative genetic study to estimate genetic variances and covariance and the assignmentof relative economic weights to each trait (Strefeler and Wehner, 1986a). The Smith (Smith, 1936)
and Hazel (Hazel, 1943) index and its various modifications (Kempthorne and Nordskog, 1959;
Tallis, 1962; Elston, 1963; Pešek and Baker, 1969) have been shown to be the most efficient methods
to achieve aggregate genetic progress compared with any other direct single trait selection methods.
OBJECTIVE
The objectives of this study were to determine the interrelationship between yield and yieldcontributing characters and to select the rice line(s) based on the selection indices and their relative
efficiencies in providing improvement in yield.
MATERIALS AND METHODS
Fifty rice genotypes developed at Yezin Agricultural University (YAU), Myanmar were used in thisstudy. These genotypes were developed by crossing parental lines such as Sin Thwe Latt, YadanarToe, Sin Thu Kha, Long 8, Shwe Thwe Yin and Long 6. Pedigree, bulk and single seed descentmethods were used to develop these lines. The genotypes were evaluated at the Department of Plant
Breeding, Physiology and Ecology at YAU during the 2017 dry season. The experiment site was
located in Yezin Agricultural University, Zeyar Thiri Township, Nay Pyi Taw, Myanmar, latitude
19° 10' N and longitude 96° 07' E with an elevation of 102 m above sea level.
These genotypes were grown in a randomized complete block design, with three replications.
The spacing was 20 cm × 20 cm with 100 hills per block. Standard agronomic practices and plant
protection measures were applied to ensure good crop growth and complete grain development. The
data collected were; days to 50% flowering (days) (DTF), plant height (cm) (PH), number of effective
tillers per hill (no.) (ETPP), panicle length (cm) (PL), filled grain percentage (FGP), 1000 grain
weight (g) (TGW), number of spikelets per panicle (no.) (SPP), harvest index (HI) and seed yield per
plant (g) (SYPP). All the traits were measured following the guidelines provided by the Standard
Evaluation System for Rice (SES) prepared by the International Rice Research Institute, Philippines(IRRI, 2002).
Analysis of variance (ANOVA) and correlations were generated using STAR v.2.0.1 (STAR,
2014). Path coefficient analysis was worked out using SPAR v 2.0 (Statistical Package for
Agricultural Research, Version 2.0) software and R programs. Selection indices were constructedusing the method developed by (Smith, 1936) based on the discriminate function of (Fisher, 1936).
The economic weight for Smith Hazel Index was used to evaluate the direct effects from path analysis.
The 10 % selection intensity was used to estimate genetic advances. The estimates of genetic advance
were expressed as a percentage of the genetic progress obtained from seed yield per plant alone,which was assumed to initially be 100%, and it was used to compare the relative efficiencies of thedifferent selection indices.
RESULTS AND DISCUSSION
Mean Performances and Analysis of Variances for Yield and Yield Component TraitsⒸ ISERD

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The analysis of variance revealed statistically significant differences at 0.1% probability level among
the genotypes, for all traits except panicle length (Table 1). This indicates that there is much genetic
variation among genotypes in all characters.
Table 1 Analysis of variance for yield and yield components in 50 rice genotypes
Trait
Days to 50% flowering
Plant height
Panicle length
No. of effective tillers per hill
Filled grain percentage
No. of spikelets per panicle
1000 grain weight
Harvest index
Seed yield per plant

Replication
2.007
179.554
6.125
4.903
14.992534.0683.079
0.000919.227

Genotype
79.728**657.449**
5.679
6.509**
94.504**2422.678**
28.801**0.0067**145.634**

Error
5.367
294.131
4.012
0.747
4.966
102.3841.013
0.0004
7.989** Significant at 1% probability level

Correlation Coefficient Analysis
There were 12 positive and 3 negatively significant correlations at phenotypic level and 14 positiveand 4 negatively significant correlations at genotypic level for the nine traits measured (Fig. 1 a andb). At genotypic and phenotypic levels, seed yield per plant was positively and significantly
correlated with days to 50% flowering, plant height, number of effective tillers per hill, filled grain
percentage, number of spikelet per panicle and harvest index. This showed that indirect selection
based on these traits will improve grain yield.

(b)

(a)

Fig. 1 Phenotypic correlation (a) and genotypic correlation (b) among agronomic traits
in 50 rice genotypes
The tests of significance were indicated as **, * at 1% and 5 % probability level, respectively. The blue colour
shows the positive association and red colour indicates the negative association and the intensity of the colour
indicates the degree of association.

Path Coefficient Analysis
At phenotypic level and genotypic level, all of the direct effects, with the exception of one, were
below one, suggesting that inflation due to multicollinearity was minimal (Fig. 2). At both levels, thedirect effects for number of spikelets per panicle were positive and of greater magnitude than direct
effects for the other traits. At phenotypic level, number of spikelets per panicle (1.07), 1000 grain
weight (0.60), number of effective tillers per hill (0.42), filled grain percentage (0.30), plant heightⒸ ISERD

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(0.04) and harvest index (0.01) showed a significant positive direct effect with seed yield per plant.
At genotypic level, path coefficient analysis showed that number of spikelets per panicle (1.05), 1000
grain weight (0.67), filled grain percentage (0.34), number of effective tillers per hill (0.32), plantheight (0.14) and harvest index (0.02) influenced seed yield directly in a positive direction. These
are the primary yield components in tested genotypes. In other words, when there is an increase in
the performance of these characters, seed yield per plant can also increase. However, days to 50%
flowering (-0.15) and panicle length (-0.17) had direct negative effect on seed yield per plant.
At genotypic level, days to 50% flowering (0.61) followed by harvest index (0.55), plant height(0.37) and filled grain percentage (0.30) exhibited a high order of positive indirect effect on seedyield per plant via number of spikelets per panicle. The remaining estimates of indirect effects in thisanalysis were too low to be considered of any consequence. The estimates of residual factors (0.0581)
were negligible in the present study. The residual effect determines how best the causal factors
account for the variability of the dependent factor such as the standard evaluation score. Residual
effect indicated that the characters which are selected in this study contributed 94% of variability ofthe standard evaluation score.
Therefore, the number of effective tillers per hill, filled grain percentage and number of spikelets
per panicle had significant positive correlation with seed yield as well as exercising a positive direct
effect on seed yield, suggesting the selection for these traits would be helpful for the improvementof seed yield. Path analysis studies revealed that the traits, such as the number of effective tillers perhill, filled grain percentage and number of spikelets per panicle can be considered as selection criteria
in improving the seed yield of rice as these have a prominent direct effect. Hence, selection for these
traits will improve the yield.

(a)

(b)
Fig. 2 Direct and indirect effects of seed yield and other related traits
in path analysis at (a) phenotypic level and (b) genotypic level

Selection IndicesFifteen selection indices containing two or more traits simultaneously were constructed. Out offifteen, four selection indices were more efficient than direct selection for seed yield per plant. Using
different combinations of yield and yield contributing traits, different selection indices were
formulated and their expected genetic gain and relative efficiencies were estimated (Table 2). It wasobserved that among all selection indices, the index based on number of effective tiller per hill +filled grain percentage + number of spikelets per panicle + seed yield per plant (ETPP+ FGP+ SPP+
SYPP) had the maximum genetic advance (57.79) with relative efficiency (498.65). Among theothers, the indices based on filled grain percentage + number of spikelets per panicle + seed yield
per plant (FGP+SPP+SYPP), number of effective tillers per hill + number of spikelet per panicle +seed yield per plant (ETPP+SPP+SYPP), number of spikelets per panicle + seed yield per plantⒸ ISERD

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(SPP+SYPP) showed high genetic gain with relative efficiency over straight selection for grain yieldalone. Therefore, an improvement of grain yield is suggested through these selection indices.
Table 2 Selection indices for seed yield and their relative efficiency
in YAU promising rice genotypes
Index
ETPP + FGP + SPP + TGW + SYPP
FGP + SPP + TGW + SYPP
ETPP + SPP + TGW + SYPPETPP+ FGP + TGW + SYPP
ETPP + FGP + SPP + SYPPSPP + TGW + SYPP
FGP +TGW + SYPP
FGP + SPP + SYPP
ETPP + TGW + SYPPETPP+ SPP + SYPPETPP+ FGP + SYPP
ETPP + SYPP
FGP +SYPPSPP + SYPPTGW + SYPP
SYPP

Genetic advance (g)/plant
55.94
55.93
54.51
13.82
57.79
54.60
13.51
57.67
11.68
56.36
13.54
11.25
13.28
56.31
11.40
11.59

Relative efficiency (%)
482.63482.54470.36119.20498.65471.10116.57497.61100.80486.32116.8497.03
114.55
485.8398.33
100.00

Table 3 Comparison between relative genetic score of 50 rice genotypes
based on the best selection index (ETPP + FGP + SPP+ SYPP)
Rank

Genotypes

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25

YAU-1215-S-S-S-41-1-1
YAU-1211-9-3-1
YAU-1211-71-1-1
YAU-1211-118-2-1
YAU-1201-151-1-1
YAU-1201-151-1-3
YAU-1215-S-S-S-78-3-1
YAU-1211-116-3-4
YAU-1211-26-1-2
YAU-1201-1-2-1
YAU-1215-S-S-S-40-2-1
YAU-1211-22-2-1
YAU-1201-39-2-1
YAU-1215-S-S-S-55-2-1
YAU-1211-223-3-1
YAU-1215-B-B-B-153-3-1
YAU-1215-S-S-S-77-2-1
YAU-1215-73-2-3-1-1-1
YAU-1201-74-1-2
YAU-1201-187-1-2
YAU-1214-S-S-S-77-1-1
YAU-1215-188-3-1-1-1-1
YAU-1201-202-1-2
YAU-1201-9-1-1
YAU-1214-183-35-1-1-1-1

Selection Index(Selection Score)
187.776
185.773
173.982
172.725
171.689169.348168.001
165.081164.421162.572160.616158.096155.626138.238
137.691137.037134.943134.882
134.623132.461131.854129.958
129.379129.155
127.852

Rank

Genotypes

26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50

YAU-1201-187-1-1
YAU-1215-B-B-B-168-1-1
YAU-1215-B-B-B-10-1-1
YAU-1201-206-2-1
YAU-1211-121-2-1
YAU-1201-202-2-1
YAU-1214-B-B-B-33-1-1
YAU-1201-90-2-2
YAU-1201-90-1-1
YAU-1214-183-3-3-1-1-1
YAU-1201-202-2-2
YAU-1201-61-3-3
YAU-1215-188-3-1-2-1-1
YAU-1215-B-B-B-139-3-1
YAU-1215-B-B-B-134-1-1
YAU-1214-183-3-4-1-1-1
YAU-1201-61-3-1
YAU-1215-S-S-S-115-1-1
YAU-1215-B-B-B-141-3-1
YAU-1201-16-2-1
YAU-1201-121-3-1
YAU-1215-80-1-2-1-1-1
YAU-1215-B-B-B-52-3-1
YAU-1215-S-S-S-113-1-1
YAU-1214-187-1-1-1-1-1

Selection Index(Selection Score)
127.507126.567
125.120122.602122.587
122.458
122.174
120.390117.818
117.552
116.408
115.993115.741112.413112.031109.247
107.198
103.131102.619101.81299.83095.56495.30479.83977.424

Selection based on yield alone may be often misleading due to high environmental influenceand multiple traits selection can improve selection efficiency and can attain largest economic gain.
Therefore, utilizing the best selection index (number of effective tiller per hill + filled grain
percentage + number of spikelets per panicle + seed yield per plant) (ETPP+FGP+SPP+SYPP), therelative genetic score of each genotype was determined (Table 3). It was found that the genotypes
YAU-1215-S-S-S-41-1-1, YAU-1211-9-3-1, YAU-1211-71-1-1, YAU-1211-118-2-1 and YAUⒸ ISERD90

IJERD – International Journal of Environmental and Rural Development (2020) 11-2

1201-151-1-1 were superior among all genotypes tested, having the optimal combination of attributes.
These genotypes should be used for further evaluation.
CONCLUSION
Except panicle length, all the tested genotypes have a high variation in all studied traits. Number ofeffective tillers per hill, filled grain percentage and number of spikelets per panicle had significant
positive genetic correlation with seed yield as well as employed positive direct effect on seed yieldat genotypic and phenotypic levels. The selection index based on the combination of number ofeffective tiller per hill, filled grain percentage, number of spikelets per panicle and seed yield per
plant (ETPP+FGP+SPP+SYPP) resulted the highest genetic advancement and relative efficiency.
This indicates that indirect selection via these traits would be more efficient than direct selection
considering yield alone. Therefore, the genotypes; YAU-1215-S-S-S-41-1-1, YAU-1211-9-3-1,
YAU-1211-71-1-1, YAU-1211-118-2-1 and YAU-1201-151-1-1 are superior among all genotypes
and could be selected for further evaluation.
ACKNOWLEDGEMENTS
The authors would like to express their sincere thanks to Japan International Cooperation Agency(JICA), Project for Capacity Development of Yezin Agricultural University for financial andtechnical support to conduct this study.
REFERENCES
Elston, R. 1963. A weight-free index for the purpose of ranking or selection with respect to several traits at atime. Biometrics, 85-97.
Fisher, R.A. 1936. The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7, 179-188.
Hallauer, A.R. and Miranda, J. 1981. Quantitative genetics in maize breeding. Iowa State University Press,
Iowa, US.
Hazel, L.N. 1943. The genetic basis for constructing selection indexes. Genetics, 28, 476-490.
Hill, J., Becker, H. and Tigerstedt, P. 1998. Quantitative and ecological aspects of plant breeding. Chapman
and Hall, London.
Ibrahim, E.A., Abdalla, A.W.H., Rahman, M.E.A. and El-Naim, A.M. 2012. Path coefficient and selection
indices in sixteen guar (Cyamopsis Tetragonoloba L.) genotypes under rainfed. Int. J. Agric. Forest., 2, 7983.
IRRI. 2002. Standard evaluation system for rice. International Rice Research Institute, Philippine, 1-45.
IRRI. 2014. Statistical tools for agricultural research, Version 2.0.1. Biometrics and Breeding Informatics,
PBGB Division, International Rice Research Institute, Philippine.
Kempthorne, O. and Nordskog, A.W. 1959. Restricted selection indices. Biometrics, 15, 10-19.
Pešek, J. and Baker, R. 1969. Desired improvement in relation to selection indices. Canadian Journal of Plant
Science, 49, 803-804.
Rabiei, B., Valizadeh, M., Ghareyazie, B. and Moghaddam, M. 2004. Evaluation of selection indices for
improving rice grain shape. Field Crops Research, 89, 359-367.
Sarwar, G., Sadiq, M.S., Saleem, M. and Abbas, G. 2004. Selection criteria in F~ 3 and F~ 4 population of
mungbean (Vigna radiata (L.) Wilczek). Pakistan Journal of Botany, 36, 297-310.
Smith, H.F. 1936. A discriminant function for plant selection. Annals of Eugenics, 7, 240-250.
Strefeler, M.S. and Wehner, T.C. 1986a. Comparison of six methods of multiple trait selection for fruit yieldand quality traits in three fresh-market cucumber populations. Journal of the American Society for
Horticulture Science, 111, 792-798.
Strefeler, M.S. and Wehner, T.C. 1986b. Estimates of heritabilities and genetic variances of three yield andfive quality traits in three fresh-market cucumber populations. Journal of the American Society for
Horticultural Science, 111, 599-605.
Tallis, G. 1962. Note: A selection index for optimum genotype. Biometrics, 18, 120-122.

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Research article
erd

Production and Quality of Biogas from Pilot Biodigesters
using Cow Manure
LYTOUR LOR*
Faculty of Agricultural Engineering, Royal University of Agriculture, Phnom Penh, Cambodia
Email: llytour@rua.edu.kh

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

BUNTHAN NGO
Royal University of Agriculture, Phnom Penh, Cambodia

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

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

CHANMAKARA MEAN
Faculty of Agricultural Engineering, Royal University of Agriculture, Phnom Penh, Cambodia

BART FREDERIKS
United Nations Industrial Development Organization, Vienna, Austria
Received 30 January 2020

Accepted 30 November 2020(*Corresponding Author)

Abstract Biogas systems are being applied at commercial pig farms and at starch processing
plants to manage their wastes and produce biogas for generating electricity or heat for on-siteuse. The installation numbers are increasing in Cambodia. The data on potential biogas
production quantity from different feedstocks as well as on biogas quality are required todesign the biogas systems. The purposes of this study was to determine biogas production
and biogas quality from dairy cow manure produced in pilot digesters, and to analyze thevariation in biogas production and quality during the year of 2019 and 2020. Pilot biodigesters were installed at the Biogas Technology and Information Center, a research unit
located in the Royal University of Agriculture, to obtain these data, since it is easier to do theexperiments with the pilot digesters than that with commercial ones. The experiments wereconducted during the year of 2019. In the experiments, 3 identical floating drum bio-digesters
were used. Each bio-digester has 1 m3 of volume and has been supplied mixture of 5-10 kg
of fresh manure from dairy cattle with 5-10 liters of water every day. The daily biogas
production quantity was recorded using a gas flow meter attached to the outlet of each biodigester; also the gas quality, such as methane, carbon dioxide, oxygen, and hydrogen sulfide
was measured using a portable biogas analyzer. The average rate of biogas production wasaround 37 liters of biogas per kg of wet manure. Average percentage of methane was around52%, and average concentration of hydrogen sulfide varied from around 390 ppm to 604 ppm.
These two parameters are the main indicators of biogas quality.
Keywords biogas, floating drum digester, cow manure, methane, hydrogen sulfide

INTRODUCTION
Global warming is the worldwide concern which is caused by greenhouse gas emissions. In
Cambodia, methane is a major greenhouse gas from animal production. Ministry of EnvironmentⒸ ISERD

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(2002) projected that methane emission from domestic livestock would be 545 Gg in 2020 compared
to 303 Gg from rice production, 2 Gg from grassland burning, and 5 Gg from agricultural residue
burning.
Recently in Cambodia, animal production has increased in all kinds of animals, especiallycommercial farms. In 2017, there were 83 commercial cattle farms, 653 pig farms with total numberof cattle and pig 20,363 heads, and 742,771 heads, respectively (MAFF, 2018a). According to Prakas
no. 549 of the Ministry of Agriculture, Forestry and Fisheries issued on December 12, 2018, allcommercial animal farms are required to manage their waste properly, especially using biogas
systems (MAFF, 2018)
Currently, some commercial farms and agro-processing plants have already installed biogas
plants to treat their waste and convert biogas to electricity for use on farms. To design biogas systems,
data on potential biogas production and quality from various feedstocks are required. These data are
available in other countries but not in Cambodia. To obtain these data in local condition, the use ofpilot digester is more appropriate since it is difficult to do on commercial biogas systems.
OBJECTIVE
The objectives of this study were (1) to determine biogas production and quality from dairy cow
manure by pilot digesters and (2) to analyze the variation in biogas production and quality during theyear of 2019 and 2020.
METHODOLOGY
Experimental Procedure
The experiment was conducted in 2019 and early 2020. Fresh cow manure was collected from dairy
cattle farm located on the campus of the Royal University of Agriculture. The ratio of manure towater was 1:1 to bring down the percentage of DM to around 10% in the mixture (Farouk et al.,2017). The mixture was thoroughly mixed and solid pieces of grass were removed before feeding
into the digesters to avoid sludge build up in the digesters. Daily manure used was 5kg/day or
10kg/day (fresh manure). At the beginning feeding rate of 5kg/day was used to start up the digester
and then was increased to 10kg/day. Ground water was used to mix with the manure.
Table 1 Amount of feedstock and water used
Digester

Mass of Water(liter)5 to 10Mix Ratio

RemarkDigester 1

Mass of Feedstock(kg)
5 to 10

1:1- 25 February to 11 March 2019,8kg/day of cow manure used
- 12 March to 29 July 2019, 10kg/day ofcow manure used
- 30 July 2019 to 31 January 2020,
5kg/day of cow manure used

Digester 2
Digester 3

10
10

10
10

1:1
1:1

Three floating drum biodigesters of identical design were used, see Fig. 1. This design was
selected because it would ease the modification of the digester for various experiments. It is equippedwith two sampling pipes on the sides of the digester from which substrate can be extracted foranalysis. Each biodigester has a total volume of 1m3. The hydraulic retention time was around 47
days, which depends on daily feeding rate of 5 kg or 10 kg, to ensure complete anaerobic digestionof the feedstock.
The duration of data collection was shown in Table 2. Digester 1 was started up in December
2018 and started to produce stable biogas in February 2019 and the daily biogas production wasrecorded. It took longer than 1 month before the digester started to produce biogas. After the low
biogas production was observed for Digester 1, it was opened in September 2019 to make sure thatⒸ ISERD

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there was no sludge building up in the digester. The digester 1 was restarted up again and began
producing biogas in October 2019. Digester 2 and Digester 3 was completed the construction andstarted up in July 2019. During long holidays such as Cambodian New Year in April and Pchum Ben
in September and Water Festival in November, data was not collected daily.

(a)

(b)
Fig. 1 Drawing of the pilot digester (a) side view (b) top view
From July to early August 2019, the biogas composition was measured once every two weeks.
It was done daily since late August 2019 when the air injection experiment was conducted on
Digester 2 to remove H2S.
Daily biogas production was measured by using gas counter which was attached to the outlet
end of the pipe. To avoid direct emission of methane into the atmosphere, it was burned by using abiogas stove after passing through the gas counter.
For the quality of the biogas produced, contents of methane, carbon dioxide, oxygen, andhydrogen sulfide were measured using a portable gas analyzer. The gas analyzer, Geotech Biogas
5000, was regularly calibrated to ensure its accuracy in measuring. At the beginning, the biogas
quality was measured weekly. Later on, it was measured daily since there was a need to test hydrogensulfide removal using air injection into gas holder of the digesters. The content of hydrogen sulfide
before and after the air injection need to be measured daily.
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Table 2 Duration of Data Collection
DigesterDigester 1

Duration of data collection
February 2019 to January 2020

Digester 2
Digester 3

July 2019 to January 2020
July 2019 to January 2020

Remark-In September 2019, the digester was opened since thelow biogas production was observed. After new startup,
the digester started produce biogas in October 2019.
-24 February to 11 March 2019, 8kg of manure per day

RESULTS AND DISCUSSION
Production of Biogas
During the monitoring, the average daily biogas production of digester 1, digester 2, and digester 3
were 238 L/day, 426 L/day, and 371 L/day, respectively. The average daily biogas production of thedigester 1 was the lowest since it was fed mostly only 5 kg of cow manure per day. The average daily
biogas production of digester 1 was only 71 L/day in February 2019. At that time, it was the
beginning of biogas production after it was started up in December 2018. The daily biogas productionof digester 1 and digester 2 were similar. The two digesters were constructed at the same time andfed 10 kg of cow manure daily. The fluctuation of average biogas production in each month may
have been caused by quality of animal feed and weather conditions. Matos et al. (2017) reported thatbiogas production potential from dairy cattle manure raised under organic production system is lower
than that of the conventional one which supplement commercial feed in the animal diet. Daily biogas
production is higher in summer than in winter as reported by Choudhury et al. (2019) during
evaluation of hydrogen sulfide scrubbing systems on two US dairy farms.
Table 3 Average daily biogas production of each digester (L/day)Digester 1
Month
Jan-19Feb-19Mar-19Apr-19
May-19Jun-19Jul-19Aug-19Sep-19Oct-19
Nov-19Dec-19Jan-20
Average

Digester 2

Avg(L/day)Min(L/day)Max(L/day)Std(L/day)

71
159
290
253
250
251
192

55
67
251
184
152
178
133

90
223
512
300
302
316
596

15
42
77
25
34
33
92

411
199
179
204
223

175
66
24
98

652
549
367
350

133
123
80
71

Digester 3

Avg(L/day)Min(L/day)Max(L/day)Std(L/day)Avg(L/day)Min(L/day)Max(Lday)

Std(L/day)

467
466
375
453
409
390
423
426

417
158
104
276
146
126
227

523
544
500
599
494
497
719

38
68
99
70
73
107
108

428
354
375
416
302
306
415
371

200
123
104
259
227
176
299

517
501
500
579
419
429
664

125
101
99
80
52
76
79

Fig. 2 Average daily biogas production per kg of wet manure (L/kg)Ⓒ ISERD

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Average daily biogas productions per kg of wet manure were 33 L/kg, 42 L/kg, and 36 L/kg indigester 1, digester 2, and digester 3, respectively; see Fig. 2. The mean biogas production of the threedigesters was 37 L/kg of fresh manure. After opening for checking in August 2019, the digester was
restarted and began to produce biogas in early October 2019. In October 2019, the rate of biogas
production was highest, around 80 L/kg of wet manure, due to the change of feedstock from cow to pig
manure which yield higher biogas production rate from the same mass. Aremu and Agarry (2012)
reported a little higher biogas production from pig manure than cow manure in Lithuania. Matulaitis(2015) found higher methane content in biogas produced from pig manure than from cattle one.
Quality of Biogas
Table 4 Biogas composition
Digester 1

Digester 2

Digester 3

Month

CH4
(%)

CO2
(%)

O2
(%)

H2S
(ppm)

Bal
(%)

CH4
(%)

CO2
(%)

O2
(%)

H2S
(ppm)

Bal
(%)

CH4
(%)

CO2
(%)

O2
(%)

H2S
(ppm)

Bal
(%)

Jul-19

48.8

35.0

1.1

410.5

14.6

50.7

35.3

0.3

446.5

13.8

50.9

35.6

0.2

503.0

13.4

Aug-19

48.2

36.2

0.6

410.0

14.6

51.2

38.3

0.3

273.1

10.1

51.3

38.6

0.3

265.4

10.1

51.1

41.6

0.4

115.6

6.1

51.1

41.6

0.4

115.6

6.1

Sep-19Oct-19

51.9

38.4

0.1

751.7

9.7

49.4

40.2

0.2

169.7

10.2

49.0

39.0

2.0

242.6

9.9

Nov-19

52.5

39.3

0.1

692.4

8.1

50.0

40.6

0.1

299.6

9.3

50.4

41.3

0.1

584.6

8.2

Dec-19

55.4

42.2

0.2

722.0

2.2

54.9

41.9

0.1

740.3

3.1

54.6

41.3

0.0

936.1

2.3

Jan-20

54.3

43.3

0.1

637.5

2.8

53.2

42.4

0.2

693.3

4.2

53.8

43.3

0.1

897.5

2.7

Average

51.8

39.1

0.4

604.0

8.7

51.5

40.0

0.2

391.2

8.1

51.6

40.1

0.4

506.4

7.5

The average percentage of methane in digester 1, digester 2, and digester 3 were 51.8%, 51.5%,
and 51.6% respectively; see Table 4. Abubakar and Ismail (2012) reported that average methane inbiogas from cow dung from slaughterhouse in Malaysia was 47% which is similar to these results.
Choudhury et al. (2019) reported average methane content of 64.1±0.2% in biogas of US dairy farms.
Methane content fluctuates according to digester conditions and quality of feedstock. Average
percentages of carbon dioxide in the three digesters were around 40%, while average percentage ofoxygen was less than 1%. The average hydrogen sulfide varied from around 390 ppm to 604 ppm.
The average highest concentration of 936.1 ppm was in the digester 3 in December 2019. Meanhydrogen sulfide in biogas from dairy farms in the US was 450±42 ppm (Choudhury et al., 2019). It
is suitable for use with gas heating boiler and combined heat and power (CHP) systems (Allegue andHinge, 2014; Petersson and Wellinger, 2009). To use with engine, it is recommended that hydrogensulfide should be reduced to 100 ppm to 250 ppm (Bioclean, 2020).
CONCLUSION
The average daily biogas production of the pilot digesters, each with 1m 3 working volume, varied
from 223 L/day to 426 L/day when feeding with 5 kg to 10 kg of cow manure per day and mixed
with water using 1:1 ratio. The average rate of daily biogas production was around 37 L/kg of wet
cow manure.
The biogas contained on average 51.6% methane, 39.7% carbon dioxide, 0.3% oxygen, 500ppm
hydrogen sulfide, and other gases was around 8.1%. Average percentage of methane was lower thanthe one reported in US dairy farms, which was around 64%. However it was similar to the one in
Malaysia which was around 47%. The average hydrogen sulfide varied from around 390 ppm to 604
ppm. It is suitable to use with gas heating boiler and combined heat and power (CHP) systems.
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However, it is not suitable to use with gas engine without pre-treatment system which is used toreduce hydrogen sulfide concentration in the biogas to 100 ppm to 250 ppm.
ACKNOWLEDGEMENT
This paper is made possible by funding from U IDO through the project entitled “Reduction of
GHG emission through promotion of commercial biogas plants”, which is jointly implemented by
the Ministry of Environment (MOE), the Ministry of Agriculture, Forestry and Fisheries (MAFF)
and UNIDO with financial support from the Global Environment Facility (GEF).
REFERENCES
Abubakar, B.S.U.I. and Ismail, N. 2012. Anaerobic digestion of cow dung for biogas production. ARPN
Journal of Engineering and Applied Sciences, 7 (2), 169-172.
Aremu, M.O. and Agarry, S.E. 2012. Comparison of biogas production from cow dung and pig dung undermesophilic condition. International Refereed Journal of Engineering and Science (IRJES), 1 (4), 16-21.
Allegue, L.B. and Hinge, J. 2014. Biogas upgrading evaluation of methods for H2S removal. Danish
Technology Institute, 31, Denmark.
Bioclean. 2020. Why it is necessary to reduce the H2S? Retrived from https://www.biogasclean.com/h2s.aspx.
Choudhury, A., Shelford, T., Felton, G., Gooch, C. and Lansing, S. 2019. Evaluation of hydrogen sulfide
scrubbing systems for anaerobic digesters on two U.S. dairy farms. Energies, 12 (24), 4605.
Farouk, H., Lang, A., Bakheet, K., Salah, M., Elobaid, M. and Omer, A. 2017. Design of a household anaerobic
digester for rural areas in Sudan. International Journal of Energy Applications and Technologies, 4 (2), 5363.
Matos, C.F., Paes, J.L., Pinheiro, É.F.M. and De Campos, D.V.B. 2017. Biogas production from dairy cattle
manure, under organic and conventional production systems. Engenharia Agrícola, 37 (6), 1081-1090.
https://dx.doi.org/10.1590/1809-4430-eng.agric.v37n6p1081-1090/2017
Matulaitis, R., Juškienė, V. and Juška, R. 2015. Measurement of methane production from pig and cattle
manure in Lithuania. Zemdirbyste-Agriculture, 102, 1, 103-110.
Ministry of Agriculture, Forestry and Fisheries. 2018a. Annual report on achievements of the Ministry ofAgriculture, Forestry and Fisheries in 2017-2018 and future plan for 2018-2019. Phnom Penh, Cambodia.
Ministry of Agriculture, Forestry and Fisheries. 2018b. Classification, technical standard, procedure forlicensing animal production and breeding. Prakas No. 549, Phnom Penh, Cambodia.
Ministry of Environment. 2002. National communication of Cambodia. Phnom Penh, Cambodia.
Petersson, A. and Wellinger, A. 2009. Biogas upgrading technologies, Developments and innovations, IEA
Bioenergy, Paris, France.

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Research article
erd

Efficiency Evaluation of Solar Pumping System for Wadi
Agriculture in Djibouti
MAKOTO SHINOZAKI
Graduate School of Agriculture, Tokyo University of Agriculture,
VSN, Inc., Minato-ku, Tokyo, Japan
Email: wt2bp24955@gmail.com

SAWAHIKO SHIMADA*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Japan
Email: shima123@nodai.ac.jp

AYAKO SEKIYAMA
Faculty of Regional Environment Science, Tokyo University of Agriculture, JapanKIYOSHI TAJIMA
Faculty of Regional Environment Science, Tokyo University of Agriculture, JapanHASSAN ALI BARKAD
Institute of Industrial Technology, University of Djibouti, Djibouti
Received 11 Septem 2020

Accepted 30 November 2020(*Corresponding Author)

Abstract Crop cultivation in Djibouti is mainly done by irrigation agriculture obtaining
groundwater from wadi aquifer. The decreasing in the efficiency of solar power generation
system due to panel-on-dust is reported to be the issue in terms of energy loss in pumping up
water. In this paper, the effect of dust deposition for solar pumping system was evaluated at
wadi agriculture farm in Dikhil, Djibouti. The amount of panel-on-dust was measured to be
1.88 and 2.1 g/m2 in cooler season (dry deposition) and in hot season (wet deposition),
respectively. Clearance of the panel-on-dust resulted a decline in the output power ofphotovoltaic panel due to the rise in panel surface temperature in January (cooler season),whilst the output power increased in September (hot season) when the panel surface
temperature was relatively higher. The conversion efficiency of the photovoltaic power
generation was calculated to be about 5 - 6% lower in September than in January. The wholeconversion efficiency of solar pumping system was estimated to be about 2%. Since the ideal
conversion efficiency was calculated as 6.76%, the gap from observed value of about 4.5%
can be implied by suppressing water leakages from the system in pumping process.
Keywords Djibouti, panel-on-dust, photovoltaic panel, wadi agriculture

INTRODUCTION
The Republic of Djibouti, Northeastern Africa, locates under high temperature and low-rainfall
climate environment. Most of the land surface is dominated by barren land (67-89%; Shimada et al.,2006) and the rainwater easily run off from the ground surface through wadi, ephemeral riverbed.
Due to this harsh natural environment, agricultural activity is very difficult. In Djibouti, groundwateris pumped up to be used since enough amount of water cannot be collected from rainwater for
agriculture. In the arid land under low-latitude regions such as Djibouti, abundant solar radiation isavailable, hence solar power generation has a potential for the pumping system. However, initialexpense for installation of solar power system costs relatively higher than that of engine system. For
this reason, engine systems are the most adopted cases for wadi agriculture, although the runningcost exceeds in the long run for the engine pumps and causes pressure on management. The
Government of Djibouti pronounces the use of renewable energy as a great important issue for theⒸ ISERD

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management of sustainable water resources to enhance the agricultural productivity. Therefore, it isimportant to establish an optimal method for operating solar power generation system in terms of
cost and efficiency. Previous studies analyzed the cost of a pumping system using photovoltaic panel
in wadi agricultural farm in Djibouti, a method for estimating an appropriate scale of pumping system(Tajima et al., 2012; 2014). However, in arid areas such as Djibouti, dust tends to accumulate on
photovoltaic panels, and the dust accumulation normally reduces its output power (Sulaiman et al.,2011; Ghazi et al., 2014; Maghami et al., 2016; Daher et al., 2018). When introducing a PV system
for agriculture, in arid environment like Djibouti, it is necessary to consider the effects of dust
accumulation on photovoltaic panel. However, only a few studies analyzed on this effect andevaluated quantitively on photovoltaic pump in arid area like Djibouti (e.g., Tajima et al., 2012; 2014;
Aden et al., 2009). In the current paper, we investigated one whole pumping system of wadi
agricultural farm, where photovoltaic power generation is introduced as groundwater pumping
system, in Dhikhil, Djibouti, in order to evaluate the efficiency of the system including the effect of
dust deposition on photovoltaic panel.
METHODOLOGY
The target farmland located in Dikhil city (11.08863° , 42.40089°E) (Fig. 2). The configuration of
the solar pumping system used in the farm was as follows. LORE TZ: PS1800, SOLARWORLD:
SW80 poly R A: 80 W x 18 sheets. The solar array installation inclination angle was 11°, theazimuth angle was 130° (i.e., southeast), and the area of the array was about 12 m2.

Fig. 1 Location of the study site in Djibouti

Fig. 2 Overview of the target farmland in Dikhil

Overview of solar pumping system is shown in Fig. 3, and agricultural system is shown in Fig.
4. During daytime, the farmers use solar pumping system to store groundwater into reservoir tank(about 100 m3 storage). After around sunset, they switch to engine pumping system to pump up thegroundwater from the well. The farmers use all the water needed for the farm management, such as
irrigation, livestock, and others.

Fig. 3 Overview of solar pumping system inthe target farmland

Fig. 4 Agriculture-livestock material cycling
scheme in the target farmland

Survey was conducted in 2 seasons, i.e., cooler season (December 29, 2018 - January 14, 2019),
and hot season (September 1, 2019 - September 30, 2019). Table 1 shows the items and periods ofthe data measurements, and Fig. 5 shows the overview of the measuring equipment in the farmland.
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Solar pumping system consists of photovoltaic system and pump, which converts the electric power
into the potential energy of water. However, the system has some loss of efficiency in the process ofenergy conversion (Fig. 6). The output electric power of the solar pumping system was measured by
the multiplication of current and voltage. The values were compared before and after cleaning thepanel-on-dust. The output efficiency was evaluated by comparing the changes in the output of thephotovoltaic system with the output of the pumping system. The output efficiencies regarding panelon-dust and panel surface temperature were also evaluated.
Table 1 Items and periods of data measurements

Fig. 5 Overview of the measuring equipmentin the target farmland

Fig. 6 The flow and loss of energy in thefarm solar pumping system

RESULTS AND DISCUSSION
Cleaning of panel-on-dust was conducted on January 6, September 13 and 24, for the cooler and the
hot season experiments, respectively. Fig. 7 shows the schedule and measured dry weights on
cleaning of panel-on-dust. The panel-on-dust seems to occur more in September than in January.
Dust accumulation for cooler season was observed to be dry deposition and weighed 1.88 g/m2 indry mass, while weighed more than 2.1 g/m2 in dry mass and seemed as wet deposition due to rainfall
events for hot season.
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Fig. 7 Results of panel-on-dust measurement
Fig. 8 shows comparison of the output electric power of the photovoltaic system before and after
clearance of panel-on-dust in January and September. As a result, the effectiveness of panel cleaningon output power was negative in January (75%), while positive in September (140%). This result
indicates that clearing of the dust on the solar panel can cause decrement of photovoltaic efficiency
in cooler season (January). This efficiency loss can be explained by the reason that effect of risen
temperature of the photovoltaic panel surpassed the increase in input solar irradiance from theclearance of panel-on-dust.

Fig. 8 Output power with solar irradiance (horizontal and on panel) before andafter cleaning panel-on-dust (Left: cooler season, Right: hot season)

Fig. 9 Surface temperature of photovoltaic panel, air temperature and power loss
before and after cleaning panel-on-dust (Left: cooler season, Right: hot season)
Fig. 9 shows panel surface temperature in January and September, and the output power loss
due to the panel surface temperature. The maximum panel surface temperatures in January and
September were 60.8℃ and 71.9℃, respectively. The theoretical daily power loss due to high panel
temperature calculated from the photovoltaic panel specification (-0.48% ℃-1) was 11-13%, and 1316%, in January and September, respectively. From the above results, the power loss from the highpanel temperature is more remarkable in the hot season (September) than in cooler season (January).
Clearance of panel-on-dust in the hot season can gain the efficiency of the output power, although
theoretical energy loss from high panel temperature is relatively higher.
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Table 2 shows calculated pumped water amount in January and September. Fig. 10 shows input
and output energy of whole solar pumping system. Input energy is the solar radiation intensity
received by the panel. The input energy was observed to be greater in January than in September.
Ideal efficiency was estimated as 6.76% (Fig. 6), however, the efficiency of whole pumping system
was calculated to be between 2.1 - 2.4% (Fig. 10). The reason for this gap in efficiency might cause
mainly in the water loss, such as leakage from the water pipe.
Table 2 Output capacity of water pumping system before and after cleaning panel-on-dust

Fig.10 Input and Output energy of daily integrated energy before and after
cleaning panel-on-dust (Left: cooler season, Right: hot season)
CONCLUSION
The panel-on-dust effects on photovoltaic efficiency for wadi agriculture solar pumping system in
Djibouti was examined. The efficiency decline by the clearance of panel-on-dust in cooler season
was discovered in this paper for the first time. This energy output loss was implied by the effect ofrisen temperature of the photovoltaic panel from the clearance of panel-on-dust. However, theclearance of panel-on-dust in the hot season can gain the efficiency of the output power.
The whole conversion efficiency of solar pumping system of wadi agriculture in Djibouti wasalso evaluated in this study. It was estimated to be slightly above 2%, although the ideal conversion
efficiency was calculated as 6.76%, which gap can be caused by the water loss in the pumping
process.
REFERENCES
Aden, A.S., Bryan, P., Matthew, B. and Anna, P. 2009. Irrigated agriculture in Djibouti: An economic andphysical analysis of irrigation systems based on the Aden Atteyeh Sougal Family farm. FAO Family
Farming Knowledge Platform.
Daher, D.H., Gaillard, L, Amara, M. and Menezo, C. 2018. Impact of tropical desert maritime climate on theperformance of a PV grid-connected power plant. Renewable Energy, 125, 729-737.
Ghazi, A., Sayigh, A. and Ip, K. 2014. Dust effect on flat surfaces, A review paper. Renewable and Sustainable
Energy Reviews. 33. 742-751.
Maghami, M.R., Hizam, H., Gomes, C., Radzi, M.A., Rezada, M. and Hajighorbani, S. 2016. Power loss due
to soiling on solar panel: A review. Renewable and Sustainable Energy Reviews, 59, 1307-1316.
Shimada, S., Toyoda, H., Takahashi, S., Tajima, K. and Takahashi, S. 2006. Monitoring the land surfacechanges of Djibouti using LANDSAT images. Journal of Arid Land Studies, 15 (4), 387-390.
Sulaiman, S.A., Hussain, H.H., Nik Leh, N.S.H. and Razali, M.S.I. 2011. Effects of dust on the performanceof PV panels. Engineering and Technology International Journal of Mechanical and MechatronicsⒸ ISERD

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Engineering, 5 (10), 2021-2026
Tajima, K., Sanada, A., Tachibana, R. and Watanabe, F. 2014. Effectiveness of solar pumping system in thewadi agriculture in Northern East Africa. Journal of Arid Land Studies, 23 (4), 179-183.
Tajima, K., Suzuki, S., Shinohara, T., Sanada, A. and Watanabe, F. 2012. Application example of the small
solar pumping system in the Djiboutian wadi agriculture. Journal of Arid Land Studies, 22 (1), 337-340.

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Research article
erd

Growth and Yield Performance of Different Potato Varieties
under Upland Condition in Cambodia
KHEANG SONG
Graduate School, Royal University of Agriculture, Phnom Penh, Cambodia

SOPHAL VAR*
Faculty of Agronomy, Royal University of Agriculture, Phnom Penh, Cambodia
Email:var.sophal@gmail.com

SAVRY POENG
Faculty of Agronomy, Royal University of Agriculture, Phnom Penh, Cambodia

KIMYEE ORNG
Faculty of Agronomy, Royal University of Agriculture, Phnom Penh, Cambodia

CHANTHA SENG
Faculty of Agronomy, Royal University of Agriculture, Phnom Penh, Cambodia

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

SIRANET ROEUN
Faculty of Agronomy, Royal University of Agriculture, Phnom Penh, Cambodia

HONG CHEANG
Faculty of Agronomy, Royal University of Agriculture, Phnom Penh, Cambodia
Received 12 March 2020

Accepted 1 December 2020(*Corresponding Author)

Abstract In Cambodia, potato is imported. Currently, potato has the fourth largest productionin the world cultivated in many countries even in semi-arid and tropical countries. Numerous
new and improved varieties were developed to sustain and maintain production systems.
Thus, performance evaluation of these varieties in Cambodia condition is important toimprove potato production in the country. The experiment was conducted from December
2016 to March 2017 by testing 8 different imported varieties (Tornado, Corodana, Georgina,
Madeira, Jelly, Julkinka, Red fantasy and Sorentina) under upland climate of Cambodia. The
result showed that all varieties showed similar performance in terms of growth, but different
in yield components and yield. Tornado variety was most adapted and productive varieties
with an average yield of 23ton ha-1 followed by Madeira (19 ton ha-1) while Red fantasy had
the lowest production among the tested varieties under upland environment in Cambodia.
Keywords: Tornado, Madeira, Mondulkiri, upland, Cambodia.

INTRODUCTION
Potato, Solanum tuberusom L., is considered as an important source of carbohydrate and plays a keyrole for food security in many develop and developing countries (Scott et al, 2000). Thus, potato iscurrently the fourth largest production crop next after rice, corn and wheat (FAOSTAT, 2006). At
the present, potato is fast adapted and grown throughout the continents, though the crop prefers coolclimate (18 oC without chilled) follow by warm environment (Havetkort and Struik, 2015). Optimum
yield, at least 20 ton per hectare, has been attained in most temperate regions with averagetemperature of around 18-20oC. High temperature, in the face of climate change, is one of limitingⒸ ISERD

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factors affecting potato production which is commonly found in most tropic and subtropics countries.
In Cambodia, where the average daily temperature exceeds higher than 28 oC, fresh potato isimported mostly from Vietnam, Thailand and China. A number of production problems that accountfor such low yield have been identified. The major concerning of low and poor production were lackof well adapted cultivars, unavailability and high cost of seed tubers, inappropriate agronomic
practices, diseases, insect pests, inadequate storage, transportation and marketing facilities (MAFF,
2016). As potato production continuously expand throughout the world, lots of new improved
varieties have been bred and improved for different regions and countries. In connection with climatechange, several technology package and new cultivar are highly considered as keys to maintain the
production and prevent potato farming from exposed to the threat. Thus, new cultivars that are more
resilient to high temperatures have been developed (Monneveux et al., 2014). Some of those varieties
were mainly breed in tropical countries (Muthoni and Kabira, 2015).
OBJECTIVE
The study was conducted to understand performance of different potato varieties planted in
Mondulkiri province, Cambodia.
METHODOLOGY
Experiment was carried out under field condition from December 2017 to March 2018 at Mondulkiri
province (12o28’27” , 107o12’33” E). The site was 710 meters above the sea level with average of
26 to 30 oC and relative humidity of 70-90% upon the research conducted. Chemical and physical of
the field was described in Table 1. The trial was layout in randomize complete block design with 4
replications. The treatment consisted of eight different imported potato varieties namely Tornado(IMP Potato group limited, Ireland) Coronada, Madeira, Goergina, Jelly, Red Fantasy, Jelly, Julinka,
Sorentina (Europlant International, Germany).
Table 1 Soil physical and chemical properties analysis of experiment site
Soil Texture

EC

pH

P
ppm

K
cmolc kg-1

N
%

SOM
%

CEC
cmolc kg-1

Clay

Silt

Sand

38.0

4.20

0.1

0.42

0.29

5.07

72.4

22.3

35.3

42.4

Class
Clay
Loam

Source; Soil Laboratory, Faculty of Agronomy, Royal University of Agriculture, Cambodia

Trail was planted at density of 4.8 plants m-2 in plot of 6 meters long. Spacing of 70 cm between
row and 40 cm between plant. Each plot was fertilized with 80 kg N ha-1, 80 kg P2O5 ha-1 and 150 kg
K2O ha-1 at planting date. Addition of 40 kg N ha-1 and 100 kg K2O were applied at ridging (45 days
after planting). Weeds and pathogens were controlled chemically at the manufacturer’s
recommended rate to prevent biotics damage. The plots were surface irrigated every 3 days interval.
Plant plants were harvested at 115 days from sowing. Growth and yield parameters were recorded.
Plant height was recorded at flowering stage while number of tuber per plant, weight per tuber,weight per plant and marketable yield were measure at harvest.
RESULTS AND DISCUSSION
The result showed that all of the eight varieties reached its normal height and statistically similar to
one another (Pvalue<0.05) (Fig. 1). Lizana et al., (2017) explained that physical changing would notobserved when the potato was cultivated under similar or little higher temperature (28 oC) which was
about 30-47cm tall. The author also emphasizes that external factors such as high temperature(greater than 28 oC) would cause the change of the plant height.

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Fig. 1 Plant height at flowering stage of eight varieties
All of yield parameters were observed statistically different (Pvalue>0.05). In terms of yiedcomponent, Madeira, Julinka and Jelly had the highest number of tuber compared to Coronada and
Red fantasy, but statistically similar to other three varieties (Fig. 2). Notably, the trial showed thatRed fantasy produced the lowest number of tubers (Fig.2). In addition, Red fantasy also produced
less weight per plant (less than 300 grams per plant) (Fig.3). However, similar result was recorded
for Sorentina variety. The highest tuber weight per plant was observed for Tornado variety which
could obtain about 700 grams followed by the second highest Madeira (about 600 grams per plant).
Other varieties like Coronada, Jelly, Julinka and Georgina was third and not significantly different
to one another (Fig.3).

Means within the figure followed by the same letter are not significantly different using LSD (0.05).

Fig. 2 Tuber produced per plant

Means within the figure followed by the same letter are not significantly different using LSD (0.05).

Fig. 3 Tuber produced per plantⒸ ISERD

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In particular, Tornado, white flesh and red skin color, attained the highest yield (23ton ha -1). It
was commendably that different potato varieties result vary response to different growing conditionand production system (Masengesho et al., 2012; Gairhe et al., 2017). Gairhe et al., (2017) suggested
that improved potato varieties had different response to different field condition such as altitude, soil
type and ambient temperature. Author had also claimed that in warm and hot climate countries, most
potato could grow well in upland rather than lowland areas, but not all improved varieties showedsimilar response or obtained higher yield.

Means within the figure followed by the same letter are not significantly different using LSD (0.05).

Fig. 4 Marketable yield obtain in the experiment
CONCLUSION
Our result suggested that all of the eight varieties had similar performance in terms of growth.
Majority of the tested varieties were less productive (less than 13 ton ha -1) which 20 percent lower
than the average of global yield. However, Tornado and Madeira showed outstanding performance.
Thus, Tornado, white flesh color and red skin, and Madeira, yellow flesh and skin color, were more
adapted and productive in Mondulkiri province, Cambodia. Despite the yield, most of potatoes
severely damage by diseases which literately susceptive for long-term production and suggested that
farmers need to purchase and used only certified seeds for the production. However, the price ofcertified seed would cost 3.00 USD/kg with that farmers need to invest 2,000 to 3,000 USD to hectare
cultivation. Thus, yield obtained should at least between 12 to 13 ton per hectare for economic benefit.
ACKNOWLEDGEMENTS
The authors would like to express his sincere thankfulness and appreciation to KOPIA Cambodia
Center (2016-KHM-03), assistance funds, the Europlant International for the seed, GIZ for technicaladvice, my assistant; selected farmers for supporting and encouragement, key informants andinformation; your mighty support being my greatest source of motivation and inspiration.
REFERENCES
FAO. 2016. FAO statistics database on the world wide web. Retrived from http://faostat3.fao.org/browse/Q/QC/S.
Gairhe, S., Guachan, D. and Timsina, K. 2017. Adoption of improved potato varieties in Nepal. Journal of
Nepal Agriculture Research Council, 3, 38-44. http://dx.doi.org/10.3126/jnarc.v3i1.17274
Haverkort, A.J. and Struik, P.C. 2015. Yield levels of potato crops: Recent achievements and future prospects.
Field Crops Res., 182, 76-85. http://dx.doi.org/10.1016/j. fcr.2015.06.002.
Lizana, C.X., Avila, A., Tolaba, A. and Martinez, J.P. 2017. Field response of potato to increased temperatureduring tuber bulking: Projection for climate change scenarios at high yield environments of Southern Chile.
Agricultural and Forest Meteorology, 239, 192-201.
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Masengesho, J., Nshimiyimana, J.C., Senkesha, N. and Sallah, Y.K. 2012. Performance of Irish potato varieties
under aeroponic condition in Rwanda. Rwanda Journal, 28. http://dx.doi.org/10.4314/rj.v28i1.7.
Ministry of Agriculture, Forestry and Fisheries. 2016. Country report: Agriculture current and future prospects.
Ministry of Agriculture Forestry and Fisheries, 35, 65-67, Phnom Penh, Cambodia.
Monneveux, P., Ramírez, D.A., Awais Khan, M., Raymundo, R.M., Loayza, H. and Quiroz, R., 2014. Drought
and heat tolerance evaluation in potato (Solanum tuberosum L.). Potato Res., 57, 225-247, http://dx.doi.
org/10.1007/s11540-014-9263-3.
Muthoni, J. and Kabira, J.N. 2015. Potato production in the hot tropical areas of Africa: Progress made inbreeding for heat tolerance. Journal of Agriculture Science, 7, 220-227.
Scott, G.J., Rosegrant, M.W. and Ringler, C. 2000. Global projections for root and tuber crops to the year 2020.
Food Policy, 25, 561-597. http://dx.doi.org/10.1016/ S0306-9192(99)00087-1.

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Research article
erd

Reaction of Different Rice Varieties to Bacterial Blight
HAN SU YIN*
Yezin Agricultural University, Yezin, Nay Pyi Taw, Myanmar
Email: hsyyau@gmail.com

SEINT SAN AYE
Yezin Agricultural University, Yezin, Nay Pyi Taw, Myanmar

HTAY HTAY OO
Yezin Agricultural University, Yezin, Nay Pyi Taw, Myanmar

YI YI MON
Yezin Agricultural University, Yezin, Nay Pyi Taw, Myanmar

TIN AYE AYE NAING
Yezin Agricultural University, Yezin, Nay Pyi Taw, Myanmar
Received 20 January 2020

Accepted 5 December 2020(*Corresponding Author)

Abstract Rice is the major food crop in Myanmar and bacterial blight is one of thedevastating diseases affecting production. In this study, 37 local rice varieties and 41 ricelines were tested at Yezin Agricultural University, Myanmar, to three different isolates of
Xanthomonas oryzae pv. oryzae to evaluate the resistance levels of these different rice
varieties. The three bacterial isolates used in this experiment were collected from Zeyathiri,
Zabuthiri and Pyinmana townships in Nay Pyi Taw Union Territory. At maximum tillering
stage, the uppermost fully expanded leaves were inoculated by the clipping method. Three
weeks after the inoculation, the percent leaf area of the inoculated leaves was visuallyestimated and the disease reaction of the rice varieties determined. The thirty-seven local rice
varieties were classified into seven groups, with this grouping based on the reaction patterns
to the three isolates. Group VII, which contained two varieties, Nga Sar Kay and Sinthukha,
was moderately resistant to Pyinmana isolate and moderately susceptible to the Zeyathiri and
Zabuthiri isolates. The rice varieties included in Group I to Group VI showed susceptible
reactions to testing with all three isolates. Among YAU rice lines tested, YAU-1211-71-1-1
exhibited moderate resistance to the Pyinmana isolate only. Apart from the line mentioned
above, all the other YAU rice lines, did not exhibit resistance reactions to the test isolates.
Nga Sar Kay, a local rice variety, has the potential to be used in the future rice breeding
programs and YAU-1211-71-1-1 is the promising one to be used in areas where rice bacterial
blight disease is prevalent.
Keywords bacterial blight, resistant varieties, rice, Xanthomonas oryzae pv. oryzae

INTRODUCTION
Rice (Oryza sativa L.) is the most widely eaten staple food crop, especially in Asia, and is consumed
by more than half the world’s population. Unfortunately, rice crops are threatened by a considerable
number of diseases (more than 40 diseases) of fungal, bacterial and viral origin, and these diminish
rice yields throughout the world (Singh et al., 2013). Among rice diseases, bacterial leaf blight (BLB)
caused by Xanthomonas oryzae pv. oryzae (Ishiyama) (Swings et al., 1990) is one of the mostdestructive and widespread diseases of rice. In Myanmar, bacterial blight is also one of the mostserious diseases present, and every year, its occurrence has been reported from the different rice
growing regions throughout the country (Lwin, 2006). Higher losses are common in tropical Asian
countries, such as Myanmar, because of the prevalence of virulent pathogen populations and theⒸ ISERD

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susceptibility of the high yielding cultivars in tropical area (Aye et al., 2007). Yield losses due to thedisease are estimated to range from 0.5% to 50% (Myint et al., 1983; Win, 2013).
Many control strategies, including various cultural practices, application of various chemicals
and systematic use of chemical fertilizers have been attempted in an effort to control bacterial blightdisease, but these management tactics have not been very effective. Although chemical control plays
an important part in an integrated disease management program, it has a detrimental effect on humanhealth and non-target, beneficial microorganisms. Non-systematic use of agricultural chemicals canalso contribute to the emergence of new races of the pathogen and ultimately prove a waste of money
for resource limited farmers. The most feasible, effective and economical way of controlling bacterial
blight in Myanmar, is the exploitation of the host plant resistance. Moreover, use of resistant varietiesis also compatible with other disease control methods. Although research on varietal resistance isconducted irregularly in Myanmar, varietal resistance is probably the most important area to focus
on for effective disease management.
OBJECTIVE
This study was conducted to evaluate the resistance levels of different rice varieties and lines to
Xanthomonas oryzae pv. oryzae.
METHODOLOGY
Test Varieties and Preparation of Plants
Thirty-five local rice varieties, and 41 YAU rice lines were used in this study. Manawthukha wasused as a ‘susceptible’ control and Sinthukha was used as a ‘resistance’ control variety. Seeds ofthese rice varieties were obtained from the Department of Plant Breeding, Physiology and Ecology,
Yezin Agricultural University. Firstly, rice seeds were sterilized in hot water at 56 ˚C for 15 minutes
and germination accomplished using the paper towel method. Germinated seeds were sown in 20 cm
× 20 cm plastic pots containing sterilized soil, and twenty- one day old seedlings of each of the test
varieties were transplanted individually in plastic pots, containing 3 kg of lowland soil, and thesewere watered as necessary. Fertilizer application was carried out according to the standard methodsof managing rice plants.
Bacterial Isolates
Three very virulent isolates (Isolate I, Isolate II and Isolate III which were collected from Zeyathiri,
Zabuthiri and Pyinmana townships in Nay Pyi Taw Union Territory) of Xanthomonas oryzae pv.
oryzae were used for inoculation in this experiment.
Inoculum Preparation and Inoculation
Isolates from preserved tubes were sub-cultured on peptone sucrose agar (PSA) (Tsuchiya et al.,1982) medium plates and incubated for two days. The bacterial suspension was prepared bysuspending the bacterial mass from PSA plates in sterilized distilled water and adjusted to 108 cfu/ml
using a Thermo Scientific Evolution 201 Uv-Visible Spectrophotometer. In order to distinguish the
inoculated isolates, plants in a pot were bundled into three groups by labelling with different coloredties (Aye et al., 2007). Inoculation was done at maximum tillering stage, by clipping the uppermost
fully expanded leaves of five tillers 2-3 cm from the leaf tips with a pre-sterilized pair of scissors,which were then dipped in the bacterial suspension (Kauffman et al., 1973).
Disease Assessment and Data AnalysisⒸ ISERD

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Percent leaf area infected on inoculated leaves were visually estimated 21 days after inoculation.
Disease reaction of the rice varieties to the bacterial isolates were determined based on the diseasescores (IRRI 1988) (Table 1).
Table 1 Standard Evaluation System for Rice (for bacterial blight) (IRRI, 1988)% Leaf area infected

Score scales

Description

1-5

1

R

6-12

3

MR

13-25

5

MS

26-50

7

S

>50
9
HS
R: Resistant, MR: Moderately resistant, MS: Moderately susceptible, S: Susceptible, HS: Highly susceptible

RESULTS AND DISCUSSION
Reaction of Myanmar Local Rice Varieties
Thirty-seven Myanmar local rice varieties were evaluated for their reaction to three isolates of
Xanthomonas oryzae pv. oryzae. Based on the reaction patterns to these three isolates, 37 rice
varieties were characterized into seven varietal groups, Group I-VII is shown in Table 2. Thirteen
Myanmar local rice varieties belonging to Group I were highly susceptible to Isolate I and Isolate II,
and susceptible to Isolate III. Group II consists of seven rice varieties, which showed moderate
susceptibility to Isolate III and were high susceptibility to Isolates I and Isolate II. In Group III, Khao
Phee Phan and Thiri Done Pathein were highly susceptible to Isolate I, susceptible to Isolate II andmoderately susceptible to Isolate III. Only one variety, Kauk Kyi Shan Ma, showed the same reaction(susceptible) to all three test isolates. Three varieties in Group V were susceptible to Isolate I, highly
susceptible to Isolate II and moderately susceptible to Isolate III. Bacterial isolates I, II and III werevirulent to all plants in Group VI, including the nine rice varieties which presented susceptible
reactions to Isolate I and II and moderately susceptible reactions to Isolate III. Two varieties, namely
Nga Sar Kay and Sinthukha, belonging to Group VII, exhibited a moderate resistance reaction to
Isolate III and a moderate susceptible reaction to Isolates I and II.
Reaction of Yezin Agricultural University (YAU) Rice Lines
Forty-one varieties of YAU’s promising rice lines were also tested for their response to these threeisolates of Xanthomonas oryzae pv. oryzae. According to disease severity, these YAU rice lines wereclassified into eight groups, Group I-VIII is shown in Table 3. Group I include only the Manawthukha
variety, which was highly susceptible to all test isolates. In Group II, three YAU lines showed highly
susceptible reactions to bacterial Isolates I and II and a susceptible reaction to Isolate III. The threerice lines included in Group III expressed highly susceptible reactions to Isolate II and susceptible
reactions to Isolates I and III. In Group IV, YAU-1201-90-2-2 showed the same reactions to Isolate
I and II as in Group III but it displayed a moderately susceptible reaction to Isolate III. The twelve
rice lines that belonged to Group V were susceptible to all test isolates. Group VI included nineteen
tested lines and they were susceptible to Isolates I and II and moderately susceptible to Isolate III.
Two rice lines in Group VII, YAU-1211-116-3-3 and YAU-1211-223-3-2, presented moderately
susceptible reactions to the three test isolates. The lowest disease severity values were found in thevarieties YAU-1211-71-1-1 and Sinthukha, which belong to Group VIII. Compared to other test
varieties, these rated as moderately resistant to Isolate III and moderately susceptible to Isolate I and II.
In the evaluation of the reaction of rice varieties, almost all of the local rice varieties showedsusceptible reactions to the three test isolates. Of the 37 Myanmar rice varieties, Nga Sar Kay and
Sinthukha, expressed a moderate resistance reaction to Isolate III (Pyinmana) only. This result
indicates that these varieties may harbor a gene resistant to Isolate III and so might be useful forⒸ ISERD

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further rice breeding program. In the present study, Sinthukha was moderately susceptible to two
isolates (Isolate I and II). Although Xa21 was used as a broad-spectrum resistance gene (Khush etal., 1990) in its breeding program, the Sinthukha variety which contains the Xa21 gene, showed amoderately susceptible reaction to two isolates. A similar result was observed by Swamy et al.,(2006) who reported that Pusa Basmati 1 and its transgenic derivative PB-Xa21 were much more
susceptible to virulent Mxo isolates than IRBB 21. The present finding is in conformity with theresults of (Myint, 2008) and (Maung, 2014) who reported that Sinthukha was susceptible to a test
isolate which showed a resistant reaction to IRBB 21.
Table 2 Reaction of thirty-seven rice varieties to three most virulent isolates of Xanthomonas
oryzae pv. oryzae
Sr. No.

Name of local varieties

Disease reaction and Disease severity (%) to bacterial isolate
Isolate I
Isolate II
Isolate III( Zeyathiri)( Zabuthiri)(Pyinmana)

Group I
1
Boke Thwin Phyu
HS (72)HS (84)
S (43)
2
Khao LinHS (59)HS (56)
S (26)
3
Muyinn Saba
HS (63)HS (72)S (30)
4
Yoe WaHS (53)HS (63)S (29)
5
V15
HS (60)HS (71)S (30)
6
Bu ToylHS (56)
HS (72)S (30)
7
Khun Na Yar Po
HS (63)HS (67)
S (27)
8
Sa WanaHS (66)HS (90)S (28)
9
Japan Ni
HS (73)HS (66)
S (41)
10
Khao Mae Pan
HS (59)HS (70)S (29)
11
Lone Phyu
HS (55)HS (84)S (30)
12
Sa Bong Thaw
HS (72)HS (86)
S (31)
13
Manawthukha
HS (73)HS (71)S (49)
Group II
14
Ant Paw
HS (59)HS (64)
MS (24)15
Khao Pi Paung
HS (55)HS (54)
MS (24)
16
Thu Kha-2
HS (55)HS (67)MS (24)17
Tayote Hmwe
HS (59)HS (67)MS (25)18
Shal Thu Kha
HS (54)HS (66)
MS (24)19
Aye Yar Padae Thar
HS (54)HS (67)MS (24)20
Shwe Thwe Yin
HS (51)HS (60)MS (24)
Group III
21
Khao Phee Phan
HS (51)S (49)
MS (19)22
Thiri Done Pathein
HS (52)S (50)
MS (24)
Group IV
23
Kauk Kyi Shan Ma
S (47)S (44)S (26)
Group V
24
Kauk Kyi
S (48)HS (60)MS (17)25
Khao Kham To
S (39)HS (64)
MS (22)26
Shwe War Yin
S (34)
HS (55)MS (14)
Group VI27
Paw (1)S (50)S (50)
MS (25)28
Paw San Hmwe
S (36)S (39)
MS (21)29
Khao Lamil
S (42)S (45)
MS (17)30
Naung Ta Moe Se
S (46)S (48)
MS (21)
31
Kun Lone
S (48)S (47)
MS (25)32
Hmaw Bi Kyauk Nyin Hmwe
S (42)S (27)
MS (21)33
IR 36
S (43)S (34)
MS (18)34
Ma Naw Tun
S (50)S (39)
MS (20)35
Bu Aung Ban
S (48)S (45)
MS (23)
Group VII36
Nga Sar Kay
MS (19)MS (24)MR (10)37
Sinthukha
MS (16)MS (14)MR ( 8 )Sr. No.: Serial number, MR: Moderately resistant, MS: Moderately susceptible, S: Susceptible, HS: Highly susceptibleⒸ ISERD112

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Table 3 Reaction of forty-one YAU rice lines and two check varieties to three most virulent
isolates of Xanthomonas oryzae pv. oryzae
Sr. No.

Name of YAU rice lines

Disease reaction and Disease severity (%) to bacterial isolate
Isolate I
Isolate II
Isolate III( Zeyathiri)( Zabuthiri)(Pyinmana)

Group I
1
Manawthukha
HS (84)HS (90)HS (81)
Group II2
YAU-1214-B-B-B-153-3-1
HS (52)HS (66)
S (33)3
YAU-1214-183-3-4-1-1-1
HS (54)HS (68)S (36)4
YAU-1215-S- S- S-77- 2-1
HS (52)HS (66)
S (30)
Group III5
YAU-1201-187-1-2
S (44)
HS (56)
S (26)6
YAU-1201-1-2-1
S (39)
HS (53)S (26)7
YAU-1211-223-3-1
S (39)
HS (72)S (28)
Group IV8
YAU-1201-90-2-2
S (40)
HS (54)
MS (23)
Group V9
YAU-1201-179-2-1
S (39)S (43)S (32)10
YAU-1211-22-2-1
S (34)S (48)S (27)11
YAU-1211-118-1-1
S (40)S (48)S (28)12
YAU-1211-211-2-1
S (31)S (45)S (29)13
YAU-1214-S-S-S-77-1-1
S (36)S (44)S (26)14
YAU-1215-B-B-B-139-3-1
S (41)S (42)S (31)15
YAU-1215-B-B-B-153-3-1
S (41)S (43)S (27)16
YAU-1214-183-3-1-2-1-1
S (35)S (42)S (31)17
YAU-1214-183-3-3-1-1-1
S (38)S (42)S (28)18
YAU-1214-183-35-1-1-1-1
S (30)S (38)S (26)19
YAU-1215-73-2-3-1-1-1
S (39)S (41)S (29)20
YAU-1215-B-B-B-168-1-1
S (39)S (43)S (27)
Group VI21
YAU-1215-S-S-S-40-2-1
S (36)S (49)
MS (20)22
YAU-1215-S-S-S-41-1-1
S (29)S (37)
MS (23)23
YAU-1215-S-S-S-55-2-1
S (30)S (34)
MS (21)
24
YAU-1215-B-B-B-10-1-1
S (31)S (41)
MS (17)25
YAU-1201-61-3-3
S (27)S (32)
MS (19)26
YAU-1201-90-2-4
S (32)S (37)
MS (25)27
YAU-1201-121-3-1
S (36)S (42)
MS (24)28
YAU-1201-202-1-2
S (30)S (28)
MS (21)
29
YAU-1201-202-2-2
S (34)S (41)
MS (24)30
YAU-1201-202-2-1
S (38)S (34)
MS (22)
31
YAU-1211-20-1-1
S (33)S (40)
MS (20)32
YAU-1211-54-2-1
S (26)S (32)
MS (22)
33
YAU-1211-95-2-1
S (28)S (31)
MS (19)34
YAU-1211-116-3-4
S (33)S (44)
MS (23)35
YAU-1211-118-2-1
S (35)S (44)
MS (18)36
YAU-1211-154-3-1
S (35)S (41)
MS (25)37
YAU-1211-179-3-2
S (32)S (31)
MS (22)
38
YAU-1214-183-3-1-1-1-1
S (30)S (39)
MS (22)
39
YAU-1215-80-1-2-1-1-1
S (27)S (29)
MS (22)
Group VII40
YAU-1211-116-3-3
MS (19)MS (25)MS (13)
41
YAU-1211-223-3-2
MS (25)MS (21)
MS (14)
Group VIII42
YAU-1211-71-1-1
MS (19)MS (24)MR (11)43
Sinthukha
MS (17)MS (18)MR (12)
Sr. No.: Serial Number, MR: Moderately Resistant, MS: Moderately Susceptible, S: Susceptible, HS: Highly Susceptible

As mentioned, in this study, all YAU rice lines except YAU-1211-71-1-1 displayed moderately
susceptible to highly susceptible reactions and rice lines differed in reaction with different isolatesof the pathogen. The present study reached similar conclusions to Noor et al., (2006), who stated that
the Xanthomonas oryzae pv. oryzae strains which induced a susceptible reaction in one variety ofⒸ ISERD

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rice, are not necessarily able to induce similar reaction in other varieties. YAU-1211-71-1-1 andSinthukha varieties showed moderate resistance to isolate III (Pyinmana) in the present study. The
YAU-1211-71-1-1 may also contain a resistance gene (Xa21) because it was developed from a crossof Sinthukha, a popular variety which is resistant to bacterial blight disease (and as mentioned, carries
the resistance gene Xa21), and Long 8, a hybrid rice variety which is high yielding.
CONCLUSION
The Nga Sar Kay and Sinthukha rice varieties and YAU-1211-71-1-1 rice line are moderately
resistant to Isolate III (Pyinmana). Nga Sar Kay, considered as a Myanmar local variety, has potential
to be used in future rice breeding program. Also Sinthukha and YAU-1211-71-1-1 show goodpotential for use in disease prone areas, especially in combination with other management practices.
The YAU-1211-71-1-1 can be considered as a promising rice line that could be grown in bacterial
blight prone areas, again in combination with other management practices. The emergence of a newrace is responsible for the removal of many resistant varieties according to the gene-for-gene concept.
Therefore, further research such as the investigation of new strains that have arisen in nature and thescreening of rice varieties for their resistance or/ susceptibility to that race, need to be constantly andfrequently undertaken in the future.
ACKNOWLEDGEMENTS
We acknowledge the financial support provided by YAU-JICA Technical Cooperation Project,
Yezin, Nay Pyi Taw, Myanmar.
REFERENCES
Aye, S.S., Matsumoto, M., Kaku, H., Goto, T., Furuya, N. and Yoshimura, A. 2007. Evaluation of resistancein rice plants to Myanmar isolates of Xanthomonas oryzae pv. oryzae. J. Fac. Agri., Kyushu University,
52 (1), 17-21.
IRRI. 1988. Standard evaluation system for rice. 3rd Ed., International Rice Testing Program, IRRI. Los Banos,
Laguna, Philippines.
Kauffman, H.E., Reddy, A.P.K., Hsieh, S.P.Y. and Merca, S.D. 1973. An improved technique for evaluating
resistance of rice varieties to Xanthomonas oryzae. Plant Disease Reporter, 57, 537-541.
Khush, G.S., Bacalangco, E. and Ogawa, T. 1990. A new gene for resistance to bacterial blight from O.
longistaminata. Rice Genet. Newsl., 7, 121-122.
Lwin, T. 2006. Pathogenic diversity of Xanthomonas oryzae pv. oryzae from major rice growing divisions ofMyanmar and resistance of indigenous rice germplasms to bacterial blight. Ph.D. Thesis, Yezin
Agricultural University, Yezin, Nay Pyi Taw, Myanmar.
Maung, T.T. 2014. Race identification of Xanthomonas oryzae pv. oryzae, Response of some rice varieties tobacterial blight and effectiveness of some bactericides. M.Sc Thesis, Yezin Agricultural University, Yezin,
Nay Pyi Taw, Myanmar.
Myint, H., Hlaing, T. and Htay, K. 1983. Analysis of crop loss caused by bacterial leaf blight incidence.
Research Policy Direction Board, Agricultural Science Research Division, Burma Research Congress.
Myint, S.S. 2008. Reaction of ten rice varieties to five races of Xanthomonas oryzae pv. oryzae. Postgraduate
Diploma in Agricultural Science Dissertation, Yezin Agricultural University, Yezin, Nay Pyi Taw,
Myanmar.
Noor, A., Chaudhry, Z., Rashid, H. and Mirza, B. 2006. Evaluation of resistance of rice varieties against
bacterial blight caused by Xanthomonas oryzae pv. oryzae. Pak. J. Bot., 38 (1), 193-203.
Singh, M.K., Singh, P., Singh, R.P., Mohapatra, C. 2013. Association analysis for yield and quality attributes
in Indica rice and screening of hybrids against blast disease (Magnaporthe grise Barr.). J. P. Sci,
DOI:10.3923/jps.2013.
Swamy, P., Panchbhai, A.N., Dodiya, P., Naik, V., Panchbhai, S.D., Zehr, U.B., Azhakanandam K. and Char,
B.R. 2006. Evaluation of bacterial blight resistance in rice lines carrying multiple resistance genes andXa21 transgenic lines. Current Science, 90 (6), 818-824.
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Swings, J., Mooter, M.V.D., Vauterin, L., Hoste, B., Gillis, M., Mew, T.W. and Kersters, K. 1990.
Reclassification of the causal agents of bacterial blight (Xanthomonas campestris pv. oryzae) and bacterial
leaf streak (Xanthomonas campestris pv. oryzicola) of rice as pathovars of Xanthomonas oryzae(exIshiyama 1922) sp. nov., nom. rev. Int. J. Systematic Bacteriology, 40, 309-311.
Tsuchiya, K., Mew, T.W. and Wakimoto, S. 1982. Bacteriological and pathological characteristics of wild
types and induced mutants of Xanthomonas campestris pv. oryzae. Phytopathology, 72 (1), 43-46.
Win, K.K. 2013. Bacterial diseases of Myanmar. Workshop on Plant Protection, Department of Agricultural
Research, Yezin, Nay Pyi Taw, Myanmar.

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Research article
erdStudy on the Factors of Awareness for the Production andDevelopment of Vegetables by Farmers in Cambodia
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, Tokyo, JapanKUMIKO KAWABE
Extension Center, Institute of Environmental Rehabilitation and Conservation, Tokyo, Japan
Received 10 September 2019

Accepted 5 December 2020(*Corresponding Author)

Abstract Recently, vegetable has also been cultivated by many farmers in Cambodia due tothe increase of its demand in the local market. The main objective of this study was to clarify
the awareness levels of the local farmers with an emphasis on agriculture production
information for the sustainable development of vegetable production. Based on the multiple
correspondence analysis results, the information required by local farmers was shown to bedifferent depending on farm management scale. It can be concluded that it is important toprovide information and technology that is adapted to the development stage of agricultural
management of each local farmer. Moreover, a categorical principal component analysis isused to categorize and clarify the effectiveness of kind of agricultural production information
was needed to develop vegetable production.
Keywords categorical principal component analysis, Cambodia

INTRODUCTION
In Southeast Asia, the rapid increase of population and lifestyle transition results the increase of
demand in various agricultural crops particularly on vegetables. Although the main agricultural
product in Cambodia is rice, vegetable has also been cultivated recently by many farmers.
According to the Census of Agriculture of the Kingdom of Cambodia (National Institute of
Statistics, 2013), a wide variety of vegetables were cultivated across the country including leafy,
stem and fruit bearing, root, bulb and tuberous, leguminous green, and others. Leafy vegetables suchas Water Convolvulus (Ipomoea aquatica), Cabbage (Brassica oleracea), Lettuce (Lactuca sativa),
Green Garlic (Allium sativum), Spring Onion (Allium fistulosum), Celery (Apium graveolens),
Spinach (Spinacia oleracea), Watercress (Nasturtium officinale), Chinese Kale (Brassica oleracea),
Clover (Trifolium L.), Amaranth (Amaranthus L.) and Pigweed (Amaranthus) are amongst of thecommon vegetables produced in the country. Tomato (Solanum lycopersicum), Bitter Melon(Momordica charantia), Watermelon (Citrullus lanatus), Wing Bean (Psophocarpus
tetragonolobus), Bhendi (Abelmoschus esculentus), Snake Gourd (Trichosanthes cucumerina), Ivy
Gourd (Coccinia grandis), Winter Squash (Cucurbita moschata), Chili (Capsicum), Cucumber(Cucumis sativus), Muskmelon (Cucumis melo), Eggplant (Solanum melongena), Gourd (Lagenaria
siceraria), Green Gourd (Cucurbitaceae) are also some of the commonly cultivated fruit bearing
vegetables. Fruit bearing vegetables were cultivated over 35,000 ha of which cucumber covers thelargest area accounting 7,000 ha followed by watermelon at more than 6,000 ha while chili andpumpkins are at 5,000 ha each. However, many of these areas are cultivated in small scale and forthe purpose of farmer’s household consumption. In addition, many local farmers cultivate vegetables
during the dry season that results lesser production than cultivated in the wet season. Thoseconditions contributed a limited supply of vegetable in the market. To boost up and sustain theⒸ ISERD

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production of vegetables in Cambodia, it was determined that there is a need to support small scale
vegetable growers in technical, farm inputs and a win-win price control of vegetable in the market(Chen et al., 2018). However, there is also a need to find out the instincts of farmers on how they
will deal the possible supports they need. Therefore, this study has been proposed to clarify theawareness levels of the local vegetable growers with an emphasis on agriculture production
information.
METHODOLOGY
The research site was in Kampong Cham Province. It is located at the northeast of Phnom Penh, andsoutheast of Siem Reap. In Kampong Cham Province during the French colonial period, the hilly
terrain was developed as a rubber plantation zone. The population of Kampong Cham province isapproximately 1.75 million and much of the population is engaged in agriculture. Table 1 shows theacreage and domestic share of major vegetables in Kampong Cham province. According to table 1,
Kampong Cham Province is a major producing center of cabbage, lettuce and muskmelon.
Table 1 Acreage of major vegetables produced in Kampong Cham Province
Kompong Cham
Cambodia
Planted Area
Planted Area
Composition ratio
Kind of Vegetables
(ha)
(ha)
(%)
Leafy or Stem Water Convolvulus
2306.539.9
1.7
Vegetables Cabbage
648.6
223.0
34.4
Lettuce
824.8
153.0
18.5
Chinese Kale
327.4
11.2
3.4
Fruit‐Bearing Chilli
4637.8618.4
13.3
Vegetables Cucumber
6894.5164.0
2.4
Muskmelon
1901.9847.4
44.6
Eggplant
2997.4
103.8
3.5
Gourd
1687.461.8
3.7
Pumpkin4624.922.7
0.5
Tomato1065.222.7
2.1
Watermelon
5911.871.8
1.2
Bhendi
406.2
302.0
74.3
Total
34234.4
2641.5
7.7
Source: Census of Agriculture of the Kingdam of Cambodia 2013

In this study, the following two multivariate analyses are applied. Firstly, Correspondence
analysis is an analysis method that visualizes the cross-tabulation and facilitates the interpretation of
the survey results. In this study, correspondence analysis is an appropriate method for understanding
the awareness of local farmers and the results of the response patterns of necessary agricultural
information. Secondly, Categorical principal component analysis is an analysis method forclassification by integrating strongly correlated variables and creating new synthetic variables.
Categorical principal component analysis is an appropriate method for creating new synthetic
variables from many variables such as local farmer attributes agricultural information for vegetableproduction, and information sources, which is one of the purposes of this study. In addition, aprevious study (Yamada et al., 2018) used categorical principal component analysis to classify farmmanagement characteristics for development assistance in rural Cambodia.
The research site was ten districts in Kampong Cham Province, Cambodia. The target area ofthe questionnaire survey consisted of the following ten districts: Batheay district: 45 respondents(10.3% of the total respondents), Chamkar Leu district: 50 (11.4%), Chueng Prey district: 36 (8.2%),
Kaoh Sotin district: 46 (10.5%), Kampong Siem district: 38 (8.7%), Krong Kampong Cham district:Ⓒ ISERD

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48 (11.0%), Kang Meas district: 44 (10.1%), Prey Chhor district: 36 (8.2%), Srei Santhor district: 50(11.4%) and Stueng Trang district: 44 (10.1%).

Fig. 1 Location of the study site in Kampong Cham Province
RESULTS AND DISCUSSION
Table 2 shows the index of the questionnaire carried out, which contains categories for gender, ageof the respondent, educational background, farm acreage, cropping pattern, sales destination andfarmers' revenues.
Table 2 Demographic information of respondents
Index
Gender

1. Male2. FemaleAge
1.Less than 29 years old
2.30-39years
3.40-49years
4.50-59years
5.More than 60 years old
Educational background 1. Never had been to school
2. Primary
3. Secondary
4. High school
5.College/University
Farm acreage
1.Less than 0.5 ha
2.0.6-1ha
3.1.1-1.5ha
4.1.6-2ha
5.More than 2.1ha
Source ： Survey Date

Number of response
(n)
(％)
282
64.5
155
35.5
17
3.9
113
25.9
140
32.0
116
26.5
51
11.7
42
9.6
228
52.2
133
30.4
33
7.6
1
0.2
91
20.8
116
26.5
117
26.8
40
9.2
73
16.7

Index
Cropping pattern 1.Vagetables
2.Rice3.Rice,Vagetables
4.Rice,Vagetables,fruit
Sales destination 1.Middleman only
2.Middleman and Market in the village
3.Market in the village only
4.Other market only
5.No answer
farmers' revenues 1.Less than 1,000,000 Riel
2.1,000,000-2,999,999 Riel
3.3,000,000-4,999,999 Riel
4.5,000,000-6,999,999Riel
5.7,000,000-8,999,999 Riel
6.More than 9,000,000 Riel

Number of response
(n)
(％)
43
9.8
48
11.0
98
22.4
248
56.8
302
69.1
53
12.1
57
13.0
25
5.7
7
1.6
30
6.9
169
38.7
122
27.9
57
13.0
32
7.3
27
6.2

The attributes of the respondents are as follows. Concerning the “Gender” of the respondents,
64.5% were “male” and 35.5% were “female.” Concerning the “Age” of the respondents, the majorityof respondents were between the ages of “40-49” years (32.0%), followed by “50-59” years (26.5%)
and “30-39” years (25.9%). The lowest percentage was aged “Less than 20 years” old. Concerning
the “Educational background”, the majority of respondents had “Primary” (52.2%), followed by“Secondary” (30.4%) and lastly “Have never been to school” (9.63%). Concerning the “Farm acreage”
of the respondents, the majority of respondents were between a farm acreage of “1.1-1.5” ha (26.8%),
followed by “0.6-1.0” ha (26.5%) and “Less than 0.5” ha (20.8%). Concerning the “Cropping pattern”
of the respondents, the majority of respondents were “Rice, Vegetables, Fruit” (56.8%) followed by“Rice, Vegetables” (22.4%). Concerning the “Sales destination” of the respondents, about 70% of
the local farmers answered “Middleman only”. Concerning the “farmers' revenues” of the
respondents, the majority of respondents were between the farmers' revenues of “1,000,0002,999,999” Riel (38.7), followed by “3,000,000-4,999,999” Riel (27.9%) and “5,000,000-6,999,999”
Riel (13.0%).
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As a result, vegetable production is carried out by local farmers with a management area of
1.5ha or less, and most of the produced vegetables are shipped to Middlemen. In addition, womenare often involved in vegetable production.
Characteristic of Respondents and Data of the Information for Sustainable developmentof Vegetable Production by Multiple Correspondence Analysis
This part clarifies characteristics of respondents and the information for sustainable development ofvegetable production by Multiple Correspondence Analysis. The indices used for the analysis are
X1: Farm acreage, X2: Farmers' revenues, X3: Information about seeds, X4: Information aboutmachinery, X5: New technology information, X6: Information about chemical fertilizer, X7:
Information about organic fertilizer, X8: Market information, X9: Information about training, X10:
Price information, X11: Information about harvest and X12: Planting information. Figure 1 shows
the results of the answer pattern for Characteristic of respondents and information with an emphasis
on sustainable development of vegetable production by Multiple Correspondence Analysis.
According to the results of Multiple Correspondence Analysis, respondents with small farm acreageand low income are X3: Information about seeds, X6: Information about chemical fertilizer and X12:
Planting information. Furthermore, the local famer who answered the farm acreage as 1.1-1.5 ha wasfound to be related to X5: New technology information and X9: Information about training.
Additionally, the local famer who answered the farm acreage as 1.6-1.2 ha and more than 2 ha were
found to be related to X10: Price information and X11: Information about harvest. This clarified thecharacteristics of the local farmer consciousness and information of the emphasis on sustainable
development of vegetable production. According to the results of Multiple Correspondence Analysis,
it was clear that the preference divisions of the local farmers were difference of farm acreage asimportant characteristics for the classification.

Fig. 2 The result of answer pattern for the local farmers consciousness andrequired agricultural information (Correspondence Analysis)Grouping of Respondents by Category Principal Component Analysis
In this section, information on each variable, such as farmer attributes, cultivated land, theinformation for sustainable development of vegetable production and Information source aresummarized and a "total index" is created and grouped. We employed a categorical principalⒸ ISERD

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component analysis for this purpose. Index and answer patterns used for categorical principal
component analysis were as follows.
Table 3 Estimation results of categorical principal component analysis
Index
X1 Gender
X2 AgeX3 Educational background
X4 Cultivated land
X5 Average annual income from agricultural activity
X6 Cropping pattern
X7 Sales destination
X8 Information about seeds
X9 Information about machinery
X10 New technology information
X11 Information about chemical fertilizer
X12 Information about organic fertilizer
X13 Market information
X14 Information about training
X15 Price information
X16 Information about harvest
X17 Pranting information
X18 Government officer (DDAFF officer)
X19 Village leader
X20 Other farmers in the village
X21 Parents
X22 Scientist
X23 NGO officer
X24 Other (Community)
Sourse Sarvey date
Note Eigenvalue: Factor 1; 2.69, Factor 2; 2.44

FACTOR FACTOR
1
2-0.0720.176-0.1120.206
0.264-0.0370.294-0.0960.422-0.438-0.1760.303-0.402
0.361
0.223
0.502
0.348
0.538
0.208
0.078
0.216
0.518
0.251
0.337
0.342
0.149
0.570
-0.073
0.486
0.511
0.491
0.393
0.081
0.396
0.494
-0.3180.326-0.130-0.2940.053-0.375
0.368
0.152
0.122
0.538
-0.384-0.090-0.041

Table 3 shows the estimation results of the categorical principal component analysis. At thesame time, the eigenvalues of each factor were factor 1: 2.69 and factor 2: 2.44. In the following, it
is confirmed for each principal component what index feature an element constitutes. In the following,
it is confirmed for each principal component what index feature an element is constituted. Firstly,
the indices positively contributing to factor 1 were X3: Educational background (0.264), X4:
Cultivated land (0.294), X5: Average annual income from agricultural activity (0.422), X10: New
technology information (0.208), X14: Information about training (0.570), X18: Government officer(DDAFF officer) (0.494) and X23: NGO officer (0.538). From these indices, factor 1 can beinterpreted as "the factor representing the priority of information for the future of agricultural
management". Secondly, the index positively contributing to factor 2 were X1: Gender (0.176), X2:
Age (0.206), X6: Cropping pattern (0.303), X7: Cultivated land (0.361), X8: Information about seeds(0.502), X9: Information about machinery (0.538), X11: Information about chemical fertilizer(0.518), X17: Planting information (0.396), and X21: Parents (0.368). From these indices, factor 2
can be interpreted as "Factors expressing intention to form production areas by collaboration".
For local farmer grouping, it can be classified into the following 4 groups from each positive
and negative combination of factor 1 and factor 2. Group 1 is local farmers that are positive for both"the factor representing the priority of information for the future of agricultural management" and"Factors expressing intention to form production areas by collaboration." This group is underⒸ ISERD

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situations that ensure stable income such as agricultural machinery is in place, has an interest in
improving the quality of agricultural crops and sales outlets and also shows an understanding ofcooperation with others. Therefore, it is suggested that local farmers classified as group 1 are suitable
as model farmers for projects for sustainable vegetable production. The local farmers of group 2 arepositive for "the factor representing the priority of information for the future of agricultural
management" and negative for "Factors expressing intention to form production areas bycollaboration". This group is already aiming to achieve modern agricultural production and toadvance agricultural management on an individual level. This is considered to be highly adaptableto projects aimed at improving the agricultural techniques for vegetable production of local farmers,such as the start of new crops and Introduction of new customers. Group 3 are local farmers that are
negative for both "the factor representing the priority of information for the future of agricultural
management" and "Factors expressing intention to form production areas by collaboration." It is
speculated that the local farmers in this group are in a situation where the infrastructure required for
agricultural production is not well developed. Therefore, a project is needed to disseminate basic
agricultural production techniques. The local farmers of group 4 are negative for "the factor
representing the priority of information for the future of agricultural management" and "Factors
expressing intention to form production areas by collaboration" positive. Similar to Group 3 andGroup 4, the development of agricultural production infrastructure is not sufficient. However, thelocal farmers expect the development of regional agriculture by collaborating with others to offset
its weaknesses. In addition, local farmers classified as Group 4 and Group need to propose to expand
vegetable production from self-consumption by the houses to vegetable production for sale.
According to the results of categorical principal component analysis, local farmers who produce
vegetables were found to have disparities in the development stage of agricultural management. In
addition, it became clear that local farmers have a different awareness of the priorities of information
for the future of agricultural management and their intentions for the formation of main producing
areas.
CONCLUSION
In this study, focusing on the vegetable production in Cambodia, the local farmers analyzed whatkind of agricultural production information was needed to develop vegetable production based ondata obtained from a questionnaire survey. Therefore, the main objective of this study was to clarify
the characteristics of awareness of the local farmers with an emphasis on information of agriculture
production.
The results of the analysis are summarized as follows. Based on the multiple correspondence
analysis results, the information required by local farmers was shown to be different depending onfarm management scale. Based on the categorical principal component analysis results, the relevanceof awareness for the production and development of vegetables and the information required by local
farmers became clear. In addition, local farmers with multiple sales destinations are highly consciousof the factor representing the priority of information for the future of agricultural management.
According to the results of the analysis, for the development of vegetable production in
Cambodia, it can be concluded that it is important to provide information and technology that is
adapted to the development stage of agricultural management of each local farmer.
ACKNOWLEDGEMENTS
This work was supported by JSPS KAKENHI Grant Number JP18K05857.
REFERENCES
Sokhan, C., Thavrak, H. and Mardy, S. 2018. The effect of agricultural cooperative on income’s smallholdersin Svay Chrum commune, Svay Rieng province, Cambodia. Asian Journal of Agricultural andEnvironmental Safety, 1, 6-11.
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The National Institute of Statistics. 2013. Census of agriculture of the Kingdom of Cambodia 2013. National
Report on Final Census Result, The National Institute of Statistics (NIS), Cambodia.
Yamada, S, Mihara, M. and Kawabe, K. 2018. Classification by characteristics of farm management fordevelopment aid in rural area of Cambodia. International Journal of Environmental and Rural Development,
9 (1), 191-197.

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Research article
erd

Yield and Yield Components of Potato Response to Various
Planting Date in Cambodia
KHEANG SONG
Graduate School, Royal University of Agriculture, Phnom Penh, Cambodia

SOPHAL VAR*
Faculty of Agronomy, Royal University of Agriculture, Phnom Penh, Cambodia
Email: var.sophal@gmail.com

SOVANBOREY OYFaculty of Agronomy, Royal University of Agriculture, Phnom Penh, Cambodia

SEANGLY KHEANG
Faculty of Agronomy, Royal University of Agriculture, Phnom Penh, Cambodia

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

SIRANET ROEUN
Faculty of Agronomy, Royal University of Agriculture, Phnom Penh, Cambodia

HONG CHEANG
Faculty of Agronomy, Royal University of Agriculture, Phnom Penh, Cambodia
Received 12 March 2020

Accepted 7 December 2020(*Corresponding Author)

Abstract: Potato (Solanum tuberosum L.), a tuberous plant well known as a highly
nutritional diet and an economic crop s, is the world’s fourth largest production after rice,wheat and corn. Recent experiments have shown some potential places and varieties forcultivation in Cambodia. Thus, the experiment aimed to understand the response of thepotential potato varieties to different planting dates in Sen Monorom town, Mondulkiri
province (a mountainous area), Cambodia. The trail was laid out in randomized complete
block design with 4 replications and 3 different planting dates namely October, November
and December of 2018. The Coronada, certified seed from the Europlant International
company in Germany, was the ideal variety used in the experiment and lasted 115 days fromplanting to harvest. Only the number of tuber per plant, tuber weight, weight per plant, andmarketable yield were recorded. Suggested that planting date significantly affected to allmeasured parameters. Plot planting in December produced the highest number of tubers withan average of 9.3 tubers per plant while a similarity was noticed for October and November
planting. However, the November planting surprisingly produced the highest weight per plant,heavier tuber and the highest marketable yield with 19.15 ton ha-1. The two other planting
dates obtained an average yield of 14.49 and 12.39 ton ha-1 for October and December
consequently. This is understandable that November planting and harvest at end February,which is the long cold and windy season with less rainfall, was the most comprehend planting
season in Mondulkiri province, Cambodia.
Keywords: Mondulkiri, Coronada, upland, Cambodia, planting date

INTRODUCTION
Potato, Solanum tuberusom L., is the fourth largest production crop next after rice, corn and wheat(FAOSTAT, 2006), and the key crop for food security in many developed and developing countriesⒸ ISERD

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(Scott et al., 2000). At the present, potato production is expanding at an incredible rate throughout
the world. Despite its popularity, the crop is not an easy success production in all places. Potato
prefers a cool climate followed by a warm environment for the best massive production. Optimum
yield has been observed in temperate regions with an average temperature around 18-20 oC without
chill (Havetkort and Struik, 2015). In Cambodia, fresh potato is largely imported from Vietnam,
Thailand and China. Production of potato was first introduced in late 2016 under an experiment by
the Faculty of Agronomy at the Royal University of Agriculture (MAFF, 2016). In most hot andtropical countries, potato farming is recommended during the rainy and short rainy season, but mostupland produced areas would not be benefit due to the threat of the soil borne disease such as lateblight (Gebremedhin et al., 2008; Gildemacher et al., 2009). In association with climate change,
several technology packages, and cropping calendar are keys to succeed and maintain the production(Monneveux et al., 2014). Global yield losses were estimated from 18 to 32% without adaptation in
production technologies packages, or 9 to 18% without consideration of cropping calendar and use
d of heat tolerant varieties (Hijmans, 2003). Tittonell et al. (2007) suggested that yield losses in mostrainfed areas is generally largely due more to management aspects than to low physical potential.
The Optimum timing of the planting date is considered as one of the key factors that strongly affectpotato production in a rainfed zone (Wang et al., 2008). Similar to other crops, the optimum planting
date for potato is mostly specific to each production region. However, there was no scientificrecommendation s to adaptable varieties with consideration of the environmental condition in uplandproduction areas in Cambodia, in particular, Mondulkiri province. Therefore, manipulation of theperfect timing of the planting date is the most important key to overcome the negative impact ofenvironmental on potato production in Mondulkiri province, Cambodia. The present study aimed todetermine the optimum planting date for potato production which can produce maximum yield under
the upland climate of Cambodia.
METHODOLOGY
Experiments were carried out under field conditions from October 2018 to April 2019 at Mondulkiri
province (12o28’27” , 107o12’33” E). The site was 710 meters above the sea level. The trial waslaid out in randomized complete block design with 4 replications. The treatment consisted of threedifferent planting dates namely second week of October, November and December, respectively.
Plant density was 4.8 plants/m2 in plots of 12 rows, 0.70 m apart and 25 m long. Each plot was
fertilized with 80 kg N ha-1, 80 kg P2O5 ha-1 and 150 kg K2O ha-1 at planting date and 40 kg N ha-1
and 100 kg K2O were applied at ridging (45 days after planting). Chemical and physical of theexperiment field was described in Table 1. Weed and pathogens were controlled chemically at the
manufacturer’s recommendation rate to prevent biotics damage. The plots were surface irrigatedduring the growing season, according to weather station evapotranspiration data. Coronada, yellow
flesh and skin color from Europlant International, Germany, were used and allowed to stand on the
ground for 115 days from sowing to harvest. Marketable yield and yield components parameter wererecorded. The key data was the number of tubers per plant, weight per tuber, weight per plant andmarketable yield were measured at harvest.
Table 1 Soil physical and chemical properties analysis of experiment site
EC
38.0

pH
4.20

Soil Texture

P
ppm

K
cmolc kg-1

N
%

SOM
%

CEC
cmolc kg-1

Clay

Silt

Sand

0.1

0.42

0.29

5.07

72.4

22.3

35.3

42.4

Source; Soil Laboratory, Faculty of Agronomy, Royal University of Agriculture

RESULTS AND DISCUSSIONⒸ ISERD

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Class
Clay
Loam

IJERD – International Journal of Environmental and Rural Development (2020) 11-2

12

140

10

120

a

b

8

b

6

4
2
0
OctoberNovember

Weight of tuber (grams)

Number of tuber per plant

There was significantly different yield obtained due to variation of environmental condition during
the October, November and December. The highest tuber produced was recorded for December
planting while statistically similar were reported for October and November. The increase
temperature during the vegetative stage led to an increase in the number of stolon which led tovariation in the number of tuber produced per plant. In the upland environment in Cambodia, thetemperature increase was normally observed from mid-January onward while the low temperature
occurred from September or when the rain fell (September-November). Wolf et al. (2017)
emphasized that increased temperature for 20 days at tuber development could affect the number oftuber produced depending on genotype.
a
b

100

b

80
60
40
20
0
October

DecemberNovember

December

Month

Month

Fig. 1 Result of tuber number per plants

Fig. 2 Result of weight of tuber

25
20

b

a
b

15
10
5

Yeild (ton per hectare)

Weight per plant (grams)

November planting produced larger and heavier tubers than any other planting date (Fig. 2).
Higher temperature aboveground over the potato favor limited tuber enlargement, which result in
reduced in tuber per plant (Wolf et al., 1991; Basu and Minhas, 1991). At a higher little temperaturethan 28 degrees Celsius, only 50% of assimilates produced were transferred to tubers, whereas 20%
more of assimilates were translocated at an optimum temperature of 18 oC (Randeni andCaesar,1986). Thus, planting potatoes in November in the upland environment of Cambodia attained
the highest yield which was about 19 ton per hectare. A Decrease in marketable yield was observedfor October planting which was similar to December cultivation. The result showed that November
was the optimum season which was 25-35% higher than growing during October and December.
25

20

November

a
b

15
10

0
Octoberb50December

OctoberMonthNovember

DecemberMonthFig. 3 Average weight of tuber per plantFig. 4 Average marketable yield

Yield of the potato was relatively low due to infection by soil borne disease such as late blight.
Optimum growth and yield of potato was obtained in the tropical region when there was not muchrain and a cool dry climate. October was considered the main rainy season in Cambodia, with many
rainy days and high precipitation (Fig. 5). The Number of rainy days started to decrease form
November and little or no rainfall could be observed from middle of December and temperatures
started to increase. In most hot and tropical countries, potato farming was recommended during therainy and short rainy season, but most upland produced areas would not benefit due to the threat of
the soil borne disease such as late blight (Gebremedhin et al., 2008; Gildemacher et al., 2009).
Ⓒ ISERD

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160
140
120
100
80
60
40
20
0

40
35
30
25
20
15
10
5
0
7

8

9

10

11

12

1

2018

Rainfall

2

3

4

5

Temperature (℃)

Rainfall (mm)IJERD – International Journal of Environmental and Rural Development (2020) 11-2

6

2019

Min Temp

Max Temp

Fig. 5 Climate condition during the experiment
CONCLUSION
Our results is suggested that November was the optimum season for potato farming in uplandenvironment at Mondulkiri province, Cambodia. Planting potatoes in this season produced large
tuber and maximum yield with less damage from soil borne disease due to fewer rainy days andwarm temperature without chilled or exposing the potato to high temperature. October planting wasconsidered the second option, however well drainage system and chemical prevention need to beprepared to prevent crops from damage by excess water and spread of disease. In addition, for
December planting, variety was the key to obtaining better yield due to increase in temperature during
tuber bulking (45 day after sowing). Short and medium varieties are highly recommended, while
long varieties are highly exposed to low productive and crops failure.
ACKNOWLEDGEMENTS
The authors would like to express their sincere thankfulness and appreciation to KOPIA Cambodia
Center (2016-KHM-03), the Europlant International for delivering the seed, GIZ for technical advice,selected farmers for support and encouragement, key informants and information; your mighty
support has been being my greatest source of motivation and inspiration.
REFERENCES
Basu, P.S. and Minhas, J.S. 1991. Heat tolerance and assimilate transport in different potato genotypes. J. Exp.
Bot., 42, 861-866. http://dx.doi.org/10.1093/jxb/42.7. 861
FAOSTAT. 2006. FAO Statistics database on the world wide web. Retrived from http://faostat3.fao.org/
browse/Q/ QC/S.
Gebremedhin, W., Endale, G. and Lemaga, B. 2008. Potato agronomy. In Gebremedhin, W., Endale, G. andLemaga, B. (Eds.), Root and Tuber Crops: The Untapped Resources, Ethiopian Institute of Agricultural
Research, 33-36. Addis Abeba.
Gildemacher, P.R., Kaguongo, W., Ortiz, O., Tesfaye, A., Gebremedhin, W.G., Wagoire,W.W., Kakuhenzire,
R., Kinyae, P.M., Nyongesa, M., Struik, P.C. and Leeuwis, C. 2009. Improving potato production in Kenya,
Uganda and Ethiopia: A system diagnosis. American Journal of Potato Research, 52, 173-2052.
Havetkort, A.J. and Struik, P.C. 2015. Yield levels of potato crops: recent achievements and future prospects.
Field Crops Res., 182, 76-85. http://dx.doi.org/10.1016/j. fcr.2015.06.002
Hijmans, R.J. 2003. The effect of climate change on global potato production. American Journal of Potato
Research, 80, 271-279.
Ministry of Agriculture, Forestry and Fisheries. 2016. Country report: Agriculture current and future prospects.
Ministry of Agriculture Forestry and Fisheries, 36, 69-72, Phnom Penh, Cambodia.
Monneveux, P., Ramírez, D.A., Awais Khan, M., Raymundo, R.M., Loayza, H. and Quiroz, R. 2014. DroughtⒸ ISERD

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and heat tolerance evaluation in potato (Solanum tuberosum L.). Potato Res., 57, 225-247. http://dx.
doi.org/10.1007/s11540-014-9263-3
Randeni, G. and Caesar, K. 1986. Effect of soil temperature on the carbohydrate status in the potato plant. J.
Agron. Crop Sci., 156, 217-224. http://dx.doi.org/10.1111/ j.1439-037X.1986.tb00030.x.
Scott, G.J., Rosegrant, M.W. and Ringler, C. 2000. Global projections for root and tuber crops to the year 2020.
Food Policy, 25, 561-597. http://dx.doi.org/10.1016/ S0306-9192(99)00087-1.
Tittonell, P., Shepherd, K.D., Vanlauwe, B. and Giller, K.E. 2007. Unraveling the effects of soil and crop
management on maize productivity in smallholder agricultural systems of western Kenya, An applicationof classification and regression tree analysis. Agriculture, Ecosystems and Environment, 10, 1-14.
Wang, Y.M., Traore, S. and Kerh, M. 2008. A climatic data information model for computing crop yields in
Burkina Faso. 10th WSEAS International Conference on Mathematical Methods and Computational
Techniques in Electrical Engineering, Sofia, Bulgaria.
Wolf, S., Marani, A. and Rudich, J. 1991. Effect of temperature on carbohydrate metabolism in potato plants.
J. Exp. Bot., 42, 619-625. http://dx.doi.org/10. 1093/jxb/42.5.61933.

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Research article
erd

Economic Impact of Rice Tractor and Combine Harvester
Custom Services in Northwest Cambodia
DALIN SUN*
Graduate School of Agriculture, Tokyo University of Agriculture, Japan
Email: da.lin3019@gmail.com

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

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

Accepted 12 December 2020(*Corresponding Author)

Abstract Agricultural machinery has become significantly important to carry out farm workand to address labor scarcity in Cambodia. However, rural areas face many challenges suchas lack of farmers’ improper machinery utilization and lack of skilled operators in order toimplement agricultural mechanization. The effective use of tractor or combine harvester (CH)requires not only management knowledge and experience, but also proper the economic
evaluation. This study aims to determine the potential of rice tractor and combine harvester
custom service to create an economic advantage for the agricultural machinery owners. A
survey of 28 tractor owners (group T), 21 CH owners (group CH), and 23 tractors and CH
owners (group B) in Banan District, Battambang Province was conducted in March 2019.
The result indicated that the annual custom service area by group T, CH, and B were 133.4
ha, 213.1 ha, 398.9 ha (tractor 180.8 ha, and CH 216.1 ha), respectively. The average
operating cost was estimated at 30.0 USD/ha for group T, 58.9 USD/ha for group CH, and26.2 USD/ha (tractor) and 56.3 USD/ha (CH) from group B. Among the costs incurred,depreciation cost was the highest cost, followed by diesel and labor costs. In some cases,
owners tend to offer higher pay to skilled operators to work for them especially during thepeak seasons. The break-even point per year were estimated at 116.4 ha for group T, 117.5
ha for group CH, and 113.0 ha (tractor) and 109.6 ha (CH) for group B. In general, custom
service by group seemed to vary on the field and infrastructure conditions, operators’ skill,frequently machine breakage, and owners’ desire to gain profit. Therefore, this study suggeststhat the owners should prolong the economic life of tractors or CHs by conducting properand regular maintenance that will eventually lead to decrease break-even area.
Keywords tractor, combine harvester, custom service, operating cost, break-even point,
payback period

INTRODUCTION
In some areas of Cambodia, rice farming system has been changed in agricultural sense from single
cropping to double cropping per year and transplanting method to direct seeding method. Also, theuse of animal powers has been declined from 47% in 2001 to 33% in 2013 (Chhim et al., 2015). Due
to urbanization, the size of rice cultivated land has been reducing, and productivity is also declining
due to non-availability of inputs such as fertilizers, labor inputs, and machineries. According toMinistry of Agriculture Forestry and Fishery (MAFF) Cambodia, the total labor force was decreasingfrom 57.6% in 2009 to 45.3% in 2014.
Agricultural machinery has played a significant role in increasing agricultural production bycompleting farm operations in time, reducing production costs, and address labor scarcity (Chan etal., 2014). Currently, Cambodia has imported hundreds of modern farm machineries to enhance land
preparation or harvesting proportionally. The number of tractors increased 5-fold from 2,602 unitsⒸ ISERD

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in 2001 to 13,701 units in 2015. The number of CHs increased 18-fold from 325 units in 2006 to
5,893 units in 2015. The most common model utilized by farmers is Kubota. However, theimplementation of mechanization in a rural area still faces many challenges, such as impropermachinery use, the high cost of machinery, and lack of skilled operators (Abu et al., 2015). Due topoverty, some farmers found it difficult to access all inputs and acknowledge in modern farmmachinery. And there are available the custom services (custom service refers to a business that is
managed by either group or individual person to provide farming operation with any farmmachineries in the set of rate or fee) from other farmers to other farmers but the demand is still notenough (Banan district annual report, 2017). The effective use of a tractor or combine harvester
requires not only management knowledge and experience but also proper economic evaluation.
OBJECTIVE
This study aims to determine the characteristics and the awareness of farmers about various aspectsof mechanization; and examine costs and profitability of the business to create economic advantage
for the owner.
METHODOLOGY

Fig. 1 Map of Cambodia and Banan District
Source: Google image

This study is conducted in Banan District, Battambang Province. Located 28 km away from
Battambang city, this district is also one of the largest rice-growing areas in the province. There arealso a prevalent large number of farmers using tractors and combine harvesters. The total rice fieldarea of this district is 47,321 ha, of which 38739 ha are wet season rice and 8,582 ha are dry season
rice (Banan district annual report, 2017). Kamping Pouy and Kanghot dam is the main irrigation
system that brings the water to supply the whole district for farming usage.
Primary data were collected through farm questionnaire survey of randomly selected 72
machinery owner-farmers in Banan district in March and August 2019. The respondents were further
divided and categorized into tractor owner-farmers, CH owners, and tractor and CH owners. Data
was obtained both in wet and dry seasons for land preparation and harvesting paddy rice. The
collected data included a year of purchase, initial purchase price, hectares of tractor and CH
utilization, operator wage, repair and maintenance, and fuel costs, and rates of service charge.
Simple descriptive methods cost and return, break-even, and payback analysis were utilized.
RESULTS AND DISCUSSIONⒸ ISERD

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General Characteristics of Respondents
The 72 respondents were categorized into three groups: namely group tractor (T) has 28 tractor
owner-farmers, group combine harvester (CH) has 21 CH owner-farmers, and group both (B) has 23
tractors and CH owner-farmers. Table 1 show average age of the owners was 40 years, with at least
14 years in farming experience. There is no significant difference between those groups.
Table 1 General characteristic of machinery owners
Itemsn
Average family size (persons)Average member involves in rice farming (persons)Average age (years old)
Average farm experience (years)
Education background (years)

Group T
28
3.8
1.8
43.4
14.9
7.8

Group CH
21
4.0
2.1
42.1
14.2
7.5

Group B
23
3.5
2.0
44.6
16.1
7.3

Source: Field survey, 2019

Fig. 2 Percentage of machinery owners accessed to information
In this study, approximately 20% of machinery owners have attended training programs related
to tractor and CH at least one time a year. According to the interviewed owners, training programs
are related to managing, maintenance and repair, and operation of machinery properly, which isusually provided by the Kubota dealer. Yet, there was no training provided by the provincial
department or extension workers.
The rate of machinery owners’ access to information related to tractor and CH is still limited.
Those three group owners commonly received the information from intermediate agents, such asneighbor farmers, friends, and relatives, and some received information from the dealer rather thanfrom the provincial department (Fig. 2).
Tractor and Combine Harvester Utilization
In the survey area, most tractors and CH worked seasonally with an average of 200 days/year. The
variation of working days between tractor and CH is due to differences in local climatic conditions
and land conditions. Tractors work mostly concentrated on land preparation (plowing, harrowing,
and rotavating) and the working hours about 7 to 8 hours/day with an average capacity of about anhour/ha. CH work focused only on rice harvesting and frequently can harvest at least 4 to 5 ha/day(about 2 hours/ha).
Table 2 shows that total annual utilization of group T was from the owners’ farm (40%) andremaining (60%) was custom service. Group CH, approximately 85% of CH was from custom
service. Besides, annual utilization of a tractor and CH on group B owners’ farm was 36% (tractor),and 28% (CH), and remaining from custom service. This result means that tractor or CH owners onlyoffered custom service during the rice cropping season and after they completed with their farm.
Aside from that, machines are stored in the shed or parked in open area when they not in use.
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Table 2 Average annual use per tractor and CH by group machinery owners
Items
Group TOwn farm
Custom service
Group CHOwn farm
Custom service
Group B
TractorOwn farm
Custom service
Combine harvester
Own farm
Custom service

NHH
28

21

Average operated land (ha)
133.4
53.0
80.4
213.1
31.0
182.1

%
40
60
15
85

23
181.2
65.6
115.6
216.1
60.6
155.5

36
64
28
72

Source: Field survey, 2019

Total Cost of Tractor and Combine Harvester Custom Service
Table 3 shows average annual operating cost, which calculated both custom service and the owners’
farm. Tractors and CH operators are the owners, owners’ relatives, or hired operators. Approximately
80% of tractor and CH operators are hired operators who have reimbursed on a hectare basis.
Machinery owners commonly contracted operators during land preparation and harvesting.
Sometimes machinery owners tend to offer higher pay to skilled operators to work for them,especially during peak seasons.
Table 3 Average operating cost per tractor and CH operation
Items
Annual operated land (ha)a. Fixed cost (USD)
b. Variable cost (USD)
RepairOperators
DieselCommission broker
c. Total annual cost (c=a+b)
Total operating cost (USD/ha)Group T
Tractor
133.4
1,832.0
2,169.7
60.0
388.7
1,648.2
72.8
4,001.7
30.0Group CHCH
213.1
5,574.9
6,981.8
423.4
1,291.3
5,133.6
133.5
12,556.7
58.9

Group B
Tractor
CH
180.8
216.1
1,895.7
5,205.0
2,841.6
6,963.4
89.0
296.9
509.5
1,597.2
2,164.8
4,971.7
78.3
97.6
4,737.3
12,168.4
26.2
56.3

Source: Field survey, 2019
Note: Fixed cost consists only depreciation

As a result, average operating cost was estimated at 30.0 USD/ha for group T, 58.9 USD/ha forgroup CH, and 26.2 USD/ha (tractor) and 56.3 USD/ha (CH) from group B. Diesel is the highest
single cost of total variable cost, followed by labor and repair cost. The higher cost of diesel andrepair may be due to differences in machine age, annual use, operator skill as well as field conditions.
Few machine owners revealed that they commonly did not use the aging tractor or CH for providing
custom service because of low power and high risk of failure.
Fig. 3 presents the relationships between total operating costs per hectare and the annual use of
three group owners. In order to derive a function for each cost, the least-squares regression method
was used to determine the best fit function. The total operating cost is taken as the dependent variable(y) and annual use rates as the independent variable (x). The curves describe in terms of data points
related to the above cost items per hectare to annual hectares of use. The r square value could explainat 83% and 84% of the observed variations in group T and B, respectively. This result indicated that
there is a significant contribution to the annual use of decreasing total costs. The total operating costsⒸ ISERD

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of machinery owners per hectare show a quick decline with an increase in annual use. The result
suggests that there is a great potential to reduce total operating costs by increasing annual use (ha).

Group T

Group CH
140.0

y = -0.0733x + 112.62
R = 0.8447

Total Cost (USD/ha)

120.0
100.0

80.0
60.0
40.0
20.0
0.0
0

200

400
600
Annual Use (ha)

800

1,000

Group B

Fig. 3 Relationships between total cost per hectare and annual use
Service Charge and Profitability of Tractor and Combine Harvester Custom Service
Normally, farmers contacted machine owners before any operations to secure their place to beavailable on time. In addition, farmers usually asked the same custom service providers of theprevious year because they have been satisfied with that service. But in some emergency cases,
farmers made decision to choose a new custom service provider who can respond to their needs.
The service charge of ploughing ranged from 25 USD to 29 USD per hectare, and rotavating
ranged from 27 USD to 33 USD per hectare. The harvesting operation depends on the rice varieties
and season (wet and dry season). The service charge of wet season rice varieties is about 85 to 90
USD per hectare, while the price of dry season rice varieties ranged from 68 to 80 USD per hectare.
In some cases, it found that the rate of harvesting service was a bit higher than the average
estimated. The reasons were that rice stalks are bent and difficult to harvest, so hiring farmers had to
pay higher rates according to an agreement made by farmer and machinery owners.
Table 4 Average profitability per tractor and CH operation
Items
Annual operated land (ha/year)
Service charge (USD/ha)
Annual revenue (USD/year)
Annual cost (USD/year)
Annual profit (USD/year)
Profit (USD/ha)Break-even area (ha/year)
Payback period (years)

Group T
Tractor
133.4
32.0
4,268.8
4,001.7
267.1
2.0
116.4
11.9

Source: Field survey, 2019
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Group CH
CH
213.1
80.2
17,090.6
12,556.7
4,533.9
21.3
117.5
3.4

Group B
Tractor
CH
180.8
216.1
32.5
79.7
5,876.0
17,223.2
4,737.3
12,168.4
1,138.7
5,054.8
6.3
23.4
113.0
109.6
8.2
3.6

IJERD – International Journal of Environmental and Rural Development (2020) 11-2

Table 4 presents the average profitability per tractor and CH operation. As a result, group T,
CH, and B received a profit from the operation were roughly 2 USD/ha, 21.3 USD/ha, and 29.7
USD/ha (tractor 6.3 USD/ha, CH 23.4 USD/ha). Moreover, the annual utilization of tractor and CH
required for economic feasibility was evaluated using break-even analysis. The result indicated thatthe break-even areas per year were estimated at 117.4 ha for group T, 117.6 ha for group CH, and112.8 ha (tractor) and 109.8 ha (CH) for group B. This means that after an additional hectare of either
tractor or CH used would make a profit for the owners. Moreover, the payback period was estimatedto be at 11.9 years for group T, 3.4 years for group CH, 8.2 years (tractor) and 3.6 years (CH) forgroup B to earn back investment.
CONCLUSION
There were no significant differences in characteristic respondents and approximately 20% fromthree group owners aware of training programs about tractor and CH, which is usually conducted by
the dealer. Yet, there were no training programs on proper management, repair, and operatemachinery provided by extension workers or department of agriculture engineering.
Generally, farmers contacted machine owners before any operations to secure their place to beavailable on time, and they usually asked the same service providers of the previous year. Amongthe operating costs incurred, depreciation cost was the highest cost, followed by diesel and laborcosts. In some cases, machinery owners tend to offer higher pay to skilled operators to work for them,especially during the peak seasons. Regarding profit, the utilization of tractor and CH under current
conditions was profitable for machinery owners. Three group owners should increase annual use
beyond the break-even areas by providing more custom service to other farmers in order to earn backthe investment on tractors or CH. This result suggests that the break-even area and payback period
analysis can also give an indication for farmers to decide whether to purchase a new tractor or
combine harvester or ask more custom service.
Therefore, this study recommends that the owners should prolong the economic life of tractors
or CHs by conducting proper and regular maintenance that will eventually lead to shorten the breakeven areas and payback period in order to gain more profit. Additionally, the government or privatecompany should provide special training programs for the machine operators, farmers, andmechanical extension officers on proper management, repair, and operation. Also, the local
government should setup the formula for ensuring the fair prices of the custom service.
REFERENCES
Abu, S., Hossain, M., Talukder, M., Mahedi, H., Mohammad A. and Mosharaf, H. 2015. Farm machinery usedand problems associated with rice cultivation as well as farmers expectation in two villages of ComillaDistrict in Bangladesh. International Journal of Advanced Research, 3 (8), 112-121.
Banan District. 2019. Annual district report of 2017 and 2018. Battambang Province, Cambodia.
Chan, S., Lytour, L. and Santy, S. 2014. Status and prospect of agricultural mechanization in Cambodia. United
Nations Centre for Sustainable Agricultural Mechanization, 7-11.
Chhim, C., Buth, B. and Ear, S. 2015. Effect of labor movement on agricultural mechanization in Cambodia.
CDRI Working Paper Series, No. 107, Cambodia Development Resource Institute, Cambodia.
IRRI. 2016. Combine harvesting in south and southeast Asia: Current status and trends. International Rice
Research Institute, Philippine.
MAFF. 2016. Annual report for agriculture, forestry and fisheries 2000-2016. Ministry of Agriculture, Forestry
and Fisheries, Phnom Penh, Cambodia.
Thangavel, A. 2009. An analysis of the impact of mechanization in paddy cultivation in Thanjavur District ofTamilnadu. Ph.D. Dissertation, Department of Post Graduate Studies and Research in Economics, India.

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Research article
erd

Coping Strategies of Japanese Farmers to Recent
Challenges in K City, Chiba, Japan
NINA N. SHIMOGUCHI*
Faculty of International Agriculture and Food Studies, Tokyo University of Agriculture,
Tokyo, Japan
Email: n3nocon@nodai.ac.jp

JENNICA AMIELLE M. MORA
Graduate School of Agriculture, Tokyo University of Agriculture, Tokyo, Japan

ELIZA C. AQUINO
Graduate School of Agriculture, Tokyo University of Agriculture, Tokyo, Japan
Received 7 February 2020

Accepted 12 December 2020(*Corresponding Author)

Abstract Japanese agriculture has been facing various challenges such as increasing
population of elderly farmers and lack of successors. Moreover, several environmental andmarket issues have tested the capability of Japanese farmers to cope. Through a case study
approach, this study aims to clarify the coping strategies of farmers in K City, Chiba
Prefecture to recent challenges and determine the issues to support and sustain their local
agriculture. A series of visits were conducted in 2018 and 2019, and in-depth key-informant
interview was conducted in June 2019. In-depth key-informant interview revealed that
farmers from K City organized a Farmers’ Market at their own initiatives to sustain andsupport the local agriculture for the next 10 to 20 years. Since the establishment of theFarmers’ Market in 2003, the farmers faced pesticide residue reports on turnip and various
vegetables in 2008 and 2010, respectively; radiation residue report as an effect of the 2011
Great Tohoku Earthquake and Nuclear Plant Meltdown have brought negative impacts to thefarmers as harmful rumors on the safeness of the agricultural products from K City spread toname a few. Farmers have initiated innovative actions and adapted strategies to overcome
these challenges. SWOT analysis revealed that the farmers, at their own expense, regularly
tested the produce for pesticide and radiation residue to assure its quality and safeness.
However, if not continued, misconception among consumers will prevail then lead to distrust.
They even provided other services such as restaurant, café, farm tour and seminars. On theother hand, the farmers recently tend to supply to other markets aside from the Farmers’Market, conveying a significant supply issue to be addressed. In general, these strategies andinitiatives which reflect the farmers’ passion and motivation to achieve sustainability seemed
to be the factors that made them resilient to the changing environment.
Keywords resiliency, farmers’ market, motivation, adaptation strategies, SWOT analysis

INTRODUCTION
Japanese agriculture has been facing various structural challenges that need to be addressed for thesector to survive. Among these, some of the most important challenges are the increasing populationof elderly farmers and lack of successors (Brady, 2016) and decreasing population of newcomers(MAFF Japan, 2018). The average age of farmers in Japan is 66 years old (MAFF Japan, 2018;
OECD, 2019) which implies that the sector highly depends its labor on elderly people. The
dependence of labor on elderly people can affect the production of the agriculture sector in the longrun, in terms of loss in human capital once they are only treated as those who receive social services(Haga, 2018). According to Su et al. (2018), lack of farm successors and insufficient agriculturallaborers are some of the factors that contribute to the abandonment of farmland which can have asignificant impact on the socio-economic conditions of the farmers as well as on environment inⒸ ISERD

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terms of rural landscape loss. On the other hand, the Organization for Economic Co-operation andDevelopment (OECD, 2019) stated that the number of newcomer farmers is less than the numbers offarmers who are exiting the agriculture sector. One way to support and encourage these farmers is toprovide accessible markets.
On a more micro-level, Japanese farmers are often faced with several environmental and market
issues which test their capability to cope. Japan is an archipelago located in the Pacific Ring of Fire
which makes it vulnerable to earthquakes. The Great Tohoku Earthquake, the strongest recorded
earthquake to hit Japan which happened last 2011, left a total of 18,186 areas of damaged agriculturalland in prefectures such as Tochigi, Ibaraki, and Chiba among others (MAFF Japan, 2013).
OBJECTIVE
This study aims to clarify the coping strategies of farmers in K City, Chiba Prefecture to recent
challenges and determine the issues to support and sustain their local agriculture.
METHODOLOGYThis study gathered primary data through a series of visits conducted in 2018 and 2019 and an indepth key-informant interview in June 2019. This study interviewed the president of farmer-based
corporation (hereafter, A Corp) and K Farmers’ Market manager through purposive sampling. In
order to further grasp the situation on the ground, impromptu interview of farmers market staff,
farmers and consumers were also conducted. The qualitative approach is used as this can reveal thepassion and motivation of the farmers in coping with the different challenges that they encounter.
The data were analyzed through SWOT analysis since it is descriptive and qualitative in nature.
SWOT analysis plays an important role in certain situations in a theoretical, historical, and time frame
perspective (Gürel, 2017). This study focused on the practices and experiences of a farmers group in
K City, Chiba Prefecture as they have experienced various environmental and market issues that
affected their local agriculture and welfare.

Fig. 1 Map of Chiba, Japan where the K Farmers’ Market is locatedSource: Google Maps

Located Northwest of Chiba Prefecture, K City is about 40 km, away from Tokyo (Fig. 1).
Agriculture land accounts for 1,773 ha, of which rice fields occupy about 1,047 ha, followed byvegetables (663 ha) and fruits (63 ha). In terms of total domestic production volume, K City is
considered the major producing area of turnip, leek and spinach. With proximity to Tokyo and goodaccessibility, it is also a popular bedroom or commuter town. Thus, this city is also experiencing
agricultural land conversion to residential.
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RESULTS AND DISCUSSION
K Farmers’ Market Profile
The group of farmers from K City, Chiba Prefecture established a limited company in 2003, and built
the K Farmers’ Market at their own initiative in order to sustain and support the local agriculture forthe next 10 to 20 years. In 2004, this company was converted to a corporation with 15 stakeholders.
These initiatives were triggered by threats from cheap imported leek and were encouraged by thedemand of local consumers for freshly harvested local produce.
In the early 2000, Japanese farmers was severely affected by imported vegetables from China(Teramachi, 2002). Harashima (2006) presented the initiatives of the Japanese government andfarming communities on significant increase of imported leeks and low market price. During thistime, most farmers in the study resorted to keep their harvest in cold storage since their produce could
not compete with significantly low-priced imported leeks. This resulted to income losses anddecrease in farmer’s motivation.
As mentioned earlier, turnip is one of the famous agricultural products of K City. However,
local consumers do not have the opportunity to taste freshly harvested turnips since these arecommonly shipped to a wholesale market and sold via auction before some are shipped back to local
supermarkets or vegetable stores.
K Farmers’ Market has four (4) management principles: 1) place of sale, sharing information,and interaction; 2) consideration of consumer satisfaction; 3) promotion of local production – local
consumption; and 4) development of the community. Currently, it employs six (6) full-time and 66
part-time workers. Although there were only 150 farmer-members during the early years in 2003, it
grew up to 230 farmers in 2019. However, only 150 farmer-members are currently active. Amongthese farmers, there are only about 50 farmers who are under 40 years old, conveying that young
farmers only comprise one-third of the active members. Although majority of farmers produce
vegetables, there are also 15 and 10 farmers who produce rice and fruits (e.g. blueberry, strawberry,and grape among others), respectively. Agricultural products such as citrus, apples, dried persimmon,and melon are not available in K City, but these products are sourced from prefectures such as
Kagoshima, Aomori, Nagano, and Ibaraki, respectively.

Fig. 2 Sticker tag produced using the label-printerSource: Market visit, June 2019

Each farmer-member has the control on the time of harvest and the amount and kinds of produce
to harvest. They can also decide on the amount per pack or set as well as on the method and place ofsorting and packing. In terms of the pricing and labeling of the products, the farmer-members candecide on the price of their produce when they print sticker tags using the official label-printer. Fig.
2 shows the label of the produce which includes farmer name, product name, production area, price,and tax. It is important for them to keep a production history record, which is required to be submitted
on a regular in order to be able to issue or print sticker tags for their products. Inside K Farmers’Market, the farmer-members personally display their produce and make placards for promotion.
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IJERD – International Journal of Environmental and Rural Development (2020) 11-2

member for five times per day via SMS based on the cashier data. This enables the farmer-members
to have the option of harvesting additional produce for the market. However, any unsold products
should be picked up by the farmers before the market closes.
The K Farmers’ Market uses Teraoka Cashier System which includes production history
recording, label printer, semi-automated cashier. In order to increase transparency, the label printerrequires submission of production history records and use of farm ID number. This also enables thefarmer-members to set their own price. Meanwhile, semi-automated cashier requires one staff per
cashier which decreases the cash handling mistakes. Although the market only accepts cash payment,
accepting credit card payments is also being considered. Moreover, self-bagging is also implemented.
In terms of information sharing, the market has an official website and Facebook page where
products, upcoming events, store schedules, activity reports, recommendations, and reviews are
regularly showcased. As the latest initiative, the market engaged in Choku-Buy (https://chokubuy.com) for promotion and information dissemination. This encourages each farmer-member toestablish individual pages on the Choku-Buy website to share updates on their farm, and eachconsumer to give feedbacks directly to farmers and use Choku-Buy Point Card.
Humble Beginnings and Challenges of K Farmers’ Market
The K Farmers’ Market was established in 2003; however, Table 1 shows the significant events andchallenges that tested their capabilities to cope. Five years after the establishment, there was a reportabout the pesticide residue on turnip. They organized a task force in order to address the situation.
They also invited experts and coordinated group studies. They had to conduct their own regularpesticide residue testing at their own expense. All these are done to regain the trust of the consumers.
Table 1 Significant events and challenges in K Farmers’ Market

Source: Market visit, June 2019

In 2010, the farmer-members faced another report on pesticide residue concerning various
vegetables. They had to close the Farmers’ Market to focus on the issue. Another task force wasformed and decided to check the production records, visit the farms, and examine the awareness ofthe farmer-members on pesticides and its usage. As this was the second time to have the incident on
pesticide residue report, they resorted to conduct regular testing on all vegetables at own expense.
By December 2010, the Farmers’ Market re-opened after testing all 150 produce which all had
negative results from pesticide residue.
Another challenge that could have destroyed their passion and motivation in sustaining local
agriculture was the Great Tohoku Earthquake in March 2011. This also caused the nuclear plant
meltdown and reports identified K City as a radiation hotspot nearest Tokyo (Japan Today, 29Ⓒ ISERD

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November 2011). This started the harmful rumors about the nuclear contamination on the produceof K Farmers’ Market which significantly affected their sales. Due to the harmful rumors and low
trust on farmers conducting the residue testing, farmer empowerment and collective action were
initiated which include inviting experts for training and seminars, conducting sampling and testing,and engaging consumers by letting them observe and understand the safety activities and procedures
done to ensure quality of their produce. These gradually increased the number of market visitors.
In 2016, farmers’ restaurant and café were established with a concept of traditional Japanesehouse. They introduced local dishes which are made and served by all female staff including thefarmers’ wives. This also aids in encouraging the consumers to buy local products and to consume
more vegetables (e.g. vegetables in season). The restaurant and café are open every day except on
Wednesdays from 11:00 AM to 03:00 PM. They offer a “ o Meat, o Fish, All Local Vegetables”
kind of buffet with drinks and desserts which utilizes 100 kinds of vegetables. They can serve
approximately 100 customers per day. The restaurant and café have also faced challenges such as tlimited kinds of local vegetables available and unstable income with only 4 hours of operation. As
part of their solution, they started offering the restaurant as an activity space after 3:00 pm.

SWOT Analysis of K Farmers’ Market
SWOT analysis (Table 2) revealed three main points. First, farmers conduct regular pesticide andradiation residue testing (SO1), but this incurs additional expenses to each farmer (WO1). If this is
not continued, the misconception among consumers that the produce is unsafe will prevail (T1) which
will lead to consumers’ distrust and eventually prefer other markets (WT1). Since the K Farmers’Market value their loyal customers and those customers who once left them, they have been
conducting testing until now.
Table 2 SWOT analysis of K Farmers’ Market

Opportunities(O)

Threats(T)

Strengths (S)Weaknesses (W)

1. Conduct pesticide and radiation residue testing
2. Provide alternative marketing channel to local
farmers and newcomers
3. Offer different activities, products and services
all year round
1. Possible misconception may prevail if notcontinued
2. New marketing channels has emerged
3. Management may not function if one role isunavailable

1. Create additional farmers’ expense
2. Experience unstable and unpredictablesupply of produce
3. Different thinking, priorities, and interestsof farmer-members
1. May result to customers distrust andeventually prefer other markets
2. Puts pressure to availability and variety ofsupply, which may result to costumer
dissatisfaction
3. Lack of successors

Source: Market visit, June 2019

Second, the provision of alternative marketing channel to local farmers and newcomers is
another strength of K Farmers’ Market (SO2). This gave farmer-members to make their own
production and marketing decisions. In other words, each farmer-member freely decides on thevolume and time of harvest. They are also free to set the amount, condition and price of each package
if they are transparent in the production process (e.g. production history). They even have the choice
to replenish their produce or not since sales update is sent 5 times a day. However, since farmers
need to collect unsold produce before the market closes, most farmer seemed not to be proactive in
replenishing their produce. Market observation and key-informant interview revealed that limited
choices of vegetables by 12 noon is a common. With this situation, K Farmers’ Market experience
unstable and unpredictable supply of produce (W2), which is getting alarming with the emergenceof new marketing channels (e.g. supermarkets with designated local vegetable area). This puts morepressure to the availability and variety of supply, which may result to customer dissatisfaction (WT2).

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In order to address this issue, there is a need to understand the farmers behavior towards K Farmers’Market and determine the impact of ICT to farmers.
Third, K Farmers’ Market have been offering different activities (e.g. harvest festival, rice
harvesting, potato harvesting), products and services (e.g. restaurant, café) all year round. This served
as a “ba” or place of action (i.e. opportunities for various stakeholders to interact, share information
and understand one another towards a better community) (SO3). However, with different thinking,priorities and interests of farmer-members, it seemed that all members are not active as mentioned
in the previous section (W3). It is expected that management may not function if one role isunavailable (WT3). Key-informant interview clarified that there may be existing differences invalues and thinking between original incorporators and current farmer-members. Therefore, aging
incorporators have the responsibility to address the possible lack of successors (W3), who will bewilling to continue for the next 10-20 years.
CONCLUSION
In general, the strategies and initiatives of K Farmers’ Market seemed to clearly reflect the farmers’
passion and motivation to achieve sustainability and resiliency under the changing environment.
However, SWOT analysis revealed that despite all the strengths it possesses and opportunities it
offers, K Farmers’ Market needs to address the lack of successors since the original incorporators
are aging, and the unstable and unpredictable supply which is further threatened by the recent
emergence of new marketing channels.
For further study, there is a need to understand the farmers behavior towards K Farmers’ Market
and determine the impact of ICT to farmers.
ACKNOWLEDGEMENTS
We wish to extend our sincere appreciation to A Corporation President, and K Farmers’ Market
manager, staffs and farmers for their support and cooperation.
REFERENCES
Brady, J. 2016. Japanese agriculture: Towards a sustainable, trade-oriented future. Asia Pacific Institute of
Research, 8-9, Japan.
Gürel, E. 2017. SWOT analysis: A theoretical review. Journal of International Social Research, 10, 994-1006.
Haga, K. 2018. Innovation in rural Japan: Entrepreneurs and residents meeting the challenges of aging andshrinking agricultural communities. Journal of Innovation Economics & Management, 1 (25), 87-117.
Harashima, A. 2006. Nousanbutsu no tainichi yunyu kakudai ni kansuru seifu sanchi no torikumi – Negi nojirei. In Hiratsuka, D. (ed.) Higashi Ajia no Chousen – Keizaitougou Kouzoukaikaku Seizou Kouchiku,
Institute of Developing Economics, Japan External Trade Organization (IDE-JETRO), 251-270 (inJapanese).
Japan Today. 2011. Radiation hotspot in Chiba linked to Fukushima. Japan Today on 29 November 2011,Retrived from https://japantoday.com/category/national/radiation-hotspot-in-chiba-linked-to-fukushima
Ministry of Agriculture, Forestry and Fisheries. 2018. The 92nd statistical yearbook, 241, Japan.
Ministry of Agriculture, Forestry and Fisheries. 2013. The damages caused by the great east Japan earthquake
and actions taken by Ministry of Agriculture, Forestry and Fisheries. Ministry of Agriculture, Forestry and
Fisheries, Japan.
Organization for Economic Co-operation and Development. 2019. Innovation, agricultural productivity andsustainability in Japan. OECD Food and Agricultural Reviews, OECD Publishing, Paris, 148.
Teramachi, N. 2004. Increased vegetable imports from China and the interests of groups involved in the tradebusiness. Kyoto Sangyo University Essays. Social Science Series, 21, 1-30.
Su, G., Okahashi, H. and Chen, L. 2018. Spatial pattern of farmland abandonment in Japan: Identification anddeterminants. Sustainability, 10, 3676 (in Japanese).

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Research article
erd

The Abundance of Hemiptera and Diptera Fauna on
Monsoon Rice at Nay Pyi Taw, Myanmar
NWE NI WIN*
Yezin Agricultural University, Myanmar
Email: nweniwinyau99@gmail.com

MOE HNIN PHYU
Yezin Agricultural University, Myanmar

THI TAR OO
Yezin Agricultural University, Myanmar

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

Accepted 12 December 2020(*Corresponding Author)

Abstract The abundance of Hemiptera and Diptera fauna studied on monsoon rice at Kyee
Inn village, Pyinmana Township, Myanmar, 2018. Insect species were collected from 56 grid
points (G) using a D-Vac vacuum suction-machine. Using simple correspondence analysis,
the peak number of Sogatella furcifera occurred in G33, the second-highest number of
Nephotettix virescens in G35, followed by Nilaparvata lugens in G30, they belong to theorder Hemiptera. In order Diptera, Aedes stimulans in G38 is the highest mean number,
followed by Chironomus sp. and Uranotaenia sapphirina from G32 and Hydrellia philippina
from G33 was observed. Correspondence analysis showed species population of order
Hemiptera is more abundant than the order Diptera. The population of major insect pest
species such as Nilaparvata lugens and Sogatella furcifera occurs at higher density during
the study period. It is due to the usage of broad-spectrum chemical insecticides in the earlycrop growth stage. In order Diptera, Hydrellia philippina is a pest on rice, but Aedes stimulans
and Uranotaenia sapphirina are not the rice pests, even though Aedes stimulans is a vector
of dengue disease. Meanwhile, Uranotaenia sapphirina feeds on the invertebrate host. The
results indicated that Hemipteran fauna is more abundant than Dipteran. We need to give
Hemiptera's serious pests more attention to provide the proper control measure for them.
Keywords Hemiptera, Diptera, monsoon rice

INTRODUCTION
Rice (Oryza sativa L.) is one of the most important crops in the developing world. Insect pests are
the significant biotic constraints in rice production throughout the country. Insects have the largest
number of species present in the rice field. More than 100 species of insects attack the world ricecrop. Almost 20 insects are considered rice pests of economic importance, including stem borers,
gall midge, defoliators, and vectors like leafhoppers planthoppers that cause direct damages andtransmit various diseases. The actual species complex differs in abundance and distribution fromlocality to locality and from year to year (Pathak and Khan, 1994). Moreover, knowledge of thespecies present and their role in the ecosystem can be essential for deciding whether to use
insecticides (Wang et al., 2000).
Dooling (1991) stated that Hemiptera is also crucial in agriculture, which causes direct damage
to plants by herbivory and indirectly by transporting diseases. Diptera is a disease vector, agricultural
pests, pollinators, and biological control agents (Wikipedia, 2020). Many aquatic organisms likehemipterans, coleopterans, dipterans are known to reproduce in paddy fields (Bambaradeniya et al.,2004). Hemipteran and dipteran insects have behavioral, cellular, and chemical strategies to evadeⒸ ISERD

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or cope with the host plant defenses making these insects incredibly destructive pests worldwide(Kaloshian and Walling, 2016). Most farmers do not realize that the role of insect species
composition found in their rice field and cannot differentiate pest or natural enemies. They often
apply pesticides when they see species of arthropods in the rice field. There is limited information or
knowledge on the Hemiptera and Diptera fauna in the study area. Therefore, it is essential to provide
necessary and critical information about the abundance of insect species as a part of a taxonomic
framework to bolster rice production in Myanmar.
OBJECTIVE
The study's objective was to investigate the abundance of Hemiptera and Diptera fauna to provide atheoretical basis for pest management's sustainable control in the study area.
METHODOLOGY
Experimental Site
The experiment was conducted in 56 farmers' fields from Kyee Inn village, Pyinmana Township,
Nay Pyi Taw, located between 19°70'66''-19°72'62'' N and 96°22'43''-96°25'73'' E. The study area 's
measure 2.4 km wide by 3.9 km long (550 ha) was selected for hemipteran and dipteran fauna in the
monsoon rice season of 2018. The rice cultivar was Manawthukha grown as farmers' usual practices
in all experimental fields.
Insect Species Sampling
Insects were collected on a 300 m - by 300 - m grid pattern, resulting in 56 grid points (G). The
species sampling was done at fortnightly intervals from 20 days after sowing (DAS) to the ripeningstage. We took five subsamples at random from each rice field. We collected samples from 56 grid
points collected near the center of the field, at least 5m away from the edge, to reduce edge effects
by using D-Vac vacuum (Insect Net-Hand Carry Model 122S, made by Rincon-Vitova Insectaries).
One sample usually came from 4-5 hills of rice plant at an early stage and 2-3 hills at maximum
tillering stage. The duration sampling time is 1 to 2 min, depending on the rice's growth stage. Eachsampling was performed three times in each field. All the collected specimens were immediatelytransferred to sample jars preserved in a labeled and filled with 90% methylated spirit (Zhang et al.,2013).
Identification of Insect Species
All the collected samples were identified to the order, family, genus, and species level using thereferences and keys; the textbooks of Insects of Australia (CSIRO, 1970), Manual of Nearctic Diptera,
Volume 1, 2, 3 (McAlpine et al., 1981), and Pests of rice and their natural enemies in Peninsular
Malaysia (Vreden and Ahmadzabidi, 1986). Species identification was done using OLYMPUS SZ
61 camera attached microscope (10 x × 45 x).
Data Analysis
Correspondence analysis of the abundance of Hemiptera and Diptera species composition was doneby the software program SAS 9.1 (SAS Institute, 2008).
RESULTS AND DISCUSSION
Correspondence Analysis of Hemiptera and Diptera Fauna in Different Grid PointsⒸ ISERD141

IJERD – International Journal of Environmental and Rural Development (2020) 11-2

Correspondence analysis was carried out to examine the most abundant insect species' mean
population in different grid points (Table 1). Average values give the number of insect species. The
ordination of other grid points (56 Grid Points) and the mean number per sample of insect species
were different. It is necessary to provide critical data in insect species abundance as a partiallytaxonomic aspect in rice production. The arthropod community is also considered an essential
component in rice ﬁeld ecosystems, showing differences in composition, diversity, and species
richness between communities of different habitats and development stages (You, 1997). The
collected Hemipteran and Dipteran are used as variables.
Table 1 Contingency table of the observed Hemipteran and Dipteran in different grids points
Order

HemipteranDipteran

Grid
Point

Nephotettix
nigropictus

Nephotettix
parvusNephotettix
virescens

Nilaparvata
lugensSogatella
furcifera

Chironomus
sp.

Aedes
stimulans

Uranotaenia
sapphirina

Hydrellia
philippina

G1
G2
G3
G4
G5
G6
G7
G8
G9
G10
G11
G12
G13
G14
G15
G16
G17
G18
G19
G20
G21
G22
G23
G24
G25
G26
G27
G28
G29
G30
G31
G32
G33
G34
G35
G36
G37
G38
G39
G40
G41
G42
G43
G44
G45
G46
G47
G48
G49
G50
G51
G52
G53
G54
G55
G56

1.41
5.00
1.73
2.45
3.87
6.00
4.24
5.39
6.00
8.06
1.41
8.31
8.19
6.16
13.19
4.47
6.86
2.00
3.32
7.62
10.63
13.11
6.78
2.00
5.83
4.24
1.73
9.33
9.38
4.12
7.75
0.00
1.41
6.48
11.40
5.66
4.36
2.00
5.57
11.22
5.10
4.80
3.00
4.36
3.16
7.07
7.87
8.94
6.93
3.32
7.81
1.00
5.00
1.73
0.00
4.36

0.00
4.58
1.00
1.73
0.00
5.29
4.58
3.16
4.47
5.66
6.08
5.66
4.12
4.58
6.71
3.61
3.46
2.00
2.45
4.12
4.69
8.60
3.74
4.69
3.46
2.65
5.66
6.08
14.66
1.41
3.61
1.00
0.00
3.61
10.05
2.45
1.41
0.00
2.45
6.00
2.83
4.36
2.45
1.41
5.10
7.55
4.24
5.20
5.10
1.73
4.58
0.00
3.16
0.00
0.00
3.32

1.73
6.32
2.65
3.46
3.61
9.54
6.78
6.08
8.37
13.60
7.48
12.85
10.54
7.75
12.69
9.00
9.75
2.65
6.63
9.70
12.88
16.00
9.06
5.57
5.48
5.00
6.48
7.87
24.04
4.69
10.54
1.41
0.00
6.16
21.31
7.81
4.24
2.83
7.21
14.25
5.48
5.92
9.43
5.20
7.55
19.05
11.83
13.96
7.48
0.00
10.77
1.41
7.21
2.24
3.16
7.21

7.94
10.63
9.95
13.45
7.48
7.14
12.21
10.30
8.31
5.57
7.35
4.00
5.29
7.81
8.06
6.86
7.28
22.25
15.23
7.94
7.21
7.42
6.78
8.06
9.70
6.56
7.68
7.48
6.24
15.62
7.62
7.28
6.56
6.63
6.86
11.22
6.86
7.00
10.86
8.66
11.09
7.00
7.07
12.08
16.94
6.00
16.16
8.77
9.33
6.24
5.20
8.12
8.00
13.53
9.43
12.37

16.28
13.67
13.08
18.73
10.00
18.47
26.17
14.42
11.87
16.46
14.53
24.82
11.70
11.31
15.75
24.54
16.46
48.85
10.20
13.27
10.72
8.12
11.05
14.59
13.19
14.70
11.87
10.82
11.05
7.00
8.00
9.22
10.58
10.95
7.14
12.04
17.41
6.32
8.94
8.89
14.49
17.80
19.62
10.15
20.98
11.31
18.33
9.17
15.52
8.66
10.63
9.06
14.11
16.31
12.12
10.30

3.61
13.08
3.87
3.16
3.87
6.00
14.90
1.41
0.00
4.24
9.00
22.52
4.90
4.90
5.20
7.94
16.67
26.04
4.36
6.78
5.00
3.46
10.91
10.77
6.08
3.00
13.75
4.47
16.28
7.94
2.83
14.39
0.00
3.16
3.87
4.90
7.14
8.00
5.66
1.41
6.71
15.36
4.90
3.32
9.64
17.20
0.00
11.70
2.00
4.80
7.48
3.16
3.16
5.57
7.81
1.41

6.56
4.00
4.00
2.45
2.45
0.00
13.30
0.00
6.48
2.65
7.14
6.93
7.75
8.66
5.00
6.08
4.36
5.39
5.10
4.69
7.00
2.00
7.62
5.00
6.63
5.29
15.56
9.43
4.24
4.58
0.00
8.77
1.73
8.19
3.74
2.65
3.46
13.00
1.73
2.00
7.21
3.00
2.65
5.10
4.69
4.69
4.00
6.00
13.00
4.80
1.73
1.41
1.00
7.14
3.16
1.41

7.28
8.77
2.24
3.74
1.00
7.42
15.68
4.24
7.00
2.65
8.49
24.27
2.45
3.61
4.47
11.96
11.96
24.08
10.10
5.66
4.12
2.45
9.59
11.96
2.45
6.63
12.25
8.77
9.75
4.36
5.92
14.70
3.16
6.08
2.00
0.00
5.00
5.00
1.41
4.90
10.25
12.73
0.00
4.80
7.28
9.33
5.10
11.31
8.19
4.24
0.00
5.29
9.49
8.83
9.33
0.00

3.00
6.40
4.24
8.89
2.65
9.06
6.56
5.48
5.10
12.69
4.12
5.83
6.00
7.42
3.74
4.00
6.86
2.24
8.37
6.63
6.93
4.00
5.66
4.90
4.24
5.00
5.29
6.71
3.87
5.48
2.83
3.87
5.20
5.83
5.10
6.32
4.24
4.36
4.69
5.83
3.16
3.74
6.93
5.83
5.48
4.69
7.21
2.45
5.00
3.46
6.32
3.87
3.00
7.68
2.24
5.57

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Correspondence analysis confirmed the peak number (0.37) Sogatella furcifera from G33, thesecond-highest number (0.30) Nephotettix virescens from G35, followed by Nilaparvata lugens(0.28) from G30, then Nephotettix nigropictus (0.20) from G22 and Nephotettix parvus (0.15) from
G29, respectively. These species belong to the order Hemiptera. However, order Diptera, the peakmean number (0.27) Aedes stimulans from G38, the second-highest number (0.24) Chironomus sp.
and Uranotaenia sapphirina (0.24) from G32, followed by the third highest mean number (0.18)
Hydrellia philippina from G33. Correspondence analysis showed that the species population of order
Hemiptera was more abundant than order Diptera. Therefore, Hemiptera was the dominant group in
the study area. Indian Hemiptera includes several species of agricultural pests that are important from
economic damage and loss to various crops. These insects act as a menace to agriculture because ofsome hemipteran insects' remarkable ability to transmit viral diseases of many plants in our country
documented by (Ghosh, 2008).

Fig. 1 Correspondence analysis of Hemiptera and Diptera species compositionin different grid points
Correspondence analysis showed that the insect pest species Sogatella furcifera and Nilaparvata
lugens had the most remarkable association with G1, G3, G4, G5, G26, G33, G37, G41, G44, G45,
G50, G52, G54, and G55, respectively. Catindig et al., (2009) documented that Brown planthoppers
transmit viral diseases while white backed plant hopper indirectly damage rice crops immensely.
Similarly, Nephotettix virescens and Nephotettix parvus were closely associated with G22, G28, G29,
G35, G46, and G48. Nephotettix virescens is a great threat to rice production because it is the mosteffective vector of rice tungro virus disease (Hibino and Cabunagan, 1986). Moreover, Chironomus
sp., Uranotaenia sapphirina and Aedes stimulans were most associated with G2, G7, G11, G12, G16,
G17, G23, G24, G27, G32, G38 and G42. However, Hydrellia philippina and Nephotettix nigropictus
were more closely associated with G8, G9, G10, G20, G25, G34, G36, G39, G40, G47, and G56,
respectively (Fig 1.). Diptera, given their diversity and abundance, drive ecosystem processes, bothon land and in water. All species are of ecological importance, although the degree of their ecosysteminfluence varies in space and time and across taxa (Adler and Courtney, 2019). The results indicatethat the mean population density of species differs widely among the different grid points. The
species richness of arthropods in the rice plantation depends on the study's location, cultivation
technique, and sampling methods (Zhang et al., 2013).
The first principal axis (Fig 1.) explains 87.31% of the total inertia and indicates the association
between insect species and different grid points. However, the second principal axis accounts for
12.69% of the total inertia and shows that insect species also contribute to the relationship. The
column categories' positions on the plot (Fig 1.) indicate that the first principal dimension is regarded
as showing a contrast among insect species populations. The second principal dimension, on theother hand, is dominated mainly by different grid points. Hence, it may be concluded that about 87%Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2020) 11-2of the given data's information can be accounted for by a contrast between the insect species
population belonging to the orders Hemiptera and Diptera. The different grid points may influence
the remaining data (about 13%).
The distance of Sogatella furcifera and G45 is quite close. Nilaparvata lugens and grid points
G5 and G44 are more intimate, and Nephotettix nigropictus was very close to G40, with all of thesebelonging to order Hemiptera. Lee and Park (as cited in May Thet Hlaing, 2018) stated that the pest
species were mainly Homoptera and dominated by Delphacidae (Nilaparvata lugens Stal andSogatella furcifera Horvath) and Cicadellidae (Nephotettix virescens), which involved more than 81
percent of pest abundance. These pests are responsible for substantial economic losses to rice yields.
Most of the farmers use broad-spectrum insecticides such as acephate, cypermethrin, carbofuran,chloropyrifos, and imidacloprid in the study area. Multiple reports indicated that white-backed
planthopper (Sogatella furcifera) and small brown planthopper (Nilaparvata lugens) had developed
resistance to chlorpyrifos, buprofezin, and imidacloprid (Matsumura et al., 2014). In the agricultural
field, the use of insecticides caused planthoppers damage. Similarly, under order Diptera, the distanceof Hydrellia philippina was quite close to G8 and G36. Ferino (1968) reported that rice whorl maggot(Hydrellia philippina) damage led to a significant reduction in productive tillers. Chironomus sp. andG12 were even closer, while Uranotaenia sapphirina closely associated with G24, G27, and G42,
respectively. Chironomids are considered potential pests, and most chironomids are root feeders(Heong et al., 1991). The resurgence of chironomids due to insecticide applications in rice has been
noted elsewhere (Takamura, 1993). Flood irrigated rice fields serve as an ideal breeding site forpotential vector mosquito species, resulting in a negative impact on human health, causing vectorborne diseases (Amarasinghe and Weerakkodi, 2014).
CONCLUSION
The present study reveals that the insect species population of order Hemiptera is more abundant
than order Diptera. The mean population density of insect species composition varies widely for thedifferent grid points. All experimental grid points were on farmers' fields; they sprayed insecticides
in the early stages of the rice plant with a lack of knowledge of these chemical insecticides' effect onpest insects' natural enemies in the field. The consequence of this action is a major population
increase in insect pests such as Nilaparvata lugens and Sogatella furcifera. The observed species
Aedes stimulans, and Uranotaenia sapphirina are not pests on rice, but they live primarily in sunlit
semi-permanent and water bodies with floating and emergent vegetation. Aedes stimulans is a vector
of dengue fever disease and negative impact on human health. The obtained results indicated thatorder Hemiptera composed of severe pests and order Diptera composed of vector-borne mosquito
species and one species feed on annelid's blood in the study area. The presences of hemipteran anddipteran species are essential things to be considered when designing pest management methods.
Moreover, these findings will provide valuable information to the rice farmers in that area for atheoretical basis to improve rice insect pests' sustainable control. Therefore, further studies should
be made on the relationships between these insects and their arthropod natural enemies to understandthe rice ecosystem and improve pest management.
ACKNOWLEDGEMENTS
The authors would like to thank the generous financial and technical training support of the Japan
International Cooperation Agency (JICA) Project for Capacity Development of Yezin Agricultural
University (YAU-JICA TCP).
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Amarasinghe, L.D. and Weerakkodi, W.G.I.S. 2014. Density and diversity of mosquito larvae associated withrice field and marshland habitats in two climatically different areas in Sri Lanka. International Journal of
Entomological Research, 2 (2), 5971.
Bambaradeniya, C.N.B., Edirisinghe, J.P., De Silva, D.N., Gunatilleke, C.V.S., Ranawana, K.B. and Wijekoon,
S. 2004. Biodiversity associated with an irrigated rice agroecosystem in Sri Lanka. Biodiversity andConservation, 13, 1715-1753.
Catindig, J., Arida, G., Baehaki, S., Bentur, J., Cuong, L. and Norowi, M. 2009. Situation of plant hoppers in
Asia. Planthoppers: New threats to the sustainability of intensive rice production systems in Asia.
International Rice Research Institute, 191-220. Los Banos, Philippines.
CSIRO (Commonwealth Scientific and Industrial Research Organization) and Scientific, C. 1970. The insectsof Australia. Melbourne University, Australia.
Dooling, W.R. 1991. The Hemiptera, Oxford University Press, New York.
Ferino, M.P. 1968. The biology and control of the rice leaf-whorl maggot, Hydrellia philippina Ferino(Ephydridae, Diptera). Philippine Agriculturist, 52 (6), 332-383.
Ghosh, L.K. 2008. Handbook on Hemipteran pests in India. Zoological Survey of India.
Heong, K.L., Aquino, G.B. and Barrion, A.T. 1991. Arthropod community structures of rice ecosystems in thePhilippines. Bulletin of Entomological Research, 81, 407-416.
Hibino, H. and Cabunagan, R.C. 1986. Rice tungro associated viruses and their relation to host plants andvector leafhopper. Trop. Agr. Res. Ser., 19, 173-182.
Hlaing, M.T. 2018. Species diversity of arthropods in intensive rice-ecosystem of Nay Pyi Taw Council Area.
Master thesis of Dept. of Entomology and Zoology, Yezin Agricultural University, Myanmar.
Kaloshian, I. and Walling, L.L. 2016. Hemipteran and dipteran pests: Effectors and plant host immune
regulators. Journal of Integrative Plant Biology, 58 (4), 350-361.
Matsumura, M., Sanada‐Morimura, S., Otuka, A., Ohtsu, R., Sakumoto, S., Takeuchi, H. and Satoh, M. 2014.
Insecticide susceptibilities in populations of two rice planthoppers, Nilaparvata lugens and Sogatella
furcifera, immigrating into Japan in the period 2005–2012. Pest Management Science, 70 (4), 615-622.
McAlpine, J.F., Peterson, B.V., Shewell, G.E., Teskey, H.J., Vockeroth, J.R. and Wood, D.M. 1981. Manualof Nearctic Diptera. Volume 1, Manual of Nearctic Diptera, 1 (27).
Pathak, M.D. and Khan, Z.R. 1994. Insect pests of rice. International Rice Research Institute, Los Banos,
Philippines.
SAS (Suite of Analytics Software) Institute. 2008. SAS/ STAT user’s guide, version 9.1. SAS Institite, Cary,
NC. USA.
Takamura, K. 1993. Population changes among chironomid species related to secondary effects of pesticide
application in rice fields. Archiv fur Hydrobiologie, 127, 205-225.
Vreden, G.V. and Ahmadzabidi, A.L. 1986. Pest of rice and their natural enemies in Peninsular Malaysia.
Pudoc Wageningen Netherlands.
Wang, C., Strazanac, J. and Butler, L. 2000. Abundance, diversity, and activity of ants (Hymenoptera:
Formicidae) in oak-dominated mixed Appalachian forests treated with microbial pesticides. Environmental
Entomology, 29 (3), 579-586.
Wikipedia. 2020. Biology of Diptera. Retrived from https://en.wikipedia.org/wiki/Biology _of_Diptera.
You, M. 1997. The species richness and diversity of the arthropod communities in rice ﬁelds. Insect Sci., 4,238-248.
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structures of organic rice ecosystems in Guangdong Province, China. Florida Entomologist, 1-9.

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Research article
erdChanges in Soil Physical and Chemical Properties with
Depth due to Megascolicidae Movements
TAKANORI KANEKO
Graduate School of Agriculture, Tokyo University of Agriculture, Japan
Email: taka1504kaneko@gmail.com

TOMONORI FUJIKAWA*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Japan
Email: t3fujika@nodai.ac.jp

MACHITO MIHARA
Faculty of Regional Environment Science, Tokyo University of Agriculture, Japan
Received 29 April 2020

Accepted 12 December 2020(*Corresponding Author)

Abstract Earthworms have significant impacts on the physical and chemical properties ofsoils. It is known that they are remarkably improving soil fertility as well as promoting plant
growth because earthworms make castings, which are rich in nitrogen, phosphorus and othernutrients. Additionally, earthworm’s movements effects soil properties by their movementsin the soil, notably soil aggregates, nitrogen and phosphorus concentration. Earthworms from
Megascolecidae family are a major earthworms found in Japan, but there is lack of knowledge
on its effect on soil properties compared to other earthworms. Subsequently, this study
discusses the changes in soil aggregates, nitrogen and phosphorus concentration changes withdepth due to Megascolicidae movements in the soil. An experiment was conducted using
cylindrical columns of 12 cm height divided into 3 layers at 4 cm interval. Additionally, twogroups were made, with litter and without litter, which were divided into subgroups withvariations in earthworm numbers. The results of aggregates showed the tendency of aggregate
formation in both the groups, with high formation rate in litter added group. The results of
NO3 and P2O5 content significantly differed among the 3 layers in the treatments. The trendof higher NO3-N and P2O5 concentration was observed in middle layer and lower layer
respectively. According to the results obtained, Megascolicidae movements effect the
distribution of nutrients in subsurface soils.
Keywords Megascolecidae, earthworm movements, soil chemical and physical properties

INTRODUCTION
It is known that earthworms improve soil structure and enhance soil productivity (Barley, 1959b;
Lee and Foster, 1991). They promote transport of nutrients and ions in subsurface soil with theirbodily movements.
Earthworms are broadly divided into two families, Lumbricidae and Megascolicidae.
Earthworms form Lumbricidae family are found in the area from temperate to polar regions ofEurope and Asia and those from Megascolicidae family are found in the area from tropical totemperate zones of East and South East Asia. Further, ecologists divide them into three groups into
anenic, epigiec and endogeic earthworms based on their habitual preferences (Bouche, 1977). Anenic
earthworms are large species, which dig and inhabit upright, make deep burrows in soil and come tosurface for feeding. Epigiec earthworms are small species, which lives and feeds on the surface ofsoil. Many literatures have been made on earthworm from Lumbricidae family on the effects of theiractivity to the soil properties. Langmaack et al., 1999, estimated that earthworm from Lumbricidae
family (Lumbricus terrestris) makes 82.3 km/ha of burrows in the agricultural field. These burrows
increase air and water permeability, transport oxygen and water and better penetration of roots of thesoil (Kavdir and Ilay, 2011). In these literatures, many researches were concentrated on the nutrientⒸ ISERD

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availability in the casts on soil surface and the large part of the effects of these casts were clarified,
but the knowledge of the effects of the cast in subsurface soil (12 cm depth) which will havesignificant roles on plant growth was limited. Therefore, this study tries to discuss the effects on soil
physical and chemical properties in different layers of subsurface soil released by epigiec earthworm
movements in subsurface soil.
OBJECTIVE
The objective of this study is to assess the changes in soil aggregates, nitrogen and phosphorus
contents with depth due to movements by epigiec earthworm from Megascolicidae family.
METHODOLOGY
Sampling of Earthworms, Soil and Litter
Epigeic earthworms from Megascolicidae family (Fig. 1) were collected from depth up to 10 cm soil
using hand-sorting method. The soil used in this experiment was Andosol, which are volcanic soils
and covers 47% of land area in Japan. The soil was passed through 2 mm sieve (Fig. 2). Litter wascollected from fallen leaves of oak and cereus trees (Fig. 3). The leaves were made into small pieces
before using it. All the samples were collected from the same field in Kanagawa prefecture, Japan.

Fig. 1 Megascolicidae used inthis study

Fig. 2 Soil used in the study Fig. 3 Litter used inthis study

Experimental Set-up and Conditions
Cylindrical columns of size 15 cm in diameter and 12 cm in height were used having surface area of
0.000018 m2 for the experimental apparatus. In the experiments, the depth of soil was set 12 cm. The
apparatus could be separated into three layers with intervals of 4 cm (Fig. 4). In this experiment, 0-4
cm is assumed as the subsurface soil. The experiments were conducted for 28 days in an incubator
whose temperature was set at 17.1 ℃ ± 0.5 ℃ which is similar to the annual average temperature of
the area where soil and litter were sampled.
In this experiment, 1.8 kg of soil was used. Patterns of soil organic matter content were set into
two groups of 0% added litter and 5% added litter. Each group was further divided into threetreatments with 0, 3 and 10 earthworms (Table 1). This experiment was designed with assuming thedensity of 1 earthworm per one column corresponding approximately 56 earthworms per one hectare.
Soil and litter were mixed thoroughly for litter added group. The three column treatments were named
from A1 to A3 for litter added group. Likewise, for 5% added litter group, treatments were named
from B1 to B3 (Table 1).
The soil in the column was saturated before the start of the experiment by capillary action for
24 hours. After saturation, the excess water was released by gravity for 24 hours. Earthworms wereput on the surface of the soil in the start of the experiment. The moisture content of soil for eachtreatment was maintained at 50 to 60%. To maintain the water content, weight of the treatments wasmeasured on daily basis and equal to lost amount of water was added.

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15 cm

4 cm

12 cm

Fig. 4 Schematic diagram ofcylindrical columns

Fig. 5 Column used in this study

Table 1 Column treatment patterns
Litter added (%)

05

Number of earthworms /cylindrical columns

Treatments

0

A1

3

A2

10

A3

0

B1

3

B2

10

B3

Sampling and Parameters Measured
Soil was sampled on 0, 7, 14 and 28 days from the start of the experiments from each layer of 0 to 4
cm, 4 to 8 cm and 8 to 12 cm randomly at 6 different points. The samples were analyzed for water
stable aggregate using Yoder’s method (Yoder, 1936), total available phosphorus using Troug
method (Troug, 1930) and Nitrate nitrogen using Cataldo method (Cataldo et al., 1975).
RESULTS AND DISCUSSION
Survival of Earthworms at Different Layer of Soil
Table 2 shows the change in survival of earthworms at the depth of 0 to 4, 4 to 8 and 8 to 12 cm in
0% and 5 % added litter group at 28 days of experiment. There was no earthworm found in 0 to 4 cm
layer in all the groups. The number of earthworms increased with depth. In 0% added litter group,
most earthworms were present at 4 to 8 cm layer. Whereas, in 5% added litter group, a greater numberof earthworms were present in 8 to 12 cm layer. In B3, 12 earthworms were seen at 28 days, forwhich an assumption was made that new earthworms were born. With the obtained results, it wasproved that the epigiec earthworm from Megascolicidae family used for this study are active insubsurface soil.
Table 2 Result of survival of earthworm at different layer of soil at 28 days
Layer (cm)

A2

A3

B2

B3

0~4

0

0

0

0

4~8

2

7

2

4

8~12

1

2

1

8

Total

3

9

3

12

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Periodic Change in Water Resistant Aggregate
The ratio of 2 mm water resistant aggregates increased with time in all layers of the treatments forboth the groups (Figs. 6, 7 and 8). High aggregate content was seen in 4 to 8 and 8 to 12 cm layers
wherethe larger number of earthworms existed. Similarly, the Mean Weight Diameter (MWD) of
100%
aggregates increased in 4 to 8 and 8 to 12 cm layers with time (Figs. 9, 10, 11 and 12). Group B
having added litter content increased aggregates content in all the three layers. It could be explainedby 80%
the activation of earthworm metabolism by the litter, which provided nutrient to the earthworm.
100%

100%

Percentage of aggregates

Percentage of aggregates

60%

80%

40%

80%

＜0.1 mm60%＜0.1 mm60%0.25＞d≧0.1 mm

20%0.25＞d≧0.1 mm

0.5＞d≧0.25 mm

40%

0%
20%

40%

0.5＞d≧0.25 mm

1＞d≧0.5 mm

1＞d≧0.5 mm

2＞d≧1 mm

2＞d≧1
mm
20%

B1
≧2 mm

0 day

0%
0 day

≧2 mm
80%

B3

≧2 mm

28 day

0%
A1

100%

B2

A2

A3

B1

28 day2＞d≧1 mm0 day

1＞d≧0.5 mm

B2B328 day0.5＞d≧0.25 mm＜0.1 mm0.25＞d≧0.1 mm

Fig. 6 Changes in aggregate percentage at 0 to 4 cm depth in A and B

100%

100%

80%

Percentage of aggregates

Percentage of aggregates

60%
80%

＜0.1 mm

40%
60%

20%

40%

0.25＞d≧0.1
mm
60%＜0.1 mm0.5＞d≧0.25 mm

0.25＞d≧0.1 mm

40%0.5＞d≧0.25 mm

1＞d≧0.5 mm

0%
20%

20%

B2

≧2 mm

0 day
0%

2＞d≧1 mmB3

28 day

≧2 mm

0%
A1

0 day

100%

1＞d≧0.5 mm

2＞d≧1 mm

B1

≧2 mm

A2

A3

B1

28 day2＞d≧1 mm0 day

1＞d≧0.5 mm

0.5＞d≧0.25 mm

B2

B3

28 day＜0.1 mm0.25＞d≧0.1 mm

Fig. 7 Changes in aggregate percentage at 4 to 8 cm depth in A and B
80%
100%

100%

Percentage of aggregates

Percentage of aggregates

60%
80%

40%

60%

20%40%
0%20%

80%

60%

＜0.1 mm＜0.1 mm0.25＞d≧0.1 mm

0.25＞d≧0.1 mm

40% mm0.5＞d≧0.25

0.5＞d≧0.25 mm

1＞d≧0.5 mm

1＞d≧0.5 mm

20%
2＞d≧1
mm

B1
0 day

0%

0%
A1

0 day

≧2 mm

A2

2＞d≧1 mm

B2

≧2 mm

1＞d≧0.5 mm≧2 mm

28 day

A3

B1
0 day

28 day2＞d≧1 mmB3

0.5＞d≧0.25 mm

B2
28 day0.25＞d≧0.1 mm＜0.1 mmFig. 8 Changes in aggregate percentage at 8 to 12 cm depth in A and BⒸ ISERD

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The results of this study show that earthworm feeds on soil and litter and releases them in theform of casts. The released casts by the assimilation with soil to form aggregates of 2 mm or larger.
This has been also showed in laboratory conditions by Kawaguchi et al., 2011, and in field conditions
by Marinissen and Hillenaar, 1997; Ketterings et al., 1997 and Arai et al., 2013. In addition,
Kawaguchi et al., 2011, found that 92% of casts weight had 2 mm or more water-resistant aggregates.
MWD (mm)

MWD (mm)0day
7day・B1
7day・B2

7day・A1
7day・A2
7day・A3
14day・A1

7day・B3

Depth (cm)Depth (cm)

0day

14day・B1

14day・B2
14day・B3

28day・B1
28day・B2

14day・A2

28day・B3

14day・A3
28day・A1

28day・A2
28day・A3

Fig. 9 Periodic changes of MWD content
in A1 to A3

Fig. 10 Periodic changes of MWD content
in B1 to B3

MWD(mm)a**b**

MWD (mm)

b**

b**

a**

b**

A**

B**

B**

0day

Depth (cm)Depth (cm)

0day

28day・B1
28day・B2
A**

B**

B**

28day・B3

28day・A1
28day・A2
α**

β**

β**

28day・A3

α*, **

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

Fig. 11 MWD content in A1 to A3
at 0 and 28 daysb*, **

b**

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

Fig. 12 MWD content in B1 to B3
at 0 and 28 days

Periodic Changes in Nitrate Nitrogen Content
The nitrate nitrogen content became higher in all three layers of treatment A2 and A3, with A3
showing comparative high nitrate nitrogen content as shown in Fig. 13. Similarly, the nitrate nitrogencontent in 5% added litter treatment B3, increased with time (Fig. 14). Nitrate nitrogen content was
highest in treatment B3 in 28 days of experiment (Fig. 16). The highest value was observed in layerof 0 to 4 cm in B3. This increase of nitrate nitrogen content could be explained by nitrification oforganic matter enhanced by microbial action present in casts of earthworms. As, B3 had the highest
amount of organic matter, it is speculated that earthworm activity was highest in this treatment,
resulting in excretion of casts and higher microbial activity. In this process, organic nitrogen getsconverted to NH4-N to NO2-N, which further changes into NO3-N. NH4-N is converted to NO2-N by
the action of ammonia oxidizing bacteria. Whereas, NO2-N is converted into NO3-N by the action of
nitrite oxidizing bacteria. Nitrifying bacteria are aerobic microbes and are active near surface of soils(Ward, 2008) which supports the result of this study where nitrate nitrogen content was high in upper
layer of soil compared to lower layers. According to Su et al., 2017, Amynthas corticis from
Megascolicidae family has nitrifying bacteria in casts. The results with high nitrate nitrogen content
in treatment with high litter content can be discussed with the fact that nitrifying bacteria gets
attached in the surface of the litter.
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NO3-N (mg/100 g)

NO3-N (mg/100 g)

Depth (cm)0day

Depth (cm)

7day・A1
7day・A2
7day・A3
14day・A1

0day

7day・B1
7day・B2
7day・B3

14day・A2

14day・B1

14day・A3

14day・B2

28day・A1

14day・B3

28day・A2

28day・B1

28day・A3

28day・B2
28day・B3

Fig. 13 Periodic changes of NO3-N content
in A1 to A3

Fig. 14 Periodic changes of NO3-N content
in B1 to B3NO3-N (mg/100 g)

b**

A**

a**

c**

B**

b**

a**

Depth (cm)Depth (cm)a**NO3-N (mg/100 g)

C**

A**

A**

B**
0day

0day
28day・B1

28day・A1

α**

β**

γ**

28day・A2

α**α**28day・B2

β**28day・A3

28day・B3

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

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

Fig. 15 NO3-N content in A1 to A3 at 28 days Fig. 16 NO3-N content in B1 to B3 at 28 days
Periodic Change in Total Available Phosphorus
High content of total phosphorus in lower layers of column was observed for treatment A3 and B3
contrasting to the results of nitrate nitrogen (Figs. 17 and 18).
P2O5 (mg/100 g)

P2O5 (mg/100 g)

0day
7day・B1
7day・B2

7day・A1
7day・A2
7day・A3

7day・B3

Depth (cm)Depth (cm)

0day

14day・B1
14day・B2
14day・B3

28day・B1

14day・A1

28day・B2

14day・A2

28day・B3

14day・A3
28day・A1
28day・A2
28day・A3

Fig. 17 Periodic changes of P2O5 content
in A1 to A3

Fig. 18 Periodic changes of P2O5 content
in B1 to B3

This tendency can be linked with high presence and activity of earthworm in lower layers. It is
speculated that high phosphorus content is caused by high phosphatase activity in earthworm casts.
High phosphatase activity results in increased inorganic phosphorus released by mineralization oforganic phosphorus. Satchell and Martin, 1984 reported high level of phosphatase activity inearthworm casts of Aporrectodea trapezoides, an earthworm from Lumbricidae family. The resultsof laboratory experiments conducted by Matsumoto and Taniguchi, 1995, hypothesized highphosphatase occurrence in earthworm leading to high phosphatase activity in earthworm casts andsurrounding soils.
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P2O5 (mg/100 g)

a**

b**

P2O5 (mg/100 g)

a**

b**

b**, *

c**, *
0day

A**

C**, *

Depth (cm)Depth (cm)

28day・B1

B**, *

28day・B2

A**

B**

C**

28day・B3

0day
28day・A1

α**

β**

γ**

28day・A2

α**

β**

α**

28day・A3

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

Fig. 19 P2O5 content in A1 to A3
at 0 and 28 days

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

Fig. 20 P2O5 content in B1 to B3
at 0 and 28 days

CONCLUSION
This study was conducted to clarify the effects of epigiec earthworm from Megascolicidae family on
soil aggregates, nitrogen and phosphorus content with their ecological behavior in subsurface soil
using column treatment in incubator. Survival rate of earthworm at different layers resulted in highearthworm number between 4 to 8 and 8 to 12 cm deep, irrespective of litter content. Water resistantaggregates (larger than 2 mm) and MWD increased with time, where the earthworm numbers were
high. Similarly, available phosphorus content was high in the layer with high earthworm numbers.
This increase can be explained with phosphatase activity in earthworm casts. High phosphataseactivity results in increased inorganic phosphorus released by mineralization of organic phosphorus.
Whereas, nitrate nitrogen was high in the upper layer having less number of earthworm. The resultsof nitrate nitrogen content would be due to the presence of nitrifying bacteria in earthworm’s casts,
which are aerobic microbes and are active near surface of soils. With the obtained results, earthworm
activity and movement showed potential for growth and development of plant by enhancing soil
structure, increasing nitrogen and phosphorus content.
REFERENCES
Araia, M., Tayasu, I., Komatsuzaki, M., Uchida., Shibata, Y. and Kaneko, N. 2013. Changes in soil aggregate
carbon dynamics under no-tillage with respect to earthworm biomass revealed by radiocarbon analysis.
Soil and Tillage Research. 126, 42-49.
Barley, K.P. 1959. Earthworms and soil fertility. IV. The influence of earthworms on the physical propertiesof a red-brown earth. Aust. J. Agric. Res., 10, 371-376.
Bouche, M.B. 1983. The establishment of earthworm communities. Earthworm Ecology. From Darwin to
Vermiculture. Chapman and Hall, 431-448.
Cataldo, D.A., Maroon, M., Schrader, L.E. and Youngs, V.L. 1975. Rapid colorimetric determination of nitratein plant-tissue by nitration of salicylic-acid. Communications in Soil Science and Plant Analysis. 6, 71-80.
Kavdir, Y. and Ilay, R. 2011. Earthworms and soil structure. Biology of Earthworms. Springer-Verlag, 39-50
Kawaguchi, T., Kyohima, T. and Kaneko, N. 2011. Mineral nitrogen dynamics in the casts of epigeic
earthworms (Metaphire hilgendorfi: Megascolecidae). Soil Sci. Plant Nutr., 57, 387-395.
Ketterings, Q.M., Blair, J.M. and Marinissen, J.C.Y. 1997. Effect of earthworms on soil aggregate stability andcarbon and nitrogen storage in a legume cover crop agroecosystem. Soil Biol., Biochem., 29, 401-408.
Lamgmaack, M. 1999. Quantitative analysis of earthworm burrow systems with respect to biological soilstructure regeneration after soil compaction. Biology and fertility of soils, 28, 219-229.
Lee, K. and Foster, R.C. 1991. Soil fauna and soil structure. Aust. J. Soil. Res., 29, 745-776.
Lunt, H.A. and Jacobson, G.M. 1994. The chemical composition of earthworm casts. Soil Sci., 58, 367.
Marinissen, J.C.Y. and Hillenaar, S.I. 1997. Earthworm-induced distribution of organic matter in macroaggregates from differently managed arable fields. Soil Biol., Biochem., 29, 391-395Ⓒ ISERD

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Matumoto, S. and Taniguchi, K. 1995. Earthworms contribution to soil fertilization. Part Ⅰ. A mutual
relationship between the available phosphate and phosphatase activity in earthworm casts. Edaphologia.
53, 19-24 (in Japanese).
Su, T., Bee, S., Ohike, T., Okanami, M. and Ano, T. 2017. Studies on the effect of earthwoms on soil
characteristics and plant growth. Memoirs of the Faculty of Biology-Oriented Science and Technology of
Kindai University, 39, 27 - 38
Truog, E. 1930. Determination of readily available phosphorus of soils. J. Am. Soc. Agron. J., 22, 874-882.
Ward, B.B. 2008.Nitrification. In Nitrogen in the Marine Environment, Elsevier, 199-262.
Yoder, R.E. 1936. A direct method of aggregate analysis of soils and a study of the physical nature of erosion
losses. Agro. J., 28, 337-351.

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Research article
erd

Postharvest Management Options to Improve Tomato Value
Chain in Cambodia
TONG SOCHEATH*Division of Research and Extension, Royal University of Agriculture, Phnom Penh, Cambodia
Email: tsocheath@rua.edu.kh

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

ANTONIO ACEDO JR.
Institute of Crop Science, University of the Philippines Los Banos, College, Laguna, Philippines
Received 23 April 2020

Accepted 12 December 2020(*Corresponding Author)

Abstract Tomato (cv. Mongal) value chain practices of a farmers’ cooperative as pilot modelin Siem Reap, Cambodia, were assessed and improved through the introduction of
postharvest technologies and best practices. The existing value chain (EVC) practices
included harvesting tomatoes at the breaker stage, use of harvesting container with smoothsurface (plastic pail), use of plastic crate in hauling harvested tomatoes to the farmers’ house
where packaging in ordinary plastic bags at 10 kg fruit per bag was done. No sorting andspecial storage were practiced except for overnight storage at ambient when harvesting wasdone in the afternoon. The packed fruit were then transported to the city market about 12 km
from the farm or 30-45 minutes ride using a motorcycle-driven carrier (locally named‘TukTuk’). Marketing tomatoes usually took half day. Using the cooperative’s simple
packhouse which linked farm production and marketing, improved value chain (IVC)
practices were introduced, including sorting to ensure more uniform quality and damage-free
fruit, sanitizing with 0.01% calcinated calcium (non-chlorine sanitizer) by dipping fruit in thesolution for 3 minutes, modified atmosphere packaging (MAP) using perforated 50 µm thicklow-density polyethylene bag at 10 kg fruit per bag, and transporting and direct retailing in
ice box using a dedicated motorcycle-driven carrier. In another set of trials, three-day storage
simulating extended period of distribution and marketing was included using ambientcondition in the EVC while in the IVC, three storage options were introduced: ice box (3 kg
ice per box with about 25 kg fruit replenished every day); low-cost cold storage using the
Coolbot chamber; or evaporative cooler (EC). Results revealed that without storage (direct
marketing after harvest) total postharvest loss was about 14% in the EVC; this was
remarkably reduced to 4% in the IVC. IVC fruit were also firmer, had higher soluble solids
and much reduced microbial load than EVC fruit. No pesticide residue was detected in both
EVC and IVC fruit. With the three-day storage, the three storage options in the IVC did not
differ much in reducing postharvest loss to about 3-6% from 22% in the EVC. IVC fruit also
ripened slowly resulting in higher firmness than EVC fruit. Other quality attributes were notaffected. Vitamin C content was slightly higher in IVC fruit than in EVC fruit. From theresults, there is potential for integrating postharvest management options in value chains to
reduce postharvest loss and enhance quality of tomatoes.
Keywords Solanum lycopersicum, value chain improvement, farm-packhouse-market
model, postharvest loss reduction

INTRODUCTION
Tomato (Solanum lycopersicum) is a major fruit-vegetable in Cambodia with production continually
expanding as a result of the introduction of improved varieties and production techniques as well as
increased market demand and entry of modern market outlets (e.g. supermarkets, hotels andⒸ ISERD

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restaurants) due to the flourishing tourism industry (Buntong et al., 2012). However, poor postharvest
practices are a serious problem resulting in poor quality perception and high postharvest losses(Genova et al., 2006; AVRDC-The World Vegetable Center, 2016). Postharvest losses vary with typeof produce, location, growing season and the value chain stage (Weinberger and Acedo, 2011; Acedo
and Easdown, 2015). Postharvest losses of tomato in Cambodia were estimated at 11-35% in Kandal
province (Genova et al., 2006), 23% in traditional and modern supply chains in Kandal and Kampong
Speu provinces (Buntong et al., 2012) and 26% in Battambang and Siem Reap provinces (AVRDCThe World Vegetable Center, 2016). Aside from poor postharvest practices and the perishable natureof fresh produce, other factors contributing to losses include the fragmented and unorganized supply
chains and the hot and humid tropical climate. Postharvest losses are often absorbed by farmers as
reduced farm gate prices and by consumers through an increased purchase price. Postharvest losses
contribute to Cambodia’s high dependence on vegetable imports from Vietnam and Thailand
estimated at about 80% of domestic consumption (Millar, 2017). As part of Cambodia’s strategic
priorities to achieve inclusive and sustainable development, domestic production and marketing of
all kinds of vegetable are being promoted in order to substitute imports (Royal Government of
Cambodia, 2018).
Postharvest losses have significant economic, social, and environmental consequences.
Globally, food loss amounts to about one-third of total production valued at almost one trillion US
dollars in annual economic losses; contributes to hunger and malnutrition; represents about 25% ofwater used by agriculture; requires cropland area the size of China; and generates about 8% of global
greenhouse gas emissions (GHG) which is the third largest after China and USA (FAO, 2013; HLPE,
2014). Reducing postharvest losses is a global agenda embedded in the United ations Sustainable
Development Goal (SDG) 12.3 which targets reducing food waste including postharvest losses by
50% by 2030 (https://sustainabledevelopment.un.org/). About half of the global food losses can beprevented with a more efficient supply chain and the saved food can feed about one billion extra
people, thereby reducing the pressure to raise more food to feed an additional two billion people by
2050. Postharvest technologies play a vital role toward this end and can enable developing countries
to improve the quality and competitiveness of their horticultural produce in domestic andinternational markets as they integrate into the world economy and global value chains proliferate.
Additionally in Cambodia, reducing postharvest losses could potentially contribute to vegetable
import substitution and self-sufficiency.
Postharvest management (PHM) is vital to reduce postharvest losses and contribute to improved
food and nutrition security through three different pathways: (1) increasing the availability of foodat farm-gate and market level, (2) reducing the price of food and thus enhancing potential access,and (3) reducing the volatility and quality of food availability (Van Gogh et al., 2017). PHM also
contributes to food safety which is the most critical dimension of food quality. If the quality has
deteriorated to a level that the food is no longer safe for human health, the food needs to be removed
resulting in quantitative food loss (Bin Liu, 2016). Economic revenues of improved PHM include
both efficiency (positive benefit-cost ratio) and effectiveness (incentives for supply chain
stakeholders to engage in PHM activities). Furthermore, PHM increases employment as farmers andother value chain agents are engaged in postharvest loss reduction activities. PHM can also reduce
GHG emission and global warming.
A value chain approach on PHM is important to effectively reduce postharvest losses (Batt andCadilhon, 2007; Van Gogh, 2017). It should target smallholders who are the dominant players in
supply chains in developing countries including Cambodia; otherwise, they would be further
disadvantaged and marginalized (Van der Meer, 2006; Chan, 2009). PHM can overcome theunderperformance in postharvest chains in terms of the loss of quantity and quality of the harvested
produce, and hence the loss of revenues and resources. Postharvest losses are not caused by one or
two specific links in the chain but are the result of an entire value chain. Tackling these losses
therefore requires a value chain approach rather than actions from a single stakeholder or a single
solution approach. The value chain approach specifies that the costs incurred in specific parts of thechain to create the added value will be sufficiently compensated by the revenues from the entire value
chain. PHM measures are stimulated when there is good prospect of obtaining the revenues inexchange for the costs and risk of investment.
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Reducing postharvest losses is context specific, and strategies to developing competitive andsustainable value chains have to be tailored to the socioeconomic and ecological environment inwhich the value chain operates. The root causes of postharvest losses can be generalizable; however,
the magnitude and causes of losses and the measures to reduce losses will differ with supply chain.
Attempting one-size-fits-all approaches can create more challenges than they address. In improving
value chains, PHM measures need to be tested before commercialization. For example, in thecabbage supply chain in Central Philippines, postharvest loss in the traditional chain was estimatedat 34% and introduction of 3-4 wrapper leaf retention and plastic crate packaging at the farm level;2-3 wrapper leaf retention, 15% alum treatment for bacterial soft rot control and plastic crate
packaging prior to transport to market; and 15% alum treatment prior to retail reduced losses to 3%,
6% and 11%, respectively, or a total loss of 20% (Gonzales and Acedo 2016). In the modern chain
involving supermarkets, total loss was 25%, and introduction of 3-4 wrapper leaf retention and plastic
crate packaging at the farm level; 2-3 wrapper leaf retention, 15% alum treatment and plastic crate
packaging prior to transport to market; and 15% alum treatment and individual plastic film wrapping
prior to supermarket display reduced losses to 3%, 7% and 6%, respectively, or a total loss of 16%.
With the introduction of the different PHM measures, net income and return on investment increased.
In Cambodia’s tomato traditional chain in Kandal province, improved packaging (20 kg capacity
plastic crate with modified atmosphere packaging or MAP using 50 μm-thick low density
polyethylene or LDPE), precooling (5 min dip in 5oC water) and sanitizing (2 min dip in 200 ppm
chlorine solution) at the farm level decreased fruit damage at the wholesale and retail stages andreduced weight loss at the retail stage by about two-fold compared to that of fruit conventionally
packed in 20 kg capacity 50 μm-thick high density polyethylene (HDPE) and without precooling andchlorine treatments (Buntong et al., 2013). In the tomato modern chain in Kampong Speu province
wherein only one intermediary (collector-wholesaler) was involved between farmers andsupermarkets, MAP was only required, with 11 μm-thick film overwrap being more effective thanLDPE in reducing weight loss and retarding fruit ripening.
In the present study, the existing value chain of tomato in Siem Reap province was improvedby introducing selected PHM techniques in two scenarios, with and without storage options tosimulate temporary holding prior to marketing and immediate marketing after harvest, respectively.
Postharvest loss was quantified and fruit quality (physicochemical and food safety attributes) was
determined.
OBJECTIVE
The study aimed to determine the effectiveness of selected PHM techniques in improved value chain
in reducing postharvest loss and enhancing physicochemical quality of tomato and assess thecomparative advantage of improved value chain over the existing value chain with and without astorage component.
METHODOLOGY
Tomato fruits cv. Mongal at the breaker to turning stage were sourced from local farms of farmermembers of a cooperative in Siem Reap. The harvested fruit were placed in plastic crates and hauledeither to the farmers’ house representing the existing value chain (EVC) or to the cooperative’s simple
packhouse located nearby representing the improved value chain (IVC). Ten kg fruit were used foreach treatment per replicate. Three replications were used.
Experimental Trials Without Storage Component
In the EVC, after arrival at the farmers’ house, tomatoes were packed in ordinary plastic bags at 10kg fruit per bag without sorting or grading as usually practiced. The bags of fruit were thentransported to Siem Reap city wet market using ‘TukTuk’ (motorcycle-driven rickshaw) about 12 km
away or 30-45 min travel time. After the usual half day marketing period, the fruit were assessed forⒸ ISERD

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losses and quality attributes.
In the IVC, after arrival at the simple packhouse, the fruit were sorted and only defect-free fruit
were used. The sorted fruit were sanitized by dipping for 3 min in 0.01% (100 ppm) calcinatedcalcium (CCa) solution which was followed by rinsing in clean water and air-drying. The fruit werethen packed in MAP (50 μm-thick LDPE) at 10 kg fruit per bag and placed in 25-kg (30 x 30 x 40cm) Styrofoam box with 1 kg ice (ice box) for transport to Siem Reap in dedicated ‘TukTuk’ for
direct retailing and after half day, the fruit were assessed for losses and quality attributes. All
treatments were replicated three times.
Experimental Trials with Storage Options
The same procedure as in trials without storage component was followed except that a 3-day storage
period was included prior to transport to Siem Reap market to simulate temporary holding before
marketing. In the EVC, the 3-day storage period was done at ordinary ambient condition. In the IVC,
three storage options were tested; low-cost cold storage using the Coolbot chamber, storage inevaporative cooler, and storage in 25-kg ice box with 1 kg ice per box per day. All treatments werereplicated three times.
Data Gathered
Postharvest loss: This was determined as the sum of percent outright volume loss, percent weightloss and percent loss of damaged fruit which were still marketable. After the half day marketing
period and storage (for trials with storage component), non-marketable fruit due to rotting, breakage
and/or over-ripening were weighed and expressed as percentage of the initial weight to represent theoutright volume losses. Weight loss was also taken as percentage of the initial weight. For damaged
fruit that were still marketable, they were subjected to evaluation of price reduction by 5 trained
panelists. The magnitude of price reduction was expressed as percentage of the price of sound or
undamaged fruit to represent equivalent loss of damaged but still marketable fruit.
Fruit quality attributes: Red-ripe fruit were counted and expressed as percentage of the total
number of fruit samples per replicate. Firmness was measured non-destructively using the Fruit
Hardness Tester (TR Turoni, Italy). Total soluble solids of the fruit juice was determined using a
digital refractometer while juice pH was measured using an electronic pH meter (Hanna Instruments).
Vitamin C was analyzed following the 2, 6-Dichloroindophenol Titrimetric method and the result
reported as mg/100g of tomato fruit (AOAC, 2006).
Food safety attributes: Pesticide residue analysis was performed using the GT Rapid Pesticide Test
Kit (Bangkok, Thailand). Microbial analysis determined the total bacteria (total plate count),
coliform and E. coli counts. Triplicate 25g fruit samples were placed in Stomacher for 2 min and thensubjected to serial dilution using sterile distilled water under aseptic condition in a laminar flow
cabinet. Triplicate aliquot of 0.1 ml was aseptically micropipette and placed in a petri dish with plate
count agar. The petri dishes were then placed in an incubator at 35oC for 24 hours and colony forming
units (CFU) were counted. For coliform enumeration, violet red bile agar (VRBA) was used. The
plates were incubated in 35 ± 2 ∘C for 24 hours and red colonies were counted. For E. coli analysis,
25g fruit samples were mixed with 225 ml saline water and placed in Stomacher for 2 min and addedwith 9 ml EC broth before serial dilution. Aliquots of 0.1 ml were aseptically pipetted out and placedin E. coli agar plates followed by incubation at 44oC for 24 hours. Microbial counts were determinedusing dilution plates with 15–300 colonies expressed as colony forming units per ml (CFUml−1).
When CFU exceeded 300 per plate, counts were taken from four 1-cm squares per plate. Logarithmicvalues of counts (logCFUml−1) were computed for every plate.
Storage conditions: Temperature and relative humidity (RH) during storage were measured using
an Infrared Temperature-RH meter.
Statistical AnalysisⒸ ISERD

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All experimental trials were conducted in completely randomized design with three replications. Data
were subjected to analysis of variance and treatment mean comparison by least significant difference(LSD) test using the SAS Statistical Package.
RESULTS AND DISCUSSION
Value Chains without Storage Component
Postharvest loss: Postharvest loss in both EVC and IVC was due to the combination of weight loss,
outright volume loss and equivalent loss of price reduction of damaged but still marketable fruit(Table 1). However, EVC had much higher weight loss (3.7%), outright volume loss (4.8%) andequivalent loss of damaged fruit (5.1%) compared to that of IVC (1.6%, 1% and 0.9%, respectively).
Overall, the total postharvest loss in the EVC was 13.6%, which was about four times higher thanthat in the IVC (3.5%). Several factors contribute to the reduction of postharvest loss in the IVC. The
temperature of the ice box (21oC) used during transport of tomatoes to market was much lower while
RH (100%) was much higher than that in the EVC (ambient, 29oC and 60% RH). Low temperatureand high humidity are known to reduce water loss which is mainly responsible for weight loss (Nunes,
2008; Holcroft, 2015). The ice box in the IVC may have also protected the fruit from damage more
effectively being a more rigid container than the plastic bag in the EVC during transport andmarketing. In addition, sorting, CCa sanitizing and MAP in IVC may have contributed to postharvest
loss reduction as previous reports indicated (Kumar et al, 2015; Arah et al., 2016). Specifically intomato, MAP has been found to be very effective in reducing weight loss (Gautam et al., 2017;
Rahman et al., 2017; Seng et al., 2017).
Table 1 Postharvest loss of tomato in existing value chain (EVC) and improved value
chain (IVC) without storage component
Parameter
A. Weight loss, %B. Outright volume loss, %

EVC
3.7
4.8

IVC
1.6
1.0

ANOVA1****

C. Damaged fruit, %D. Price reduction of damaged fruit, %E. Equivalent loss of damaged fruit, %F. Total postharvest loss (A+B+E), %

23.8
21.0
5.1
13.6

4.2
21.0
0.9
3.5

**
**
**

Fruit quality: No fruit turned full ripe in both EVC and IVC as transport and marketing were doneon the same day of harvest (Table 2). Vitamin C content and pH were also statistically similar
between EVC and IVC fruit. However, IVC fruit were significantly firmer than EVC fruit. Total
soluble solids content was also significantly higher in IVC fruit than in EVC fruit. These responses
suggest slowed metabolic activity in the IVC fruit which could have been induced by low temperaturein the ice box and MAP as also found in earlier studies (Beckles, 2012; Facundes et al., 2015; Gautam
et al., 2017; Rahman et al., 2017; Seng et al., 2017).
Food safety: No pesticide residue was detected in both EVC and IVC fruit (Table 2). However,microbial load was remarkably reduced in IVC fruit with aerobic bacteria (total plate count) of 2.95
log CFU/g and non-detectable level of coliform bacteria and E.coli. In contrast, EVC fruit had 4.02
log CFU/g aerobic bacteria, 2.85 log CFU/g coliform bacteria and 1.48 log CFU/g E. coli. Acceptablelevels for food safety include <4.0 log CFU/g aerobic bacteria, <2.0 log CFU/g coliform and no E.
coli. IVC fruit met these acceptable microbial levels for food safety while EVC fruit did not. This
result can be attributed to the CCa sanitizing treatment in the IVC fruit. The effectiveness of CCa
sanitizing in reducing the microbial load on tomato and other vegetables was obtained in previous
studies (Ahmed et al, 2017a, 2017b; Rahman et al., 2017).

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Table 2 Quality attributes of tomato in existing value chain (EVC) and improved value chain(IVC) without storage component
Parameter
Full-ripe fruit, % of total
Firmness, nondestructive, Shore
Total soluble solids, %pH
Vitamin C content, mg/100g FW
Microbial load
Total plate count, log CFU/g
Coliform, log CFU/g
E. coli, log CFU/g
Pesticide residue, GT Rapid Test

EVC
0
122
5.2
4.3
9.3

IVC
0
133
5.8
4.4
9.3

4.02
2.85
1.48
negative

2.95<1.0 (0)<1.0 (0)negative

ANOVA1
*
**
ns
ns
**
**
**

Value Chains with Storage Options
Postharvest losses: Total postharvest loss was very high in the EVC (21.6%) due to high weightloss (11.1%), outright volume loss (7%) and equivalent loss of damaged fruit (3.5%) (Table 3). In
the IVC, total loss was comparable among the three storage options and ranged from 2.5-6.1%
consisting of 1.9-2.8% weight loss, 0-2.8% outright volume loss and 0.6-0.9% equivalent loss ofdamaged fruit.
Table 3 Postharvest loss of tomato in existing value chain (EVC) with 3-day ambient storageand improved value chain (IVC) with 3-day storage in ice box, Coolbot chamber or
evaporative cooler (EC)Parameter
A. Weight loss, %B. Outright volume loss, %C. Damaged fruit, %D. Price reduction of damaged fruit, %E. Equivalent loss of damaged fruit, %F. Total postharvest loss (A+B+E), %EVC-

IVC-iceambient
11.1a
7.0a
17.4a
21.0
3.5
21.6a

box
2.4b
2.8b
4.7b
21.0
0.9
6.1b

IVC-Coolbot
1.9b
0.0b
3.2b
21.0
0.6
2.5b

IVC-EC
2.8b
0.0b
3.0b
21.0
0.6
3.4b

Table 4 Temperature and relative humidity (RH) during 3-day storage at ambient inexisting value chain (EVC) and in ice box, Coolbot chamber or evaporative cooler(EC) in improved value chain (IVC)
Value chain and storage option
EVC – ambient storage
IVC – ice box storage
IVC – Coolbot storage
IVC – EC storage

Temperature (oC)
28-33
20-23
14-17
21-26

RH (%)
58-78
85-10073-10079-100Weight loss reduction in the IVC can again be attributed to the use of MAP as well as the lower
temperature and higher RH in the three storage options (Table 4), which are conducive to fruit water
retention as water loss is the primary cause of weight loss of fruit and vegetables. Other metabolic
activities, particularly respiration rate are also reduced under MAP and low temperature conditions.
Earlier, MAP and Coolbot storage were found to reduce weight loss of tomatoes (Gautam et al.,2017a; Rahman et al., 2017; Seng et al., 2017). The reduced outright volume loss and damage
incidence in IVC fruit were due to fewer fruit that turned overripe and diseased during storage andlower incidence of mechanical damage compared to that of EVC fruit.
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Fruit quality: The three storage options in IVC slowed the rate of ripening depicted as much lower
number of fruit that fully ripened after storage (3.9-10.5%) as compared to EVC fruit (40.9%) (Table5). Fruit firmness was higher in IVC with Coolbot or EC storage relative to that of EVC fruit and
IVC with ice box storage. High firmness indicates lower degree of ripening in which softening is amajor indicator. Total soluble solids, pH and vitamin C content did not significantly differ with value
chain and storage option (Table 5). Total soluble solids ranged from 3.8-4.4%, pH from 4.3-4.4, andvitamin C content from 17.7-23.4 mg/100g fresh weight. The results show the remarkable effect of
IVC with storage options was on the retardation of fruit ripening. Earlier studies showed that MAP
in combination with Coolbot storage delayed ripening of tomatoes (Seng et al., 2017). MAP
atmosphere of low oxygen and high carbon dioxide together with low temperature are known to
inhibit physiological process including ripening in harvested produce.
Table 5 Quality attributes of tomato in existing value chain (EVC) with 3-day ambientstorage and improved value chain (IVC) with 3-day storage in ice box, Coolbot
chamber or evaporative cooler (EC)Parameter
Full-ripe fruit, % of total
Firmness, nondestructive, Shore
Total soluble solids, %pH
Vitamin C content, mg/100g FW

EVCambient
40.9a
83.3b
3.8
4.3
17.7

IVC-ice
box
3.9b
96.9b
4.0
4.4
20.7

IVC-Coolbot

IVC-EC

3.9b
113.7a
3.9
4.3
23.4

10.5b
114.2a
4.4
4.4
21.9

CONCLUSION
Improving tomato value chains with the infusion of postharvest technologies and best practices, suchas sorting, non-chlorine sanitizing using CCa, MAP, storage techniques, and cold packing fortransport and marketing, proved to be highly promising in reducing postharvest losses and enhancing
fruit quality and food safety. Considering that postharvest loss reduction is context specific, it isimportant to examine existing value chains and know the deficiencies in order to identify, test andadopt postharvest management measures.
ACKNOWLEDGEMENTS
This research is made possible by the generous support of the American People provided to theCenter of Excellence on Sustainable Agricultural Intensification and Nutrition (CE SAIN) of theRoyal University of Agriculture through the Feed the Future Innovation Lab for Collaborative
Research on Sustainable Intensification at Kansas State University funded by the United States
Agency for International Development (USAID) under Cooperative Agreement No. AID-OAA-L14-00006. The contents are the sole responsibility of the authors and do not necessarily reflect theviews of USAID or the United States Government. Many thanks also go to The World Vegetable
Center-USAID Packehouse project for research site support.
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Research article
erd

Assessing the Yield of a High Yielding Rice Variety, Byaw
Htun, Planted Using the Cut-stem Transplant Method andCultivated in a Deep-water Area, Bago Region, Myanmar
YU MON*
Yezin Agricultural University, Nay Pyi Taw, Myanmar
Email: yumonseven@gmail.com

YOSHINORI YAMAMOTO
Yezin Agricultural University, Nay Pyi Taw, Myanmar

MIE MIE AUNG
Yezin Agricultural University, Nay Pyi Taw, Myanmar
Received 20 January 2020

Accepted 12 December 2020(*Corresponding Author)

Abstract Among the five rice ecosystems in Myanmar, submerged and deep-water areas
occupy 13.5% of the total cultivated area. If flooding occurs, most rice varieties elongate andlay flat after the water recedes. In such a situation, the lodged stems are cut and transplanted
without roots. This cut-stem transplant (CST) method is practiced locally in Ywa Houng
village, Thanatpin Township in the Bago Region, using deep-water rice (DWR) varieties suchas Pawsan and Yoesein in deep-water areas. However, a high yielding variety, Byaw Htun,
is cultivated in the shallow-water areas by using direct seeding (DS) or the normaltransplanting (NT) method. Unusual levels of flooding in 2018 resulted in almost all of the
fields being subject to deeper water conditions than normal in Ywa Houng village. The
highest flood level occurred on 19th July, with a 45cm depth recorded, in what is normally ashallow area (normally less than 25cm depth) and the flood peaked for about 25days. Hence,transplanting of Byaw Htun was delayed until the 10% heading stage in the nursery. Thus,
farmers tested the CST method in place of NT method in Byaw Htun. This study examined
to clarify the growth and yield of CST method for the Byaw Htun variety. Byaw Htun CSTplants exhibit plant growth and yields comparable to those of DS plants. In addition, the yieldof Byaw Htun CST was similar to, or higher than those of Pawsan and Yoesein CST.
However, the harvesting of Byaw Htun CST took place far later than that of DS areas.
Consequently, it was found that CST can be applied for Byaw Htun varieties when the plants
were damaged by flooding, but due to delays in harvesting, the application of this methodshould be considered in relation to any subsequent crops to be cultivated.
Keywords cut-stem transplant, deep water rice, direct seeding, high-yielding rice variety,submerged and deep-water areas

INTRODUCTION
Rice is cultivated on over 7 Million ha in Myanmar, which is more than half of the arable land. There
are five rice ecosystems that have been described for Myanmar. These are lowland rain-fed andirrigated, flooded, deep-water, upland and sea water intrusion areas (MOALI, 2015). Among them,flooded and deep-water areas occupy 13.5% of the total area under rice cultivation (Rice Division,2016). Therefore, construction of flood protection measures, the growing of flood tolerant rice
varieties and/or the development of climate resilient cultural practices are necessary to sustain riceproduction in these areas.
The conventional rice crop establishment methods used throughout the world are direct seeding(DS) and transplanting (NT). In the deep-water areas, dry seeding is fairly common, but transplanting
or double transplanting is practiced in some flooded area in Asia (De Datta, 1981). Likewise, there
is a locally used and adapted method in accord with flooded conditions employed in Ywa HoungⒸ ISERD

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village, Thanatpin Township in the Bago region (Mon et al., 2019a). Ywa Houng is situated at the
Sittaung River basin area, and monsoon flooding occurs frequently. Therefore, a high yielding
variety (HYV) such as Byaw Htun, also a moderate flood tolerant variety, is cultivated in shallowwater areas and photoperiod sensitive deep-water rice varieties (DWR) such as Pawsan and Yoeseinin the deep-water areas.
Normally, DS and NT are undertaken in shallow-water areas. Seeding is done after land
preparation, which starts when the soil moisture content is sufficient for land preparation.
Transplanting in NT method will be carried out when the seedlings are about 35-40 days old.
However, seeding time will vary from field to field and depends on the water availability in thenursery field, adjustments being made to coincide with a suitable depth of water in the fields fortransplantation, and expected moisture availability for a second crop such as legumes, which requiresufficient residual soil moisture. If a second crop will not be cultivated, seeding time will likely be
postponed until the water recedes, to escape the possibility of flood damage.
For deep-water areas, dry seeding is done in April-May after the first flash of monsoon andwater levels start to increase when the seedlings are 1.5 months old. If the plants are not damaged byflooding, NT is followed. However, if flooding occurs, the plant will respond by elongation of thestem and laid flat after the water recedes. In such a case, the lodged stems are cut and transplanted
by using a transplanting fork and the cut-stem transplant method (CST) is practiced (Mon et al.,2019a).
Due to torrential rain in the 2018 monsoon season, abnormal flooding occurred even in
relatively higher-level fields, and transplanting had to be delayed until the growth of Byaw Htun in
the nursery field reached the late booting stage. Hence, farmers tested the CST on this variety in 2018.
Previously CST had only been applied to the DWR varieties such as Pawsan and Yoesein in 2016
and 2017 (Mon et al., 2019a and b), but a HYV, Byaw Htun was planted with the CST method inthat 2018 monsoon season. Hence, this survey was conducted with the following objectives.
OBJECTIVE
The objectives of this study are (1) to clarify the growth and yield performance of CST comparing
with DS planting for Byaw Htun and (2) to compare the yield of CST for Byaw Htun with DWR
yields for Pawsan and Yoesein.
METHODOLOGY
The survey was conducted in Ywa Houng village, Thanatpin Township where the CST method islocally practiced. The location of each harvested field is shown in Fig 1. The water depth wasrecorded at 2 days intervals, starting from 9th June to the 10th November 2018, by setting of threemarking posts at the diagonal of each field. The water depths were measured in 2, 2 and 3 fields forshallow, medium-deep and deep-water areas respectively (Fig 1). Changes of water depth are shownin Fig 2. The water depth was 3, 5 and 10cm in the shallow, medium-deep and deep-water areas at
the beginning of June (9th June) (160 calendar days). The water level gradually increased and thepeak flooding occurred on 17-19th July (198-200 calendar days) with depths of 45, 55 and 85cm
respectively, in each area. Flooding was stagnant for 25 days until 14th August (226 calendar days)
and after that, the water depth gradually decreased and finally receded by the end of October (304
calendar days). The seeding date, transplant date and the harvest date of all varieties are shown in
Table 1. Although the seeding of Byaw Htun CST was 67 days earlier than that of DS, harvesting
was 7 days later. Moreover, the seeding of Byaw Htun CST was 25 days and 18 days later while theharvest date was 26 days and 15 days earlier than those of Pawsan and Yoesein CST. In terms offertilizer application, Byaw Htun DS and CST fields were applied with urea at 62 days after seeding,and 14 days after transplanting (DAT) with the rate of 21 kg ha -1 and 42 kg ha-1, respectively.
Similarly, Pawsan and Yoesein CST were applied with urea at 15 DAT and 16 DAT with the rate of
63 kg ha-1 and 42 kg ha-1, respectively.

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Sampling was done at harvest in farmers’ fields by sampling seven 1m2 plots in each field along
the transverse of the field’s diagonal to determine the yield rates, and hill density was recorded atthese plots. In addition, samplings of 10 hills for each 1m2 plot in the DS fields and 5 hills each for
the CST fields were randomly excavated near each plot, to measure the growth and yield components.

○ Byaw Htun DS● Byaw Htun CST ▲ Pawsan CST■ Yoesein CST

Fig. 1 Map of the sampling plots situated in north west part of Ywa Houng village

Continuous thick line: deep-water area, Dotted line: medium-water area, Continuous thin line: shallow-water area.

Fig. 2 Changes of the water depth at three locations of the paddy fields in Ywa Houng village,
Thanatpin Township, Bago Region, Myanmar (2018)
Table 1 Outline of cultivation methods of Byaw Htun, Pawsan and Yoesein
Seeding

Growth stage
at transplant

Harvestdate

Growthduration(days)*--

20-Nov

116

96

24-Aug10% heading

27-Nov

191

224

129

1-Sep

Tillering

23-Dec

242

103

117

27-AugTillering

12-Dec224

Cultivation
methodMethodDate

Seedling Transplant
Rate
date
(kg/ha) age (days)

DS

WSR

27-Jul

103

-

CST

WSR

20-May103

PawsanCST

DSR

25-AprYoesein

CST

DSR

2-May

Varieties

Byaw
Htun

*: days from seeding to harvest, WSR: Wet seeded rice, DSR: Dry seeded rice, DS: Direct seeding,
CST: Cut-stem transplant

The plant samples were washed for removing the soil and hung for one week. After that, thegrowth parameters and yield components were measured. When measuring the growth parameters in
CST, the two types of plants were observed; the main stem existing, and the main stem died and only
the tillers existing. About 25% of the plant samples in Byaw Htun CST were the main stem died. TheⒸ ISERD

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plants of which the main stem died were skipped to count the number and the length of elongatednodes. For statistical analysis, the average value of each fields resulting from 7 harvested plots was
regarded as one replication. The data were analyzed by using Statistix version 8.0 and mean
separation was done at Least Significant Distance (LSD) at a 5% level.
RESULTS AND DISCUSSION
Comparing the Growth and Yield of CST and DS in Byaw Htun
The internode elongation patterns of CST and DS in Byaw Htun are shown in Fig 3 (A). In both CST
and DS, the basal internodes (1st to 3rd) were almost the same length and after that there was anincrease from 4th internode to succeeding nodes. However, the basal internodes’ lengths of DS wereshorter than comparable nodes of CST plant. It showed that a DS plant was not affected by flooding
at the vegetative stage. Because, the DS fields were located on the river bank, drainage of excesswater was easier (Fig 1) and seeding was done after flooding.
The growth parameters of Byaw Htun DS and CST are shown in Table 2. The plant length, culm
length, panicle length, the number of elongated nodes and the number of roots per hill of CST weresimilar and not significantly (p<0.05) different than those for DS plants. All the shoot dry weight (g)showed no significant difference except the shoot dry weight per stem. Yields and yield components
are shown in Table 3. The hill density of CST (29.2) was about half of DS (63.6). However, thenumber of panicles per hill was higher in CST. The number of grains per panicle was not statisticallydifferent between the two methods. In addition, filled grain (%) and 100 grains weight were notsignificantly different, as well. Finally, the yield (g/m 2) of CST (412.7 g/m2) was not significantly
different from that of DS (400.3 g/m2). Although, the grain yield of Pawsan DS was lower than thatof CST in Ywa Houng village (Mon et al., 2019b), similar yield in Byaw Htun DS and CST were
due to the field location and cultivated condition. DS in this experiment was cultivated in the shallow
area, not affected by flooding and being able to apply fertilizer during the plant development.
Therefore, it could produce the plant growth and yield comparable to that of CST.
Internode number*

12

(A)

8
4

0
0

10

20

30

40

50

Internode number*

Length of elongated internode in Byaw Htun (cm)
DS
CST

12

(B)

8
4
0

0

10

20

30

40

50

Length of elongated internodes (cm)
Byaw Htun
PawsanYoeseinFig 3 Internode length of each elongated internodes of DS and CST in Byaw Htun (A)and CST in Byaw Htun, Pawsan and Yoesein (B)* Node number count from the stem base

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Despite the yields of these two methods were similar, the growth duration of CST was 75 days
longer than that of DS (Table 1). Because, Byaw Htun was photoperiod insensitive HYV andmaturity was depended on the growth duration. After transplantation, some of the main stem diedand the tillers were produced from the remaining nodes of the stem. CST plants reset the growthfrom the tillering stage although it was transplanted at 10% heading stage. Therefore, the growthduration was longer than that of DS. In addition, CST needed high cultivation cost especiallytransplantation cost than that of DS. Therefore, in consideration of the cost and labor for the CSTtransplantation and the effective use of the paddy field, CST in Byaw Htun would not be applicablein the area where the flooding is not use to occur.
Table 2 The plant growth parameters of Byaw Htun cultivated with direct seeding andcut-stem transplant method
Cultivation
Plant
methodlength(cm)DS
CST

108.5a98.7aCulm
Length
(cm)
84.0a
76.6a

PanicleLength (cm)

No. of
nodes

24.5a
21.4a

7.2a
6.9a

Shoot dry weight (g)No. of roots
per hill(/stem) (/hill)(/m2)
252.1a474.9a

6.9a
4.6b

28.6a
19.1a

1038.1a816.2a*DS: Direct seeding, CST: Cut-stem transplant, Values followed by the same letter within each column do not different at
p<0.05 by using statistix version 8.0

Table 3 Yields and yield components of Byaw Htun cultivated with direct seeding andcut-stem transplant method
VarietyHilldensityNo. of panicle
per hill

No. of grains
per panicle

Filled grain(%)

100 grains
weight (g)Yield(g/m2)

DS
CST

63.6
29.2

2.8
6.7

166.2
138.6

63.78
72.06

2.34
2.26

400.3
412.7

*DS: Direct seeding, CST: Cut-stem transplant, Values followed by the same letter within each column do notdifferent at p<0.05 by using Statistix version 8.0.

Comparing the Growth and Yield of Byaw Htun CST with those of Pawsan and Yoesein
The pattern of internode elongation among CST is shown in Fig 3 (B). The internode elongation
patterns of Byaw Htun, Pawsan and Yoesein CST were similar in that the internode length from the
1st to 3rd nodes were short and then the length gradually increased from the 4th to the higher nodes. It
showed all CST developed under similar field condition. However, the number of elongated nodes
in Byaw Htun (6.9 nodes) was less than those of Pawsan (8.2 nodes) and Yoesein (8.7 nodes) and it
could depend on the plant type. Byaw Htun was a photoperiod insensitive HYV while the other 2varieties (Pawsan and Yoesein) were photoperiod sensitive DWR. There was a correlation between
the number of elongated internodes and the vegetative growth period in DWR and local rice varieties,
while no correlation was found in the semi-dwarf cultivar (Hamamura, 1978). Hence, the number of
elongated nodes of Byaw Htun might be expected to be less than those of Pawsan and Yoesein. In
addition, the younger seedling age and the shallower field condition in Byaw Htun causes a smaller
number of elongated nodes than DWRs.
The growth parameters of Byaw Htun and Pawsan are compared in Table 4. Among the plants
following CST method, plant length, culm length and number of nodes of Byaw Htun were the lowest
while those of Pawsan and Yoesein showed a very similar value. However, the panicle length (cm)of Byaw Htun was not significantly different from those of Pawsan. The number of roots per hill of
Byaw Htun was the lowest, although it was not significantly different from Pawsan. The shoot dry
weight per stem and per hill of Byaw Htun were significantly less than those of Pawsan, though theshoot dry weigh per m2 of Byaw Htun was not significantly different due to higher hill density in
Byaw Htun. The yields and yield components are shown in Table 5. Among the varieties, the hill
density of Byaw Htun was the highest followed by Yoesein and Pawsan. In contrast to that, thenumber of panicles per hill of Byaw Htun was significantly lower than other varieties. Whereas, theⒸ ISERD

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number of grains per panicle of Byaw Htun was statistically higher than that of Pawsan. Filled grain(%) of Byaw Htun and Yoesein was higher than that of Pawsan. Because the grain filling period of
Byaw Htun was earlier than those of Pawsan and Yoesein by 26 days and 15 days, the availability ofsoil moisture for grain filling of Byaw Htun was higher than those of Pawsan and Yoesein. However,the 100 grains weight of Byaw Htun was the lowest due to small grain size. Yields (g/m 2) of Byaw
Htun (412.7) was the highest, followed by Yoesein (291.9) and Pawsan (286.7) although this did not
represent a significant difference between Byaw Htun and Pawsan. Because of the earlier maturity
in Byaw Htun, the moisture availability at grain filling would be higher than those of Pawsan and
Yoesein. In some years, the rainfall finishes early and moisture deficit affecting the grain yield occur
in the late harvested varieties especially Pawsan. Under such condition, Byaw Htun would produce
significantly higher yield than that of Pawsan particularly in Ywa Houng village where no irrigatedwater was available for grain filling. Therefore, Byaw Htun can be followed with CST in the deepwater area if the flood damage occurred.
Table 4 The growth parameters of Byaw Htun, Pawsan and Yoesein cultivated with
cut-stem transplant method
Variety

Plant

Culm

Paniclelength (cm) Length (cm) Length (cm)

No. ofnodes

No. ofShoot dry weight (g)roots per(/stem) (/hill)
(/m2)
hill

Byaw Htun

98.1b

76.6b

21.5a

6.9b

474.9a

4.6b

28.6b

816.1aPawsan141.5a117.4a

24.1a

8.2a

561.5a

7.0a

66.1a

867.3aYoesein*

152.5

127.5

24.2

8.7

566.9

5.9

41.6

842.3

Analysis was done for Byaw Htun and Pawsan only by using statistix version 8.0, * No replication. value followed by thesame letter within each column do not different at p< 0.05.

Table 5 Yields and yield components of Byaw Htun, Pawsan and Yoesein cultivated with
cut-stem transplant method

Byaw Htun

Hilldensity
27.1a

No. of panicles
per hill
6.7b

No. of grains
per panicle
138.6aFilled grain(%)
72.06a100 grain
weight (g)
2.26b

Yield
(g/m2)
412.7aPawsan

13.4b

11.6a

94.3b

61.17b3.24a286.7aYoesein*

20.4

6.7

105.2

69.05

2.97

291.9

Variety

Analysis was done for Byaw Htun and Pawsan only by using statistix version 8.0, * No replication, value followedby the same letter within each column do not different at p<0.05

CONCLUSION
Although CST in Byaw Htun can be transplanted, it took longer growth duration than that of DS.
Therefore, CST in Byaw Htun should not be followed in the area where no flood damage occurs andthe second crop such as legume will be cultivated after rice harvest. However, Byaw Htun CST
produce the yield comparable to those of Pawsan and Yoesein CST. Moreover, it can harvest earlier
than those of Pawsan and Yoesein. Therefore, CST in Byaw Htun could be practiced in the area
where the flood damage occurred.
ACKNOWLEDGEMENTS
This research was financially supported by the YAU-JICA Technical Cooperation Project.

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REFERENCES
De Datta, S.K. 1981. Principles and practices of rice production. John Wiley & Sons, Inc. UK.
Hamamura, K. 1978. Relation between number of elongated internodes and days from seeding to heading infloating and non-floating rice varieties. Jpn. J. Trop. Agr., 22 (2),77-81.
MOALI (Ministry of Agriculture, Livestock and Irrigation). 2015. Myanmar agriculture at a glance.
Department of Agricultural Planning, Ministry of Agriculture, Livestock and Irrigation, Myanmar.
Mon, Y., Yamamoto, Y. and Aung, M.M. 2019a. The special rice transplanting method, cut stem transplant,(A Sit Phyat) practiced in deep water areas of Bago Region in Myanmar. Trop. Agr. Develop., 63 (1), 38-46.
Mon, Y., Yamamoto, Y. and Aung, M.M. 2019b. The growth and yield of cut-stem transplant (A Sit Phyat)
rice practiced in deep-water area of Bago Region, Myanmar. Trop. Agr. Develop., 63 (4), 176-185.
Rice Division. 2016. Annual report for rice production in 2015-2016. Department of Agriculture, Ministry ofAgriculture, Livestock and Irrigation, Myanmar.

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Research article
erdPhysiological Variables Associated with Yield of Improved
Rice (Oryza sativa L.) Genotypes in Normal and Late
Growing Seasons
ZUN PHOO WAI*
Yezin Agricultural University, Nay Pyi Taw, Myanmar
Email: zunphoowai.yezin@gmail.com

NYO MAR HTWE
Yezin Agricultural University, Nay Pyi Taw, Myanmar

SU LATT PHYU
Yezin Agricultural University, Nay Pyi Taw, Myanmar
Received 20 January 2020

Accepted 12 December 2020(*Corresponding Author)

Abstract Genotypic selection for higher total dry weight has become a key method of
research and experimentation to increase grain yield. Therefore, this experiment was carriedout to determine the relationship of leaf area index (LAI) and yield and its components forten genotypes of improved rice, for normal and late growing seasons. The experiments wereconducted in the experimental fields of the Department of Plant Breeding, Physiology andEcology, Yezin Agricultural University. The study was undertaken from December 2016 to
May 2017 for testing normal growing season plants and March 2018 to July 2018 for late
growing season plants. A randomized complete block design with three replications wasused. For the relationship among all the traits tested, positive associations were found (R2 >0.5) for LAI at harvest and yield (R2 = 0.574), for panicle weight at harvest and yield (R2 =0.558), and for harvest index (HI) and yield (R2 = 0.61). The study showed that yields increase
along with an increase in LAI and panicle weight, for the improved rice genotypes that were
tested. There was a positive and significant correlation found between LAI at heading stage
and percent of filled grains in normal season, and LAI at heading and number of panicles permeter square in late season. In late season, the correlation between LAI at harvesting stageand yield was significant; HI was also significantly correlated with percent of filled grains
and yield. As LAI and harvest index contribute to yield and yield component characters,
breeders may successfully attempt to boost potential yields by increasing growth traits suchas plant foliar surface and harvest index.
Keywords yield, LAI, correlation

INTRODUCTION
Rice is the most important food crop in the world and serves as a staple food for more than one thirdof the world’s population (Singh and Singh, 2008). About 90% of the world’ rice growing area is on
the Asian continent (Salim et al., 2003). It is estimated, farmers in the world need to produce about
60% more rice than at present to meet the food demands of the world population expected by 2025
(Thakur et al., 2011).
In Myanmar, rice is a staple food and is cultivated in an area of 7.28 million hectares. Total
production is 28.09 million metric tons, giving a yield of 3.92 ton/ha (Department of Planning,
Ministry of Agriculture, Livestock and Irrigation, 2018). Rice makes up 33 % of total area cropped
with 84% (6,474,970 ha) of rice grown during monsoon and 16% (1,214,056 ha) grown during
summer (Sein, 2014). Okamoto (2004) affirms that rice production is very important for both theeconomic livelihood and food security for the population of Myanmar.
Increases in rice production have mainly relied on the expansion of the area of cultivable land
used to grow rice, and increases in yield per unit area (Evans, 1993). Climate change and urbanizationⒸ ISERD

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can result in decreases in rice cropping areas. Therefore, the increase of yield per unit area has
become the focus to achieve increases in production. The grain yield of rice is a complex trait,
controlled by many genes and highly affected by the environment (Jennings et al., 1979). Grain yieldis also related to other characteristics, such as plant type, growth duration, and yield components(Yoshida, 1981). In comparing semi-dwarf and traditional rice cultivars, the increase in harvest index
is the contributing factor improving yield potential, rather than any increase in production of biomass(Takeda et al., 1983; Evans et al., 1984). However, modern cereal breeding programs have provided
evidence of the possibility of boosting grain yields by selecting genotypes exhibiting higher biomass
production (Boukerrou and Rasmusson, 1990; Damisch and Wiberg, 1991). The efficiency withwhich dry matter is accumulated and allocated to harvestable organs, the grains in rice, determines
the size of yield components and final yield (Fageria et al., 2006).
There are two rice growing seasons in Myanmar; summer and monsoon or dry and wet. The
summer (dry) rice growing season is from December to May and the monsoon season (wet) from
June to November. Sometimes summer rice growing is delayed because of labour scarcities, delaysin obtaining irrigation water or due to a late harvesting time for the previous crop.
OBJECTIVE
The aim of this research is to determine the relationship of LAI and yield, and yield related traits ofimproved rice genotypes, under normal and late growing seasons.
MATERIALS AND METHOD
The experiment was carried out in the experimental fields of the Department of Plant Breeding,Physiology and Ecology, Yezin Agricultural University from December 2016 to May 2017 fornormal season rice and March 2018 to July 2018 for late growing rice. Experimental field is locatedat longitude 19º 10′ and latitude 96º 07′ E with the elevation of 102 meters (m) above sea level.
Ten improved rice genotypes which were preliminary selected based on agronomic traits and yield,
were grown and yield estimated (Table 1) by using randomized complete block design with three
replications. Each plot was (4m × 4m) with a spacing of 20cm × 20cm. Each genotype was plantedwith 20 rows, and 20 plants per row (total 400 plants per plot). Twenty-one-day-old seedlings weretransplanted with one seedling per hill. Other agronomic practices were followed as required by using
recommended cultural practices.
Table 1 List of tested improved rice genotypes in this study
No.
1
2
3
4
5
6
7
8
9
10

Improved Genotype
YAU- 1201-1-2-1
YAU-1201-202-1-2
YAU-1214-183-3-1-1-1-1
YAU-1214-183-35-1-1-1-1
YAU-1215-S-S-S-40-2-1
YAU-1215-S-S-S-41-1-1
YAU-1211-116-3-4
YAU-1211-71-1-1
YAU-1201-151-1-1
YAU-1201-151-1-3

In this study, LAI and dry weight were measured at heading stage and at harvesting stage.
Heading stage was defined as the time when the main stem panicle had emerged and the harvestingstage was defined as the stage of the plants’ physiological maturity. Two rows in border areas wereleft out of the sample collected to avoid the border effect. Three representative hills (hills with a meanvalue of tillers per hill) from each plot were sampled for the determination of dry weight. All plant
samples were separated into green leaf blades (leaf), culm plus sheath (stem), and panicles. AllⒸ ISERD

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samples were oven-dried at 80°C for 72 hours to obtain a constant weight. At the time of harvest,
five representative hills were selected to measure yield and yield component traits. The weight offilled spikelets was adjusted for a moisture content of 14%. Leaf area index (LAI) was calculated as
the ratio of the sum of the leaf area of all leaves to the ground area of the field where the leaves had
been collected (Watson, 1947).
LAI=

Sum of the leaf area of all leaves
Ground area of field where the leaves have been collected

Yield per plant (g)=1000 grains weightFilled grain %Spikelet number/paniclePanicle number
1000100

The data were analyzed with Microsoft Excel (2007) and correlation analysis was also
performed by using Statistical Tool for Agricultural Research (STAR) 2.0.1 (2014).
RESULTS AND DISCUSSION
Temperature regimes were different during vegetative, reproductive and ripening stages during two
growing seasons (Table 2).
Table 2 Average of daily temperature and total rainfall during different growth stages of rice
Daily temperature

Daily temperature

Daily maximum(°C) during NS(°C) during LS

temperature ≥35°C

max

min

max

min

NS

LS

NS

LS

Vegetative

35.2

18.5

37.3

22.9

50

89

44

311

Reproductive

37.4

24.4

31.8

24.9

24

1

58

264

Ripening

38.4

26.2

31.5

24.7

28

0

93

272

Growth stage

Total rainfall(mm)Source: Weather Station of Department of Agricultural Research, Yezin. NS=Normal Season, LS=Late Season

Correlations between physiological variables and yield and yield components for improved rice
genotypes in both NS and LS are showed in Table 3. In NS, there was no significant correlation
between the variables except LAI at heading and percentage of filled grain. It could be suggested
that percentage filled grain correlates with optimum LAI at heading. For LS crops, LAI at heading
was positively and significantly correlated with the number of panicles per meter square. Also, filled
grains percentage was positively and significantly correlated with harvest index (HI). LAI atharvesting stage, and harvest index (HI) were positively and significantly correlated with yield/m2.
A positive correlation between LAI and yield has been reported in the literature (Xie et al., 2011;
Moraditochaee et al., 2014). An increase in harvest index results in an increase in grain yield that
produces heavier grain in improved rice cultivars (Kiniry et al., 2001). Yield/m2 is demonstrably
affected by LAI and HI.
Regression analysis showed that yield/m2 is associated with dry weight at heading stage in LSwith an R2 of 0.027 though this relationship is relatively weak in NS (R2=0.038) (Fig. 1). The
relationship between yield and dry weight at harvesting stage is associated in both NS and LS with
R2s of 0.154 and 0.054 respectively (Fig. 2) . Van der Werf (1996) stated that above-ground total dry
matter (ATDM) accumulation (areal total dry weight) along with its partitioning to various parts ofthe plant determined crop productivity. Under favorable growing conditions, the increased yield of
F1 hybrid rice was associated with increased total dry weight (Song et al., 1990; Yamauchi, 1994).
Yield/m2 was positively related with HI in both seasons and this was a strong relationship with an R2of 0.61 (Fig. 3). Increasing the harvest index and dry weight can achieve an increase in grain yield.
An association between yield/m2 and panicle weight in both growing seasons (Fig. 4) was foundand there was a moderate relationship with an R2 of 0.558 in LS. Panicle weight is positively relatedⒸ ISERD

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to increased dry weight from heading to harvesting with an R2 of 0.223 in NS and R2 of 0.175 for LS(Fig. 5). Weng et al. (1982) reported a similar result. The result showed that yield can be increased
with increased dry weight through the increase of panicle weight.
It was found that yield/m2 was positively related with LAI at heading stage in both NS and LS(Fig. 6). This indicates that an increase in LAI at heading stage results in an increase in yield. In NS,
yield had no relationship to LAI at harvesting stage but there was positive association of yield with
LAI at harvesting stage with an R2 of 0.574 (Fig. 7) for LS. Yield/m2 was positively related withdecreased LAI from heading to the harvesting stage with an R2 of 0.141 in NS, but there was anegative association for LS (Fig. 8). Moradpour et al. (2013) stated that a strong relationship between
yield and LAI was observed. An increase in LAI at harvesting stage contributes to an increased yieldfor the late season rice.

Fig. 1 Relationship between yield/m2 and dryweight at heading stage in NS and LS

Fig. 2 Relationship between yield/m2 anddry weight at harvesting stage in NS
and LS

Fig. 3 Relationship between yield/m2 and HI
in NS and LS

Fig. 4 Relationship between yield/m2 andpanicle dry weight in NS and LS

Fig. 5 Relationship between panicle weightand increased dry weight from heading
to harvesting in NS and LS

Fig. 6 Relationship between yield/m2 and
LAI at heading stage of in NS andLSⒸ ISERD

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Fig. 7 Relationship between yield/m2 and LAI
at harvesting stage in NS and LS

Fig. 8 Relationship between yield/m2 anddecreased LAI from heading toharvesting in NS and LS

Table 3 Correlation between physiological variables and yield and yield components ofimproves rice genotypes during two seasons

No. of panicles(/m2)

No. of grains (/m2)

NS
2017

LS
2018

NS
2017

LS
2018

NS
2017

LS
2018

NS
2017

LS
2018

LAI at heading

0.32830.7166*-0.4555-0.1294

0.6856*0.47940.35810.2769

LAI at harvesting-0.1478

0.13-0.54540.4476

0.55150.22310.04750.7574*

0.3966

0.5672-0.3475-0.2992

0.596

0.32380.3763-0.0752-0.47970.54740.44130.1823-0.16280.59170.19630.3822-0.2881-0.4026

0.12810.4363-0.056-0.2051

0.393

0.234

0.3093-0.5767-0.412

0.19550.1439-0.4670.1293-0.0527-0.16390.50340.16620.2456

0.06830.7413*0.33480.6840*

Yield and yield components

Decrease of LAI fromheading to harvesting
Dry weight at heading(g/m2)
Dry weight at harvesting(g/m2)
Increase of dry weight fromheading to harvesting (g/m2)
HI

Filled grains percent

Yield (g/m2)

NS= Normal growing season, LS= Late growing season

CONCLUSION
In this study, correlation analysis showed that yield and yield components correlated with LAI, dryweight and HI, especially for late growing season crops. According to regression results, yield
increasing was influenced by the increase of HI, LAI and panicle weight, especially in late season
and panicle weight was contributed by dry weight. As yield and yield components are correlated with
LAI, dry weight and HI, tall varieties of rice, susceptible to lodging rice should not be grown in thelate season and breeders should attempt to increase growth traits such as plant foliar surface and HI
in order to boost potential yields.
ACKNOWLEDGEMENTS
The authors would like give special thanks to the Japan International Cooperation Agency (JICA),
Project for Capacity Development at Yezin Agricultural University for the financial and technicalsupport given in conducting this study.

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REFERENCES
Boukerrou, L. and Rasmusson, D.D. 1990. Breeding for high biomass yield in spring barley. Crop Science, 30,
31-35.
Damisch, W. and Wiberg, A. 1991. Biomass yield, A topical issue in modern wheat breeding programmes.
Plant Breeding, 107, 11-17.
Department of Planning. 2018. Myanmar agriculture at a glance. Ministry of Agriculture, Livestock and
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Evans, L. 1993. Crop evolution, adaptation and yield. crop evolution, adaptation and yield. Cambridge
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Evans, L., Visperas, R. and Vergara, B. 1984. Morphological and physiological changes among rice varieties
used in the Philippines over the last seventy years. Field Crops Research, 8, 105-124.
Fageria, N.K., Baligar, V.C. and Clark, R. 2006. Physiology of crop production. CRC Press, USA.
Jennings, P., Coffman, W. and Kauffman, H. 1979. Rice improvement. International Rice Research Institute(IRRI), Los Baños, Laguna, Philippines.
Kiniry, J.R., McCauley, G., Xie, Y. and Arnold, J.G. 2001. Rice parameters describing crop performance offour US cultivars. Agronomy Journal, 93, 1354-1361.
Moraditochaee, M., Azarpour, E. and Bozorgi, H.R. 2014. Evaluation of some growth indices on vegetativeand reproductive stage of rice cultivars under nitrogen fertilizer management. Journal of Biodiversity andEnvironmental Sciences (JBES) , 4, 1-8.
Moradpour, S., Koohi, R., Babaei, M. and Khorshidi, M.G. 2013. Effect of planting date and planting density
on rice yield and growth analysis (Fajr variety). International Journal of Agriculture and Crop Sciences.
s5, 267.
Okamoto, I. 2004. Agricultural marketing reform and rural economy in Myanmar. The Successful Side of theReform World, 5, 1.1.
Salim, M., Akram, M., Akhtar, M. and Ashraf, M. 2003. Rice. A Production Hand Book, Pakistan Agricultural
Research Council, Islamabad 70.
Sein, W.H. 2014. Overview of Myanmar rice. Asian Rice Forum, Bangkok, Thailand, Retrived from http://
afmaasia.org/Asian_rice_forum/Myanmar%20Mr.%20Sein%20Win%20Hlaing
Singh, Y. and Singh, U. 2008. Genetic diversity analysis in aromatic rice germplasm using agro-morphologicaltraits. Indian Journal of Plant Genetic Resources, 21, 37-42.
Song, X., Agata, W. and Kawamitsu, Y. 1990. Studies on drymatter and grain production of F 1 hybrid rice in
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Takeda, T., Oka, M. and Agata, W. 1983. Characteristics of dry matter and grain production of rice cultivars
in the Warmer Part of Japan. I. Comparison of Dry Matter Production between Old and New Types of Rice
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Thakur, A.K., Rath, S., Patil, D. and Kumar, A. 2011. Effects on rice plant morphology and physiology ofwater and associated management practices of the system of rice intensification and their implications forcrop performance. Paddy and Water Environment, 9, 13-24.
Van der Werf, A. 1996. Growth analysis and photo-assimilate partitioning. In Photo-assimilate Distribution in
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Weng, J.H., Takeda, T., Agata, W. and Hakoyama, S. 1982. Studies on dry matter and grain production of rice
plants. I. Influence of the Reserved Carbohydrate until Heading Stage and the Assimilation Products during
the Ripening Period on Grain Production, Japanese Journal of Crop Science, 51, 500-509.
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matter accumulation of rice under high temperature at heading stage. African Journal of Agricultural
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Yamauchi, M. 1994. Physiological bases for higher yield potential in F hybrids. In Virmani, SS. (Ed.) Hybrid
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Yoshida, S. 1981. Fundamentals of rice crop science. Int. Rice Res. Inst., Philippines.

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IJERD – International Journal of Environmental and Rural Development

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