ISSN 2185-159X

erd

International Journal ofEnvironmental and Rural Development

Volume 6 Number 2

December 2015

International Society of Environmental and Rural Development

IJERD – International Journal of Environmental and Rural Development

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

Aims and Scope:
The International Journal of Environmental and Rural Development, IJERD, is an interdisciplinary journal
concerning environmental and rural development research in the education for sustainable development, ESD.
The IJERD is devoted to publishing peer-reviewed research article, review article and technical report in thefields of environmental and rural development, such as education for sustainable rural development, ruraldevelopment, environmental management or agricultural systems. Every article or report in IJERD must be
accepted by at least 2 reviewers and an editorial member.
The aims of IJERD are to publish the latest research development and achievements, to strengthen
education systems, to promote cooperation in environmental and rural development and to contribute to theprogress in sustainable development. The editorial board of this journal covers a variety of scientificdisciplines.
Thematic Areas:
The following areas are envisioned in IJERD.
Education for Sustainable Rural Development:
Environmental Education, Food and Agricultural Education, Participatory Approach, Capacity Building,Community Empowerment, Agricultural Extension, etc.
Rural Development:
Marketing, Partnership, Value Added Product, Community Development, Access to Technology,
Cultural Preservation, etc.
Environmental Management:
Bio-Diversity, Soil Degradation and Land Conservation, Water Quality Conservation, Deforestation andSustainable Forest Management, Environmental Management, etc.
Agricultural Systems:
Organic Farming, Conservation Tillage, Mechanization, Irrigation and Drainage, Nutrient and Pest
Management, Cattle Breeding, Agro-Forestry, Indigenous Technology, etc.
Infrastructural Systems:
Water Resource Development, Land Reclamation, Road Construction, etc.
Editorial Board:
Editor in Chief:
Prof. Dr. Machito Mihara, Tokyo University of Agriculture, Japan /Institute of Environmental Rehabilitation and Conservation, Japan
Managing Editors:
Dr. Jeeranuch Sakkhamduang, Institute of Environmental Rehabilitation and Conservation,
Southeast Asia Office / Association of Environmental and Rural Development, Thailand
Dr. Junaid Alam Memon, Pakistan Institute of Development Economics, Pakistan
Dr. Julian Torillo, Jr., Bohol Island State University, Philippines
Dr. Carlos Onan Tovar Mendoza, Honduras Embassy in Japan, Japan
Editorial Advisory Board:
Dr. Venkatachalam Anbumozhi, Asian Development Bank Institute, Japan
Dr. Robert J. Farquharson, The University of Melbourne, Australia
Prof. Dr. Keishiro Itagaki, Tokyo University of Agriculture, Japan
Dr. Chuleemas Boonthai Iwai, Khon Kaen University, Thailand
Prof. Dr. Arata Koga, University of Veterinary and Animal Science, Pakistan
Prof. Dr. Robert J. Martin, University of New England, Australia
Prof. Dr. Bunthan Ngo, Royal University of Agriculture, Cambodia
Dr. Hiromu Okazawa, Tokyo University of Agriculture, Japan
Prof. Dr. Salvador Catello, University of the Philippines, Philippines
Dr. Rajendra P. Shrestha, Asian Institute of Technology, Thailand
Prof. Dr. Murari Suvedi, Michigan State University, USA
Prof. Dr. Mario T. Tabucanon, United Nations University, IAS, Japan
Dr. Vidhaya Trelo-Ges, Khon Kaen University, Thailand
Editorial Secretariat:
Dr. Shinobu Terauchi, Institute of Environmental Rehabilitation and Conservation, Japan

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Contents
Effect of Different Dietary Nutritional Compositions on Clark's Anemonefish(Amphiprion clarkii) Growth
Boontarika Thongdonphum, Kittima Vanichkul,
Saming Champasri, Suphamas Tipayanon
and Suthat Worasiri

1

Effect of Nitrous Oxide on Physiological and Biochemical Changes during
Fruit Drop of Longkong Postharvest
Intira Lichanporn, Nunchanok Nanthachai,
Palida Tanganurat and Unchalin Singkhum

6

Characterization of Potential Molave (Vitex parviflora Juss.) Mother Treesin Lila, Bohol, Philippines
Noel S. Gamil and Noel T. Lomosbog

11

Efficiency of Crude Extract from Pummelo Peel on Controlling the Growth ofColletotrichum gloeosporioides (Penz.)
Nunchanok nanthachai,Intira lichanporn,
Palida Tanganurat and Unchalin singkhum

17

Utilization of Coconut Fronds for Weed and Insect Pest Management inTomato Production
Marina A. Labonite, Sandra Mcdougall, Gordon Rogers,
Jose G. Labonite, Dennis B. Jomoc and Merigine C.Otara

23

Working with Ethnic Group: A Case Study of Introducing Pig Fattening to Garay Ethnicity in
Ouyadav District, Ratanakiri Province
Phem Menghak, Thim Sokha, Theng Kouch and Seng Mom

29

Problems in Rural Areas of Bosnia, Montenegro and Serbia: A Comparative Analysis
Sinisa Berjan, Hamid El Bilali, Aleksandra Despotovic,
Snezana Jankovic, Adriana Radosavac
and Noureddin Driouech

35

Reuse of Wastewater from Cassava Industry for Napier Grass Production
Chuleemas Boonthai Iwai, Mongkon Ta-Oun
and Barry Noller

42

The Study of Greenhouse Gas Emissions of Ethanol Production from
Agro-industrial Fruit Residues
Somporn Pleanjai and Pongsri Siwarasak

48

Evaluation on Agro-forestry System in Salt Affected and Non-salt Affected Areas
Jeeranuch Sakkhamduang and Machito Mihara

54

Pollen Food Source Diversity of Stingless Bee Tetragonula pegdeni and
Lepidotrigona terminata in Cultivated Area
Anchalee Sawatthum and Rawadee Kumlert

61

Analysis of Urban Ecosystem Services Considering Conservation Priority
Makoto Ooba, Kiichiro Hayashi, Takahiro Suzuki
and Rui Li

66

Micro Hydroelectricity Using Irrigation Ponds for Better Water Management
Katsuyuki Shimizu, Yasuyuki Kusaka
and Yoshinobu Kitamura

73

Analysis of Fiscal Gap and Financing of Cambodia’s Protected Areas
Somaly Chan

79i

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Business Activities of “Transformed” Agricultural Cooperatives andtheir Role in Supporting Local Agriculture in Northern Vietnam
Fumie Takanashi

87

Floristic Inventory of the Proposed Site for Tarsier Tourism Center in
Villa Aurora, Bilar, Bohol, Philippines
Tomas D. Reyes, Jr., Jeralyn B. Abadingo, Shiela G.
Tabuno, Eunice Kenee L. Seriño, Joecel B. Mabanag,
and Rizaldy C. Mercadal

94

Rapid Carbon Stock Appraisal (RACSA) Implementation in
Wahig-Inabanga Watershed, Bohol, Philippines
Tomas D. Reyes, Jr. and Erwin G. Ludevese

102

Effect of Stake Storage Methods on Germination, Growth andYield of Cassava (Manihot esculenta Crantz.)
Arunee Promkhambut, Pikul Manuta, Anucha Laoken,
Kiriya Sungthongwises and Anan Polthanee

110

Impacts of Atmospheric Temperature - Humidity Change on
Yield Quality of Thai Soybean Cultivar
Kanita Thanacharoenchanaphas and Orose Rugchati

115

Periodic Fertilization Using Urea and Chicken Manure as Source of
Natural Productivity in a Biofloc System during the Nursery ofPacific White Shrimp Litopenaeus vannamei
Maria Danesa S. Rabia, Jomel G. Baobao,
Guillermo P. Tutor and Ernesto C. Ruilida

121

Ecotoxicology of Copper on Freshwater Fish with Different Water Hardness
on the Mekong River, Lao PDR
Naksayfong Khounnavongsa, Chuleemas Boonthai Iwai,
and Tham C. Hoang

128

Agricultural Extension and Advisory Services in Bosnia, Montenegro
and Serbia: An Overview
Snezana Jankovic, Aleksandra Despotovic, Sinisa Berjan,
Hamid El Bilali, Noureddin Driouech, Adriana Radosavac,and Aleksandar Stojanovic

133

Relation Between Rural Diversification and Governance: Some Insights from
Bosnia, Montenegro and Serbia
Hamid El Bilali, Sinisa Berjan, Adriana Radosavac,
Aleksandra Despotovic, Snezana Jankovic
and Noureddin Driouech

140

Promoting Gummy Guyabano (Anona muricata Linn.) Candy
Regucivilla A. Pobar

147

Heavy Metal Contamination in Meat and Crustaceans Products fromThailand Local Markets
Montip Jankeaw, Natagarn Tongphanpharn,
Rattanapon Khomrat, Chuleemas Boonthai Iwai
and Nisa Pakvilai

153

Comparative Spatial Assessment of Regulating and Supporting Ecosystem
Services in Nay Pyi Taw, Myanmar
Kay Khaing Lwin, Kiichiro Hayashi and Makoto Ooba

159

Comparison of Semi-Quantitative and Statistical Regression Models in Assessing
Landslide Prone Areas in Wahig-Inabanga Watershed, Bohol, Philippines
Tomas D. Reyes, Jr.

166

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Farm Machineries and Equipment Needs Assessment of the Corn Block Farming in Dagohoy,
Bohol, Central Philippines: Basis for Financial and Support Services
Marina A. Labonite and Dennis b. Jomoc

172

Evidence-based Modeling of Landslide Hazard in Wahig-Inabanga Watershed,
Bohol, Philippines using GIS and Statistical Models
Tomas D. Reyes, Jr.

178

iii

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Research article
erd

Effect of Different Dietary Nutritional Compositions on
Clark's Anemonefish (Amphiprion clarkii) Growth
BOONTARIKA THONGDONPHUM*
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi,
Pathum Thani, Thailand
Email: Boontarika_T@rmutt.ac.th

KITTIMA VANICHKUL
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi,
Pathum Thani, Thailand

SAMING CHAMPASRI
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi,
Pathum Thani, Thailand

SUPHAMAS TIPAYANON
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi,
Pathum Thani, Thailand

SUTHAT WORASIRI
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi,
Pathum Thani, Thailand
Received 12 February 2015

Accepted 1 April 2015(*Corresponding Author)

Abstract Clark's Anemonefish (Amphiprion clarkii) is one of marine ornamental fish. The
nutritional requirements of A. clarkii are important for their growth. This study aimed toassess the effect of different diets on A. clarkii growth performance. The experiments
comprised of three treatments including (1) grinding pacific white shrimp (Litopenaeus
vannamei), (2) grinding white perch fish (Lates calcarifer), and (3) grinding surf clam
(Paphia undulata). Growth rate, survival rate, and other growth parameters were studied
within 30 days after starting of the experiments. Results indicated that growth rate of A.
clarkii based on weight and length was highly significant on grinding white perch fish
treatment. Average daily growth was also the best on grinding white perch fish treatment(0.46r0.09 g), followed by ground pacific white shrimp (0.37r0.04 g) and grinding surf
clam (0.35r0.03 g), respectively. Survival rate showed significant difference on grinding
surf clam (97.78r3.85%), followed by grinding pacific white shrimp (75.57r8.38%) and
grinding white perch fish (64.44r5.09%), respectively. Food conversion ratio tended to bebetter on grinding white perch fish. This finding indicates that grinding white perch fish
could be used as dietary source of A. clarkii.
Keywords Clark's Anemonefish, marine ornamental fish, nutritional requirement,
nutritional composition

INTRODUCTION
Marine ornamental fish are one of the most popular attractions world-wide due to adaptability tolive in confinement. The tropical ornamental fish has increased trust among aquarists due to theirmultitudinous color and gorgeousness (Ghosh et al., 2011). Thus, marine ornamental aquaculture
has become economically feasible, and much interest has been generated for inland (Watson and
Hill, 2006). Feed composition and water management in containing tank are important. DietaryⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

sources are important to fish growth (Koedprang ,2006), especially fish are rare in high density
indoor systems or confined in cage and cannot forage freely on natural feeds. They must provide
complete diet (Craig and Helfrich, 2009). The protein requirements of fish seem to be higher thanterrestrial animals (Lovell, 1988). The commercial fish feed was designed to complete nutritional
intake for the marine ornamental fish growth, which has an impact to the high price. The enriched
live feed, the rotifers and artemia had to prepare by using microalgae for feeding the fish (Madhu et.
al., 2013). Artemia could be a good alternative live feed to be used in the hatchery of ornamental
fish but lack of the facilitated supplies (Lim et. al., 2003). Limited supply and high cost of fishmeal have forced fish nutritionists to search for alternative protein sources (Silva et al., 2010). The
application of live feeds in marine ornamental fish culture has been hampered by the lack live feed
information for feeding the fish. Live feeds of nutritional composition were the alternative dietswith comparable nutritional quality that needed to maintain the cost competitiveness of marine
ornamental fish and remained healthy in suitable diet, which could be contributed to enhancing
growth of Clark's Anemonefish culture.
OBJECTIVE
This study aimed to assess the growth rate, survival rate, and other growth parameters of Clark's
Anemonefish fed by three different nutritional compositions.
METHODOLOGY
Fish source
Two hundred and seventy larvae of Clark's Anemonefish (Amphiprion clarkii) were obtained fromthe ornamental fish culture at Krabi Coastal Fisheries Research and Development Center, Krabi
province and transported to the hatchery at Division of Fisheries, Rajamangala University ofTechnology Thanyaburi, Pathum Thani province. The total of A.clarkii all between 1.5-3 cm inlength was acclimatized in a conditioning tank for three days by using natural seawater withsalinity maintained at 30 psu after passing through a sandy filter. Then, fish were distributed intonine 100-liter tanks (100 L capacity; 30 individuals per tank). The experiments were assigned for
30 days study period.
Experimental design
The experiments followed a completely randomized design (CRD) comprising three feed
treatments of grinding pacific white shrimp (Litopenaeus vannamei) (T1), grinding white perch fish
(Lates calcarifer) (T2), and grinding surf clam (Paphia undulata) (T3). The larvae were fed on thethree different diets twice a day, 08:30 and 16:00 h, at a rate of 34% of their body weight per day.
After one hour of each feeding, uneaten diet and fecal matter were siphoned out of the tanks.
The proximate nutritional compositions (protein, lipid, fiber, ash, moisture, and dry matter) in
the experimental diets were analyzed according to Association of Analytical Chemists (AOAC,
2000). The number of dead fish was recorded during the experiments. Length and weight data wererecorded at the 30th day after the start of the experiment to determine the growth performance.
Average daily growth (ADG) as in Eq. (1) , survival rate (SR) as in Eq. (2), and food conversion
ratio (FCR) as in Eq. (3) were calculated using the equations,
ADG = (We-Ws)/t(1)

where We was the weight at the end of the experiment, Ws was the weight at the start of theexperiment, and t was the number of days.
SR = ((Ne-Ns)/Ns) x 100(2)Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

where Ne was the number of fish alive at the end of the experiment, and Ns was the number of fish
alive at the start of the experiment.
FCR = Wf/Wt(3)

where Wf was the feed intake, and Wt was the total weight of fish at the end of the experiment.
The general water quality factors, namely temperature, salinity, and pH were measured with amulti-parameter probe (YSI-6600 Sonde instrument, USA).
Data analysis
Analysis of variance (ANOVA) was used to consider the growth factors for each treatment. The
significance between the means was compared by using Duncan's new multiple range test (DMRT)
at a probability level of 0.05 (p<0.05).
RESULTS AND DISCUSSION
Average weight of A. clarkii at the end of the experiment (We) was significantly affected bydifferent types of diets (p<0.05), the highest average weight was on grinding white perch fish
treatment (0.46r0.09 g), followed by ground pacific white shrimp (0.37r0.04 g), and grinding surf
clam (0.35r0.03 g), respectively. The final length of fish varied between 2.49r0.13 cm, as found in
T3 to 2.86r0.15 cm, as found in T2 (p<0.05). The results indicated that growth rate of A. clarkii, interms of weight and length,were better in grinding white perch fish treatment (T2) (Table 2).
According to Chambel et al. (2015), it was reported that Percula Clownfish (Amphiprion percula)averaging 1.92r0.01 cm size was treated by using commercial marine fish diets with different
crude protein levels, 52.5, 48, 41, and 38%. Results showed the final length of A. percula varied
between 2.865r0.066 to 3.108r0.066 cm.
Different types of diets also significantly affected on average daily weight (ADG) and survival
rate (p<0.05), the highest ADG were recorded on grinding white perch fish (0.008r0.001 g/day),and the lowest one in those fed on grinding surf clam (0.004r0.000 g/day). Survival rate (SR)values showed the highest significant in T3 (97.78r3.85%). No statistically significant difference
was found on food conversion ratio (FCR) fed on different diets. However, T2 tended to reveal thehighest value (10.92r2.47) as shown in Table 2. This study indicated that the diets effected to A.
clarkii growth performance.
Water quality during culture period showed that water temperature, pH, and salinity varied
from 21.0-26.0 oC, and 7.0-8.0, and 30-32 psu, respectively. Those parameters had no significant
difference by different diets (p>0.05). In this study, the water quality factors were similar to results
obtained by Chambel et al., (2015) in the A. percula culture.
Table 1 Growth parameters (meanrSD) of Clark's Anemonefish fed on the three diettreatments
Parameters
Ws (g)We (g)Ls (cm)Le (cm)ADG (g/day)
SR (%)FCR

Diets
Treatment 1
0.19r0.06a
0.37r0.04b
1.94r0.25a
2.69r0.13b
0.005r0.000b
75.57r8.38b
12.55r4.36a

Treatment 2
0.19r0.05a
0.46r0.09a
1.93r0.16a
2.86r0.15a
0.008r0.001a
64.44r5.09b
10.92r2.47a

Treatment 3
0.20r0.06a
0.35r0.03b
1.98r0.21a
2.49r0.13c
0.004r0.000b
97.78r3.85a
14.80r3.85a

Weight at the start (Ws) and the end (We) of the experiment, length at the start (Ls) and the end (Le) of the experiment,
average daily growth (ADG), survival rate (SR), and food conversion ratio (FR). The values in each row followed by thesame letter are not significantly different (p<0.05).
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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Growth performance of fish could be assessed from protein requirement depended on the
dietary feed intake of fish. The nutritional composition of the three diets is shown in Table 2.
Protein and lipid composition showed high level in T2 (19.81% and 0.03%) followed by T1, andT3, respectively (Table 2). The optimal protein level in dietary feed played the key role to produce
maximum weight gain in the least time (Martínez et al., 2004). Chuapoehuk (1999) reported thatthe kinds of aquatic animal that had the high level of protein and energy were fish (20.4% and 111
calories/100g), shrimp (19.7% and 94 calories/100 g) and clam (12.3% and 63 calories/100 g),
respectively. The optimal protein level in the diet of fish raised in captivity and most fish farmers
used complete diets containing required protein 18-50% (Craig and Helfrich, 2009). In addition,
Chambel et al. (2015) indicated that the compound diet of 40% protein would provide nutrients thatwould ensure optimal growth of A. percula.
Table 2 Composition of the feeds (%) in each treatment
Parameters
Protein
Lipid
Fiber
Ash
Moisture
Dry matter

Diets
Treatment 2
19.81
0.03
0.08
1.11
79.54
20.46

Treatment 1
18.31
0.01
0.04
1.09
77.35
22.65

Treatment 3
14.25
0.02
0.12
1.32
79.91
20.09

CONCLUSION
This study indicated that grinding white perch fish had significant effect on Clark's Anemonefish
growth in terms of weight, length, and average daily growth. Based on this study, grinding white
perch fish had the optimal protein levels for growth performance and could be included in diet for
Clark's Anemonefish culture.
ACKNOWLEDGEMENTS
The authors would like to express deep gratitude to all the staff members of the Division ofFisheries, Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi,
for all supports and assistance.
REFERENCES
AOAC. 2000. Official methods of analysis. 15th ed. Wilson Boulevard Arlington, Verginia, USA.
Chambel, J., Severiano, V., Baptista, T., Mendes, S. and Pedrosa, R. 2015. Effect of stocking density anddifferent diets on growth of Percula Clownfish, Amphiprion percula (Lacepede, 1802). Springer Plus,
4(183), 1-7.
Chuapoehuk, W. 1999. Animal nutrition and fish feed. 1 th ed. Department of Aquaculture, Kasetsart
University, Bangkok.
Craig, S. and Helfrich, L.A. 2009. Understanding fish nutrition, feeds, and feeding. Verginia Tech, Verginia
State University.
Ghosh, S., Ajith Kumar, T.T., Nanthinidevi, K. and Balasubrananian, T. 2011. Hatchery production of
Clark's Clownfish, Amphiprion clarkii (Bennett, 1830) using brackishwater. IPCBEE, 22, 51-56.
Koedprang, W. 2006. Anemonefish. 1th ed. Odean store, Bangkok.
Lim, L.C., Dhert, P. and Sorgeloos, P. 2003. Recent developments in the application of live feeds in the
freshwater ornamental fish culture. Aquaculture, 227, 319-331.
Lovell, T. 1988. Nutrition and feeding of fish. Van Nostrand Reinhold, New York.
Madhu, R., Madhu, K. and Retheesh, T. 2013. Breeding and seed production of clown fishes under captivity.
Central Marine Fisheries Research Institute, India.

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Martínez, I.P., Real, M. and Álvarez, R. 2004. Growth of Rana perezi Seoane, 1885 floglets fed on diets withdifferent nutrient compositions. Aquaculture, 241, 387-394.
Silva, F.C.P., Nicoli, J.R., Zambonino-Infante, J.L., Gall, M.L. Kaushik, S. and Gatesoupe, F. 2010.
Influence of partial substitution of dietary fish meal on the activity of digestive enzymes in the intestinal
brush border membrane of gilthed sea bream, Sparus aurata and goldfish, Carassius auratus.
Aquaculture, 306, 233-237.
Watson, C.A. and Hill, J.E. 2006. Design criteria for recirculating, marine ornamental production systems.
Aquacultural Engineering, 34, 157-162.

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Research article
erd

Effect of Nitrous Oxide on Physiological and Biochemical
Changes during Fruit Drop of Longkong Postharvest
INTIRA LICHANPORN*
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi,
Phathum Thani, Thailand
Email: lintira@yahoo.com

NUNCHANOK NANTHACHAI
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi,
Phathum Thani, Thailand

PALIDA TANGANURAT
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi,
Phathum Thani, Thailand

UNCHALIN SINGKHUM
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi,
Phathum Thani, Thailand
Received 23 February 2015

Accepted 1 April 2015(*Corresponding Author)

Abstract Longkong (Aglaia dookkoo Griff) is a popular tropical fruit which currently has
about 99.37% consumer demand. In the case of exporting, the main problem is that
longkong fruit drops from its bunch after harvesting. Therefore, the objective of thisresearch is to study the effect of nitrous oxide on physiological and biochemical changes
during fruit drop of longkong postharvest. The addition of 90% nitrous oxide (at times 1, 3,
6, 12 and 24 h) induced the reduction of loosening of longkong fruit after harvest. Exposure
to nitrous oxide delayed the onset of fruit drop of the longkong bunches with the mosteffective treatment being fumigation with 90% nitrous oxide for 6 h. Longkong fruit
exposed to 90% nitrous oxide for 24 h, showed an increased respiration rate and ethylene
production. While Longkong fruit exposed to 90% nitrous oxide, there was no significant
effect on the activity of enzymes polygalacturonase (PG), pectinesterase (PE), cellulase(Cx) and peroxidase (POD) during storage.
Keywords longkong, fruit drop, nitrous oxide

INTRODUCTION
Longkong (Aglaia dookkoo Griff.) is a subtropical fruit which can be grown in various parts ofThailand. The quality deterioration of longkong leads to consumer rejection that makes the productcannot be sold. Besides, there is a loss of economic value for both producers and consumers.
Senescence of longkong can be seen as browning, disease, and fruit drop, which is a criticalproblem that results in a lower sales price. The study of morphology shows change in abscission
zone (AZ) area which has cell wall degradation in the middle lamella (Oberholster et al., 1991;
Sexton et al., 1983) as well as microfibril expansion and disorganization in the primary cell wall in
the AZ (Sexton and Robert, 1982). Enzymes associated with degradation of the cell wall are pectin
esterase (PE), endo-polygalacturonidase (PG), exopolygalacturonase, rhamnogalacturonase, ∞galactosidase and cellulase (Downs et al., 1992). In grapes, the stem of the fruit becomes detachedfrom the fruit in the area which gradually extends from the sides of the phloem until the middle ofthe tissue and causes fruit drop. The fruit drop of grapes is related to an increase of the cellulose
enzymes hydrolases and polygalacturanase in AZ (Deng et al., 2007). Nitrous oxide (N2O) is anatural occurrence of atmospheric gas principally produced by aerobic denitrifying bacteria in soil,
which has been demonstrated to inhibit ethylene action and synthesis in higher plants (Frontiera etⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

al., 1994; Gouble et al., 1995; Leshem and Wills, 1998). N2O, like CO2, has an isosteric linear
structure that confers similar physical properties such as relative stability and high solubility toboth molecules (Leshem and Wills, 1998; Benkeblia and Varoquaux, 2003). This biophysicalsimilarity of N2O to CO2 might be pertinent to the control of ethylene in the controlled atmospherestorage of postharvest climacteric fruit (Leshem andWills, 1998). In addition, N2O is not toxic. It is
used in medical practice as an anaesthetic (Gouble et al., 1995), and it is a permitted additive forfood (Benkeblia and Varoquaux, 2003). Other studies report the inhibition of postharvest decay offruit by N2O, which have also been carried out in the non-climacteric strawberry and mandarin, andin the climacteric fruit apple, persimmon and tomato (Qadir and Hashinaga, 2001). Therefore, inthis study, we determined the effects of N2O gas on the reduction of fruit drop of longkong after
harvest.
OBJECTIVES
The objective of this study was to determine effects of N2O gas on the reduction of fruit drop of
longkong after harvest.
METHODOLOGY
Freshly harvested bunches of longkong with full yellow fruits were procured from a commercial
orchard. Each bunch longkong was separated into individual bunches, which were placed intosealed plastic chambers with 90% N2O with 20% O2 for 0, 1, 3, 6, 12 or 24 hours at 20qC. After
treatment, the fruits were stored at 13qC with 90+5% relative humidity. The treatments werereplicated three times with 25 fruit bunches per replication. Standard procedures were followed inmeasuring fruit drop, weight loss, respiration rate (Gemma et al., 1994), ethylene production(Gemma et al., 1994), PG (Lohani et al., 2004; Pathak and Sanwal, 1998), PME (Abu-Goukh andBashir, 2003; Nagel and Patterson, 1967), Cx and POD activities (Lohani et al., 2004).
RESULTS AND DISCUSSION
Longkong fruit was fumigated with 90% nitrous oxide (N2O) for 0, 3, 6, 12 and 24 hours followed
by storage at 13 qC. The result showed that the longkong fumigated with 90% N2O for 0, 6 and 24
hours delayed the fruit drop for 6 days. At hour 6, the fruit drop of longkong was 11.69%, whereas
longkong fumigated with 90% N2O for 12 hours had the highest occurrence of fruit drop with84.21% on day 12 of storage (Fig. 1A). Weight loss of longkong fumigated with N2O increased
over the duration of storage, which averaged 4% weight loss (Fig. 1B).
There was no statistical comparison of the relative effect of weight loss and nitrous oxide
because the low temperature storage delayed the weight loss and reduced deterioration of the
longkong.The respiration rate of longkong fumigated and non-fumigated with N2O slowly
increased during storage time, the control fruit had a lower respiration rate than the longkong
fumigated with N2O, especially with fumigation for 24 hours which had the highest rate ofrespiration in day 12 of storage (76.77 mL CO2.kg-1.h-1 ) (Fig. 2C).
Fruit fumigated with N2O for long time may result in an increase in respiration and ethylene
production rates (Oszmianski et al., 1985: Macheix et al., 1990). Ethylene production of longkong
fumigated with N2O for 24 hours rapidly increased more than that of other fumigations on day 3
and day 6 of storage. However, longkong fumigated with N2O less than 3 hours had lower theethylene production on day 3. It is possible that N2O may delay deterioration through two
mechanical formulas (Gouble et al, 1995; Bemish et al, 1996). In the first form, N2O bonded with
ethylene. In the second form, N2O inhibited ACC Oxidase (ACO) and synthesis ACC synthase(ACS) with N2O and CO2, which both forms had similar functions. However, the effect of N2O andCO2 maintained the quality of strawberry (Qadir et al., 2000). If N2O bonded with ethylene, thenethylene could not bond with itself. It was resulting in delay of the senescence for a short time,Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

which ripening or senescence occurred. At day 12, there was no significant difference for theethylene production in all treatments (Fig. 2D).
Research in other fruit species indicates that hydrolytic enzymes, including endo-beta-1, 4glucanase (cellulose), polygalacturonase (PG), pectinmethylesterase (PME), play a significant rolein the abscission stage by affecting middle lamella dissolution and cell-wall degradation andstimulating with exogenous ethylene (Tucker et al., 1984; Taylor et al., 2001), as well as with highactivity when there was fruit drop such as with grapes (Deng et al., 2007). As a result, pectin
methylesterase (PME) activity in the first day was equal to 0.040 unit/mg protein, after that theactivity decreased in the longkong fumigated with N2O for 3 hours on day 3 and 6 of the storage.
Subsequently, activity of enzymes increased at first and then decreased in the end of storage, while
longkong fumigated with N2O for 12 and 24 hours maintained the activity of PME during storage(Fig. 2E). Polygalacturonase activity increased after storage until day 6 and reduced over the
storage. Longkong fumigated with N2O for 6 and 12 hours had lower polygalacturonase activity
than the control fruit on 3 day of storage. (Fig. 2F). Cellulase activities increased until the
maximum on day 6 and then reduced after that. On day 3, Longkong fumigated with N 2O for eachtime period had higher cellulase activity than the control fruit (Fig. 2G). Peroxidase enzymes
activities of fumigation and control fruit showed no statistical difference in the peroxidase activity
on 3 days of storage, reduced the activity on day 6, and increased on day 9 of storage. Longkong
fumigated with N2O for 3 and 6 hours had the peroxidase enzyme activity equal to 0.280 and 0.353
unit/mg protein, while longkong fumigated with N2O for 0, 1, 12 and 24 hours had the activity
equal to 0.570, 0.507, 0.570 and 0.597 unit/mg protein, respectively (Fig. 2H).

Fruit drop (%)

100
80

90% N2 O, 0 hr.
90% N2 O, 1 hr.
90% N2 O, 3 hr.
90% N2 O, 6 hr.
90% N2 O, 12 hr.
90% N2 O, 24 hr.

A

60
40
20
0
0

Weight loss (%)

10
8

3

6

9

12

Days after storage

90% N2 O, 0 hr.
90% N2 O, 1 hr.
90% N2 O, 3 hr.
90% N2 O, 6 hr.
90% N2 O, 12 hr.
90% N2 O, 24 hr.

B

6
4
2
0
0

3

6

9

12

Days after storage

Fig. 1 Change in fruit drop (A), weight loss (B) in abscission zone of longkong exposed to
90% nitrous oxide for 0, 1, 3, 6, 12 or 24 h and then stored at 13 qCⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Fig. 2 Change in respiration rate (C), ethylene production (D), pectin methylesterase (E),polygalacturonase (F), peroxidase (G), cellulose (H) in abscission zone of longkong
exposed to 90% nitrous oxide for 0, 1, 3, 6, 12 or 24 h and then stored at 13 qC
CONCLUSION
Longkong fumigated with 90% N2O for 6 hours, delayed the fruit drop but showed no effect on
activities of PG, PME, Cx and POD during storage.

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ACKNOWLEDGEMENTS
This work was supported by Faculty of Agricultural Technology, Rajamangala University ofTechnology Thanyaburi (RMUTT) and Thailand Toray Science Foundation (TTSF).
REFERENCE
Abu-Goukh, A.A. and Bashir, H.A. 2003. Changes in pectic enzymes and cellulase activity during guava
fruit ripening. Food Chemistry, 83, 213-218.
Bemish, R.J., Rhee, W.M. and Miller, R.E. 1996. The structure and intramolecular dynamics of the nitrous
oxide-ethylene complex: Experiment and ab initio theory. Journal of Chemical Physics, 104, 4411.
Benkeblia, N. and Varoquaux, P. 2003. Effect of nitrous oxide (N 2O) on respiration rate, soluble sugars andquality attributes of onion bulbs Allium cepa cv. Rouge Amposta during storage. Postharvest Biology
and Technology, 30, 161-168.
Deng, Y., Wu, Y., Li, Y.F., Yang, M.D., Si, C.B. and Zheng, C.J. 2007. Studies of postharvest berry
abscission of ‘Kyoho’ table grapes during cold storage and high oxygen atmospheres. Postharvest
Biology and Technology, 43, 95-101.
Downs, C.G., Brady, C.J. and Gooley, A. 1992. Exopolygalacturonase protein accumulates late in peach fruit
ripening. Physiologia Plantarum, 85,133-140
Frontiera, M.S., Stabler, S.P., Kolhouse, J.F. and Allen, R.H. 1994. Regulation of methionine metabolism:
effects of nitrous oxide and excess dietary methionine. Journal of Nutritional Biochemistry, 5, 28-38.
Gemma, H., Yuri, M. and Hong-kong, W. 1994. Ripening characteristics and chilling injury of banana fruit
1: Effect of storage temperature on respiration, ethylene production and membrane permeability of peel
and pulp tissue. Japanese Journal of Tropical Agriculture, 38, 216-220.
Gouble, H., Fath, D. and Pierre, S. 1995. Nitrous oxide inhibition of ethylene production in ripening andsenescing climacteric fruits. Postharvest Biology and Technology, 5, 311-321.
Leshem, Y.Y., Wills, R.B.H. and Ku, V.V.V. 1998. Evidence for the function of the free radical gas nitricoxide (NO) as an endogenous maturation and senescence regulating factor in higher plants. Plant
Physiology and Biochemistry, 36, 825-833.
Lohani, S., Trivedi, P.K. and Nath, P. 2004. Changes in activities of cell wall hydrolases during ethyleneinduced ripening in banana: effect of 1-MCP. ABA IAA. Postharvest Biology and Technology, 31, 119126.
Macheix, I., Fleuriet, A. and Billot, J. 1990. Fruit phenolics. Florida, CRC Press, 398.
Nagel, C.W. and Patterson, M.E. 1967. Pectin enzymes and development of the Pears (Pyrus communis).
Journal of Food Science, 32, 292-297.
Oberholster, S.D., Peterson, C.M. and Dute, R.R., 1991. Pedicel abscission of soybean:cytological andultrastructural changes induced by auxin and ethephon. Canadian Journal of Botany, 69, 2177-2186.
Oszmianski, J., Sapis, J.C. and Macheix, J.J. 1985. Changes in grape seed phenols as affected by enzymic
and chemical oxidation In Vitro. Journal of Food Science, 50, 1505-1506.
Pathak, N. and Sanwal, G.G. 1998. Multiple forms of polygalacturonase from banana fruits. Phytochemistry,
48, 249-255.
Qadir, A., Karim, M.R. and Hashinaga. F. 2000. Effect of nitrous oxide on non-climacteric tissue. In:
Improving postharvest technologies of fruits, vegetables and ornamentals. IIR Conference, Murcia, Spain,
19/21 October, 114.
Qadir, A. and Hashinaga, F. 2001. Nitrous inhibits in vitro growth of multiple postharvest fungi. HortScience,
36, 1302-1304.
Sexton, R. and Roberts, J.A. 1982. Cell biology of abscission. Annual Review of Plant Physiology, 33, 133162.
Sexton, R., Struthers, W.A. and Lewis, L.N., 1983. Some observations on the very rapid abscission of thepetals of Geranium robertianum. Protoplasma, 116, 179-186.
Taylor, J.E. and Whitelaw, C.A. 2001. Signals in abscission. New Phytologist, 151, 323-339.
Tucker, G.A., Schindler, B. and Roberts, J.A. 1984. Flower abscission in mutant tomato plants. Planta, 160,
164-167.

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Research article
erdCharacterization of Potential Molave (Vitex parviflora Juss.)
Mother Trees in Lila, Bohol, Philippines
NOEL T. LOMOSBOG*
Bohol Island State University, Bohol, Philippines
Email: ntl4747@yahoo.com

NOEL S. GAMIL
Bohol Island State University, Bohol, Philippines
Received 16 December 2014

Accepted 1 April 2015(*Corresponding Author)

Abstract Molave (Vitex parviflora Juss.) is a timber species which naturally grows in theprovince of Bohol and is considered as the province’ flagship timber species. Molave isgenerally used for furniture, hand tools, and is known for its durability as beams on bridges
and as railroad ties without artificial preservatives. Molave is also a recommendedafforestation species in the marginal uplands. The lack of information about the locationand distribution of superior Molave mother trees is a major constraint in scaling up the
production of high quality seedlings of native timber trees in Bohol. The study aimed tophenotypically characterize the potential mother trees in Municipality of Lila, Bohol using
the standard selection criteria (stem straightness, stem forking, branch angle, stem
circularity, tree health, branch thickness, and branch persistence), which were developed by
the Department of Environmental and Natural Resources (DENR). Specifically, to know thenumber of potential, Molave is a mother tree with its merchantable height, diameter andelevation. Molave trees with at least 28 cm in diameter and at least 3 meters in height wereconsidered as potential mother trees. Out of 242 potential mother trees, only 160 trees
satisfied the DENR Administrative Order 2010-11. The average height and Diameter at
Breast Height (DBH) were 5.91 meters and 40.47 cm, respectively. The biggest DBH
recorded is 110 centimeters while the highest merchantable is 12 meters. On the other hand,the average elevation was 120.9 meters above sea level. Many good Molave mother trees inLila, Bohol, Philippines are qualified to provide seed for tree propagation and to produce
quality seedlings for reforestation of the Bohol upland areas especially on the National
Greening Program (NGP) of the Philippine government.
Keywords Molave tree, mother tree, phenotype, afforestation species

INTRODUCTION
In the Philippines, there is a scarcity of information on the distribution and phenology of premiumindigenous timber species because of limited research and development effort (Gregorio et al.,2006), except for dipterocarps. Most research activities focus on a few exotics that have been usedin large-scale industrial tree plantations, reforestation projects and smallholder tree plantings. The
limited knowledge about the distribution and phenology of mother trees constrains seedling
producers from diversifying their seedling production and has led to the use of wildlings, which
often results in the production of seedlings of low physical quality (Gregorio, 2006). Because of
these reasons, the scaling up of the domestication of native timber trees is constrained by thelimited availability of planting materials and low quality germ plasm.
There is an increasing interest in planting premium indigenous timber species in tree farming,
agroforestry, and reforestation in the Bohol, for ecological and economic reasons. Milan andMargraf (1994) argue that the planting of indigenous trees promotes biological diversity. Generally,
the timber quality of native timber trees (including Molave) is superior to that of the common
exotics, leading to a higher market value.
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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Molave is a flagship timber species in Bohol generally used for furniture, hand tools, andknown for its durability as beams on bridges and as railroad ties without artificial preservatives.
Molave is a medium to large tree attaining a diameter of 100 to 150 cm and a height from 25 to 30
m. In exceptional cases, it reaches a height of 35 m or more and a diameter up to 200 cm with abole from 16 to 20 cm. It is a tree that grows irregularly too far with a clear bole of 2 m or less inlength (Dichoso, 2000). Fortunately, Molave stands in Lila, Bohol attain a clear bole height of
more than 3 m to a maximum of 8 m, which is sufficient enough to initially qualify as potential
mother trees.
A mother tree is a tree selected from the forest stands, which gather seeds for propagation
purposes (DAO 09, s. 1995). A mother tree should provide a sustained supply of forest tree seeds
and other planting stock for the country’s collection, distribution and use of forest tree seeds andother forms of plating materials.
The government, through Department of Environment and Natural Resources, promotes theuse of high quality planting materials in its afforestation and other afforestation activities topromote biodiversity conservation in marginal uplands/watershed areas (Lomosbog, 2013), and toensure sustainable production and supply of wood and other forest products in the country. In mostrecent government and non-government greening endeavor in the province of Bohol, they are using
low quality planting stocks because of the limited access to phenotypically and genotypically –superior mother trees as a source of planting stocks especially Molave. To increase the possibilityof collecting good quality seed, mother trees should be selected in stands that consist of goodquality trees (Mulawarman et al., 2003).
Therefore, the intention of this study is to assess the possible potential mother trees of Molave
in Lila, Bohol as future sources of seeds in the production of quality planting materials in supportof the National Greening Program (NGP) and other related government and non-government
reforestation endeavor.
OBJECTIVE
The study aimed to phenotypically characterize the potential Molave mother trees in municipalityof Lila Bohol by using the standard DENR selection criteria. Specifically, it sought to know thenumber of potential Molave mother trees and its merchantable height, diameter, and elevation
within each barangay1.
METHODOLOGY
The study was conducted in all barangays of Lila, Bohol, namely: Taug, La Fortuna, Tiguis,
Calvario, Lumanoy, Catugasan, Cayupo, Candulang, Poblacion, Macalingan, Cogon, Nagsulay,
Malinao East, Malinao West, Bonkokan Ilaya, Bonkokan Ubos, Janbawan, and Banban. Lila is atown on the southern coast of Bohol, twenty-eight and a half km from Tagbilaran City. It lies
between Loay and Dimiao. Sometimes it was a part of the latter municipality. The climate is typefour characterized by even distribution of rainfall with dry season in January to May and wet
season in June to December (BAMP, 2006). The classification of land is karst and limestone areas
with a vegetation of grassland and forest areas.
Selection Criteria of the Potential Mother Trees
Potential mother trees were determined based on its: (a) diameter measurement ≥28 cm; (b)merchantable height ≥3 m; (c) stem straightness; (d) stem forking; (e) branch angle; (f) stem
circularity; (g) tree health; (h) branch thickness; and (i) branch persistence (DAO, 2010-11). The
candidate mother trees were rated from 1-6 as shown in Table 1.
1

A barangay (Brgy. or Bgy.; Filipino: baranggay, [baɾaŋˈɡaj]), formerly called barrio, is the smallest administrative division in thePhilippines and is the native Filipino term for a village, district or ward.

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Table 1 Selection criteria for potential mother trees and their corresponding ratings
Criteria
Stem straightness
Stem forking
Branch angle
Stem circularity
Tree healthBranch thickness

6
Perfectly straight
Forking above 6m

Rating Scales
5
4-3
Slight bending
Bending
Forking between 6m
Forking below 3mand 3mBranches forming
Branches forming
90˚
between 90˚ and 75˚Stem is roundNot perfectly round
Green-lushIntermediate
vigorous crownThin branches relative to tree size

Branches forming
between 75˚ and 60˚Oblong shapeThin yellow crown

2-1
Over bending
Multi-stem forking
Branches forming
between 60˚ and 45˚
No shape

Intermediate

Thick coarse
branches relative totree size
Branch persistence
Dry branches shed relatively fast afterIntermediate
Dry branches remain
canopy closureon the stem forseveral years after
canopy closure
Source: DAO (2010) (1 as very unacceptable; 2 as unacceptable; 3 for relatively acceptable; 4 as fair; 5 as good; and 6
as highly acceptable)

Data Collection and Analysis
Diameter at breast height of each potential Molave mother tree was measured using improvised
Molave tree caliper. The tree caliper was placed at the right angle to the trunk at a point 1.3 m
above the ground. For trees growing on slopes, it was recommended that DBH be measured fromthe uphill side of the tree.
Merchantable heights of potential mother trees of Molave were determined using simple
ocular estimation. Merchantable height was estimated from the first big branch of the Molave tree.
After determining the diameter and height of the potential mother trees, the trees were marked
with yellow enamel paint to serve as permanent marker or a guide mark during the determination ofelevation and coordinates.
Assessment of the potential mother trees of Molave was limited only on the stem straightness,stem branching, stem circularity, tree health, branch angle, branch thickness, and branchpersistence as physical tree attributes.
Global Positioning System (GPS) units were used to determine the locations (elevation) of
each potential Molave mother tree per barangay. Each mother tree was given its own unique codefor future mapping purposes.
The study used frequency counts and simple percentage functions of Microsoft Office Excel
2007 Data Analysis as statistical analysis.
RESULTS AND DISCUSSION
Number of Potential Mother Trees
The potential mother trees of Molave in Lila, Bohol were evaluated using the DENR assessment
criteria. Out of 242 potential mother trees of Molave, only 160 (66.12%) trees obtained a rating of“good”; on the other hand, 82 (33.88%) trees garnered a rating of “fair”. Of the 160 Molave mothertrees rated as “good”, barangay Bongkokan Ubos had the most number of mother trees with 22(68.75%), followed by barangay Catugasan with 21 (80.77%). On the other hand, barangays
Cayupo, Candulang and Macalingan had the same number of good Molave mother trees with 16,
while barangay Calvario had the least number of good mother tree with only one (Table 2).

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Table 2 Number of Molave mother trees per barangay
Name of Barangays
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.

Bongkokan Ubos
Catugasan
Candulang
CayupoMacalingan
Lumanoy
Cogon
Taug
TiguisMalinao West
Jambawan
Bongkokan Ilaya
Malinao East
La Fortuna
BanbanNagsulay
Poblacion
Calvario
Total

Good
22
21
16
16
16
11
8
7
7
6
6
4
4
4
4
4
3
1
160

%
68.75
80.77
64.00
76.19
94.12
40.74
88.89
46.67
70.00
66.67
54.55
80.00
80.00
50.00
100.00
80.00
33.33
25.00
66.12

Number of trees
Fair
10
5
5
9
1
16
1
8
3
3
5
0
4
1
1
1
6
3
82

%
31.25
19.23
36.00
23.81
5.88
59.26
11.11
53.33
30.00
33.33
45.45
20.00
20.00
50.00
0.00
20.00
66.67
75.00
33.88

Total
32
26
21
25
17
27
9
15
10
9
11
4
8
5
5
5
9
4
242

%=percentage

Merchantable Height
Table 3 presents the average merchantable height (m) of potential mother trees of Molave perbarangay in Lila, Bohol. A total of 242 potential mother trees was identified in the study. Potential
Molave mother trees in barangay Bongkokan Ilaya had the highest average height of 8.75 m,
followed by barangays Lomanoy, Malinao East, Malinao West, and Jambawan with 7.33 m, 6.65m, 6.56 m, and 6.18 m, respectively. The said barangays were the first five barangays in Lila,
Bohol having the most abundant potential Molave trees, which at least 3 meter height were found(Fig. 1b). On the other hand, barangay Poblacion of Lila, Bohol had the lowest average height ofpotential Molave mother trees with 4.11m.
ab

Fig. 1 Molave mother tree assessed based on stem growth such as (a) diameter measurementand (b) merchantable height
Diameter at Breast Height (DBH)
Among the 242 potential mother trees of Molave in Lila Bohol, barangay Catugasan had thebiggest average Diameter at Breast Height of 55.85 cm, followed by barangays Bongkokan Ubos,Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Macalingan, Tiguis and La Fortuna with average DBH of 46.69 cm, 45.53 cm, 44.50 cm and 43.80
cm, respectively. Moreover, barangay Jambawan had the smallest average DBH of 33.82 cm(Table 3).
Elevation
Table 3 illustrates the average elevation in meters above sea level (masl) of potential mother treesof Molave per barangay in Lila, Bohol. The table further shows that barangay Jambawan had thehighest elevation of 221.6 masl, followed by barangay Calvario with 220 masl. On the other hand,barangays Malinao West, Malinao East and La Fortuna had the next top elevations of 132.2, 126.4,
and 123.2 masl, respectively.
Table 3 Merchantable height, diameter at breast height and elevation of Molave mother trees
per barangay
Name of Barangays
1.
2.

Bongkokan Ubos
Catugasan

3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.

Candulang
CayupoMacalingan
Lumanoy
Cogon
Taug
TiguisMalinao West
Jambawan
Bongkokan Ilaya
Malinao East
La Fortuna
BanbanNagsulay
Poblacion
Calvario
Averagemasl (meters above sea level)

Merchantable Height(m)

Diameter at Breast Height(cm)

Average Elevation(masl)

5.61
5.12

46.69
55.85

80.10
112.40

6.00
5.68
5.29
7.33
5.56
5.40
5.40
6.56
6.18
8.75
6.75
6.00
5.60
5.00
4.11
6.00
5.91

36.00
40.68
45.53
39.37
39.00
39.33
44.50
34.89
33.82
41.25
35.67
43.80
36.25
36.80
42.89
36.20
40.47

113.80117.90119.70120.50123.00100.10115.70132.20221.60109.20126.40123.20
75.60
73.20
92.00
220.00120.92

CONCLUSION
A lot of good Molave mother trees in Lila, Bohol, Philippines met the requirements to provide
quality seed and seedlings based on DAO 2010-11 for reforestation of the Bohol upland areas,
especially on the National Greening Program (NGP) of the Philippine government. A total of 160
Molave trees was considered as good mother trees sporadically distributed in five barangays of Lila,
Bohol namely Bongkokan Ubos, Catugasan, Cayupo, Candulang and Macalingan. The heightmeasurements of the good mother trees ranged from 6.18 m to 8.75 m while its diameter ranged
from 43.80 cm to as big as 55.85 cm.
It is recommended to conduct Geo Tagging of the identified good Molave mothers for seed
documentation and exact location of seed sources. Furthermore, it is needed to provide financial
benefits and technical assistance to land owners who continuously protect the growing Molave
mother trees.

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ACKNOWLEDGEMENTS
1. Bohol Island State University - for the support in the conduct of the Study
2. Local Government Units of Lila, Bohol - for allowing the researchers to conduct this Study
3. The Punong Barangay (Captains) of the 18 barangays of Lila, Bohol - for the assistance during
the actual field data gatherings
4. DENR Extension Officer assigned in Lila, Bohol – for the company in the initial field locationof the potential mother tree of Molave
REFERENCES
BAMP. 2006. Bohol Agricultural Master Plan (2006-2026). Provincial Government of Bohol, Philippines.
Department Administrative Order 1995-09. Regulation of forest tree seed production, collection anddispositions, signed by Secretary Angel C. Alcala on 29 March 1995.
Department Administrative Order 2010-11. Revised regulations governing forest tree seed and seedling
production, collection and disposition, signed by Secretary Horacio Ramos on 5 May 2010.
Dichoso, W.C. 2000. Useful plant species with toxic substance. Research Information Series on Ecosystems(RICE). DENR-ERDB Los Bańos Laguna, Philippines. 12, 2, May-August 2000, 7-8.
Gregorio, N.O. 2006. Improving the effectiveness of the forest nursery industry in Leyte Province, thePhilippines, PhD thesis, The University of Queensland, Gatton, Australia.
Gregorio, N.O., Doydora, U., Harrison, S., Herbohn, J., and Sebua, J. 2006. Inventory and assessment ofmother trees of indigenous timber species on Leyte Island and Southern Mindanao, Philippines. ACIAR
Seedling Enhancement Project.
Lomosbog, N.T. 2013. Upland development program in Bohol watersheds: A rehabilitation and climatechange mitigation strategies, Ph.D. dissertation, College of Advanced Studies, Bohol Island State
University, Main Campus, Tagbilaran City, Philippines.
Milan, P. and Margraf, J. 1994. ‘Rainforestation farming: An alternative to conventional concepts’, Annals of
Tropical Research, 16, 4, 17-27.
Mulawarman, Roshetko, J.M., Sasongko, S.M. and Irianto, D. 2003. Tree seed management – seed sources,
seed collection and seed handling: A field manual for field workers and farmers. International Centre for
Research in Agroforestry (ICRAF) and Winrock International. Bogor, Indonesia.

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Research article
erd

Efficiency of Crude Extract from Pummelo Peel onControlling the Growth of Colletotrichum gloeosporioides(Penz.)NUNCHANOK NANTHACHAI*
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi,
Phathum Thani, Thailand
Email: eaye22@yahoo.com

INTIRA LICHANPORN
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi,
Phathum Thani, Thailand

PALIDA TANGANURAT
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi,
Phathum Thani, Thailand

UNCHALIN SINGKHUM
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi,
Phathum Thani, Thailand
Received 15 December 2014

Accepted 1 April 2015(*Corresponding Author)

Abstract The objective of this research was to investigate the antifungal efficiency ofpummelo peel extracted with different solvents on Colletotrichum gloeosporioides. Crude
extracts from pummelo peels were eluted with four solvents, such as ethanol, hexane,
dichloromethane and ethyl acetate. Chemical compounds of the crude extracts wereanalyzed by GC-MS and HPLC and inhibition the growth of C. gloeosporioides was tested
by PDA culture. The result showed that limonene was the major compound in all extracts(79.55-89.91%). D-Phellandrene and 2, 6-octadien-1-ol, 3, 7-dimethyl were found only incrude extracts using ethyl acetate as a solvent. In addition, the extract was eluted with ethyl
acetate also had the amount of flavonoids: nobiletin and 3-hydroxy-7, 3’, 4’, 5’tetramethoxyflavone, higher than those eluted with other solvents. Inhibition the growth of
C. gloeosporioides of pummelo peel extracted with dichloromethane, ethanol, hexane andethyl acetate were 19.16, 52.81, 65.58, and 95.61%, respectively. Therefore, pummelo peel
extracted with ethyl acetate was the highest efficiency on controlling C. gloeosporioides (pd 0.05).
Keywords Crude extract, pummelo, C.gloeosporioides

INTRODUCTION
Mango is one of the most popular and best known tropical fruits (MacLeod and Troconis, 1982;
MacLeod and Pieris, 1984). It is a highly priced fruit due to its attractive color, delicious taste, andhigh nutritional values (Mitra and Baldwin, 1997; Lalel et al., 2003). Traditionally, the majormango exporting countries are the Philippines, Thailand, Mexico, and India (Jacobi et al., 2001).
Many different ripening conditions, postharvest treatments, and processing methods are used toprepare mangoes for marketing to consumers (Moore, 2003). Its short shelf life limits thecommercialization at long distances. It is also highly susceptible to damages caused by fungi,
bacteria and fruit fly larvae (Diaz-Sobac et al., 1996).
Anthracnose is a major pre‐ and post‐harvest disease on mangoes, causing direct yield loss inthe field and packing plant, and quality and marketing issues (Ploetz, n.d.).Mango anthracnose isⒸ ISERD

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caused by the fungus Colletotrichum gloeosporioides (Pitkethley and Conde, 2007). Ripe fruits
affected by anthracnose develop sunken, prominent, dark brown to black decay spots before orafter picking. The fruit spots can usually do coalesce and can eventually penetrate deep into thefruit, resulting in extensive fruit rotting. Most green fruit infections remain latent and largely
invisible until ripening (Nelson, 2008). Post-harvest treatments are available for control ofanthracnose in mango fruits. Prochloraz is used as a cold nonrecirculating spray. Hot water dips,used to control fruit flies, will also control anthracnose and stem end rots. Hot benomyl dips willcontrol anthracnose and are useful where stem end rots are a problem (Pitkethley and Conde,2007). However, there are many studies using plant extracts such as essential oils and purecompounds against plant pathogenic fungi, which have been conducted. Antifungal compounds
have been found in plants, derived from secondary metabolites such as tannins, terpenoids,
alkaloids and flavonoids (Arif et al., 2009).
Pummelo (Citrus grandis or Citrus maxima) is an original citrus fruit, with the look of a big
grapefruit, native to South and Southeast Asia. Citrus fruits contain several bioactive compounds
such as flavonoids, limonoids, and organic acid. Polymethoxyflavones are group of flavonoids that
present mainly in the fruit peel. There are some reports that show polymethoxyflavones, which areimportant components of plant defensive mechanism against various diseases causing pathogens
such as phytophthora and Colletotrichum gloeosporioides (Del Rio et al., 1998; Ortuño et al., 2006;
Uckoo et al., 2011). Thus, this research aimed to investigate the major volatile compounds,
flavonoids and polymethoxyflavones as well as the antifungal efficiency of crude extract frompummelo peel on C. gloeosporioides.
OBJECTIVESThe study was conducted with the following objectives:
1. To determine the major volatile compounds and flavonoids of crude extract from pummelo peel;and2. To investigate the effect of crude extracts from pummelo peel on inhibition the growth ofColletotrichum gloeosporioides.
METHODOLOGY
Pummelo was purchased from a commercial market in Phathumtani province, Thailand. The
flavedo of the fruit was cut into small pieces and then immersed with a solvent for 24 hours and theratio of peel and solvent was 1:3. The four solvents were ethanol, dichloromethane, hexane andethyl acetate which were used in this experiment. The extracts were pooled and evaporated at 40 oC
using a rotary evaporator. Then the extracts were stored at freezer until used. Volatile compounds
and polymethoxyflavones in the extracts were analyzed by GC-MS and HPLC. Each sample wasanalyzed in triplicate.
C. gloeosporioides was isolated from infected mango fruits with typical symptoms andmaintained on potato dextrose agar (PDA) at 25 oC for seven days. The pathogen was inoculated
into mango and re-isolated on PDA before the experiment.
The effect of extracts from pummelo peel on mycelial growth of C. Gloeosporioides was
assayed by modifying the method of Liu et al., (2007). Mycelial disks (5 mm in diameter) fromone-week-old culture of C. gloeosporioides were placed in the center of Petri dishes containing 20
ml of PDA with the 10,000 ppm extracts eluted with different solvents, and then incubated at 25oC.
The plate without the extract served as the control. Mycelial growth was determined by measuringcolony diameter (mm) each day after inoculation. Each treatment was five times replicated, and theexperiment was repeated thrice. The inhibition rate on mycelial growth was calculated according to
the following formula: Inhibitory rate (%) = 100 x (colony diameter of the control − colony
diameter of the treatment) / (colony diameter of the control).

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RESULTS AND DISCUSSION
Pummelo peel in this study had the color L* a* and b*, which the values were between 62.8-67.6,
3.1-8.7 and 47.3-48.7, respectively. Chemical compounds of the crude extracts were analyzed by
GC-MS (Table 1) and HPLC (Table 2). The result showed that the extract from pummelo peel was
eluted with ethyl acetate that could identify volatile components and flavonoids better than those
extracted with dichloromethane, hexane and ethanol (Table 1). Terpenes were the major
components in extracts of pummelo peel. Volatile compounds were always found in citrus such aspinene, sabinene, myrcene, phellandrene, limonene, ociemene, linalool, terineol, carvone,caryophyllene, and geraniol. Ester such as geranyl acetate was also found in the extracts. Limonene
was the major compound in all extracts (79.55 - 89.91%) and the result was consistent with Hosni
et al., (2010). However, this research could identify the compounds of the extracts less than anotherresearch. This might be due to the difference of solvents and extraction methods. Hosni et al.,(2010) used both of pummelo flavedos and leaves in their research as well. Linalool was also foundin all extracts; however, it was presented in very small amounts (0.20 - 2.22% peak area).
Jabalpurwala et al., (2009) found that linalool was the main compound in pummelo blossom. DPhellandrene and 2, 6-octadien-1-ol, 3, 7-dimethyl were found only in crude extracts using ethyl
acetate as a solvent.
Table1 Volatile compounds (% peak area) of extracts from pummelo peel eluted
with four solvents
Volatile Compounds
D-Pinene
Sabinene
E-Pinene
E-Myrcene
D-Phellandrene
Limonene
E-Ociemene
Linalool
D-Terpineol
2-Cyclohexen-1-ol, 2-methyl-5-(1methylethene)-cis
D-Carvone
2,6-Octadien-1-ol, 3,7-dimethyl
Geraniol
Geranyl acetate
Caryophyllene
1,6-Cyclodecadiene, 1-methyl-5-methylene8-(1-methylethyl)nd: Not detected

Ethanol
nd
nd
nd
0.35
nd
79.55
nd
2.22
nd
nd

Hexane
0.42
0.98
nd
1.49
nd
81.52
0.19
0.20
nd
nd

Solvent
Dichloromethane
nd
nd
1.52
nd
nd
84.62
0.167
0.63
0.76
0.21

Ethyl acetate
0.72
nd
2.26
2.54
0.20
89.91
0.15
0.28
nd
nd

nd
nd
nd
0.47
0.55
0.73

nd
nd
nd
nd
0.25
1.17

0.28
nd
0.44
nd
nd
nd

nd
0.58
0.30
0.12
0.10
0.71

Citrus peel was rich in flavanones and polymethoxlated flavones (Ortuño et al., 2006).
Nobiletin in the extracts were eluted with ethanol, dichloromethane, hexane, and ethyl acetate were
4.87, 0.20, 0.24 and 0.68%, respectively. Tangeretin of pummelo peel extracted with ethanol,
dichloromethane, hexane and ethyl acetate were 7.39, 4.36, 0.10 and 7.80%, respectively.
Polymethoxyflavones were groups of flavonoids that presented mainly in the fruit peel. These
compounds had two or more methoxyl’s on their basic flavonoid structure (Uckoo et al., 2011).
Pummelo peel extracted with ethanol had very small amount of 3, 6, 3’, 4’-tetramethoxyflavone(0.66%), when compared to other solvent extractions. And 3-hydroxy-7,3’,4’,5’tetramethoxyflavonein the extract were eluted with hexane, and dichloromethane were found only
0.34 and 0.47%, respectively. Whereas extraction pummelo peel with ethanol and ethyl acetate had
3-hydroxy-7, 3’, 4’, 5’-tetramethoxyflavone higher than 7.00% (Table 2).

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Table2 Flavonoids and polymethoxyflavones (% peak area) of extracts
from pummelo peel eluted with four solvents
Flavonoids and Polymethoxyflavones
Nobiletin
3, 6, 3’, 4’-Tetramethoxyflavone
3-Hydroxy-7, 3’, 4’, 5’- tetramethoxyflavone
Tangeretin

Ethanol
4.87
0.66
8.35
7.39

Hexane
0.20
77.44
0.34
4.36

Solvent
Dichloromethane
0.24
70.59
0.47
0.10

Ethyl acetate
0.68
75.72
7.67
7.80

Figure 1 showed that mycelial growth of C. gloeosporioides on PDA plate without the extract
served as the control. Antifungal efficiency of crude extract from pummelo peel on C.
gloeosporioides was showed in table 3 and figure 2. Inhibition the growth of C. gloeosporioides ofpummelo peel extracted with dichloromethane, ethanol, hexane and ethyl acetate were 19.16, 52.81,
65.58 and 95.61%, respectively. Thus, pummelo peel extracted with ethyl acetate was the highest
efficiency on controlling C. gloeosporioides (p d 0.05). Polymethoxyflavones are importantcomponent of plant defensive mechanism against various disease causing pathogens such as
Phytophthora and C. gloeosporioides (Del Rio et al., 1998). The present study found two
compounds of polymethoxyflavones; 3, 6, 3’, 4’-tetramethoxyflavone and 3-hydroxy-7, 3’, 4’, 5’tetramethoxyflavone. Extraction of pummelo peel with hexane and dichloromethane had the highpeak area of 3, 6, 3’, 4’-tetramethoxyflavone (more than 70%), while 3-hydroxy-7, 3’, 4’, 5’tetramethoxyflavone were only 0.34 and 0.47%, respectively. On the contrary, the extract eluted
with ethanol had a higher 3-hydroxy-7, 3’, 4’, 5’- tetramethoxyflavone (8.35%), whereas 3, 6, 3',4'-tetramethoxyflavone was very low. Extraction of pummelo peel with ethyl acetate had the highpeak area of both 3, 6, 3’, 4’-tetramethoxyflavone and 3-hydroxy-7, 3’, 4’, 5’-tetramethoxyflavone
were 75.72 and 7.67%, respectively, which was different from the extracts eluted with othersolvents. Therefore, this might be the cause of effectiveness in inhibiting the growth of C.
gloeosporioides.
Table 3 Effect of crude extracts from pummelo peel eluted with four solventson the growth of C. gloeosporioides
Solvent

Inhibitory rate (%)
52.81b65.58b
19.16c95.61aEthanol
HexaneDichloromethane
Ethyl acetate

Mean of the same column with different superscripts indicating significantly differences (p ≤ 0.05)

Fig. 1 Mycelial growth of C. gloeosporioides (on plate without crude extractfrom pummelo; control) after incubated at 25oC for 7 days

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Fig. 2 Effect of extracts from pummelo peel eluted with ethanol (A), hexane (B),dichloromethane (C) and ethyl acetate (D) on mycelial growth of C. gloeosporioides
after incubated at 25oC for 7 days
CONCLUSION
The major volatile compound of crude extract from pummelo peel was limonene. The extract
eluted with ethyl acetate had the most volatile components, followed by the extraction withdichloromethane, hexane, and ethanol, respectively. Flavonoids (nobiletin and tangeretin) andpolymethoxyflavones (3, 6, 3’, 4’-tetramethoxyflavone and 3-hydroxy-7, 3’, 4’, 5’tetramethoxyflavone) were found in all solvent extractions. However, the extract eluted with ethyl
acetate had the amount of nobiletin and 3-hydroxy-7, 3’, 4’, 5’- tetramethoxyflavone, which werehigher than those eluted with other solvents.
Inhibition the growth of C. gloeosporioides of pummelo peel extracted with dichloromethane,
ethanol, hexane and ethyl acetate were 19.16, 52.81, 65.58, and 95.61%, respectively. The crude
extract of pummelo peel eluted with ethyl acetate was the highest efficiency on controllingmycelial growth of C. gloeosporioides.
ACKNOWLEDGEMENTS
This work was supported by National Research Council of Thailand (NRCT) and Faculty ofAgricultural Technology, Rajamangala University of Technology Thanyaburi (RMUTT).
REFERENCES
Arif, T., Mandal, T.K. and Dabur, R. 2009. Natural products–antifungal agents derived from plants. Journalof Asian Natural Products Research, 11, 621-638.
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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Del Rio, J.A., Arcas, M.C., Benavente-Garcia, O. and Ortuno, A. 1998. Citrus poymethoylated flavones canconfer resistance against Phytophthora citrophthora, Penicillium digitatum and Geotrichum species.
Journal of Agricultural and Food Chemistry. 46, 4423-4428.
Diaz-Sobac, R., Luna, A.V., Beristain, C., De La Cruz, J. and Garcia, H.S. 1996. Emulsion coating to extend
postharvest life of mango (Mangifera indica cv. Manila). Journal of Food Processing and Preservation.
20, 191-202.
Hosni, K., Zahed, N., Chrif, R., Abid, I., Medfei, W., Kallel, M., Brahim, N.B. and Sebei, H. 2010.
Composition of peel essential oils from four selected Tunisian Citrus species: Evidence for the genotypic
influence. Food Chemistry. 123, 1089-1104.
Jabalpurwala, F.A., Smoot, J.M. and Rouseff, R.L 2009. A comparison of citrus blossom volatiles.
Phytochemistry. 70, 1428-1434.
Jacobi, K.K., MacRae, E.A. and Hetherington, S.E. 2001. Postharvest heat disinfestation treatments ofmango fruit: a review. Scientia Horticulturae. 89, 171-193.
Lalel, H.J.D., Singh, Z. and Tan, S.C. 2003a. Glycosidically-bound aroma volatile compounds in the skin andpulp of ‘Kensington Pride’ mango fruit at different stages of maturity. Postharvest Biology andTechnology. 29, 205-218.
Liu, J., Tian, S.P., Meng, X.H. and Xu, Y. 2007. Control effects of chitosan on post-harvest diseases andphysiological response of tomato fruit. Postharvest Biology and Technology, 44, 300-306.
MacLeod, A.J. and Pieris, N.M. 1984. Comparison of the volatile components of some mango cultivars.
Phytochemistry. 23, 361-366.
MacLeod, A.J. and Troconis, N.G. 1982. Volatile flavor components of mango fruit. Phytochemistry. 21,2523-2526.
Mitra, S.K. and Baldwin, E.A. 1997. Mango. In: Postharvest Physiology and Storage of Tropical and
Subtropical Fruits. Mitra, S.K. (Ed.), pp. 85-122. CAB International, Wallingford, Oxon.
Moore. J.P. 2003. Carotenoid synthesis and retention in mango (Mangifera indica) fruit and puree as
influenced by postharvest and processing treatments. M.S. Thesis, University of Florida.
Nelson, S.C. 2008. Mango anthracnose (Colletotrichum gloeosporioides). Plant Disease. Retrieved
November 29, 2014, from http://www.ctahr.hawaii.edu/oc/freepubs/pdf/pd-48.pdf
Ortuño A., Báidez, A., Gómez, P., Arcas, M.C., Porras, I., García-Lidón, A. and Del Río, J.A. 2006. Citrus
paradisi and Citrus sinesis flavonoids: Their influence in the defence mechanism against Penicillium
digitatum. Food Chemistry. 98, 351-358.
Pitkethley, R. and Conde, B. 2007. Mango Anthracnose. Agnote No: I23. Retrieved November 29, 2014,
from http://www.nt.gov.au/d/Content/File/p/Plant_Pest/604.pdf
Ploetz, R.C. (n.d.) Anthracnose of mango: Management of the most important pre‐ and post‐harvest disease.
Retrieved November 29, 2014, from http://www.mango.org/media/55703/anthracnose_of_mango.pdf
Uckoo, R.M., Jayaprakasha, G.K. and Patil, B.S. 2011. Rapid separation method of polymethoxyflavonesfrom citrus using flash chromatography. Separation and Purification Technology. 81, 151-158.

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Research article
erd

Utilization of Coconut Fronds for Weed and Insect Pest
Management in Tomato Production
MARINA A. LABONITE*
Bohol Island State University-Bilar Campus, Bohol, Philippines
Email: mtalabonite@yahoo.com.ph

SANDRA MCDOUGALL
Australian Center for International Agricultural Research, Australia

GORDON ROGERS
Australian Center for International Agricultural Research, Australia

JOSE G. LABONITE
Bohol Island State University-Bilar Campus, Bohol, Philippines

DENNIS B. JOMOC
Bohol Island State University-Bilar Campus, Bohol, Philippines

MERIGINE C. OTARA
Bohol Island State University-Bilar Campus, Bohol, Philippines
Received 15 February 2015

Accepted 7 April 2015(*Corresponding Author)

Abstract The study assessed the effectiveness of coconut frond or cocofrond mulch inmanaging weed and insect pest population in tomato crops. Specifically, it aimed todetermine if cocofrond mulch can reduce weed infestation in tomato; to evaluate its
influence in minimizing insect pest population affecting the crop; and to find out the yield
performance of tomato mulched with cocofronds. Randomized Complete Block Design
with four treatments and four replicates was employed in a 139.50 m2 experimental lot
using the Diamante Max variety. The woven and unwoven cocofronds, polyethylene plastic
mulches, and control plots with hand weeding were compared. Weed and insect pest
species, its population counts, and yield data were taken and analyzed statistically throughanalysis of variance and Tukey’s HSD Test. The findings revealed that either woven or
unwoven coconut frond used as bed mulch was as effective as black plastic mulch insuppressing the dominant broadleaf, the Button weed (Borreria laevis) but had no effect on
the populations of the other 17 minor weed species observed. Bed mulch reduced thenumbers and damage caused by the 12-spotted ladybird beetle (Epilachna philipinensis
remota) larvae but had no effect on its adult population nor on the damage caused by otherpests like the green looper (Chrysodeixis chalcites) and fruitworm (Helicoverpa armigera)
larvae. Neither coconut frond nor black plastic bed mulch had any significant effect on
tomato crop’s yield. These findings are ample basis for a wider exploration on the potential
use of coconut fronds as a low-cost weed and pest management techniques for organic
vegetable production.
Keywords coconut frond, weed management, insect pest management, mulch,broadleaf weed

INTRODUCTION
In the Philippines context, tomato ranks second in the top horticultural crops being produced by a
production industry, which dominated by small scale farmers. Although it is grown widely, theaverage yield in the Philippines is relatively low with 9.79 mt posted in 2005 (PCAARRD, 2007).
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Low production in small scale farming is due to high incidence of diseases, insect pests, and highlogistics costs. Other farmers encounter problems on nutrient deficiency diseases, insect pest
infestation, and weed competition. Weeds reduce yields by competing for space, light, water, andnutrients, weakening crop stand, and by reducing harvest efficiency. Weed infestation throughout
the crop life cycle results in about 40 to 60% reduction in potential tomato fruit yield (Adigun,
2005). Some weeds increase pest problems by serving as hosts for insects and pathogens. Weeds
are most competitive if they emerge prior to or at planting until about 6 to 8 weeks after crop
emergence (University of California, 2014). Despite the high costs in insect pest, disease and weed
management measures, the problems result to low income due to low yield. Thus, farmers grope fora safe and economically productive technology to counter weed and insect pest problems in tomato
culture, and mulching is believed to be one.
Studies on mulching frequently present straw mulch, plastic mulch and live-mulch cowpea.
This is tested in pepper and shown that cowpea mulch is more effective in suppressing pest
populations of pepper but straw mulch provide a better refuge for the natural enemies (Mochiah etal., 2012). Mulching trials on plant growth, yield, and pest control in organic yellow zucchiniproduction reveal that paper, rye straw, black plastic, and rye straw plus paper greatly reduce weeds
as compared with the bare soil control and are not significantly different in their weed suppression
effect (Hulsey, 2013). Black plastic mulch results in significantly higher total yields as compared toall other treatments and the bare soil control. Black plastic also has significantly greater densities ofsquash bugs and stink bugs as compared to other treatments and the control. None has ever tried
mulching coconut leaves and fronds in tomato or other vegetables but this experiment.
OBJECTIVE
The main purpose of this study was to assess the usefulness and applicability of coconut fronds as
mulch for weed and insect pest management in tomato production. Specifically, the purpose was todetermine the influence of cocofrond mulch on weed population, pest incidence and yield oftomato.
METHODOLOGY
The experiment was conducted at the Bohol Island State University, Zamora, Bilar, Bohol with areddish soil that had 2.27% organic matter content, 3.5 ppm Phosphorus, 10 ppm K, and a pH of
4.88. The area had previously been abundantly occupied by Humidicula grass apart from Paspalum
conjugatum, Euphorbia hirta, Digitaria ciliaris, Dactyloctinium aegyptium, Ehinochloa colona andPanicum repens. A randomized complete block design was used with four treatments and four
replicates. All cultural practices in tomato production were followed, except on weed and insect
pest management after transplanting. Diamante Max variety of tomato seedlings were transplantedon December 6, 2013. Vermicompost and carbonized rice hull combination at the rate of 5 tons per
hectare was applied as basal fertilizer. The study compared coconut fronds and the commonly
recommended black plastic mulch. Fig. 1 presents the treatments.

T1

T3

T2

T4

Fig. 1 Treatments: T1- control-hand weeding, T2- woven cocofrond mulch,
T3- unwoven cocofrond mulch, T4- plastic mulch

Fig. 1 Treatments: T1- Control-Hand Weeding; T2-Woven Cocofrond Mulch; T3-Unwoven Cocofrond Mulch; T4-Plastic MulchⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Data collected were weed species, population per species at 30 and 60 days fromtransplanting; insect pest population per species taken fortnightly in ten sample plants per treatment
per block; and yield of five harvests per treatment per block computed in tons/ha. Analysis ofvariance and Tukey’s HSD Test were applied.
RESULTS AND DISCUSSION
Influence of Coconut Fronds and Plastic Mulches on Weed Infestation
Table 1 presents the 18 weed species found in the experimental plots where majority werebroadleaf weeds, no grass weeds identified, and only one sedge species the Cyperus kyllingia. All
were dominated by a broadleaf Borreria laevis.
Table 1 Mean population weeds per species per treatment
MorphologicalClassification
Broadleaf
Broadleaf
Broadleaf
Broadleaf
Broadleaf
Broadleaf
Broadleaf
Broadleaf
Broadleaf
Broadleaf
Broadleaf
Broadleaf
Broadleaf
Broadleaf
Broadleaf
Broadleaf
Broadleaf
Sedge

Scientific NameControl
0.8
16.3
16.8
9.3
0
6.8
255.0
2
1.8
3.5
1.3
0
1.5
8.5
0
1.0
0
3.3

Calpogonium mucunoides
Ageratum conyzoides
Mimosa pudica
Phyllanthus.amarus
Cassia tora
Ipomea triloba
Borreria laevis
Borreria ocymoides
Commelina diffusa
Phyllathus niruri
Desmodium triflorum
Chromolaena odorata
Cleome rutidosperma
Corchorus olitorious
Euphobia hirta
Stachytapheta jamaicensis
Bidens pilosa
Cyperus kyllingia

Mulch / Mean Population*
ParallelWoven
Cocofrond
Cocofrond
1.8
0.8
10.5
8.0
25.8
34.5
1.3
9.3
0.8
0
5.3
7.8
75.0
119.0
0
0
0.3
0.3
4.5
1.3
1.8
0.8
0
0
2.0
6.0
7.3
11.3
0
0.3
1.0
1.0
0
0.5
0.3
1.5

Plastic Mulch
0.8
20.0
9.5
2.5
1.0
1.5
31.5
0
1.5
2.5
0.5
0.3
0.3
0.5
0
0
0
0

*means from 3 replicatesMultivariate analysis showed that only the population of Borreria laevis significantly differedamong treatments. Tukey’s HSD Test in Table 2 reveals that all kinds of mulch significantly
reduced the population of B. laevis compared to hand weeding. The test also illustrates that all
mulches have similar suppressive effects on the B. laevis. This initial finding encourages further
studies to prove its potential in weed management in tomato as well as in other vegetables.
Table 2 Comparison of treatment means of B. laevis using Tukey’s HSD test
TreatmentN

T4 - PE plastic mulch
T3 - Parallel cocofrond
T2 - Woven cocofrond
T1 – Control/Hand Weeding

4
4
4
4

Subset*
1

2

31.50
75.00
119.00
255.00P-value*means in the same subset are not significantly different to each otherⒸ ISERD

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0.149

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Effects of Coconut Fronds and Plastic Mulches on Insect Pest Incidence
The population of the three insect pest species found the most damaging to the experimental tomato
crops: 12-spotted ladybird beetle, Epilachna philipinensis remota; tomato fruitworm, Helicoverpa
armigera and the green looper, Chrysodeixis chalcites differed in terms of time and the mulch used.
Figure 2 reveals that plastic mulch reduced their population for a number of weeks. This wasfollowed by cocofrond mulches while tomatoes with hand weeding had higher pest population inmost of the time.

Fig. 2 Population of 12-spotted ladybird beetle adults (above left), its larvae (above right);
greenlooper larvae (lower left), and tomato fruitworm larvae (lower right) infesting
tomato crops per time
Analysis on the population of 12-spotted ladybird beetle adults, fruitworm larvae, and green
looper larvae presented in Table 3 shows highly significant difference between time/weeks, while
the beetle larvae had significant result. This implies a similar effectiveness of the mulches on thepest though time element or crop stage had significant effect on the pest irrespective of themulching materials. However, pest population was not significantly affected by the treatments
except for 12-spotted ladybirds beetle larvae which had been significantly affected by the mulches.
Time and treatment interaction was not significantly denoting the independent influence of timeand mulches on the pest population. The same analysis illustrated that Epilachna larvae was
influenced by mulch while the adults were not affected. This suggests that there was a difference in
egg lay and survival of the eggs or of the hatching larvae in mulched plots versus the control.
Tukey’s HSD test results on the 12-spotted ladybird beetle larval population presented inTable 4 reveals that plastic mulch had a significantly lower number compared to the rests of themulches. The unwoven and the woven cocofrond mulches had intermediate populations whichwere not significantly different from either the black plastic mulch or the control plots.

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Table 3 Analysis of variance on the insect pest population infesting the tomato crops
Source of Variations
Within-Subjects
Pests

Time
F-Statistic**

Spotted ladybird beetle adults
15.085
Spotted l. beetle larvae
3.988*
Fruitworm larvae
9.181**
Green looper
17.878**
Note: Tested at 95% level of confidence

Between Subjects

Time x Treatment

P value

F-Statistic

0.000
0.043
0.000
0.000

ns

0.966
1.438ns0.304ns
1.070ns

P value

Treatment
F-Statistic

0.494
0.256
0.986
0.406

ns

1.745
4.949*
0.165ns
0.389ns

P-Value
0.211
0.018
0.918
0.763

Table 4 Comparison of means on spotted ladybird beetle larval population
using Tukey’s HSD test
Subset* 1

Subset* 2

4 – Plastic Mulch
4
0.0415
3 – Parallel/Unwoven Cocofrond
40.1545
2– Woven Cocofrond Mulch
4
0.5810
1– Control/Hand weeding
4
P-value
0.114*means in the same subset are not significant to each other at 95% level of confidence

Treatment

0.15450.58100.7605
0.068

The damage counts based on infested leaves by the 12-spotted ladybird beetles and thefruitworm bored tomato fruits are shown in Fig. 3. The figure illustrates that there was lesser
damage on the crops that were mulched with cocofronds, compared to the ones that planted withhand weeding and with plastic mulch.

Fig. 3 Number of Epilachna beetle-infested leaves (left) and the fruitworm-infested
fruits tomato (right)
Table 5 Analysis of variance on the 12-spotted ladybird beetle and fruitworm infestation on
tomato crops
Source of Variations
Within-Subject
Time
Time x Treatment
F-Statistic
P value
F-Statistic
P value
12-spotted l. beetle infestation
2.258ns
0.130
0.385ns
0.873
32.395**0.000
0.307ns
0.968*
Fruitworm infestation
Note: Tested at 95% level of confidence
PestsⒸ ISERD

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Between-Subjects
Treatment
F-Statistic
P-Value
4.540*
0.024
0.254ns
0.857

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Analysis of the Epilachna beetle infested leaves in Table 5 indicates no significant interaction
between time and treatments, but main effects between treatments differed significantly. Thismeans that the beetle-infested tomato leaves were significantly reduced with the use of mulchingmaterials. Tukey’s HSD test on infested leaves showed that plants with hand weeding hadsignificantly higher infested leaves compared to mulched plants, particularly to unwoven
cocofronds. Analysis also showed that fruitworm damage was not significantly different among
treatments indicating that mulching had no influence on the number of infested fruits. A significant
difference between times indicated that fruitworm-infested fruits irrespectively increased with crop
age applied with mulching materials.
Influence of Coconut Fronds and Plastic Mulch on Yield of Tomato
Yield of tomato with and without mulch did not differ significantly from each other as shown in
Table 6. This implies the lack of influence of the mulch on the crop’s yield. There could have beena treatment difference if the control plots had not been hand weeded.
Table 6 Yield analysis of tomato in tons/ha as influenced by cocofrond mulch
Source of Variation
Sum of Squares
Treatment
0.183
Error
0.675
Total
0.858
Note: Tested at 95% level of confidence

df
3
12
15

Mean Square
0.061
0.056

F
1.086ns

P-value
0.392

CONCLUSION
Mulching is useful in suppressing the dominant weed, B. laevis in tomato production. The three bed
mulches, woven and parallel arranged coconut fronds, and black plastic similarly suppressed the
population of B. laevis. The black plastic mulch was highly effective in reducing spotted ladybird
beetle [SLB] (Epilachna sp.) larval population, while both woven and unwoven/parallel arranged
cocofronds had slightly suppressed the pest. The mulches reduced the SLB larval damage on
tomato, although in this case the woven cocofronds was highly effective while, the nonwoven/parallel cocofrond mulch and plastic mulch were slightly effective in minimizing thedamage. Despite the effectiveness of the mulches on weeds and insect pest management, they did
not influence crop yield, implying additional tests.
ACKNOWLEDGEMENTS
Indebtedness is hereby conveyed to the Australian Center for International Agricultural Research(ACIAR) for the financial support provided, likewise the ACIAR and the Visayas State University
Research Teams for their technical assistance.
REFERENCES
Adigun, J. 2005. Critical period of weed interference in rainfed and irrigated tomatoes in Negerian Savannah.
Agricultura Tropica, 38 (2), 73.
Hulsey, J. 2013. Effects of different mulching methods on organic yellow zucchini production. University of
Florida. Library System, November 2013.
Mochiah, M.B., Baidoo, P.K. and Acheampong, G. 2012. Agriculture and biology. Journal of North America
ISSN Print: 2151-7517, ISSN Online: 2151-7525, doi:10.5251/abjna.2012.3.6.253.261 ©, ScienceHuβ.
Philippine Council for Aquatic and Agricultural Resources Research and Development (PCAARRD). 2007.
PCAARRD commodities, tomato industry status.
University of California. 2014. UC IPM Pest Management Guidelines: Tomato.UC ANR Publication 3470.
WeedsAgriculture and Natural Resources, University of California, USA.
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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Research article
erdWorking with Ethnic Group: A Case Study of Introducing
Pig Fattening to Garay Ethnicity in Ouyadav District,Ratanakiri Province
PHEM MENGHAK*
Royal University of Agriculture, Phnom Penh, Cambodia
Email: menghak44@yahoo.com

THIM SOKHARoyal University of Agriculture, Phnom Penh, Cambodia

THENG KOUCH
Royal University of Agriculture, Phnom Penh, Cambodia

SENG MOM
Royal University of Agriculture, Phnom Penh, Cambodia
Received 15 December 2014

Accepted 8 April 2015(*Corresponding Author)

Absract Ratanakiri is remotely located in northeast of Cambodia about 600 km from
Phnom Penh. Pig production of Garay ethnicity was challenged with poor feeding and highrisk of mortality. The study aimed to compare the effect of feed supplement, estimate theeconomic efficiency, and study the adoption of target group to the demonstrated experiment
pig fattening. A group discussion was launched to select 5 volunteer farmers from eachvillage who met the criteria. The chosen farmers were trained on pig fattening process.
Each of them had been subsidized two piglets; hand in hand pen construction, and feed
supplements for 4 months. Some information was informally interviewed to understand thecurrent feeding and management; and determine the suitable interventions. Farmers werethen randomly allocated into two treatments, viz. T0 (Control group – free range feeding)and T1 (Supplement group – 40% concentrates, 30% rice bran, 30% cassava chip).The
growth rate was recorded every 2 weeks for 4 months. After a 7-month period, all adopted
farmers were interviewed by using questionnaire for impact study. The results have shown
significant 3-fold improvement in daily average weight gain of improved diet groupalthough the economic efficiency of the two groups did not differ. After seven months ofinterventions on the ground, some changes were observed. For example, 80% of theselected farmers kept pigs in pens regularly and started to utilized local available feeds.
Thirty percent was willing to buy commercial feeds. All management tasks were done 50%,
40%, 10% by wives, husbands, and children, respectively. Vaccination was not totally
implemented by them. We concluded that our interventions have changed some behaviors
of focused famers and neighbors on the production in terms of management practices andfeeding for pig fattening. More feeding options need to be assessed for better economic
efficiencies.
Keywords fattening pig product on, productivity, intervention, Garay ethnicity

INTRODUCTION
Ratanakiri province is located in the northeast of Cambodia. It borders with Laos PDR to the west
and Vietnam to the east. The province is located about 600 km from Phnom Penh and the averageannual temperature is in the range of 26-31 o C. Ethnic Group was the main target of the study;
there is Garay ethnicity contributing totally 98% of population in Ka Te and Samkaninh villages ofLumchor and Soam Thom communities, respectively belonging to Ouyadav district selected asstudied area. The main jobs of villagers are cassava and rice cropping, animal husbandry (moreⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

noted as local breeds), as well as forestry such as hunter and labor work (RPDA, 2010). In
Cambodia, pig raising is one of the sources of income for farmers through selling of pigs, pork, andprocessed pork, which are good sources of protein (Sorn, 2011). 92.81% of Pig production was
conducted by smallholder in 2010 and this percentage decreased to 84.87% in 2013 due to rising of
disease outbreak and low profit when selling to the market (DAHP, 2013). In general, small scale
animal production depends on locally available feed resources such as rice bran, broken rice, sugar
cane tops, sweet potato vines, cassava roots, and kitchen waste; while commercial feeds are rarely
used due to high cost. The proportion of commercial feed used is about 20 % of pig smallholder,
while the remaining 80 % depends on mainly crop residues and farm by-products, which are often
poor quality and low nutritional value (Khieu et al., 1996). Biosecurity is defined as theimplementation of creation the barrier to prevent most contamination and infection by segregation,cleaning, and disinfectant; the practices depend on production system concerned, the local
geographic and socio-economic (FAO & OIE, 2010). However in Ratanakiri, the pigs of the ethnic
group are freely raised, challenging poor feeding, no deworming and vaccination programs;
resulting to high risk of diseases and mortality. In addition, due to land converting from forestrycovered to agro-industry land such as rubber farm, cassava, and so on; less scavenging areas areavailable. This leads farmers to hesitate to increase number of pigs, or even continue their raising.
The introduction of pig fattening by concentrating diet supplemented to local basal diet, and proper
management and bio-security (pig housing, deworming, and vaccination) by farmers would be asolution to overcome the constraints; while pig production performance and farmers’ income would
be improved. The farmtrials in this paper employ hypothesis testing and lessonlearn methods tostudy the adoption of new techniques of participating famers and neighboring ones.
OBJECTIVESThe study aimed to compare the effect of feed supplements, estimate the economic efficiency, andstudy the adoption of the target ethnic group to new techniques of the demonstrated experiment of
pig fattening.
METHODOLOGY
There are 2 steps in this study: the first is to select the focused group and set up a trial of pig
fattening, and the second is evaluation of farmer adoption.
Farmer Selection
Ka Te and Samkaninh villages were selected as the studied areas based on the ethnic resident thatis 98% of Garay group. The discussions were conducted with local authority about farmers’situation in the selected villages. Farmer meetings were set up to introduce the project purposes andactivities in each village. The selection of volunteer farmers to join the project was done during themeetings. Then, all willing farmers’ houses were visited to observe their resources. The criteria ofselecting the farmers were as follows: be ethnic group, willing to work, have available labors andhouse-area for constructing the pig pen, and grow some vegetables for the pigs. The household
heads that were women, widows, and disable people were also encouraged to participate. After all
criteria were met, the selected farmers were trained on fattening pig production, breed and breed
selection, feed and feeding, housing, and bio-security.
Experimental Design
The selected farmers were assigned into 2 treatments as shown in Table 2, with five replications(farmers), and two piglets were distributed to each farmer. The two treatments were: T0: control
group by supplementing rice bran and T1: supplement group: supplementing concentrates at 40%
with cassava chip 30%, and rice bran 30%, mixed with farmer’s basal diet.
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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Table 1 Feed supplementation
Group
Duration
Quantity for 2 piglets (kg/day)
Piglets (heads)
Crude Protein (%)

T0 (Control)
Jul-Aug
Sep-Oct
0.4
0.5
10
9.5 %

T1 (Supplement)
Jul-Aug
Sep-Oct0.8
1.0
1020.5 %

Piglet Housing and Distribution
After completed the training course, pig pens were constructed by full participation from farmers to
improve their understanding about pig pen. The method was learning by doing as they had noexperience to construct the pen before. The pen size was 2 meters in width and 3.5 meters in lengthwith concrete floor, iron sheet roof, and wooden barred to protect the piglets out. Twenty local
breed piglets of three months old were bought from nearby villages, and then they were randomly
distributed to volunteer farmers. The initial piglet-weigh in both groups was non-significant as: T0
was 6.39 ± 0.38 kg and T1 was 6.41 ± 0.36 kg.
Feed and Feeding for Pig Fattening
Concentrate feed was used as a part of supplement diet to show farmers how much feed richprotein could improve the growth performance of their pigs. The basal diet of both groups was
based on locally available feed resources such as taro stem, banana stalk, sweet potato vines,
pumpkin, papaya and vegetables. Feeds for supplement of both groups were packed for 1-time
feeding to be mixed with basal diet.
Management and Bio-security
In order to introduce the farmers, some parts of bio-security were implemented; the pens weredisinfectant by applying commercial calcium bicarbonate, cleaned by boiled water 100 0C after 1day period, and piglets were kept in individual pens with drinking nipples. All the pigs were
vaccinated against hog cholera disease, treated with an anti-parasitic drug (Ivomic given by
injection) at the first week of keeping and beyond after one month next. Pigs were fed 2-3 times per
day depending on available time of the farmers.
Table 2 Vaccination
Date
27/07/2013
27/08/2013

Piglet Age
3 months
4 months

Vacine name
Pest Porcine
Pest Porcine

Disease
Hog Cholera
Hog Cholera

Usage
Muscle injection
Muscle injection

Data Collection and Analysis
The piglets were weighed every two weeks in the morning before feeding. Feed supplementary andfeed refusals were daily recorded. All data were recorded using Microsoft Office excel 2010. The
study of farmers’ adoption was conducted by questionnaire 3 months after the experiment finished.
In every 2 weeks, growth performance deviation was analyzed by using Independent Sample T-test
Statistics of SPSS version 18. The adoption data from the questionnaire was analyzed by Microsoft
Excel to calculate the descriptive statistics and to design graphic.
Chemical Analysis
Samples of feed supplement—concentrated feed, rice bran, cassava chips, were collected from thearea of study and analyzed for Dry matter (DM) and Nitrogen (N), according to Undersander et al.
(1993) and AOAC (1990), respectively.
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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

RESULTS AND DISCUSSION
Table 3 Average daily gain of pig (Gram/day/head)
Group

No.
1

Control2

Supplement

N
10

Mean
86.25

Std. Deviation
16.36

10

277.5926.05

P. value
0.00

The supplementation group had higher daily weight gain than control group, piglets insupplementation group had ADG at 277.59 ± 26.05 gram per day (P<0.001) as shown in Table 3.
Comparing to the study of Phengsavanh et al. (2013), as providing the concentrated feed containing
CP 20 % on Growing Local Breed gave an average daily gain at 263.5 gram/day. Yin (2008)
showed that cross breed of local and exotic breed fed by normal food of famers (rice bran andkitchen waste), provides growth performance at 82.00 ± 9.36 gram/day; and another groupsupplemented commercial concentrated feed 15% of live body weight (LBW) provided up to
313.00 ± 18.00 gram/day.

Percentage (%)

100
80
60
40
20
0

Pre-Trial (%)

Post-Trial (%)

Fig. 1 Feed used as Pig’s food pre-intervention and post-intervention
Before starting this study, the Garay ethnicity has raised their pigs by letting them freely
scavenge with poor feeding. Pigs were fed irregularly depending on the convenience of owners.
After 7 months of participatory with the study, the focused farmers have been utilizing someavailable local materials to feed their pigs such as banana stalk, taro stem, cassava root, cassava
vine, spinach, pumpkin vine, pumpkin fruit, amaranth, sweet potato, and forages (Stylo 184), ricebran, kitchen waste, and other local vegetables as shown in Fig. 1.

Fig. 2 Family participation in pig productionⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

The Garay live traditionally, as men work on farm. All housework and taking care children
are done by women. Normally, women are not allowed to make any decision. During the training,
women were encouraged to work for pig fattening program and actively contact with theresearchers to increase their social rights in terms of gender equality. Figure 2 shows that most of
pig raising processes were done by women 50 %, men 40 %, and children 10 %.
90

Percentage (%)

100
80

80

90

60

60

30

40

30

30

20

0

Fig. 3 Farmer adoption to component intervention
During the study, farmers kept their pigs in pens, and regularly fed 2-3 times a day. Two autodrinking machines were broken by pig biting, whereas the rest 80 % could be used. Every morning,
farmers cleaned the pens and pigs. These tasks were handled by children when the farmers were
not available. Some farmer houses had a machine, which eased cleaning process. However, thevaccination and deworming process were complained by farmers, as it was expected to be done bya national program.
30 (%)
Rice Bran + Basal Diet (%)

Concentrated Feed + Basal Feed (%)
70 %Fig. 4 Feed used during adoption study
The commercial feed is too expensive and the market is far from the village, causing farmers
burdens to travel or buy as pig diet. As shown in Fig. 4., most of the farmers have used the ricebran mixed with vegetables, whereas there were three farmers who have bought the commercial
feed for their pigs.
Estimated Economic Efficiency
The economic efficiency between two groups was not much different. For Group T1,
supplementing by the concentrate feed was less economic than the result of using expensive
commercial concentrate feed. The commercial feed was not recommended to use as pig foodbecause feed conversion ratio (FCR) of local pig is a limitation.
CONCLUSION
The use of commercial feed supplement for pig production improved the growth performance butits expensive price caused non-economic production. On-farm experiment would help farmers tounderstand the real condition.

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Table 4 Economic efficiency of control and supplement group
T0 (Control)
Items

Unit

Piglets
Food
Medication
Housing
Drinker
Grand expense
Gross Income
Economic efficiency

heads
Kg
per cycle
per cycle
per cycle
USD
USD
(%)

Price/unit
(USD)
15.00
0.23
0.50
2.65
0.38
2.13

T1 (Supplement)

Number

Price

10
500
10
10
10

150
112.5
5
26.5
3.75
297.75341.061.15

160.5

Price/unit
(USD)
15
0.54
0.5
2.65
0.38
2.13

Number

Price

10
1000
10
10
10

150
540
5
26.5
3.75
725.25796.881.10375Knowledge that they gained could be more effective for making decision with considerationof process that was applicable for their areas. Some techniques and complicated process such as
vaccination made farmers hesitate to follow; hence, they always thought the government would
support it. Moreover, the information from this on-farm practice was rare to be done forsmallholder farmers. Otherwise, further study should focus more on on-farm experiment with
farmers, who have less understanding of how to involve their livestock production to newtechnology.
ACKNOWLEDGEMENTS
Much grateful to CIAT and IFIAD for fund support, and all professors and lecturers of Animal
Science Faculty and all staff at Center for Livestock Development Studies for critical commentand document support, senior researcher from Department of Animal Health and Production and
Ratanakiri Provincial Department of Agriculture for suggestion and physical contribution into thestudy.
REFERENCES
Association of Official Analytical Chemists (AOAC). 1990. Official methods of analysis, 15th edition (KHelrick editor) Arlington, 1230.
Department of Animal Health and Production (DAHP). 2013. National annual report of animal health andproduction.
Food and Agriculture Organization of the United Nations / World Organisation for Animal Health / World
Bank. 2010. Good practices for biosecurity in the pig sector, issues and options in developing andtransition countries. FAO Animal Production and Health Paper No. 169. Rome, FAO.
Khieu, B., Preston, T.R. and Lindberg, J.E. 1996. Juice production from the sugar palm tree (Borassus
flabellifer) in Cambodia and the performance of growing pigs fed sugar palm juice. MSc thesis, Swedish
University of Agricultural Sciences, Uppsala. Livestock Research for Rural Development, (15) 8, 1-11.
retrieved from, http://www.cipav.org.co/lrrd/lrrd15/8/kea158.htm
Phengsavanh, P. and Lindberg, J.E. 2013. Effect of dietary protein levels on growth performance and feedintake in native Moo Lath Loa pig. Animal and veterinary advances, 12, 406-411.
Ratanakiri Provical Department of Agriculture (RPDA). 2010. Agro-ecosystems analysis of Ouyadav District,Ratanakiri Province.
Sorn, S. 2011. Cambodia swine industry profile. National veterinary research institute (NaVRI), Departmentof animal health and production, Phnom Penh, Cambodia.
Undersander, D., Mertens, D.R. and Thiex, N. 1993. Forage analysis procedures. National Forage
Testing Association, Omaha, 154.
Yin, R. 2008. Using of concentrate feed (GF: 74A) on homemade feed for growing fattening pig. Bsc. thesis,
Faculty of Animal Science and Veterinary Medicine, Royal University of Agriculture, Cambodia.

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Research article
erd

Problems in Rural Areas of Bosnia, Montenegro and Serbia:
A Comparative Analysis
SINISA BERJAN*
University of East Sarajevo, East Sarajevo, Bosnia and Herzegovina
Email: sinisaberjan@yahoo.com

HAMID EL BILALI
Mediterranean Agronomic Institute of Bari (CIHEAM-IAMB), Valenzano, Bari, Italy

ALEKSANDRA DESPOTOVIC
University of Podgorica, Podgorica, Montenegro

SNEZANA JANKOVIC
Institute for Science Application in Agriculture, Belgrade, Serbia

ADRIANA RADOSAVAC
Faculty of Agriculture, University of Novi Sad, Novi Sad, Serbia

NOUREDDIN DRIOUECH
Mediterranean Agronomic Institute of Bari (CIHEAM-IAMB), Valenzano, Bari, Italy
Received 13 February 2015

Accepted 30 April 2015(*Corresponding Author)

Abstract: Bosnia, Montenegro, and Serbia (BMS) are in a phase of consolidation, which
implies rising of economic growth, agricultural productivity, and fostering ruraldevelopment. Therefore, it is crucial to have a clear idea about problems faced by rural
population in order to design effective rural development policies. The paper aims at
highlighting the main problems in rural areas of BMS with a particular focus on those
hampering good governance and increased diversification of their rural economies. For
each country, significance of the problems was identified; and a critical analysis was
performed to highlight causes, implications in terms of rural governance and policy, andpotential solutions. Problems were identified in the framework of surveys dealing with
agricultural and rural development governance that involved representatives of public, civilsociety, and international organizations: 120 in Bosnia (winter 2011), 50 in Montenegro(winter 2012), and 120 in Serbia (summer 2013). Economic problems include difficultaccess to financial resources, low level of investments, rural economy diversification,
limited employment opportunities, small and uncompetitive farms, and rural enterprises.
Remoteness and isolation, bad local natural resources management, and increased
pollutions were the main environmental and geographic problems mentioned by theinterviewees. Socio-cultural and demographic problems encompass rural poverty, low
quality of life, gender inequity, low human capital of the rural population, unpopularity ofagriculture and alarming negative demographic trends. Focus of local development
strategies mainly on agriculture and lack of local spatial plans are some of the political andregulatory problems. There are also problems related to the poor physical infrastructure andservices, and lack of processing facilities and local markets. For smooth accession to theEuropean Union (EU), BMS should address these problems urgently in a systemic andholistic way to unlock the growth potential of rural areas, taking stock of the current EU’s
rural development policy.
Keywords rural areas, agriculture, problems, Bosnia, Montenegro, SerbiaⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

INTRODUCTION
The three countries of the Western Balkan (WB), namely Bosnia, Montenegro and Serbia (BMS),
are in a phase of consolidation, which implies rising of economic growth, agricultural productivity, andfostering rural development. Therefore, it is crucial to have a clear idea about problems faced byrural population in order to design effective rural development policies.
Around 61% of the Bosnian population can be classified as rural (UNDP, 2013). The share ofMontenegrin population living in the countryside accounts for 38% of the total population(Arcotrass-consortium, 2006). Approximately 43% of the Serbian population lives in rural areas(RDNS, 2010). The rural areas of BMS lag behind in terms of socio-economic development andstill face many problems such as low quality of life and limited employment opportunities. In suchcontext, agriculture plays an important socio-economic role for employment and poverty reduction.
Moreover, since a large share of population lives in rural areas, there can be no balanced
development of BMS without devoting more attention to rural population and combating rural
poverty. For the development of agriculture and rural areas, evidence from other countries such as
those of the EU, show that agriculture is not sufficient to ensure the sustainable development ofrural areas. It is the core reason why rural economy should be diversified (OECD, 2006).
Participation of local actors in rural development processes is particularly important; especiallythere is a transition to adopt people-centred approaches and policies. It is clear nowadays that
achieving sustainable and inclusive development of rural areas means long-term effective andefficient policy measures. It is important that these policy measures and instruments have real
impact on rural population livelihood and quality of life. Hereinafter, they should create an enable
environment for investments, improve household assets, and service delivery in rural areas.
The paper aims at highlighting the main problems in rural areas of BMS with a particularfocus on those hampering good governance and increased diversification of the rural economy.
METHODOLOGY
The applied methodology comprised both primary and secondary sources of information. Many
literature sources were consulted and primary data were collected by a questionnaire survey thatwas sent via email to different key stakeholders in BMS.
BMS share similar traditional, cultural, and historical background as ex-republics of theformer Yugoslavia. The spoken language is the same, which made easier communication for online
questionnaire dissemination and the overall survey. Problems were identified in the framework ofsurveys dealing with agricultural and rural development (ARD) governance that involved
representatives of public, civil society, and international organizations; 120 in Bosnia (winter 2011),
50 in Montenegro (winter 2012) and 120 in Serbia (summer 2013). Unit of data collection was
individuals, one representative per eligible organisation, while unit of data analysis wasorganizations. Only institutions that are involved in ARD were considered in the surveys. The
selection of eligible institutions was mainly based on internet search and literature review as well
as authors’ personal and professional networks. Questions were open ended to say that no list of
problems was previously prepared and respondents were left at their own to identify problems. The
questionnaire was pre-tested in all target countries with representatives of public, civil society, andprivate sector. Feedback gained was useful for making improvements, especially in terms of usedterminology and question wordings. For each country, the significance of each identified problem
was identified and a critical analysis was performed to highlight causes, implications in terms ofrural governance and policy, and potential solutions.
RESULTS AND DISCUSSION
Problems in rural areas mentioned by the respondents can be divided in several categories:
economic problems; environmental and geographic problems; institutional, political and regulatoryⒸ ISERD36

LEM

mic problemssabour market
opmentIJERD – International Journal of Environmental and Rural Development (2015) 6-2

problems; social, demographic and cultural problems; and infrastructure- and service-related
problems (Table 1).
Table 1 Major problems in rural areas of Bosnia, Montenegro and Serbia
INDENTIFIED PROBLEM
Economic problems
Lack of financial resources and of investments
Lack of labour force and undeveloped rural labour market
Low level of SMEs and new businesses development
Limited use of machinery
Extensive agriculture
Difficult access to credit due to lack of collateral
Limited employment opportunities
Low prices of agricultural products
Difficult procurement of agricultural inputs and high costs
Low productivity and low remuneration for workers
Undeveloped rural tourism
No added value to agricultural products
Low level of rural economy diversification and high dependence on the
agricultural sector
Obsolete farm machinery and equipment
Small and uncompetitive farms
Environmental and geographic problems
Long distance to urban areas
Bad management of local resources and increased pollution due touncontrolled use of chemicals
Insufficient development of organic production
Unused natural resources
Mined agricultural land from the war
Limited arable landInstitutional, political and regulatory problems
Non-stimulating tax policy and existence of “grey economy”
Local strategies mainly focus on agriculture activities
Small and irregular economic incentives
Lack of spatial plans at the local level

BO
A
C
B

nd high dependence on the

A
C
C

B

eral

nd high costs
workers

COUNTRY
MO
SE

A
B
C
C
C
C

A
C
B
B

C
A

A
C

C
C
C

C

C

B
A

B

B
B

C

A

d geographic problems

ased pollution due toConl and regulatory problems
grey economy”
ctivities

C
C

C
C
C

C
A
C
B

C
B
C
B

A
C
B

INDENTIFIED PROBLEM
Social, demographic and cultural problems
Rural poverty
Low quality of life
Lack of qualified human resources
Lack of knowledge and information
Low educational level and use of ICT
Lack of vision, initiatives and willingness
Lack of training activities for farmers
Use of traditional methods and technologies
Poor social and cultural life
Disorganization of farmers
Gender inequity
Lack of cooperation between producers and scientists
Disappearance of common interest and emerging individualistic
mentality of rural population
Unpopularity of agriculture
Obsolete educational and cultural facilities
Territorial dispersion of rural settlements and low density
Prejudices of youngsters about staying in the countryside
Negative demographic trends (low birth rate, depopulation,
migration, ageing, single men, etc.)
Infrastructure- and service-related problems
Difficult access to rural areas (i.e. bad roads)
Poor physical infrastructure and communal services(e.g. sewage, garbage, ambulance, transport, etc.)
Lack of processing capacities, equipment and resources
Lack of tourist accommodation facilities and services
Instability of electrical power supply
Lack of collection centres for rural products
Lack of local markets

BO
A
C
B

COUNTRY
MO
SE
A
C
C

B
A
B
C
C
C
C

A
C
B
B

C
A

A
C

C
C
C

C

C

B
A

B

C

A

B
B

C
C
C

C
C
C

C
A
C
B

C
B
C
B

BO

COUNTRY
MO
SE

A
A
A
A
A

A
A
A
A
A

A
C
B

INDENTIFIED PROB

Social, demograph
Rural poverty
Low quality of life
Lack of qualified human resources
Lack of knowledge and information
Low educational level and use of ICT
Lack of vision, initiatives and willingness
Lack of training activities for farmers
Use of traditional methods and technologies
Poor social and cultural life
Disorganization of farmers
Gender inequity
Lack of cooperation between producers andDisappearance of common interest and eme
mentality of rural population
Unpopularity of agriculture
Obsolete educational and cultural facilities
Territorial dispersion of rural settlements an
Prejudices of youngsters about staying in th
Negative demographic trends (low birth ratemigration, ageing, single men, etc.)
Infrastructure- andDifficult access to rural areas (i.e. bad roads
Poor physical infrastructure and communal(e.g. sewage, garbage, ambulance, transport
Lack of processing capacities, equipment an
Lack of tourist accommodation facilities an
Instability of electrical power supply
Lack of collection centres for rural products
Lack of local markets

A
A
A
A
A
C

C
B
C
B
C
C

C
C

B
C
C
C
C

A
C
C
A

B
C
B

B

A

A

A

B
A
B
A
B
A

B

C
A
A
C
C

A
B
A
C
C

Source Authors’ elaboration based on survey results. Legend: BO=Bosnia; MO=Montenegro; SE=Serbia;
A=Significant (problems mentioned by >50% of respondents); B=Average (25-50%); C=Poor (>25%).

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Economic Problems
Lack of financial resources is one of the main indicators used for assessing poverty. This problem
is more expressed in those rural areas in which employment opportunities are limited and where
many people suffered due to loss of jobs. This is particularly true in the Bosnian case where many
companies were totally devastated or partially during the civil war. However, overall unstable
political and economic situation in whole WB also negatively affected the quality of life in the rural
areas of Montenegro and Serbia. In addition, the lack of financial resources is connected to difficultaccess to credits due to lack of collaterals. Therefore, rural population hardly has access to credits
and does not have savings that allow to live with dignity and to make investments for future.
Financing agriculture and agribusiness has always been difficult due to the risky nature of thebusiness. Traditional forms of collateral are often not available, and not acceptable when they areavailable. Thus, limiting access needs funding for the sector (Winn et al., 2009).
Rural economy diversification is still a challenge in many rural areas of BMS, both in terms ofoff-farm and non-farm income-generating activities. Despite its declining gross value added,
agriculture continues to have an important influence on the rural economies of these countries.
Farm activities diversification in BMS is hampered by the lack of financial resources, willingness,initiatives, and knowledge and skills of rural households to start new endeavours. Diversification
endeavours can allow, among others, to add value to products through some on-farm processing
and packaging activities, as well as to make products widely recognized by developing productswith geographic indications and regional quality labels. Rural economy is still highly dependent on
agricultural sector, not only because of reluctance and resistance of rural households to start new
activities in the non-farm sector but also the focus of national rural development strategies andlocal development plans on agriculture.
As for small fragmented uncompetitive farms, there is lack of farmers’ organization, which is
coupled with the dispersed farm settlements, hinders the participation of farmers in ARD. Thishinders also the supply of extension services, farm credit, and other vital inputs to farmers andinfrastructure. All these factors negatively impact competitiveness of single farms but also theoverall agricultural sector of whole countries.
Environmental and Geographic Problems
Long distance to urban areas is often mentioned especially in Montenegro. This is related touneven regional development and lack of urban nuclei that aggregate economic activities near torural areas. This problem is further aggravated by poor road infrastructure, which makes mobility
more difficult. Another problem is bad management of local resources and increased pollution due
to uncontrolled use of chemicals. The excessive exploitation of forests and the irrational use of landcaused a change in land use structure (Nyssen et al., 2014), and the quality of vegetation cover. In
these cases, it is necessary to adopt conservation agriculture techniques and practices. Bosnian
agriculture is rather traditional and the use of chemicals is low (Stanojcic-Eminagic, 2010).
Fertilizers and chemicals application should be under control especially in Serbia (cf. Vojvodina).
Although many scholars and practitioners highlight the potential of organic agriculture as asustainable development opportunity for the developing and transition countries, it is still at theearly developmental stage in BMS. In fact, less than 0.01% of the products consumed in Serbia isorganic (GAIN, 2009), while in Bosnia organic area represents less than 0.1% of the total
agricultural area (Driouech et al., 2013). The main obstacles for organic production development in
BMS region are the lack of adequate government support (Vittuari, 2011), the undeveloped market,
the small range of organic products, and the underdeveloped processing infrastructure.
Unused natural resources and mined agricultural land is mainly a legacy of the civil war in
Bosnia that compelled many people to migrate from rural areas. Limited arable land in Montenegro
is predominantly due to geomorphology as quite a large part of the country is mountainous andkarst.

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Institutional, Political and Regulatory Problems
The main problem is lack of a stable ARD policy. ARD policy-making in the WB region in generaland in BMS in particular has often been dictated by ad-hoc considerations. Agricultural policy is
still mostly implemented based on annual programs of budget allocation, which are not stable interms of funds, support measures, and eligibility criteria. Rural development policy is generally
subordinate to production support. Funds aimed at supporting rural development are much lower(Volk, 2010). One characteristic specific to Bosnia is state administration complexity, which
complicates the implementation of its agricultural policy. Montenegro has already undergone majorchanges in the process of reforming agricultural policy but many challenges remain (Marković andMarković, 2010). In Serbia, the implementation of agricultural policy has been permanently
changing. Programs and regulations were changed and/or abolished several times during the year.
The agricultural policy in Serbia is only partly designed on a strategic basis. In recent years, it has
been characterized by the increasing estrangement from the EU model of support. Frequentchanges in administrative structures bring radical changes in the support system (Bogdanov andBozić, 2010).
Social, Demographic and Cultural Problems
Rural poverty is a serious problem faced in many rural areas in BMS. Poverty is a complicatedissue that is influenced by endowments and capital of rural households; and also by general social
environment, especially in terms of presence or absence of social programs and safety nets.
Gender inequity is still an issue in the rural areas in BMS. This should be broadly understood
not only in terms of equity between men and women but also in terms of different socio-economicand ethnic groups. Female rural population has very limited participation in the decision-making
processes (FAO-Bosnia, 2012). The truth is also regarding their share in the most important
positions within ministries and other public institutions. Rural youth are also among the mostdisadvantage groups. They sometimes have limited access to educational programmes. Very often,
rural young women are not given the same opportunities comparing with young men. Youngpeople are not enough involved in rural policy cycle. Unfavourable environment “push” youngsters
to migrate and rural areas remain without human capital and cannot achieve development. Youth’s
knowledge and skills are of vital importance for the implementation of sustainable ARD
programmes (FAO, 1991).
Prejudices of youngsters about staying in the countryside and unpopularity of agriculture are
related to their mind-sets. The education that they receive in rural areas is very often urban oriented
and makes them believe that their future perspectives will be better in the urban areas. Living incities is perceived as prestigious and fashionable especially in rural mentality; and it can happen
that rural people, especially the young, prefer to move even when they find less paid jobs incomparison with the ones they can get in rural areas. Bad services quality influences negative
demographic trends in rural areas because it fosters out-migration. In addition, poor services areamong the consequences for intensified urban drift.
As for the use of traditional technologies, despite effort made for modernizing the agricultural
sector in the three countries, agriculture is still mainly traditional except in some fertile areas such
as Vojvodina (Serbia) and Semberija (Bosnia). In fact, the use of traditional methods andtechniques calls into question about the efficiency of agricultural extension services. Most of farmmanagers are old and not open to modern technologies. Difficult access to plots makes
mechanization difficult. Agricultural production is predominantly in the hands of a multitude ofsmall-scale and unorganized farmers. State level interventions are needed to address the issue ofland fragmentation through land consolidation.

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Infrastructure and Service Problems
Dispersion of rural settlements is a big problem as it influences the availability and quality of arange of services. Adequate access of all rural people to services and structures (including
infrastructure) necessary to engage in diversification endeavours is far from optimal. It has to belinked to costs related to service provision in rural areas especially in times of financial andeconomic crisis. Low population density in rural areas exponentially increases the cost of services
delivery per rural citizen. Even when some services exist in small rural communities, they are very
often of lower quality with respect to urban centres. However, the quality of rural services and theperformance of service delivery structures are a problem in most of rural areas in BMS, especiallyin remote rural areas.
What is alarming is the general observation that the situation is getting worse regarding
human capital in the rural areas of BMS because of the out-migration of its well-educated youth.
This undermines one of the most important endogenous assets and resources that can speed up thediversification journey. In fact, it is well-known that non-farm activities require a range of new
managerial and soft skills. This highlights the importance of the role of extension and advisory
services as well as of other institutions and international development agencies dealing withcapacity building, business skills development, and human capital strengthening in rural areas.
These actors should work together and coordinate their activities in order to address this challenge.
CONCLUSION
It is essential to analyse the problems in the rural areas as these not only influence the impact ofpolicies but also the different phases of the policy cycle. Appropriate diagnosis of problems is
crucial for designing effective ARD strategies and policies. One of the common problems faced inrural areas of BMS is related to low human capital. This has implications in terms of policy
implementation as well as policy monitoring and evaluation. For implementation phase, it isnecessary to have at disposal competent and endogenous human capital with high education level.
Furthermore, skills and education level influences quality of data that are collected on the field
which directly impacts evaluation. Sustainable development of rural areas cannot be based only on
agriculture, as rural economies should also be diversified. In general, rural regions face many
problems that reduce the critical mass needed for effective public services, infrastructure, andbusiness development. Rural enterprises face many disadvantages compared to urban-based
counterparts due to small size of local markets, sparse distribution of potential customers in rural
areas, and more difficult access to credits. Better coordination and governance of ARD can help
solving most of the identified problems.
REFERENCES
Arcotrass-consortium 2006. Study on the state of agriculture in five applicant countries: Montenegro Country
Report. Study undertaken by Arcotrass GmbH (Germany), in association with Vakakis International SA(Greece), EuroCare GmbH (Germany) and AKI (Hungary).
Bogdanov, N. and Bozić, D. 2010. Review of agriculture and agricultural policy in Serbia. In, Volk T. (ed.).
“Agriculture in the Western Balkan Countries”. Leibniz Institute of Agricultural Development in Central
and Eastern Europe (IAMO), Halle.
Driouech, N., Milic, V., El Bilali, H., Despotovic, A., Simic, J., Berjan, S. and Kulina, M. 2013.
Development of organic animal and crop production in Bosnia. International Journal of Environmental
and Rural Development, 4 (1), 196-201.
FAO 1991. Rural youth situation, needs and prospects, An overview with special emphasis on Africa. Foodand Agriculture Organization of the United Nations (FAO), Rome.
FAO-ROECA. 2012. Analysis of economic diversification in Bosnia and Herzegovina. Food and Agriculture
Organization (FAO), Regional Office for Europe and Central Asia (ROECA), Budapest.
GAIN. 2009. Organic agriculture in Serbia. GAIN (Global Agriculture and Information Network) report
number RB9002. United States Department of Agriculture (USDA), Washington D.C.
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Marković, B. and Marković, M. 2010. Review of agriculture and agricultural policy in Montenegro. In, Volk
T. (ed.). “Agriculture in the Western Balkan Countries”. IAMO, Halle.
Nyssen, J., van den Branden, J., Spalevic, V., Frankl, A., van de Velde, L., Curovic, M. and Billi, P. 2014.
Twentieth century land resilience in Montenegro and consequent hydrological response. Land
Degradation & Development, 5 (4), 336-349.
OECD. 2006. The New Rural Paradigm - Policies and Governance. OECD, Paris.
RDNS. 2010. Action Plan 2011-2015. Rural Development Network of Serbia (RDNS), Belgrade.
Stanojcic-Eminagic, S. 2010. Food and agricultural import regulations and standards. Country Report:
Bosnia and Herzegovina. United States Department of Agriculture (USDA), Washington D.C.
UNDP. 2013. National human development report. Rural development in Bosnia and Herzegovina: Myth andreality. United Nations Development Programme (UNDP), Sarajevo.
Vittuari, M. 2011. Organic balkans - Stakeholders, policies, and institutions: a regional perspective.
Osservatorio Balcani e Caucaso, Trento.
Volk, T. 2010. Agriculture in the Western Balkan Countries. IAMO, Halle.
Winn, M., Miller, C. and Gegenbauer, I. 2009. The use of structured finance instruments in agriculture in
Eastern Europe and Central Asia. FAO, Rome.

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Research article
erd

Reuse of Wastewater from Cassava Industry for Napier Grass
Production
CHULEEMAS BOONTHAI IWAI*
Integrated Water Resource Management Research and Development Center in Northeast
Thailand,Khon Kaen University, Khon Kaen, Thailand
E-mail: chuleemas1@gmail.com; chulee_b@kku.ac.th

MONGKON TA-OUN
Faculty of Agriculture, Khon Kean University, Khon Kean, Thailand

BARRY NOLLER
The University of Queensland, Centre for Mined Land Rehabilitation (CMLR), Sustainable Minerals
Institute, Brisbane, Australia
Received 23 February 2015

Accepted 15 May 2015(*Corresponding Author)

Abstract Cassava industry plays an important socio-economic role in Thailand economy. The
growth of the cassava processing industry has resulted in extensive water pollution, as it
generates large amounts of wastewater with extremely high concentrations of organic pollutantsfrom washing and extraction. The need for wastewater management from cassava processing
was apparent and fit with green technology for reuse of wastewater for agriculture. Napier grass(Pennisetum purpueum), a perennial species, has become a priority source of biomass foralternative energy production in Thailand, as the National Energy Policy Council has raised thetarget of power production from Napier Grass to 3,000 MW under the 10-year alternative
energy development plan (2012-2021) for Thailand. This study aimed to investigate thefeasibility of using Napier Grass cultivation from cassava industry wastewater. Wastewater
quality (effluent and influent) from cassava industry and its impact on soil chemical properties
were studied at a site in Kalasin province, northeast Thailand to observe the effects of different
concentrations (0%, 25, 50%, 75% dna 100%) on germination test and Napier Grass biomass
production. The wastewater characteristics were: pH of 7.2, EC 4 dSm-1, BOD 119 mgL-1, COD
1070 mgL-1, TS 3230 mg L-1, TKN 207 mg L-1, TP 226 mgL-1 and water soluble K 1490 mgL-1.
The soil exposed to wastewater gave higher EC, more organic matter accumulation, higher total
N, and available P when compared to soil without being exposed to cassava wastewater. The
results showed that the wastewater concentrations significantly increased the Napier grassbiomass. Therefore, wastewater from cassava industry can be used in Napier grass production
as an example of application of green technology.
Keywords cassava production, wastewater quality, soil property, Napier grass biomass
production

INTRODUCTION
Reuse wastewater in agriculture is gaining wider acceptance worldwide. It represents an agronomic
option that is increasingly being investigated and taken up in regions with water scarcity, growing
urban populations, and rising demand for irrigation water (Gatta et al., 2014; Meli et al., 2002; FAO,
2011). Many irrigated areas around the world are experiencing water shortages due to several factors,
including climate change, and surface and groundwater pollution. Water scarcity poses serious
economic, social, and even political concerns in all of its aspects. Under these circumstances, reuse ofⒸISERD42

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

wastewater can help to mitigate the damaging effects of local water deficits (Gatta et al., 2014; FAO,
2010). Treated wastewater not only offers an alternative irrigation source, but also the opportunity torecycle plant nutrients (Chen et al., 2008). Its application might ensure the transfer of fertilizing
elements, such as nitrogen (N), phosphorous (P), potassium (K+), organic matter, and nutrients, into
agricultural soil (Gatta et al., 2014). The cassava processing industry is considered to be one of thelargest food processing industries in Thailand. However, the growth of the cassava industry has
resulted in serious environmental pollution as it generates large amount of solid waste and wastewaterwith high organic content (Chavalparit and Ongwandee, 2008).
Together with the rice and sugarcane industries, the tapioca starch-processing industry has played
an important role in Thailand’s agricultural economy. Known as the world’s largest producer andexporter of tapioca starch, Thailand produced over seven million tons of starch in 2004. Approximate
annual revenue from tapioca starch export was 38,805 million baht or 1,060 million dollars (DOA,
2005). Tapioca is produced from treated and dried cassava (manioc) root and used in the food, paper,and toothpaste industries. Only 20% of the cassava root harvested in Thailand is delivered to starchprocessing plants while the rest is used in the production of pellets and chips. Currently, Thailand has
92 tapioca processing plants with a total production capacity of native and modified starch at about
16,910 and 4350 ton/day, respectively (DOA, 2005). Normally, these tapioca-processing plants operate
24 hours per day from September to May each year.
The production of native starch from cassava root involves seven major stages. These are root
washing, chopping and grinding, fibrous residue separation, dewatering and protein separation,
dehydration, drying, and packaging. The production facilities experience a number of environmental
problems such as the consumption of large volumes of water and energy, and the generation of highorganic-loaded wastewater and solid waste. The starch extraction process requires a vast volume ofwater, which in turn produces large amount of wastewater. According to the study of Tanticharoen andBhumiratanatries (1995), the production of one ton of starch from cassava generates an average of 20
m3 of wastewater. Hien et al. (1999) reported the characteristics of wastewater from Vietnamese
tapioca starch plants with values of 11,000-13,500 mg CODL-1, 4200-7600 mg SSL-1, and pH of 4.55.0. The approximate generation of wastewater and solid waste (fibrous residue and peel) from one tonof starch was 12 m3 and 3 kg, respectively (Hien et al., 1999).
Thus appropriate wastewater management from cassava starch industry is needed. Reuse of such
wastewater and its nutrients for agriculture fits with green technology. An appropriate class to consider
for nutrient uptake is grass with high biomass. Pennisetum purpureum (Napier grass) is also known aselephant grass or Ugandan grass and is a species of perennial tropical grass native to the African
grasslands and is cultivated extensively. Napier grass (P. purpueum) is a perennial plant that is also apriority source of biomass for alternative energy production in Thailand. The National Energy Policy
Council, in its 10-year alternative energy development plan (2012-2021), has set a target to produce
3,000 MW of electricity from Napier grass. Napier grass has low water and nutrient requirements,
therefore it can make use of uncultivated lands. Historically, this species has been used primarily for
grazing. Recently, however, it has been incorporated into a pest management strategy. In addition tothis role, Napier grass improves soil fertilityand protect arid land from soil erosion. They are alsoutilized for firebreaks, windbreaks, in paper pulp production and most recently to produce bio-oil,biogas and charcoal.
The perennial Pennisetum purpureum Schumach (Napier or elephant grass) readily crosses withthe annual Pennisetum americanum (L.) Leeke (pearl millet) and the resultant interspecific hybrids are
more vigorous than the parent species. Hence, several hybrid Napier grass cultivars (P. purpureum and
P. americanum) have been developed (Premaratne and Premalal, 2006). Because of the high biomass
production and very high forage quality for livestock, growth of these hybrids is widely promoted in
subtropical and tropical countries including Thailand (Tudsri et al., 2002; Premaratne and Premalal,
2006). Recently, a very productive cultivar (Pakchong1) of this hybrid grass has been developed andmarketed by Thailand’s Department of Livestock Development. The Pakchong1 cultivar is claimed toⒸISERD43

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

have several advantages over other Napier grass cultivars, as it grows taller, has a higher content of
crude protein, has an annual yield exceeding 500 ty-1, and can be harvested 5-6 times per year
(Jampeethong et al., 2014).
The nutrients wastewater from the cassava industry has the potential to contribute to crop
production, including that of Napier grass. Nevertheless, there is a need for periodic monitoring, toavoid any imbalance in the nutrient supplies, which might cause an imbalance; such wastewater canalso be a source of pathogenic organisms, enteric bacteria and viruses and potentially hazardous
chemical substances such as salts, heavy metals, and surfactants. Hence, there is the need for further
studies to investigate the feasibility of using wastewater from cassava industry for Napier grass
production.
OBJECTIVES
The objectives of the study were: (i) to evaluate the effects of nutrients in the wastewater from cassava
industry on qualitative and quantitative aspects of Napier grass production; and (ii) to assess the impactof the wastewaters on the soil properties.
METHODOLOGY
Water and Soil SamplingThree samples of the wastewater from influent and effluent from biogas system at cassava industry
were collected in sterile 1000-mL glass bottles, and transported to the laboratory in refrigerated bags.
The samples collected were kept in a refrigerator at +4◦C, and examined within 24 hours of theircollection. Soil samples were collected in triplicate from each of 5 treatments before and after. All of
the soil samples were taken from a 15-cm layer in each plot, from under the drippers, and they were
air-dried, crushed, and passed through a 2 mm sieve before the chemical analysis.
Water Quality Analysis
The water samples were analyzed in triplicate, according to the international standard methods(APHA-AWWA-EF, 2005). The analysis included the physico-chemical parameters of pH, electricalconductivity (ECw; dSm−1), total solids (TS; mgL−1), biological oxygen demand over 5 days (BOD5;
mgL−1), chemical oxygen demand (COD; mgL−1), Total Kjeldahl Nitrogen (TKN), Total Phosphorus(TP; mg L−1) and potassium (K+; mgL−1).
Soil Chemical Analysis
The soil electrical conductivity and pH were measured ion 1:2 (w/v) and 1:2.5 (w/v) aqueous soil
extracts, respectively. The pH and EC were measured using a digital pH meter in 1/2.5 (w/v) deionizedwater. Total N (total nitrogen) was measured by the micro Kjeldahl method (Jackson, 1973; Bremnerand Mlvaney, 1982). Exchangeable phosphorous (Exch. P) was determined by using the Bray II
extraction method (Schroth et al., 2003) and Exchangeable Potassium (Exch. K) was determined by 1
N Ammonium acetate and Flame photometry method.

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Plant Growth Test
An experiment was carried out to investigate the effects of wastewater from cassava industry on
germination and plant growth under greenhouse conditions at Khon Kaen University, Thailand, at(latitude of 16° 28' N and longitude of 102° 48' E) during the rainy season of 2014.
Napier grass plants were used in this experiment. The experiment was laid out in a completely
randomized design (CRD) with three replications for each crop. Five-wastewater concentration
treatments were used (T1: tap water only, T2: 25% wastewater concentration, T3: 50% wastewater
concentration, T4: 75% wastewater concentration, and T5: 100% wastewater concentration) were used.
For five kilograms of 2 mm sieved air-dried of each soil sample were placed in each black plastic potsof 30 cm height and 25 cm diameter for each treatment. Wastewater was applied before planting inevery three days until termination. Bud per stem, height, fresh weight, dry weight, yield of stem androot were recorded.
Statistical Analysis
The data obtained from different experiments were analyzed by using the one-way analysis of variance(ANOVA) function of Statistica 8 software (Version 8, USA) to test for variations (p<0.05) that weredeemed significant between treatment groups and controls.
RESULTS AND DISCUSSION
The wastewater released from cassava industry characteristics were pH of 3.9, 7.2, EC of 1.5, 4.0
mS/cm, BOD of 633, 119 mg/l, COD of 4267, 1067 mg/l, TS of 4853, 3227 mg/l, TKN of 28, 207 mg/l,
TP of 120, 226 mg/l and water soluble K of 1833, 4900 mg/l, respectively (Table 1). The result
suggests that nutrients were high in wastewater. Therefore, it could be use for grass nutrient uptake.
Table 2 shows the effects of wastewater from cassava industry on soil properties. In the soil
exposed to wastewater, the pH of the soil increased compared to the soil without exposure towastewater. Similarly, the application of wastewater resulted in higher EC, N, P, K than the soil
without exposed to wastewater. The exposed soil contained more organic matter accumulation andhigher exchangeable K than the soil without exposure to wastewater. The noticeable increase of
exchangeable K in the soil exposed to wastewater might be explained by the presence of high levels oforganic matter in it. The soil exposed to wastewater had the higher total N content, whereas the soil
without being exposed to wastewater had low value. The high total N content in soil by exposing towastewater might be due to the fact that wastewater might enhance salt uptake and immobilization of
N. The application of wastewater resulted in higher available P than the soil without exposed towastewater. It might be due to the fact that the wastewater resulted in increasing available P in thesurface layer. The soil exposed to wastewater gave higher exchangeable K + when compared to the soil
without being exposed to wastewater. This might be the initial high content of these elements in thewastewater. Therefore, the results of this study show that soil chemical properties after being treatedwastewater from cassava were better than the ones without application of wastewater.
Plant Growth Experiment
The biomass yields of the Napier grass plants grown on the amended soils have been determined using
their height and weight data for plant stem and root biomass. The biomass of the Napier grass plants
increased in the treatment using wastewater for all the samples. The highest yields were recorded for
wastewater at 25% concentration (Tables 3 and 4).

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Table 1 The wastewater from cassava industry characteristics
Wastewater
Parameter (unit)pH
EC (dSm-1)
BOD (mgL-1)
COD (mg L-1)
TS (mg L-1)
Total N (mg L-1)
Total P (mg L-1)
Total K (mg L-1)

Influent
3.9
1.5
633
4270
4850
28
120
1830

Effluent

Water quality standard for effluent discharge(MOST, 1996)

7.2
4.0
119
1070
3230
210
226
4900

5.5-9.060400
100-200-

Table 2 Soil quality after apply wastewater from cassava industrypH

EC (dSm-1)

ytil uqdlioS
TN (%)

Exchangeable
P (ppm)Exchangeable
K (ppm)Before6.12b0.038c0.008c
34b
44c
rotf
6.01c
0.091a0.021b48a64b)inrlqtno)
6.44a
0.065b
0.028a43a
92a
rotf)trrlqtno)
F-test
**
**
**
*
**
CV (%)
0.45
3.12
8.04
5.18
2.79
Note: Mean (n=3) in the same column followed by the same lower case letters are not significantly different at p≤0.05

Table 3 The effects of wastewater from cassava industry (influent) on Napier grass production
Treatment
Buds/ stem
HeightStem fresh
Stem dry
Root fresh
Root drywastewater(cm)
biomass(g)biomass
biomass
biomass
concentration
(g)
(g)
(g)
0 %(Control)
2.67
64.33
19.86b
2.35 b
2.71c
0.31b
ab
ab
b
25%
3.67
72.68
43.30
3.67
7.09
0.50ab
ab
ab
ab
50%
4.33
77.00
50.87
4.09
8.02
0.72ab
75%
4.33
76.33
43.70ab2.22 b7.00b0.28 b
a
a
a
100%
3.33
78.667
71.67
4.75
11.58
0.76 aF-test
ns
ns
**
**
*
**
C.V. (%)
26.35
13.02
26.87
21.40
30.72
22.23
Note: Mean (n=3) in the same column followed by the same lower case letters are not significantly different at p≤0.05

Table 4 The effects of wastewater from cassava industry (effluent) on Napier grass production
Stem dry
Root dryTreatment
No.
HeightStem fresh
Root fresh
biomass
biomass
wastewater
Bud/
(cm)
biomass
biomass(g)(g)
concentration
stem
(g)
(g)
0 %(Control)
2.676
4.33
19.86
2.35
2.71
0.31
25%
3.67
76.33
35.26
2.87
5.47
0.38
50%
3.00
70.68
37.11
3.19
5.70
0.51
75%
2.67
72.33
33.39
2.60
5.44
0.39
100%
2.67
64.68
23.06
1.60
3.04
0.14
F-test
ns
ns
ns
ns
ns
ns
C.V. )%)
35.21
12.46
41.93
35.62
44.49
62.27
Note: Mean (n=3) in the same column followed by the same lower case letters are not significantly different at p≤0.05ⒸISERD46

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

CONCLUSION
Every wastewater application significantly produced maximum Napier grass biomass based on
measured data. Therefore, wastewater from cassava industry natural can be reused to give enhanced
Napier grass biomass production. The reuse of wastewater from cassava industry for Napier grass
production considered the aspects of water reuse, nutrient reuse, and biomass production. The highbiomass yield of Napier grass also makes it a possible potential feedstock in producing cellulosic
ethanol, with the added benefit of water quality improvement and sustainable energy. This study
suggests that through the cultivation of highly productive, low input, perennial and valuable plant
species, benefits can be realized in the form of water quality improvement, water reuse, nutrient reuse,biomass production, and sustainable energy.
ACKNOWLEDGEMENTS
This research project was supported by Integrated Water Resource Management Research andDevelopment Center in Northeast Thailand, Khon Kaen University, Thailand. We would like to thankKalasin cassava industry, Miss Matanee Polsuwan, Miss Arpaporn Mudnawed, and Mr. Thongchai
Seangchad for research assistance.
REFERENCES
Chavalparit, O. and Ongwandee, M. 2009. Clean technology for the tapioca starch industry in Thailand. Journalof Cleaner Production, 17, 105-110.
DOA. 2005. Database of agriculture: starch. Thailand: Department of Agriculture, Ministry of Agriculture andCooperatives. Available in: http//www.doa.go.th/data-doa/starch/stat/st04.htm.
Gattaa, G., Libuttia, A., Gagliardia, A., Beneducea, L., Brusettib, L. Borrusob, L., Disciglioa, G., and Tarantinoa,
E. 2015. Treated agro-industrial wastewater irrigation of tomato crop: Effects on qualitative / quantitative
characteristics of production and microbiological properties of the soil. Agricultural Water Management, 149,
33-43.
Hien, P.G., Oanh, L.T.K., Viet, N.T., and Lettinga, G. 1999. Closed wastewater system in the tapioca industry in
Vietnam. Water Sci Technol, 39, 89-96.
Ministry of Science, Technology and Environment (MOST). 1996. Water quality standard: Issued under the
Enhancement and Conservation of the National Environmental Quality Act B.E.2535 (1992), published in
the Royal Government Gazette, Vol. 113 Part 13 D, dated February 13, B.E.2539.
Tanticharoen, M. and Bhumiratanatries, S. 1995. Wastewater treatment in agro-industry: A case study inThailand. In: Sastry, C.A., Hashim, M.A., Agamuthu, P. editors. Waste treatment plants. John Wiley & Sons
(Asia).

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Research article
erd

The Study of Greenhouse Gas Emissions of Ethanol
Production from Agro-industrial Fruit Residues
SOMPORN PLEANJAI*
Rajamangala University of Technology Thanyaburi, Pathumthani, Thailand
Email: somporn_p@rmutt.ac.th

PONGSRI SIWARASAK
Rajamangala University of Technology Thanyaburi, Pathumthani, Thailand
Received 3 March 2015

Accepted 15 May 2015(*Corresponding Author)

Abstract Nowadays, bio-ethanol is playing an important role as an alternative fuel forpassenger cars in Thailand. The use of biofuel can reduce greenhouse gas (GHG) emissions
because it is derived from plant materials. This study aimed to analyze greenhouse gas (GHG)
emissions of ethanol production from agro-industrial fruit residues based on a life cycle
approach. The results showed that the life cycle GHG emissions of ethanol production were
found to be 123.10 kg CO2-eq/kg of anhydrous ethanol. The main source of GHG emission was
the electricity used in the process stage (97.83%) and the second was materials and reagentsused in the stage (2.64%). It showed major energy consumption came from the conversion
process to produce ethanol. Another encouraging result is that 1 kg non-pretreated pineapple
peel waste inputs could produce 525 g of ethanol fuel; or it is was estimated to be 52-53% of
ethanol production. Therefore, agro-industrial fruit residues can be feedstock for ethanol
production in Tropical countries.
Keywords LCA, GHG, ethanol, pineapple peel waste

INTRODUCTION
Biofuels are important because they replace petroleum fuels. The emissions of greenhouse gases(GHGs), in particular carbon dioxide (CO2), are expected to reduce when fossil fuels are replaced with
biofuels; because the latter are derived from plant materials. Bioethanol is by far the most widely usedbiofuel for transportation worldwide. Ethanol utilization for sustainable energy in this decade is desired
especially ethanol produced from agricultural waste. The reason is, in the sense of economy andenvironmental prevention, it can reduce greenhouse effects. There are studies on ethanol production
from agricultural waste such as sweet sorghum bagasse, cassava waste, rice straws, and pineapple peel
waste, which are renewable and interesting resources (Itelima et al., 2013; Nigam, 1999; Siwarasak etal., 2006; Siwarasak et al., 2012; and Wang et al., 2012). Ethanol production is an alternative energythat can solve environmental impact and a value added form of solid-waste for agricultural industries,
particularly in Thailand. The bioconversion of cellulose and hemicelluloses to monomeric sugars, forexample, carbohydrates with 5 and 6 carbons are harder to accomplish than the conversion of starch,presently used for bioethanol production (Ohgren et al., 2006). There are several options for alignocelluloses-to-bioethanol process, which is chosen. However, a few data on an environmental
analysis of bioethanol production from agro-industrial fruit residues have been reported. The cassava
waste and rice straws are high potential raw materials to produce ethanol from fermentation. Moreover,pineapple peel is a potential raw material to produce ethanol due to its containing an appreciable
amount of insoluble fiber-rich fraction, which primary consists of cellulose, pectin substances,hemicelluloses, and notable proportions of lignin (Huang et al., 2011). According to Thai Office ofⒸISERD48

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Agricultural Economics, Thai pineapple products in 2011 were increased by 25.41% compared to theprevious year (OIE, 2012). The products mostly included fresh pineapples and processed pineapple
products. Canned pineapple processing industry is one of the highest potential industries in Thailand,
due to its geography of locating in monsoon region. The skins, cores, and ends of a pineapple are notdiscarded in pineapple canneries but instead used to make a number of products such as vinegar,
alcohol, and animal food. Thailand is ranked as the top of the pineapple exporting countries with amarket share of 40-50% (Eapsirimetee et al., 2013). Table 1 shows the 2015 forecasting of farm crop
perennial trees and fruit trees in the whole kingdom including harvested areas, productions, and yieldof pineapple (OAE, 2015). Furthermore, an analysis of supply or productivity of pineapple in Thailand
is also reported in the table. Pineapple peel, a by-product of the pineapple processing industry, accountfor 29-40% (w/w) of total pineapple weight (Choonut et al., 2014). From Table 1, this implies a highpotential of using pineapple peel for ethanol production.
Table 1 Forecasting of farm crop perennial trees, fruit trees and pineapple productivity in
ThailandPineapples
Harvested areas (rais)
Productions (tons)
Yield (kgs/rai)

2013
532,947
2,067,908
3,880

Year
2014
479,072
1,748,222
3,649

2015
476,433
1,702,735
3,574

Quantity±-2,639-45,487-75

Percent
±
-0.55
-2.60
-2.06

OBJECTIVES
The aim of this study was to investigate the impact of bioethanol production by fermentation fromagro-industrial fruit residues with Trichoderma reesei RT-P1 and Saccharomyces cerevisiae RT-P2 tothe environment and to promote the use of indigenous and renewable sources for transportation fuels.
Life cycle assessment (LCA) was carried out to determine the GHG emissions performance.
Bioethanol from pineapple peel wastes in Thailand was considered in the analysis.
METHODOLOGYLife cycle assessment (LCA) was used as an environmental assessment tool to identify and evaluate
the GHG emissions of bioethanol production from agro-industrial fruit residues (pineapple peel wastes).
LCA methodology used in this study was based on ISO 14040 framework, which consisted of four
steps: goal and scope definition, inventory analysis, impact assessment, and interpretation (Lee andInaba, 2004). The life cycle inventory analysis and impact assessment were carried out based on ISO
14040 for all stages involved in the production of 1 kg of 99.5% ethanol (anhydrous ethanol) frompineapple peel wastes which included transportation and bioethanol conversion, but not cultivation andharvesting. The functional unit (FU) of this study was 1 kg of 99.5% ethanol production. The systemboundary is shown in Fig. 1. Most of input-output data were collected as primary data at the actual
sites in Thailand. These collected data included raw materials used, energy consumption, utilities, andwaste generated within the system boundary. The secondary data were used in this study as necessary
from literatures, calculation, etc. The analyses focused on the three most important GHGs of bioenergy
systems including i.e. carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), with the global
warming potential factors of 1, 25, 298 kg CO2-eq/kg substance, respectively (IPCC, 2007).

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Pineapple peel
wastesTransport

Chemical substances
EnzymeWater
Electricity

Bioethanol
conversion

Emission to-air-water-soil

Bioethanol

Fig.1 Product system boundary of this study

Fig.1 Product system boundary of this study
Preparation of Raw Materials and Transportation
In this study, pineapple peel waste was tendered by United Winery and Distillery Company limited,
Nakhon Chai Si, Nakhon Pathom province, Thailand. Pickup Trucks with load 560 kg transported
pineapple peel wastes from the factory to Chemical Engineering Laboratory. The laboratory is locatedin Rajamangala University of Technology Thanyaburi, Pathumthani province, Thailand. The transportdistance was 200 km (round trip). The data were collected at the sites. Diesel fuel consumption was
24.5 L per 200 km (Table 2). The samples were dried before performing the experiment.
Bioethanol Conversion
Based on the optimal fermentation conditions obtained from analysis results of orthogonal experiment,
the verification of ethanol conversion was obtained from fermentation by using crude enzyme powder.
Crude enzyme powder was produced from co-culture of Trichoderma reesei RT-P1 andSaccharomyces cerevisiae RT-P2. The ethanol fermentation was carried out in 250 mL shaking flasks
at 120 rpm, by using 8% dried weight of pineapple peels in 100 mL liquid medium for 1 to 5 days
cultivation at initial pH 5 at room temperature (30 oC). Samples were collected daily for analysis ofethanol and reduced sugar concentration. Ethanol concentrations were estimated by the dichromate
colorimetric method (Williams and Reese, 1950), and the reduced sugar concentrations were estimatedto be 3, 5-dinitrosalicyclic acid (Miller, 1959). Three replications were done in this experiment.
RESULTS AND DISCUSSION
Ethanol batch fermentation from pineapple peels wastes with the crude enzyme powder was analyzed.
The results of batch fermentation are shown in Fig. 2. From the figure, ethanol concentration was
initially around 8 g/L for batch fermentation. Ethanol values increased to 42 g/L on day 4. Then
Ethanol concentration decreased to about 18 g/L on day 5. The more increasing ethanol led the moredecrease of sugar due to the enzyme hydrolysis done by cellulose of the crude enzyme powder during
its exponential growth and the decrease of sugar converted to ethanol (Lever et al., 2010; Mamma et al.,1996). In addition, direct energy and material inputs in the ethanol production system are summarizedin Table 2, which the GHG emissions per kg of 99.5% ethanol production were calculated. The
calculated emission results are presented in Fig.3, representing 123.10 kg CO2-eq/kg ethanol. The
assessment reveals that there were wide ranges of GHG emissions depending on the productionⒸISERD50

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

50
45
40
35
30
25
20
15
10
5
0

45
40
35
30
25
20
15
10

g/L Reducing sugar

g/L Ethanol

environment such as type of fuel used in transportation, water consumption, materials and reagents andelectricity used in the ethanol production.

5
0
0

1

2

3

reducing sugar

4

5

day

ethanol

Fig. 2 Ethanol and reducing sugar in batch fermentation (SD 3%)
Table 2 Direct material and energy-related input/output associated with ethanol production
systemSegment
Ethanol conversion
pineapple peel waste
EnzymeCaHPO4
MgSO4
Urea
K2PO4
Sugar
Water
Electricity
Transportation
Diesel used for transport
Ethanol product

Unit

Input

g
g
g
g
g
g
g
L
kWh

1000.00
750.0012.50
12.50
100.00187.50375.0012.50
112.70km/L

8.16

Output525.00

The results of this study showed higher ethanol yield than other studies. For example, themaximum yield of bioethanol (9.69g/L) with no hydrogen production by S.cerevisiae with 36 % ofcellulose was achieved from pineapple peel after pretreatment with water and heat at 100 0C for 4 h.
(Choonut et al., 2014). The fermented broth using S. cerevisiae TISTR 5048 with 20.44 % of cellulose
gave the highest percentage of bioethanol yield which was 65 % (Niwaswong et al., 2014). Other
studies, lignocellulosic ethanol production could alternatively be done from agricultural wastes such as
corn stover, sugarcane bagasse and rice straw (Kadam and McMilland, 2003; Kadam et al., 2000; andKim and Dale, 2004). Lignocellulosic materials represented a promising option as a feedstock forethanol production by considering output/input energy ratios, great availability both in tropical andtemperate climate countries, low cost (primary related to their transport), and ethanol yields (Sánchez
and Cardona, 2008). Furthermore, it was found pineapple peel waste is quite simple, uncomplicated,
and low cost as it can be applicable in the ethanol production industries.

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Fig. 3 GHG emissions from ethanol production
In Thailand, with its agriculture-based economy, employs 20% of available agricultural residues
through agricultural wastes and by-products. Moreover, there is potential to produce 3.1-8.6 million
liters/day of ethanol (Kumar et al., 2013). However, the great production of ethanol from industrial
fruit residues can entail serious economic and environmental consequences. The greenhouse gas
reduction of ethanol with respect to conventional gasoline, on a well to wheel basis, is about 13% when
ethanol is derived from grain; and up to 90% for sugarcane-based ethanol (Quadrelli and Peterson,2007).
CONCLUSION
The maximum ethanol production was obtained from fermentation crude enzyme powder, which was
produced from co-culture of Trichoderma reesei RT-P1 and Saccharomyces cerevisiae RT-P2. Ethanol
values increased on day 4 with the use of 8% dried weight of pineapple peels in 100 mL liquid medium
for cultivation at initial pH 5 at room temperature (30oC). Among all processes in the ethanol
production system, ethanol conversion created the highest amount of GHG emissions (electricity used),
up to 97.8% of the total emissions. Materials and reagents used created 2.1% of the total GHG
emissions. The other processes, which were transportation (diesel used) and water consumption createdless than 1% of the total GHG emissions. Another encouraging result was 1 kg of non-pretreatedpineapple peel waste input could produce 525 g of ethanol fuel, or it is estimated to be 52-53% of
ethanol production. In this study, pineapple peel was proved as one of the potential raw materials forbioethanol production. Therefore, agro-industrial fruit residues can be used as feedstock for ethanol
production in tropical countries.
ACKNOWLEDGEMENTS
Financial support by the Thailand Research Fund under the Faculty of Science and Technology,
Rajamangala University of Technology Thanyaburi (Grant annual/2011)is gratefully acknowledged.
REFERENCES
Choonut, A., Saejong, M. and Sangkharak, K. 2014. The Production of ethanol and hydrogen from pineapple peel
by Saccharomyces cerevisiae and Enterrobacter aerogenes. Energy Procedia, 52, 242-249.
ⒸISERD52

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Eapsirimetee, P., Suthikarnnarunai, N. and Harnhiran, S. 2013. Balancing canned pineapple supply chain in
Thailand. European Journal of Business and Management, 5 (4), 32-39.
Huang, Y.I., Chow, C.J. and Fang, Y.J. 2011. Preparation and physical properties of fiber-rich fraction frompineapple peels as a potential ingredient. J. Food Drug Anal., 19, 318-323.
IPCC. 2007. Working group III report “mitigation of climate change”, Fourth assessment report. Cambridge
University Press.
Itelima, J., Onwuliri, F., Onwuliri, E., Onyimba, I. and Oforji, S. 2013. Bio-Ethanol production from banana,plantation and pineapple peels by simultaneous saccharification and fermentation process. International
Journal of Environmental Science Development, 4 (2), 213-216.
Lee, K. and Inaba, A. 2004. Life cycle assessment best practices of ISO 14040 Series. Asia-Pacific Economic
Co-operation, Singapore, 1-5.
Lever, M., Ho, G. and Cord-Ruwisch, R. 2010. Ethanol from lignocelluloses using crude unprocessed cellulose
from solid-state fermentation. Bioresource Technology, 101, 7083-7087.
Kadam, K.L. and McMillan, J. 2003. Availability of corn stover as a sustainable feedstock for bioethanol
production. Bioresource Technology, 88, 17-25.
Kadam, K.L., Forrest, L.H. and Jacobson, W.A. 2000. Rice straw as a lignocellulosic resource: Collection,
processing, transportation, and environmental aspect. Biomass and Bioenergy, 18, 369-389.
Kim, S. and Dale, B.E. 2004. Global potential bioethanol production from waste crops and crop residues.
Biomass and Bioenergy, 26, 361-375.
Kumar, S., Salam, A. P., Shrestha, P. and Ackom, E. K. 2013. An assessment of Thailand’s biofuel development.
Sustainability, 5, 1577-1597.
Mamma, D., Koullas, D., Fountoukidis, G., Kekos, D., Macris, B.J. and Koukios, E. 1996. Bioethanol from sweetsorghum: Simultaneous saccharification and fermentation of carbohydrates by a mixed microbial culture.
Process Biochemistry, 31 (4), 377-381.
Miller, G.L. 1959. Use of dinitrosalicylic acid and reagent for determination of reducing sugar. Analytical
Chemistry, 31, 426-427.
Nigam, J.M. 1999. Continuous ethanol production from pineapple cannery waste. J. Biotecthnol., 72, 197-202.
Niwaswong, C., Chaiyamate, P., Chotikosaikanon, P., and Ruangviriyachai, C. 2014. Simple and enhanced
production of lignocellulosic ethanol by diluted acid hydrolysis process of pineapple peel (Ananas comosus)
waste. African Journal of Biotechnology, 13 (38), 3928-3934.
OAE. 2015. Division of Agricultural Forecasting. Office Agricultural Economics (OAE). Forecasting resulting ofimportant
plant’sjournal(March2015)[Online].
Available:
http://www2.oae.go.th/
forecast/17_MAR2558/Eng/all/wh_e_02.htm
OIE. 2012. Office of Industrial Economics Team. Office of Industrial Economics (OIE). Industrial government(21 January 2012). [Online]. Available: http://www.oie.go.th
Ohgren, K., Bengtsson, O., Gorwa-Grauslund, M.F., Galbe, M., Hahn-Hagerdal, B., and Zacchi, G. 2006.
Simultaneous saccharification and co-fermentation of glucose and xylose in steam-presented corn stover athigh fiber content with Saccharomyces cerevisiae TMB3400. J. Biotechnol., 126: 488-98.
Quadrelli, R. and Peterson, S. The energy-climate change: Recent trends in CO2 emissions from fuel combustion.
Energ. Policy, 35, 5938-5952.
Sánchez, Ơ.J. and Cardona, C.A. 2008. Trends in biotechnological production of fuel ethanol from different
feedstocks. Bioresource Technology, 99, 5270-5295.
Siwarasak, P., Srinophakun, P. and Chatmanop, J. 2006. The study on growth kinetics of Trichoderma reesei inbatch fermentation of cassava waste and rice straws. J. Eng. RMUTT., 8 (2), 94-99.
Siwarasak, P., Pajantagate, P. and Prasertlertrat, K. 2012. Use of Trichoderma reesei RT-P1 crude enzyme
powder for ethanol fermentation of sweet sorghum fresh stalks. Biores. Technol., 107, 200-204.
Wang, W., Zhuang, X., Yuan, Z., Yu, Q., Qi, W., Wang, Q. and Tan, X. 2012. High consistency enzymaticsaccharification of sweet sorghum bagasse pretreated with liquid hot water. Biores. Technol., 108, 252-257.
Williams, M.B. and Reese, D. 1950. Colorimetric determination of ethyl alcohol. Analytical Chemistry 22, 14631582.

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Research article
erd

Evaluation on Agro-forestry System in Salt Affected andNon-salt Affected Areas
JEERANUCH SAKKHAMDUANG
Institute of Environmental Rehabilitation and Conservation, Southeast Asia Office, Thailand
Email: j.sakkhamduang@gmail.com

MACHITO MIHARA*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan /Institute of Environmental Rehabilitation and Conservation, Tokyo, Japan
Received 22 December 2014

Accepted 20 May 2015(*Corresponding Author)

Abstract Low economical return is the main constraint that makes farmers not grow more trees
in salt affected areas. So, the research interest was paid to the applicable agro-forestry system
combining advantages of trees and crops for rehabilitating salt affected soils and increasing
local farmers’ income. Accordingly, existing agro-forestry systems in salt affected and non-salt
affected areas in Khon Kaen province were investigated and evaluated. For the evaluation, theplant profile of each system was described in the investigation plot at 20m x 20m. In addition,
Simpson and Shannon indexes were used to evaluate plant diversity of each investigation plot.
Agro-forestry systems on salt affected areas could be categorized into five types: patch forests
in farmlands, trees on paddy bunds, tree plantations associated with animal husbandry, homegardens, and trees in vegetable gardens. On the other hand, agro-forestry systems in non-salt
affected areas could be categorized into seven types: trees in farm boundaries, trees on paddy
bunds, tree plantations associated with animal husbandry, trees in home gardens, trees invegetable gardens, trees in fruit orchards, and trees and aquaculture. The results of the two
indexes revealed that the diversity of plants in agro-forestry systems in non-salt affected areas
was higher than that in salt affected areas, except in the systems of tree plantations associatedwith animal husbandry and of trees in home gardens. It was considered that as the plant
diversity in salt affected areas was lower than that in non-salt affected areas due to soil salinity;
local people in salt affected areas kept higher plant diversity in the systems of tree plantations
associated with animal husbandry and of trees in home gardens for their livelihoods.
Keywords agro-forestry system, salt affected and non-salt affected areas,
Simpson diversity index, Shannon diversity index

INTRODUCTION
Reforestation by fast growing trees for lowering saline groundwater level is one of practices that can beapplied by local people for rehabilitating salt affected soil in northeast, Thailand (Yamklee et al, 1995;
Wada, 1998; Yuwaniyama, 2011). Several organizations in Thailand and overseas introduced theutilization of salt-tolerant trees and plants to solve or to mitigate salinization problem. However, local
farmers have not adapted planting trees, as it takes long time to gain the profit (Vittayakorn et al.,1994). Thus, the applicable practice that combines the advantage of growing trees for mitigating salt
affected soils along with generating income should be considered to introduce to local people.
Agro-forestry is an interface between agriculture and forestry and encompassed mixed land use
practices. Agro-forestry practices are ranging from simple forms of shifting cultivation to complex
hedgerow intercropping systems. All agro-forestry systems have the purposeful growing trees with

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

crops and/or animals for multiple products or benefits from the same management unit. Agro-forestry
also has three attributes: productivity, sustainability, and adoptability (Nair, 1993).
Agro-forestry systems for rehabilitating salt affected soils are widely applied in several countries
such as Australia, Bangladesh, and China, and India (Singh et al., 2002; Zang et al., 2004; Ahmed,
1991; Eastham et al., 1993).
Agro-forestry in Thailand has been practiced for a long time since the Forest Village Scheme wasintroduced by the Forest Industries Organisation of Thailand (FIO) in 1967 as an attempt to stop
further spreading of the fast shifting cultivation and deforestation in the country (Boonkird et al., 1984).
In Nakorn Ratchasima province, Im-Erb et al. (2004) reported that an agro-forestry system being
promoted in recharge area of the province for mitigating salt affected soils was well accepted by
farmers according to their additional income. In 2007, Ruaysoongern studied about agro-forestry
systems in the northeast of Thailand and categorized into 25 systems.
While there were some researches regarding agro-forestry systems in Thailand, there were a few
investigations focusing on agro-forestry practices in salt affected areas. The objectives of this study
were to categorize and evaluate the existing agro-forestry systems in salt affected and non-salt affectedareas in Khon Kaen province.
Salt affected and non-salt affected areas are defined by the salinity level of soils. Salinity level in
Thailand is defined by percentage of salt crust on soil surface in dry season. The area that salt crust
covers more than 50% is defined as very severely affected class, and the salt crust covers 10-50% isdefined as severely affected class, and for the 1-10% as moderately affected class and non-salt crust is
defined as non-salt affected area (Arunin, 1998).
METHODOLOGY
Field investigation on existing agro-forestry practices in salt affected areas and non-salt affected area
were conducted in September, 2009 and March 2013 in Khon Kaen province, Thailand. Aerial maps
were used for identifying the land utilization. After the land utilization was identified, agro-forestry
practices were categorized based on the studies of Ruaysoonngern (2007) and Nair (1993). The
sampling plots of 20m x 20m were made for observing plant profiles of each practice. For thecomparison of agro-forestry in salt affected and non-salt affected areas, Simpson diversity index andShannon diversity index were employed in this research. The Simpson diversity index is theprobability of any two individuals drawn at random from an infinitely large community belonging tosame species. The Shannon diversity index assumes that individuals are randomly sampled from anindefinitely large population and also assumes that all species are represented in the sample.
Simpson diversity index (1949)𝑠(𝑃𝑖 2 )

𝐷=

where

𝑖=1

and Shannon’s index (1949)

𝑠
′

𝐻 =−
𝑖=1

where

(1)

D = Value of Simpson’s diversity index
Pi = proportion of individuals in the ith speciess = number of species𝑛𝑖𝑛𝑖{( ) ∙ ln( )}𝑁𝑁H’ = Value of Shannon’s diversity index
Pi = proportion of individuals in the ith species
ln = natural logarithms = number of species in communityⒸISERD55(2)

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

The indexes were used for calculating diversity index of each sampling plot. Moreover, hearing
survey to farmers regarding their land utilization were also conducted.
Research Sites
Salt affected areas: Phra Yun district is one of the salt affected areas of Khon Kaen province.
According to Regional Environment Office 10, Khon Kaen reported that salt affected areas cover 6,095
hectare or around 35 percent of the district area (REO 10, 2003). Agriculture is the main occupation ofpeople in the district while paddy rice and sugarcane are the main agricultural products (Phra Yun
Community Development Office, 2012).
Non-salt affected areas: Nong Rue district is one of the non-salt affected areas of Khon Kaen
province. Agriculture is the main occupation of the people in the district while paddy rice, cassava, veg
etable, and sugarcane are main agricultural products (Nong Rue Community Development Office, 201
2).

Non salt affected area
Salt affected area

Fig. 1 Study areas
RESULTS AND DISCUSSION
Salt Affected Areas
Land uses in the salt affected areas were classified into paddy field, upland field, patch forest along thestream, settlement area, and bare area. Five agro-forestry systems were found in salt affected areas.
Patch forest in farmland was a small area of natural forest surrounded by naked land or farmland, as thenatural Dipterocarp trees were kept in farmland for collecting fuelwood and being source of timber, as
well as food such as leaves, flowers, shoots, and mushrooms. The samples of tree from patch forests
were Sindora siamensis, Dipterocarpus obtusifolius, Xylia xylocarpa, and Lannea coromandelica.

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Farmers in the northeast of Thailand preferred to keep trees in their paddy bunds for
multipurposes. Trees found in the paddy bunds were considered important due to their commercial
value. Shorea obtusa was the dominant tree found in the paddy bunds. Farmers with large areas planted
trees and let their cows graze in the plantation for weed control. The cows also provided natural
fertilizer for trees in the plantations. The samples of trees from the plantation were Eucalyptus
camaldulensis, Tectona grandis, and Pterocarpus macrocarpus.
20 m

20 m

2

2

1

1

5

5

5

3

5

5

5

3

5

5
5

5

1

1

3
3

5

5

2

00

5

1

1

2

5

5
5
5
5
4
5

00
20 m
2
1
1
2
5
Fig. 2 Trees in home gardens

20 m

As shown in Fig. 3, farmers planted several kinds of tree in their home garden. The examples oftree in the home gardens were Bambusa bambos, and Thyrsostachys siamensis, S. siamensis andAzadirachta indica. Fast-growing Anthocephalus chinensis was found to be used for temporary
construction materials and Pennisetum purpureum for fodder. In vegetable gardens, farmers planted
several kinds of tree together with vegetables. The trees of Mangifera indica, Cocos nucifera, Musasapientum,and Anthocephalus chinensis were used as edible fruits and temporary construction
materials.
Non-salt Affected Areas
Land uses in the non-salt affected areas were classified into paddy field, upland field, trees plantation, water
bodies, fruit orchards, and settlement area. Agro-forestry systems in non-salt affected area could be
categorized into seven types.
Farmers often grew trees for indicating farm boundary because it was cheaper than construct farm
fence. Trees that mainly grew for indicating farm boundary were valuable trees or fast growing ones
such as E. camaldulensis, A. indica, and Bambusa sp. In the sampling plot, P. marcrocarpus weregrown for indicating boundary of sugarcane farm.
20 m

20 m

0

20 m

0

20 m

Fig. 3 Trees in home gardenⒸISERD57

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Trees on paddy bunds were kept for several purposes. Aside from natural trees, in non-salt
affected area farmers also grew fast growing trees for economical purpose. In the sampling plot, E.
camaldulensis and A. indica were grown on the paddy bund for economical purpose. Farmers who had
enough farmland grew commercial trees in large area and let their cows graze in the plantation forweed control. Besides weed control, cows also provided natural fertilizer for the trees in the plantations.
The sample of the tree from the plantation was E. camaldulensis.
As shown in Fig. 3, home gardens consisted of various kinds of tree for foods, construction
materials, fuel wood, and material for handicraft. The samples of trees in the home gardens were B.
bambos for construction and handicraft, garden fences; Cocos nuciferus and Musa sapientum for food;and Cyperus alternifolius for weaving mat. In vegetable gardens, several kinds of trees were planted
together with vegetables. For this agro-forestry practice, 18 species of plants were found included trees
such as fruits trees and timber trees for construction materials.
Farmers grew trees and mixed them with fruit trees for several purposes. In fruit orchard, trees
were grown and resulted in multi-storey pattern, the highest tree P. macrocarpus and Tamarindus
indica provided shade to Annona squamosa and Dimocarpus longan while B. bambos was the middle
storey. Two of agro-forestry practices that commonly applied in non-salt affected areas were trees andaquaculture. In this practice, several kinds of trees were grown around fish pond for fruit, construction
material, and shadow. Moreover, trees around fish pond also provided shade that decreased
evaporation. Trees found in this practice included; P. macrocarpus, Mangifera indica, A. indica,
Borassus flabellifer, Leucaena leucocephala and Erythophleum succirubrum.
Trees found on the paddy bund in salt affected areas were the trees surviving from the forest whiletrees found on paddy bund in non-salt affected area were domesticated or new introduced trees. The
result was similar to Vityakon (1993) finding that surviving trees were once a part of dry Dipterocarp
forest while the domesticated or new introduced trees were grown intentionally.
Comparison of Agro-forestry System in Salt Affected and Non-salt Affected Areas
The results of the field investigation of agro-forestry systems in salt affected and non-salt affectedareas in Khon Kaen province indicated that the agro-forestry systems as well as plant varieties in salt
affected areas had a lower variety than that in non-salt affected areas.
Table 1 Simpson and Shannon diversity indexes of plant species found in each agro-forestry
system in salt affected and non-salt affected area
Salt affected area

Non-salt affected area

Practice

1/D

ShannonDiversityindex

1. Patch forests in farmland

2.666

1.165

non
observed
1.001

nonobserved
0.004

4. Tree plantation associatedwith animal husbandry

1.134

0.279

4. Tree plantation associatedwith animal husbandry

5. Trees in home garden

2.909

1.098

6. Trees in vegetable garden

3.111
non
observed
nonobserved

1.174
nonobserved
nonobserved

2. Trees on farm boundary
3. Trees on paddy bunds

7. Trees in fruit orchard
8. Trees and aquarculture

1. Patch forests in farmland

nonobserved

ShannonDiversityindex
nonobserved

2. Trees on farm boundary

1.04

0.097

3. Trees on paddy bund

1.002

0.01

1

0

5. Trees in home garden

1.006

0.024

6. Trees in vegetable garden

34.7350.512

7. Trees in fruit orchard

3.459

1.284

8. Trees and aquarculture

9.142

1.126

PracticeⒸISERD58

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Moreover, total plant species, as well as plant numbers that were found in agro-forestry systems insalt affected area were lower than that in non-salt affected area. The results of Simpson diversity index
and Shannon’s index revealed that the diversity of plants in agro-forestry systems in non-salt affected area
were higher than that of in salt affected area except in the practices of tree plantation associate with animalhusbandry and trees in home garden (Tables 1).
CONCLUSION
The agro-forestry systems found in salt affected areas consisted of five practices while in non-salt
affected areas consisted of seven practices. Simpson diversity index and Shannon’s index revealed thatthe diversity of plants in agro-forestry systems in non-salt affected area were higher than that of in salt
affected area except in the systems of tree plantation associate with animal husbandry and trees in homegarden. Based on the investigated results, it was suggested that the suitable agro-forestry system withhigher varieties of plant be introduced in salt affected area.
It was suggested that farmers in salt affected area increase the diversity of tree species especiallysalt tolerant tree together with salt tolerant or halophyte vegetable or field crop in each agro-forestry
practice in salt affected areas for increasing plants diversity and income, as well as rehabilitating salt
affected soil.
REFERENCES
Ahmed, P. 1991. Agroforestry: A viable land use of alkali soils. Agroforestry Systems, 14, 23-37.
Arunin, S. 1998. Soil salinity of Thailand. Land Development Department, Ministry of Agricultural andcooperative (in Thai). Bangkok, Thailand.
Boonkird, S.A., Fernandes, E.C.M. and Nair, P.K.R. 1984. Forest villages: An agroforestry approach torehabilitating forest land degraded by shifting cultivation in Thailand. Agroforestry System, 2, 87-102.
Eastham, J., Scott, P.R., Steckis, R.A., Barton, A.F. M., Hunter, L.J. and Sudmeyer, R.J. 1993. Survival, growthand productivity of tree species under evaluation for agroforestry to control salinity in the Western Australian
wheatbelt. Agroforestry Systems, 21, 223-237.
Nair, P.K.R. 1993. An introduction to agroforestry. Kluwer Academic Publisher, Massachusetts, USA.
Phothithai, M. 1993. Agroforestry in Thailand: Perspective of forest industry organization (FIO). Thai Journal ofForestry, 12, 27-33.
Ruaysoongern, S. 2007. Agroforestry systems in the northeast of Thailand. Faculty of Agriculture, Khon Kaen
University, Thailand. (in Thai with English abstract)
Shannon, C.E. and Weaver, W. 1949. The mathematical theory of communication. The University of Illinois
Press, Urbana, USA.
Simpson, E.H. 1949. Measure of diversity. Nature, 163, 688.
Singh, S.S. and Khan, A.R. 2002. Enhancing productivity of salt affected soils through crops and cropping
system. The Abdus Salam International Centre for Theoretical Physics, Italy.
Vityakon, P. 1993. The traditional trees-in-paddy fields agro-ecosystem of northeast Thailand: It potential for
agroforestry development. Department of Soil Science, Faculty of Agriculture, Khon Kaen University,
Thailand.
Vityakorn, P., Polthani, A. and Kritsanaphuti, W. 1994. Factors influencing number of tees and farmers
conditions for trees integration in the farming system. A case study of District of Kranuan, Khon Kaen,
Northeast Thailand (in Thai with English abstract). Faculty of Agriculture, Khon Kaen University, Thailand.
Wada, H. 1998. Techniques and strategies to ameliorate salt-affected lands in Northeast Thailand. Japan
Agricultural Research Quarterl, 32, 79-85.
Yamklee, P., Dissataporn, C. and Arunin, S. 1995. Change in groundwater depth and quality resulting from
Eucalyptus reforestation on potential source area. Proceedings of the 3 rd Conference of Land Development
Department, 346-361. (in Thai)
Young, A. 1997. Agroforestry for soil management. 2 nd edition.
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Yuwaniyama, A. 2011. Impact of tree plantings on saline groundwater control. Proceeding of the 49 th Kasetsart
University Annual Conference, Natural Resources and Environment, 12-19. (in Thai with English abstract)
Zhang, J., Xing, S., Li, J., Makeschin, F. and Song, Y. 2004. Agroforestry and its application in amelioration ofsaline soils in eastern China coastal region. Forest Studies in China, 6 (2), 27-33.

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Research article
erdPollen Food Source Diversity of Stingless Bee Tetragonula
pegdeni and Lepidotrigona terminata in Cultivated Area
ANCHALEE SAWATTHUM*
Rajamangala University of Technology Thanyaburi, Thailand
Email: anchsawat@hotmail.com

RAWADEE KUMLERTThe Office of Disease Prevention Control, 12, Songkhla, Thailand
Received 23 February 2015

Accepted 31 May 2015(*Corresponding Author)

Abstract Stingless bees play an important role in pollination of local economic crops. During
rainy season, numbers of stingless bee population decline because of lack of food plants. It canlead to colony collapse situation. The main purpose of the first study was to survey the pollen
food source of stingless bees in the beginning of rainy season (June) to dry season (December)in the rambutan orchard plantation area in Chantaburi province. The result revealed that 11
species of blooming flowers in observation area were visited by stingless bees in June, fivespecies in October, and four species in December. The second study aimed to identify speciesof pollen food source from pollen load collected from stingless bees (Tetragonula pegdeni and
Lepidotrigona terminate) colonies in vegetable planting area. It was found that the mostfavorite plants that stingless bees collected as their pollen food source were amaranth(Amaranthus lividus) and corn (Zea mays. Linn).
Keywords pollen food source, diversity, stingless bee

INTRODUCTION
Pollination for fruit and seed set is very important for most crop plants. It has been estimated that about
30% of human food is derived from bee-pollinated crops (Kearns and Inouye, 1997). Stingless bee is akind of bees considered as an important pollinator of the native flora in tropical and subtropical parts of
the world. Stingless bees have been used as insect pollinators of many crops (Heard, 1999). In easternpart of Thailand, stingless bees have been kept and used as insect pollinators especially for rambutan
for decades (Sawatthum, 2004). In Chantaburi province, several stingless beekeepers sell or rent out
stingless bee hives. To be able to use stingless bees for commercial pollination purpose, proper
management of colonies in hives is very important. As this type of bees can form perennial colonies
from which they forage for food all year-round. Nectar and pollen are food of adult bees as they feed
their larvae with pollen. For the bees, an understanding of their main pollen sources allow us toestablish plantations providing them with pollen and consequently leading to the stability of thecolonies (Kerr et al., 1986). There are a few plants blooming during rainy season in Thailand.
Moreover, it is hard for stingless bee workers to fly out when it rains. These cause lack of storage foodsituation for all members in the colonies, especially pollen for the larvae. These conditions weaken thecolonies and have an affect on the survival of the colonies due to the scarcity of pollens. To reducethese problems, the stingless beekeepers need to know the pollen sources in rambutan plantation(Meliponiary) and in vegetable farms in order to plant them to support pollen for the bees. Pollens fromviable sources are vital inputs that stingless beekeepers should sustainably manage so that the stinglessbee colonies can be protected and promoted for economic and ecologicalpurposes.

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OBJECTIVESThis research was implemented with the following objectives:
1. Observation on flower visited by stingless bees in rambutan plantation
2. Studies of pollen sources of 2 stingless bees in vegetable farm
METHODOLOGY
Plant and Pollen Specimens Collection
Pollen specimens collection: Pollen was collected during the period of greatest pollen scarcity (fewer
species in the flowering phase). The collecting expedition took place from June to December 2010. The
collection locations were Meliponiary of stingless beekeeping in Wang-Pla sub-district, Thamai district,
Chantaburi province and stingless bee nests were kept in vegetable farm nursery of Crop Production
Department, Faculty of Agricultural Technology, Rajamagala University of Technology. Pollen wascollected from bloom flowers around 300 meters far from Meliponiary rambutan plantation in the
beginning of rainy season (June), beginning of dry season (October), during dry season (December),and blooming flowers 300 meters around vegetable farm nursery all year round to be used as reference
pollens. Another pollen samples were collected from bee pollen loading from worker bees in front of
the nests. Two species of stingless bees were chosen, namely: Tetragonula pegdeni (8 colonies) and
Lepidotrigona terminate (4 colonies). The pollen samples were chemically processed via acetolysis(applied from Erdtman, 1952 and Brown, 1960). The samples were then mounted in glycerin jelly andsealed with paraffin. Three slides were prepared for each sample. Pollen types were determined bycomparing each slide to reference slides (known flowers) and by consulting the specialized literature inthis field.
Plant specimens collection: Flowering plant specimens were collected from both sites at the sametime as collected pollen samples. Five specimens per plant were collected and preserved as herbarium
specimens and identified with the help of specialized literature.
Pollen Sources of Stingless Bees Analysis
Data on flowering plants, types of pollen from pollen loads were matched to the analyzed pollen
sources of both stingless bees.
RESULTS AND DISCUSSION
Flowering plants around Meliponiary in rambutan plantation in Wang-Pla sub-district, Thamai district,
Chantaburi province, visited by stingless bees were observed and sample were collected in June,
October, and December; 2010. The small numbers of blooming flowers visited by stingless bees wasshown in those three observations. Eleven species were found in June, five species in October, and four
species in December (Table 1).
The Pollen Source Analysis
The pollen load collected in front of 12 colonies from two species of stingless bee (T. pegdeni and L.
terminata) in vegetable farm showed that pollen of 17 plant species was found in pollen load species
and colonies of stingless bees showed individual character of collecting the various species of pollen
plants.
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Table 1 Blooming flowers visited by stingless bee
Month ofobservation
June

Common nameSulfur Cosmos
Goat Weed
Bird Chilli
Hairy Basil.
Holy basil, Sacred BasilJava Tea, Kidney tea, Cat’ s
Whiskers
white gourd, wax gourd
White Popinac, Lead Tree,
Wild TamarindAngel face pin

October

DecemberCommon Purslane,Verdolaga,
Pigweed, Little Hogweed,
PusleyUnknowWhite Popinac, Lead Tree,
Wild Tamarind
Rose
Hairy Basil
Purslane, Pussley, Rose mose,Sun plant, Eleven-o'clock
Unknown
Water lily
Coral Vine, Pink Vine
white gourd, wax gourd
banana blossom

Plant
Scientific nameCosmos spp.
Ageratum conyzoides Linn.
Capsicum annuum
Ocimum basilicum L.f. var.
citratum Back.
Ocimum sanctum L.
Orthosiphon aristatus(Blume) Miq. Bolding
Benincasa hispida
Leucaena leucocephala(Lamk.) de Wit.
Cynoglossum lanceolatum
ForsskPortulaca oleracea L.

FamilyAsteraceae
Asteraceae
Solanaceae
Labiatae
Labiatae
Labiatae
Cucurbitaceae
Leguminosae
Boraginaceae
Portulacaceae

Leucaena leucocephala(Lamk.) de Wit.
Rosa hybrids
Ocimum basilicum L.f. var.
citratum Back.
Portulaca oleracea L.

Leguminosae

Nymphaea lotus L.
Antigonon leptopus. Hook. &Arn
Benincasa hispidaMusa sapientum L.

Nymphaeaceae
Polygonaceae

Rosaceae
Labiatae
Portulacaceae

Cucurbitaceae
Musaceae

Tetragonula pegdeni colony number 8 collected the highest variety of pollen plants (sevenspecies) while L. terminata colony number 11 collected six species of pollen plants (Fig. 1). Figure 2
shows the most favorite plants found in pollen load in yellow flame. (Peltophorum pterocarpum (DC.)
Backer ex K.Heyne) and Corn (Zea mays. Linn), respectively. The observation in the field showed thatamaranth (Amaranthus lividus Linn.) was the favorite place of visiting of the stingless bees.
In southeastern Brazilian Atlantic Forest, stingless bees Tetragonisca angustula preferred to visit
Asteraceae and Anacardiamore than others (Braga J. A., et.al., 2012) while in manmade plantation in
Thailand, the two stingless bee species preferred Leguminosae (Peltophorum pterocarpum), Poaceae(Zea mays), and Amaranthaceae (Amaranthus lividus). Therefore, corn and amaranth could be pollen
plants providing pollen food sources for bees during pollen-scared season, as both of them were easy togrow in almost every kind of environment.

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1* Tp = Tetragonula pegdeni
Lt = Lepidotrigona terminata

Fig. 1 Number of plants found in pollen loads collected from worker stingless beesin front of the stingless bee colonies* 1 = Peltophorum pterocarpum (DC.) K. Heyne
3 = POACEAE
5 = Vaccinium sprengelii (G.Don) Sleumer
7 = Unknow 2
9 = Antigonon leptopus Hook. & Arn.
11 = Pterocarpus indicus Willd.
13 = AMARYLLIDACEAE
15 = Unknow 3
17 = Mikania micrantha H.B.K.

2 = Zea mays Linn.
4 = NYMPHAEACEAE
6 = Unknow 1
8 = Luffa acutangula (Linn.) Roxb.
10 = SOLANACEAE
12 = Maoutia puya (Wall. ex Hook.) Wedd.
14 = Solanum torvum Sw.
16 = Unknow 4

Fig. 2 Numbers of stingless bee colonies collected pollen from each pollen plant
CONCLUSION
Results of floral diversity using as pollen source of two stingless bees T. pegdeni and L. terminata
showed a small number floral plants visited by stingless bees during observation. There were eleven
species in June, five species in October, and four species in December. The most common pollen types
found in stingless bee pollen loads were Peltophorum pterocarpum (DC.) and K. Heyne and Zea mays
but the most popular plant visited by stingless bees found in vegetable farm was amaranth.

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ACKNOWLEDGEMENTS
This work was supported by Rajamangala University of Technology research fund. The author would
like to thank Assoc. Prof. Danai Vannavanich for his comments.
REFERENCES
Braga, J.A., Sales, E.O., Neto, J.S., Conde, M.M., Barth, O.M. and Lorenzon, M.C. 2012. Floral sources toTetragonisca angustula (Hymenoptera: Apidae) and their pollen morphology in a Southeastern Brazilian
Atlantic Forest. Rev.Biol.Trop, 60 (4), 1491-1501.
Heard, T.A. 1999. The role of stingless bee in crop pollination. Ann. Rev. Entomal., 44, 183-206.
Kearns, C.A. and Inouqe, D.W. 1997. Pollinator, flowering plants, and conservation biology. BioScience, 47,
297-307.
Kerr, W.E., Absy, M.L., Souza, A.C.M. 1986. Especies nectariferas poliniferas utilizadas pela abelha Melipona
compressipes fasciculate (Melipolinae - Apidae) no Maranhāo. Acta Amezonica, 16 (17), 145-156.
Sawatthum, A. 2004. Stingless bee keeping in Thailand. 8th International Conference on Tropical Bee and VI
Encontrosobre Abelhas 2004, September 6-10, 2004, Ribeirao Preto, SP. Brazil.

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Research article
erdAnalysis of Urban Ecosystem Services Considering
Conservation Priority
MAKOTO OOBA*National Institute for Environmental Studies, Tsukuba, Japan
Email: ooba.makoto@nies.go.jp

KIICHIRO HAYASHI
Nagoya University, Nagoya, Japan

TAKAHIRO SUZUKI
Nagoya University, Nagoya, JapanRUI LI
Nagoya University, Nagoya, Japan
Received 16 December 2014

Accepted 31 May 2015(*Corresponding Author)

Abstract Many cities lose their green space and ecosystem services, especially in developing
countries, which represent a problem as serious as an environmental pollution. Japan has also
experienced the problem as a result of rapid economic growth. A system to assess ecosystemservices and to create conservation maps in urban area was developed for use as a policy
suggestion for urban planning. Nine ecosystem services were calculated by proxy variables inthe studied area, Nagoya city, Japan. After selecting a subset of relatively and highly
independent proxy variables, five ecosystem services significantly decreased before and after aperiod of strong economic growth (1955 and 1997). Distributions of the ecosystem services had
trends of fragmentation indicated by a cluster analysis. Conservation priority maps created byusing the conservation planning software called Zonation were presented. In the eastern andwestern areas, ecosystem services decreased with the loss of green space indicated by theauthors in a previous study. The conservation priority level of the central area was relatively
high due to the loss of green space. The results of this study are helpful planning for green
space and offset-evaluating system.
Keywords Geographical Information System, green space, landuse, Nagoya, Zonation

INTRODUCTION
Many cities lose their green space (parks, agricultural fields, and secondary forests) and related
ecosystems due to an increase in population, industry, and business, especially in developing countries.
This loss represents a problem as serious as an environmental pollution. Japan has also experienced the
problem as a result of rapid economic growth. Currently, the green space in many Japanese cities isstill over 10% of the land area. However, it appears that the quality of this green space, as measured bycharacteristics such as continuousness and ecological complexity, has not remained high.
Ecosystem services (e.g., Costanza et al., 1997; Millennium Ecosystem Assessment, 2005),
defined as goods and services provided by ecosystems to human society, are essential for a sustainable
society. Green space in urban areas, including grass, agricultural, and forest ecosystems, provides
ecosystem services such as biodiversity conservation, air and water purification, climate mitigation,
disaster control, and cultural services (recreation, landscape, etc.). However, ecosystem services fromthese ecosystems decrease with urban development.
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From a socioeconomic point of view, setting ecosystem conservation priorities is an effective way
to maximize ecosystem services and/or biodiversity under economic constraints. Many software
programs have been applied to conservation planning for biodiversity, including C-Plan, Marxan, andZonation. Moilanen et al. (2011) researched competing land uses (in terms of their biodiversity, carbon
storage, agricultural production, and urban area) in Great Britain using Zonation software. Fan andShibata (2014) applied Zonation to the evaluation of ecosystem services in a river basin and found that
forest ecosystems should be prioritized, especially for the water supply service that they provide, for
Hokkaido, Japan.
In a previous study (Ooba and Hayashi, 2014), the authors indicated that land use in Nagoya,Japan differed before and after a period of strong economic growth, with the green space in Nagoya,including agricultural fields and forests, decreasing drastically. Those results mentioned that theprovisioning of ecosystem services also decreased drastically; however, quantitative evaluation was not
performed. In addition, conservation policy suggestions would be useful for the remaining green space,especially information on the areas that are the most important for maintaining or enhancing ecosystemservices based on detailed geographical and quantitative research.
OBJECTIVE
The aim of this study is the development of a system to assess ecosystem services in urban areas andcreate maps of ecosystem conservation priorities for use as a policy suggestion for urban planning.
METHODOLOGY
Study Area and Data Set
The study area (the city of Nagoya) is the same area as the previous study (Ooba and Hayashi, 2014).
The annual average temperature and precipitation are 15.8°C and 1,535.3 mm, respectively. With apopulation of approximately 2,260,000, metro Nagoya (ca. 32,600 ha) is Japan’s fourth largest city andis representative of urban Japan.
Digital maps of land use in 1955 and 1997 at a 10 m resolution were developed in the previous
study. The maps categorized 5 types of land use: water surface, built-up urban (residential andindustrial) areas, roads, agricultural fields, and forest. In this study, green space was defined as the
agricultural field and forest land uses. A digital elevation map (10-m resolution) was also used toestimate prevention of soil erosion. The following geographical processing and calculations were
performed using ArcGIS 10.2.
Evaluation of Ecosystem Services
Several variables were calculated as proxies for supply of ecosystem services from the studied area
(Table 1) at the resolution of the Japanese standard mesh defined by the Japan Industrial Standard,corresponding to approximately 1 km. The following variables were calculated using an area-based
primary unit for each land use: carbon sequestration, prevention of eutrophication, food supply, air
purification, climate mitigation (contribution to increase of air temperature), infiltration rate, andprevention of soil erosion. The detailed calculations used to generate these values are indicated in Table
1. For cultural services, a proxy variable was estimated from the distance to the nearest relatively large
green space (recreation index), defined as an area larger than 1 ha. A proxy for biodiversity
conservation was estimated from the continuousness of green space (biodiversity index) by using Focal
Statistics in ArcGIS and setting the proximity radius to 2 km. For the 1997 data set, these 9 variablesⒸISERD67

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

were converted to normalize values due to difference of units by subtracting the mean and dividing by
the standard deviation. Some variables (prevention of eutrophication, climate mitigation, prevention ofsoil erosion, and distance to a large green space) were of the opposite scale to the other variables.
These variables were reversed by multiplying by −1. For comparison to 1997, the variables for 1955
were normalized by the statistics of 1997.
A matrix of correlation coefficients among all proxy variables was generated to identify linear
relationships. After selecting a subset of relatively highly independent proxy variables, a cluster
analysis was performed using the k-mean method for the 1997 data set to clarify the characteristics of
ecosystem services at each mesh cell in the city. For the 1955 data set, each mesh cell was reclassified
and compared to the result for 1997 to obtain the differences between the two years. These calculations
were performed using statistical software (Excel statistics, Social Survey Research Information, Japan)
in Microsoft Excel 2013.
Table 1 Proxy variables of ecosystem services in urban area
Name
Carbon sequestration
Prevention ofeutrophication**
Food supply
Air purification
Climate mitigation**
Rain infiltration
Prevention of soil
erosion**

Cat*
S
S

Recreation **

C

P
R
R
R
R

Estimation Method
Primary unit

Values or Details
3.09(F)16.5(U), 42(A), 3.8(F)

Unit
t/y

2.98(A)
0.00615(A), 0.011(F)
6(U), −2.9(A), −1.3(F), 2(W)12.7(U), 89.3(A), 258.2(F)kg-N/yt/yt-NO2/y°Cmm/h

S = 65.41sin2T+ 4.56sinT+ 0.065
C = 1 (U), 0.33(A), 0.0085(F)S and C coefficient in
RUSLE 6-

Distance of relatively Enquired distance for large greenmlarge green space
space (A and F) polygon (> 1ha)
Biodiversity
S
continuousness of green Focal statistics (proximity radius 2
spacekm) (ArcGIS spatial tools)
Abbreviation: U: Urban area and road, A: Agricultural area, F: Forest area, W: Water surface* Category of ecosystem services: Supporting (S), Provisioning (P), Regulating (R), Cultural (C)** Opposite scale. High value of the variable indicated negative effect about the concerned ecosystem service.
1. Ogawa et al. (2003)
2. Japan Sewage Works Association (1997)
3. Aichi prefecture (2012)
4. Yokoo et al. (2003)
5. Murai and Iwasaki (1975)
6. Renard et al. (1997), RUSLE: Revised Universal Soil Loss Equation.
7. Ogawa et al. (2005)
8 Kitahara et al. (2000)
9 Li (2014)

Ref.
1
2
3
1
4
5
6
7(A)
8(F)
9
9

Algorithm of Calculating Conservation Priority
The conservation planning software Zonation provides several algorithms to determine conservation
priorities (e.g., core-area zonation). The authors chose the simplest algorithm, the additive benefit
function, which calculated the sum of all calculated values of ecosystem services for each mesh celland produced a mesh-map of the sums. In this study, the input values were the proxy values of
ecosystem services. The weight and cost for each proxy variable were assumed to be 1.0 (the default).
For a technical reason, the raster data for Zonation were created at a 500-m mesh converted from theabove mentioned approximately 1-km mesh.

ⒸISERD68

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

RESULTS AND DISCUSSION
Ecosystem Services Evaluated by Proxy Variables
Nine ecosystem services were estimated at a 1-km mesh for 1955 and 1997 for Nagoya city (data notshown). The matrix of correlation coefficients among all proxy variables was also calculated. The
variables calculated from the digital maps of land use type using the primary units exhibited highcorrelations with the other variables calculated by the same method. On the other hand, the variables
calculated using ArcGIS had low correlations with the former variables. For further analysis, thefollowing five variables of which correlation coefficients were less than 0.6 were selected: carbon
sequestration, food supply, prevention of soil erosion, recreation index, and biodiversity index. The
food supply variable was the only proxy of a provisioning service that was selected; it was chosen overprevention of eutrophication, which displayed a high correlation with food supply.
The values of all of the selected variables decreased from 1955 to 1997, which was related to adecrease in green space from 55% of the total city area to 16% (Ooba and Hayashi, 2014). The
distribution of the supply of ecosystem services also changed, becoming sparse and isolated in 1997.
Classification of Supply of Ecosystem Services
The distribution of classified mesh cells from the selected 5 proxies is indicated in Fig. 1. Because thenumber of classes is arbitrary in the k-mean method, the authors chose 5, which was the same as thenumber of classified types in the original land use maps. The following labels were used in referring to
the land use maps: core urban area, urban area, agricultural area, forested area, and green area.
Between the dates of the two land use maps, urban areas expanded and agricultural and forested areas
contracted complementarily. In 1997, green areas (mixture of urban area and green space area)
appeared as a result of the fragmentation of green space.
(a) 1955(b) 1997

Nagoya Stn
Higashiyama
Park
Urban area
Urban (core) area
Agricultural area
Forest area
Mixed area

Fig. 1 Classification from the proxy variables of ecosystem servicesⒸISERD69

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

10
Carbon sequestration

Food supply

Prevention of soil erosion

Recreation index

Biodiversity Index

Fig. 2 Relative priority ranks (0-1) of the selected ecosystem services(a) 1955(b) 1997(c) Difference of 1997 to 1955

0.75
−0.95

1
0

Fig. 3 Relative priority ranks and difference of integrated ecosystem services
Conservation Priorities
Priority maps for each of the 5 selected proxies were calculated using Zonation and are presented as
Fig. 2. The maps represent the conservation priority order of each mesh cell for each proxy variable(the blue colored cells supply the most ecosystem services). In 1955, the mesh cells on the east andwest sides in the city had relatively high values in the all ecosystem services, whereas almost half thecells in those areas had low values in 1997.
Integrated priority maps, presented as Fig. 3, were also calculated from the 5 variables using
Zonation. The conservation priority level of the marginal area of the city is high levels in 1955
provided from both agricultural and forest ecosystems. This east, especially east-south and east-north,high priority area almost disappeared by 1997. The west area remained a high priority. Compared tothe east area, the west and northeast areas were also assigned high priority. Fig. 3(c) presents thedifferences between the two years. This indicates an overall loss of ecosystem services, which isconsistent with the pattern observed above for each individual ecosystem service. It is notable that theⒸISERD70

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

conservation priority level of the central area is relatively high due to the loss of green space in themarginal area.
OutlookA relatively simple method (primary units) was applied to estimate the supply of ecosystem services.
Derived variables such as carbon sequestration and prevention of eutrophication were highly correlatedwith the other variables derived by the same method. For each estimate of supply of ecosystemservices, more appropriate methods may be developed that depends not only on land use but also onother geographic, statistical, or process-based methods. For several services, especially those related to
culture and biodiversity, innovative proxy variables and estimation methods are needed.
The default settings of the Zonation software program (weight and cost) were used in this study.
For widespread applicability, these values must be determined by suitable methods: Cost may be
estimated by building up the management costs of conserving an ecosystem. Weight may be estimatedby social investigation, such as an economic survey or questionnaire about the value of the ecosystem.
In a more practical context, discussions about an offset system for development have begun, andmany studies related to the design of such an offset system have been performed. Offset systems
focused on conserving natural land uses or biodiversity have already been introduced in the UnitedStates, Australia, and many European countries. The authors place a special focus on offset systems
based on assessing ecosystem services because the methodology for such a system provides not only
on-site offset (offset sites located near the development site) but also off-site offset because thesimilarity of ecosystems is assessed by the supply of ecosystem services from the target ecosystems.
CONCLUSION
The authors’ previous work revealed a drastic change in green space in Nagoya city from 1955 to 1997
(Ooba and Hayashi, 2014). This study included not only a quantitative evaluation of ecosystemservices but also an integrated assessment of ecosystem services in this area. The supply of ecosystemservices decreased along with the decreased area of green space. A high supply of ecosystem services
present in the marginal area of Nagoya city in 1955 disappeared, while in the eastern area, loss of
ecosystem services was relatively low. Conservation priority maps created using Zonation software
were presented, which is helpful planning for green space and offset-evaluating system in the studied
area.
ACKNOWLEDGEMENTS
This study was supported by the funding program for next generation world-leading researchers(MEXT, Japan) and the Environment Research and Technology Development Fund (1-1401, 2-1404,
MOE, Japan). The authors thank H. Shibata, M. Fan, and Y. Inagaki.
REFERENCES
Aich Prefecture. 2012. Statistics of agricultural production. http://www.pref.aichi.jp/0000038930.html (inJapanese)
Fan, M. and Shibata, H. 2014. Spatial and temporal analysis of hydrological provision ecosystem services forwatershed conservation planning of water resources. Water Resourc. Manage., 28. DOI: 10.1007/s11269014-0691-2.
Japan Sewage Works Association. 1997. Research guide and commentary for the integrated plan of seweragesystem development. (in Japanese)ⒸISERD71

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Kitahara, H., Okura Y., Sammori, T. and Kawanami, A. 2000. Application of Universal Soil Loss Equation(USLE) to mountainous forests in Japan. J. For. Res., 5, 231-236.
Li, R. 2014. The potential distributions of mammalian by Maxent model, Case of Nagoya City. Master Thesis,
Graduate School of Environmental Studies, Nagoya University, Japan.
Millennium Ecosystem Assessment. 2005. Ecosystems and human well-being, Synthesis. A Report of theMillennium Ecosystem Assessment, Island Press, Washington.
Moilanen, A., Meller, L., Leppanen, J., Pouzols, F.M., Arponen, A. and Kujala, A. 2012. Zonation version 3.1 user manual. Biodiversity Conservation Informatics Group, Department of Biosciences, University of
Helsinki, Finland. http://cbig.it.helsinki.fi/software/zonation/.
Murai, H. and Iwasaki, Y. 1975. Studies on function of water and soil conservation based on forest land (I). Bull.
Gov. For. Exp. Sta., 274, 23-84. (in Japanese with English summary)
Ogawa, K., Miwa, M., Shimada, T. and Ogawa, S. 2002. Air purification function and economic value of green
space in Japan. Report of Center for Environmental Science in Saitama, 1, 106-117. (in Japanese)
Ogawa, S., Shima, T., Yoshisako, H. and Fukumoto, M. 2005. Evaluation of farmland conservation forpreventing soil erosion. Tech. Rep. Natl. Res. Inst. Agric. Eng. Japan, 203, 139-146.
Ooba, M. and Hayashi, K. 2014. Comparative assessments of ecosystem services between rural and urban areas.
Int. J. Environ. Rural Develop., 5-2, 35-40.
Renard, K.G., Foster, G.R., Weesies, G.A., McCool, D.K., Yoder, D.C., coordinators. 1997. Predicting soil
erosion by water: A guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE)(Agricultural Handbook 703). Washington, D.C.: U.S. Goverment Printing Office.
Yokoo, N., Miyamoto, M., Shudo, H. and Oka, T. 2003. A study on the air temperature distribution influenced byvarious land uses: Part 3 secular change at Kanto area. J. Archit. Plann. Environ. Eng., 565, 107-112. (inJapanese with English summary)ⒸISERD72

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Research article
erd

Micro Hydroelectricity Using Irrigation Ponds for Better
Water Management
KATSUYUKI SHIMIZU*
Faculty of Agriculture, Tottori University, Tottori, Japan
Email: shimizu@muses.tottori-u.ac.jp

YASUYUKI KUSAKA
Sanyu Consultants INC, Nagoya, JapanYOSHINOBU KITAMURA
Arid Land Research Center, Tottori University, Tottori, Japan
Received 22 January 2015

Accepted 15 July 2015(*Corresponding Author)

Abstract This paper discusses estimates of hydroelectricity potential using irrigation ponds inmountainous areas. Hydroelectric power output is calculated from hydrological observations
such as discharge from the ponds and water level at two irrigation ponds. Although these ponds
have almost the same water storage capacity, water discharge patterns differ due to differencesin the command areas. Results show that water management influences the pattern ofhydroelectric power generation. The use of electricity is also important to consider sinceirrigation ponds in mountainous areas are distant from villages, which have no electricity
infrastructure. In most cases, the irrigation ponds in mountainous areas are difficult to access. In
addition, most of the water managers are aging and are having difficulty maintaining irrigation
ponds and its water management. Therefore, using hydroelectric power to support the operationand maintenance of irrigation ponds would be one of the best ways to use the hydroelectric
power generated at irrigation ponds. Finally, a field experiment of a micro-hydroelectricity
system is conducted at an irrigation pond and the pond monitoring system is installed.
Keywords renewable energy, siphon intake, automatic control, monitoring system

INTRODUCTION
Irrigation ponds are used as supplemental irrigation for paddy rice fields in Japan. Recently, thegeneration of micro hydroelectricity using irrigation facilities as a form of renewable energy hasreceived much attention due to encouragement by the Japanese government and the significant priceincreases in electric power. Irrigation ponds, especially those located in mountainous areas, can easily
generate the gravitational drop, which is necessary for hydroelectricity generation and gives advantage
to ponds in these areas more than the ones in flat areas.
Lots of investigations have been conducted by the government and local governments so thegovernments can estimate hydroelectricity potential in mountainous areas in Japan. However, most ofthem were calculated only by using topographic information and rainfall data without considering
actual water management. Ueda et al. (2013) have reviewed small-scale hydropower generation using
irrigation water in Japan. Ueda et al. (2015) had conducted a scenario analysis to propose a water
management scheme to balance two objectives, irrigation and hydropower. There is no research onhydropower generation using small irrigation ponds, as there are many in mountainous areas especiallyin western part of Japan.
Therefore, this paper discussed and estimated hydroelectricity potential using Nanatani pond andMatsutani irrigation ponds in Tottori, Japan and the use of electricity by considering current waterⒸISERD73

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

management practices. Moreover, field experiment of hydroelectricity was conducted at Yanaka pondin Tottori.
METHODOLOGY
Irrigation ponds are categorized into two groups, including ponds in mountainous areas and in flat
areas. In this paper, siphon intake is assumed to estimate the hydroelectricity potential using irrigation
ponds in mountainous areas. There are advantages of employing siphon intake, such as preventing dust
entering, making use of water head for hydroelectricity, reducing initial investment for hydroelectricity,and easier water management than conventional practices.
Study Areas
Two irrigation ponds, Nanatani and Matsutani, were selected in this study. Both of them are located in
mountainous areas of Tottori Prefecture, Japan. Storage capacities of the two ponds are more than
200,000 m3 and the height of both ponds are over 12 m. Considering more than 50% of irrigation
ponds in Tottori, the ponds have less than 10,000 m3 of water storage capacity, which are relatively
big ponds. Besides, there were significant differences in beneficiary areas and catchment areas.
Catchment areas of Nanatani pond were about half of the Matsutani’s one while beneficiary areas ofNanatani were more than 3 times of the Matsutani’s one. Water was collected from runoff of eachcatchment area only and there was no water supply from river water. General descriptions of theselected irrigation ponds are summarized in Table 1.
Table 1 General information about observed ponds
Name of Pond
Storage capacity (10,000 m3)
Dam height (m)Catchment area (ha)Beneficiary area (ha)Water resource

Nanatani
210.0
12.0
30.0
44.5
RunoffMatsutani
259.2
16.5
62.0
13.0
RunoffHydrological Observation and Estimation of Hydroelectricity
Siphon intake was assumed in this study instead of conventional operation. The opening and closing
bulbs on inclined inlet pipe were employed to make use of advantages of siphon for hydroelectricity
such as avoiding trash intake, easier operation of open and close gate, and getting water head and lower
cost. The outlines of hydroelectric system are illustrated in Fig. 1.
Also, hydroelectric power output (kW) is calculated as following Eq. 1.
𝑃 = 𝜌𝑔𝐻𝑒 𝑄 𝜂(1)3

Where, P is electric output (kW), 𝜌 is density of water (1,000kg/m ), g is gravity acceleration (9.8m/s2), He is effective head (m), Q is discharge (m3/s), 𝜂 is efficiency (0.601).
Water levels of irrigation ponds and canals were monitored in every 10 minutes during irrigationseason in 2010 and 2011. A level survey was conducted to determine the head and for hydrologicalobservations such as discharge from the ponds and water level. Height-volume curves of irrigations
ponds and height- discharge curves of irrigation canals were also prepared for the two ponds based on
the field survey.

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Fig. 1 Outlines of hydroelectric system
Field Experiment
Field experiment of siphon intake and hydroelectricity was conducted at Yanaka pond in Tottori during
non-irrigation period. Usage of generated electricity was also demonstrated such as installing electricbulb for easier water management and or monitoring system to inform water managers for the waterlevel of the ponds.
RESULTS AND DISCUSSION
Estimated Hydroelectricity
Fig. 2 (a) shows the estimated power output of Nanatani pond in 2010. Irrigation period is 106 days
from May 30 to September 12. Water discharge varied daily because water managers conventionally
opened the gate at 6 a.m. and close at 6 p.m. Water manager also adjusted the discharge according torainfall events. If it rained at 6 a.m., the water manager would not discharge water. If it rained at
daytime, the manager would go to the pond to decrease and/or stop discharge.
Fig. 2 (b) shows estimated power output of Matsutani pond in 2010. Irrigation period is 104 days
from June 1 to September 12. Compared with Natanani pond, Water level and discharge at Matsutani
pond were more stable. Irrigation water was released 24 hours and water discharge was adjusted every
3-4 days at Matsutani pond.
Table 2 Summary of the estimated output, 2011
Pond
Gross generation (kWh)Total discharge (103 m3)
Maximum output (kW)Average output (kW)Monitoring time (h)Discharge time (h)Generating time (h)CO2 conversion (kgCO2)
Oil conversion (L)NanataniMatsutani

1,821.0
199.7
5.0
1.7
2,538.0
1,080.0
1,080.0
1,011.0462.6

3,443.0
265.2
3.6
1.3
2,610.0
2,610.0
2,610.0
1,911.0
874.5

Table 2 shows the results of estimated hydroelectricity of two ponds for the year of 2011. The
maximum electric power output and electric power were 4.92 kW and 1,420 kWh at Nanatani pondand 3.57 kW and 3,000 kWh at Matsutani pond. Although these ponds had almost the same water
storage capacity, water discharge patterns differed due to differences in the command areas. NanataniⒸISERD75

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

pond had larger command area than Matsutani pond; therefore, strict water management was practiced
at Nanatani pond. The water manager at Nanatani pond usually opened the gate at 6 a.m. and closed at
6 p.m., and the water gate was closed when it rained. On the other hands, the water manager at
Matsutani pond usually kept the gate opened and the discharge was controlled twice a week during theirrigation period. Therefore, the water level of the pond decreased continuously at Matsutani pond
while the water level of the pond slowly decreased at Nanatani pond due to its strict water management.
As a result, hydroelectric power was continuously generated at Matsutani pond compared with
Nanatani pond. It shows that water management influences the pattern of hydroelectric power
generation.
Result of Field Experiment
A field experiment of a micro-hydroelectricity system was conducted at Yanaka irrigation pond in
Tottori, Japan. Electricity output was also continuously monitored in two weeks to examine thestability of output. Fig. 3 shows the results of field experiment. Stable output about 1.2 kW wasobserved during the first 10 days from February 1 to 10. Then the output decreased according to thelowering of water level in the pond.

(a) Nanatani
pond Park
Nanatani
PondHigashiyama(b) Matsutani pond
Fig. 2 Estimated power output at observed ponds, 2010 (Kusaka et al., 2011)(Discharge: 52 L/s, Generating efficiency: 45~50%)

Fig. 3 Power output of the field experimentⒸISERD76

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Usage of Generated Electricity
The usageof the electricity was also important since irrigation ponds in mountainous areas were distantfrom villages and had no electricity infrastructure. Consequently, the electricity generated at ponds
could not be readily used by villagers and farmers. In most cases, it was observed that the farm ponds
in mountainous areas were difficult to access. In addition, most of the water managers were aging, over
65 years old, and were having difficulty in maintaining farm ponds and their water management(Taniguchi et al., 2011). Using hydroelectric power to support the operation and maintenance anirrigation pond, replacing manpower, and fuel with electricity would be one of the best ways to to
generate electricity at a farm pond. Moreover, some water managers havd problems with illegal
disposal of cabbages into the ponds and illegal fishing by fishermen who deliberately discharged water
to lower the water level in the ponds for easier fishing. However, since the location of irrigation ponds
were far from the villages, water managers could not check the ponds often.

Pic. 1 Installation of an electric bulb
(Left: outlines of hydroelectric system)

Pic. 2 Outlines of the monitoring
systemPic. 3 View of a live camera throughsmartphoneⒸISERD77

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Considering those conditions, an electric bulb and monitoring system with water level sensor andlive view camera was installed. Through the monitoring system, water managers could check the waterlevel of their irrigation ponds and also watch the conditions of water intake and its surroundings
through a computer or smart phone if the internet connection was available. A monitoring system wasinstalled at Yanaka irrigation pond, which had a water level sensor and live view camera. Users could
check the water level and view of the irrigation pond through the internet connection. The system
required 200W for its operation.
Pictures 1, 2, and 3, show the electric bulb, monitoring system, and the view of irrigation pond
through smart phone, respectively.
CONCLUSION
Hydropower potential using irrigation pond was estimated. Estimated electric power output andelectric power were different at the ponds with similar storage capacity due to different water
management. Field experiment of siphon intake generation was also conducted and constant power
output was generated. Using hydroelectric power to support the operation and maintenance of a farm
pond, replacing manpower and fuel with electricity, would be one of the best ways to generate electricity
at a farm pond.
ACKNOWLEDGEMENTS
The authors gratefully acknowledge financial support from “Community Contribution Support
Activities”, Tottori University and technical supports from Tottori Institute of Industrial Technology
and Asahi Organic Chemical Industry Co. Ltd.
REFERENCES
Goto, M., Uchida, T., Kato, S., Okamoto, M., Oki, H., Hasegawa, D., Takaki, K. and Namihira, A. 2010.
Development of technology for small-scale hydropower generation on gently slope. Jounal of the JapaneseSociety of Irrigation, Drainage and Rural Engineering, 78 (8), 7-11. (in Japanese)
Ueda, T., Goto, M., Namihira, A. and Hirose, Y. 2013. Perspectives of small-scale hydropower generation using
irrigation water in Japan. Japan Agricultural Research Quarterly, 47 (2), 135-140.
Ueda, T., Goto, M., Namihira, A. and Hirose, Y. 2015. Water management strategies for hydropower annexation
at existing irrigation dams in Japan, Paddy and Water Environment ,13 (3), 229-240.
Kusaka, Y., Fukatsu, T., Kitamura, Y. and Shimizu, K. 2011. A study on potential of micro-hydropower
generation using irrigation ponds. Proceedings of Annual Meeting of The Japanese Society of Irrigation,
Drainage and Rural Engineering, 632-633. (in Japanese)
Agency for Natural Resources and Energy, Ministry of Economy. Trade and industry, Japan,
http://www.enecho.meti.go.jp/category/electricity_and_gas/electric/hydroelectric/database/energy_japan003/(in Japanese)
Ministry of the Environment, Japan. https://www.env.go.jp/earth/report/h25-05/05chpt5.pdf (in Japanese)
Taniguchi, M., Kitamura, Y. and Shimizu, K. 2011. A study on the actual management of farm ponds in theeastern part of Tottori Prefecture. Proceedings of Annual Meeting of The Japanese Society of Irrigation,
Drainage and Rural Engineering, 662-663. (in Japanese)ⒸISERD78

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Research article
erdAnalysis of Fiscal Gap and Financing of Cambodia’s Protected
Areas
SOMALY CHAN*
National Council for Sustainable Development/Ministry of Environment, Cambodia
Email: somalychan.ca@gmail.com
Received 16 December 2014

Accepted 15 July 2015(*Corresponding Author)

Abstract The Analysis of Fiscal Gap and Financing of Cambodia’s Protected Area (PA)conducted by the Department of International Conventions & Biodiversity, Ministry ofEnvironment (MoE), aimed to identify resource gaps in the management of 23 PAs of
Cambodia. The pressure & response indicators were used to analyze resource gaps. Pressure
indicators were population, number of visitors of each PA, roads, and hiking trails within PAs;
while response indicators included the number of full time staff and operational expenditure. To
examine resource gaps for PAs management, all PAs were classified into three clusters
according to the area size. The comparisons between pressure and response demonstrated trendsof existing resources for the management of PAs, therefore they were analyzed by pairingpressure and response indicator. To calculate resource gaps, two benchmarks were set for eachcluster: the average and the highest. Each PA resource gap was identified based on two rules: 1)
bringing the number of fulltime staff and operational expenditure that was below average to the“average benchmark”; 2) bringing the number of fulltime staff and operational expenditure thatwas higher than the average to the “highest benchmark”. As a result, the total gap of full time
staff in 2009 was 449 personals, equal to 1/3 of existing staff. However, the gap of full time
staff in this context did not take into account of their capacity to fulfill PA management tasks.
The total operational expenditure gap in 2009 was 1,221,405 USD, equal to 25% of thebenchmark estimation of 2,462,881 USD. In conclusion, for better management of 23 PAs, thebudget for PAs operation should be doubled; therefore it should be increased up to 2.5 million
USD per year.
Keywords fiscal gap, Cambodia, protected area, financing

INTRODUCTION
A 1993 degree of the Royal Government of Cambodia designated 23 Protected Areas (PA) comprising
approximately 18% of the total land areas of the country. Following IUCN (2004) categorization, thesePAs can be classified into National Park (7), Wildlife Sanctuary (10), Multiple-use Areas (3), andProtected Landscape (3). Through Royal decree (2001) and Declaration N.4010 (1999), one Biosphere
Reserve has been established and three Ramsar sites have been identified in addition to the 23 PAs.
Those PAs are managed by the General Department of Administration for Nature Conservation andProtection (GDANCP) of the Ministry of Environment by Law on Protected Areas 2008.
In addition, the Royal Government of Cambodia has designated 6 Protected Forests (PF), which
are managed by the Ministry of Agriculture Forestry and Fisheries (MAFF). The management ofProtected Forests is regulated under the Forestry law and relevant Royal Decree, Sub-Decree andDeclaration of the MAFF.
Each type of PA has a specific inclusion definition and a management objective. The managementof PAs has complied with the Royal Decree on the Creation and Designation of Protected Areas (1993),
the Law on Environmental Protection & Natural Resource Management (1996), the Law on ProtectedⒸISERD79

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Areas (2008), which define a framework of PA management, biodiversity conservation, andsustainable use of natural resources within PA. Other PA related legislations and regulations include
the Environmental Impact Assessment (EIA) sub-decree (1999), Biosafety reserve (2008), Forestry
Law (2002), Fisheries Law (2002), Royal Decree, Sub-Decree and Declaration, and other relevant laws.
Protected Areas is the main approach to biodiversity conservation in Cambodia. Data collection andinterview in 2012 by Department of International Convention and Biodiversity, it showed that 23
Protected Areas had residents within or around them; tourism activities, unsustainable use of natural
resources, illegal logging, wildlife trade, and insufficient resources, which were main challenges for
PA management. The resources for PA management are generally considered to be insufficient while
updated information and practical evaluation are lack to support the argument. This research finding
and recommendation options are expected for use by PA responsible institutions to increase budget andsustain finance for effective management of PA System in Cambodia.
OBJECTIVESThis paper aimed to identify the fiscal gap and financing needs for Cambodia’s Protected Area
management. The overall objective was to analyze the resource gaps in PA management. The research
was targeted for 23 Cambodian PAs under administration and management of the Ministry ofEnvironment (MoE). The data were analyzed based on setting internal and external indicators andrelevant criteria as appropriate. The findings of resources gaps and recommendations in filling thegapes by either increase national budgets and recruit more rangers or full time staffs are expected to be
used by PA responsible institutions for effective management of PAs in Cambodia.
METHODOLOGY
Research was conducted using both primary and secondary data/information collected from 23
Protected Areas established by Royal Decree in 1993. The data were collected directly from each PA’s
manager, key experts, relevant institutions, partners, stakeholders, and any available sources. Analysisof data collection, cluster classification, and benchmark identification were based on the following
methodologies:
Primary Data Collection and Surveys
A research questionnaire was designed in Khmer language for data collection from 23 PAs. It was
divided into four parts: part one focused on background information of PA including name, date ofestablishment, land area, location, IUCN’s classification, and its purpose; part two related to thephysical characteristics of PA such as access to PA, inhabitants of PA, travelling within PA, andfacilities available within PA; part three aimed to gather information on visitor characteristics such as
the number of visitors to PA, visitors entry fee, visitor accommodation fee, and activity fee; and partfour captured information on staffing revenues and costs, number of staff, staff capacity, operation
expenditure; fee collection, and annual revenues for an individual PA.
Secondary Data Collection
Some data could not be collected from the field. The research team directly communicated with
relevant institutions, local authorities, and international agencies through available contact persons
before sending official letters to request for cooperation in providing data. Data and information fromresearch projects, annual reports, census, materials from workshops and seminars were also collected.
ⒸISERD80

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Data Analysis
To analyze the Fiscal Gap for each PA, pressure and response indicators were identified. The pressure
indicators included population within 5 km radius, visitors, road, and hiking trail; while the number offull time staff and operational expenditures were identified as respond indicators. The analysis of
population focused on total population in the 5 most populated villages within a 5 km radius of theboundary; the less population caused less pressure on natural resources. The total operational
expenditure from government budget and other external sources supported some PAs’ activities.
The following methods were used to identify resource gaps: analysis pressures and respond, andset benchmark.
Response: This study selected the number of full time staff, and operational expenditures in 2009 as
response variable to assess the response to the pressure factors including: population, visitors, road,and hiking trail.
Benchmarking: According to size variance of PA and to maximize the accuracy of gap analysis, 23
PAs were classified into three clusters as follows:- Cluster 1: PA with total land areas of 0 ≤5,000 ha; 2 Pas- Cluster 2: PA with total land areas of> 5,000 ha ≤50,000 ha; 6 Pas- Cluster 3: PA with total land areas of> 50,000 ha ≤402,500 ha; 15 PAs
A benchmark of response indicators was identified for each cluster to analyze resource gaps, which
was carried out for full time staff (FTS) per 1,000 ha and operational expenditure (OpEx) per ha. The
average and highest indicators of FTS/1,000 ha and OpEX/ha within each cluster were used as
benchmarking tools to estimate gaps.
Resource GAPs: According to the method introduced by the Economy and Environmental Programfor Southeast Asia (EEPSEA, 2012), the following rules were applied for calculation resource gaps.
1. If the Number of Full-Time Staff & Operational Expenditure is lower than the average, bring thevalue of Full Time Staff & Operational Expenditure to the Cluster Average (Avr).
2. If the Number of Full-Time Staff & Operational Expenditure is higher than average in Cluster,
bring the value of Full Time Staff & Operational Expenditure to the Highest (Hst) value in Cluster.
The resource gap analysis was carried out by comparing existing resource allocation for PAs
management with averages & highest of individual clusters. The comparisons scenarios presented forlooking at how PAs were currently managed, and should stimulate discussion as any action was to betaken for further improvement.
RESULTS AND DISCUSSION
The Cambodia Protected Areas were divided into three clusters based on size: Cluster 1 was for PA
that had total land areas from 0 ≤5,000 ha; Cluster 2 was for PA with total land area from between
5,000 ha and ≤ 50,000 ha; while Cluster 3 was classified for any PA having land area more than 50,000
ha but less than or equal 402,500 ha (Table 1). Cluster 3 represented highest number of PA in theamount of 15 PAs out of 23 PAs. According to the data in Table 1, the average total land area in cluster
1 is 3,898 ha, cluster 2 is 28,004 ha, cluster 3 is 209,919, and Kulen-Promtep wildlife sanctuary has
highest total land area of 402,500 ha.
In 2009, 204,117 Cambodians visited 9 PAs: three national parks, three wildlife sanctuaries, one
protected landscape, and two multiple use areas. In the same year, 339,199 foreigners visited 10 PAs.
Therefore, the total number of tourists recorded in 2009 was 543,316 people. However, Bokor National& Phnom Kulen National Parks, and Ankor Multiple Use Area were not included in this analysis as theinformation on the number of visitors as these PAs could not be obtained as these were managed byother agencies and private companies.

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Table 1 Cluster and benchmark for full time staff and operational expenditure

No. PA in
Cluster

PA total area clustering
Cluster Interval (ha)Avr.Total Area(ha)

Full time staff (FTS)
Avr. No.
FTS

Avr. No.
FTS per
1000 ha

Hst No.
FTS per
1000 haTotal = 23
0 ≤ 5,000> 5,000 ≤ 50,000

26Highest = 402,500 ha
3,898
10.50
2.97
28,004
30.17
1.03

3.94
1.77

> 50,000 ≤ 402,500

15

209,919

0.52

45.93

0.25

Operation expend (OpEx)
Avr.
OpEx
(USD)

Avr
OpEx/ha(USD)

Lowest = 2795 ha
7,570
2.10
17,5760.60
74,7250.30

Hst OpEx
per ha
(USD)
2.67
0.94
1.24

According to interview information received from PA’s directors, deputy directors, rangers, andcommune chiefs, the revenue of each PA were through entry fees (0.25 - 0.75 for local visitors & USD
5 for foreigner), accommodation, and facilities such as boat rental, car park, guide fee, etc. Tourist
facilities and accommodation rates varied from PA to PA depending on customer demand. As the roadcondition of PA was not so good and far from the town, entry fees were lower, e.g. $0.12 per person.
Some PAs had additional charges for visitors to see rare species.
Response Indicators
Number of full time staff in 2009: The Ministry of Environment set up 32 offices and 78 sub-offices
around and within 23 PAs. For daily operations 891 full-time staff were employed by government towork in 23 PAs.
Operational expenditures in 2009: The operational expenditure for each PA including staff salary,
uniforms, and medicine were covered under the government budget. Other operational costs such as
project based activities supported by other donors. The total operation expenditures in 2009 for 23 PAs
was USD 1,241,476.
Pressure Indicators
Population of five largest villages within 5 km radius in 2009: The total population in the 5 largest
villages in a radius of 5 km from border of each PA was 347,625 people.
Roads and hiking trails: Roads & trails in each PA were constructed for filed monitoring recreationand ecotourism. Phnom Prich wildlife Sanctuary had the longest road (380 km), while Botum Sakor
National Park had more trails (1,750 km) compared to other PAs. On the other hand, for Roniem Daun
Sam Wildlife Sancturay, no road has been constructed and Preah Vihear Protected Landscape only has
a 4 km trail.
Response vs PressureThis research has compared pressure with response in pairs of: Population vs Full Time Staff;
Population vs Operational Expenditure; Visitor vs Full Time Staff; Visitor vs Operational Expenditure;
Road vs Full Time Staff; and Hiking Trail vs Full Time Staff. Road and Hiking Trail identified aspressures factors have elaborated in follow paragraph.
Population vs full time staff: According to data collection from all PAs (2009) the distribution of
population and full time staff in 1000 ha tended to have a positive association in general because themore population was the more full time staff were employed. In this regard, the high pressure by
population within 5 km radius in PAs had a response of higher number of full time staff, exceptⒸISERD82

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Angkor Protected Land Scape which had less full time staff (0.93/1,000 ha) in proportion to populationof 4,212.50 per 1000 ha compared to other PAs.
Population vs operational expenditure: The same source of data from directors and rangers in 23
PAs (2009) on the distribution of population and operational expenditure for 23 PAs resulted inpositive conditions. The results indicated that the greater the population was, the more staff were
employed for management. However, distribution of both factors in Prea Vihar Protected Landscape,Phnom Samkos Wildlife Sanctuary, and Kirorom National Park had more response and less pressure,especially Prea Vihea with operational expenditures of 1,533 USD per 1000 ha in 2009 with nopopulation within this PA. Besides, Angkor Protected Landscape had less resources in term ofoperational expenditures (470.09 USD/1,000 ha) to response with a high population of 4,212.50 per
1,000 ha.
Visitors vs full time staff: Only nine PAs recorded the number of visitors. The distribution ofpressures and response factors for visitors and full time staff was the focus for nine PAs that had data
available. The trend of Visitors vs Full Time Staff moved to a positive relationship although three PAs(Preah Vihea Protected Land Scape, Kirirom National Park, and Peam Krosop Wildlife Sanctuary) had
high pressure because of the number of full time staff did not fully respond to the number of visitors,
so it led to limited human resources for effective management in those PAs.
Visitors vs operational expenditure: The distribution of the number of visitors per 1,000 ha and total
operational expenditure per 1,000 ha in 23 PAs also had a positive trend. Distribution of visitors ranged
from 0 to 3,589 per 1000 ha, while operational expenditure had a distribution range from 82.27 USD
per 1,000 ha in Roniem Daun Sam Wildlife Sanctuary to 2,674.06 USD per 1,000 ha in Kep National
Park. In general, many distributions of both factors showed less pressure.
Roads v full time staff: Length of road per 1,000 ha had been considered as pressure factor for PA
management due to it was potential and easy for poacher to conduct illegal activities within PA.
Besides, it could be considered also as respond factor for PA manager or ranger to control otheractivities. Nevertheless, this study deliberated existing road, which PA was a pressure factor, but its
distribution tended to be positive respond. According to data in this study, there was two contrast
outliers at Angkor Protected Land Scape trended to have high pressure with road distribution in 13.80
km per 1,000 ha, and Kep National Park had high response within 4 full time staffs per 1,000 ha.
Hiking trails vs full time staff: Moreover, the length of hiking trails was also considered as pressure
factor. The results showed that almost of PAs had enough staff to patrol illegal activities if poachers
used only hiking trail.
Benchmarking
This study set benchmarks of full time staff/1,000ha and operational expenditure/ha at average andhighest points for each cluster, to estimate and calculate resource gaps with the above rules andmethodology. However, resource gaps of PAs management did not refer to the quality of full time staff
and sufficient financial resources for effective PAs management.
Resource GAPs
To estimate resource gaps, the number of full time staff/1,000 ha and operational expenditure/ha had
been identified as shown in Table 1. The serial number on horizontal axis in Figs. 1, 2, 3, and 4
represent each PA. The 7 National Parks are: 1- Kirirom, 2- Bokor, 3- Kep, 4- Ream, 5- Botum Sakor,
6- Phnom Kulen, and 7-Virachey; 10 Wildlife Sanctuaries are: 8- Phnom Aural, 9- Peam Krasop, 10Phnom Samkos, 11- Roniem Daun Sam, 12- Kulen Promtep, 13- Beng Per, 14- Lomphat, 15- Phnom
Prich, 16- Phnom Nam Lyr, and 17- Snoul; 3 Protected Landscapes are: 18- Angkor, 19- Banteay
Chmar, and 20- Preah Vihear; and 3 Multiple Use Areas are: 21- Dong Peng; 22- Samlaut; and 23Tonle Sap.
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Full time staff GAP: According to the average and highest benchmark of Full Time Staff (Table 1)
and data shown in Fig. 1, cluster 1 had only one PA below average and cluster 2 had four PAs below
and one PA above its average, while cluster 3 had eight PAs below and six PAs over average.
Therefore, Cluster 1 had 0.97/1,000 ha or approximately 5 (4.8) full time staff gap, cluster 2 had
1.47/1,000 ha or 42 full time staff gap and cluster 3 had 1.85/1,000 ha of 402 full time staff gap. The
calculation of full time staff gap in each PA was shown in Fig. 2. Among 23 PAs, only Tonle Sap
multiple use area and Phnom Aural wildlife sanctuary had high full time staff gap: 82 staff gap werefor Tonle Sap and 66 staff gap for Phnom Aural. For other PAs, the gap was between 0 to 45 staff. The
result of full time staff gap assessment indicated that an additional 448.55 staff needed to be employed
to the existing 891 staff to meet the benchmark of 1,339.55 staff. That means 1/3 of existing staff isrequired to recruit in addition.
Full Time Staff per 1000 Hectars for Each PA
4.00

Total Gap in Full Time Staff for Each PA

3.94
90.0
82.4

3.50

80.0

70.0

65.8

60.0

2.50

2.00

Staff Gap in PAs

Full Time Staff/1000 ha

Average for Cluster 1 = 2.97
3.00

1.77

1.50

Average for Cluster 2 = 1.03

50.0

44.8

40.0

35.6

22.9

22.4

20.4

1.00

28.7

28.3

30.0

21.0

19.1

20.0

15.2

13.7

Average for Cluster 3 = 0.25

0.52

0.50

10.0

1.2

0.7

-

7.9

7.0

5.8

4.8
-

0.9

-

-

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

1

23

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

Protected Area (PA)Protected Are (PA)Fig. 1 Full time staff / 1000 ha

Fig. 2 Full time staff gap in each PA

Operational expenditure GAP: The assessment of the financial gap was based on the annual budget(2009) for PA management of the Ministry of Environment. The funding for supporting PA
management received from Government was 40 person (equivalent to USD 499,515) and from otherexternal sources was 60 person (equivalent to USD 741,964). This amount of external sources
pertained to only nine PAs. There was not any donor’s funding included, as some portion was
undisclosed due to the confidential policy of the management. Therefore, this paper focused only
donor’s funding that worked with government or had a joint project through the Ministry ofEnvironment.
The operational expenditure for each PA included salary for full time staff, expenditure foruniform, medicine and conservation projects. The average and highest of operational expenditure foreach cluster are presented in Table 1. Figure 3 shows that cluster 1 had an average expenditure of USD
2.10/ha and the highest expenditure USD 2.67/ha, so the total gap was USD 2,853. In cluster 2,
operational expenditure in six PAs was not very diverse and was below the average, only Dong Pengmultiple use area was spending above the average. Therefore, the total gap for this cluster was USD
16,886. Besides, cluster 3 operational expenditure in 15 PAs was variance from one PA to another; and10 PAs were below the average, while 4 PAs were above the average. The total operational
expenditure for cluster 3 was USD 1,201,666. Total gap for each PA is shown in Fig 4. It articulated
that Kelen Promtep wildlife sanctuary had highest gap (347,092.7 USD) while Tonle Sap multiple use
was the second highest gap of operation expenditure in 2009. Phnom Prich wildlife sanctuary and
Botum Sakor national park also presented high gaps.
Total gap of operational expenditure in 2009 for 23 PAs was USD 1,221,405 approximate 50 percent
of benchmark estimation at USD 2,462,881. For better management of PA system in Cambodia,
operational fund should be increased to double of 2009 budget.
As the results of assessment, the resource gaps for full time staff & operational expenditure for 23
PAs are shown in Table 2.
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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Total Gap in Opera ng Expenditure for Each PA

Opera ng Expenditure per Ha in 2009
400,000.0

3.00

347,092.7

350,000.0

300,000.0

Average for Cluster 1 = 2.10

Opera ng Gap in PA (USD)

Opera ng Expenditure (USD)

2.50

2.00

1.50

1.00

255,550.6
250,000.0

194,393.2

200,000.0
162,857.7
150,000.0

100,000.0

Average for Cluster 2 = 0.60
0.50

Average for Cluster 3 = 0.30

50,000.0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

-

23

1

2

3

4

Protected Area (PA)

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

Protected Area (PA)Fig. 3 Operational expenditure per ha.

Fig. 4 Operational expenditure gap

Table 2 Resource gaps
Resources gap assessment

FTS (Number)

OpEx. (USD)

Existing resources (2009)

891.001,241,476

Estimated resources benchmark

1,339.55

2,462,881

Estimated resources gap

448.55

1,221,405

CONCLUSION
The resource gap analysis is reliant on data availability in setting indicators. The gap analysis is basedon the average and the highest full time staff per 1,000 ha and operational expenditure per ha in year
2009. The average and the highest for both indicators vary from cluster to cluster according to the sizeof PAs. Logically, the bigger size of the PA presents bigger number of full time staff and a bigger
operations budget. However, results of this study showed that the smaller PA size had the higher
average of full time staff, and the higher average of operational expenditure. It is more than double
expenditure compared with PAs which highest size.
Generally, PAs that had high resource gaps were from cluster 3 as this cluster had very wide gap
between the highest and above average. For cluster 1 and cluster 2 each PA was not much different gap
in terms of proportion.
The full time staff gap in this research did not taking into account the qualification of staff.
Therefore, this study focuses on quantity only. To assess the effectiveness of PA management, staff
quality should be considered as an important indicator and it should be considered for further research.
The protected area depending on the government budget was only able to support for staff salaries,
uniforms, and medicine. This budget is neither adequate for effective management nor to improve
facilities for resource mobilization. More than half of the total operational expenditure in 2009 received
from external sources, if this study could assessed more information on budgets of conservation
projects for PA management that supported and implemented by external partners, the figure ofoperation expenditure for 23 PAs would be increased.
In conclusion, to assess the resource gaps for effectiveness in PA management, gap of full time
staff should examine both quantity and quality, including skills & professional requirements, and othercriteria such as management plan, equipment, operation facilities etc. Without quality, motivation, andincentives, even if there are adequate staff, a successful or an effective PA management is notguaranteed. Although 1/3 of existing staff is required to fill the gap; or if existing staff can improvetheir capacity with well equippied facilities, there will be improvement in PAs management.

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ACKNOWLEDGEMENTS
The author would like to thank the General Department of Administration for Nature Conservation andProtection, MoE for authorization to conduct this research, and thank the research team of the
Department of International Conventions & Biodiversity for strong support in data collection. The
author acknowledges all stakeholders including PAs' directors and rangers who were involved andprovided information/data for this research. The author expresses her sincere thanks to Dr. Fermi
Fransisco, Director of the Economy and Environmental Program for Southeast Asia (EEPSEA) for thefinancial support to conduct this research. Finally, the author would like to give sincere thanks to Prof.
Dr. Machito MIHARA, Institute of Environmental Rehabilitation and Conservation, Tokyo Universityof Agriculture, for his support and professional guidance on this paper.
REFERENCES
Fransisco, F. 2012. The economy and environmental program for Southeast Asia.
IUCN. 2004. IUCN Protected Areas Categories System. (http://www.iucn.org).
Ministry of Environment. Annual budget for PA management in 2009. Cambodia.
Ministry of Foreign Affairs & International Cooperation, Declaration No.4010. 1999. Endorsement date for threeRamsar sites on the list of wetlands of international importance to the Ramsar Convention. Cambodia.
Preah Reach Kram, No NS/RKM//0208/007. 2008. The promulgation of the law on protected areas, The
management of protected areas shall be under the jurisdiction of nature protection and conservation
administration of the Ministry of Environment. Cambodia.
Preah Reach Kram, No. NS/RKM//0208/006. 2008. Law on biosafety. Cambodia.
Preah Reach Kram, No. NS/RKM/0802/016.2002. The promulgating of the law on forestry. Cambodia.
Preah Reach Kram, No. NS/RKM/0802/015.2002. The promulgating of the law on fisheries. Cambodia.
Royal Decree. 1993. The creation and designation of the protected areas, national park, wildlife sanctuary,
multiple use area and protected landscape. Cambodia.
Royal Decree. 2001. The establishment and management of Tonle Sap biosphere reserver. Cambodia.
Royal Kret NS/RKM/1296/36.1996. The promulgation of the law on environmental protection and natural
resource management. Cambodia.
Sub Decree. 1999. Ministry of Environment, the environmental impact assessment (EIA). Cambodia.

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Research article
erdBusiness Activities of “Transformed” Agricultural
Cooperatives and their Role in Supporting Local Agriculture
in Northern Vietnam
FUMIE TAKANASHI*
Hirosaki University, Aomori, Japan
Email: fumie-t@hirosaki-u.ac.jp
Received 31 January 2015

Accepted 20 July 2015(*Corresponding Author)

Abstract This study investigates the potential of “transformed” agricultural cooperatives innorthern Vietnam to support local agriculture as the market-oriented economy develops. Thiscase study approach examines four agricultural cooperatives introduced by the local
government. This study finds that, first, cooperatives try to provide agricultural support tomembers, but the private sector mainly leads this business. Second, the range of agricultural
cooperative business activities is expanding from production to livelihood support. Third, quite
a few cooperatives provide marketing support and began to direct production instead of selling
their members’ products in order to secure the quantities required to fulfill their contracts. The
results empirically indicate that cooperatives’ business activities has limited impact on local
agriculture or their members.
Keywords Vietnam, agricultural cooperatives, local agriculture, business activities

INTRODUCTION
The Vietnamese government began strengthening agricultural cooperatives’ (created by small holders)ability to operate in the market economy. First formed under Vietnam’s planned economy (similar to
China’s Model), the cooperatives have changed and lost their social role since the “Doi Moi” economic
reformed. A Cooperative law in 1996 forced them to choose between transformation into a new type ofcooperative serving their members according to International Co-operative Alliance (ICA) rules or
dissolution. In twenty years after the enforcement, there have been currently two types of agricultural
cooperatives. The first is the “transformed” cooperatives resulting from the 1996 law. The second is
newly established cooperatives formed after 1996. Transformed cooperative are multi-purpose
organizations organized around the community and based on regional relationships. Newly establishedcooperatives are organized based on members’ products, such as flowers, fruits, vegetables, fish,
livestock, and other single purposes.
Transformed cooperatives generally take over the organization, assets, activities, and businesses
from old cooperatives, which existed as politically controlled organizations. Accordingly, transformed
cooperatives are seen as nominal organizations, which business activities are diminishing. On the other
hand, after the transition, and particularly because of the new cooperative law established in 2003,
there is a clear lack of identity for such cooperatives. It is difficult to distinguish among limited
companies, charity organizations, and cooperatives. Aside from acceptance as a registered legal entity
as a cooperative member, cooperatives similar to a joint stock company are growing rapidly, especiallyin the South of Vietnam. Most cooperatives, in this case study, offer agricultural marketing output orbusiness efficiency, and are newly established. These are economically effective compared totransformed cooperatives, though they have lost the cooperative’s fundamental purpose.
Previous studies of agricultural cooperatives in Vietnam discussed changes in cooperative
functions after the Doi Moi reforms (Nghiem, 2006; Miyazawa, 2005). Trends or changes in activitiesⒸISERD87

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

at the provincial or national level were also studied (Wolz and Bao Duong, 2010; Trung, 2009). Some
researchers investigated the role of cooperatives in agricultural distribution and marketing (Moustier etal., 2010; Takanashi and Sakazume, 2013) and compared Vietnamese agricultural cooperative
characteristics with those in Japan (Dung, 2010). These studies concluded that most agricultural
cooperatives worked mainly on irrigation management, assisted with starting difficult new businesses
to address the shortage of capital, and human resources. Most transformed cooperatives had
economically stagnated while new cooperatives achieved good economic performance. However,Miyazawa et al. (2005) argued that agricultural cooperatives maintained some security for theirmembers by maintaining the traditional rural community and working as a mutual cooperative, evenafter Doi Moi, and emphasized the importance of “transformed” cooperatives.
Transformed cooperatives organized around rural communities have the potential to coordinate tocounter the power of capital, support small holders’ livelihoods, and the local subsistence agriculturethat is the foundation of food security and an important part of the socio/economic/ecologicallandscape (FAO, 2013). Although previous studies mainly focus on efficiency in developing
commercial agriculture or cooperatives’ economic performance, few researches emphasize on how
agricultural cooperatives support local agriculture through their business activities.
OBJECTIVE
The main objective of this research is to examine the potential for “transformed” agricultural
cooperatives to support local agriculture and members as the market-oriented economy deepens.
METHODOLOGYThis study takes a case study approach to explore the trends in business activities of northern
Vietnamese “transformed” agricultural cooperatives. In-depth interviews were undertaken with four
agricultural cooperatives in Hanoi and Hai Duong provinces between November 2012 and January
2013 with the heads and management boards of each cooperative. They were asked about theirbusiness activities, how they started each business, and the businesses’ management systems. The
cooperatives were introduced to the researchers by the Department of Agriculture and Rural
Development in Hanoi and Hai Duong provinces, in accordance with the study purpose. This paper isorganized as follows. The next section provides general statistical data for current Vietnamese
agricultural cooperatives, as background information. The subsequent section presents the main results
and a discussion of the field research. The paper then concludes with findings and implications.
RESULTS AND DISCUSSION
Current Status of Agricultural Cooperatives in Vietnam
Cooperative sector and agricultural cooperatives: Table 1 summarizes the number of cooperatives
and agricultural cooperatives in Vietnam by type and industry sector in primary production. Vietnam
has 14,500 cooperatives, of which 44% are agricultural. The Red River Delta has a relatively highnumber of cooperatives, as 62.4% of all cooperatives are agricultural, and almost half are of thetransformed type. A high number of cooperatives are located in the North part of Vietnam. However,the new type of cooperatives tends to be established in southern Vietnam. Previous studies show thatthe most popular activity or business for agricultural cooperatives is irrigation, carried out by 73.4% of
agricultural cooperatives (Table 2). This is because most transformed cooperatives maintain irrigation
canals taken over from the old cooperatives and hold as a fixed asset. Technical extension comes andⒸISERD88

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

42.0% of agricultural cooperatives providing these services is usually done through collaboration with
the District Office of the Department of Agriculture. Providing electricity (38.5%) is the third highest
activity. Marketing output considered as the most expected activity from an agricultural cooperative
accounts for only 1.8%, so only a limited number of agricultural cooperatives engage in this business.
Table 1 Cooperatives in Vietnam (2008)
Total

Newly
establishedTransformed

By Industrial sector(primary production)
Agriculture
Forestry
Fishery6374.0
59
200

Total

14,500

5,742

8,149

Red River Delta
North- East
North-WestNorth-Central
Central coast
Central highland
North-east

5,059
2,628
604
2,754
985
490
834

2,926
385
123
1,051
719
87
306

1,857
2,214
402
1,612
245
380
505

3155.0354.0
190.0
1462.0
527.0
136.0
109.0

9
17
3
11
4
9
3

26
57
11
18
13
3
13

Mekong Delta

1,146

145

934

439.0

3

59

561

335

218

274.0

Hanoi city

3

Ha Tay**
672
468
115
519.0
1
Hai Duong
701
183
475
318.0
3
* “To Hop Tac” (Farmer’s Group) is a voluntary association of farmers without cooperate personality**Ha Tay province is absorbed by Hanoi city
Source: Ministry of Planning and Investment (2009)

1
5

Table 2 Agricultural cooperatives’ business activities by region (2005)

153
15
58
4
9
11
28
13

Supplyingelectricity
3201
1696
348
20
660
418
31
19

Agriculturalextension
3492
2019
307
97
608
263
56
37

316

15

9

-

-

-

Total

Irrigation

MarketingTotal
Red River Delta
North- East
North-WestNorth-Central
Central coast
Central highland
North-east

8322
3463
1010
305
1591
707
200
282

6106
3047
627
180
1124
636
69
107

Mekong Delta

764

Ha Noi (2012)

958

CreditOthers

770
100
67
9
124
327
24
54

4331
2560
324
117
997
191
62
51

105

65

29

-

-

-

Hai Duong (2011)
349
315
4
0
27
0
- : no data
Source: data by region: Nghiem (2006), Data for Hanoi: DARD Hanoi (2012), Data for Hai Duong: DRD, Hai
Duong (2011).

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Outline of sample cooperatives: The four sample cooperatives are of the transformed type, which
each includes 2-4 communes; so there is a relatively large number of cooperatives (888 for A, 1,680 for
B, 2,440 for C, and 1,457 for D). A and D cooperatives can secure some government land for housing
and industrial use because these cooperatives are located close to the center of Hanoi or Hai Duongprovinces. A cooperative lies along the dike of the Red River, an area that traditionally suffers fromfrequent floods. It is recognized as a disadvantaged production area. However, Hanoi city approves A
cooperative as a safe vegetable production and marketing cooperative and the city has invested inirrigation. Consequently, safe vegetable production is rapidly growing, especially for leafy vegetables
as this area has good access to the center of city. B cooperative is 18 km from the center of Hanoi andis strongly influenced by urbanization though it maintains the traditional production system dominatedby rice. C cooperative is located between Hanoi and Hai Duong city. D cooperative is between Hai
Duong and Hai Phong city. As many industrial zones have been constructed, there is an outflow offarm labor, and the number of part time workers has significantly been increased.
Previously, new members without cultivated land in a cooperative’s jurisdiction could not join atransformed cooperative, and these cooperatives did not accept capital injection from members. B andC cooperatives revised their constitutions to solicit new members in 2008, and 38 and 43 new members
were registered for B and C. The cooperatives pay dividends to these new members based only on theircapital contribution invested in the cooperative’s operations.
Additionally, business activities for daily support are growing, especially in the two cooperatives
in Hanoi city. Agricultural cooperatives pick up garbage, supply household water, manage consumer
markets in the commune, and subcontract construction. Table 4 shows that these activities provide alarge percentage of total business profit.
Business Activities of Transformed Agricultural Cooperatives
Overall business direction: Table 3 shows the sample cooperatives’ current business activities. Most
are engaged in irrigation, technical extension, pest extermination, purchasing inputs, and distribution ofelectricity, which they continue from the old cooperatives. In terms of agricultural production, thesecooperatives begin contracting agricultural work such as plowing by tractor, agricultural production,and marketing after the transition.
Table 3 Business activities of sample CooperativesⒸISERD

90○○

ConStruc-tion

Management ofmarket

▲
○

Water

A ○
○
○
○
○
○
B ○
○ ○
○
●
○
○
C ○
○ ○
○
○
○
D ○
(seed)○○○
Shaded activities are taken over from old cooperatives*cooperatives’ own farm. Cooperatives manage the farm as their business▲ Until 2011 (from 2011, People’s committee undertaking）● From 2012, started on a trial basis
Source: Field Research (2011-2012

Garbage pickup

Electricity

MarketingGroup purchase

Production*

Daily life support

Plowing

Pest
Exterminati
on

Plant
protection

Extension

Irrigation

Agricultural production
Support for agricultural
work○

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Table 4 Annual profit and rate by business activity
Construction

Garbagepickup

ElecTricity

Grouppurchase

Marketing(mil. VND)

Production

Veterinary

ProfitPlant
protection

Total
revenue

Irrigation

Rate by business activities

50.0
-

12.0
-

(%)

A
NA
750
10.0
30.0
10.0
B
10,012
373.4
3.0
75.0
C
1,292
4.09
49.7
48.8
0.4
1.0
D
0
-0.1
Whole
1,011
833
country
Hanoi
950
70
Hai
491
11
Duong
**including all cooperatives (not only agricultural cooperatives)** - = no benefit, space=no data
Source: Field research (2011-2012), MPI (2009), DARD Hanoi (2012), DRD Hai Duong (2011）

10.0-

Support for Agricultural Production: Plowing
Of the cooperatives, three of them contract plowing by tractor. However, B and C cooperatives do not
own a tractor, and so coordinate and mediate contracts between members and a contractor.
Contractors are usually a local group with members contributing capital that own a tractor. Eachcommune has several groups with contracting services that cooperatives coordinate, so all members
have equal access to the service. Cooperatives determine contracting needs through board members or
the heads of internal groups before plowing season, then negotiate prices with a contractor, allocate andrequest the work. Once complete, the cooperatives collect bills from each farmer and settle thepayment. Contract fees are presented for consideration before a general meeting of cooperative
representatives to ensure that the price is reasonable. B cooperative does not take commission for thiswork.
C and D cooperatives, which do not have enough contractors in their commune to provide
plowing services to all households, make an effort to meet members’ needs. For these cooperatives,
members’ demand for plowing service has increased with the development of contractors inneighboring communes. C cooperative has started its contract plowing service since it received
government financial support in 2008 to purchase three tractors. Now, two board members are engaged
in this business, and the cooperative has hired six operators. Accordingly, these groups can plow all
agricultural lands in the commune.
D cooperative also lacks the contractors to meet members’ demand and considers purchasing
tractors. Though the cooperative cannot follow through the plan, it is unable to obtain a loan orgovernment support. As a result, six board members, managers of the cooperative, executive membersof the People’s committee, and farmer’s union together capitalized on this new business by purchasing
three tractors, which are owned and managed by the cooperative. The six invested members canreceive dividends when this business earns a profit.
Support for Agricultural Production: Marketing and Production
Among the four cooperatives, only A cooperative markets agricultural outputs. A and B have begun
cooperative farm management and production on a trial basis.

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Since Hanoi city was selected as a safe vegetable production area in 1999, A cooperative hasarranged contracts with supermarkets and venders for school meals since 2003. It is to provide a stable
distribution outlet for members’ products. It has become difficult to secure enough supply to meet thecontract amounts in terms of quality and assortment because agricultural labor is declining as thenumber of farm households. A cooperative opens the cooperative’s land by leasing land from members
and hiring labor. Some of the cooperative’s farms are used as experimental fields for new agricultural
techniques.
B cooperative has started producing and marketing seed potato since 2012. The cooperative
provides training and information for all members, and 14 interested members invest to hire labor andlease 3 ha of agricultural land to produce seed potato. All products from this field are sold to othercooperatives through B cooperative, which will consider investing in cold storage if more members
participate in this business in the future.
CONCLUSION
Transformed agricultural cooperatives took over the business and activities from old cooperatives. The
cooperatives have recently expanded their activities to include daily life support. Quite a few
cooperatives market their agricultural outputs. Some of the cooperatives distribute agricultural products
due to changes in the local agricultural production structure. Cooperatives have now become a businessorganization and a competitor to small households.
The consumer market is scattered, as the population has not yet concentrated in Vietnam’s big
cities. Additionally, agriculture in Vietnam is traditionally very small and multi-item production, so it
is still not specialized and geographically concentrated. Under these conditions, it is difficult forcooperatives to organize marketing by taking advantage of scale, especially in urban neighborhoods.
Marketing support through other means, as supporting farmer’s markets, might be required in the
future. Due to structural changes in the business sector and an outflow of labor, demand for agricultural
production support is expanding. Most agricultural cooperatives act as intermediaries between
contractors and members, though farmers’ groups usually lead this business rather than the cooperative.
However, contractors who can not provide services to meet members’ demand for contract work havestarted to provide plowing services as their own business. This kind of effort will be important tomaintain local agriculture.
There are three basic trends in cooperatives’ business activities. First, the private sector mainly
leads agricultural support. Second, business has expanded to include daily life support. Third, many
have begun to own land; and because of coming from the same background, they have suffered from a
serious capital shortage. All agricultural cooperatives have tried different means to earn active capitaland profits. Under existing conditions, transformed cooperatives have prioritized keeping profits frombusiness activities for the cooperative itself rather than for its members, so these business activities
have limited impact on members or local agriculture.
There are several limitations to this study. The sample consists of cooperatives located in only two
provinces, which are too small to draw conclusions about the entire cooperative movement in Vietnam.
Future studies can explore some of the issues identified in this study by using a larger sample of“transformed” agricultural cooperatives.
ACKNOWLEDGEMENTS
This work is supported by the JSPS “Institutional Program for Young Researchers Overseas Visits.”ⒸISERD92

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

REFERENCES
Department of Agriculture and Rural Development (DARD). 2012. Planning report for economic development in2013. (in Vietnamese). Hanoi, Vietnam.
Department of Rural Development (DRD). 2011. Report on the status of the direction and measures to promote
the development of agricultural cooperatives in the new economic phase. (in Vietnamese). Hai Duong,
Vietnam.
Dung, N.M. 2010. A comparative analysis of business activities of agricultural cooperatives between Japan and
Vietnam. J of Soc. Dev, 8 (Eng. Iss.2), 163-174. Hanoi University of Agriculture.
FAO. 2013. Investing in smallholder agriculture for food security, A report by HLPE.
Hai, T.M., et al., 2013. Current status of agricultural cooperatives in the Mekong Delta, Vietnam, Jpn. J. of Agric.
Mark., 22 (1), 67-74.
Ministry of Planning and Investment (MPI). 2009. The status of cooperatives in our country. (in Vietnamese)
Miyazawa, C. 2005. The relationship between culture and economic development in the Red River Delta,
Northern Vietnam., Miyazawa Chihiro edu. Culture and Sociology in Asian Markets, Hukyo-sha. 191-217.
(in Japanese)
Moustier, P., Tam, P.T.G., Anh, D.T., Binh, V.T., and Loc, N.T.T. 2010. The role of farmer organizations in
supplying supermarkets with quality food in Vietnam. Food Policy, 35, 69-78.
Nghiem, N.V. 2006. Agricultural cooperatives in Vietnam, In Proc. of Semin, Agricultural Cooperatives in Asia:
Innovations and Opportunities in the 21st Century. Seoul, Korea.
Takanashi, F. and Sakazume, H. 2013. Safe vegetable marketing and role of agricultural cooperatives in northern
Vietnam. Jpn. J. of Food, Agric. and Resour. Econ., 64 (1), 19-128. (in Japanese)
Trung, T.P. 2009. Agriucltural cooperatives in Vietnam, VDM Verlag Dr. Muller.
Tu, N.M. 2011. Cooperative development in Vietnam, Success and challenges. UN Expert Group Meeting on
Cooperatives in Social Development, Ulaanbataar, Mongolia.
Wolz, A., and Bao Duong, P. 2010. The transformation of agricultural producer cooperatives, The case ofVietnam. J. of Rural Coop., 38, 117-133.

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Research article
erdFloristic Inventory of the Proposed Site for Tarsier Tourism
Center in Villa Aurora, Bilar, Bohol, Philippines
TOMAS D. REYES, JR.*
Bohol Island State University, Bohol, Philippines
Email: tomseyer@yahoo.com, tomseyer@gmail.com

JERALYN B. ABADINGO
Bohol Island State University, Bohol, Philippines

SHIELA G. TABUNO
Bohol Island State University, Bohol, Philippines

EUNICE KENEE L. SERIÑO
Bohol Island State University, Bohol, Philippines

JOECEL B. MABANAG
Bohol Island State University, Bohol, Philippines

RIZALDY C. MERCADAL
Bohol Island State University, Bohol, Philippines
Received 3 March 2015

Accepted 27 August 2015(*Corresponding Author)

Abstract. The study assessed the present vegetation composition of the proposed site for theTarsier Tourism Center (PTTC) at Villa Aurora, Bilar, Bohol and performed comparative
analysis with the existing Tarsier Sanctuary (TS) at Canapnapan, Corella, Bohol. The bases forcomparison were the computed importance values, species richness, species dominance, andpercent distribution of plants according to self-defined diameter at breast height DBH classes.
Results showed that both sites had very high species richness and evenness values. Common
overstorey and understorey plant species found in both areas were katagpo (Psychotria sp.),sagimsim (Syzygium brevistylum [C.B. Rob] Merr.) and bagauak (Clerodendrum minahassae
Teijsm. & Binn.). Apart from sagimsim (S. brevistylum [C.B. Rob.] Merr.), selaginella(Selaginella cuppresina Lin.), and lunas (Lunasia amara Blanco) were also common in the
ground vegetation of both areas. Percent distribution of trees according to self-defined DBH
classes revealed that PTTC had 87.55% of the total recorded plants with DBH measurements of<10 cm. This was found lower by almost 10% from TS. Considerable percentages of trees werealso shared in other DBH classes for PTTC. DBH class range of 10-20 cm had 6.88%, while
5.58% was computed for DBH class of >20 cm. Percent distribution of trees on these DBH
ranges (especially on DBH class >20 cm) indicated the presence of medium and large trees. The
largest DBH measured in PTTC was 70 cm, while in TS was only 22 cm. Based on the findingsof the study, it has been concluded that the proposed 10-ha site in Villa Aurora, Bilar is suited tobe utilized as Tarsier Tourism Center. In case the proposed project is to be pursued, enclosure
similar to what has been constructed in Canapnapan, Corella, Bohol, Philippines should also beestablished to prevent stray animals from predating the captive tarsiers.
Keywords floristic inventory, Philippine tarsier, BoholⒸISERD94

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

INTRODUCTION
The Philippine tarsier (Carlitos syrichta (L.) Shykelle) has attracted a lot of attention of scientists andcollectors because of its interesting physical features and habits. It is often fancied as a crossbreed of abat and a rat. The name “tarsier” is derived from the fact that the tarsal region is elongated, a trait ofboth tarsiers and gala goes (Embury, 1994 as cited by Villamor, 1995). Its size is not bigger than two
fists held together. Undeniably, the Philippine tarsier, with three subspecies: syrichta, fraterculus andcarbonarius, is one of the smallest among the different known species (Goodwin, 1991; Embury, 1994
as cited by Villamor, 1995; Neri-Arboleda, et al., 2002). This trait and its rarity status would be thereason why this creature is on the CITES endangered list. It was once then considered as “lower risk
conservation dependent” based on the IUCN 2004, then became “data deficient” in 2006, and now
under the “near-threatened” category since 2008.
The Philippine tarsier habitats are primarily located in secondary lowland rainforest of early- to
mid-succession stage (Neri-Arboleda, et al., 2002; Reyes, 2006). In Bohol, it generally occurs in hilly
areas with patches of second-growth forest (PAWB-DENR, 1992; Lagapa, 1993; Villamor, 1995;
Reyes, 2006), bushes, bamboos, palms and some grasses (Karnain, et al., 1997 as cited by Reyes,2006). The short trees, as well as bamboos, are good for the arboreal adaptation by the tarsiers. The
dense nature of the undergrowth supports a wide variety of insects and small vertebrates which arevital to the survival of tarsiers. The close distance in between small diameter trees, on the other hand,appears to be a necessary condition which favors the locomotive behavior of tarsiers thus enablingthem to have a firm grasp of the small trunks and branches making this type forest a favorable place tolive (Villamor, 1995; Karnain, et al., 1997 as cited by Reyes, 2006). It is also found in abandoned
clearings with signs of new growth of medium-high plants in lands of both low and medium elevations(Hoogstraal, 1947). These types of clearing were believed to be the tarsier’s feeding sites (Rabor, 1977;
Villamor, 1995) until they were disproved by Neri-Arbodela et al., (2002).
Habitat characterization of the Philippine tarsier has been conducted in Bohol by several local
researchers and research institutions (Madulid [undated]; PAWB-DENR, 1992; Lagapa, 1993;
Villamor, 1995; Neri-Arboleda, et al., 2002; Reyes, 2000, 2006; and ERDS, 2009). Among the
researchers, Neri-Arboleda, et al., (2002) and Reyes (2006) provided detailed discussions on several
habitat classifications. Reyes (2006), in particular, described 11 variants of the tarsier’s roosting
territories based on species composition and thicket structure. He also correlated the presence oftarsiers and its scent-markings on abundance of small diameter plants in his study sites. The findings ofthe study of Reyes (2006), on this aspect, were used as the basis in evaluating the suitability of
proposed Tarsier Tourism Area in Villa Aurora, Bilar, apart from the usual species richness anddominance assessment.
The study assessed the present vegetation composition of the proposed tarsier tourism site at Villa
Aurora, Bilar, Bohol, Philippines and compared with the existing tarsier sanctuary at Canapnapan,
Corella, Bohol, Philippines in terms of plant species composition.
METHODOLOGY
Study Site
The Proposed Tarsier Tourism Center (PTTC) is planned to be established at barangay Villa Aurora in
the municipality of Bilar. The total area of the proposed tourism site is 10.194 ha (CENRO-Tagbilaran,2013). It is located along the stretch of the prominent winding road of barangay Villa Aurora, akilometer away from the famous Bilar-Loboc Man-made Mahogany Plantation. This will serve as anextension of the 6-ha Tarsier Tourism Area established at Upper Bonbon, Loboc, Bohol, Philippines.

ⒸISERD95

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

The Tarsier Sanctuary and Conservation Site (TS), on the other hand, which is used forcomparison is situated at barangay Canapnapan in the municipality of Corella, Bohol, Philippines. This
134-ha conservation site is managed by the Philippine Tarsier Foundation Incorporated (PTFI) and isopen to public, since 1990s, for recreation and research.
Field Data Collection
Quadrat sampling was used in the collection of data. Twenty quadrats were established preferentiallywithin the 10-hectare PTTC in Villa Aurora, Bilar. The 10 m x 10 m plots were laid selectively on
thickets of small diameter trees and shrubs which could be identified as potential roosting sites of thePhilippine tarsier. All plants with diameter at breast height (DBH) of > 1 cm were recorded. Small
nested subplot with a dimension of 1 m x 1 m was also established at the middle of each plot tofacilitate the identification of the ground vegetation.
For comparative analysis, 10 plots and subplots were also established at TS in Canapnapan,
Corella. The first five plots and subplots were laid in the PTFI tarsier enclosure where visitors areallowed to enter and see the captive tarsiers, and the remaining plots and subplots were laid outside theenclosure, about 30 m away from the PTFI building.
Data Analysis
Analysis of data was mainly concentrated on the determination of species abundance parameters suchas density, frequency, and dominance values of each plant species. These parameters were used in thecalculation of importance value (IV) of all encountered plants in the overstorey, understorey, andground vegetation. IV is a measure of species abundance in an area. It is the summation of the relativevalues of density (number of species per unit area), frequency (number of occurrences of species
relative to the number of plots established), and dominance (basal area of species relative to the total
computed basal areas).
For the purpose of comparison of the two sites, species richness and dominance indices likediversity (Shannon-Wiener diversity index), evenness (Evenness index), and dominance (Simpson’s
index) were computed based on IV. The Shannon-Weiner diversity index assumes that individuals
were randomly sampled from an indefinitely large population and also assumed that all species wererepresented in the sample. Evenness index, on the other hand, is the ratio of observed diversity tomaximum diversity, while Simpson’s index is the probability of any two individuals drawn at random
from an infinitely large community belonging to same species.
Density of plants, in percent (%), on each pre-defined diameter class was also calculated toevaluate the suitability of the proposed site for tarsier conservation as the project proponents (wildlife
permitees from Loboc) claimed its very purpose. This was based on the work of Reyes (2006) who
tested the relationship of DBH to the number of tarsiers seen in the wild. DBH classes used in thisstudy were: <10 cm; 10-20 cm; and >20 cm.
Formulas used in this study and presented below were adopted from Gruezo (1997), Fernando etal., (1998), Reyes (2000, 2006), and ERDS (2009).
For Tree and Shrub Layer:
Density = total number of individuals of a species/unit area
Relative Density = density of a species/total densities X 100
Dominance = basal area of a species/total area sampled
Relative Dominance = dominance of a species/total dominances X 100
Occurrence = number of times a species appeared/total number of established plots X 100
Frequency = number of occurrence of a species/total number of occurrences X 100
Relative Frequency = frequency of a species/total frequencies X 100
Importance Value = Relative Density + Relative Dominance + Relative FrequencyⒸISERD96

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

For the Understorey Plants and Grasses (weeds and broadleaves):
Species Dominance = Cumulative crown cover (%) of a species
For the Diversity and Evenness Indices:
Shannon Diversity (H’) = -∑ pi * (LNpi) where pi = species proportion
Evenness Index (E) = H’/ LN(s)where s = number of species
RESULTS AND DISCUSSION
Vegetation Composition
Overstorey and understorey plants: A total of 112 species of overstorey and understorey plants wereidentified in the PTTC at Villa Aurora, Bilar. These belonged to 82 genera under 44 families (Fig. 1).
The recorded plant species and genera in PTTC were roughly twice than those in TS. Tables 1 and 2
show the summary lists of common overstorey and understorey plants in both areas. From the list in
Table 1, the first three most common species were katagpo (Psychotria sp.), bayukbok (Elaeocarpus
macranthus Merr.), and langin (Micromelum caudatum Merr.) based on the computed IV of 28.96,
10.94, and 10.62, respectively. The three most common species in Table 2, on the other hand, werealabihig (Arthrophyllum diversifolium Blume), tagoang uak (Croton leiophyllus Muell.-Arg.), andkatagpo (Psychotria sp.) with IVs of 29.70, 19.91, and 19.77, respectively.
As shown in Tables 1 and 2, the species of plants which were found in both areas, apart fromkatagpo, were sagimsim (Syzygium brevistylum (C.B. Rob.) Merr.) and bagauak (Clerodendrum
minahassae Teijsm. & Binn.).
There were also 52 species, 43 genera, and 35 families of ground vegetation in the PTTC. Samewith the overstorey and understorey vegetation, its ground cover was more than twice species rich thatthe recorded ground vegetation in TS. Table 3 presents the summary list of common plants species
identified on the ground based on the number of individuals. The most common species recorded withmore than 30 individuals each, in decreasing order, were sagimsim (S. brevistylum [C. B. Rob.] Merr.),
selaginella (Selaginella cuppresina), and lunas (Lunasia amara Blanco). These species were also listedcommon in TS, as shown in Table 4.

Fig. 1 Bar graph showing the taxonomic information of the Proposed Tarsier Tourism Center,
Villa Aurora, Bilar and Tarsier Sanctuary, Canapnapan, Corella, Bohol, PhilippinesⒸISERD97

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Table 1 List of common overstorey and understorey plants arranged based on importancevalues (IV) in PTTC, Villa Aurora, Bilar, Bohol, Philippines
Common Name

Scientific Name

Family NameIV

KatagpoPsychotria sp.

Rubiaceae

28.96

Bayukbok

Elaeocarpus macranthus Merr.

Elaeocarpaceae

10.94

LanginMicromelum caudatum Merr.

Rutaceae

10.62

Sagimsim

Syzygium brevistylum (C. B. Rob.) Merr.

Myrtaceae

9.89

Paginga

Discocalyx cybianthoides (A. DC.) Mez.

Myrsinaceae

7.80

Katong matsin

Chisocheton pentandrus (Blanco) Merr.

Meliaceae

7.18

Bagauak

Clerodendrum minahassae Teijsm. & Binn.

Lamiaceae

6.98

BatinoAlstonia macrophylla Wall. ex DC.

Apocynaceae

6.72

Malak-malak

Palaquium philippense (Perr.) C. B. Rob.

Sapotaceae

6.52

Big-leaf mahogany

Swietenia macrophylla King.

Meliaceae

6.44

Aniam-gubat

Antidesma subolivaceum Elm.

Euphorbiaceae

6.35

Malaikmo

Celtis philippensis Blanco

Ulmaceae

6.05

Talang gubat

Diospyros copelandii Merr.

Ebenaceae

5.79

AlahanGuioa koelreuteria (Blanco) Merr.

Sapindaceae

5.74

Lunas

Lunasia amara Blanco

Rutaceae

5.62

DuguanMyristica philippensis Lam.

Myristicaceae

5.51

Palosapis

Anisoptera thurifera (Blanco) Blume

Dipterocarpaceae

5.23

Table 2 List of common overstorey and understorey plants arranged based on importancevalues (IV) in TS, Canapnapan, Corella, Bohol, Philippines
Common Name

Scientific Name

Family NameIV

Alabihig

Arthrophyllum diversifolium Blume

Araliaceae

29.70

Tagoang uak

Croton leiophyllus Muell.-Arg.

Euphorbiaceae

19.91

KatagpoPsychotria sp.

Rubiaceae

19.77

Sagimsim

Syzygium brevistylum (C. B. Rob) Merr.

Myrtaceae

19.50

Balinghasai

Buchanania arborescens Blume

Anacardiaceae

18.30

Bagauak

Clerodendrum minahassae Teijsm. & Binn.

Lamiaceae

14.04

Matang arau

Melicope triphylla (Lam.) Merr

Rutaceae

13.74

Takip asin

Macaranga grandifolia (Blanco) Merr.

Euphorbiaceae

10.08

Sudiang

Ctenolophon philippinense Hallier F.

Linaceae

8.19

Mussaenda sp.

Rubiaceae

8.01

Niog-niogan

Ficus pseudopalma Blanco

Moraceae

7.93

Pandan gubat

Freycinetia sp.

Pandanaceae

7.83

Kubi

Artocarpus nitida Trec. subsp. nitida

Moraceae

6.77

MolaveTambo

Vitex parviflora Juss.
Thysonolaena latifolia (Roxb. ex Hornem.)
Honda

Lamiaceae

5.66

Poaceae

5.23

Ficus sp.

Moraceae

5.14

Ficus

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Table 3 List of common plants species comprising the ground vegetation arranged based on
the number of individuals in PTTC, Villa Aurora, Bilar, Bohol, Philippines
Common Name

Scientific Name

Family Name

Individuals

Sagimsim

Syzygium brevistylum (C. B. Rob.) Merr.

Myrtaceae

53

Selaginella

Selaginella cuppresina

Selaginellaceae

40

Lunas

Lunasia amara Blanco

Rutaceae

38

Flacourtia sp.

Flacourtiaceae

27

LanginMicromelum caudatum Merr.

Rutaceae

22

Tubli

Derris sp.

Fabaceae

20

Paginga

Discocalyx cybianthoides (A. DC.) Mez.

Myrsinaceae

17

Takipan

Caryota rumphiana Mart. var. philippinensis Becc

Arecaceae

11

White nato

Pouteria macrantha (Merr.) Baehni

Sapotaceae

11

Table 4 List of common plants species composing the ground vegetation arranged based on thenumber of individuals in TS, Canapnapan, Corella, Bohol, Philippines
Common Name

Scientific Name

Family Name

Individuals

Sagimsim

Syzygium brevistylum (C. B. Rob) Merr.

Myrtaceae

49

Selaginella

Selaginella cuppresina

Selaginellaceae

40

LanginMicromelum caudatum Merr.

Rutaceae

27

Tagpo

Ardisia squamulosa Presl.

Myrsinaceae

15

Nino

Morinda bracteata Roxb.

Rubiaceae

10Species Richness and Dominance
The results of species richness and dominance computations (Fig. 2) revealed that both sites were
species rich given by Shannon-Weiner diversity index values of 4.26 for PTTC and 3.56 for TS.
According to Fernando et al., (1998), diversity index values above 3.5 are considered very high. Valuesof the dominance indices such as evenness and Simpson’s dominance index also supported this finding.
Evenness value of almost 1.0 (0.9031 for PTTC and 0.9012 for TS) means that the observed (orcomputed) diversity value is almost equal to the expected maximum diversity value (Gruezo, 1997;
Fernando et al., 1998; Reyes, 2000).

Fig. 2 Species richness and dominance index values for the Proposed Tarsier Tourism Center,
Villa Aurora, Bilar and Tarsier Sanctuary, Canapnapan, Corella, Bohol, PhilippinesⒸISERD99

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Very high evenness index is always accompanied by very low dominance index. For both sites,
Simpson’s dominance index values were computed less than 0.04. This only means that there is only
less than 4% chance that two individual plants to be selected in both sites would belong to the same
species.
Reyes (2000) reported that the species diversity in the identified six roosting territories of thePhilippine tarsier in barangay Cabacnitan, Bilar ranged from 2.01 (low) to 3.125 (high).
Self-defined DBH Classes
The computation on percent distribution of plants in three different self-defined DBH classes showedthat PTTC had 87.55% of the total recorded plants with DBH measurements of <10 cm. This wasfound lower by almost 10% from TS. Considerable percentages of trees were also shared in other DBH
classes for PTTC. DBH class ranged of 10-20 cm had 6.88%, while 5.58% was computed for DBH
class of >20 cm. Percent distribution of trees on these DBH ranges (especially on DBH class >20 cm)
indicated the presence of medium and large trees. The largest DBH measured in PTTC was 70 cm.
For TS, only less than 3% combined was computed for DBH classes of >10 cm. The largest DBH
measured was 22 cm (Table 5).
Table 5 Percent distribution of plants in self-defined DBH classes
DBH Class (cm)Study Site

<10

10-20

>20

Proposed Tarsier Tourism Center

87.55

6.88

5.58

Tarsier Sanctuary and Conservation Site

97.13

2.01

0.86

CONCLUSION AND RECOMMENDATION
Based on the findings of the study, it is concluded that the proposed 10-ha site in Villa Aurora, Bilar issuited to be utilized as Tarsier Tourism Center. Apart from the site’s inherent diversity in plant species,
the current vegetation composition and the presence of medium and large size trees in PTTC suggests
its similarity to one of the variants described by Reyes (2006) as advance thickets of many small
diameter trees, few medium- and large-sized trees and dense undergrowth. However, in case theproposed project will be pursued, enclosure similar with what has been constructed in Canapnapan,
Corella should also be established to prevent stray cats and other animals from predating the captive
tarsiers.
REFERENCES
Community Environment and Natural Resources Office-Tagbilaran. 2013. Map of the proposed tarsier tourism
site at Villa Aurora, Bilar. CENRO Tagbilaran, DENR.
Ecosystems Research and Development Services. 2009. Floral and faunal assessment of the proposed tarsier
sanctuary in Corella, Bohol. Unpublished Technical Report. Ecosystems Research and Development Services(ERDS) Region 7, DENR.
Fernando, E., Jumawid, R.J. and Peras, J. 1998. Resource inventory and assessment of biodiversity in the Subic
Bay metropolitan authority area. Unpublished Terminal Report. UPLB-SBMA-PCARRD-DOST.
Gruezo, W.S.M. 1997. Floral diversity profile of Mount Makiling Forest Reserve, Luzon, Philippines, In: The
Conditions of Biodiversity Maintenance in Asia. Michael R. Dore and Percy E. Sajise (eds.). East-WestCenter, Honolulu, Hawaii.

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Hoogstraal, H. 1947. The inside story of the tarsier. Chicago Natural History Museum Bulletin, 18, 7-8 (Nov.), 45 (Dec.).
Lagapa, E.P.G. 1993. Population estimates and habitat analysis of the Philippine tarsier (Tarsius syrichta L.) in
Bohol. Bachelor’s Thesis. University of the Philippines, Los Baños.
Madulid, D.A. (undated). Vegetation analysis of the forest in Corella, Bohol. Unpublished Report. National
Museum, Manila.
Neri-Arboleda, I., Scott, P. and Arboleda, N.P. 2002. Home ranges, spatial movements and habitat associations of
the Philippine tarsier (Tarsius syrichta L.) in Corella, Bohol. Journal of Zoology, London, 257, 387-402.
Protected Areas and Wildlife Bureau - Department of Environment and Natural Resources. 1992. The Philippine
tarsier. Philippine Wildlife Series, 2, PAWB-DENR.
Rabor, D. 1977. Philippine birds and mammals. University of the Philippines Press: Baltimore.
Reyes, T. JR. D. 2000. Population estimation, habitat characterization, and mapping of identified Philippine
tarsier (Tarsius syrichta Linne.) territories in Cabacnitan, Bilar, Bohol. Tropical Technology Journal, 3 (4),ISSN 1656-0264.
Reyes, T. JR. 2006. Plant-environment relations in the Philippine tarsier (Tarsius syrichta Linne.) habitats.
Unpublished Masteral Thesis. Wageningen University and Research Centre. The Netherlands.
Villamor, C.I. 1995. Captive breeding of Philippine tarsier (Tarsius syrichta L.). Terminal Report. ERDB-DENR
and PCARRD-DOST Project.

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Research article
erd

Rapid Carbon Stock Appraisal (RACSA) Implementation in
Wahig-Inabanga Watershed, Bohol, Philippines
TOMAS D. REYES, JR.*
Bohol Island State University, Bohol, Philippines
Email: tomseyer@yahoo.com, tomseyer@gmail.com

ERWIN G. LUDEVESE
Bohol Island State University, Bohol, Philippines
Received 3 March 2015

Accepted 27 August 2015(*Corresponding Author)

Abstract. The study aimed at assessing the biomass and carbon stocks of all major land uses in
Wahig-Inabanga Watershed, Bohol, Philippines and to estimate its total carbon budget. The “Apriori stratification cum purposive sampling” was used. Field measurements were conductedfollowing the destructive and non-destructive methods. The total C stored in the different land
uses surveyed in the watershed was estimated at 3.89 Megatons, 83.23% of which was held in
the cultivated perennial crops. Among the land uses assessed, it was only mangrove which had
lower carbon density estimate relative to previously reported values indicating substantial
degradation of mangroves vegetation over the years. The possibility of increasing its potential
to store more carbon could only be improved if appropriate management and alternative
livelihood interventions, coupled with conservation and protection measures are properly
implemented.
Keywords RACSA, carbon stock, carbon budget, Wahig-Inabanga Watershed

INTRODUCTION
Carbon stock assessment is not new to science. Many researchers have attempted to document andquantify carbon stocks of almost every land use in the Philippines since the late 1990s, and even earlier
in other countries. Lasco and Pulhin (2003) provided a list of several studies which have investigatedthe carbon stocks of forest ecosystems and other land cover types in the Philippines. Most of the
carbon stock assessments were conducted in plantations where dynamics were only affected by the
choice of species, management styles and decisions, silvicultural operations and environmental factors.
Few have even designs species-plantation/stand-based allometric equations (Codilan et al., 2009).
These were all triggered by the increasing importance of carbon stock assessment in policy and thepossible consequences for economic incentives (C markets) (Hairiah et al., 2001 and Hairiah et al.,2011). In Bohol, carbon stock studies were implemented in a 2-hectare rubber plantation at Magsaysay,
Talibon (Reyes et al., 2011) and oil palm plantations in Carmen, Sierra Bullones, and Pilar (Pulhin,
personal communication).
The RACSA appraisal tool, which was used in this study, was designed to provide a basic level
understanding of carbon appraisal and it introduced a scientifically sound methodological frameworkof accounting carbon sinks; while focusing on activities that could improve local livelihoods andalleviated rural poverty (Hairiah et al., 2011). Its application in the Wahig-Inabanga Watershed
provided an idea of how much carbon was stored in the watershed and its potential in sequestering
more carbon dioxide from the atmosphere.
This report focused only on the rapid carbon stock estimation of Wahig-Inabanga Watershed in
Bohol, Philippines based on the current scenario. It assessed the biomass and carbon stocks of all majorⒸISERD102

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land uses in Wahig-Inabanga Watershed, Bohol, Philippines and determined the watershed’s total
carbon budget.
METHODOLOGY
Study Site
The study was conducted in Wahig-Inabanga Watershed, Bohol, Philippines. This watershed is thebiggest in Bohol Province embracing a total land area more than 610 km2 or over 15 % of the total landarea of the Province. It is geographically located between 124º 3’ 36” and 124º 23’ 24” East longitude,
and between 9º 43’ 48” to 10º 4’ 48” North latitude. It has two headwaters namely the Wahig andPamacsalan Rivers and its outlet is geographically located at 10º 4’12” North latitude and 124º 4’12”
East longitudes (Fig. 1). It traverses the municipalities of Garcia Hernandez, Jagna, Duero, Sierra
Bullones, Pilar, Alicia, Carmen, Dagohoy, San Miguel, Sagbayan, Trinidad, Talibon, Jetafe,
Buenavista, Danao, and Inabanga.

Fig. 1 Location of the study area: (a) map of the Philippines showing the Central Visayas; (b)map of the Central Visayas showing Bohol; and (c) map of Bohol showing the WahigInabanga Watershed
Site Selection and Sampling Procedure
The rapid carbon stock appraisal was carried out only in four identified municipalities of WahigInabanga Watershed. Among the 16 municipalities within the watershed, Pilar, Sierra Bullones, Danao,
and Inabanga were selected for this study. These are municipalities which cover large areas in thewatershed. Selection criteria considered were the variability of land cover and land uses, elevationdifferences, and geological features which would represent the characteristics of the whole watershed.
The strategy used in this research was the “Apriori Stratification cum Purposive Sampling”(Hairiah et al., 2001) commonly known as preferential sampling patterned from the methodology
suggested by Hairiah et al., (2011). This means that the sampling locations and plots are identified
prior to successive field surveys. This approach was employed for the reason that it would be more
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expensive and very time consuming if one of the regular field survey methods, such as random
sampling, systematic sampling, and stratified random sampling, is to be applied following a definite
sampling intensity.
In this study, plots were laid in secondary forests; shrub/scrublands; cultivated perennial crops
also referred in this paper as agroforestry areas; rice and cornfields; grasslands; mangroves; andexisting tree plantations (i.e. Swietenia, Gmelina, Tectona, Elaeis, and Acacias).
Sampling Layout and Plot Sizes
In this study, rectangular-shaped plots were chosen since these tended to include more of the withinplot heterogeneity, and thus, represented more heterogenic species than square or circular plots of thesame area. Three different plots sizes were employed in the study based on Hairiah et al. (2001) andHairiah et al. (2011). The 20m x 100m plot for trees with diameter at breast height (DBH) >30 cm andwas used mainly in secondary forests, shrubs, and apitong (Dipterocarpus grandiflorus) natural stand.
The 5m x 40m plot was established for trees in plantations, agroforestry farms (perennial crops), andmangrove sites. The same size of plot was also nested in the middle of the 20m x 100m plot to measuretrees with DBH < 30 cm. On the other hand, plot with a dimension of 1m x 1m was employed toappraise undergrowths, agricultural crops (rice and corn), low stature weeds, and grasses.
Biomass Measurement of Aboveground Carbon Pools
Trees and other woody plants: Non-destructive measurement of trees, shrubs, and other woody
plants as suggested by Hairiah et al. (2001) was adopted in this study. Diameter at breast height (DBH),
merchantable height (MH), and total height (TH) were among the biometrics measured.
Understorey vegetation: Destructive or harvest method was used to determine the biomass ofunderstorey vegetation. Total fresh samples were weighed and recorded, however only approximately
50-500 g of samples were collected for oven-drying. Oven-dried weight was again recorded in eachsample after 3 days of drying.
Floor litter: Similar with the understorey vegetation, destructive or harvest method was also employed
for floor litter. Total fresh samples were weighed and recorded, and only approximately 50-200g ofsamples were kept for subsequent oven-drying.
Cereals and weeds: The method applied to determine the biomass of the understorey vegetation was
also used for land uses such as rice, corn, and grassland.
Estimation of Belowground Carbon Pool
Belowground biomass (root biomass): This is a fraction of aboveground biomass. An equation in
Table 1 was used for this purpose.
Soil Stock Pool: Percent soil organic carbon and bulk density are important variables in the calculationof soil carbon. These values were derived from the ACIAR-BSWM project report (ACIAR, 2006) andresults of BSWM soil chemical analysis on soils collected during the series of soil surveys done by the
CSIRO-BSWM team.
Parameter values for percent soil organic carbon in each survey location were obtained using the
Kriging interpolation function in ArcGIS. The values were derived employing the extract by sample
function in the spatial analysis tool. On the other hand, bulk density values were directly taken fromthe BSWM soil survey report.
Data AnalysisⒸISERD104

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Quantifying biomass and carbon stock: Allometric equations for trees and other plants suggested by
Hairiah et al., (2011) for estimating above-ground and root biomass were used (Table 1). Biomass andcarbon content were calculated in kilograms and then finally converted in tons (=mega grams [Mg])
per hectare.
Table 1 Allometric equations used to compute for the above-ground (AGB) and below-groundbiomass (BGB)
Plant Type / Species
Tree/shrub
Mangrove
Rhizophora
Sonneratia
Avicennia
BananaAllometric Equation
AGB= ρ* EXP(-1.499 + 2.148 LN(DBH) + 0.207(LN[DBH])2 - 0.0281*(LN[DBH])3)

SourceChave et al., 2005

AGB = 0.2453 – 0.2165*(DBH) + 0.0658*(DBH2) +0.0270*(DBH2*TH)
AGB = 0.2301 – 0.5382*(DBH) + 0.3370*(DBH2) +0.0474*(DBH2*MH)
AGB = 0.0198 – 0.0013*(DBH) + 0.0097*(DBH2) +0.0155*(DBH2*MH)
AGB = 0.030*(DBH2.13)

Codilan et al., 2009
Codilan et al., 2009
Codilan et al., 2009
Arifin, 2001; Noordwijk
et al., 2002
Priyadarsini, 2000
ICRAF, 2009
Frangi and Lugo, 1985
Modified from Teopolo
et al., 2002

AGB = 0.131*(BDC2.28)
AGB = 0.0976 *(TH) + 0.0706
AGB = 4.5 + 7.7*(TH)AGB = 0.3999 + (7.907*TH)*0.2
Note:
0.2 added in the equation since nipa does not have
aboveground stem
Coffee
AGB = 0.281 D 2.06
Arifin, 2001
Root Biomass
RB = EXP(-1.0587 + 0.8836*LN[AGB])
Cairns et al., 1997
Note: AGB = estimated aboveground biomass (kg/tree); RB = estimated root biomass; DBH = diameter at breast
height (cm); BDC = basal diameter of cluster (cm); TH = total height (m); ρ = wood specific gravity (Mg/m 3); EXP =exponent; LN = natural logarithm
BambooOil palm
Palm
Nipa

For this study, a conservative estimate of 45% tons of C per 100% tons of oven-dried biomass was
adopted since the carbon content of biomass dry weight based on the studies conducted in and out of
the country ranges from 40% to 55% (Lasco and Pulhin, 2000 as cited by Lasco et al., 2005).
Conversely, a simple formula on oven dried weight was used to compute for the biomass ofunderstorey plants, weeds, rice, corn, and floor litter.
ODW = TFW- (TFW*(SFW-SODW))/SFW
Where ODW is total oven dry weight, TFW total fresh weight, SFW sample fresh weight and SODW
sample oven dry weight
The carbon content of each pool was calculated by getting the 45% of the total biomass, except
for soil carbon which was computed by obtaining the product of soil weight and % organic carbon. The
total carbon was calculated as the summation of all carbon content in all pools.
RESULTS AND DISCUSSION
Biomass and Carbon Stock Assessment
Plantation: Among the major land uses considered in the study, plantation had the largest above- andbelowground biomass which was estimated to be 630.64 tons ha-1 and 102.45 tons ha-1, respectively. Its
soil carbon was also computed at 3.64 tons ha-1. Forty five percent of its combined biomass inclusiveof soil carbon amounted to 333.53 tons of carbon per hectare (Table 2). Such quantity of carbon isⒸISERD105

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

almost 300 tons larger than the average of the total stored carbon in selected Philippine plantations
amounting to only 55.6 tons ha-1 (Lasco and Pulhin, 2000 as cited by Lasco et al., 2005). Though thetypical condition of most of the tree plantations in the watershed is not ideal (crooked, and mostly
thinner and shorter (stunted) relative to the trees age), their density (close spacing) has contributed
much to their current biomass.
Conversely, Lasco and Pulhin (2003) reported that carbon stocks of plantations in Mt. Makiling
ranged from 125.6 to 285.7 tons ha-1 and even way lower in other parts of the country. A separate study
conducted earlier by Racelis (2000), however conformed with the result of this study and revealed thatmahogany plantation in Mt. Makiling, due to its age, dense stocking and large girth, had a computed
carbon stock of 542.05 tons ha-1. These results also added that the dipterocarp stand in the same study
area, sharing similar features, had even higher stored carbon of about 639.81 tons ha-1.
Secondary forest including apitong stand: The second type of land use in Wahig-Inabanga
watershed having considerable quantity of biomass and, thus, carbon was the secondary forest. Its
above- and belowground biomass were 209.51 tons ha-1 and 38.13 tons ha-1, respectively. Its soil
carbon of 3.78 tons ha-1 was the largest among the computed soil carbon in all land uses. These gave a
total carbon stock of 115.22 tons ha-1 (Table 2). The computed total stored carbon of secondary forest
in Wahig-Inabanga watershed was comparable with that of the secondary forest in Kaliwa watershed.
The latter, according to Lasco et al. (2005), has a total carbon stock of 121.21 tons ha-1. Lasco andPulhin (2009) stated an average of 111.10 tons ha-1 of stored carbon for several surveyed secondary
forests in the country.
Agroforestry: Same with the first two land uses, agroforestry had an estimated total carbon stock ofmore than 100 tons ha-1. Its estimated total stored carbon was 104.05 tons ha-1 (Table 2). This value istwice as high as the estimate presented by Lasco and Pulhin (2000) as cited by Lasco et al. (2005)
disclosing an average of 50.3 tons ha-1 for agrorestry sites in the country. The bloated values in thepresent study were attributed to the dominance of coconuts and other tree crops in the surveyed areas.
However, such amount of carbon is still below the carbon stocks of Taungya agroforestry and mixed
multistorey systems in Bukidnon with 174 tons ha-1 and 162 tons ha-1, respectively (Labata et al., 2012).
Shrub/brushland: The computed above- and belowground biomass per hectare in shrub/brushlandamounting to 172.56 tons ha-1 and 32.77 tons ha-1, and a soil carbon of 3.50 tons ha-1 provided anequivalent carbon stock of 95.90 tons ha-1 (Table 2). This value is comparatively higher than theestimates of Lasco and Pulhin (2000) as cited by Lasco et al. (2005), in several watersheds in the
country which ranged from 29.0 tons ha-1 to 74.27 tons ha-1. This could be due to the presence of few
invasive timber species such as yemane (Gmelina arborea), mahogany (Swietenia macrophylla) and
ipi-ipil (Leucaena leucocephala) which have been naturally dispersed from adjacent plantations andhave grown with small-sized native shrubs and trees.
Mangrove: Among the major land uses, mangrove is generally noted as the most represented in termsof number of individuals. However, the density alone is not the only requisite for a particular land use
to acquire high biomass. The foremost requirement is the availability of considerable number of hugediameter trees which, unfortunately, is not a good trait of the surveyed mangrove areas. Based onrecords, more than half of the measured plants (mostly young Rhizophoras) had diameters of less than
5 cm. For this reason, the computed biomass densities were only 87.98 tons ha-1 for aboveground and17.72 tons ha-1 for belowground, with a corresponding carbon stock of not more than 50 tons ha -1(Table 2). These values are over 3 times smaller than the country’s average mangrove biomass andcarbon stock of about 401.8 and 176.8 tons ha-1, respectively (Lasco and Pulhin, 2000 as cited byGevana et al., 2008). Gevana et al., (2008) reported that mangroves’ biomass density may reach up to
more than 500 tons ha-1 especially if it is dominated by large-sized Rhizophoras. One good example isthe study of Fujimoto (2000) as cited by Gevana et al., (2008) in Matang, Malaysia which revealed thatabove-ground biomass alone was computed to reach 558 tons ha-1. Rhizophora-dominated mangroveⒸISERD106

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stands are noted to have large biomass and carbon density (Tanouchi et al., 2000 as cited by Gevana etal., 2008). The presence of their unique physiognomic characteristics such as the presence of stilt roots,
dense stem and branches, and relatively large canopy contributes much to the total biomass.
Grass: The result of the above-ground biomass density computation for the surveyed grasslands,
together with its carbon stock, coincides with the estimates of Lasco and Pulhin (2000) as cited by
Lasco et al., (2005). The carbon stock of 5.48 tons ha-1 is comparable with the country’s averagecarbon stock for grasslands of about 5 tons ha-1 (Table 2).
Rice: Farms planted to rice are among the land uses with little amount of biomass and consequently
carbon content. This is due to seasonal harvests leaving almost no traces of biomass especially afterland preparation. The rice farms’ computed above-ground biomass density and total carbon stock were
4.11 tons ha-1 and 5.3 tons ha-1, respectively (Table 2). Same with grass, more than half of the total
carbon stock for rice came from the soil carbon.
Corn: Among the land uses assessed in this study, it was corn which had the least estimated biomass
and carbon stock. This was because of having only 3-4 individual plants which were harvested forbiomass calculation in a standard one square-meter plot. In addition, regular care and maintenance likeharrowing and weeding limit the growth of herbaceous weeds and grasses. For these reasons, thecomputed above-ground biomass was only 2.97 tons ha-1 and its carbon stock was 4.74 tons ha-1. It isalso noticeable that a big chunk, roughly 3.4 tons, of carbon per hectare was derived from soil carbon(Table 2).
Table 2 Computed above and belowground biomass and carbon in major land uses in WahigInabanga Watershed, Bohol, Philippines
Land Use
Plantation
Secondary forest with Apitong standAgroforestry
Shrub/Scrubland
Mangrove with nipa
Grassland
Rice
Corn

AGB
(ton ha-1)
630.64209.51
188.28172.56
87.98
4.52
4.11
2.97

BGB
(ton ha-1)
102.45
38.13
34.71
32.77
17.72
-

Soil Carbon(ton ha-1)
3.64
3.78
2.21
3.50
2.21
0.96
3.45
3.40

Total Carbon(ton ha-1)
333.53115.22104.05
95.90
49.77
5.48
5.30
4.74

Note: AGB = aboveground biomass; BGB = belowground biomass

Table 3 Carbon storage of different land uses in Wahig-Inabanga Watershed, Bohol,
Philippines
Land Use
Secondary forest
Shrubland
Cultivated perennials*
a. Coconut/tree-based
agroforestry farmb. Tree plantation
Mangrove with nipa
Rice
Corn
Grassland

Area of Coverage(ha)1,247.75
5,910.05
23,878.82
(90%)
(10%)
537.6314,146.65
9,401.21
4,073.16

Carbon Stock(tons ha-1)
113.2992.12

Total Carbon Stock(tons)
141,357.60
544,443.81

104.052,236,132.10

333.53
49.78
5.30
4.74
5.48
Total

796,430.28
26,763.22
74,977.25
44,561.74
22,320.92
3,886,976.90

Note: *“Cultivated perennials” is assumed composed of 90% coconut/tree-based agroforestry farms and 10% plantations.
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Total Carbon Budget
Table 3 provides a rough estimate of the carbon budget of the whole watershed. A total of
3,886,976.90 tons or 3.89 megatons of carbon was computed based on the land uses’ areas of coverageand computed carbon stocks. The biggest share comes from cultivated perennial crops which had thelargest area of coverage within the watershed and the highest estimated carbon stocks.
Shrub/brushland and secondary forest also had significant contributions on the watershed’s carbon
budget due to the substantial number of trees and shrubs which were appraised in these types of land
use compared to those with extensive area of coverage however dominated by low stature annual plants.
CONCLUSION AND RECOMMENDATION
The Wahig-Inabanga watershed’s estimated overall carbon stock of 3.89 megatons presents the finest
contribution of the watershed to the global carbon budget. Around 83.38% of these are presented incultivated perennial crops, while the rests are stored other land uses. The possibility of increasing its
potential to store more carbon could only be harnessed if appropriate management interventions were
implemented.
Open areas like grasslands, for instance, offer immense potential of sequestering carbon throughtree planting and agroforestry. If in case tree planting and agroforestry, as immediate interventions, areinappropriate, natural or artificial regeneration may be the best alternative option.
Among the land uses assessed in the watershed, it was only mangrove which had lower carbon
density estimate relative to previously reported values. This indicates substantial degradation ofmangroves vegetation through time. For this type of land use, provision of alternative livelihood,protection and conservation, apart from reforestation activities are the best options to undertake. Any
management intervention would only be wasted if alternative livelihood options are not available andconservation and protection measures are not properly enforced.
REFERENCESACIAR. 2006. Final report: Integrated watershed management for sustainable soil and water resourcesmanagement of the Inabanga watershed, Bohol Island, Philippines (LWR/2001/003). Australian Centre forInternational Agricultural Research, Canberra.
Chave, J., Andalo, C., Brown, S., Cairns, M.A., Chambers, J.Q., Eamus, D., Folster, H., Fromard, F., Higuchi, N.,
Kira, T., Lescure, J.P., Nelson, B.W., Ogawa, Puig, H., Riera, B. and Yakamura, T. 2005. Tree allometry andimproved estimation of carbon stocks and balance in tropical forests. Oecologica, 145, 87-99.
Codilan, M., Carandang, G., Calderon, M.M. and Eslava, F.M. 2009. Aboveground biomass production of threemangrove species in Real, Quezon Province, Philippines.
Gevaña, D.T., Pulhin, F.B. and Pampolina N.M. 2008. Carbon stock assessment of a mangrove ecosystem in San
Juan, Batangas. Journal of Environmental Science and Management, 11 (1), 15-25.
Hairiah, K., Sitompul, S.M., Van Noordwijk, M. and Palm, C.A. 2001. Methods for sampling carbon stocks
above and below ground. ASB_LN 4B.
Hairiah, K., Dewi, S., Agus, F., Velarde, S., Ekadinata, A., Rahayu, S. and Van Noordwijk, M. 2011. Measuring
carbon stocks across land use systems, A manual. Bogor, Indonesia. World Agroforestry Centre (ICRAF),SEA Regional Office, 154 pp.
Labata, M.M., Aranico, E.C., Tabaranza, A.C.E., Patricio, J.H.P. and Ruben, A.F.Jr. 2012. Carbon stock
assessment of three selected agroforestry systems in Bukidnon, Philippines. Advances in Environmental
Sciences. International Journal of the Bioflux Society, 4 (1).
Lasco, R.D. and Pulhin, F.B. 2003. Philippine forest ecosystems and climate change, Carbon stocks, rate ofsequestration and the Kyoto Protocol. Annals of Tropical Research, 25 (2), 37-51.
Lasco, R.D., Pulhin, F.B., Cruz, R.V.O., Pulhin J.M. and Roy, S.S.N. 2005. Carbon budgets of terrestrial
ecosystems in the Pantabangan Carranglan Watershed.
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Lasco, R.D. and Pulhin, F.B. 2009. Carbon budgets of forest ecosystems in the Philippines. Journal ofEnvironmental Science and Management, 12 (1), 1-13.
Racelis, M.E. 2000. Carbon stock assessment of large leaf mahogany (Swietenia macrophylla King.) and
dipterocarp plantations in the Mt. Makiling Forest Reserve, Philippines. Unpublished MSc Thesis. Universityof the Philippines Los Baños, College, Laguna.
Reyes, T.Jr., Lomosbog, N., Abadingo, J. and Bautista, B. 2011. Latex production potential and carbon budget
assessment of rubber (Hevea brasiliensis) plantation Talibon, Bohol, Philippines. KAPLAG Journal, Bohol
Island State University.

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Research article
erd

Effect of Stake Storage Methods on Germination, Growth andYield of Cassava (Manihot esculenta Crantz.)
ARUNEE PROMKHAMBUT*
Faculty of Agriculture, Khon Kean University, Khon Kaen, Thailand
Integrated Water Resource Management Research and Development Center in Northeast, Thailand
Email: arunee@kku.ac.th

PIKUL MANUTA
Faculty of Agriculture, Khon Kean University, Khon Kaen, Thailand

ANUCHA LAOKEN
Mahasarakham Agricultural Research and Development Centre, Mahasarakham, Thailand

KIRIYA SUNGTHONGWISES
Faculty of Agriculture, Khon Kean University, Khon Kaen, Thailand

ANAN POLTHANEE
Faculty of Agriculture, Khon Kean University, Khon Kaen, Thailand
Received 15 December 2014

Accepted 11 September 2015(*Corresponding Author)

Abstract Quality of stakes is an important factor to determine the germination and plant
population, consequently the tuber yield of cassava. Storage of cassava stakes before planting
can affect the quality of the cutting. Therefore, the objective of this research was to investigate
the effect of different storage stake methods on germination, growth, and yield of cassava. The
field experiment arranged in randomized complete block design with 3 replications was
conducted in Yasothorn soil series during April-October 2014 in Khon Kaen province, Thailand.
The three stake storage methods comprised of storage under tree shade, under sunlight and store
under sunlight with gunny sack coverage. Local cultivar of cassava was employed and stakes
were stored for 45 days before planting. The results showed that moisture content of the stake,available part and germination percentage at 7 days after planting (DAP) of the stake stored
under the sun with gunny sack coverage (69.08%, 73.93% and 85.71%, respectively) was
significantly higher than that under shade (57.23% , 47.56% and 28.57%, respectively) and insun (55.59%, 68.13% and 40.47%, respectively ). However, germination at 14 DAP andsurvival rate at 30 DAP were not significantly different among storage methods but stakes
covered with gunnysack tended to be higher than other methods. Stakes stored by covered withgunnysack gave the highest plant height at 14, 21, 28, 35, 42, 72, and 180 DAP. Moreover,there was no significant difference in leaf, shoot and total aboveground dry weight, tuber yieldand starch contents that were found amongst the storage methods. The stakes stored under thesun and covered with gunnysack tended to give the highest values. This study shows thepotential method for storing cassava stakes under field conditions before planting.
Keywords cutting storage method, germination, survival rate

INTRODUCTION
Cassava is usually planted by using vegetative part called stem cutting or stake. Normally, farmers use
the cassava stems after harvest for the next growing season. These cassava stakes are kept in the fieldⒸISERD110

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for a period of time before planting. Thus, exposure of the cutting to the sun can result in lost viability
within a short time due to dehydration. These poor stakes cause a poor establishment and finally a low
yield. Andrade and Leihner (1980) reported that stake storage conditions were more critical than the
duration of the storage. Sinthuprama and Tiraporn (1986) reported that stakes stored upright undershade for 45 days could obtain 80% survival rate but decreased faster when stems were stored in thesun and covered with leaves. However, Boonma et al., (2007) found that stake stored in the sun withthe base earthen up resulted in greater stem moisture content and stem length than shade storage withno significant effect on germination and survival percentage. These contradicting opinions, therefore,
needed to be proved by alternative method, which could be convenient for field practices by farmers.
OBJECTIVE
The objective of this study was to investigate the effect of different storage stake methods ongermination, growth and yield of cassava.
METHODOLOGY
Experimental site and design: A field experiment was conducted at the Agronomy Field Crop
Research Station, Faculty of Agriculture, Khon Kaen University, Thailand (latitude 16° 26´N andlongitude 102° 48´E) during April-October 2014. The experiment was conducted in a loamy-sand soil
(Yasothorn soil series) with pH 5.14, 0.48 % of organic matter, 28.60 mg/kg of available phosphorus,
and 39.55 mg/kg of extractable potassium. The experiment was laid out in Randomized Complete
Block Design with 3 replications. The treatments included stakes storage upright under 3 different
conditions: under tree shade, in sun, and in sun with gunny sack coverage.
Materials and cultural practices: A local cultivar cassava named E-dam which was stored under
different methods for 45 days was used in the study. The stakes of 20 cm in length were planted
vertically with a 100 x 100 cm spacing in a 5 x 8 m plot. Plots were manually weeded 2 times at 1 and2 months after planting. Chemical fertilizer grade 15-7-18 (N, P2O5, K2O) at the rate of 312.5 kg/ha
was applied 1 month after planting. Irrigation was applied during the period of 1-2 months after
planting to ensure good establishment during April-May 2014 and the field was kept under rain for the
rest of the growing period. The total amount of rainfall during the growing period was 946.7 mm andthe mean values of daily maximum and minimum temperature were 33.5°C and 24.5°C, respectively.
Crop measurement: Before planting, 4 stakes were randomly selected to estimate moisture content byoven dried at 80°C to constant weight. The moisture content was calculated based on the stem fresh
weight. Available portion in percentage was measured by dividing the length of vital or usable parts
with total stem length and multiplying it by 100. Germination at 7 and 14 days after planting (DAP)
was counted and a survival rate at 30 DAP was also recorded. Plant height was continuously measured
at 14, 21, 28, 35, 42, 72, and 180 DAP. Biomass measurement was done at 180 DAP by cutting thestem base of three plants at random per plot. Plants were separated into leaves, stems, and tubers andwere oven dried at 80°C to constant weight. The fresh tuber root yield (t/ha) were calculated based on
the harvested crops. The starch content in the tuber was determined by specific gravity method.
Statistical analysis: Analysis of Variance (ANOVA) for all data was done by using Statistix 10.0
software (Analytical Software, Tallahassee, Florida, USA.). The Least Significant Difference (LSD)
was used to compare all mean values.

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RESULTS AND DISCUSSION
Stake Characteristics and Germination
Storage of cassava stems under different conditions had a significant effect on stake moisture content
and available plant part usable for planting. Cassava stems stored in the sun with gunny sack coverage
had significantly higher stake moisture content (69.08%) and available plant part (73.93%) than othermethods (Table 1). However, this study opposed with the report of Boonma et al. (2007) who had
found that stakes stored in the sun with base earthen up had greater stem moisture content and stems
length usable for planting than that in the shade. They indicated that photosynthesis of the newly
sprouts is an important factor in maintaining the stems moisture content compared to the low lightintensity perceived by the sprouts of stems stored under the shade. In this experiment, it was found thatstems stored in the sun were burnt by sunlight which might result in lower stake moisture content.
Stems stored in the sun with gunny sack coverage produced some bud sprouting but with pale andyellow color. Stakes stored under tree shade were destroyed by termite leading to the lowest available
part (47.56%).
Table 1 Effect of stake storage methods on germination and survival percentage of cassava
Storage method

Stake moisture
content (%)
57.23b55.59b69.08aAvailable
part (%)
47.56b68.13a73.93aGermination(%) at 7DAP
28.57b40.47b85.71aGermination(%) at 14 DAP
88.64
93.56
95.92

Survival (%) at
30 DAP
83.33
90.48
92.86

Under tree shadeIn sunIn sun with gunnysack coverage
F-test
**
*
**
ns
ns
CV (%)
9.04
17.10
14.60
3.30
14.18
Ns, *, **= not significant, significant different at p<0.05, 0.01, respectively. Means in the same column with different letters
are significantly different at p<0.05 and 0.01 by LSD
DAP= days after planting

At 7 DAP, cassava stems kept in the sun with gunny sack coverage germinated significantly faster(85.71%) than stems stored by other methods (28.57-40.47%) (Table 1). This might be contributed by
the higher moisture content in the stakes which supported by the study of Leihner (1984) who foundthat stakes lost its viability when dehydration reduced moisture content less than 60%. The decrease inreserved carbohydrate of the cutting stem by respiration during the storage might also affect thegermination rate of stakes (Leihner, 1984). However, no significant difference was found in
germination at 14 DAP and survival percentage at 30 DAP among storage methods. But stakes storedin sun with gunny sack coverage tended to have the higher survival rate. Boonma et al., (2007) also
found the same results when stems stored in the field and under tree shade. Even no significant
difference in germination at 14 days after planting onward, the results from this study indicated thatstem with high moisture content had vigorous germination. This would be important for growing
cassava at the end of the rainy season, which soil moisture content was quickly loss. The faster
germination of crop also indicated the higher leaf area coverage which could be possibly competingwith weed.
Plant Height
Different storage methods significantly affected plant height at 14, 28, 35, and 42 DAP. Stakes stored
in the sun with gunny sack coverage had significant higher plant height than other methods at 14, 28,
35, and 42 days after planting and tended to have higher plant height than other methods at 21, 72, andⒸISERD112

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180 days after planting (Table 2). This might be due to the ability of early germination of seedlings
grown from this method, which indicating the strong vigor of the stored materials.
Table 2 Effect of stake storage methods on height (cm) of cassava at 14-180 days after planting
Storage method
14 DAP
21 DAP
28 DAP
35DAP
42DAP
72DAP
180DAP
Under tree shade
12.15b
14.00
14.85b
20.67b
27.15b77.49
238.78In sun13.31b
14.58
15.41b
22.79b
29.84ab86.14
246.66
In sun with gunny
15.96a18.30
19.61a27.31a35.52a86.91
250.78sack coverage
F-test
**
ns
*
*
*
ns
ns
CV (%)
3.28
10.74
8.17
6.50
8.67
12.75
7.00
Ns, *, **= not significant, significant different at p<0.05, 0.01, respectively. Means in the same column with different letters
are significantly different at p<0.05 and 0.01 by LSD
DAP= days after planting

Table 3 Effect of stake storage methods on cassava population, growth and yield at 180 days
after planting
StoragemethodPlant
population/ha

Under tree
shade
In sunIn sun withgunny sackcoverage
F-testCV (%)
Ns = not significant

8333

Leaf dryweight(kg/ha)1752.9

Stem dryweight(kg/ha)5558.1

Aboveground
dry weight(kg/ha)7311.0Tuber dryweight(kg/ha)11556

Tuber fresh
weight(t/ha)
32.6

Starchcontent
(%)
20.90

9048
9286

1776.12549.15412.47092.97188.59642.0

10516
12365

30.8
36.1

21.95
22.60

ns
14.18

ns
18.15

ns
12.58

ns
12.92

ns
15.84

ns
13.31

ns
7.56

Plant Population, Crop Biomass and Yield
Due to the higher survival percentage, population per ha of cassava grown from stems stored in sun
with gunny sack coverage was higher than the other methods (Table 3). Different stem storage methods
had no significant effect on crop biomass, root fresh yield, and starch content in the tuber (Table 3).
However, due to the higher population, cassava planted from stems stored in sun with gunny sackcoverage tended to have higher leaf, stem, aboveground, tuber dry weight per ha, and tuber fresh yield
per ha than other methods. Storage methods did not have significant effect on root starch content.
Boonma et al., (2007) also reported no significant difference between stakes stored in the field with thebase earthen up and under tree shading in terms of fresh and dry root yield and root starch content. This
study is consistent with the findings of Andrade and Leihner (1980) who indicated that final standpercentage or population of crops were not the factors responsible for yield variation of cassava if stem
cuttings were kept under appropriate conditions.
CONCLUSION
Storage of cassava stake under field conditions before planting is critical for better germination andsurvival of the seedlings. The results show that stems stored in the sun with gunny sack coverage had
the highest germination and survival percentage, which resulted in higher population and higher crop
biomass and tuber yield per area. However, under the three studied storage conditions, other factors
affecting shoot and root growth, rather than population, may determine cassava yield. Therefore, stakes
can be stored by any of the three methods from this study.
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However, in order to get the higher root yield and higher starch content, stem cutting stored in thefield with gunny sack coverage should be recommended.
REFERENCES
Andrade, A.M.S. and Leihner, D.E. 1980. Influence of period and conditions of storage on growth and yield of
cassava. In: Cassava Cultural Practices. Proc. Workshop held in Salvador, Brazil, 18-21 March 1980, 33-37.
Boonma, S., Vichukit, V. and Sarobol, E. 2007. Effects of cutting storage duration and methods on germination,
growth and yield of cassava (Manihot esculenta Crantz.). Proc. 45th Kasetsart University Annual Conference:
Plants. 30 January - 2 February 2007. Bangkok, Thailand, 131-138.
Leihner, D.E. 1984. Storage effects on planting material and subsequent growth and root yield of cassava(Manihot esculenta Crantz). (Retrieved: 24 September 2015 from http://www.istrc.org/images/
Documents/Symposiums/Sixth/6th_symposium_proceedings_0043_section_3_257.pdf).
Sinthuprama, S. and Tiraporn, C. 1986. Improving the productivity of cassava in Thailand. In: Cassava in Asia,
Its Potential and Research Development Needs. Proc. 1st Regional Workshop, held in Bangkok, Thailand.
June 5-8 1984, 277-287.

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Research article
erd

Impacts of Atmospheric Temperature - Humidity Changes on
Yield Quality of Thai Soybean Cultivar
KANITA THANACHAROENCHANAPHAS*
Naresuan University, Phitsanulok, Thailand
Email: kanitat@nu.ac.th

OROSE RUGCHATI
Naresuan University, Phitsanulok, Thailand
Received 12 December 2014

Accepted 11 September 2015(*Corresponding Author)

Abstract This study aimed to assess the impact of atmospheric temperature and humidity
change on yield of Thai soybean, Chiang Mai 60 cultivar. The research experiment was
conducted during July - October 2013 at Naresuan University Crops Field, Phitsanulok,
Thailand. Soybean seed Chiang Mai 60 cultivars were planted in 16 open top chambers (OTCs)
under 4 different temperature and humidity levels. The four simulated climate change situations
in OTCs were, lower than ambient temperature, higher than ambient temperature, combined
elevated temperature and high humidity and ambient temperature level, which all were
controlled by an electrical system. Results indicated that yield loss by statistical significanceoccurred in all Low-level temperature treatment (25r2.9 ๐C), High-level temperature treatment(37r2.2๐C), and high Temperature-humidity (36r2.8๐C/ 81.7r2.2%), compared with ambientlevel temperature treatment (31r1.7๐C). Exposure to simulated climate change situation in Lowlevel temperature treatment obviously reduced total pod/plant and total seed/plant by 40.8% and48.5%, respectively. High-level temperature caused yield loss in total pods/plant and total
seeds/plant by 35.6% and 39.5%, respectively. The combined effect of high temperature andhumidity on soybean crop reduced total pods/plant and total seeds/plant about 36.4% and 47%,
respectively. Finally, low temperature evidently increased in lipid content and all types of fatty
acid in experiment, whereas the high temperature treatment could reduce the total monounsaturated fatty acids. It was concluded that temperature change situations at above and lower
than ambient level in growing season could induce yield loss and some fatty acid in Thaisoybean, Chiang Mai 60.

Keywords temperature change, Thai soybean, open top chamber, yield quality
INTRODUCTION
Climate change and variability can have significant impacted on phenology, physiological mechanisms,
growth, nutritional value, genetics, and yield of crops (Bainy et al., 2008; Thanacharoenchanaphas andRugchati, 2011). The “Fifth Assessment Report of the Intergovernmental Panel on Climate Change(IPCC)” conclude that by 2081–2100, the globally averaged surface temperature will be in the range of
2.6-4.8 ◦C in comparison with 1986–2005 and, daily and seasonal high temperature extremes over mostland areas will be more frequent in the future (IPCC, 2013). These changes and variability in climate
may have significant impacts on yield of crops in various regions of the world (Smit and Yunlong,
1996; Kumagai and Sameshima, 2014).
Soybean is one of the important C3 plants that is sensitive to temperature change (Newman et al.,2011). On the basis of long-term field experiments (1987–2007) in northeastern China, Zheng et al.,(2009) reported that soybean seed yield was increased by 6–10% per 1 ◦C rise in mean daily maximum
temperature during seed filling. Thailand Department of Meteorology reported that the annual mean
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temperature in Thailand rose by approximately one degree Celsius from 1981 to 2007. By 2050, themean daily maximum temperature in Thailand will have been increased by 1.2 to 1.9 ◦C (Marks, 2011).
Hence, current mean temperature during the soybean growing season in Thailand has been changed at
meteorological observatories in the northern regions of Thailand. Based on these facts, wehypothesized that the increase/decrease in temperature and humidity during growing season haveeffects on soybean production. Our data clearly demonstrate the differences in soybean yield responses
to the change of temperature – humidity.
OBJECTIVE
This study was set to investigate the differences in Thai soybean yield responses to the changes oftemperature – humidity during growing season.
METHODOLOGY
Field Study and Experimental Design
The field study was carried out at Naresuan University in northern Thailand. The experiment was done
at agricultural crops field in the university. It is located at coordinates 16 degrees and 44.003 minutes
north of the equator, and 100 degrees and 11.810 minutes east of Prime Meridian. The total study area
covered about 300 m2.
Thai Soybean (Glycine max (L.) Merr.) Chiang Mai 60 cultivar was selected for the study; thiscultivar was widely cultivated in northern Thailand. It was planted in growing season of Thailand
during July 2013 to October 2013. Four replications of a Randomized Complete Block Design (RCBD)
were used in four treatments with four different levels of air temperature and relative humidity. At thevegetative growth stage, the soybeans in all four treatments were exposed to temperature-humidity
variability for 8 hr exposure (9.00 am – 5.00 pm) in open top chambers until harvest.
Temperature - Humidity Control
The square open top chamber was used throughout the study period. The chamber size was 1.5 m(width) x 3 m (length) x 2.5 m (height). It was constructed out of transparent plastic. There were foursituations of air temperature-humidity change, at an ambient level (AT-treatment or control treatment),
combination of low temperature and humidity at ambient level (LT-treatment), combination of hightemperature and humidity at ambient level (HT-treatment), and combination of high temperature andhigh humidity (HHT-treatment). These were controlled by an electronic system. The high temperatureand low temperature system was set up by green lighting and air conditioning exposure, whereas theelevated humidity treatments were set up by electronic water spray. Mean air temperature /humidity
levels ( ± S.D) for 8 hr for each treatment were 25r2.9 ๐C / 62 ± 9.8 % in LT-treatment, 31r1.7 ๐C/ 63± 7.4 % in AT-treatment, 37 r 2.2 ๐C/ 61 ± 5.7 % in HT-treatment, and 36r2.8 ๐C/81.7r2.2% in HHTtreatment, respectively.
Yield Quality Determination
Soybean seeds were harvested from the experimental field at maturing stage (95 days). Yield quality
was analyzed by determination in yield quantity and nutrition value (lipid and fatty acid content).
These samples were determined by number of pods/plant, number of seeds/plant and weight of 100
seeds. Lipid content and some important fatty acids were determined by gas chromatography (GC)based on analysis of nutrition content by AOAC (1995) method to estimate grain quality.
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Statistical Analysis
The experiment was designed as Randomized Complete Block Design (RCBD) with 4 replications.
Data of yield and fatty acids content were statistically analyzed by the analysis of variance (ANOVA).
Significant differences of parameters were reported at p<0.05 by DMRT.
RESULTS AND DISCUSSION
Yield Quantity
Seed yields were harvested at maturing stage. The yield component, including number of pods/plant,
number of seeds/pod and weight of 100 seeds were determined to assess grain quantity. The results areshown in Fig. 1a - Fig.1b. The significant reductions were found in all 3 parameters of yieldcomponent. The significant reductions in number of pods/plant and number of seeds/plant appeared in
LT treatment, HHT treatment, and HT treatment when compared to control treatment. Exposure to
Low-level temperature treatment obviously reduced total pods/plant and total seeds/plant incomparison with control by 40.8% and 48.5%.
We also found that the cumulative effects of high-level temperature caused yield loss in total
pods/plant and total seeds/plant by 35.6% and 39.5%, respectively. The combined effect of hightemperature and humidity on soybean crop reduced total pods/plant and total seeds/plant by 36.4% and47%, respectively. The results obviously showed that high level of temperature (plus ambient
humidity) reduced the 100 seeds weight when compared to the others (Fig. 2). These results indicatedthat the higher temperature level and the lower temperature level (above ambient level) in growing
season induced high suppression in yield Chiang Mai 60 cultivar soybean.

abFig. 1 (a) Effects of different air temperature – humidity levels on number of pod/plant ofsoybean, Chiang Mai 60 cultivar and (b) Effects of different air temperature –humidity
levels on number of seed /plant of soybean, Chiang Mai 60 cultivar

Note: The different letters for each treatment indicate a significant difference at Ud0.05. Error bars above eachhistogram indicated standard deviations (S.D.) observed from samples of each treatment.

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Fig. 2 Effects of different air temperature – humidity levels on 100 seed weight of soybean,
Chiang Mai 60 cultivar

Note: The different letters for each treatment indicate a significant difference at Ud0.05. Error bars above eachhistogram indicated standard deviations (S.D.) observed from samples of each treatment.

Nutrition Value in Lipid and Fatty Acid Content
Exposure of soybeans to different air temperature-humidity levels was carried out in an open top
chamber. In Table 1, we observed that the LT treatment (at lower temperature level than ambient level)
induced high lipid content in the full maturing stage (R8). However, there were no significantly
different results found in HT treatment (higher temperature level than ambient level). The significantly
different results were also clearly shown in total saturated fatty acids (TSFA), total mono-unsaturated
fatty acids (TMUFA), and total poly-unsaturated fatty acid (TPUFA). The results showed the mostobvious effects of increasing air temperature (HT treatment) led to the reduction in fatty acid whencompared with others. In contrast, the interested results showed that the low temperature treatment (LTtreatment) in growing season (than ambient level) led to the significant increase in all 3 types of fatty
acid (Table 1).
Table 1 Summary of the results of Lipid content, TSFA, TMUFA and TPUFA of soybean seed,
Chiang Mai 60 cultivar grown under four temperature treatments (LT, CT, HHT andHT) in this study
Lipid andFatty acid

4 treatments under different air temperature levels
LTCT

21.5 r 0.3 b
2815.7 r 24.3 c
4680.7 r 45.8 c
11697.9r 67.6 b

19.9 r 0.4 a
2547.6 r 18.5 a
4498.1 r 64.3 b
11257.8 r 61.3 a

HHT

19.8 r 0.1 a
2592.8 r 25.5 ab4753.7 r 26.5 c
11195.0 r 78.4 a
Note: The different letters for each treatment indicate a significant difference at Ud0.05.
Lipid content (g)TSFA(mg/100g)
TMUFA (mg/100g)
TPUFA (mg/100g)

HT19.6 r0 0.2 a
2621.2 r 34.2 b
4414.8 r 24.8 a11237.2 r 87.9 a

Many researches that have been investigated for decades showed similar results as this study. For
example, Hatfield et al., (2011) predicted that a 0.8 ◦C temperature rise would cause a 2.4% decline insoybean yield in southern USA (current growing season temperature of 26.7◦C). Numerous studies
have carried out to understand biochemical reaction taking place in plant’s physiology under climate
factors change, leading to the inhibition of photosynthesis and yield production. Its photosynthesis isvery sensitive to ratio of CO2 to O2 in the atmosphere. Increasing in this ratio of CO2 to O2 leads toⒸISERD118

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higher rates of photosynthesis (Newman et al., 2011). However, the reaction of photosynthesis isdisrupted at high temperatures and inhibit CO2 fixation (Araus and Slafer, 2011). One of the mosttemperature-sensitive reactions of carbon assimilation is rubisco activase. Rubisco activase activity is
exceptionally sensitive to thermal denaturation. Hence inhibition of the activase at high temperature
prevents activation of rubisco in leaves suffering heat stress and leads to inhibition of CO2 fixation(Crafts-Brandner and Sulvucci, 2000; Salvucci et al., 2001). Heat stress is a serious threat to crop
production worldwide. High leaf temperatures reduce plant growth and limit crop yields. Estimates
range up to a 17% decrease in yield for each degree Celsius increasing in average growing season
temperature (Lobell and Asner, 2003).
CONCLUSION
The results from the experiment showed that Thai soybeans, Chiang Mai 60 were grown undertemperature-humidity change and revealed that exposure to high temperature, low temperature, andcombination of high temperature-humidity during growing period led to the significant and obvious
reduction in yield quantity. Even though low temperature evidently increased in lipid content and alltype of fatty acid in experiment, the high temperature treatments could also reduce total monounsaturated fatty acids (TMUFA).
ACKNOWLEDGEMENTS
The authors thank Naresuan University, Thailand for the funding. This work was also financially
supported by Center for Agricultural Biotechnology, Faculty of Agriculture, Natural Resources andEnvironment, Naresuan University. We also thank to Office of Agricultural Research andDevelopment, Phitsanulok for soybean seeds, Chiang Mai 60 cultivar.
REFERENCES
Araus, J.L. and Slafer, G.A. 2011. Crop stress management and global climate change. CABI, UK.
Bainy, E.M., Tosh, S.M., Correding, M., Wooddrow, L. and Poysa, V. 2008. Protein subunit composition effects
on the thermal denaturation at different stages during the soy protein isolate processing and gelation profilesof soy protein isolates. J Am Oil Chem Soc., 85, 581-590.
Crafts-Brandner, S.J. and Salvucci, M.E. 2009. Rubisco activase constrains the photosynthetic potential of leaves
at high temperature and CO2. Proc Natl Acad Sci U , 97 (24), 13430-13435.
Hatfield, J.L., Boote, K.J., Kimnball, B.A., Ziska, L.H., Izaurralde, R.C., Ort, D., Thom-son, A.M. and Wolfe, D.
2011. Climate impacts on agriculture: implications for crop production, Agron. J., 103, 351-370.
Intergovernmental Panel on Climate Change (IPCC). 2013. Climate change 2013, The physical science basis,
report WGIAR5, summary for policymakers, technical summary and frequently asked questions. Cambridge
University Press, Cambridge, United Kingdom and New York, NY, USA.
Thanacharoenchanaphas, K. and Rugchati. O. 2011. Simulation of climate variability for assessing impacts onyield and genetic change of thai soybean. World Academy of Sci., Engineering and Technology, 59, 14841488.
Lobell, D.B. and Asner, G.P. 2003. Climate and management contributions to recent trends in U.S. agricultural
yields, Science, 299, 1032.
Kumagai, E. and Sameshima, R. 2014. Genotypic differences in soybean yield responses to increasing
temperature in a cool climate are related to maturity group. Agr. Forest Meteorology. Available online, 198199, 265-272.
Marks, D. 2011. Climate change and Thailand: Impacts and response. Contemporary Southeast Asia, 33, 225-258.
Newman, J.A., Anand, M., Henry, H.A.L., Hunry, S. and Gedalof, Z. 2011. Climate change biology. Gutenberg
Press, Malta.

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Sionit, N., Strain, B.R. and Flint, E.P. 1987. Interaction of temperature and CO 2 enrichment on soybean,
Photosynthesis and seed yield, Can. J. Plant Sci, 67, 629-636.
Smit, B. and Yunlong, Cai. 1996. Climate change and agriculture in China. Global Environmental Change, 6,205-214.
Sulvucci, M.E. Osteryoung, K.W. Craffs-Brandner, S.J. and Vierling, E. 2001. Exceptional sensitivity on rubisco
activase to thermal denaturation in vitro and in vivo. Plant Physiol. , 127, 1053-1064.
Zheng, H., Chen, L. and Han, X., 2009. Response of soybean yield to daytime temperature change during seedfilling, A long term field study in Northeast China. Plant Prod. Sci., 12, 526-532.

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Research article
erdPeriodic Fertilization Using Urea and Chicken Manure as
Source of Natural Productivity in a Biofloc System during the
Nursery of Pacific White Shrimp Litopenaeus vannamei
MARIA DANESA S. RABIA*
Research, Development and Extension Office
Bohol Island State University, Calape Campus, Calape, Bohol, Philippines
Email: senillo_danesa@yahoo.com

JOMEL G. BAOBAO
Research, Development and Extension Office
Bohol Island State University, Calape Campus

GUILLERMO P. TUTOR
Research, Development and Extension Office
Bohol Island State University, Calape Campus

ERNESTO C. RULIDA
Research, Development and Extension Office
Bohol Island State University, Calape Campus
Received 5 March 2015

Accepted 11 September 2015(*Corresponding Author)

Abstract The effect of periodic fertilization on natural productivity, growth and survival during
the nursery of Litopenaeus vannamei under a zero water exchange set up was investigated.
Nursery culture was carried out for 15 days in 2 m3 indoor concrete tanks with stocking densityof one post larvae (PL)·liter-1 using PL 16 shrimp. Urea and chicken manure were initiallyapplied a week before stocking and added weekly to maintain green water condition. There wasno significant difference in the phytoplankton densities and microbial flocs in the twotreatments. The results demonstrated that the weekly periodic application of urea in a zerowater exchange set up was not viable while fertilization using chicken manure improved feed
conversion rate as well as shrimp survival and production.
Keywords fertilizer, natural productivity, specific growth rate, post larvae

INTRODUCTION
World aquaculture has dramatically grown in the last 50 years. From a production of less than a million
tonnes in the early 1950s, production in 2006 had risen to 51.7 million tonnes excluding aquatic plants(FAO, 2008). In terms of value, shrimp was by far the largest commodity representing 17% of the total
value of international-traded fishery products in 2006 (FAO, 2009). From 2000 to 2005, its global
market had expanded from less than $1 billion to $5.8 billion (FAO, 2008). Since then the increase in
shrimp production has been brought about by so many factors, as it is the intensification of culture
systems. Advancements in aquaculture engineering and biotechnology amongst others have triggered
the transformation from extensive to intensive culture of shrimps. Introduction of new aquaculture
species in certain regions is another major factor. An example is the introduction of the Pacific white
shrimp Litopenaeus vannamei to Asia. In 1996, L. vannamei was introduced on a commercial scale inmainland China and Taiwan and subsequently spreaded to the Philippines and other neighbouring
countries (FAO, 2004).
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However, the intensification of shrimp aquaculture is coupled with pollution, environmental
degradation, and occurrence of diseases caused by heavy effluent discharge and pathogen
contamination of water supply. Thus, reducing waste outputs of shrimp aquaculture operations isessential to ensure a long-term sustainability. According to McIntosh et al., (2001), this could beachieved by improving feed and water management, application of water treatment to wastewater andadoption of zero or minimal water exchange. The latter is the soundest possible option because it does
not only control effluent discharge but also reduces introduction of water borne pathogens byincreasing biosecurity of the cultured organism (Gomez-Jimenez, 2005). The bioflocs technology is an
important discovery in the zero water exchange or closed system of shrimp farming. Bioflocs
technology (BFT) is a system wherein heterotrophic bacteria, algae, and other microorganisms aregrown in flocs controlled conditions within the culture period (Jorand et al., 1995; Avnimelech, 2009).
The microbial biomass or bioflocs utilize dissolved and particulate nitrogenous compounds in thewater coming from the waste of the cultured organism; the assimilation of these compounds is
stimulated by addition of carbon sources to the system (Avnimelech, 1999). The presence of bioflocs
does not only improve water quality but also serves as additional food for the cultured organism. The
BFT represents a sustainable way of producing food by the production of new biomass grown on the
nutrient waste and is used as an alternative food source (Crab et al., 2007). Studies on zero waterexchange during the nursery culture of L. vannamei showed several benefits. Baloi et al., (2010)
reported higher survival of L. vannamei post larvae cultured using reclaimed water from a superintensive zero-water exchange pond in tanks without water exchange for seven days. Widanarni et al.,(2010) demonstrated that the optimum carbon-nitrogen ratio 2:1 using the biofloc technology in L.
vannamei nursery production obtained the best shrimp growth, yield and feed efficiency.
Another strategy to improve sustainability while increasing shrimp production is to promotenatural productivity in the culture system. Natural food production in an aquatic system is enhanced byfertilization. Inorganic and organic fertilizers supply nutrients needed to increase primary productivity
that supports the maintenance of other communities occupying higher trophic levels. Stahl (1979)
reported that natural food alone consisting primarily of a mixture of organic detritus and soil, produced
growth rates in freshwater prawn Macrobrachium rosenbergii post larvae better than commercial
production ponds. Anderson et al., (1987) demonstrated that 53–77% of the growth of juvenile L.
vannamei raised in earthen ponds was due to the assimilation of in situ natural pond biota. PorchasCornejo et al., (2011) reported that promotion of natural feed had a positive effect on weight gain,
survival and final biomass of L. vannamei. Martinez-Cordova et al., (1998) found out that the growthand biomass of L. vannamei were higher in fertilized ponds despite lower feeding rate. L. vannamei
grown extensively (without supplemental feeding) in fertilized ponds resulted to moderate to highsurvival rates (Jaspe et al., 2010). However, research on the use of different fertilizers in a zero waterexchange set up during the nursery of L. vannamei is limited.
OBJECTIVE
This study determined the effects of periodic fertilization on natural productivity, growth and survivalin the nursery of L. vannamei under a zero water exchange set up. Specifically, the following indiceswere measured: water quality – dissolved oxygen, pH, salinity; natural productivity – phytoplankton
and zooplankton count and microbial floc; growth – specific growth rate in terms of weight and length,
feed consumption rate; yield or production – survival.
MATERIALS AND METHODS
Experimental design and set up: The experiment utilized a complete randomized design with twotreatments: inorganic fertilizer (urea) and organic fertilizer (chicken manure). Rearing of L. vanammeiⒸISERD122

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post larvae lasted for 15 days (from PL 16 to PL 30). It was conducted in the facilities of the Central
Bangus Hatchery located in Pangangan Island, Calape, Bohol. The experiment used six (2 m3) indoor
concrete tanks assigned to the two treatments. The tanks were chlorinated and washed prior, whichwere provided with 7-10 cm mud substrate. Tea seed was added at 100 ppm to eradicate naturally
occurring predators in the mud and lime was applied at 100 ppm subsequently. Chicken manure andurea were applied initially at 1250 kg·ha-1 and 100 kg·ha-1 a week before stocking and added weekly at
a rate of 625 kg·ha-1 and 50 kg·ha-1, respectively to maintain green water condition. Tanks were filledwith seawater with a salinity range of 30-35 ppt. Pond green water was inoculated in the tanks toprovide initial algal population. Each tank was equipped with aeration line to provide sufficientdissolved oxygen level.
Stocking and feeding: L. vannamei post larvae (PL 14) were purchased from a private hatchery (DobeExport International). The shrimps were acclimatized in a ten-tonner rectangular tank with same
salinity and temperature of the hatchery water and were fed to satiation twice a day. Stocking in theexperimental tanks was done early morning on the third day after obtaining the fry at a rate of 1
individual·liter-1. Initial weight and length of the shrimps were 17.85 mg and 1.49 cm. First feeding
was done a day after stocking based on 2.5% body weight. Subsequent feeding was adjusted based on
the actual body weight. Feeding ration was administered four times a day at 8 am, 10 am, 1 pm, and 4pm.
Water quality and natural productivity monitoring: Phytoplankton and microbial-floc population in
the rearing water were monitored weekly and physico-chemical parameters such as temperature,salinity, dissolved oxygen, and pH were checked daily. Temperature and dissolved oxygen wasmeasured using portable DO meter, pH with portable pH meter, and salinity with a refractometer.
Dominant phytoplankton, zooplanktons, and microbial flocs were counted weekly using a standard
haemacytometer under a compound microscope.
Growth and survival monitoring: Weight of the shrimps was monitored weekly to assess growth andadjustment of the feed ration. The shrimps were harvested after 15 days and counted individually. One
hundred (100) representative samples from each tank were weighed using 1.0 g precision electronicbalance and length measured using Vernier caliper to the nearest 0.01 cm. To estimate the specificgrowth rate (SGR), food consumption rate (FCR), and survival rate (SR), the following formulas wereused: SGR = [(ln final weight − ln initial weight) /days] ×100. Where: ln = natural logarithm of final
and initial weight. FCR = weight of feeds consumed/weight gained and SR = (recovered stocks/total
stocks) × 100.
Statistical analysis: To determine significant differences in the water quality parameters, microbial
floc and phytoplankton counts, growth, survival, yield, and FCR between treatments, T-test forindependent sample was used.
RESULTS AND DISCUSSION
Water Quality
Good water quality is essential in the success of shrimp nursery operation. Table 1 shows the minimum,
maximum, and mean levels of these parameters all throughout the duration of the culture period. The
mean daily values recorded during the experiment fall under the optimum range for culture of L.
vannamei. Moreover, the results of all the water quality parameters showed no significant difference
between the two treatments. The mean salinities of the two treatments were at 37.1 ppt and 36.7 ppt,
respectively. Ponce-Palafox et al., (1997) found out that the optimum range for best survival andgrowth of L. vannamei was between 33-40 ppt. Dissolved oxygen is one of the most important waterⒸISERD123

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quality parameters, minimum DO standard for good growth of shrimps is at 3 ppm (Fast and Boyd,
1992). The mean dissolved oxygen concentrations of the two treatments were at 5.0 ppm and 5.1 ppm,
respectively. The temperature readings were relatively stable throughout the culture period in all theexperimental tanks, which fall under the optimum temperature for shrimps at 26°C to 33°C. Mean pH
in the two treatments was at 7.6 and 7.5 with very minimal fluctuation until the end of the experiment.
The recorded pH, fall under the optimum pH in aquaculture systems, at 7.5 to 8.5 values.
Table 1 Dissolve Oxygen, pH, temperature and salinity of water in Pacific white shrimp(L. vannamei) nursery culture with different fertilizers
Treatment/Parameters

Salinity (ppt)
Min

Max

Mean

Dissolved Oxygen

Temperature (oC)

Min

Min

Max

Mean

pH

Max

Mean

Min

Max

Mean

4.8
5.2
5.0a
26.7
29.0
Inorganic Fertilizer (Urea) 33.7 40.0 37.1a
Organic Fertilizer
32.0 39.0
36.7a
4.5
5.7
5.1a
26.4
29.0
(Chicken Manure)
Means with different letters indicate significant differences between treatments (P<0.05).

27.6a

7.6

10.2

8.1a

27.6a

7.5

10.2

7.6a

Phytoplankton and Microbial Flocs
Phytoplankton play a significant role in stabilizing the whole pond ecosystem and in minimizing thefluctuations of water quality. A suitable phytoplankton population enriches the system with oxygen
through photosynthesis during day light hours and lowers the levels of CO2, NH3, NO2, and H2S.
During the first week of the experiment there was no significant difference in the phytoplankton
densities between the two treatments (Table 2). Common phytoplankton observed were diatoms and
Chaetoceros species. A day after the 3rd fertilization, the algae bloomed, manifested by dark green
coloration of the water in the tanks applied with urea. Mean phytoplankton count in these tanks
increased from 372,500 + 2,500 cells·ml-1 to 513,333 + 11,273 cells·ml-1 and was significantly higher
compared to the tanks fertilized with chicken manure. Generally, the phytoplankton densities all
throughout the experiment were relatively low compared to the healthy phytoplankton abundance
reported by Cordova et al. (1998) in ponds applied with organic and inorganic fertilizer at 530,000980,000 cells·m-1. The denseness could be attributed to the use filtered seawater. Pond green water was
only added in the tanks to provide initial algal population.
Phytoplankton aggregates with microorganisms in the aquaculture system to form microbial flocs.
Bio-flocs or the microbial flocs are a mixture of microorganisms (bacteria, phytoplankton, andzooplankton), algae, and other particles (Jorand et al., 1995). Typical flocs are irregular by shape, havea broad distribution of particle sizes, which are fine, easily compressible, highly porous, and permeable
to fluids (Lee Chen, 2004). Microbial floc or flocculated particles were observed to be increasing as
shown in Table 2. The build-up rates of the floc on the 2nd week followed the standard community
succession principle wherein from a clear water condition, algal bloom follows, and bacterial
communities are established when the water turns to brown. Build up of flocculated particles in the two
week time was relatively low.
The microbial flocs observed in the experiment were visibly large and distinct under the
microscope. Optimum water quality conditions were important in maintaining healthy population of
microbial flocs and these were met during the experiment. High dissolved oxygen in the system was
not only essential for the shrimps but also for the metabolic activity of the cells and structure of the
microbial flocs. A trend towards larger and more compact flocs at higher dissolved oxygen
concentrations was noted by Wilen and Balmer (1999). Temperature was also important in microbial
floc morphology. Krishna and Van Loosdrecht (1999) observed that higher temperatures (30-35°C)
resulted in bulking of the sludge due to the excessive production of extracellular polysaccharide, thusintermediate water temperature of 20-25°C would be best to obtain stable microbial flocs. Similarly,ⒸISERD124

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pH has an effect on microbial floc; according to Mikkelsen et al., (1996) changes in pH determine thestability of bio-flocs present in the system.
Table 2 Mean phytoplankton and microbial floc count in the water of Pacific white shrimp(L.vannamei) nursery culture with different fertilizers
Treatment
Inorganic Fertilizer (Urea)

Phytoplanktons (cell density ml-1)
Initial
Day 7
372,500 + 2,500 a
513,333+ 11,273a

Microbial Flocs (cell density ml-1)
InitialDay 7
723 + 13a
797+ 17a

Organic Fertilizer (Chicken Manure) 365,833 + 3,819 a
423,333 + 3819 b
732 + 38a
Means with different letters indicate significant differences between treatments (P<0.05).

836+ 15a

Growth and Survival
A day after the 3rd fertilization, the algae bloomed in the tanks applied with urea which resulted to massmortality of all stocks. However, the fatality could not be attributed to the increase in phytoplankton
density because it was relatively lower compared to a healthy phytoplankton bloom (Cordova et al.,1998). Furthermore, dissolved oxygen remained at its optimum level and apparently was not the causeof mortality. One possible reasons of the fatality could be the increase of NH3 in the system triggeredby the addition of urea. In the experiment conducted by Das et al., (2005) application of organic andinorganic fertilizer increased inorganic nutrients including ammonia. Application of inorganic fertilizer
gave peak values of nitrogen species such as ammonia, nitrite and nitrate earlier during first to second
week. Although natural food production was enhanced by applying organic and inorganic fertilizers,
the results showed that weekly application of urea at 50 kg·ha-1 significantly affected survival, causingmass mortality of stocks. On the other hand, survival of shrimps in tanks fertilized with chicken
manure was 92.68%; with specific growth rate (%·day-1) of 14.05 in terms of weight and 18.17 interms of length and total yield of 128.37 g·m-1. Lara-Anguiano et al., (2013) found out that L.
vannamei culture in tanks with zero water exchange using organic fertilizer (molasses) had higher
survival and production rates and reduced ammonia concentrations toward the end of the experiment
while the use of inorganic fertilizer caused increased nitrogen and phosphorus.
CONCLUSION
Periodic fertilization using chicken manure at a rate of 625 kg·ha-1 improved feed conversion rate aswell as shrimp survival and production within this experiment. Moreover, the results indicate thatweekly periodic application of urea at a rate of 50 kg·ha-1 without any water replacement in tanks
during the nursery of L. vannamei is not viable.
RECOMMENDATIONS
Further studies should design experiments that include the measurement of other water quality
parameters such as NH3, nitrites, nitrates, total suspended solids, and microbial evaluation such as total
plate count and Vibrio count. It is also very interesting to determine the density of the zooplankton in
the water vis-à-vis the feeding incidence.
ACKNOWLEDGMENT
We would like to express our sincerest gratitude to Engr. Ramon Alegre of DOBE Export International
for free Vannamei fingerlings; Mr. Dionisio Colantro for the use of facility of Central Bangus HatcheryⒸISERD125

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

at Barangay Lawis, Pangangan Island, Calape; 4th year BS Fisheries students for the assistance of theexperiment.
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Apun-Molina, J.P. and Klanian, M.G. 2013. Effects of inorganic and organic fertilization on physicochemicalparameters, bacterial concentrations and shrimp growth in Litopenaeus vannamei cultures with zero waterexchange. Journal of the World Aquaculture Society, 44 (4), 499-510.
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McIntosh, D., Samocha, T.M., Jones, E.R., Lawrence, A.L., Horowitz, S. and Horowitz, A. 2001. Effects of twocommercially available low-protein diets (21% and 31%) on water and sediment quality, and on the
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Ponce-Palafox, J., Palacio, C.A. and Ross, L.G. 1997. The effects of salinity and temperature on the growth andsurvival rates of juvenile white shrimp (Penaeus vannamei (Boone, 1931). Aquaculture, 157, 107-115.
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Research article
erd

Ecotoxicology of Copper on Freshwater Fish with Different
Water Hardness on the Mekong River, Lao PDR
NAKSAYFONG KHOUNNAVONGSA
Faculty of Agriculture, Khon Kaen University, Khon Kaen, Thailand
Email: nakstudent@gmail.com

CHULEEMAS BOONTHAI IWAI*
Integrated Water Resource Management Research and Development Center in Northeast Thailand,
Khon Kaen University, Khon Kaen, Thailand

THAM C. HOANG
Institute of Environmental Sustainability, Loyola University Chicago, Chicago, USA
Received 23 February 2015

Accepted 11 September 2015(*Corresponding Author)

Abstract The aquatic resources of the Mekong River are important to support the livelihoods ofa large percentage of 60 million or more people living in the Lower Mekong Basin. A study on
the impact of heavy metals on tropical freshwater fish in the Mekong River is needed.
Ecotoxicology of copper on freshwater fish was studied using field-collected water from two
local sites along the Lower Mekong Basin in Lao PDR, which focused on two different water
hardness. In this study, US EPA method was used for the acute toxicity test to larvae Labeorohita with 7 different copper concentrations (0, 0.02, 0.09, 0.16, 0.23, 0.3, and 0.37 mg/L) in
moderately hardness of water (108±0.00 mg/L as CaCO3) and (0, 0.02, 0.03, 0.04, 0.05, 0.09,
and 0.13 mg/L) in soft hardness of water (20±2.83 mg/L as CaCO3). The mortalities of fish
were observed at 24, 48, 72, and 96 hr. The results clearly showed that amount of mortalities
were increased from low to high copper concentrations. The 96-hr LC50 values of copper onlarvae L. rohita with moderately hardness and soft hardness of water were 0.106 and 0.038
mg/L, respectively.
Keywords acute toxicity, copper, Labeo rohita, the lower Mekong basin

INTRODUCTION
The Mekong River is the 12th longest river in the world in terms of volume of water. The river runs forapproximately 4,350 km from China through five countries, namely Myanmar, Lao PDR, Thailand,
Cambodia, and Viet Nam. The millions of people living in different parts of the Lower Mekong Basinrely on some extent on the water resources of the Mekong River Basin for food supply andsustainability of their livelihoods (MRC, 2010a), due to the fact that the resources have potential tocontribute to economic development of the countries. If not properly planned, managed, and monitored,
it could also exert tremendous pressure on the basin’s ecological health, livelihoods, and water quality.
Copper in the aquatic environment is usually related to anthropogenic sources rather than natural
sources (McNeely et al., 1979). Industrial sources of copper include mining, electroplating, petroleum
refining, metal works, and foundries. Copper is a micronutrient for both plants and animals at low
concentrations and is recognized as all plants and animals (Kapustka et al., 2004). Concentrations ofcopper have been reported from 0.03 to 0.23 µg/L in surface seawaters and from 0.20 to 30 µg/L in
freshwater systems (Bowen, 1985). However, it may become toxic to some forms of aquatic life atelevated concentrations.
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Water hardness is one of the water qualities, usually expressed as mg/L CaCO3. It substantiallyaffects metal toxicity but seemingly has little effect on the toxicity of organic chemicals (Sprague,
1985; Mayer, 1988; Inglis, 1972). The relation of water hardness to metal toxicity concerning the lethal
tolerance of freshwater fish to copper, is mainly dependent to the hardness of the water; as theincreasing hardness reduces the uptake rate of copper by gill tissue. One hypothesis suggested thatcalcium-magnesium hardness may act intrinsically upon cell-membrane permeability at the gills (Spearand Pierce, 1979). Therefore, the objective of this study was carried out on the tropical fish species
Cyprinidae, Labeo rohita to evaluate acute toxicity of copper with different water hardness tocontribute the ecotoxicology data for the management of aquatic environment towards environmental
quality standard revision in Lao PDR.
METERIALS AND METHOD
Location and sampling: The study sites were conducted at two different locations along the Lower
Mekong Basin in Lao PDR by focusing on different water hardness. The first study site was Vientiane,
the capital city (Lao PDR), located at 17°58´1.18´´N/ 102°35´1.66´´E. The city is around 692,900
inhabitants with a density of 176 people per km2 (ADB, 2000). Municipal sewage is normallydischarged into That Luang wetland and is consequently discharged into the Mekong Riverdownstream. The second study site was Pakxan district, located at 18°22´23.29´´N /103°39´43.85´´E.
Sources of pollution of this district included domestic, industrial waste, agricultural runoff, and mining
activities. The sites were chosen based on proximity and activities that potentially polluted the MekongRiver.
Reagents: All laboratory glassware, polyethylene, and polypropylene were soaked in 10% HNO3 acidfor at least 48 hr and rinsed with distilled water more than 3 times prior using. Deionized (DI) waterfrom a Millipore Milli-QTM ultra-pure (<18.2 MΩ/cm) water system was used throughout the study.
Water hardness was measured by EDTA titration method. A standard solution of copper 1000 mg/L
(Spectrosol grade, Merk) was prepared and diluted 100 mg/L with DI water for acute toxicity test.
Test specimen: Tropical freshwater fish, juvenile Cyprinidae Labeo rohita used in this investigation
were obtained from the hatchery maintained by Khon Kaen Department of Fisheries, Thailand. The test
specimen was conducted at Ecotoxicology Laboratory in Khon Kaen University. Juvenile L. rohita
were acclimated with tap water by a portable pump for a period of 48 hr at 25⁰C±1⁰C and arewere
more sensitive to toxicants than adults, appeared healthy, behaved normally, fed well, and had low
mortality in cultures12a. Therefore, juvenile L. rohita 1-14 day(s) of age were used for acute toxicity
test. At the beginning of bioassay, 25ºC±1ºC at a temperature control room with 16-hr light, 8-hr
darkness photoperiod. Moreover, copper concentrations for each test chambers were determined basedon the factorial experiment in Completely Randomized Design (CRD). One fish was randomly selected
at a time from the aquaria to complete the experiment of 7 treatments and 4 replications of 20 fish at
200 mL of test solution volume.
Data analysis: The acute toxicity of copper was determined as the median lethal concentration (LC50)
for 96 hr in each exposure time, with 95% confidence intervals. The analysis used the Probit Analysis
function of SPSS Version 17, statistical software.
RESULTS AND DISCUSION
Percent mortality of larvae Labeo rohita was evaluated at soft hardness and moderately hardness ofwater (20±2.83 and 108±0.00 mg/L as CaCO3). After being exposed in different periods of time,copper concentrations are resulted in highly significant difference (P<0.01), as presented in (Tables 1ⒸISERD129

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

and 2). The LC50 values of copper to larvae L. rohita at 24, 48, 72 and 96-hr for 20±2.83 mg/L as
CaCO3 were 0.083 (0.069-0.106), 0.065 (0.06-0.071), 0.055 (0.045-0.069), and 0.038 (0.021-0.077)
mg/L; and for 108±0.00 mg/L as CaCO3 were 0.271, 0.157, 0.129, and 0.106 mg/L, respectively. The
result of LC50 values with 95% confidence limits of copper are summarized in (Table 3) which clearly
indicates that at 20±2.83 mg/L as CaCO3 soft hardness of water was more toxic than 108±0.00 mg/L as
CaCO3 moderate hardness to larvae L. rohita.
Table 1 Percent mortality of larvae Labeo rohita at 20±2.83 mg/L as CaCO3 soft hardness at
exposure time with different copper concentrations% mortality on exposure time

Exposure concentration, (mg/L Cu)

24hr
48hr
72hr
96hr
0
0±0f
0±0e
4±3e
10±4e
0.02
1±3ef
3±3e
10±6e
18±10de
0.03
6±3df
14±3d
20±4d
24±9d
cd
c
d
0.04
11±5
21±3
24±3
29±5d
c
c
c
0.05
14±8
25±4
39±6
54±10c
0.09
46±3b
69±5b
75±9b
80±9b
a
a
a
0.13
86±5
91±3
98±3
100±0aF-test
***
***
***
***
C.V. %
17.63
9.71
13.7
17.08
Note:Values
Value
mean
SD (n=4).
Difference
littersaindicate
a significant
difference(p<0.01)
byNote:
arearemean± SD±(n=4).
Difference
litters indicate
significant
difference (p<0.01)
by one-way
ANOVA
analysiswith lsdanalysis
comparison
one-way
ANOVA
with lsd comparison.

Table 2 Percent mortality of larvae Labeo rohita at 108±0.00 mg/L as CaCO3 moderately
hardness at exposure time with different copper concentrations% mortality on exposure time

Exposure concentration, (mg/L Cu)
0
0.02
0.09
0.16
0.23
0.3
0.37
F-test
C.V. %

24hr
3±3d
4±8d
5±0d
13±3d
40±8c
59±10b
76±9a
***
24.38

48hr
4±5d
10±11cd
14±3c
19±3c
63±9b
95±4a
96±5a
***
14.4

72hr
6±6e
15±14de21±3cd
26±3c
66±9b
98±3a
99±3a
***
14.72

96hr
9±9e
20±17de30±0cd
34±6c
68±9b
99±3a
100±0a***16.11

Note: Values are mean ± SD (n=4). Difference litters indicate a significant difference (p<0.01) by one-way ANOVA
analysis with lsd comparison

Acute toxicity of copper in soft water hardness with copper concentration 0.13 mg/L, themortality at 96 hours of exposure was 100%. On the other hand, 100% mortality at 96 hours inmoderately water hardness was observed at copper concentration 0.37 mg/L, due to the toxic effect ofheavy metals on freshwater organisms related to hardness (Kim et al., 2001; Plye et al., 2002; Rathor
and Khangarot, 2003; Markich et al., 2006).

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Comparing the effect of copper at two different water hardness on larvae L. rohita, it wasobserved that copper at the soft water had high toxic to the fish with LC50 value of 0.038 (0.021-0.077)
mg/L, whereas copper at the moderately hardness of water was less toxic with LC50 value of 0.106
mg/L. It could be seen that the tropical freshwater fish was potentially sensititive to toxic elements.
Fish can have a quick response to various copper concentrations in the form of increased surface
movements were observed in the first few hours of the experiment, which normalized within 24hr of
exposure, thereafter fish settled on the bottom of the chamber. The response of fish mortality with
exposure time is shown in Fig. 1. In freshwater, as water hardness increased, heavy metal toxicity
decreased due to competition between metal ions and calcium and magnesium ions for the uptake sitesof organisms (Javid et al., 2007; Kim et al., 2001; Pyle et al., 2002; Ebrahimpour et al., 2010).
According to Penttinen et al., (1998), the uptake of calcium and magnesium ions by the cell membranecaused it to stabilize, and this reduced its permeability to metal ions. Water hardness reduced metal
toxicity by saturating gill surface binding sites with Ca2+ to the exclusion of metal cations (Pyle et al.,2002).
Table 3 Lethal concentration (LC50 to 95% confidence limits) of copper to larvae Labeo rohita
at exposure time
LC50 (Medium Lethal Concentration) mg/L
95% Confidence Limits for conc.
24hr
48hr

72hr

96hr

20±2.83 mg/L as CaCO3
soft hardness

0.083(0.069-0.106)

0.065(0.06-0.071)

0.055(0.045-0.069)

0.038(0.021-0.077)

108±0.00 mg/L as CaCO3
moderately hardness

0.271
-

0.157
-

0.129
-

0.106
-

Note: (-) =95% Confidence limit (lower-upper value exposure time

Fig. 1 Relation of percent mortality of larvae Labeo rohita to exposure copper concentrations
with 2 different water hardness.

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CONCLUSION
The toxicity of copper on larvae Labeo rohita under low water hardness was higher than in high water
hardness. The results of this toxicity tests for copper contribute to ecotoxicology data to the
management of aquatic environment towards environmental quality standard revision in Lao PDR.
ACKNOWLEDGEMENTS
This research project was funded by Integrated Water Resource Management Research andDevelopment Center in northeast Thailand, Khon Kaen University; and the research collaboration
project between Loyola University Chicago and Khon Kaen University supported by International
Copper Association, Ltd. (ICA).
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ADB. 2000. Country environment review, Lao’s People Democratic Republic. Policy Coordination Unit, AsianDevelopment Bank.
Bowen, H.J.M. 1985. In D. Hutzinger (ed.), The handbook of environmental chemistry, Part D, The naturalenvironment and biogeochemical cycles, Springer-Verlag, New York, 1, 1-26.
Ebrahimpour, M., Alipour, H. and Rakhshah, S. 2010. Influence of water hardness on acute toxicity of copperand zinc on fish. Toxical. Ind. Health, 21, 361-365.
Inglis, A. and Davis, E.L. 1972. Effects of water hardness on the toxicity of several organic and inorganic
herbicides to fish. U.S. Fish Wildl. Serv. Tech. Pap., 67, Washington, D.C., USA.
Javid, A., Javed, M. and Abdullah, S. 2007. Nickel bio-accumulation in the bodies of Catla catla, Labeo rohita
and Cirrhina mrigala during 96-hr LC50 exposures. Int. J. Agric. Biol., 9, 139-142.
Kapustka, L.A., Clements, W.H., Ziccardi, L., Paquin, P.R., Sprenger, M. and Wall, D. August 19, 2004. Issue
paper on the ecological effects of metals. Submitted by ERG to U.S. Environmental Protection Agency, Risk
Assessment Forum, Washington, D.C., USA.
Kim, A.D., Gu, M.B., Allen, H.E. and Cha, D. 2001. Physiochemical sectors affecting the sensitivity of
Ceriodaphnia bulba to copper. Environ. Monit. Assess., 70, 105-116.
Markich, S.J., King, A.R. and Wilson, S.P. 2006. Non-effect of water hardness on the accumulation and toxicity
of copper in freshwater macrophyte (Ceratophyllum demersum). How useful are hardness-modified copper
guideline for protecting freshwater biota? Chemosphere, 65, 1791-1800.
Mayer, F.L. and Ellersieck, M.R., 1988. Experiences with single-species tests for acute toxic effects on
freshwater animals. Ambio, 17, 367.
McNeely, R.N., Neimanis, V.P. and Dwyer, L. 1979. Water quality sourcebook, A guide to water quality
parameters. Inland Waters Directorate, Water Quality Branch. Ottawa, Canada.
MRC. 2010. The Mekong river report card on water quality, Assessment of potential human impacts on Mekong
river water quality. June 2010, Mekong River Commission, Vientiane, Lao PDR, 2, 1-15.
Penttinen, S., Kostamo, A. and Kukkonen, J.V.K. 1998. Combined effects of dissolved organic material andwater hardness on toxicity of cadmium to Daphnia magna. Environ. Toxical. Chem., 17, 2498-2503.
Pyle, G.G., Swanson, S.M. and Lehmkuht, D.M. 2002. The influence of water hardness, pH and suspended solids
on nickel toxicity to larva fathead minnows (Pimephales promelas). Water, Air, Soil Pollut., 133, 215-226.
Rathor, R.S. and Khangarot, B.S. 2003. Effects of water hardness and metal concentration on a freshwater
Tubifex tubifex Muller. Water, Air, Soil Pollut., 142, 341-356.
Spear, P.A. and Pierce, R.C. 1979. Copper in the aquatic environment: Chemistry, distribution and toxicology.
National Research Council Canada No. 16454, Associate Committee of Scientific Criteria for Environmental
Quality. Ottawa, Canada.
Sprague, J.B. 1985. Factors that modify toxicity, In Fundamentals of aquatic toxicity. Rand, G.M. and Petrocelli,S.R., Eds., Hemisphere Publishers, Washington, D.C., Chap. 6, USA.

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Research article
erd

Agricultural Extension and Advisory Services in Bosnia,
Montenegro and Serbia: An Overview
SNEZANA JANKOVIC
Institute for Science Application in Agriculture, Belgrade, Serbia

ALEKSANDRA DESPOTOVIC
University of Podgorica, Podgorica, Montenegro

SINISA BERJAN*
University of East Sarajevo, East Sarajevo, Bosnia and Herzegovina
E-mail: sinisaberjan@yahoo.com

HAMID EL BILALI
Mediterranean Agronomic Institute of Bari (CIHEAM-IAMB), Valenzano, Bari, Italy

NOUREDDIN DRIOUECH
Mediterranean Agronomic Institute of Bari (CIHEAM-IAMB), Valenzano, Bari, Italy

VEDRAN TOMIC
Institute for Science Application in Agriculture, Belgrade, Serbia
Received 13 February 2015

Accepted 7 October 2015(*Corresponding Author)

Abstract Agriculture is still important for socio-economic development in rural areas of Bosnia,
Montenegro, and Serbia (BMS), especially in terms of employment and income generation.
Good extension is recognized as a key to agricultural development. The paper aims to provide
an overview on public agricultural extension and advisory services (AEAS) in BMS. It is basedon an extended secondary data review and primary data collected by questionnaires with rural
people, as well as semi-structured interviews and focus group discussions with agriculturaladvisors and extension specialists carried out in the years 2012-2013. Current agriculturalextension structures has mainly been developed in the last two decades with international
donors’ help. Public extension structures exist besides other advisory services providers.
Advisors use many groups and individual extension methods. Advisory services face manyfinancial, management, and technical problems. Extension agents spend most of their working
hours doing administrative tasks and lack systematic professional in-service training offers.
Agriculture multifunctionality and the increasing rural economy diversification represent a real
challenge for agricultural extension services. Public extension is largely focused on crop andanimal production while rural development is only partially served. Rural advisory work is
restricted to the activities of individual extension agents, as well as NGOs, donor projects, andprivate advisors. The involvement of other actors in rural extension work is crucial if the system
is to meet rural people’s needs. AEAS have been trying to address the emerging challenges
through modernization of their extension approaches and communication media, as well as
diversification and decentralization of their services. Nevertheless, there are still someweaknesses that should be overcome. Developing a pluralistic, participatory, decentralized,
farmer-led, and market-driven advisory system is a milestone in the process of promoting ruralinnovation and diversification, and harmonization with the European Union’s acquis.
Keywords agriculture, extension, advisory services, Bosnia, Montenegro, SerbiaⒸISERD133

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INTRODUCTION
Despite the increasing diversification of the rural economy in the three countries of the Western
Balkans (WB) - Bosnia, Montenegro, and Serbia (BMS) - agriculture still plays an important socioeconomic role. The share of agriculture sector in gross domestic product amounts to 8.2% in Bosnia(EC, 2014a), 8.8% in Montenegro (EC, 2014b), and 11.4% in Serbia (EC, 2014c). The primary sector
employs 18.9% of the total labor force in Bosnia (EC, 2014a), around 4.5% in Montenegro (EC,2014b), and 21.3% in Serbia (EC, 2014c). Agricultural sectors in BMS are characterized by theprevalence of small family farms. Rural areas lag behind in terms of socio-economic development andstill face many problems. The share of rural population is around 61% in Bosnia, 36% in Montenegro,
and about 45% in Serbia (World Bank, 2014).
Easy and timely access to reliable and updated information is crucial for agricultural and ruraldevelopment (ARD). Good extension is recognized as a key to agricultural development (USAID,
2012) and can contribute to improving the welfare of farmers and other people living in rural areas(International Initiative for Impact Evaluation, 2010). One can simply say that “extension is getting
knowledge to farmers so they will make a positive change” (USAID, 2012). Advisory service iscommonly used as an alternate term for extension services. Apart from their conventional function ofproviding knowledge and technology to improve agricultural productivity, agricultural advisory
services are also expected to link farmers to markets, promote sustainable production techniques, etc.
(Swanson, 2008; Swanson and Rajalahti, 2010). Agriculture multifunctionality and rural economy
diversification are changing dramatically the classical crop production-centred mission of agriculturalextension and advisory services (AEAS). They need to provide a wider range of services to a morediverse clientele to improve their capacity to access, adapt, and use knowledge, inputs and services(World Bank, 2008). For extension to be successful, it needs to include credible content, effective
delivery, and be relevant to, and applicable by clients (USAID, 2012). In the WB, current agriculturalextension structures have been developed mainly within the last two decades with the help ofinternational donors. Public extension structures exist besides other providers such as NGOs andcommercial extension agents (FAO, 2011).
The paper aims at providing an overview on public AEAS in Bosnia and Herzegovina (BiH),
Montenegro, and Serbia with a particular focus on governance, financing, and extension approaches.
METHODOLOGY
The paper is based on an extended cross-checked secondary data review (e.g. FAO,USAID, European
Commission (EC), Ministries of Agriculture in BMS, World Bank, etc.) and primary data collected byquestionnaires with 108 rural households in BiH (winter 2012), 106 in Montenegro (autumn 2013), and
104 in Serbia (spring 2013). Questionnaires dealt, among others, with access of rural people to services
provided by AEAS. A special attention was devoted to services regarding the off-farm sector and ruraldevelopment. Moreover, semi-structured interviews and focus group discussions with agriculturaladvisors and extension specialists were carried out in the years 2012-2013. The prepared checklist forinterviews dealt with many issues regarding AEAS in BMS such as (i) governance and organization
structure; (ii) financing; (iii) human resources; (iv) role in building social capacity; (v) decentralization;(vi) gender; (vii) and advisory approaches, methods, and media. All secondary data were criticallyanalyzed by key informants from the AEAS. Some recommendations were made to improve the AEAS
performance in BMS.

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RESULTS AND DISCUSSION
Agricultural Extension and Advisory Services in Bosnia and Herzegovina
AEAS, as known in practice world-wide,started to exist in Bosnia in 2002. They are organized on
entity level: Agricultural Advisory Service of the Republic of Srpska (AAS-RS), cantonal agriculturalextension services in the Federation of BiH (FBiH), and the Department of Extension Services in
Brcko District. In May 2002, the Agricultural Extension Service of RS (AES-RS) was establishedwithin the Ministry of Agriculture, Forestry and Water Management of RS (MAFWR-RS). Two years
later, the Government of RS established the Agency for Providing Services in Agriculture (APSA), asa separate organization with a wide range of activities including agricultural extension. In January 2013,
APSA and the Agency for Animal Breeding and Selection were integrated in the AAS-RS, which was
one of the five departments within the MAFWM-RS. The AAS-RS is headquartered in Banja Luka andthere are seven regional offices i.e. Banja Luka, Gradiska, Prijedor, Doboj, Bijeljina, Sokolac, andTrebinje; where 36 advisors and 24 administrative staff (36.7% female) work for 221,000 rural
households in the RS. The extension system includes 77 municipal based advisers - within the
Department for Economic and Social Affairs - in most areas (MAFWM-RS, 2010). In the FBiH, theextension system was established at Canton level but the commitment of most Cantons was minimal
and no central services were established to support the system. Field advisors were part of themunicipal administration (FAO, 2011).
The AAS-RS is financed by the MAFWM-RS budget. All services provided by Bosnian public
advisory systems are free; advisors’ work is paid for with state, entity or municipality money (FAO,
2011). Besides public extension services, many institutions provide advisory services such as
cooperatives, agricultural and veterinary institutes and stations, as well as private actors.
Advisors use many group extension and communication methods (e.g. lectures, seminars,
demonstrations, field days, events, etc.) and individual methods (e.g. farm visits, contacts in extension
offices, phone calls). The main media used are the internet, leaflets, posters, brochures, and mass media.
Advisors provide services dealing mainly with agriculture production, processing and marketing (i.e.
vegetables and fruit growing, animal husbandry, processing and quality of agro-food products, agroeconomy). In the RS, out of the 36 extension agents, 33 are agriculture engineers that have general
educational orientation while the number of specialists is modest. The fact that the majority of the field
staff is agricultural experts, it induces a strong focus on production techniques and a relative preference
given to large farms (FAO, 2011).
Advisory services face many finance, management, and technical support problems. According to
the vice-minister in charge of AASRS (January 2015), the main problems faced by the public
agricultural extension system are (Pasalic B., pers. commun.): different levels of extension service
development between Bosnian entities, uncompleted/weak legislative (at the entity and state level),insufficient coordination between RS and FBiH extension services, low number of extension agents,
limited funding, weak participation in international projects, undeveloped system of extension agents’training, low interest of farmers for training, and weak collaboration with the research institutions.
According to FAO (2011), advisors spend most of their working hours doing administrative tasks
related to incentive measures. Bosnian extension agents lack systematic offers of professional training
as there is no systematically planned and performed in-service training program. However, there aredonor projects that provide training on a broad range of agriculture and rural development issues.
Extension and Advisory Services in Serbia
In Serbia, agricultural extension service started its initial development during the 50’s of the lastcentury (Zivkovic et al., 2009). Nowadays, the network of professional extension services in Serbia isⒸISERD135

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coordinated by the Institute for Application of Science in Agriculture (IASA), which is under the
auspices of the Ministry of Science. About 251 field advisors and administration staff (40.3% female)are employed in 34 regional offices by the Serbian public extension. AEAS in Serbia is composed bypublic extension and private advisory services. Donor projects (i.e. World Bank project) provided
extension agents with a sound base of technical (and partially methodological) knowledge and skills,
before being left on their own (FAO, 2011).
Support for public services in agriculture (e.g.extension service, veterinary and phytosanitary
services, etc.) is provided but the share of dedicated agricultural budgetary funds is small. Within thegeneral services sector, the greatest proportion of funds is directed to extension services or to financing
agricultural expert service (34-56 %) (Bogdanov and Bozić, 2010).
The majority of the field staff within the system is agricultural experts from the former system. In
fact, the majority of advisors are age over 40 years. This strengthens two biases: the strong focus that isstill directed towards production techniques and the relative preference given to large farms withrespect to small and medium holdings (FAO, 2011). Serbian public agricultural extension is mainly
addressed to commercial family farms and lesser attention is paid to small producers. Usually, small
producers must go by themselves to ask for advice (Petrović et al., 2009). Approach to farm families isbased mainly on individual contacts (sample farmer). Direct display methods include demonstration
plots, field visits, field days and workshops. Extension workers also organise public lectures. Different
media are used in information dissemination such as leaflets, brochures, Radio, TV and the internet.
The ISAA went a step ahead regarding provision of trainings to advisors in the few last years, as
during the period 2010-2014 more than 40 practical training courses were organized for extension
agents related to farm management, modern technologies in agricultural production, skill development,
EU integration, and environment protection and sustainable development.
Public extension has an intensive cooperation with applied research institutions. Moreover,extension stations apply research by themselves. There is a regular cooperation with universities
especially in Vojvodina autonomous province, where a university department developed andimplements an extension monitoring system.
Extension agents provideinformation and advice on national subsidy programs. Nevertheless,according to FAO (2011), the Serbian public extension provides farmers and rural dwellers only
partially with information and support on rural and agriculture tourism. However, Serbian extension
services have recently started providing information on national and international rural development
programs by the initiation of Rural Development Offices (RDOs). RDOs and individual municipal
advisors provide also support for the initiation of associations.
Monitoring of advisory work is fairly advanced in Serbia, having a considerable database onadvisors’ activities, farmers’ needs and the results of on-farm research. However, monitoring is more
about examining the activities of advisors than documenting the impacts of advisory work. There aremany best practices that can be shared with neighbouring countries (FAO, 2011). Nevertheless,
Serbian extension services face many problems in dealing with producers, as well as finance andmanagement problems, overload with non-extension activities, low number of extension agents, etc.
(Petrović et al., 2009).
Extension Services in Montenegro
Montenegro has a relatively simple agricultural education, extension, research, and information system
institutional set up. The main institution is the Biotechnical Institute that is the main partner of the
Ministry of Agriculture and Rural Development (MARD) (EC, 2011). The Biotechnical Institute islegally a part of the University of Montenegro and is financed from its budget, but the Livestock
Selection Service (LSS) and Plant Production Extension Service (PPES) are financed by the MARD
(EC, 2011; MARD, 2012).
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LSS was initiated in 2000 and has performed four main groups of activities: animal breeding andherd improvement program, advisory services, realization of support measures to farmers, and carryingout AMIS program - Agrarian Market Information System (MARD, 2012; Markovic and Bovic, 2010).
The first activity, animal breeding and herd improvement program, takes a major part of working time(Markovic and Bovic, 2010). PPES, established in 2003, aims at improving crops yield and products
quality. It performs three main activities: advisory services, implementation of support measures, andcarrying out of AMIS program (EC, 2011; MARD, 2012). At present it has 19 staff (academics ortechnicians) who work in seven regional centres (Bar, Bijelo Polje, Berane, Cetinje, Herceg Novi,
Niksic, and Podgorica).
PPES uses different methods in everyday work. It gives expert advice and recommendations tofarmers in the field, and organizes educative trainings, round tables, workshops, and seminars on
different topics in plant production (MARD, 2012). It also provides general information on its website
and publishes flyers and brochures (FAO, 2011). Radio and TV programs are also used to inform
farmers. Up-to-date market information is provided to the national radio station to be broadcast in aweekly program (Stanisic Vukota-Director of PPES, pers. commun.).
Common challenges for both LSS and PPES is the implementation of indicators of performanceand monitoring and the improvement of the extension staff’s abilities and expertise through regulartrainings (Markovic and Bovic, 2010). Moreover, the advisory services have sporadic cooperation with
NGOs, private extension providers and farmers’ associations but good cooperation with research
centres, input suppliers, and processors (FAO, 2011).
There is in every Montenegrin municipality a kind of advisory service for agriculture which
engages one or more employees (Stanisic V., pers. commun.). However, this service inherited from theprevious system many burdens and its function is more focused on office work than to giving advices
directly to farmers (Markovic and Bovic, 2010).
Montenegrin advisory services provide a limited support for the diversification of rural
livelihoods and income generating activities. Moreover, they also support social capital building andstrengthening activities. This is exemplified by the support for the initiation of processing andmarketing associations (Stanisic V., pers. commun.).
Agricultural Extension and Advisory Services: User Needs and Challenges Ahead
According to the field survey, the need for agricultural advisory services is very high among thesurveyed rural households in Bosnia (50.0%), Montenegro (60.4%), and Serbia (31.7%). Despite quitea high need, very few respondents (12.0%) in Bosnia use services provided by extension while inMontenegro (41.5%) and Serbia (37.5%); the share of households that in reality use services is higher.
In all the three countries, needed help is mainly related to advices about market and its players,veterinarian service, cooperatives membership benefits, marketing, plant protection, fruit pruning,products’ processing, legal-economic advices, animal husbandry, tillage operations, and manure use,etc. The majority of those who need help are agricultural households while mixed ones need less help
and non-agricultural households do not need any help.
Public extension services in the WB in general and in BMS in particular are strongly focused on
production techniques, while farm management, markets and marketing, regional rural development
and the promotion of producer organizations are only partially served. Extension agents are only able
to thinly cover the areas of farm economy and farm development planning. Rural development is not
systematically supported by the public AEAS due to an overload of work, and to the general lack ofknowledge (on projects and programs) and skills (on group facilitation and group management) (FAO,
2011). In fact, advice on rural development is generally restricted to the activities of some motivatedadvisors in the public service, as well as to NGOs, private service providers, and donor projects dealing
with rural development.
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AEAS must be flexible, user-driven, and focused on local problems. Both public and private
extension resources should be fully used; accountability to clients increased and more responsibilities
transferred to the private sector. Linkages between AEAS and public stakeholders, as well as researchand education institutions dealing with ARD should be strengthened. Agricultural education, training
and research systems should be strengthened as well. It is essential that the research system engages
universities, private sector research, and civil societies and stimulate the scaling-up of innovations(World Bank, 2008). Research needs to be more integrated into the agricultural sector transformation
by moving from agricultural research and development to Agricultural Research for Development(AR4D). The agricultural education and training system needs to adapt and to meet the new dynamics
of agricultural innovation. Education institutes have to offer more relevant subject matters for
agricultural and rural innovation (Daane, 2010).
CONCLUSIONAEAS are back on the agenda and widely recognized as critical to rural development. Rural areas
diversity in BMS, as well as the increasing diversification of the rural economy represents a challenge
for agricultural advisory services. Advisors use many group and individual extension methods andmedia. Moreover, advisory services face many financial, management and technical problems. AEAS
is largely focused on crop and animal production, while rural development is only partially served. In
fact, public extension agents provide only partial information for rural development and rural
livelihoods diversification.
Higher attention should be paid to supporting extension and advisory services in BMS to allow
them to fully assume their role in the promotion of rural innovation, diversification, multi functionality
and sustainability.It is necessary to develop a pluralistic, participatory, bottom-up, decentralized,
farmer-led, and market-driven advisory system. The involvement of other actors in the rural extension
work is crucial if the system is to keep up with rural people’s expectations and to meet their needs. The
programme for continuous training of field advisors should be strengthened and upgraded, especially in
Bosnia and Montenegro.
The need for supporting agricultural advisory services is significant in BMS. It is truly essential in
the time of institutional weakness of the sector that the technical and technological unpreparedness offarmers and rural people should meet complex requirements associated with the policy reform as it isneeded to align the ARD policy and practice in BMS with the European acquis. Moreover, wellperforming AEAS is a conditio sine qua no for achieving sustainable agricultural and ruraldevelopment.
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org/table/3.1 (accessed on 4/1/2015).
Živković, D., Jelić S. and Rajić Z. 2009. Agricultural extension service in the function of rural development.
Thematic proceedings of the 113th seminar of EAAE, 9-11 December 2009, Belgrade, 517-524.

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Research article
erd

Relation Between Rural Diversification and Governance: Some
Insights from Bosnia, Montenegro and Serbia
HAMID EL BILALI
Mediterranean Agronomic Institute of Bari (CIHEAM-MAIB), Valenzano, Bari, Italy

SINISA BERJAN*
University of East Sarajevo, East Sarajevo, Bosnia and Herzegovina
E-mail: sinisaberjan@yahoo.com

ADRIANA RADOSAVAC
Faculty of Agriculture, University of Novi Sad, Novi Sad, Serbia

ALEKSANDRA DESPOTOVIC
University of Podgorica, Podgorica, Montenegro

SNEZANA JANKOVIC
Institute for Science Application in Agriculture, Belgrade, Serbia

NOUREDDIN DRIOUECH
Mediterranean Agronomic Institute of Bari (CIHEAM- MAIB), Valenzano, Bari, Italy
Received 19 January 2015

Accepted 16 October 2015(*Corresponding Author)

Abstract Rural areas in the Western Balkans are experiencing two profound changes i.e.

increased diversification of the rural economy and new governance models and arrangements.
The paper aims at providing some insights into linkages and interdependences between rural
livelihoods, diversification, and rural governance in Bosnia, Montenegro, and Serbia (BMS). In
particular three different conceptual frameworks were used to analyze governance-ruraldevelopment, governance-rural livelihoods and governance-rural economy diversification
linkages. Input data to substantiate the conceptual frameworks in the rural contexts of BMS
were the results of surveys dealing with rural governance and rural livelihoods diversification
performed in the period 2011-2013. There is a linkage between agricultural and ruraldevelopment governance and coordination, and exploitation of the full potential for rural
livelihoods and economies diversification. Governance is relevant for rural livelihood
diversification and rural development both as process and structure. Governance - comprising
institutions, policies, and processes - affects access to and use of livelihood assets with impacts
on diversification. Diversification is also affected by a set of sectoral policies that go beyond
agriculture. Government policies can act as a stimulus to the diversification of economic
activities of rural households. Governance - as actors and institutions - also affects
diversification. Governance arrangements determine the range of actors involved in policy
design. Depending on actors involved and their interests the policy character and architecture
are defined. Meanwhile, also diversification has impacts in terms of governance in rural areas.
In fact, changes that happen in rural areas, thanks to diversification, influence also rural
governance and policy. Many new rural actors are consulted about rural development which
was not the case in the past. Diversification affects the typology of actors that are involved inpolicy design which has implications in terms of priority policy measures definition. These
insights should be taken into consideration to redesign rural development policy.
Keywords rural areas, diversification, governance, Bosnia, Montenegro, SerbiaⒸISERD140

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INTRODUCTION
Agriculture plays an important socio-economic role in the Western Balkan (WB) in general and Bosnia,
Montenegro, and Serbia (BMS) in particular. The share of agriculture in GDP amounts to 7.4% in
Bosnia (EC, 2013a), 9.5% in Montenegro (EC, 2013b), and 10.1% in Serbia (EC, 2013c). Agricultural
sector employs 20.6% of the total labor force in Bosnia (ASBiH, 2012), 5.7% in Montenegro (EC,2013b), and 21% in Serbia (EC, 2013c). Rural areas lag behind in terms of socio-economic
development and still face many problems. The share of rural population is 61% in Bosnia (UNDP,
2013), 38% in Montenegro (Arcotrass et al., 2006), and 43% in Serbia (RDNS, 2010). Rural areas in
BMS are experiencing two profound changes i.e. increased diversification of the rural economy andnew rural governance models. Sustainable development of rural areas cannot be based only on
agricultural development, rural economies should also be diversified by developing off-farm and nonfarm income-generating activities.
Diversification means exploiting all the multifunctional functions of agriculture while introducing
new off-farm and non-farm income-generating activities. Households’ income can be increased byadopting many livelihoods strategies (Chambers and Conway, 1992). In terms of agriculture, theconcept of diversification is often taken to mean a shift away from the production of surplus
commodities to those which may be expanded – a focus on the diversification of output – withemphasis placed on diversification into other agricultural products. Alternatively, it is used to describe
the strategy of utilizing excess capacity of farm production factors, involving the use of farm resources
for non-agricultural activities – a focus on diversification of resources. A third sense of diversification– a focus on the location of the activity – is also considered (OECD, 2009).
Agricultural and rural development (ARD) processes in general and farm activity diversification
initiatives in particular should be well governed in order to yield expected outcomes and impacts.
Governance comprises mechanisms, institutions and processes of decisions making andimplementation through which persons and groups articulate their interests, exercise their legal rights,
meet their obligations, and mediate their differences (Cheema, 2005). Governance analysis focuses on
the actors involved in decision-making and implementing the decisions made and the structures thathave been set in place to arrive at and implement decisions (Sheng et al., 2007).
The paper aims at exploring relations and interdependences between rural livelihoods
diversification and rural governance in BMS.
METHODOLOGY
The paper is based on an extended secondary data analysis and different surveys. Three different
conceptual frameworks were used to analyze governance-rural development, governance-rural
livelihoods and governance-rural economy diversification linkages. The conceptual framework
developed by IFPRI highlights linkages between governance and rural development. It shows why
governance decentralization and rural service delivery are so important for sustainable ARD (IFPRI,
2007; IFPRI, 2007b). The second conceptual framework of Shtaltovna (2007) focuses on relations
between governance and diversification. It shows how and in which way governmental support should
be targeted in order to contribute to rural development. In particular, it highlights how governancearrangements in local rural areas can influence the diversification of rural economy through theirimpact on household assets (Shtaltovna, 2007). The rural livelihood framework of the UK Department
for International Development (DFID) was used for getting insights into linkages between governanceand livelihood strategies. This conceptual framework shows how governance structures and processes
influence livelihoods. The framework highlights as well how livelihood strategies – including
diversification – are affected by a number of governance structures and processes (Satgé et al., 2002).

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Input data to substantiate the conceptual frameworks were the results of surveys dealing with rural
governance and rural livelihoods diversification. As for ARD governance, questionnaires were sent via
email to 120 actors in Bosnia and Herzegovina (BiH) in winter 2011, to 50 in Montenegro in winter2012, and to 120 in Serbia in summer 2013 (Berjan et al., 2014). Respondents included purposively
selected representatives of public, civil society and international organizations. Concerning rural
livelihood diversification, the field questionnaire surveys were carried out in winter 2012 with 104
randomly chosen households’ heads in south-eastern Bosnia (Berjan et al., 2013), with 50 households
in autumn 2013 in northern Montenegro and in spring 2013 with 99 households in south-western
Serbia.
RESULTS AND DISCUSSION
Analyzing linkages between rural governance and rural livelihoods diversification is about studying
policies that are put in place to foster diversification, as well as the stakes of the different involved
rural actors and how they have evolved over time with the increasing pace and level of diversification.
It goes without saying that there are differences among the three countries but there are also somecommonalities. From this point of view, it is very interesting to take a stock of the experience of othercountries, whose rural areas have been engaged in the process of diversification for many years, inorder to get insights about what policies should be enacted, as well as what are the implications of rural
economy diversification in terms of ARD policy. This is particularly the case of many OECD countries.
Creating an improved environment for farm activities, diversification requires the efforts of many
actors. The roles of government actors are often critical for facilitating, catalyzing, and mediating
initiatives taken by other private and civil society stakeholders (IFAD, 2010). Local governments aswell as civil society and the private sector have an important role to play in the provision of
infrastructure and public services in rural areas with a special emphasis placed on agricultural services
governance (IFPRI, 2007b). The system of governance of rural development policies has witnessed theprogressive coming into play of several levels (national, regional, intermediate and local); many more
actors than before; and new instruments and approaches (Mantino et al., 2010).
Governance arrangements in rural areas can influence the diversification of rural economy
through their impact on household assets. In fact, governance arrangements can influence effectivenessand efficiency of different activities that are performed by governmental institutions in rural areas.
They affect governance as a process i.e. partnerships, networks and cooperation agreements.
Governance arrangements also affect the modus operandi, visions and missions of local governancestructures, i.e. institutions and organizations, that deal with RD in general and rural livelihood
diversification in particular (cf. Shtaltovna, 2007).
Despite recurrent discourses about participation and bottom-up approaches in governance andpolicy arena, the spectrum of actors involved in the different stages of the policy cycle in the three
countries remains limited. In particular, the involvement of the private sector and civil society
organizations in rural policy design and formulation is generally still marginal. This is particularly trueat central level (i.e. entity level in BiH) while the situation is much better at local level. However, sincethese countries are still largely centralized the funds at disposal of local councils and administrations
are very low which limits their maneuvering space and the scope of their interventions.
Insufficient institutional capacities at the local level hinder economic diversification development
and it is necessary to further strengthen local structures seen as key drivers for diversification of rural
economy. In order to face this challenge, about a third of municipalities in Bosnia established funds for
local economic development and support small and medium sized enterprises (SMEs) (FAO-ROECA,
2012).
Governance surveys results show that many actors have a stake in rural economy diversification.
These stakeholders have various backgrounds but share a similar goal which is the socio-economicⒸISERD142

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development of their territory. Each single actor contributes to new activity formation and support
assets. In particular, stakeholders recognize the true value of assets, especially the human and social
capital, as new possibilities for diversification of their local rural economies. It was also noticed thatthe emergence of new participatory governance structures and arrangements allow mobilization of
local assets and resources as well as diversification of rural activities in the non-farm sector.
The larger share of the surveyed households believes that local and national governments (also
entities’ governments in the Bosnian case) should make more effort in helping them compared to what
they have done until now. Disproportion in help demand and help delivery by local councils and state
institutions in south-eastern Bosnia and western Serbia is huge and Bosnian and Serbian rural
households feel that primary responsibility lies on local and state/entity level governments while itseems that the surveyed Montenegrin rural population is quite satisfied with local and state authorities’
engagement in the development of rural areas.
Another key factor explaining why respondents in south-eastern Bosnia and western Serbia shareopinion that authorities do not take adequate care about rural areas is also the lack of trust in them. The
capacity of local NGOs, beside capacity of municipalities, is important to support economic
diversification. Willingness of NGOs and local authorities to work together is also important. However,it seems that civil society organizations yet do not have enough developed capacities to cope with thesituation in rural areas (FAO-ROECA, 2012). Effective local institutions that deliver goods andservices must be in place in rural areas to sustain positive rural livelihood outcomes. These institutional
structures condition livelihood outcomes through community capacity-building and institutional
strengthening (Frankenberger, 2001).
Government intervention is among the main factors that influences the diversification of farmhouseholds into non-farm activities. If governments want to foster diversification, they need to makesure that policies are in place, whether sectoral or broad, and do not put unintended obstacles in theway of such diversification (OECD, 2009b). For rural policy to be more effective, small fragmented
programs should be replaced by an integrated rural development policy, that rural farm and non-farmhouseholds can benefit from, which requires a strong horizontal coordination effort at all governancelevels.
Rural development policies should stimulate development of diverse income-generating activities
outside agriculture. Many of the elements of rural development policies, such as improvements ininfrastructure and the provision of local services, are crucial for economic and social sustainability inrural areas (OECD, 2010). As highlighted by IFPRI (2007b), it is important to improve the ability of
the rural population to demand services and hold service providers accountable. It is also crucial toincrease the capacity and effectiveness of local service providers. This is also related to politicaldecision-making processes with respect to the formulation of rural development strategies andagricultural policies.
The survey on rural household livelihoods diversification showed that adequate access of all rural
people to services and structures (including infrastructure) necessary to engage in diversification
endeavors was far from optimal. This is in part explained by the fact that the survey – especially in BiH
and Montenegro – was performed in remote rural areas. However, the quality of rural services and theperformance of structures in charge of service delivery was a problem in most of rural areas in thethree countries.
A number of policy measures designed to encourage diversification, have been introduced incertain OECD countries. These include vocational training and business development schemes (OECD,2010). Human capital strengthening and rural dwellers’ capacity-building efforts must focus on service
delivery as well as risk-management skills (Frankenberger, 2001).
Weak human capital is a problem in the three studied rural regions. What is alarming is that it
seems that the situation is getting worse because of migration of most of well-educated young rural
people to cities or even abroad. This undermines one of the most important endogenous assets andresources of rural areas that can be exploited in the diversification journey. In fact, it is well-knownⒸISERD143

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that, in contrast with agricultural activities, non-farm activities require a range of new skills that mostof rural people do not have. This highlights the importance of the role of extension and advisory
services as well as of other institutions dealing with capacity building and human capital strengthening
in rural areas. These actors should work together and coordinate their activities in order to address thischallenge. Coordination with international development agencies dealing with business skills
development is also crucial.
Different factors regarding livelihoods interrelate and affect each rural household quality of life.
Governance structures and processes directly influence livelihoods. Human, physical, social, financial
and natural capital in different combinations are affected by a number of governance structures andprocesses and how people use their capital in order to achieve desired livelihood outcomes throughdeveloping different livelihood strategies (Satgé et al., 2002) such as diversification (Goodrich, 2001).
Governance decentralization and rural service delivery are so important for sustainable ARD.
Decentralized political system would better answer needs of local communities. Strengthening andimproving service providers’ capacities will directly affect the supply and quality of services (IFPRI,
2007). A vibrant service sector is both vital for a prosperous local economy and crucial for meeting theneeds of the rural population (OECD, 2010b).
Some regulations governing tax, social security, land zoning, and labor markets may complicate
diversification in countries where agriculture is not treated the same as other sectors. The impact oflabor regulations and the social security and tax systems on diversification essentially depends on how
agriculture is defined under national regulations/systems. When a narrower definition is applied,
diversification activities increase the administrative requirements and complexity of the farm operation(OECD, 2009). In some countries access to other forms of support (e.g. income support), may belimited if farmers earn too much income from non-agricultural activities (OECD, 2010).
While there are references to diversification in national agricultural and rural legislation of thethree countries - which is mainly the outcome of the process of alignment with the EU acquis in ARD what is missing is a concrete long-term strategy to promote diversification on the ground as well as afavorable institutional and legal environment to foster diversification.
Harnessing farm diversification especially in the non-farm economic activities requires improving
the environment, thus strengthening incentives and reducing risks for the actors involved. This
involves improving rural infrastructure and services, as well as governance and the business climate toencourage private investment by providing business development and financial services suited to thesmall rural entrepreneurs’ needs (IFAD, 2010).
CONCLUSION
Promoting rural development through farm activity diversification poses numerous policy andgovernance challenges because it requires coordination across sectors, across levels of government,
and between public and private actors. There is a need of a paradigm shift in the approaches of thethree countries to accommodate such important challenges. Farm activity diversification initiatives andprocesses should be well governed in order to yield expected impacts. Governance is relevant for therural livelihood diversification and rural development for both process and structure.
Governance (cf. policies and processes) affects access to and use of capitals with impacts ondiversification. The pace of diversification depends on whether regulations are favorable fordiversification or not. Governance (cf. actors and institutions) affects diversification. Governancearrangements determine the range of actors that are involved in policy design. Depending on actors
involved and their interests, the policy character and architecture are defined. For rural policy, to be
more effective, it is of paramount importance that all actors, including also the civil society and rural
dwellers, are engaged in preparing a common approach to rural economy diversification.

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Meanwhile, changes that happen in rural areas, thanks to diversification, influence also rural
governance and policy. Many new rural actors are consulted about rural development, which is not thecase in the past. In fact, diversification affects the typology of actors that are involved in policy design
which has implications in terms of definition of priority policy measures. This change in rural actor
landscape represents a dramatic change in the rural policy arena with respect to some decades ago
when mainly agricultural actors are involved in rural policy formulation.
The insights provided by this paper should be integrated in rural policy in order to effectively
unlock the growth potential of rural areas in Bosnia and Herzegovina, Montenegro and Serbia. Thatbeing said, the main weakness of this study is that, it is to a large extent of quantitative and empirical.
Therefore, further quantitative studies are needed to better elucidate and understand relations andlinkages between diversification and governance in rural areas in the three countries.
REFERENCES
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EuroCare GmbH (Germany) and AKI (Hungary).
ASBiH. 2012. Anketa o radnoj snazi 2012 (Labour Force Survey 2012). Agency of Statistics of Bosnia andHerzegovina (ASBiH), Sarajevo. Available at: http://www.bhas.ba/tematskibilteni/lfs_bh.pdf
Berjan, S., El Bilali, H., Sorajic, B., Driouech, N., Despotovic, A. and Simic, J. 2013. Off-farm and non-farmactivities development in rural south-eastern Bosnia. International Journal of Environment and Rural
Development (IJERD), 4 (1), 130-135.
Berjan, S., El Bilali, H., Sorajic, B., Mrdalj, V., Raickovic, J. and Driouech, N. 2014. Agricultural and ruraldevelopment in Serbia, Governance, policy cycle and coordination. Turkish Journal of Agricultural andNatural Sciences, Special Issue 2, 1832-1837.
Chambers, R. and Conway, G. 1992. Sustainable rural livelihoods: practical concepts for the 21 st century.
Institute of Development Studies Discussion Paper 296, Brighton.
Cheema, G.S. 2005. Building democratic institutions, Governance reform in developing countries. Kumarian
Press Inc., New York.
EC. 2013a. Bosnia and Herzegovina: 2013 progress report. European Commission (EC), Brussels.
EC. 2013b. Montenegro: 2013 Progress Report. European Commission (EC), Brussels.
EC. 2013c. Serbia: 2013 progress report. SWD(2013) 412 final; European Commission (EC), Brussels.
FAO-ROECA. 2012. Analysis of economic diversification in Bosnia and Herzegovina. Preparation of IPARD
Sector Analyses in Bosnia and Herzegovina. Food and Agriculture Organization (FAO), Regional Office forEurope and Central Asia (ROECA), Budapest.
Frankenberger, T.R. 2001. A brief overview of sustainable livelihoods approaches. Food and Agriculture
Organization, Rome & Department for International Development of the United Kingdom, London.
Goodrich, R. 2001. Sustainable rural livelihoods, A summary of research in Mali and Ethiopia. Institute ofDevelopment Studies (IDS), Sussex.
IFAD. 2010. Rural poverty report 2011 - New realities, new challenges: new opportunities for tomorrow’s
generation. International Fund for Agricultural Development (IFAD), Rome.
IFPRI. 2007. Strengthening governance for rural development in developing countries. International Food Policy
Research Institute (IFPRI), Washington D.C.
IFPRI. 2007b. Governance for agricultural and rural development program. International Food Policy ResearchInstitute (IFPRI), Available online at: http://www.ifpri.org/sites/default/files/govbrochure_1.pdf
Mantino, F., Bolli, M., Fagiani, P. and Tarangioli, S. 2010. Report on policy delivery systems and their relations
with types of governance. models.http://mpra.ub.uni-muenchen.de/49975/1/MPRA_paper_ 49975.pdf
OECD. 2009. The role of agriculture and farm household diversification in the rural economy, Evidence andinitial policy implications. Organisation for Economic Cooperation and Development (OECD), Paris.
OECD. 2009b. The role of agriculture and farm household diversification in the rural economy of Canada.
Organization for Economic and Cooperation Development (OECD), Paris.
OECD. 2010. Agricultural policies and rural development, A synthesis of recent OECD work. OECD, Paris.
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OECD. 2010b. Rural policy reviews, Strategies to improve rural service delivery. OECD, Paris.
RDNS. 2010. Action plan 2011-2015. Rural Development Network of Serbia (RDNS), Belgrade.
Satgé, R., Holloway, A., Mullins, D., Nchabeleng, L. and Ward, P. 2002. Learning about livelihoods, Insightsfrom southern Africa. Periperi Publications (South Africa) and Oxfam Publishing, UK.
Sheng, Y.K. et al. 2007. Access to basic services for the poor, The importance of good governance. United
Nations Economic and Social Commission for Asia and the Pacific (UNESCAP), Bangkok.
Shtaltovna, A. 2007. Role of governance in the diversification of rural economy, Analyses of two Ukrainiancases. Master thesis. Master of Science in Rural Development. Ghent University, Belgium.
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Research article
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Promoting Gummy Guyabano (Anona muricata Linn.) Candy
REGUCIVILLA A. POBAR*
Bohol Island State University, Tagbilaran City, the Philippines
Email: regupobar@gmail.com
Received 13 March 2015

Accepted 30 October 2015(*Corresponding Author)

Abstract Guyabano fruit is from guyabano tree “Anone muricate”, a small tree, native toCentral America, the Caribbean, and South America, Guyabano can also be found in Mexico,
Colombia, Brazil, Peru, and Venezuela, and sub-Saharan African countries. The tree isadaptable to tropical climate and is currently cultivated for its fruits in most Southeast Asian
countries such as Malaysia, Indonesia, and the Philippines. Guyabano tree is usually 5 to 7
meters tall, with characteristics of fruit bearing, broadleaf, flowering, and evergreen trees.
Guyabano or soursop is known to fight cancer, diabetes mellitus, and other illnesses. It isnutritious, as it is high in carbohydrates, particularly significant amount of fructose, vitamin C,
vitamin B1, and vitamin B2. With the mentioned benefits of Guyabano, the author is motivated
to come up with a product that allows convenient consumption, availability, and attractivenessfor all ages of consumers. In this study, the author ventured into producing a type of candy byusing pulp of Guyabano fruit. The study sought to determine the candy’s acceptability andpromoted its utilization to rural community. The study also identified shelf life andmarketability of the product. This study is an experimental research using four-point hedonic
scale in rating its acceptability in overall preference, appearance, texture, scent, taste, andaftertaste. A total of 100 participants rated the product consisted of 65 students and people fromrural communities and 35 faculty members. The result showed that both faculty and community
members had the same descriptive rating, in five attributes: overall preference, appearance,
texture, taste and aftertaste; however, they was a difference in their ratings for scent attribute;students rated only Like while the faculty members rated Like Very Much for this attribute. It
was also found that the product was marketable and could last for a month. It can be concluded
that Gummy Guyabano Candy is acceptable and can be prepared in the community because of
the availability of ingredients, tools and equipments and easy to follow procedures.
Keywords Guyabano, candy, gummy, Hedonic Tasting, sensory attributes

INTRODUCTION
Guyabano fruit can be called in several names such as soursop, custard apple, graviola, and guyabano.
Its scientific name is "Annona muricata." It is a green, pear-shaped fruit covered with soft spines.
Matured guyabano or soursop fruit weighs about 2 to 5 kilograms. It is ovoid and can be up to 18
centimeters in lenght.With thin skin and soft edible whitish fleshy and fibrous pulp, Guyabano black
seeds are inedible. It has a distinctive sweet-sour flavor that tastes like pineapple and strawberry with atang of sour citrus taste.
Guyabano trees bear fruits in 3 - 5 years after planting. They flower most months of the year but
the peak period is in May and June, and the fruits ripen in November and December.
It is one of the minor crops that is gaining popularity because of its economic uses and great
demand in processing industry, especially in producing guyabano drinks. The crop is now gaining its
prospect in the world market, therefore, expansion and more production should be encouraged to meetits demand. (bpi.da).

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Guyabano is widely known to possess medicinal properties like cancer fighting, diabetes mellitus
herpes inhibiting, anti-depressive, anti-bacterial, effect against Staph aureus and Vibrio cholera (Tesio,2013).
Guyabano is a nutritious fruit, rich in ascorbic acid, potash, phosphorous and calcium. The edible
portion is 70% with food energy of 63 calories and sugar content ranges from 4 to 14%. It is high incarbohydrates, particularly fructose. The fruit also contains significant amounts of vitamin C, vitamin
B1, and vitamin B2 (Barrette, 2013). Because of the health benefits, it has been on high demand fromconsumers. Restaurants and hotels sell them raw or as fresh ripe fruit as dessert or a snack item in aform of juice or shake. The green fruits are consumed as vegetable or used for meat sweetening. Its
juice is used for flavoring ice cream, sherbet, canning and for preparation or refreshing drinks. It may
also be processed into preserved food such as candy, jam, and jelly.
The researcher intends to introduce Guyabano to community in an easy and convenient way. The
method also includes preserving the fruits in a form of candy that can be consumed anytime andanywhere, without a concern of fruiting season. preserve the fruit after its fruiting month by preparing
it into a candy so that anybody can readily take healthy guyabano fruit comfortably anytime andanywhere.
Candy is a type of sweets or lollies, a confection that features sugar as a principal ingredient.
Unlike sweet pastries served as a dessert course at the end of a meal, candies are normally eaten
casually, often with fingers or as a snack between meals. Each culture has its own ideas of what
constitutes candy rather than dessert. The same food may be considered a candy in one culture and adessert in another.
Candy is also a source of empty calories, because it provides little or no nutritional value beyond
food energy. At the start of the 20th century, when undernutrition was a serious problem, especiallyamong poor and working-class people, and when nutrition science was a new field, the high calorie
content was promoted as a virtue. Researchers suggested that candy, especially candy with milk andnuts, was a low-cost alternative to normal meals (Labau, 2012). This study aims to produce a candywith Guyabano fruit, to have a finished product with is increased nutritional value.
In this study, gelatine is added to make the candy more gummy and more appetizing to theconsumers at all ages. According to LaBau (2013), gummy candies are made with a base of gelatine
and are often flavoured with fruit juices or extracts.Gelatine gives them a distinctive chewy texture that
ranges from soft to very firm, depending on the amount of gelatine used.
Gelatine is a protein obtained by boiling skin, tendons, ligaments, and/or bones with water. It is
usually obtained from cows or pigs. Gelatine is used as a thickener for puddings (such as Jell-O),
candies, marshmallows, cakes, ice cream, and yogurts. In this study, gelatine is mixed with guyabano
fruit pulp, so that the finished candy is more nutritious, and therefore can be used as alternative food tonormal meals (Cunningham, 2013).
OBJECTIVESThis study ventured to produce gummy candy from the pulp of Guyabano fruit. It sought to identify the
ingredients, tools, and equipment to be used in producing the candy, and discover procedures which areeasy to follow. Further, the study sought to determine its acceptability in terms of overall preference,
appearance, texture, scent, taste, aftertaste, shelf life, and marketability. This study was conducted at
the Food Technology Laboratory of Bohol Island State University main campus of Academic Year2013-2014.

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METHODOLOGYThis is an experimental study where the products are subjected to sensory appraisal. According toWalker (2004), sensory appraisal is a scientific discipline used to evoke, measure, analyze, andinterpret reactions to those characteristics of food and materials as they are perceived by the senses ofsight, smell, taste, touch, and hearing. The product of this study was subjected to sensory analysis. A
total of 100 participants rated the product, 35 of them were teachers and instructors of Food
Technology, Technology and Livelihood Education, which were considered as experts in the field; and65 were students and people from rural community, acting as consumers of the product. After
preparing the candies, the finished candies were given to the two groups of participants to test the
product. A sensory score sheet of four point hedonic scale was utilized by the participants in rating the
product using the following numerical rating and descriptions: 1-Dislike Very Much, 2- Dislike, 3Like, and 4- Like Very Much. For purposes of analysis, the following ranges and descriptions werealso used: 1.00-1.75, Dislike Very Much; 1.76- 2.51, Dislike; 2.52 – 3.27, Like; and 3.28 – 4.00, Like
Very Much.
RESULTS AND DISCUSSION
Ingredients, Tools and Equipment
Gummy Guyabano Candy was produced by mixing together 2 cups of blended Guyabano pulp, 1 cupof unflavored gelatine, 2 cups of centrifugal sugar, and 2 tablespoons of glucose.
The candy was prepared with the use of a blender, a mixing bowl, a measuring cup, a measuring
spoon, a rubber scraper, a wooden ladle, a carajay pan, and a stove. It was prepared by washing the ripe
Guyabano fruit, separating skins and seeds, and blending the fruit pulp. In a mixing bowl, fruit pulp,
unflavored gelatine, and centrifugal sugar were mixed. The mixture was transferred to a carajay pan
and was cooked under moderate heat. When caramelization was almost reached, glucose was thenadded until the caramelization stage was attained.
Table 1 manifests that the faculty group rated the product as Like Very Much in all sensory
attributes with the average numerical rating of 3.52. Among the six sensory attributes, after taste
attribute got the highest rating of 3.77, which was Like Very Much. It was followed by taste andoverall attributes, the preference results showed a numerical rating of 3.57 and 3.54, respectively;
which all were described as Like Very Much. Texture attribute was rated at 3.37. Although, it showed
the lowest rating the descriptive rating was still in the Like Very Much range. The faculty group did
not like the chewy characteristics of the product.
The students and rural community group gave the product an overall rating of 3.45 with adescriptive rating of Like Very Much. Taste attribute got the highest rating of 3.69. It could be notedthat in this candy artificial flavoring was not added so the taste, which the respondents felt, was thenatural taste of the fruit. It could be deduced that the respondents liked the sour taste of Guyabano as it
was apparent in the finished product. Taste attribute was followed by aftertaste attribute, which had
overall preference with numerical ratings of 3.66 and 3.55, respectively. Normally, characteristics ofaftertaste attribute are quality, intensity, and duration. Quality describes the actual taste of the food,intensity conveys the magnitude of that taste, and duration describes how long the aftertaste of thatfood lasts. Foods that have lingering aftertastes typically have long sensation durations . In this study,
the taste of the product lingered longer making respondents rate high in aftertaste attribute. The three
sensory attributes, which were taste, aftertaste, and overall preference received a descriptive rating ofLike Very Much. This result indicated that the product was really acceptable. On the other hand, scentattribute was rated at 3.17 described as Like. This showed that the respondents did not like the smell of
the Guyabano which was very evident in the product. Aside from the rating of 3.17 which was theⒸISERD149

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

lowest rating but still under the descriptive rating of like in the scent attribute, the participantscommented that they did not like the smell of the finished candy. Usually good food and smell are
inextricable bound to one another. The product of the study although rated very high in taste, aftertaste,
and overall preference and was rated low in scent. It did not imply that the finished product was notgood but only the respondents did not like the natural smell of the Guyabano.
Talking about the appearance of the finished product, the respondents rated Like Very Much. The
appearance of a food or beverage influences crave ability and acceptance, before the product touches
the lips (Berry, 2013). This is because “we eat with our eyes before we ever smell or taste” (Shelke,2010). Visual appeal is why chefs put so much time and effort into plate presentation. “Color andappearance serve to entice the consumer” (Brown, 2012). The product of the study was molded into
heart and flower shapes in bite size with golden brown color, which the researcher believed to be thefactors that influenced the rating of the respondents. They liked the size, the color, and the form of the
product. It can be gleaned that product characteristics like color, size, and form could attract and ofcourse effected the judgment of the respondents in rating product appearance. When the ratings of twogroups were combined, the overall rating of Gummy Guyabano Candy was 3.49 or Like Very Much,despite the low rating of Like in the scent attribute given by the students and community group, which
had no effect on the entire rating of the candy.
Table 1 Participants’ rating of the productSensory attributes
Overall Liking

Rating
3.54

Faculty
Description
Like Very Much

Appearance Liking

3.43

Like Very Much

Texture Liking

3.37

Like Very Much

Odour Liking

3.49

Like Very Much

Community
RatingDescription
3.55
Like Very
Much
3.38
Like Very
Much
3.30
Like Very
Much
3.17
Like

Taste Liking

3.57

Like Very Much

3.69

Aftertaste Liking

3.77

Like Very Much

3.66

Overall Rating

3.53

Like Very Much

3.46

Like Very
Much
Like Very
Much
Like Very
Much

Overall rating
RatingDescription
3.55
Like Very
Much
3.40
Like Very
Much
3.33
Like Very
Much
3.33
Like Very
Much
3.63
Like Very
Much
3.72
Like Very
Much
3.49
Like Very
Much

Shelf Life of the ProductIn testing the product shelf life, the product had been placed in room temperature for two months anddaily observations on the product were done and properly recorded. It was observed that the changes in
the product took place on the thirtieth day where molds were found. It could be declared that the
product could be good for human consumption for a month. The occurrence of molds in the productindicated that it was no longer good to be eaten. According to Dr. Kung’u (2013), foods or feeds
contaminated with mold are risky and should be avoided at all times, eating such foods could result
food poisoning due to mycotoxin or bacterial contamination, or both.
Marketability
The product was potentially marketable because when it was displayed in an elementary school, all
was consumed in three days for three consecutive weeks. It was sold at two pesos per piece, a bit
expensive compared to other candies that were two pesos for three pieces or fifty centavos for eachpiece.
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CONCLUSION
It can be concluded that Gummy Guyabano Candy can be produced by the rural community as a value
added product of Guyabano fruit. It is easy to prepare since the ingredients are locally available in thelocality; the tools and equipment are also simple which can be found in kitchen of ordinary households;
the preparing procedures are easy to follow. It can be safely concluded that Gummy Guyabano Candyis generally acceptable.
RECOMMENDATION
It is recommended that the product be introduced to local community through the extension function of
the university. Since the product contains gelatine, this is not good for vegetarians. There is analternative chance of marketed gelatine for vegetarians called “agar agar”, which is derived from a typeof seaweed. Candy can be moulded into smaller size because bigger size can cause choking to smaller
children who might wish to eat the candy.
ACKNOWLEDGMENT
This undertaken research comes into fruition with a kind assistance from Bohol Island State University
administration, faculty members, and Food Technology students. In particular, the researcher isgrateful to Dr. Elpidio T. Magante, CE, Ed.D., University President, for the permission and warm
support in the conduct of the study. Acknowledgement is likewise given to the Campus Director Dr.
Nelson M. Patena and Mrs. Anelsa B. Sumalinog, the research assistant.
REFERENCES
Barret, M. 2013. Guyabano health benefits-revealing medicinal properties of an exotic fruit. Retrieved January 4,2014 from www.naturalsociety.com/guyabano-health-benefits-soursop-fruit/
Berry, D. 2013. Appearance matters. Retrieved December 10, 2014 from http://www.ddwcolor. com/appearancematters-excerpts-from-food-product-design-magazine-marchapril-2013-pp-28-32/
Brown, J. 2012. Why colour? Retrieved January 5, 2014 from www.ddwcolor.com/hue/why-color/
Cunningham, T. 2013. Gelatin. Retrieved February 16, 2014 from www.dailymail.co.uk/femail/article-3314562/
Guayabano (Bureau of Plant Industry) Retrieved September 3, 2013http://www.bpi.da.gov.ph/bpioldsite1/guide_guayabano.php
Kung’u, J. 2013. The health effects of eating mouldy foods. Retrieved December 2013 from: http://www.
drjacksonkungu.com.
LaBau, E. 2012. Gummy candy. Retrieved September 3, 2013 fromhttp://www.madehow.com/Volume-3/
Gummy-Candy.html
LaBau, E. 2012. How to make gummy candies. Retrieved February 12, 2014 from http://candy.about.com/
od/gumgelatinbasedcandy/r/gummy.htm
Shelke, K. 2012. DDW interviews industry expert on achieving industry sustainability. Retrieved February 5,
2013 from www.ddwcolor.com/kantha-shelke-on-achieving-industry-sustainability/
Tacio, H. 2013 The healing power of guyabano. Retrieved July 5, 2013 from http://www.sunstar.com.ph/davao/feature/2013/06/04/healing-powers-guyabano-285650
Vegetarianism. Retrieved July 6, 2013 from http://www.sunstar.com.ph/davao/feature/2013/06/04/healingpowers-guyabano-285650
Watson's Nobel Prize/ Plant Parts/ Starting a Farm/ Plant Fruit Trees! /Top Agricultural Commodities /Blog/News / Retrieved July 6, 2014 from http://www.cropsreview.com/soursop.html
Walker, G. 2004. Introduction to sensory analysis. Retrieved September 25, 2013 from http://sst-web.tees.ac. uk/external/U0000504/Notes/Sensory/SensoryIntro.htmlⒸISERD151

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

What is gelatin made of? Retrieved September 22, 2014 from http://www.peta.org/about-peta/faq/what-is-gelatinmade-ofⒸISERD152

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Research article
erd

Heavy Metal Contamination in Meat and Crustaceans
Products from Thailand Local Markets
MONTIP JANKEAW
Environmental Science Program, Faculty of Science and Technology, Valaya Alongkorn Rajabhat
University under the Royal Patronage, Thailand
Email: montip_06@hotmail.com

NATAGARN TONGPHANPHARN
Environmental Science Program, Faculty of Science and Technology, Valaya Alongkorn Rajabhat
University under the Royal Patronage, Thailand

RATTANAPON KHOMRAT
Environmental Science Program, Faculty of Science and Technology, Valaya Alongkorn Rajabhat
University under the Royal Patronage, Thailand

CHULEEMAS BOONTHAI IWAI
Integrated Water Resource Management Research and Development Center in Northeast Thailand,
Khon Kaen University, Thailand

NISA PAKVILAI*
Environmental Science Program, Faculty of Science and Technology, Valaya Alongkorn Rajabhat
University under the Royal Patronage, Thailand
Email: pakviali_n@hotmail.com
Received 23 February 2015

Accepted 30 October 2015(*Corresponding Author)

Abstract The aim of this study was to investigate heavy metal contaminations (cadmium,
chromium, and lead) in meat and crustaceans products from three markets of Pathumthani
province, Thailand. Heavy metals from beef, pork, chicken, scallop, and prawn were analyzed
by using ICP-OES. The results showed that the heavy metal concentrations ranges found inmeat and crustaceans’ products were 0.002-0.032 mg/kg for cadmium, 0.003-0.040 mg/kg forchromium, and 0.006-0.200 mg/kg for lead. The levels of heavy metal contamination in all
products are still below the food safety standard of Thailand. The maximum levels of metals inmeat and crustaceans products were found as follows: lead > chromium > cadmium, in the threemarkets. The results of this study provide valuable information to livestock and aquaculture
production for food-safety products, and for protection of human health.
Keywords heavy metals, meat and crustaceans products, local markets, food safety

INTRODUCTION
Human diet, meat, fish, and crustacean’s products provide well-known proteins, minerals, vitamins,
and trace element contents. Concerning about the effects of anthropogenic pollution, and heavy metal
contamination, it is a serious threat because of the toxicity, bioaccumulation, and biomagnification infood chain (Eisler, 1998). Not only do heavy metals have important positive roles in human life, butalso there are negative roles as well. Some of the heavy metals are considered essential, and theseinclude iron, zinc, and copper, while some other metals such as mercury, cadmium, lead, and arsenic
have toxic roles in biochemical reactions of our body (Divrikli et al., 2006). Non-essential elementsⒸISERD153

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

such as Pb, Cd, Cr, Ni considered as toxic and their presence in the body can cause profoundbiochemical and neurological changes in the body (Nielsen, 1982). All metals are toxic at certain levels
of intake, however, in contrast to elements such as arsenic chromium, copper, selenium, and zinc thathave useful biological functions, cadmium, lead, and mercury play no useful role and their intake
should be limited to avoid organ damage (Parekhan et al., 2014; Kramer et al., 1983).
In recent years, there are several studies that focus on the contamination of heavy metals, pesticide,and other toxic in raw food and environment (Iwegbue et al., 2008; Khalafalla et al., 2011; Pakvilai etal., 2012; Hussain et al., 2012; Aitbek, 2013). Samples of beef, veal, pork, chicken, and horsemeat
were analyzed for Ca, Cu, Fe, Mg, Mn, Ni, Zn, Cd, and Pb by Hecht and Kumpulainen (1995).
Furthermore, Mn, Cu, Zn, Cd, Hg, and Pb concentrations were determined in liver, kidney, and muscle
meat of ducks, geese, chicken, rabbits, and sheep slaughtered in northern of Poland (Falandysz, 1991).
Under certain environmental conditions, heavy metals might accumulate up to toxic concentrations.
Thus, heavy metals acquired through the food chain, as a result of pollution, are potential chemicalhazards threatening consumers.
The aim of this study was to assess heavy metal contamination, including Cd, Cr and Pb
concentrations, in meat and crustaceans products from local markets in Pathumthani province,
Thailand. Moreover, the data were assessed by comparing with the food safety standard of Thailand.
OBJECTIVE
The purpose of this work was to investigate heavy metal contaminations in meat products which werepurchased from three local markets in Pathumthani province, Thailand.
METHODOLOGY
Sample Collection
A total of 45 samples of meat and crustaceans products (beef, pork, chicken, scallop, and prawn) werecollected randomly from local markets in Pathumthani province. At each location, meat samples werecollected from three different local markets to provide replicate samples of each meat. According totheir types, all collected samples were stored in clean polythene bags and brought to the laboratory for
preparation and treatment. All samples were stored at -10oC until analysis (Parekhan et al., 2014).
Sample Preparation
Before being analyzed, meat and crustaceans products samples were put outside to melt at a room’s
temperature. All samples were washed with distilled water to remove any contaminated particles. Thensamples were chopped to small pieces using a ceramic knife, thoroughly mixed; weight 1-gram of meat
was placed in a test tube for the analysis. The meat was later digested by 5 ml concentration nitric acid(69%) in a water bath at 80oC for 15 minutes and cooled down to room temperature; the samples weredried in an oven at 135oC and cooled down to room temperature. One milliliter of Hydrogen peroxideacid (30%) was added and then filtered the supernatant using No.1 and No.48 filter paper.
The complete volume of the final solution was 50 mL in volumetric flask, and the determination ofheavy metal was conducted using an Inductively Coupled Plasma – Optical Emission Spectrometer(ICP-OES) ULTIMA2, HORIBA scientific, FRANCE. The samples were analyzed in triplicated. A
statistic using scientific program was used to calculate standard deviation and meanvalues. Linear
regression equations and regression coefficients (R2) of standard are presented in Fig 1.

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

(a)

(b)

(c)

Fig. 1 Calibration curve for determination of (a) cadmium (b) chromium (c) Lead
RESULTS AND DISCUSSION
The result for determination of the heavy metal residues in wet weight are shown in Table 1. Meat andcrustaceans products residue samples shown in Table 1 representing the heavy metals ranged from 33
to 100% of samples analysis while the samples were detected 100% of chromium and lead. Cadmium
found 33 % in pork, 44 % in scallop and prawn, and 56% in beef, respectively.
Table 1 Positive percentage of heavy metal residues in meat product samples
Meat and crustaceans products

Cd

Cr

Pb

Beef (n=9)

56

100

100

Pork (n=9)

33

100

100

Chicken (n=9)

nd

100

100

Scallop (n=9)

44

100

100

Prawn (n=9)

44

100

100

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IJERD – International Journal of Environmental and Rural Development (2015) 6-2

The result of the study showed that 33-100% of Cd, Cr, and Pb concentrations were found in allmeat products, Cd concentration was not found in chicken. Although, their concentrations are below
the food safety standard of Thailand, heavy metals can be harmful due to their potential to accumulate
in different parts of human body. Even in low concentrations, they can cause adverse health effects(Ikeda et al., 2000). Cadmium may accumulate in the human body and may induce kidney dysfunction,skeletal damage, and reproductive deficiencies (Commission of European Communities, 2001). Lead is
known to induce reduced cognitive development and intellectual performance in children, andincreased blood pressure and cardiovascular disease in adults (Commission of European Communities,
2001). Chromium is an essential element helping body to use sugar, proteins, and fat; at the same time
it is carcinogenic for organisms, thus excessive amount of Cr may cause adverse health effects(Parekhan et al., 2014).
Table 2 Mean concentration and standard deviation of heavy metal in meat and crustaceans
products samples (mg/kg)
Meat and crustaceans products

Cd

Cr

Pb

Beef (n=9)

0.024±0.018

0.020±0.010

0.040±0.049

Pork (n=9)

0.008±0.004

0.019±0.009

0.032±0.034

Chicken (n=9)

nd0.015±0.008

0.032±0.018

Scallop (n=9)

0.004±0.003

0.018±0.007

0.167±0.096

Prawn (n=9)

0.009±0.006

0.029±0.014

0.100±0.091

In Table 2, the results are presented as mean concentrations of a triplicate analysis of the sample
extracted. The Cd concentrations ranged from 0.004±0.003 to 0.024±0.018 mg/kg. Among the analysisof meat and crustacean product, the highest Cd level was found in beef sample at 0.024±0.018 mg/kg
but not found in chicken. The Cd concentration followed the order: beef > prawn > pork > scallop. The
study of Rahimi (2013) determined the Cd concentrations in goat, cow, sheep, and buffalo milks
collected from different regions in Iran. The study reported the amount of 0.74 ng/mL. Another studyof Pimonwan (2009) reported that the Cd concentration in seafood from Maung district, Rayong
province ranged from 0.009 to 0.31 mg/kg. But in comparison of a maximum Cd content of 0.05-0.1
mg/kg of the European Union (2008), the Cd content of this study was exceeded the standard
allowance. In general, Hech (1983) stated that Cd concentrations in meat increased with the age ofanimal and depended on the concentrations of Cd in the feed.
According to analyzed data presented in Table 2, the results ranged from 0.015±0.008 to
0.029±0.014 mg/kg of Cr concentration. Prawn was found the highest Cr level at 0.029±0.014 mg/kg,
while the Cr concentrations of other products were prawn > beef > pork > scallop > chicken. The Crvalues of the study were below those reported of Kwon and Lee (1999) at 0.18 to 0.25 µg/g of fishtissue in Masan Bay, Korea. Although, Cr3+ is an essential element that helps the body use sugar,
proteins, and fat; at the same time Cr6+ is carcinogenic for organisms (Institute of Medicine, 2003).
Lead is a toxic element that has no biological role and cause carcinogenic effects in marine biota
and humans. From the present study, Pb concentration had the highest concentration in the samples ascompared to the other elements. The Pb concentration in meat and crustaceans products ranged from
0.032±0.018 to 0.167±0.096 mg/kg. Scallop was found to have the highest Pb value at 0.167±0.096
mg/kg. The concentrations of Pb for other products were scallop > prawn > beef > pork, and chicken.
The Pb concentration in scallop (0.167±0.096 mg/kg) was similar to the study of Sankar et al. (2006),
which reported that Pb value of J. dussumerri was at 0.13 mg/kg. In addition, the study of Sivaperumal
et al. (2007) recorded 25% of Pb concentrations in finfish, shellfish, and other fishery products fromthe EU’s Indian coast. However, the EU’s acceptable limit for Pb concentration is 0.5-1.0 µg/g. The PbⒸISERD156

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

concentrations of this study were found to be lower than the acceptable limit suggested by theEuropean Union (2008).
0.25
Beef

concentration (ppm)

0.2

Pork

Chicken

0.15

Scallop0.1

shrimp

0.05
0

Cd

Cr
Market 1

Pb

Cd

Cr
Market 2

Pb

Cd

Cr

Pb

Market 3

Fig. 2 Comparison of heavy metal residues in meat samples
Fig. 2 shows of the heavy metal comparison by type and market location. Lead presents a higher
concentration than another compound in scallop of market 1 and 3, and prawn in market 1. Within
prawn samples, it was found higher chromium in markets 1 and 3 than in market 2. Market 3 wasfound to have higher chromium than other markets except in prawn from market 1. From the study, thePb levels of all samples were higher than other heavy metals trace. The result of this study indicatedthat the problem of Pb in food is more widespread.
CONCLUSION
The levels of heavy metal contaminations in meat and crustacean’s products from Thailand local
markets were determined and assessed by comparing contamination levels with permissible limits ofthe food safety standard of Thailand. However, all the heavy metal levels of this study were below theallowance of the food safety standard of Thailand. It is necessary to assess human exposure to thesevital metals through food consumption, as human is one of the top most consumers in the ecosystem.
ACKNOWLEDGEMENTS
We are grateful to Miss Sureerat Phonmasri for her assistance in sample collection and work inlaboratory for ICP-OES analysis Integrated Water Resource Management Research and Development
Center in Northeast Thailand, Khon Kaen University, Thailand.
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soil, water, vegetation and meat in the regions of East-Kazakhstan. Journal of Environmental Protection, 4,1292-1295.
Commission of European Communities. 2001. Commission regulation (EC) No. 221/2002 of 6 February 2002
Amending regulation (EC) No. 466/2002 setting maximum levels for certain contaminants in foodstuffs.
ⒸISERD

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Official Journal of the European Communities, Brussels, 6 February 2002.
Divrikli, U., Horzum, N., Soylak, M., and Elci, L. 2006. Trace heavy metal contents of some spices and herbal
plants from Western Anatolia, Turkey. International Journal of Food Science and Technology, 41 (6), 712716.
Eisler, R. 1998. Zink hazards to fish, wildlife and invertebrates, A synoptic review. US Fish Wildlife Service,
Biology of Reproduction, 85.
European Union (EU). 2008. Commission regulation (EC) No. 629/2008. Setting maximum levels for certain infoodstuffs. Official Journal of the European Union, L 173.
Farquharson, M.J., Geraki, K., Flakenberg, G., Leek, R. and Harris, A. 2010. The localization and micro mappingof copper and other trace elements in breast tumors using a synchrotron micro-XRF system. Applied
Radiation and Isotopes, 65, 183-188.
Falandysz, J. 1991. Manganese, copper, zinc, iron, cadmium, mercury and lead in muscle meat, liver and kidneysof poultry, rabbit and sheep slaughtered in the northern part of Poland, 1987. Food Additives andContaminants, 8 (1), 71-83.
Geraki, K. and Farquharson, M.J. 2001. An X- ray fluorescence for measuring trace element concentration inbreast tissue. Radiation physics and chemistry, 61, 603-605.
Ghimpeţeanu, O.M., Das, K., Militaru, M. and Scippo, M.L. 2012. Assessment of heavy metals and mineral
nutrients in poultry liver using inductively coupled plasma- mass spectrometer (ICP-MS) and direct mercury
analyzer (DMA). Bulletin UASMV, Veterinary Medicine, 69 (1-2), 258-266.
Hecht, H. and Kumpulainen, J. 1995. Essential and toxic elements in meats and eggs. Mittcilungsblattder
Bundesantalt fur Fleisch-forschung, Kulmbach, 34 (127), 46-52.
Hecht, H. 1983. Toxische scwermetalle in fleish und innerein verschie-dener tierarten. Fleischwitschaft, 63, 544558.
Hussain, R.T., Ebraheem, M.K. and Moker, H.M. 2012. Assessment of heavy metal (Cd, Pb AND Zn) content inlivers of chicken available in the local market of Basrah CITY, IRAQ. Bas.J.Vet.Res., 11 (1), 43-51.
Ikeda, M., Zhang, Z.W., Shimbo, S., Watanabe, T., Naktsuka, H., Mono, C.S., Matsuda-Inoguchi, N. andHigashikawa, K., 2000. Urban population exposure to lead and cadmium in east and southeast Asia. Sci.
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Iwegbue, C.M.A., Nwajei, G.E. and Iyoha, E.H. 2008. Heavy metal residues of chicken meat and gizzard andturkey meat consumed in southern Nigeria. Bulgarian Journal of Veterinary Medicine, 11 (4), 275-280.
Khalafalla, F.A., Ali, F.H., Schwagele, F. and Abd-El-Wahab, M.A. 2011. Heavy metal residues in beefcarcasses in Beni-Suef abattoir, Egypt. Vet Ital., 47 (3), 351-361.
Kramer, H.L., Steiner, J.W. and Vallely, P.J. 1983. Trace element concentrations in the liver, kidney, and muscleof Queensland cattle. Bulletin of Environmental Contamination and Toxicology, 30, 588-589.
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metal contamination in a coastal dredging area. Sci. Total Environ., 214, 203-210.
Nielsen, F.H. 1982. Ultra traces elements in human nutrition. A.R. Diss., Inc.,New York., 379-404.
Pakvilai, N., Prapamontol, T., Thavornyutikarn, P., Mangklabruks, A., Chantara, S. and Santasup, C. 2012.
Residues of synthetic pyrethroid pesticides in vegetables, fruit, sediment and water from an intensive
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Parekhan, A., Banaz, O.R. and Dler, M.S. 2014. Assessment of heavy metals in livers of cattle and chicken byspectroscopic method. IOSR Journal of Applied Physics (IOSR-JAP), 6 (1), 23-26.
Pimonwan, K., Linna, T. and Laddawan, R. 2009. Concentrations of cadmium and arsenic in seafood from
Muang district, Rayong province. J. Health Res., 4. 179-184.
Rahimi, E. 2013. Lead and cadmium concentrations in goat, cow, sheep and buffalo milks from different regionsof Iran. Food Chemistry, 136 (2), 389-391.
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and fish products from internal markets of India vis-à-vis international standards. Food chem. 102, 612-620.

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Research article
erdComparative Spatial Assessment of Regulating and Supporting
Ecosystem Services in Nay Pyi Taw, Myanmar
KAY KHAING LWIN*
Nagoya University, Nagoya, Japan
Email: kaykhaing.moecaf@gmail.com

KIICHIRO HAYASHI
Nagoya University, Nagoya, Japan

MAKOTO OOBANational Institute for Environmental Studies, Japan
Received 13 December 2014

Accepted 31 October 2015(*Corresponding Author)

Abstract Rapid urban development may induce deterioration in biodiversity and ecosystemservices (BD/ESs) at the global scale. According to Millennium Ecosystem Assessment (MA)
2005, it is well known that biodiversity provides benefits in the form of ESs. In particular, fourtypes of ESs (namely, provisioning, regulating, supporting, and cultural services) were definedin a previous study. Here, a case study was conducted in Nay Pyi Taw, Myanmar. First, theprimary unit values of each ES were obtained based on a literature review. Second, by utilisinga satellite image of Nay Pyi Taw from the Advanced Land Observing Satellite, land-use types
were classified into five categories: forest areas, urban areas, agricultural land, water areas, andbare land. Then, the unit values of each ES were applied to develop seven types of ESs andhabitat maps and a priority layer map was created using the Zonation software. The results
revealed the spatial distribution of ESs and the priority areas for conservation. In future, thismethod can be used to consider a wider range of ESs.
Keywords ecosystem services, land-use, zonation, Myanmar, biodiversity

INTRODUCTION
Ecosystem services (ESs) are the benefits provided by ecosystems and can be classified into four types
according to MA (2005): provisioning, regulating, supporting, and cultural services. ESs can help for
not only the environment, but also human's livelihoods. During the last decades, ESs has been
destroyed owing to development and increased economic and societal prosperity (MA, 2005). So themethods to identify priority areas for the provision of ESs need to be developed (Casalegno et al.,2014). Although scientific and political interest in ESs has increased, there are gaps in knowledge ofthe spatial distribution of ESs (Garcia-Nieto et al., 2013). In this context, spatial assessment of ESs
provides some indication of the role of spatial flows in the delivery of ESs (Serna-Chavez et al., 2013).
Although many studies have been conducted to assess ESs globally, few such studies have focused on
Myanmar, where 68% of the population live in rural areas (World Bank, 2012). This rural population
typically relies on ESs such as firewood, wood, food, etc. A new capital city, Nay Pyi Taw, wasdeveloped in Myanmar in 2006, with degradation of ESs occurring in the region during the course of
the development. Accordingly, an understanding of the characteristics of ES provision is important forconservation in this region.

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OBJECTIVE
The present study aims to understand the status of ES provision for different land use types in Nay Pyi
Taw, Myanmar. To achieve this, spatial analysis of ESs was conducted for the region. In mapping ESs,
land use/land cover classification was undertaken to help assess ES provision.
MATERIALS AND METHODS
Study Area
Myanmar, which was formerly known as Burma, is a country in Southeast Asia. Nay Pyi Taw(19°44′40.3"N, 96°07′46.1"E; city hall in Nay Pyi Taw) is a new capital city in Myanmar and wasfounded in 2006 in a previously undeveloped area. The city lies at elevations of 0-500 m and has slope
conditions of approximately 1-20q (FAO, Myanmar country profile). Its population is approximately
1,558,367 as of 2014 (Department of Population, 2014), and it covers a total area of 7,054.37 km2.
(b)

(a)

Fig. 1 (a) Location map of Myanmar and study area and (b) land use/landcover classification map produced by the authors of the present study
Source: satellite image by JAXA/Distribution RESTEC

Research Flow
In the present study, the Advanced Visible and Near Infrared Radiometer type 2 (ANVIR-2) of theAdvanced Land Observation Satellite (ALOS, dated 20101110) was used to classify land use types inthe ERDAS Imagine software version 2014 (Intergraph Corporation) and accuracy assessment was
conducted. Second, primary unit data for several ESs were collected and then applied to the land
classification maps using the ArcGIS10.1 software (ESRI). Third, seven ES maps were developed anda priority layer map was made using Zonation (Lehtomaki and Moilanen, 2013).
Land Use/Land Cover Classification of Satellite Image
Different land use types have different functions and capacities to provide ESs (Burkhard et al., 2012).
Land use classification was conducted using satellite image and was classified into five land use types
using the ERDAS IMAGINE: forest areas, agricultural land, urban areas, water bodies, and bare land
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IJERD – International Journal of Environmental and Rural Development (2015) 6-2(Fig. 1 (b)). The land use classification was conducted using a supervised classification method, which
is a type of land use classification that uses maximum likelihood criteria as parametric rules. The
overall accuracy assessment of the land classification was approximately 91% by comparing with
Google earth in ERDAS Imagine software and 2010 forest cover map of Myanmar (Forest Department,
FRA 2010) in ArcGIS 10.1.
Literature Survey of Ecosystem Services Unit Value
The area-based primary unit values for each ES were obtained based on a literature survey (Table 1). In
particular, unit values regarding provisioning services, regulating services, supporting services, andhabitat were collected. For provisioning services, the unit value of agricultural products (such as riceand pulses) was collected. For regulating services, CO2 absorption, soil erosion control, and water
infiltration were selected. For the soil erosion data, low values were considered favourable and highvalues were unfavourable; this is in stark contrast to the other ESs considered. Accordingly, the soil
erosion data were inversed before being used for analysis. The unit of water infiltration was mm/h andthe percentage of water infiltration by different land use types was calculated by using unit value ofwater infiltration. For supporting services, carbon stock, and gross primary production (GPP) wereselected. According to Rui (2014), Green Distance Index (GDI) evaluates how much green area isconcentrating in each cell for habitat distribution and the GDI is calculated from Green Index (GI)which extracts forests and water as green areas and assigns it as “255” and other land use as “0”. Datadescribing the primary unit values of ESs in Myanmar were limited for this analysis. In the unit valueof ESs in this study, the unit values of carbon stock and agricultural product (food production) were thedata of Myanmar. The other unit values were for other Asian countries in which the forest types, theelevation, and the slope conditions were similar to Nay Pyi Taw Area and were used in this study.
Table1 Types of ESs and primary unit value of ESs in this study
Types of ecosystemservices
Supporting Services:
GPP (t/ha/yr)

Forests

Agricultural
area

Urban

Water

Bare
land

Source30.7

12.093000

Carbon stock (t/ha)
Regulating Services:
CO2 absorption (t/ha/yr)
Soil erosion factor (t/ha/yr)
Water infiltration (mm/h)
Provisioning Services:
Agriculture Products (t/ha)
Habitat (GDI)

433.7

31.02

0

0

0

Chen et al. (2013), Hirata etal. (2013)
Oo (2009), Takeuchi (2012)

2.737
0.038
100

3.250
3.9
38.5

0
31
2

0
0
15

0
94.5
2

Chen et al. (2013)
Sidle et al. (2006)
Chaplot et al. (2002)

-

5.38
-

-

-

-

FAO (2009)
Rui (2014)

Mapping using Arc GIS
Spatial analysis was conducted using ArcGIS to understand the spatial distribution of ES provision andits relationship to land-use type. To develop seven ES maps, the land-classified map and the unit valuesof ESs for each land use type were used. Before applying unit values for the land classification
mapping, a grid with a mesh size of 1 km ×1 km was developed for the land classification map.

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Determination of Priority Areas for Conservation
Zonation is an approach and software for spatial conservation prioritisation, and is used primarily forthe efficient and effective allocation of conservation action. Spatial conservation prioritisation is also aform of conservation assessment (Knight et al., 2006) and incorporates decision support forconservation planning (Ferrier and Wintle, 2009). Zonation firstly sums the value of each ES layer anddiscards the least valuable cell one by one until all cells are removed. Zonation includes four types ofcell removal rules, namely, core area zonation, additive benefit function (ABF), target-based planning,and generalised benefit function; moreover, many parameters are available for analysis (Moilanen et al.,2012). Of the available rules, the present study used ABF to account for the proportions of all map
layers proportions in a given cell. ABF tends to produce a higher average proportion of feature
distributions retained. To weight the ESs in this Zonation analysis, equal weights were selected for all
ESs. Moreover, although the units of the ESs were different, the normalisation of data was conducted
automatically by Zonation. By using ABF, the present study achieved the best performance on average
for all features or ESs. The main result of this Zonation analysis was a priority ranking map for theentire landscape.
RESULTS AND DISCUSSION
In the present study, GIS-based spatial analysis was conducted for the assessment of ES provision fordifferent land use types. Fig. 1 (b) shows that forest and agricultural land were the dominant land use
types in the study area, whereas Fig. 2 demonstrates the spatial distribution of ESs in the Nay Pyi Taw
region.
(a)

(b)

(d)

(e)

(c)

(f)

(g)

Fig. 2 Maps of seven ESs in Nay Pyi Taw, showing (a) CO2 absorption, (b) carbon stock,(c) agricultural products, (d) GPP, (e) soil erosion control, (f) water infiltration and(g) habitat (GDI)ⒸISERD162

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

In Fig. 2, the red and blue colours indicate high and low values, for ES provision. Overall,
relatively high provisions of ESs, except agricultural products and CO2 absorption, were found inforest areas. Fig. 2 (a) and (c) illustrate the high provision of CO2 absorption and agricultural products
in agricultural areas. In particular, the map in Fig. 2 (a) indicates that agricultural land had a net uptakeof atmospheric CO2. Chen et al., (2013) noted that the carbon sink function of Asian cropland was
likely related to cropland management practices and cropping systems that supplied adequate nutrients,
abundant residues, and organic matter to the soil. This explains the high rates of CO2 absorption forthese agricultural areas. Fig. 2 (b, d, e, f, g) shows the ES provision of carbon stock, GPP, soil erosion
control (inversed value), habitat, and water infiltration. In particular, Fig. 2 (g) shows that habitat is thegreatest in the mesh dominated by forest and water areas. For habitat, GDI was calculated by extracting
the forests and water areas as green area because those areas were good for habitat of the wildlife. In
supporting and regulating services, all of ESs provision is high in the forest areas. So, the forests are
the most important area to conserve to provide ESs and conservation activities of forests need to bepromoted to be sustainable use of ESs.
The main output of the Zonation analysis was a priority rank layer map (Fig. 3 (a)). These results
show the important areas in terms of ES provision, with the priority rank of the site illustrated by acolour scale. The most important and valuable areas in terms of the potential distribution of ESs andconservation of ESs are shown in Fig. 3 (a), and these data were derived from the Zonation analysis. In
Fig. 3 (a), the dark red color represents the top priority areas for conservation and the violet color
represents the lowest priority areas. In Fig. 3 (a), the top priority areas were mostly forested areas andthe areas located close to forest areas had relatively high priority. It is well-known that forest
ecosystems are the main providers of ESs. Therefore, it makes sense that forested areas were identified
as the top priority areas for the conservation of ESs. In general, the lowest priority areas were urban
developed areas and bare land. Priority maps were made to identify the most important areas for ES
conservation; many of this land consisted of forested areas. Fig. 3 (b) and (c) illustrate another output
of Zonation analysis and Fig. 3 (b) shows the performance of each ESs during prioritization analysis;
and Fig. 3 (c) shows the performance of minimum, maximum, and average distribution of all ESs. Fig.
3 (b) represents that according to the algorithm of prioritization analysis, the lowest valuable cells werefirstly removed and the highest were removed lastly until no cell remains. The horizontal line of Fig. 3(b) means the percentage of the removal of cells (landscape) and the vertical line means the remaining
percentage of each ESs when cells are removed. In horizontal line, “1” means 100% of landscapewhich means “there is no removal of cells” and the dotted line represents the 20% remaining oflandscape before all cells are removed. When the 20% of landscape were remaining, the proportion ofagricultural product was nearly 10% and of soil erosion remained nearly 90%. Fig. 3 (b) and (c) are not
the main results of the analysis and can not be used as effective results. The main result of this analysis
is presented in Fig.3 (a) priority rank map.
(b)

(a)

(c)

Fig. 3 Results of Zonation analysis showing (a) priority rank map and (b), (c) performance
curves, the top 20% of priority areas remain at a level of 0.2 (vertical dashed line)ⒸISERD163

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Finally, using the Zonation conservation planning tool, the priority areas for ES provision were
determined. Based on the results of the present study, this method will be useful in determining theconservation areas required for ESs and in selecting habitat for multiple biodiversity conservation.
CONCLUSION
Land use change and urban development are likely to accelerate in the coming years. Therefore, theprotection of BD/ESs will become increasingly necessary, particularly in urban areas. In the present
study, according to the resulted land use map, the study area is covered primarily by forests andagricultural areas. Based on the results of mapping of ES unit values, forest and agricultural areas had
the highest provisions of ESs. Furthermore, according to the Zonation results, the high priority areas
should be conserved for the sustainable use of ESs in the future. And then, the priority maps should be
useful for land use planning, policy development, and protected areas establishment in the Nay Pyi
Taw region. Also, by using these results, we can remind not to extend the development activities in thepriority areas of ESs provision.
ACKNOWLEDEGMENTS
This work was performed by using the fund from the EcoTopia Science Institute, Nagoya University.
REFERENCES
Burkhard, B., Kroll, F., Nedkov, S. and Muller, F. 2012. Mapping ecosystem service supply, demand andbudgets. Ecological Indicators, 21, 17-29.
Casalegno, S., Bennie, J.J., Inger, R. and Gaston, K.J. 2014. Regional scale prioritisation for key ecosystemservices, renewable energy production and urban development. PLOS ONE, 9 (9), e107822.
Chaplot, V., Boonsaner, A., Bricquet, J.P., De Rouw, A., Janeau, J.L., Marchand, P., Phommassack, T. andValentin, C. 2002. Soil erosion under land use change from three catchments in Laos, Thailand and Vietnam.
12th ISCO Conference, May 26-31, 2002. Beijing, China.
Chen, Z., Yu, G., Ge, J., Sun, X., Hirano, T., Saigusa, N., Wang, Q., Zhu, X., Zhang, Y., Zhang, J., Yan, J.,
Wang, H., Zhao, L., Wang, Y., Shi, P. and Zhao, F. 2013. Temperature and precipitation control of the spatial
variation of terrestrial ecosystem carbon exchange in the Asian region. Agricultural and Forest Meteorology,
182-183, 266-276.
Department of Population. 2014. The population and housing census of Myanmar 2014, Summary of theprovisional results. Ministry of Immigration and Population, 2014, Myanmar.
FAO. 2009. Special report, FAO/WFP. Crop and food security assessment mission to Myanmar. 22 January 2009,
FAO and WFP, ROME.
FAO website (http://www.fao.org/countryprofiles/maps/en/?iso3=MMR), Food and Agriculture Organization of
the United Nations, country profiles, Myanmar.
Forest Department, Ministry of Environmental Conservation and Forestry. 2010. Forest resource assessment
2010 Country Report, Myanmar.
Ferrier, S. and Wintle, B.S. 2009. Quantitative approaches to spatial conservation prioritization, Matching thesolution to the need. In: Moilanen, A., Wilson, K.A., Possingham, H.P. (Eds.) Spatial Conservation
Prioritization, Quantitative Methods and Computational Tools. Oxford University Press, Oxford.
Garcia-Nieto, A.P., Garcia-Llorente, M., Iniesta-Arandia, I. and Martin-Lopez, B. 2013. Mapping forest
ecosystem services, From providing units to beneficiaries. Ecosystem Services, 4, 126-138.
Hirata, R., Saigusa, N., Yamamoto, S., Ohtani, Y., Ide, R., Asanuma, J., Gamo, M., Hirano, T., Kondo, H.,
Kosugi, Y., Li, S.G., Nakai, Y., Takagi, K., Tani, M. and Wang, H. 2013. Spatial distribution of carbon
balance in forest ecosystems across East Asia. Agriculture and Forest Meteorology, 148, 761-775.
Knight, A.T., Cowling, R.M. and Campbell, B.M. 2006. An operational model for implementing conservation
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Lehtomaki. J. and Moilanen, A. 2013. Methods and workflow for spatial conservation prioritization using
Zonation. Environmental Modelling and Software, 47, 128-137.
Millennium Ecosystem Assessment MA. 2005. Ecosystems and human well-being: synthesis. A report of themillennium ecosystem assessment. Island Press, Washington.
Moilanen, A., Meller, L., Leppanen, J., Pouzols, F.M., Arponen, A. and Kujala, A. 2012. Zonation version 3.1 user manual. Biodiversity Conservation Informatics Group, Department of Biosciences, University of
Helsinki, Finland.
Oo, T.N. 2009. Carbon sequestration of tropical deciduous forests and forest plantations in Myanmar. Ph.D,
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Rui, L. 2014. The potential distributions of mammalian by Maxent model – Case of Nagoya City. M.Sc Thesis,
Department of Civil Engineering, Nagoya University, Japan.
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2, 2012.

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Research article
erdComparison of Semi-Quantitative and Statistical Regression
Models in Assessing Landslide Prone Areas in WahigInabanga Watershed, Bohol, Philippines
TOMAS D. REYES, JR.*
Bohol Island State University, Bohol, Philippines
Email: tomseyer@yahoo.com / tomseyer@gmail.com
Received 3 March 2015

Accepted 10 November 2015(*Corresponding Author)

Abstract The study attempted to compare and evaluate the two landslide hazard assessment
models, semi-quantitative (index-based) and statistical regression (bivariate statistical analysis
and logit regression) in predicting landslide prone areas in Wahig-Inabanga Watershed, Bohol,
Philippines. This was performed by comparing the predictive power of each model based on thefrequency distribution of past landslide events. Findings revealed that the combined bivariate
statistical analysis and logit regression model outdone index-based method in predicting
landslide occurrences. Results indicated high prediction accuracy on statistical model greaterthan the 75% threshold level set for evaluation on both pooled moderate to very high hazard
zone and the combined high and very high hazard zone with accuracy values of about 83.82%
and 76.72%, respectively. Conversely, the semi-quantitative model failed to meet the accuracy
threshold. The study showed that statistical regression model, though relatively difficult toimplement, can be a better substitute to the most commonly used semi-quantitative method as adecision-support tool for watershed management and land use planning in relation to landslide
risk mitigation, reduction, adaptation, and management.
Keywords bivariate statistical analysis, landslide hazard, logit regression, semi-quantitative
methodINTRODUCTION
Several computer-based tools are found useful in landslide prediction, hazard assessment, and mapping
especially when these tools are made use in tandem with geographic information system (GIS). GIS
serves as an indispensable tool for mapping areas prone to unpredictable hazard events, particularly
landslides. One of the best advantages of using this technology is the possibility of improving hazard
occurrence models by evaluating results and adjusting the input variables (Lanuza, 2008).
There are several methods used in landslide hazard assessment. Ayalew et al., (2005) and Reyes(2014) briefly discussed each method and grouped them into three major categories: semi-quantitative,
quantitative, and hybrid. According to Ayalew et al., (2005) and also cited by Reyes (2014), some of
the methods are simple, especially those which rely on subjective assessments. Others, however,depend on complex mathematical concepts and are difficult to understand. Some old approaches havelong disappeared, others underwent a sort of refinement, and new methods are always coming. Manyof the latest methods are not yet available in known commercial GIS packages either as built-infunctions or additional modules. Data, then, are usually transformed to external software products forcore analyses.
The semi-quantitative method is the collective process of index and overlay analysis, thus termed“index-based method”. It is also called as expert-driven (Zhu and Huang, 2006) in which expert
opinions make great difference and become the basis during assessing of the type and degree of any
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units for disaster risk reduction and management and even recommended by the Department ofEnvironment and Natural Resources (DENR) to be a decision-support tool in forest management andconservation planning. A vulnerability assessment manual adopting this method has been prepared by
the Ecosystems Research and Development Bureau (ERDB) and made available for public use since2011.
On the other hand, the statistical regression model, uses logit regression to develop a functional
relationship between a process and factors inherent in them. The applications of this model in the fieldof slope instability have evolved as an important tool, with specific reference to landslide hazard
mapping. In landslide hazard mapping, an area is classified according to relative classes of instabilityon the basis of the degree of occurrence of landslide and mass movements (Jade and Sarkar, 1993).
In this study, both methods were applied for landslide hazard assessment in Wahig-Inabanga
Watershed, Bohol, Philippines to determine which between the two models is more appropriate inpredicting future landslide events based on the frequency distribution of past landslide occurrences.
METHODOLOGY
Landslide Hazard Mapping using Semi-quantitative (index-based) Method
The landslide hazard map prepared using the semi-quantitative method, particularly the index-based,
was completed following the procedures suggested by the ERDB-DENR in its vulnerability manual
published in 2011. It involved division of pre-defined landslide-related instability factors such as slope,soil type, rainfall, lithology, and land use into 5 classes using a set of criteria that influencevulnerability of the study area to landslide. These criteria were also used in assigning class ratings. The
most influential class trait was given the highest rating of 1, while the least influential was rated 0.
This was followed by overlaying of instability factors based on desired factor weights. Weights
used were 0.35 for slope, 0.20 for both rainfall and geology, 0.15 for land use, and 0.10 for soil type.
Landslide Hazard Mapping using Logit Regression (Combined Bivariate Statistical Analysis andLogit Regression) Model
The statistical regression model, same with the index-based method, also necessitated factor and classweighing. Bivariate statistical analysis was used to determine class weights, while logit regression
allowed the computation of factor weights. However, the logit regression, unlike semi-quantitative
method, required the utilization of landslide inventory or landslide occurrence map (van Westen, 1994
as cited by Wahono, 2010) to implement factor and class weighing. This means that factor and classweights are dependent on the landslide inventory and not on pre-defined vulnerability or susceptibility
criteria. To do this, the landslide inventory map was overlaid with nine significant landslide-related
instability parameters like elevation, slope, aspect, lithology, distance from fault line, distance fromrivers, distance from roads, rainfall, and land use. Landslide pixels laid on each class of instability
factors were computed as landslide frequencies. These frequencies served as class weights and wereused as class numerical values in logit regression. Important outputs of logit regression in SPSS
included regression coefficients of all parameter considered as factor weight and the model prediction
probability.
Details on how these two maps were generated are discussed in the DENR Vulnerability
Assessment Manual (ERDB, 2011) for the index-based method and the works of Reyes (2014),
Ayalew et al., (2005) and Ayalew and Yamagishi (2005) for the logit regression with bivariate
statistical analysis referred in their reports as quantitative method.

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Comparison of the Two Models
Model comparison was performed to determine which of the two approaches was more reliable inlandslide hazard prediction. Comparison was based on the frequency distribution of past landslide
events [=pixels] rested on the pooled upper moderate to very high hazard zones [P(Y=1) > 0.5 logit
regression default cut-off value] and the combined zone rated as high and very highly [P(Y=1) > 0.6]
prone to landslide occurrences using the 75% model prediction accuracy threshold. This was done by
applying the overlay and extract by sample function in spatial analyst tool of ArcGIS.
RESULTS AND DISCUSSION
Landslide Hazard Assessment
Semi-quantitative method: Table 1 presents the summary results of landslide hazard assessment
using the semi-quantitative method. Based on Table 1 and depicted in Fig. 1, the biggest part of thewatershed, about 71.50% or 44,540 ha, was predicted moderately prone to landslides. Considerable
areas had estimates of low (10,400 ha) and high (7,338) hazard ratings, while very small areas of thewatershed were estimated very low (4 ha) and very high (13 ha). From these results, it appears that thesemi-quantitative method overestimated the moderate landslide hazard zones and underestimated thevery low and very high landslide hazard areas. As shown in Fig. 1, most of the relatively flat areas in
the watershed fell within the moderate landslide hazard zone.
Table 1 Landslide hazard class ratings, area of coverage (ha) and percent distribution
generated using semi-quantitative method
Class Range
Rating< 0.2
Very low
0.2-0.4Low
0.4-0.6
Moderate
0.6-0.8High> 0.8
Very highTotal

Area (ha)410,40044,5407,338
1362,295Percent (%)
0.01
16.69
71.50
11.78
0.02
100

Table 2 Landslide hazard class ratings, area of coverage (ha) and percent distribution
generated using statistical regression model
Class Range< 0.2
0.2-0.4
0.4-0.6
0.6-0.8> 0.8

RatingVery low
Low
ModerateHigh
Very highTotal

Area (ha)38,18010,360
6,692
4,101
2,962
62,295Percent (%)
61.29
16.63
10.74
6.58
4.75
100

Statistical regression model: Table 2 shows the landslide hazard class ratings generated using thestatistical regression model, and their corresponding area (ha) and percent distribution. Results indicatethat more than 60% of the total area of the watershed (about 38,180 ha) was identified to have very low
probability of landslide occurrence. About 16.63% or 10,360 ha had low landslide hazard, whileroughly 6,692 ha or 10.74% was estimated to fall under the moderate landslide class. Conversely, high
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and very high landslide ratings were predicted for areas mostly situated on the upper elevations of thewatershed (Fig. 2) having 4,101 ha and 2,962 ha, respectively.
The results show a decreasing area distribution against the increasing vulnerability of the area tolandslide.

Fig. 1 Landslide hazard map
generated using semiquantitative method

Fig. 2 Landslide hazard map
generated using the statisticalregression model

Table 3 Comparison of two models showing the frequency distribution of landslide pixels
in different hazard classes
HazardClass range

RatingStatistical regression
Frequency

Percent

Semi-quantitative
Frequency

Percent< 0.2

Very Low

83

4.39

0

0.00

0.2-0.4

Low

124

6.56

48

2.54

0.4-0.6

Moderate

232

12.27

1,005

53.15

0.6-0.8

High

364

19.25

772

40.82

> 0.8

Very High
Total

1,088

57.54

66

3.49

1,891

100

1,891

100

Method Comparison
Table 3 indicates the result of the landslide inventory layer and the landslide hazard maps overlay. It isnoticeable that there was a direct agreement between the landslide frequency (= number of pixels lying
on each hazard class) and the hazard zones for the statistical regression model, a characteristic of an
ideal method (Fig. 3). The highest landslide frequency of 1,088 or 57.54% was obtained from the very

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high landslide hazard zone. This was followed by high and moderate hazard zones with 364 (19.25%)
and 232 (12.27%), respectively.
Conversely, the distribution of landslide pixels was variable among the hazard zones of semiquantitative model, thus no relationship was observed. The result on Table 3 clearly shows that most of
the landslide pixels were found on moderate (1,005 or 53.15%) and high (772 or 40.82%) landslide
hazard zones, while only 66 pixels (3.49%) fell on very high hazard zone.

Fig. 3 Comparison of two models based on the percent distribution oflandslide pixels in different hazard classes
A process of combined zonation (combining classes) was also used to clearly evaluate thepredictive power of each model. The combined zone is referred to as unstable zone (=area) in the studyof Dhakal et al., (2000) such as the pooled upper moderate to very high hazard, and the high and very
high landslide hazard classes. Table 4 reveals the result of the model comparison based on thecomputed landslide frequency on these combined zones. Compared to the semi-quantitative method,
statistical regression model, at par, had higher prediction accuracy values of 83.82% and 76.72% [bothgreater than the 75% threshold level] based on the frequency and percentage of landslide events thatfall on moderate to very high [P(Y=1) > 0.5] and high and very high [P(Y=1) > 0.6] hazard zones,
respectively.
Table 4 Comparison of two different models showing the frequency distribution oflandslide pixels
Model
Semi-Quantitative
Statistical Regression

P(Y=1) > 0.5*
Frequency
Percentage
1,386
73.29
1,585

83.82

P(Y=1) > 0.6**
Frequency
Percentage
838
44.32
1,452

76.78

Note: * = default logit regression cut-off value in SPSS; upper moderate to very high hazard zone** = areas rated as high and very highly prone to landslideWith lower computed prediction accuracy, the semi-quantitative method, unfortunately, failed tomeet the threshold level set for acceptability which only means that this method is not suitable forlandslide hazard assessment and mapping particularly in Wahig-Inabanga Watershed. The statisticalregression model, then, becomes a better alternative method and substitute to semi-quantitative or
index-based method.

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CONCLUSION
Based on the findings of the study, it is concluded that the statistical regression method is a better
option to use when assessing landslide hazards in Wahig-Inabanga Watershed, Bohol, Philippines. The
advantage of applying a bivariate statistical analysis provided numerical values on instability factor
classes which were used in determining factor weights through logit regression. The idea of factor
weighing in logit regression is to find the best fitting function in defining the relationship between thepresence or absence of landslides and a set of landslide-related instability parameters. The objectivityof logit regression method in determining the significance of instability parameters in landslideprediction is wanting in semi-quantitative or index-based method.
REFERENCES
Ayalew, L. and Yamagishi, H. 2005. The application of GIS-based logistic regression for landslide susceptibility
mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology, 65, 15-31.
Ayalew, L., Yamagishi, H., Marui, H. and Kanno, T. 2005. Landslides in Sado Island of Japan, Part II. GIS-based
susceptibility mapping with comparisons of results from two methods and verifications. Engineering andGeology, 81, 432-445.
Dhakal, A.S., Amada, T. and Aniya, M. 2000. Landslide hazard mapping and its evaluation using GIS, An
investigation of sampling schemes for a grid-cell based quantitative method. Photogrammetric Engineeringand Remote Sensing, 66 (8), 981-989.
ERDB. 2011. Manual on vulnerability assessment of watersheds. Ecosystems Research and Development Bureau,
Department of Environment and Natural Resources, College, Laguna.
Jade, S. and Sarkar, S. 1993. Statistical models for slope instability classification. Engineering Geology, 36, 9198.
Lanuza, R.L. 2008. Soil erosion and landslide vulnerability of Mananga Watershed, Cebu, Philippines.
SYLVATROP, 18, Nos 1-2, January-December.
Lopez, A.V.B., Estigoy, D.A., Tubal, R.S., Andrada, M.G., Baldo, H.S., Dano, A.M. and Ebora, J.B. 2008.
Landslide and fire vulnerability assessment of Pudong Watershed, Benguet, Philippines. SYLVATROP, 18,
Nos 1-2, January-December.
Reyes, T. Jr., D. 2014. Modeling of landslide and water-induced erosion in Wahig-Inabanga Watershed, Bohol.
Unpublished Doctoral Dissertation. University of the Philippines Los Baños.
Van Westen, C.J. 1994. GIS in landslide hazard zonation, A review with examples from the Andes of Colombia.
In Mountain Environment & Geographic Information System. Edited by Price, M.F. and Heywood, D.I.
Wahono, B.F.D. 2010. Applications of statistical and heuristic methods for landslide susceptibility assessments.
Unpublished Technical Report. Gadjah Mada University and International Institute for Geo-Information
Science and Earth Observation.
Zhu, L. and Huang, J.F. 2006. GIS-based logistic regression method for landslide susceptibility mapping inregional scale. Journal of Zhejiang University, SCIENCE A. ISSN 1009-3095 (Print), ISSN 1862-1775(Online). www.zju.edu.cn/jzus; www.springerlink.com.

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Research article
erd

Farm Machineries and Equipment Needs Assessmentof the Corn Block Farming in Dagohoy, Bohol, Central
Philippines: Basis for Financial and Support Services
MARINA A. LABONITE*
Bohol Island State University, Bohol, Philippines
Email: mtalabonite@yahoo.com.ph

DENNIS B. JOMOC
Bohol Island State University, Bohol, Philippines
Received 28 February 2015

Accepted 30 November 2015(*Corresponding Author)

Abstract To increase production, land productivity, and farming efficiency in the cornproducing municipality of Dagohoy, Bohol, Central Philippines, the Candelaria Multi-Purpose
Cooperative of the locality in collaboration with the Department of Agrarian Reform haveproposed corn block farming involving the Agrarian Reform Beneficiaries (ARB’s) from two
Agrarian Reform Communities (ARC’s) in the area. Funding agency of the proposed projectrequired the needed number and type of machinery and equipment for a productive andprofitable corn block farming in Dagohoy, Bohol ARCs. Thus, an in depth assessment on thefarm machineries and equipment needs of corn block farming in the area was done based on thecharacterization of its natural and physical resources, as well as the size of the potential area forcorn block farming. A set of participatory rural appraisal techniques were adopted in theassessment process. After the thorough analysis of the data collected, corn block farming was
found to be suitable in the proposed project site considering soil types, climatic condition,
availability of water, infrastructures, and other required facilities. The project site had 724
potential hectares for corn production. However, full mechanization was not possible due toexisting moderate slopes (8-18% slope) in some areas. Traditional farming methods at
production stage could be integrated considering that some of the fields do not favor fullmechanization and the farming methods could also provide employment for the displaced laborin some farm operations. Due to high investment requirement, pilot production among others
could be started in a 30-40 hectare portion to be managed by the Candelaria Multi-Purpose
Cooperative.
Keywords corn block farming, needs assessment, Agrarian Reform Communities (ARCs),
common service facilities, corn machineries

INTRODUCTION
Agriculture provides food and livelihood to the people. This sector represents 1/5 of the total economy
and generates 1/3 of the Philippines total employment (Philippine Climate Change Commission, 2010).
This great contribution to the national economy communicates the government to provide the needs
and addresses the identified gaps for continuous and more contributions. Because the poverty incidence
in Bohol, Philippines was significantly reduced in 2012 after achieving 100% rice self-sufficiency level
including some other commodities, (PGBh ELA, 2011-2013), the provincial government is thrusting toincrease agricultural production for food security and economic stability in the island. The governmentis interested on mechanized farming for timely production and postharvest operations to increase yieldwith better quality products. Hence, to minimize production cost while maximizing efficiency of farmmachineries and equipment, block farming is introduced through the support of the Department ofⒸISERD172

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Agrarian Reform (DAR) Program. In Bohol, corn block farming is proposed by Candelaria Multipurpose Cooperative (Candelaria MPC) in the municipality of Dagohoy to maximize the utilization of
the 380 hectares out of its aggregate land area of 2,302 hectares. To attain a timely production,
however, financial assistance, associated farm machineries and technical support services are highly
needed.
Based on the Sugarcane Industry Development Act of 2014 of the country, infrastructure, funding
for farm mechanization and modernization, capability trainings, and other support services areprovided for block farming. Musaba et al. (2014) also affirms that focusing access on better production
inputs will improve farm efficiency. Moreover, Asadullah et al. (2005) states that household/farmers’
education significantly reduces farm production inefficiencies, thereby, increasing productivity.
Accordingly, providing the needed input supports associated with the adoption of block farming
practice may ensure farm efficiency and productivity. To realize, and for the efficient implementationof the corn block farming project in Bohol, the Candelaria cooperative needs the information on the:number, kind/type, and specifications of the machineries and equipment which are to be used in thisimportant block farming venture. This study was conducted as commissioned by DAR.
OBJECTIVESThis study was conducted to assess the farm machineries and equipment needs of Candelaria Multipurpose Cooperative for corn block farming in a 380-hectare area in Dagohoy, Bohol, Philippines. The
objectives were specifically aimed to characterize the natural and physical resources of the community
for suitability to corn production; to determine the size of the potential area for corn block farming; todescribe the corn production and postharvest practices of the farmers; and to identify the existing farmmachineries and tools of the farmers and those needed in the operation of the corn block farming in the
ARCs.
METHODOLOGY
Pre-assessment activities were done through a series of consultations with the Municipal Agrarian
Reform Officer (MARO) and Chairman of the Cooperative, preparation, and revision of data collection
materials, as well as the orientation of the Research Team on the mechanics of the study. The needs
assessment used a set of tools from the participatory appraisal approach. The techniques and the data
sources were triangulated. The employed techniques were the collection and analysis of secondary datafrom the DARPO, MARO, and the Cooperative; the semi-structured survey questionnaire-aided
interview answered by the officials and members of the cooperative as well as barangay officials. In
addition, a focus group discussion for a group interaction was conducted to obtain detailed information
on particular issues, gaps and problems regarding their needs for farm machineries for their corn block
farming enterprise, which was led by the cooperative. Descriptive and quantitative data analysis was
adopted to obtain the needed information from the different tools used.
RESULTS AND DISCUSSION
Soil suitability of the area to corn block farming: The edaphic condition of the ARCs in Dagohoy isdominated by two soil types namely: Ubay clay and Ubay clay loam. Ubay clay covers 8,266 hectares(66.16% found in the central part of the municipality) and Ubay clay loam in the northern and easternsides, with the remaining 4,229 hectares (33.84%) of the total land area, including the south-westernborder of the municipality. The 380 hectare-corn block farm of Candelaria ARC is located at thecentral to the south-western border, (Figs. 1 and 2). These types of soil are suitable to all kinds of crops
including corn (DARPO, 2003). The most desirable soil for corn production is deep, medium textured,ⒸISERD173

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well drained, and with high organic matter and water holding capacity. Soil types with thesecharacteristics are loam, silt loam, and silty clay loam (PCARRD,1981). Hence, the soil conditions in
the ARC are very suitable for corn production but thorough land preparation remains a requirement,
which is the reason for the need of efficient farm implements and machineries.

Fig. 1 Connectivity map showing the ARC’s and ARB’s corn areas by barangay

Fig. 2 Soil Map of Bohol showing the Ubay Clay and Ubay Clay Loam soil ofthe Municipality of Dagohoy, Bohol
Climatic suitability: Most of the country’s corn-producing areas are rainfed. A good cropping of corn
is highly dependent on sustained rainfall, especially during the critical stages of the crop development(Reyes et al., 2009). It also requires fair soil moisture and warm climate. The municipality of Dagohoy
is classified as under Type IV climatic condition, characterized by more or less stable distribution of
rainfall throughout the year with moderate rainy season (kidlat.pagasa.dost.gov.ph). The averagetemperature is 28.60C with the coldest months having average temperature of 24.40C from November
to January. The relative humidity is more or less uniformed throughout the year. The area is rarely hit
by a typhoon and has high precipitation from July to November (DARPO, 2014). Hence, farmers
commonly plant corn in May for the first cropping and the second cropping in September.
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Water resources: Groundwater is the main source of potable water in the municipality. There are 3
water supplies: Level 1 comprising of 618 water wells; Level 2 including communal piped water
system; and Level 3 serving for the water system reaching respective households. There are several
springs and small creeks in Barangay Caluasan and Candelaria apart from the three rivers, namely
Wahig-Pamacsalan River, Malitbog River, and Hamoog River, which are considered potential sources
for irrigation water (DARPO, 2004). It is believed that these resources can already support corn crops
as the plant requires 4 to 5 mm of water per day. During critical periods like silking and soft doughstages, the requirement could be as much as 6 to 8 mm/day. It is estimated that the most critical point
falls around 55 days after planting (Lansigan, 2004). Literatures have stated that water should beavailable at 40 DAP during the start of flowering and reproductive stages (Reyes et al., 2009).
Slope: Most of the agricultural lands, 30-75% of the total land area, in the ARCs of Dagohoy are fromflat to undulating 0-15% slope (DARPO-DARMO, 2013). The topography of ARC Candelaria ranges
from level to rolling where 1,286 hectares have 0-3% or level to nearly level; 790 hectares have 3-8%
or gently sloping to undulating; 226 hectares with 8-18% or moderately sloping to rolling. These
ranges of slope are suitable for upland crops like corn (DARPO, 2004).
Potential production area: Barangay Candelaria, Caluasan, and Malitbog of Dagohoy have an
aggregate area of 2,302 hectares of land in which 1,889 hectares (82%) is agricultural lands including
365 hectares for cornfields (DARPO, 2014). The 2013 survey found that all of the respondent-ARBs
had a total land area of 107 hectares with 38 hectares planted with corn (Fig. 2). The respondents were
only 10% of the total number of ARBs in the community. Correspondingly, the data imply that thecurrent cornfield utilization is almost similar to the one in the year 2004 with a derived value of about
380 hectares. Thus, the expected total area covering the project is 380 hectares. Data from the MARO
and CMPC show that Dagohoy has a total potential area of 724 hectares planted with corn by 34.25%(512hectares) of the ARBs. Some of the corn fields are owned by non-ARBs. There are also areas in
the ARCs that have been previously planted with cassava potentially turning to corn fields.
Average yield: Survey results of DAPRO (2013) show that the average yield of the corn fields at the
ARCs is 2.89 metric tons(Mt)/ha with an average production of 2.66 Mt per cropping costing an
average of ₱5,000.00 per unit area. This production rate conforms with the average national production
rate of 2.83 Mt/ha (DARPO, 2004). The production cost is observed to be ₱6,000/ha providing an
average income to the farmer-respondents of ₱38,000 per hectare per cropping.
Market: Corn farming in the ARCs in Dagohoy can be classified as subsistence and market driven.
Seventy percent of the respondents who own only 0.60-1.00 ha corn area belong to the subsistencegroup, as their production is intended for food security of household. Being influenced by marketing
campaigns and given supports, other corn growers evolve themselves by adopting high-yielding hybrid
corn technology. The market of their hybrid corn products owns a feed mill and operates a commercial
scale hog and poultry farms (DARPO, 2013). This market driven corn farming has assured an
immediate market of its products.
Rural infrastructures: All barangays are accessible through the road networks constructed out ofgravel and limestone with about 17.0 km stretch within the ARCs. Few areas are not passable during
heavy rainy season due to sticky/muddy/slippery situations. The Pilar Irrigation System of the National
Irrigation Administration is functional and serving 440 hectares of agricultural areas in themunicipality. Gridlines for electrical source are also available to the majority of the areas. This facility
is needed in any electrically-powered stationary corn processing machineries and equipment. Means ofcommunications are also available to facilitate delivery of information to any farmer-officials andmembers (DARPO, 2004 and DARPO, 2013).
Production and postharvest practices of the corn farmers: The subsistence corn farmers in the
ARC employ farming methods for both production and post production operations in the same way asⒸISERD175

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the market-driven producers. There are a number of processes during production operations. Farmers
select seeds of their preferred improved varieties; hybrid; do thorough land preparation with 2-3
plowings and furrowing using carabao-drawn plow; manual planting; use commercial complete
fertilizers or do not apply any kind of fertilizer; conduct off-baring and hilling-up at knee-high stage;
perform weeding, bolo and scythe are used in traditional hand weeding; and sometimes spray chemical
pesticides for pest and disease management. Post-production activities include manual harvesting anddehusking; shelling used dull bolo or shredder; while wooden-toothed sheller or motor-driven cornshellers in shelling kernels for seeds. Sun drying in buri mats, tarpaulin, nets or drying pavement arevery common but the cooperative has mechanical drying services. Farmers deliver small volume ofcorn grains in wooden sled or motorcycle-service to buyers in the local; but corn ears in bulk are
picked-up by private feed mill operators.
Existing farm tools, equipment and machineries: The total farming households in the ARC own 621
draft animals and a total of 822 moldboard plow for land preparation (DARPO, 2004).
Table 1 The quantity, type of machineries, equipment, its specifications neededin the corn block farms in Dagohoy, Bohol with an area of 380 hectares
based on the assumptions
Quantity

Image

Technical Specifications
Front Wheel Assist (FWA), Four-wheel tractor-diesel engine,
Drawbar-96Hp (min), 172 Hp (min) PTO (includes with 6-60I disk
plow implement and an offset harrow)

5 units

Model 2BYF-3, Tractor-drawn, 3-row corn planter/seeder withfertilizer applicator

5 units

CTN Size: 1700x1620x1100 mm
1 unit13 units

No image

Self-propelled corn seeder/planter with fertilizer applicator, 3 ha
field capacity daily
Self-propelled harvester, Model 4YW-2C, 20HP, with storage tankvol (1cu.m)
CTN Size: 3200X1300x2800

The study found that the cooperative has a multipurpose drying pavement and a mechanical dryer(DA-distributed flatbed) with a shed commonly utilized in drying rice, and corn ears/grains during
inclement weather; farmers have traditional farming tools and equipment such as moldboard plow,
sharp/dull bolo, scythe (long), wooden sled, home-made shredder, home-made wooden-toothed sheller
for corn grain production and buri mat. Tarpaulins were used by the majority of the farmers in corn
production and post-production.
Machineries and equipment needs and assumptions: Corn production cycle analysis was used todetermine the machinery and equipment needs of the farmers for corn block farming. The analysis
considered the current production area of 380 hectares, existing production, and post-production
practices of the corn farmers in Dagohoy, Bohol. Some assumptions were made as follows:corn
production is fully-mechanized; land preparation will be done using 4-wheeled tractor travelling at 8
kph having 6-60 cm disk plow with offset, and effective width of 1.8-2.0 m.; land preparation will bedone for 30 days which includes one plowing and two harrowing operations; post-production
operations (harvesting to shelling) will be done for 15 days; tractors will be used for seeding/plantingⒸISERD176

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and fertilizer applications; self-propelled corn planter has fertilizer application function; and selfpropelled corn harvester has a capacity of 1.0 ha a day.
CONCLUSION
Considering the overall requirements of corn crop, the agricultural uplands of the municipality ofDagohoy are very suitable for corn production in terms of soil types, availability of water source
subsuming well-distributed rainfall during the year, and the weather condition which favors for its
growth and development. In a view of the field conditions, due to existing moderate slopes (8-18%) insome areas of the Municipality of Dagohoy, Bohol, only partial mechanization is possible. Engaging
into corn block farming, the Candilaria Multipurpose Cooperative needs a big investment based on theidentified machineries, equipment, technical support services, and skilled manpower required for
efficient and timely operation of the planned agri-enterprise.
ACKNOWLEDGEMENTS
Expression of deep and sincere gratitude is due to the Department of Agrarian Reform-Provincial
Office, the Municipal Agrarian Reform Office and the Candilaria Multipurpose Cooperative and the
Dagohoy respondent-ARBs.
REFERENCES
Asadullah, N.M. and Rahman, S. 2005. Farm productivity and efficiency in rural Bangladesh: The role ofeducation revisited. CSAE WPS/2005-10. University of Oxford. UK.
Bohol Provincial Profile. 2011. http://www.ppdobohol.gov.ph. URL viewed last January 24, 2016.
Bohol Annual Report . 2012. http://www.ppdobohol.gov.ph. URL viewed last December 15,2013.
DARPO. 2004. Candelaria Development Plan. Department of Agrarian Reform-Bohol. Tagbilaran City. DARPODARMO. 2011. DAR-ARCCESS, Farm Machineries and Equipment Support Services for Corn Block
Farming in Bohol, Agribusiness Investment Proposal of the Candelaria Multi-Purpose Coop.
DARPO. 2013. Market flow analysis, NADA-survey on farm machineries and equipment support services forcorn block farming in Bohol. Department of Agrarian Reform-Bohol. Tagbilaran City.
Lansigan, E. 2004. Linking corn production, Climate information and farm-level decision making, A case study
in Isabela, Philippines. Web page-http://www.prairieswine.com, viewed last June, 20, 2013.
Musaba, E. and Bwacha, I. 2014. Technical efficiency of small scale maize production in Masaiti District,Zambia, A stochastic frontier approach. Journal of Economics and Sustainable Development, 5 (4).
PAGASA. 2010. Climate of the Philippines, Quezon City. kidlat.pagasa.dost.gov.ph.
PCARRD. 1981. Department of Science and Technology. Los Baños, Laguna.
Philippine Climate Change Commissio. 2010. National framework strategy on climate change 2010-2022. Officeof the Philippine President. (Web page-URL viewed last June 3, 2012).
Provincial Government of Bohol (PGBh)-Executive Legislative Agenda (ELA) 2011-2013. http://www.
ppdobohol.gov.ph. URL viewed last June 3, 2013.
Reyes, C., et al. 2009. Climate variability, SCF and corn farming in Isabela, Philippines, A farm household level
analysis. Philippine Institute for Development Studies.

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Research article
erd

Evidence-based Modeling of Landslide Hazard in WahigInabanga Watershed, Bohol, Philippines using GIS andStatistical Models
TOMAS D. REYES, JR.*
Bohol Island State University, Philippines
Email: tomseyer@yahoo.com, tomseyer@gmail.com
Received 3 March 2015

Accepted 30 November 2015(*Corresponding Author)

Abstract. The study combined geographic information system (GIS) and statistical models in
predicting landslide hazard in Wahig-Inabanga Watershed, Bohol, Philippines. The bivariate
statistical analysis (BSA) and logit regression (LR) were employed for class and factor
weighting, respectively, to determine landslide prone areas using eleven significant landsliderelated instability factors such as elevation, slope, aspect, lithology, soil order, soil type, fault
line proximity, river proximity, road proximity, rainfall, and land cover. The very satisfactory
results of model evaluation warranted the application of the LR model in evidence-basedlandslide hazard assessment. Out of the eleven instability factors, only soil order and soil typewere determined not significant. The first three most important instability factors based on thevalues of regression coefficients were elevation, slope, and lithology. Landslide hazard
assessment revealed around 7,063 ha or 11.33% of the total area of the watershed had high tovery high landslide hazard ratings. The study showed that GIS, in tandem with useful models,
provided pertinent results which could be used as scientific basis for watershed management
and land use planning in relation to landslide disaster risk reduction and management.
Keywords bivariate statistical analysis, GIS, landslide hazard, logit regression

INTRODUCTION
As a natural phenomenon, landslide usually occurs in high elevation, and sloping areas. Its severity isdefinitely influenced by the type of vegetation cover and the geomorphological structure of the soil.
This geologic hazard is often triggered by excessive and continuous rainfall, and seismic events. Oneof the most unforgettable landslide events which struck the Philippines was that which happened in
Guinsaugon, Leyte where in a matter of minutes, the homes and families in barangay of Guinsaugon
were wiped out and buried under a mountain of soil and rock (Catane et al., 2006).
The province of Bohol, in particular, had experienced frequent landslides and massive erosion in
the upland, and floods at lowland areas. Its susceptibility to landslides and floods had been recorded by
the Mines and Geosciences Bureau (MGB) in 2007. There were more than 100 barangays identified
prone to these hazards out of the 46 municipalities covered in the survey. Specifically for landslide
events, 64 barangays within the Wahig-Inabanga watershed were rated with moderate to highvulnerability to landslides based on 13 out of 16 municipalities evaluated. The 52-hectare Mayanalandslide which happened on July 13, 2005 was triggered by a surface-wave magnitude 4.9 earthquakewith its epicenter recorded somewhere in Sierra Bullones on March 31, 2005. The landslide’s averageslope was only about 13%, described as elongated, oriented east-west and had a total length of 1.4 km(Catane et al., 2005).
Geospatial technology is increasingly being used in spatial decision support systems. This has
been the trend since its functions and applications have been made known to the public, especially toexperts, practitioners, and policy makers around the globe. In the Philippines, GIS, in tandem with
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remote sensing and modeling technologies, are used in many applications since the 1990s fromresource assessment, land use classification, and mapping to environmental hazards assessment andmanagement.
In the Philippines, the utilization of logit regression model and GIS for landslide susceptibility
mapping in the country was initially, and perhaps solely, conducted by Lee and Evangelista (2005) in
Baguio City. The method which has been used in this present study was a modification from their workwith the intention of increasing the predictive power of the LR model by initially applying thenumerical values of landslide frequencies as class weights derived using bivariate statistical analysis(BSA) prior to the actual logit regression analysis.
This current study assessed the applicability of GIS and logit regression combined with BSA in
determining landslide prone areas in Wahig-Inabanga Watershed, Bohol, Philippines.
METHODOLOGY
Study Site
The Wahig-Inabanga Watershed is the biggest watershed in the province of Bohol, Philippines(Fig. 1). From the northwest bay of Inabanga, the river dissects the central part of the island embracing
a total land area of more than 610 km2. According to Genson (2006) and Ludevese (2006), thiswatershed is more or less 15.20% of the total land area of the province.
It is geographically located between 124o3’36” and 124o23’24” East longitude, and betweeno9 43’48” to 10o4’48” North latitude. It has two headwaters namely the Wahig and Pamacsalan Rivers,
and its outlet is geographically located at 10o4’12” North latitude and 124o4’12” East longitude.

Fig. 1 Location map of Wahig-Inabanga Watershed, Bohol, Philippines

Acquisition of GIS Input Files
Thematic layers and other GIS input data which were used in this study were obtained from several
Philippine government authorities and well-known sources. The digital elevation model which wasused to derive elevation, slope, and aspect layers were downloaded from the ASTERGDEM website.
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The SPOT5 image, river and stream network, land use and land cover, contour, and spot height layers
were taken from the National Mapping and Resources Information Authority (NAMRIA). The soilorder and lithology layers were obtained from the Mines and Geosciences Bureau (MGB) while thesoil series and soil type layers were solicited from the Bureau of Soils and Water Management(BSWM). The political boundaries and road network layers were acquired from the Bohol Provincial
Planning and Development Office (PPDO), and the updated ground rupture map was secured from thePhilippine Volcanology and Seismology (PHIVOLCS).
Inventory of Landslide
The identification and mapping of existing landslides are prerequisite to perform statistical analysis on
the relation between the distribution of landslides and influencing parameters (Saha et al., 2005). Any
landslide susceptibility or hazard assessment must begin with the collection of information on wherelandslides are located. Collection of information is done in many forms. Most of the researchers utilize
aerial photographs and satellite image interpretation to locate landslides. Others employ the sameinterpretation method in tandem with ground validation. In this study, both image interpretation andextensive field surveys were performed.
The ortho-rectified Spot 5 Image (scene: 313330) acquired from NAMRIA was used to delineate
visible landslides. Ground validation was carried out during the field surveys. The complexity of image
interpretation for a huge watershed like Wahig-Inabanga led the conduct of extensive field surveys.
Field surveys were done mostly in, but not limited to, areas within the watershed. The buffer zone of
100 m along the watershed boundary was also considered. Major [= deep-seated] and minor [=shallow] landslides were identified and their GPS coordinates were taken either at the center or along
the landslide boundaries. A total of 215 landsides were recorded throughout the study area.
GIS Processing
Mapping of landslides: The geographic coordinates taken in the field were retrieved from GPS
receivers using Garmin BaseCamp software (version 4.2.1). Coordinates were identified as to thosetaken around the corners of huge and medium-sized landslides and those taken at the center of smalllandslides and classified as to size of the landslides.
To prepare the landslide inventory map, coordinates were all geo-processed in ArcMap. Polygon
shapefiles were created for landslides with corner coordinates, while buffer function in ArcMap
interface was used for landslides with coordinates taken at the center. These, including the digitizedlandslides from Spot 5 Image, were all clustered into one shapefile using merge function and thenprojected to WGS84_UTM_Zone_51N. To complete the landslide inventory map, the projected
landslide polygons were combined with the Wahig-Inabanga Watershed mask and was finallyconverted to raster format with a pixel size of 10-m. The landslide pixels were given a value of 1 andnon-landslide pixels as 0. There were a total of 1,891 landslide pixels and 6,749,911 non-landslide
pixels.
Sample size computation and selection: The power calculator (http://calculator.stat.ucla.edu/powercalc, accessed on December 2013) was used in the computation of the sample size. Setting theconfidence level at 95% and confidence interval of 3, sample sizes of 1,058 and 1,067 were calculated
to represent all landslide and non-landslide pixels, respectively. The rasterized landslide inventory map
facilitated the preparation of combined landslides and non-landslides vector grid map with an aid ofHawth’s Analysis Tool, a freeware ArcGIS extension. Landslide and non-landslide sample selection
was also performed from the vector grid map using the same tool. Two sets of samples were selected,
one for model generation and another for accuracy evaluation.

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Statistical analysis: The landslide hazard assessment using logit regression (LR) adopted in this study
followed the method of Ayalew et al., (2005) and Ayalew and Yamagishi (2005) which required classand factor weighing.
Bivariate statistical analysis (BSA): BSA was applied to the first set of samples to determine classweights through the calculation of landslide frequencies on input parameter classes. Overlay analysis
and extract by samples in ArcGIS were used in this respect and the output dbase file was imported in
Microsoft Excel for landslide frequency computation.
Logit regression analysis: Logit regression was employed to define factor weights. The result of BSA
in excel was imported in SPSS and the method of stepwise backward selection was used. The outputsof the regression analysis included the measures of model fit, model prediction probability, andregression coefficients. The regression coefficient of each factor [also known as predictor orparameter] served as the factor weight.
The model equation adopted in the study is shown below:
Y=bo + b1 (P1) + b2 (P2) + b3 (P3) + … + b11 (P11)
where:
Y=
landslide occurrence (presence or absence)bo=
constant value (Y intercept)
b1, b2, b3…b11 =regression coefficients
P1, P2, P3…P11 =input parameters or instability factors
Below was the equation used to compute for the probability of landslide event:P=
Pr [Y=1] = 1/1+e(-X*B)
where:
P=
probability of landslide occurrence=
Pr [Y=1] = 0 to 1e=exponential function
X*B=
Y value of the logit regression function
RESULTS AND DISCUSSION
Model Assessment
Out of 11 parameters, only soil order and soil type were found not significant and were eliminated in
the final model. Model rerun identified elevation as the most significant parameter based on the valueof regression coefficient [B=0.007162]. This was followed by slope and lithology (Table 1).
Table 1 Logit regression output for the regression coefficient estimation using
the model of significant parameters
Predictor (Factor)
Elevation
Slope
AspectLithology
Fault line proximity
River proximity
Road proximity
RainfallLand coverConstant

Regression Coefficient(B)
0.007162
0.004933
0.002949
0.003533
0.000825-0.001247-0.001002
0.000717
0.001842-6.069435ⒸISERD181

Std Error
0.001
0.001
0.001
0.000
0.000
0.000
0.000
0.000
0.000
0.535

P-Value
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Model assessment in SPSS was very satisfactory. The model of goodness of fit was significant [pvalue < 5%], model chi-square was not significant [p-value > 5%], and the pseudo R2 was relatively
high [pseudo R2 = 0.607] (Table 2). The P-value of less than 5% for the goodness of fit test shows that
the LR model fits with the selected data. This is supported by the model chi-square P-value of morethan 5% which implies the model fit is good. In addition, the pseudo R2 value 0.607 means that the
60.7% of the total variation in the data is explained by the model. According to Clark and Hosking(1986) as cited by Ayalew et al., (2005) and Ayalew and Yamagishi (2005), a pseudo R2 greater than
0.2 indicates a relatively good fit.
Moreover, the prediction probability was determined very high [PredProb = 83.2%] (Table 3).
This value denotes a very acceptable prediction accuracy of the LR model for both cases (presence[84%] and absence [82.4%] of landslides).
Table 2 Summary comparison of model fit statistics of the logit regression function
Statistics
Goodness of Fit
Omnibus Test Chi-square
P-value
Model Chi-square
Hosmer and Lemeshow Test
P-value
Pseudo R2
Nagelkerke R2

Value
1290.114
0.000
17.3300.051
0.607

Table 3 Classification table showing the results of the landslide model
prediction probability
Predicted

Absence

Absence879

Presence
188

Percentage
Correct
82.4

Presence

169

889

84.0

Model

Observed

LR with significant
factors only
Overall Percentage

83.2

Landslide Hazard Assessment
Result of the landslide hazard assessment indicated that more than 60% of the total area of thewatershed (about 38,180 ha) was identified to have very low probability of landslide occurrence. About
16.63% or 10,360 ha had low landslide hazard, while roughly 6,692 ha or 10.74% was estimated to fallunder the moderate landslide class. Conversely, high and very high landslide ratings were predicted forareas mostly situated on the upper elevations of the watershed, as shown on Figure 2, having 4,101 haand 2,962 ha, respectively. These amounted to a total of 7,063 ha or 11.33% of the total area of thewatershed.
CONCLUSION
Logit regression, with bivariate statistical analysis, is best applied if landslide inventory is available.
The landslide inventory aids in the quantitative assessment of landslide prediction probability andserves as a means of determining the accuracy of the model.

ⒸISERD182

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

The application of bivariate statistical analysis in determining landslide frequencies and theutilization of these computed frequencies as quantitative substitutes to nominal variables of landslidepredictors simplify the logit regression equation and the interpretation of its results.

Fig. 2 Landslide hazard map generated from the LR model
Modeling landslide is very important to measure the relationship between each causative factor
with every single landslide location. The relationship between landslide and its causative factors vary
according to area, time, and climate. By modeling landslide, the inherent characteristics of landslide
activities can be quantified. This is very important in order to identify which causative factor plays amajor or a minor role. Such information can then help the authority to plan the activities and land
utilization in areas prone to landslides.
REFERENCES
Ayalew, L., Yamagishi, H., Marui, H. and Kanno, T. 2005. Landslides in Sado Island of Japan, Part II. GISbased susceptibility mapping with comparisons of results from two methods and verifications. Engineeringand Geology, 81, 432-445.
Ayalew, L. and Yamagishi, H. 2005. The application of GIS-based logistic regression for landslide susceptibility
mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology, 65, 15-31.
Catane, S.G., Foronda, F. and Tamorong, C. JR. 2005. Assessment of hazards resulting from July 11, 2005 landslide,
Barangay Mayana, Jagna, Bohol, A report to the local government unit of Jagna, Bohol. Unpublished Technical
Report. National Institute of Geological Sciences. University of the Philippines, Diliman, Quezon City.
Catane, S.G., Foronda, F. and Tamorong, C. JR. 2006. Extremely rapid rockslide-debris avalanche at St. Bernard,
Southern Leyte, Philippines. Earth Surface Processes and Landforms, 28, 925-950
Genson, I.C. 2006. Erosion and water resources assessment in the upper Inbanga Watershed, Philippines,
Application of WEPP and GIS tools. Masteral Thesis. University of Western Sydney, Hawkesbury Campus,
Richmond, New South Wales, Australia.
Lee, S. and Evangelista, D.G. 2005. Landslide susceptibility mapping using probability and statistics models in
Baguio City, Philippines.
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Ludevese, E.G. 2006. Land suitability evaluation of the Wahig-Inabanga river watershed forest (Bohol,
Philippines) Using Geographic Information System. Masteral Thesis. Visayas State University, VISCA,
Baybay City, Leyte.
Mines and Geosciences Bureau (MGB). 2007. Report on landslide and flood prone areas in Bohol. UnpublishedTechnical Report from Mines and Geosciences Bureau, Region 7.
Saha, A.K., Gupta, R.P., Arora, M.K., Sarkar, I. and Csaplovics, E. 2005. An approach for GIS-based.

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IJERD – International Journal of Environmental and Rural Development

erdInternational Society ofEnvironmental and Rural Development

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

IJERD – International Journal of Environmental and Rural Development

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

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

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