IJERD – International Journal of Environmental and Rural Development (2018) 9-1

Research articleerd

New Science Tools for Spatial Distribution of Yield andManagement Practices of Major Pulse in Selected Area inMyanmar
KHIN MAR OO*Yezin Agricultural University, Myanmar
Email: khinmaroo06@gmail.com

HTAY HTAY OO
Yezin Agricultural University, Myanmar

NYEIN NYEIN HTWE
Yezin Agricultural University, Myanmar

MIE MIE AUNG
Yezin Agricultural University, Myanmar

KYAW KYAW WIN
Yezin Agricultural University, Myanmar
Received 31 December 2017

Accepted 5 May 2018(*Corresponding Author)

Abstract Pulses are one of the major agricultural exports in Myanmar. About 70 percent of
all pulses are normally grown immediately after monsoon rice in middle and lower region.
Farmers are not achieving the optimum yield due to inappropriate crop management andinsufficient technological solutions although modern varieties are cultivated extensively.
The introduction of applying new science tools such as GPS, GIS and drone image candevelop timely and accurate estimation of crop areas and forecasting its production. It may
also provide governments, planners, and decision makers with essential information to
make a successful plan of appropriate technologies in regard to import/export. The study
was conducted at Kyee Inn Village, Pyinmana Township, middle Myanmar from December
2016 to May 2017 to expose mapping for spatial distribution of yield and management
practices. Drone flying had done by using DJI Phantom 4 drone and Litchi software. Drone
photos were consolidated and prepared for digitizing and analyzing with pix 4D softwareand ArcGIS. Seventy farmers were selected as sample respondents for collecting groundtruth information of yield and management practices based on pulses cultivated area. Thestudy revealed that the major pulse grown in target area was black gram with yields ranging
from 0.16 to 2.29 MT/hectare. The majority of respondents were found to have low level
adoption of Good Agriculture Practices (GAP) of black gram recommended by AgriculturalDepartment. It is urgently needed to upgrade full adoption of improved recommended
package of practices by supporting training institutions to train the farmers and recommend
technological solutions for the increase of productivity. Thus, new science tools such as
GPS, GIS and drone image must be applied in agricultural system for increasing crop
productivity as well as improving livelihood of the farmers.
Keywordsp pulses, new science tools, mapping, yield, management practices

INTRODUCTION
Pulses are one of the major agricultural exports in Myanmar. The major pulses exported are blackgram, green gram, pigeon pea, kidney bean and cow pea. Pulses are grown on 4.20 - 4.30 million
hectares of area with an annual production of 5.04 -5.16 million tons (GAIN, 2017). About 70
percent of all pulses are normally grown immediately after the harvest of monsoon rice in middleⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2018) 9-1

and lower region. Farmers are not achieving the optimum yield due to inappropriate crop
management and insufficient technological solutions although modern varieties are cultivatedextensively (Phway Su Aye et al., 2013).
Spatial data incorporating with socioeconomic information relating to pulses cultivation ispossible to perform appropriate technological solutions for constraints of their cultivation.
Currently, nationwide pulses production area has been obtained with statistically-based groundsurveys but there has been seldom precise information on spatial distribution of yield, management
practices and constraints of major pulses. Indeed statistical data are costly, time-consuming and do
not provide sufficient detailed information to determine either the extent or the geographicaldistribution of major crops.
The introduction of applying new science tools such as Global Positioning System (GPS),
Geographical information systems (GIS) and drone image can develop timely and accurate
estimation of crop areas and forecasting its production (Wyland, 2009). Geographical information
systems (GIS) technology in combination with ground surveys can relate spatial distribution ofcrop yield and management practices that would determine the extent of major crop production andconstraints to their cultivation (Sreedevi et al., 2009). Moreover, it may provide governments,
planners, and decision makers with essential information to successfully plan and deploy
appropriate technologies in the most effective manner in regard to import/export.
OBJECTIVES
The objective of this research was to expose mapping for spatial distribution of yield andmanagement practices of major pulse in selected area using new science tools.
METHODOLOGY
Study area: The research was conducted at Kyee Inn Village, Pyinmana Township, middle regionof Myanmar, which lies between north latitudes 19q42'30'' and 19q43'40'' and east longitudes
96q13'30'' and 19q15'30'' from December 2016 to May 2017 (Fig 1.). Total study area is 483ha andpulses are grown just after the harvest of monsoon rice as double cropping (Table 1).

Kyee Inn Village

Fig. 1 Study area at Kyee Inn Village,
Pyinmana Township, Myanmar

Fig. 2 Sample plots taken in study area
using grid sampling system

Table 1 Total cultivable area and major pulses growing area in study area, 2016
Block No.
1698
1699
1708
1709
Total

Cultivable area (ha)
120
100
114
149
483

Major pulse Area (ha)
107
84
100
137
428

Source: DoALMS Pyinmana TownshipⒸ ISERD

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Percent (%)
89.17
84.00
87.72
91.95
88.61

IJERD – International Journal of Environmental and Rural Development (2018) 9-1

Data collection: Using 300m × 300m grid sampling system, total numbers of 104 grid squares
were taken in the study area (Fig 2.). Grid squares located outside of the study area were removed
and left 78 grid squares which had been cultivated with pulses. One plot from each grid squares
was randomly selected as a sample plot and surveyed in the field for ground truth data. Seventy
farmers occupied in sample plots were selected as sample respondents and interviewed with thehelp of well-structured questionnaire. The data collected were demographic characteristics of therespondents, yield and cultivation of major pulses practiced by the respondents, source of seedavailability and constraints of management practices related to major pulses cultivation in the study
area.
Field basemap hardcopy used as the base layer for digitizing and required secondary data weregathered from Department of Agricultural Land Management and Statistics (DoALMS), Pyinmana
Township, Union of Myanmar.
Drone Flying: Drone flying had done by using DJI Phantom 4 drone and Litchi software at analtitude of 120 meters above the ground. Drone photos were consolidated and prepared for
digitizing and analyzing with pix 4D software to provide digital base map of the study area.
Thematic mapping for spatial distribution of yield and management practices were provided using
ArcGIS Desktop [software] from Environmental Systems Research Institute (ESRI).
RESULTS AND DISCUSSION
Cultivation Conditions of Major Pulses in the Study Area
Major pulse grown in the study area was black gram (Vigna mungo (L.). Figure 3 shows total sown
area possessed by sample respondents ranging from 0.2 to 11.0ha. Most of sample respondents(72%) were experienced with pulses cultivation in 4-10 years, 26% in 11-20 years and only 2% in
21-30 years respectively (Fig 4.).

Fig. 3 Sown area possessed by sample
respondents in study area

Fig. 4 Pulses cultivation experience ofsample respondents in study area

Cultivation Practiced by Sample Respondents in the Study Area
Seed source and variety used: Figure 5 reveals that most of the sample respondents in study area
applied their own seed or dealer seed for sowing. Only 5% of them applied quality seed fromresearch station. They usually practiced by storing their own seed or exchanging with dealer seed at
the time of crop harvest. This clearly indicates that the necessity of quality seed multiplication
program should be undertaken with cooperative farmers by Department of Agriculture (DOA).
The black gram varieties commonly sown by sample respondents were Yezin-6 (Sepae),Yezin-5 (Paenat) and Yezin-2 (Matpae Yoeyoe) (Fig 6.). Among them, Yezin-5 is more longer
duration (100-110 days) than Yezin-6 (90-95 days) and Yezin-2 (70-75 days).

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IJERD – International Journal of Environmental and Rural Development (2018) 9-1

Fig. 5 Seed source of sample respondents
in study area

Fig. 6 Black gram varieties sown by sample
respondents in study area

Time of sowing and method of sowing: In the study area, 4%, 59% and 37% of sample
respondents sowed black gram in October, November and December, respectively. The optimum
time of sowing for black gram recommended by Department of Agricultural Research (DAR) isduring mid-October to end of November. It was found that some of the farmers in study area could
not sow black gram timely. The reason given by the farmers was late harvest of monsoon rice
possibly relating with late onset of monsoon or irregular rain during harvesting of monsoon rice inthat area.
All of the sample respondents in study area used broadcasting practice in seed sowing.
Although Department of Agriculture (DOA) endorses line sowing method for pulses cultivation, allof the farmers in study area did not adopt that practice. The constraints for adoption of practice as
expressed by a majority of farmers were labor shortage and insufficient mechanical implements forline sowing.
Applying basal fertilizer and seed treatment: The majority of sample respondents (94%) did not
apply fertilizer as basal application during land preparation. Because of the high cost of fertilizers,
they usually apply basal fertilizer for monsoon rice and rarely for black gram. Moreover 96% ofthem did not treat the seed with pesticide and fungicide at the time of sowing. Perhaps they may
not familiarized with the practice of seed treatment.
Seeding rate and plant population at vegetative growth stage: It was noticed that 59% of
sample respondents practiced the optimum seeding rate (60kg/ha) recommended by DOA whereas
less seeding rate by 10% and 31% applied more than the optimum rate. Furthermore, it wasobserved that 59% of sample respondents achieved normal plant population while 4%, sparse and37%, dense at vegetative growth stage. Probably normal plant population may be concerning not
only with seeding rate but also adequate amount of residual soil moisture at sowing time.
Spatial Distribution of Yield and Management Practices
According to spatial distribution of grid squares, it was found that black gram variety applied inmost of the sample plots was Yezin-5 in western part and Yezin-6 in eastern part of study area.
Moreover the trend in spatial distribution of yield also revealed that yield per hectare in westernpart was lower than that in eastern part of study area (Fig 7.). It may be in agreement with thepotential yield of black gram variety, 1.6-2.0 ton/ha for Yezin-5 and 2.5-3.3 ton/ha for Yezin-6,
reported by Department of Agricultural Research (DAR, 2016).
Generally, it was clear in Fig 7 that the yield of Yezin-2 and Yezin-6 variety in most of thesample plots were not considerably affected by time of sowing although a few days later thanrecommended sowing time. In contrary, the yield was diminished by late sowing time in the sample
plots applied with Yezin-5. It indicates that crop duration of the variety should be considered if thesowing time will be late because of the dependence on residual soil moisture for crop’s success.
Spatial distribution of management practices such as weed management, spraying frequencyof foliar fertilizer and pesticide were shown in Fig 7. It was found that weed management practices
are not applied in sample plots at the middle of study area. About 2-12 spraying frequency for thewhole season was applied in half of the sample plots (54%) and the rest applied till to 15.
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IJERD – International Journal of Environmental and Rural Development (2018) 9-1(a) Yield (ton/ha)(b) Variety(c) Time of sowing(d) Weed management(e) Foliar fertilizer spraying frequency
for the whole season(f) Pesticide spraying frequency
for the whole season

Fig. 7 Spatial distribution of yield and management practices based on sample plots
randomly in each grid squares in study area
Regarding to foliar fertilizer and pesticide spraying frequency mapping, it was noticed thathigher spraying frequency were applied in the sample plots at the middle and eastern part of thestudy area. The reason said by the sample respondents was that higher spraying frequency wasrequired to increase black gram yield starting from 15 days after emergence to 15 days before
harvest.
Constraints for Good Agriculture Practices of Black Gram
The data regarding the constraints for Good Agriculture Practices (GAP) of black gram perceived
by sample respondents were stated in Table 2.

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IJERD – International Journal of Environmental and Rural Development (2018) 9-1

Table 2 Constraints for good agriculture practices of black gramGood Agriculture Practices (GAP)

Constraints- To apply good quality seed for sowing- Insufficient supply of quality seed- To sow timely with recommended
sowing time
- To apply line sowing method- Late harvest of monsoon rice

- To apply fertilizer as basal- To apply seed treatment with pesticideand fungicide- Labor shortage and insufficient mechanicalimplements for line sowing- High cost of fertilizers- Not familiarized with the practice

CONCLUSIONS
Use of drone image along with GIS helps quick and accurate analysis on huge data. According tothe results, mapping allows to identify easily the correlation between spatial distribution of yieldand management practices of black gram in the study area. Since a thematic map has a table ofcontents that allows adding layers of information to a basemap of the study area. The majority ofrespondents were found to have low level adoption of Good Agriculture Practices (GAP) of black
gram recommended by Agricultural Departments. It is urgently needed to upgrade full adoption of
improved recommended package of practices by supporting training institutions for training of thefarmers and advising technological solutions for the increase of pulses productivity. It was clearthat another study can be extended across the country as the present study. The use of new science
tools are cost effective and time saving, thus it must be applied in agricultural system for increasing
crop productivity as well as improving livelihood of the farmers.
ACKNOWLEDGEMENTS
The authors would like to thank the generous financial and technical training support of Japan
International Cooperation Agency (JICA) Project for Capacity Development of Yezin AgriculturalUniversity. We also gratefully acknowledge Chief Advisor Professor Tanaka Koji, Dr. YamamotoYosi, Dr. Kazuo Watanabe and Mr. Nihsimoto Goro for their generous technical and intellectual
support and valuable involvement in this study. We are also appreciative to the authorized persons
from Department of Agricultura (DOA) and Department of Agricultural Land Management andStatistics (DoALMS) for data provision.
REFERENCES
Department of Agricultural Research (DAR). 2016. Official recommendation on yield characters and cultural
practices of high yielding black gram (Vigna mungo (L.). Ministry of Agriculture, Livestock andIrrigation (MOALI), Union of Myanmar.
Global Agricultural Information Network (GAIN). 2017. Grain and feed annual, Burma - Union of Myanmar.
GAIN Report Number BM 7003, USDA Foreign Agricultural Service.
Phway Su Aye, Hsu Wai Htun and Thaw Phone Myat. 2013. Myanmar’s beans and pulses trade, risks andprospects. Thura Swiss Special Report, Union of Myanmar.
Sreedevi, T.K., Wani, S.P., Kesava Rao, A.V.R., Singh, P. and Ahmed, I. 2009. New science tools for
managing community watersheds for enhancing impacts. Journal of SAT Agricultural Research, 7.
Wyland, J. 2009. Burma - Union of Myanmar grain and feed annual, agribusiness grows with crop-specificmaps. Best practices, GIS for agriculture, www.esri.com/agriculture.

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