IJERD – International Journal of Environmental and Rural Development (2019) 10-2

Research article
erd

The Spatial Variability of Soil Chemical Properties
in a Selected Area of Myanmar
NAING NAING MOE*
Department of Soil and Water Science, Yezin Agricultural University, Myanmar
Email: nnmoe148@gmail.com

SWE SWE MAR
Department of Soil and Water Science, Yezin Agricultural University, Myanmar

AUNG KYAW MYINT
Department of Soil and Water Science, Yezin Agricultural University, Myanmar

KYI TOE
Department of Plant Breeding, Physiology and Ecology, Yezin Agricultural University,
Myanmar

KYAW NGWE
Department of Soil and Water Science, Yezin Agricultural University, Myanmar
Received 16 December 2018

Accepted 10 July 2019(*Corresponding Author)

Abstract Sustainable crop production requires detailed knowledge of the spatial variabilityof soil properties, such as soil nutrients. The primary purpose of this study was to assess thestatus of soil fertility by evaluating selected soil chemical properties, at Kyee Inn Village
Tract, Pyinmana Township, Middle Myanmar using Geographic Information Systems (GIS).
In this study soil samples were collected for the 80 grid references examined. Variables
measured were soil pH, electrical conductivity (EC), cation exchange capacity (CEC), soilorganic matter, and the total content of nitrogen and phosphorus. Grid size is 300 m × 300
m, covering an area of about 480 hectares, and samples were taken at a depth of 0-15cm
using a Global Positioning System (GPS) to determine the coordinates of the sampling
points. Soil fertility maps were generated using Inverse Distance Weighting (IDW)
interpolation in ArcGIS software 10.5. Interviews were conducted with farmers to match
results to soil management practices. The statistical analysis demonstrated a high variabilityof total nitrogen content with a coefficient of variation of 66.84%, while the soil pH andphosphorus levels showed the minimum variability in comparison to other soil properties.
The pH values ranged from 5.48 to 7.58, while for phosphorus, minimum to maximum
levels are 0.017% to 0.024%, respectively. Values for EC can be considered normal, with amean value of 0.095 dS m-1 obtained. The CEC values ranged from 2.13 to 11.05 meq100
g-1soil. The low level of organic matter (0.2% to 1.7%) indicated a need to increase theorganic matter content to ensure sustainable crop production. This study provides farmers
with an effective management and decision-making model that encourages sustainable crop
production.
Keywords GIS, GPS, soil chemical properties, spatial variability

INTRODUCTION
Scientists face many challenges in developing strategies to develop sustainable crop production
systems (Bakhsh et al., 2000). Assessing the spatial variability of soil chemical properties is crucial
in the development of these cropping systems (Mamun et al., 2015). Agricultural sustainability
requires that this evaluation of soil fertility should be undertaken periodically (Chimdi et al., 2012).
The spatial variability of soil properties includes the variation of soil chemistry, physics, andⒸ ISERD

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biological properties in a given location. Even for the same soil type, soil characteristics may
exhibit huge differences within short distances (Li et al., 2012).
A standard method for creating maps of topsoil properties is to sample an area using a grid
sampling scheme. The density of sampling undertaken will depend on the heterogeneity of the area.
With this information a ‘prediction’ map can be produced by interpolating the measured property
values of the samples (Karydas et al. 2009). GISs are a powerful set of tools and useful for
producing soil fertility maps for an area, which will help in formulating site-specificrecommendations regarding fertilizer needs, as well as providing an understanding of the status ofsoil fertility both spatially and temporally (Thakor et al., 2014). Inverse Distance Weighting (IDW)
was applied to the data as it is a good interpolator for phenomena whose distribution is strongly
correlated with distance (Mustafa et al., 2011).
Soil fertility is one of the primary constraints to agricultural production in tropical countries,
including Myanmar. Baroang (2013) reported that there is limited information on the dynamics ofsoil types and erosion patterns in Myanmar, and what does exist, is largely based on decades-old
data. The establishment of monitoring stations and the determination of an appropriate monitoring
design would be extremely valuable, as there is an obvious need to update the data concerning
Myanmar soils.
OBJECTIVE
The main objective of this research is to generate accurate large-scale distribution maps of theselected soil properties by evaluating the current soil fertility status of the study area.
METHODOLOGY
Study Area and Soil Sampling
The study area was selected after conducting a pilot survey. The study area covers a total of 480
hectares, and is located at the Kyee Inn Village Tract, Pyinmana Township, in central Myanmar,
and is situated between 1942'30''-1943'40''N and 9613'30''-1915'30''E (Fig. 1). Myanmar
experiences three distinct seasons, hot, wet and cool, and the study area receives a mean annual
rainfall of about 1420 mm and an average temperature of 26.8°C. Monsoon rice and pulses are themain crops, and within the area there is both rain-fed and irrigated farming. The required secondary
data and hardcopy of the base-map of fields in this area are from Department of Agriculture andDepartment of Agricultural Land Management and Statistics. Sampling was done on a grid basis(300 m × 300 m), with samples taken at 0-15 cm depth using GPS to determine the coordinate of
the sampling points. Where possible, three soil samples were taken from each grid to derive a
representative sample. In total, 178 soil samples were collected from the 80 sampling plots (Fig. 2).
All samples were taken after harvest, and before any land preparation for the next cropping season
had been made. Interviews were conducted with farmers in order to identify variations in soil
management practices in different locations in the sample area.
Laboratory Analysis
The collected soil samples were composited for each grid, then air-dried, pounded, and sieved in
preparation for soil analysis. Soil pH and electrical conductivity were measured in the extract ofsoil: water (1:5) suspension using a digital pH-meter and EC meter (Hesse, 1971). Soil CEC wasmeasured using Bascomb’s method (Bascomb, 1964). Total nitrogen was determined by the
Kjeldahl digestion, distillation and titration method (Bremmer and Mulvaney, 1982). The total
phosphorus was analyzed using spectrophotometer as blue molybdate phosphate complexes underpartial reduction with ascorbic acid (Jackson, 1958). The Walkley and Black (1934) wet digestion
method was used to determine soil organic matter.
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Statistical Analysis and Soil Fertility Mapping
The laboratory results of all parameters measured were subjected to descriptive statistic using
Statistix (8th version). The low, medium and high levels of nutrients were determined according tostandard ratings. The base-map preparation enabling use of GIS software was accomplished by dataobtained from a DJI Phantom 4 drone, with this processed using Litchi software. The photos werecombined and processed using pix 4D software for digitizing and incorporated onto the digital basemap. A different thematic map for the spatial distribution of each parameter was generated using
the Inverse Distance Weighted (IDW) interpolation by ArcGIS 10.5 software.
Pyinmana Township

Kyee Inn Village Tract(480 hectares)
1942'30''-1943'40'' N
9613'30''-1915'30''E

Fig. 1 Location of the study area

Fig. 2 Grid sampling points

RESULTS AND DISCUSSION
Spatial Variation in Soil Chemical Properties
The results for each soil parameter over the 80 soil sample sites are presented in Table 1. In the study
area, there is a large variation in soil chemical properties. Total nitrogen showed the highest
variability with 66.84% in its CV (Coefficient of Variation), followed by soil electrical conductivity,with a CV value of 54.36%. However, least variability across sample areas was found for soil pH andtotal phosphorus, with CV values of 5.08% and 6.68% respectively. Moderate variability occurred
for soil CEC and organic matter, which have CV values of 28.02% and 35.93%, respectively.
Table 1 Descriptive statistics of soil chemical properties
Variables
pH
Electrical conductivity
Cation exchange capacity
Organic matter
Total nitrogen
Total phosphorus

Unit*-log[H+]dS m-1
meq100 g-1soil%%%

Minimum
5.480
0.051
2.130
0.200
0.010
0.017

Maximum
7.580
0.506
11.050
1.700
0.330
0.024

Mean
6.248
0.095
6.218
0.874
0.113
0.019

SE
0.03550.00580.19480.03510.00850.0001

SD
0.317
0.052
1.742
0.314
0.076
0.001

CV%
5.08
54.36
28.02
35.93
66.84
6.68

SE: Standard Error, SD: Standard Deviation, CV: Coefficient of Variation* Units represent for the columns of minimum, maximum and mean in the table

Soil pH and Electrical Conductivity
Soils in the study area were found to range from slightly acidic to moderately alkaline, with themean pH value of the soil being 6.25, with a range from 5.48 to 7.58. The pH of the soil samples
can be described as 21.25% moderately acidic, 58.75% slightly acidic, while 18.75% samples were
neutral (pH 7) and only 1.25% samples were moderately alkaline (Fig. 3). The variation in levels of
acidity could be due the topography of the study area, variations in moisture, or farmers’ practice inthe use of acid-forming nitrogenous fertilizers.

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The values of EC range from 0.051 dS m-1 to 0.505 dS m-1 (Fig. 4). The observed mean EC
value of 0.095 dS m-1 indicated that the study area does not have a salinity problem. According to
Moore (2001), the observed EC values were only just above the low range of levels for EC values
that is between 0.051 and 0.5 dS m-1, a level expected to have a minimum effect on plant growth.

EC (dS m-1)

Fig. 3 Spatial distribution of soil pH

Fig. 4 Spatial distribution of EC

Cation Exchange Capacity and Soil Organic Matter
The observed CEC vary from a low to a medium level, ranging from 2.13 to 11.05 meq100 g-1 soil,
with a mean value of 6.22 meq100 g-1 soil, for the study area (Fig. 5). Using Landon’s (1991)
classificatory system, 23.75% could be characterized as very low in CEC, while the remaining
76.25% has a low level of CEC. This would indicate that the study area has inadequate basic
cations which would be detrimental to plant growth. Ahmed et al. (2015) stated that any CEC of <4
meq100g-1 soil indicates a high degree of soil infertility, making it unsuitable for agriculture.
Organic matter content ranges from 0.20% to 1.70%, with a mean value of 0.87%. Figure 6
displayed the spatial distribution of organic matter (in OM%) with lowest levels in the northeastand eastern portion, with content increasing towards the southwest. This may be the result of theslightly higher elevation of the northern portion, as organic matter accumulation is often favored inthose areas at lower levels. Purdie (1998) states that soils with organic matter content greater than
2.6% provide good nutrient storage, so it can be seen that the level of organic matter content in all
sampling grid plots was very low, affecting good nutrient storage and supply. Based on the surveyof farmers’ soil management practices, this lower organic matter content may be attributed to poor
agricultural management practices, such as the complete removal of crop residues after harvest andthe infrequent application of organic manures and organic materials (rice straw, pulses residues,
cow dung, etc.) and the burning of crop residues after harvesting.

CEC(meq100 g-1soil)

Fig. 5 Spatial distribution of CEC

Fig. 6 Spatial distribution of OMⒸ ISERD

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Total Nitrogen and Total Phosphorus
The total nitrogen content varied from 0.01% to 0.33% with a mean value of 0.11% overall. The
study indicates that about 25% of the area sampled has ‘very low’ levels of nitrogen and a further
50% has ‘low’ levels, while 17.5% of the samples are in the medium range, and only 7.5% have ahigh range of total nitrogen content (Fig. 7). The low nitrogen content is probably due to theinsufficient level of organic matter, which can be depleted by constant cropping and prevailinghigh temperatures, resulting in the faster degradation and removal of organic matter, with acorresponding drop in the soil’s nitrogen reserves. On the other hand, the areas of medium to highlevel of total nitrogen appear to occur where organic materials have been added (mainly plant
residues), and also as a result of nitrogen fixed through legume cultivation.
The spatial distribution of total phosphorus levels appears to be higher, with 43.75% of thesampling area being in the medium range, whereas 56.25% of the samples showed lower levels (Fig.
8). The values of total phosphorus ranged from 0.017% to 0.024% with a mean value of 0.019%.
According to research, lower levels of phosphorus may be due to infrequent application of organicand inorganic phosphorus fertilizers. Another reason for these lower levels may be due to nutrient
depletion by crops, since this area has a cropping pattern of monsoon rice and dry weather pulses.

Fig. 7 Spatial distribution of total N

Fig. 8 Spatial distribution of total P

Survey Results for Soil Management Practices
Mostly preparation of land for cropping is mechanized, with only 21% of respondents using bothmachine and animal power. In this area, the dominant cropping pattern of monsoon rice and pulses
is practiced under both rain-fed and irrigated farming. It was found that there is minimal
application of organic fertilizers. After harvesting, farmers retain residues from the pulse crop on
their fields, but this is done by a minority. About 23% of respondents use cow-dung manure andonly 12% of respondents apply pulses residues. The most common types of inorganic fertilizers
used by the respondents were urea and compound fertilizers for rice production. There is noevidence of the application of phosphorus and potash fertilizers for crop production. Application offertilizers is mostly by the broadcast method and top dressing is applied two to three times, at thetillering and flowering stages. Fertilizers do not appear to be applied basally at planting time.
CONCLUSION
Results from the soil analysis show the following characteristics of the soil in the study area; it has
low content of organic matter, it has (mostly) low to high levels of total nitrogen, low to medium
ranges of total phosphorus, while the level of the CEC is very low to low. Although the measured
ranges of soil pH and electrical conductivity ranges should not be detrimental to the crop
cultivation, soil nutrient management for sustainable crop production should focus on addressing
problems of acidity and alkalinity. As expected, the variability of each soil characteristic exists
largely due to the differences in the management practices used by farmers. Therefore, farmers
should be encouraged to return as much crop residue as possible to the soil, introducing systematicⒸ ISERD

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practices (sufficient and consistent) that provide for the addition of manure and fertilizers, in orderto improve soil fertility levels which will lead to higher crop production. Further, a legume-based
cropping pattern should also be introduced and consistently maintained to provide a long-term
nutrient supply for better yields and diversify the economics of crop production. This study has
shown that the use of new technologies such as GIS and GPS can provide important informationfor evaluating the current status of soil fertility, and for allowing better management of soil fertility
at the farm level.
ACKNOWLEDGEMENTS
We would like to gratefully acknowledge the Japan International Cooperation Agency (JICA), who
supervise the Project for Capacity Development of Yezin Agricultural University, and who haveprovided technical and financial support for this study. We would also like to thank staff at the
Department of Agriculture and Department of Agricultural Land Management and Statistics, forthe maps and data that were provided. Assistance was provided in drone flying, photo processing
and the generation of maps, and the analysis of samples. Finally, we are very grateful to thefarmers in the study area for their keen participation throughout the study.
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