GIS FOR SOIL NUTRIENT MAPPING: SITES BATU 17, YAN, KEDAH

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1 GIS FOR SOIL NUTRIENT MAPPING: SITES BATU 17, YAN, KEDAH Nurul Syakira Samsuri, Mohammad Aufa, Mohd Shahril Shah, Mohd Syaifudin. Pusat Penyelidikan Kejuruteraan Malaysian Agricultural Research and Development Institute (MARDI) Muhammad Naim Pusat Penyelidikan Padi dan Beras Malaysian Agricultural Research and Development Institute (MARDI) Abstract Geographic information systems (GIS) play a vital role in creating, collecting, managing, and visualizing georeferenced data. The general objective of this research project was to produce an up-todate map showing the soil fertility status in paddy field especially Nitrogen, Phosphorus and Potassium (NPK) variability in a paddy field using geostatistical and interpolation technique in QGIS. This study was carried out in a paddy field at Batu 17, Yan, Kedah, Malaysia. In order to update soil information, 96 soil samples were collected and were analyzed for NPK content were analysed in the chemical laboratory. These maps can be used to guide the development, implementation of integrated soil fertility management strategies and farmers can achieve additional benefits by combining better utilization of fertilizer. 1. Introduction Agriculture is among the most important economic generating sectors in the world and the world s oldest economic practices. Agriculture has developed into a technologically advanced industry and it currently plays a substantial role in global sustainability. The world population is projected to reach 8.5 billion in 2025, which will be more than double the population in 1992 (Roy 2011). This increase in population creates increased demand for agricultural outputs. Precision agriculture refers to an emerging set of technologies to simultaneously help meet this demand and also promote sustainability. The decisions made within precision agriculture are based on information, and this information is directly derived from data. GIS now become one of the analytical tools which can incorporated into soil fertility management and assessment (Grinderud, 2009). The data within a GIS are stored and displayed in layers, adding a visual perspective for interpretation.nutrients status of paddy area using Geographic information systems (GIS) will help to showing the soil nutrients status and useful for formulating site specific balanced fertilizer requirement and recommendations locationwise for each fertility class (P Pulakeshi et al., 2012), (Motsara, 2002). Also, this information was used to make land management decisions such as nutrient rates, sources, timing and application (Rendana et al., 2016). These approaches have helped clients (farmers) reduce the impact of environmentally harmful resources whilst reducing their total fertilizer expenditures by up to 10 percent (Esri, 2007). 49

2 2. Material and method 2.1 Study area and soil sampling The research was carried out at Batu 17, Yan, Kedah located at the northern part of Peninsular Malaysia (latitude N, longitude E), and at an elevation of 5m above sea level. The area is hot and humid with average annual temperature range of C and relative humidity varying between 60% and 99%. The plot had 20 blocks with total area of 10 ha. The main textural class of the soil is clay, silty clay, silty clay loam and silt loam. The location of sampling sites is shown below in Fig. 2. Figure 1.0: Typical map of the soil sampling points 2.2 Assessment of soil nutrient status Soil samples (0-20 cm) were collected by using regular systematic sampling grid scheme (40m x 40m). The number of sample collected in the study area were 94. The latitude and longitude of sampling sites location were recorded and georeferenced using a global position system GPS, allowing the soil test results to be correlated with spatial details of the sample. Processed soil samples were analysed for nutrient availability by following standard analytical techniques. In comparison of soil nutrients this research will adopt optimum values of soil nutrients for paddy planting as recommended by Malaysian Agriculture Research and Development Institute (MARDI) (Table 1). 50

3 Table 1.0: Optimum soils chemicals properties value for paddy requirement Chemical Property Optimum requirement Total Nitrogen (%) Available P (mg/kg) >40 Exchangeable K cmol (+) /kg > Geostatistical methods Distribution of soil nutrient status in study was assessed through geostatistical methods using QGIS 2.2 software including spatial analysis (interpolation) and Inverse distance weighting (IDW). Using QGIS software, interpolation procedures were performed, which enabled visualization in the form of raster and vector maps for the spatial distribution of soil nutrient status and classifying the soil nutrient values again to define the precision of soil nutrient values and the colors of each region section to produce the spatial distribution map of soil nutrients. Different color represents different range of nutrient value. The corresponding area of color is to be used to examine each nutrient value scope and possibly to know the status of the soil nutrient in the map. Figure 2.0: Surface map of available total Nitrogen content Figure 3.0: Surface map of available total Phosphorus content 51

4 Figure 4.0: Surface map of available K content Result and Discussion GIS software was used in producing map to show the spatial distribution of the N, P, and K content. In this study, interpolation method was chosen because it was standard in the software (QGIS) used throughout this study. The results of IDW interpolation describe the spatial distribution of soil nutrients status. The data consists of 94 sampling points in Batu 17, Yan, Kedah site. The mapping of the N, P, and K soil nutrient was compared to the optimum values of soil chemical properties recommended by MARDI. Figure 2.0 show that total nitrogen content is %, range from %. The study of surface soils revealed that the content of phosphorus was varied from to mg/kg (Figure 3.0) and K ranged from 0.50 to 0.56 cmol(+)/kg. Conclusion The surface maps of the soil nutrients status can provide visual guidance as well as the quantitative information to guide nutrient application, based on the targeted yield especially for paddy. Thus, the surface maps of nutrients could be utilized to develop the nutrient management strategies for intensive small-holder systems (Chatterjee, S. et al., 2015). Finally, GIS probability maps can be of immense benefit in soil fertility management and assessments when land users and farmers want to evaluate their fields in terms of spatial variability and soil fertility studies. This can ensure where resources need to invested. On this note, it was realised that a GIS based probability map in spatial variability and fertility studies has outlined an effective option of implementing improved nutrient management in large tracts, enabling the development of appropriate and sound agricultural management recommendations. 52

5 References P Pulakeshi, H. B., Patil, P. L., Dasog, G. S., Radder, B. M., Bidari, B. I., & Mansur, C. P. (2012). Mapping of nutrients status by geographic information system (GIS) in Mantagani village under northern transition zone of Karnataka*. Karnataka J. Agric. Sci, 25(3), Rendana, M., Rahim, S. A., Idris, W. M. R., Lihan, T., & Rahman, Z. A. (2016). Mapping nutrient status in oil palm plantation using geographic information system. Asian Journal of Agricultural Research, 10(3 4), Chatterjee, S., Santra, P., Majumdar, K., Ghosh, D., Das, I., & Sanyal, S. K. (2015). Geostatistical approach for management of soil nutrients with special emphasis on different forms of potassium considering their spatial variation in intensive cropping system of West Bengal, India. Environmental Monitoring and Assessment, 187(4), Roy, D "Agriculture Gets a Makeover!" Geospatial World, geospatialworld.net/images/magazines/gw-aug %20cover%20story.pdf 53