2023, Vol. 8, Special Issue 6
Geo-statistics and GIS technique to characterize spatial variability of soil available nutrients in an experimental farm
Author(s): V Arunkumar, K Ananthi, M Vijayakumar and M Yuvaraj
Abstract: Mapping of soil properties using the Geographical Information System (GIS) is an important aspect as it plays a vital role in the knowledge about the soil properties and how it can be used sustainably. The study was carried out in an Agricultural College and Research Institute experimental farm, Killikulam, Thoothukudi district to map soil available nutrients and assess their variability. A grid pattern (200 x 200 m) was established at the experimental farm to collect soil samples at two sampling depths (0-15 & 15-30 cm). The soil samples were analyzed for available Nitrogen, Phosphorus, Potassium, pH, Electrical Conductivity (EC) and soil organic carbon (SOC). The location of the sampling points and field boundary were marked with a GPS. Descriptive statistics and geostatistical analysis were done. The results reveal that pH of surface soils varied from 6.08 to 8.73 with CV of 10.21 per cent. The EC exhibited very high variability in all the depths. The pH, available N, P, K exhibited moderate variability for both the depths. Geostatistics was used to estimate and map nutrients in unsampled areas. The spatial dependence classes were strong for EC and SOC, whereas all other soil properties exhibited moderate spatial dependence. Spatial distribution maps of soil available nutrients made using Arc GIS software. Most of the research area showed evidence of multinutrient deficiency. Critical nutrient deficiency zones were identified. The status of nutrient availability at the farm level was determined from the spatial variability maps. Farm managers can use the produced maps as a useful tool for site-specific nutrient management.
Pages: 334-342 | Views: 224 | Downloads: 3Download Full Article: Click HereHow to cite this article:
V Arunkumar, K Ananthi, M Vijayakumar, M Yuvaraj. Geo-statistics and GIS technique to characterize spatial variability of soil available nutrients in an experimental farm. Int J Stat Appl Math 2023;8(6S):334-342.