Assessment of soil quality and spatial variability of soil properties using geo-spatial techniques in sub-humid southern plain of Rajasthan, India Yadav K.K., Mali N.L., Kumar Sunil1,*, Surya Jaya N.1, Moharana P.C.2, Nogiya Mahaveer3, Meena R.L.3 Maharana Pratap University of Agriculture and Technology, Udaipur, 313 001, Rajasthan, India 1ICAR-National Bureau of Soil Survey and Land Use Planning, Regional Centre, New Delhi, 110012, India 2ICAR- National Bureau of Soil Survey and Land Use Planning, Nagpur, Maharashtra, India 3ICAR- National Bureau of Soil Survey and Land Use Planning, Regional Centre, Udaipur, 313001, Rajasthan, India *Corresponding author (Email: sunilcoa@gmail.com)
Online Published on 10 October, 2022. Abstract Soil quality and spatial variability of soil properties and their impact on the growth and yield of crops are important concerns for sustainable and site-specific nutrient management. The present study was conducted in soils of sub-humid southern plains of Rajasthan to understand the soil quality and spatial variability of soil properties using geospatial techniques. Among the different tehsils, Rashmi tehsil had the highest (0.674) soil quality index (SQI) whereas, the highest deterioration was observed in soil quality of Begun (0.557) tehsil of Chittorgarh district of southern Rajasthan. Soil pH ranged from 5.70 to 8.50 and moderately saline to highly saline soils were found in 2–5% area. Soil organic carbon (SOC), KMnO4-N, Olsen-P, NH4OAc-K, available Zn, Fe, Cu, Mn, soil pH and electrical conductivity (EC) were determined. Coefficient of variation (CV) indicated that EC, DTPA extractable Fe, Cu and Mn were high in heterogeneity (CV > 35%) whereas, SOC, Olsen-P and NH4OAc-K showed moderate heterogeneity (CV 15–35%). The spatial variability maps of soil properties indicated that SOC was deficient in 47.0% area whereas, KMnO4-N, Olsen-P and NH4OAc-K were low in 14.8, 7.56 and 26.5% area, respectively. DTPA extractable Zn and Mn were found low in 16–20% area while, DTPA-Fe was low in 47.7% area. Principal component analysis (PCA) representing 56.4% of the total variance, first PC explained 19.3% of the total variation while, PCs second, third and fourth explained 13.8, 12.6 and 10.4, respectively. The SOC was significant and positive correlation with available K, DTPA-Fe and Cu while it had significant negative correlation with soil reaction (soil pH). Top Keywords Soil properties, Spatial variability, Principal component analysis, Soil quality index, Sub-humid climate. Top |