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Classification of fields into management units based on soil variability and fertility is important for spatial crop planning. The present study was conducted in Chukanagallu subwatershed (97 km 2 ), Koppal district of Northern Karnataka Plateau, India to map the soil fertility management units and to analyse the suitability of soil for different crops. Random forest regression and classification algorithms were used to map the differentiating characteristics of soil series (soil depth, coarse fragments and soil colour), physicochemical properties (pH, EC and OC) and fertility parameters (P 2 O 5 , K 2 O, S, Fe, Mn, Zn, Cu, B). Random forest model performed well for the prediction of fertility parameters ( R2  = 44–73%) and physicochemical properties ( R2  = 39–83%) compared to soil depth and coarse fragments ( R2  = 17–18%). Predicted soil fertility parameters and physicochemical properties were used for the delineation of different homogenous fertility management units. Soil series characteristics and fertility parameters were also evaluated using a multi-criteria approach for suitability of soil for cotton, groundnut and rice cultivation and the results showed that major area of subwatershed is moderately suitable for the cultivation of cotton, rice and groundnut. The management units derived from DSM approach were symmetrical in production potential and requires similar management aspects which are useful for appropriate planning of management strategies such as crop selections and nutrient management to achieve sustainable production.

Defining fertility management units and land suitability analysis using digital soil mapping approach