Indian Journal of Dryland Agricultural Research and Development
Open Access
  • Year: 2008
  • Volume: 23
  • Issue: 2

Assessment of Influence of Soil-site Characteristics on Soybean Productivity in Swell-shrinks and Associated Soils of Semi-arid Tropics

  • Author:
  • G. Ravindra Chary, K.P.R. Vittal, G.R. Maruthi Sankar, V. Ramamurthy, R.A. Sharma, D.P. Dubey, M.N. Patil, K.L. Sharma, G. Pratibha
  • Total Page Count: 10
  • Page Number: 14 to 23

1Central Arid Zone Research Institute, Jodhpur

Central Research Institute for Dryland Agriculture, Santoshnagar, Hyderabad – 500 059

Abstract

A study has been conducted in swell-shrink and associated soils to assess the influence of soil-site characteristics on rainfed soybean yield attained with low and improved management practices across four microwatersheds viz., Varkhed and Panubali in Maharashtra; and Jaitpura and Khuj in Madhya Pradesh. There was a wide spatial variability of soil-site characteristics of swell-shrink and associated soils viz., Typic Ustorthents, Typic Haplustepts, Vertic Haplustepts, Typic Haplusterts within and across four microwatersheds. In general, soybean productivity was high in Typic Haplusterts followed by Vertic Haplustepts while it was low with Typic Ustorthents under both management levels. Based on correlation and regression analysis, the most important soil-site characteristics influencing soybean yield were found to be drainage among site characteristics; soil depth and AWC among soil physical, and OC and CEC among soil chemical characteristics. The study indicated that for improving the productivity of rainfed soybean cultivated in swell-shrink and associated soils, soil depth, AWC, OC and CEC with ideal conditions were essential for attaining a yield level of 7–8 q ha−1 with low management, while only two soil characteristics viz., soil depth and AWC were found important for attaining a yield level of 12–14 q ha−1 with improved management.

Keywords

Swell-shrink and associated soils, soil-site characteristics, regression modeling, soybean productivity