Abstract

Assessment of soil quality index (SQI) using only the surface soil properties provides an incomplete information as the crop productivity is influenced by both surface and subsurface properties, with the latter being inherently linked to pedogenic processes. Two different SQIs were estimated for soil surface (0–15cm) and control section (0–100cm) using soil profile data of six identified soil series in part of semi-arid tropical (SAT) Deccan plateau and correlated with crop yield. Principal component analysis (PCA) and expert opinion (EO) methods were used for selecting minimum soil data set (MDS). Additive and weighted index methods were compared for SQI estimation. SQI obtained showed variation as PCA and EO methods produced different results. In general, weighted index SQIs were better correlated with crop yield than the additive index SQIs for both PCA and EO methods. EO derived weighted index SQI were comparable for both surface and control section except for few cases and consistent in their correlation with the crop yield, indicating its better performance as compared to PCA. Reason is that the PCA is a data dimension reduction technique whereas EO method is primarily conceived by the experts on cause-effect relationship of soil properties (such as hydraulic conductivity, CaCO3 and exchangeable sodium percentage) that are influenced by regressive pedogenic processes in SAT environments. Results showed that consideration of both surface and control section soil properties helps in establishing a good relationship between soil functions and management goal. In addition, it also satisfies the need to integrate both surface and subsurface soil information for soil quality assessment.

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