Deterioration of soil quality under resource-intensive modern agriculture in the face of global climate change poses a huge risk to food security. Because of the complex nature, estimators of soil quality often rely upon a limited set of soil attributes, along with statistical data reduction techniques, for developing quality indices, whilst overlooking biological aspects and regional climatic variability. This study screened the most suitable soil quality indexing approaches for a rice-oilseed-based cropping system in the lower Indo-Gangetic plains (IGP).For this, surface soil samples (0-15 cm) were collected from an ongoing longterm fertilizer experiment with a rice-mustard-sesame cropping system in the IGP. The following treatments were assessed for their effect on soil quality: T 1control, T 2 -NPK (recommended NPK doses), T 3 -NPKG (NPK + in situ green manuring), T 4 -NPKGB (NPK + in situ green manuring + biofertilizer) and T 5 -NPKF (NPK + farm yard manure FYM). We found that total organic carbon (TOC), βglucosidase, CaCl 2 extractable S, alkaline KMnO 4 oxidizable N, activity of urease, amidase enzyme and mean weight diameter (MWD) were sensitive key indicators of soil quality. The NPKF treatment maintained the highest soil quality status (0.80-0.91), both under productivity and environmental protection goals, owing to the availability of decomposable carbon. Regression analysis showed a better agreement of equivalent rice yield with expert opinion (EO; R 2 = 0.89) than principal component analysis (PCA; R 2 = 0.76). Finally, we found that the expert opinion approach with the nonlinear scoring function was the best tool for soil quality assessment of the region.
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