Combined diffuse reflectance spectroscopy and digital soil mapping for soil assessment in smallholder farms

Abstract

Diffuse reflectance spectroscopy (DRS) and digital soil mapping (DSM) offer opportunities to rapidly assess soil in large areas. Specifically, the combined DRS-DSM modelling pipeline may be used to create soil test recommendations for every smallholder farm in a given region although comprehensive testing of such a pipeline is rarely attempted. With multi-year and multi-site soil spectral data from the smallholder farms of the Bundelkhand region, we evaluated the DRS-DSM pipeline for estimating soil properties and making nutrient recommendation for every smallholder farm both within and outside the DRS calibration zones. Specifically, we compared both measured and DRS-estimated soil properties as inputs in DSM approaches using 1112, 607, and 407 soil samples collected during 2018 (T₂₀₁₈: calibration zone), 2021 (T₂₀₂₁: within the calibration zone), and 2022 (T₂₀₂₂: outside the calibration zone), respectively, for estimating 17 soil parameters and their soil test crop response (STCR) ratings. For T₂₀₂₂ samples, DRS models calibrated within the calibration zone accurately predicted 7 out of 17 soil properties with Lin’s concordance correlation coefficients (LCCC) exceeding 0.6. Spiking these datasets with T₂₀₂₂ data further improved predictions to 10 properties and reduced errors by 3–29%. In T₂₀₂₁ dataset, both measured property- and DRS-based DSM approaches achieved comparable accuracy. Estimated STCR rating accuracies for the DRS-DSM pipeline exceeded 70% for 9 out of 13 properties suggesting that these two emerging technologies may be combined to make nutrient recommendations across smallholder farms within a given region.