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Optimised use of data fusion and memory-based learning with an Austrian soil library for predictions with infrared data
(2023-06-24)
Infrared spectroscopy in the visible to near-infrared (vis–NIR) and mid-infrared (MIR) regions is a well-established approach for the prediction of soil properties. Different data fusion and training approaches exist, and the optimal procedures are yet undefined and may depend on the heterogeneity present in the set and on the considered scale. The objectives were to test the usefulness of partial least squares regressions (PLSRs) for soil organic carbon (SOC), total carbon (Ct), total nitrogen (Nt) and pH using ...