Grinding and spectra replication often improves mid‐DRIFTS predictions of soil properties

• DOI: 10.1002/saj2.20021
• Publication Date: 2020-05-29T10:10:19Z
• Authors: Leonardo Deiss; Steve W. Culman; M. Scott Demyan
• Keywords: 2. Zero hunger; 0401 agriculture, forestry, and fisheries; 04 agricultural and veterinary sciences; 15. Life on land

AbstractThere is an increased interest in using diffuse reflectance infrared Fourier transform spectroscopy in the mid‐infrared region (mid‐DRIFTS) for high‐throughput prediction of soil properties, but basic methodological factors toward this end have yet to be thoroughly vetted. This study aimed to determine how the combined effects of soil grinding (sieved to <2.0 mm and finely ground to <0.5 mm) and sample replication (single or multiple soil subsamples, using one‐to‐four replicates) affect the spectral quality and predictive performance (accuracy) of automated plate‐based mid‐DRIFTS for soil analysis. We evaluated chemometric prediction performance of soil physical, chemical, and biological variables (clay, sand, pH, total organic C, and permanganate‐oxidizable C [POXC]) in 397 soils from the U.S. Midwest. Sieved soils (<2.0 mm) increased the overall spectral variability compared to finely ground soils (<0.5 mm) and led to a distinct wavenumber importance allocation in support vector machine models. These spectral changes degraded prediction performance of <2.0 mm samples when compared to <0.5 mm samples. The number of spectral replicates had a smaller effect on spectral properties, but impacted prediction accuracies of soil properties. In general, prediction outcomes improved with four spectral replicates either within a single soil subsample or across different soil subsamples. Our data collectively suggest that soil particle‐size reduction to <0.5 mm and collecting multiple spectra improve mid‐DRIFTS predictions. Recommendations to optimize high‐throughput mid‐DRIFTS should consider the tradeoffs between prediction accuracy and the effort needed to prepare soil samples and acquire spectra.