Near‐Infrared Reflectance Spectroscopy Prediction of Soil Properties: Effects of Sample Cups and Preparation

Abstract

Most methods for soil analysis are based on wet chemistry. Near infrared reflectance spectroscopy (NIRS) is a cost‐effective and environmentally sound alternative technique. This study evaluated the effect of sample fineness (0.2, 0.5, 1, and 2 mm) and sample cups (transport versus spinning) on the accuracy of NIRS predictions of soil texture, cation‐exchange capacity, pH, total C and N, organic C, and potentially mineralizable N (Nmin) using 150 air‐dried samples collected from a 15‐ha site dominated by Humaquept, Endoaquept, and Dystrochrept soils. The best spectral pretreatment was determined for each property. Principal component analysis (PCA) was used to select samples in calibration and validation sets. Calibration equations were developed using the modified partial least square regression. The accuracy of NIRS prediction was evaluated using three statistics for the prediction set: coefficient of determination (R2), ratio of performance deviation (RPD), and ratio error range (RER). Across the factorial designed treatments, successful calibrations were observed for clay, sand, and Nmin (R2 ≥ 0.90, RPD ≥ 3, RER ≥ 15). Prediction accuracy of pH was poor (0.51 ≤ R2 ≤ 0.74, 1.39 ≤ RPD ≤ 1.92, 6.13 ≤ RER ≤ 8.33), while it was intermediate for remaining properties. Sample fineness of 2 mm appeared to be sufficient since finenesses of 0.2, 0.5, or 1.0 mm did not improve calibration accuracy. These findings at small scale should not be extrapolated and further investigations are required to validate them at a larger scale.