Abstract
Soil aggregation is critical for assessing soil health; however, conventional aggregation measurement is laborious and expensive. The performance of near infrared diffuse reflectance spectroscopy (NIR) and basic soil properties for estimation of wet aggregation indices was investigated. Two samples sets representing different soils from across Lake Victoria Basin in Kenya were used for the study. A model calibration set ( n = 136) was obtained following a conditioned Latin hypercube sampling, and validation set ( n = 120) using a spatially stratified random sampling strategy. Spectral measurements were obtained for air-dried ( RPD (ratio of prediction deviation) of 1.4–2.0. Independent testing of NIR PLS gave RPD = 1.4 for macro and RPD = 1.2–1.0 for unstable and soil predictors. NIR could estimate macro and unstable fractions with moderate reliability, and; NIR was superior over soil properties for stability pedotransfer purposes. Further efforts should widely test performance for a wider range of soil types and calibration strategies for improved geographic transferability of models.
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