Development of Reflectance Spectral Libraries for Characterization of Soil Properties

Abstract

Methods for rapid estimation of soil properties are needed for quantitative assessments of land management problems. We developed a scheme for development and use of soil spectral libraries for rapid nondestructive estimation of soil properties based on analysis of diffuse reflectance spectroscopy. A diverse library of over 1000 archived topsoils from eastern and southern Africa was used to test the approach. Air‐dried soils were scanned using a portable spectrometer (0.35–2.5 μm) with an artificial light source. Soil properties were calibrated to soil reflectance using multivariate adaptive regression splines (MARS), and screening tests were developed for various soil fertility constraints using classification trees. A random sample of one‐third of the soils was withheld for validation purposes. Validation r 2 values for regressions were: exchangeable Ca, 0.88; effective cation‐exchange capacity (ECEC), 0.88; exchangeable Mg, 0.81; organic C concentration, 0.80; clay content, 0.80; sand content, 0.76; and soil pH, 0.70. Validation likelihood ratios for diagnostic screening tests were: ECEC <4.0 cmol c kg −1 , 10.8; pH <5.5, 5.6; potential N mineralization >4.1 mg kg −1 d −1 , 2.9; extractable P <7 mg kg −1 , 2.9; exchangeable K <0.2 cmol c kg −1 , 2.6. We show the response of prediction accuracy to sample size and demonstrate how the predictive value of spectral libraries can be iteratively increased through detection of spectral outliers among new samples. The spectral library approach opens up new possibilities for modeling, assessment and management of risk in soil evaluations in agricultural, environmental, and engineering applications. Further research should test the use of soil reflectance in pedotransfer functions for prediction of soil functional attributes.