Accounting for surface roughness effects in the near-infrared reflectance sensing of soils

Near-infrared reflectance sensing (NIRS) has stimulated widespread enthusiasm in recent years among soil scientists, in part for its potential to lead to the design of new “proximal” soil sensors in support of precision agriculture, and to increase significantly the amount of information that can be obtained about soils from remote sensors. However, a practical difficulty this technique faces is that soils in the field, unlike the sieved, repacked soil samples used in the laboratory, are generally moist and have uneven surfaces, especially after tillage. Unfortunately, little is known at this point on the effect of surface roughness on NIR spectra. In this context, the present research focuses on the application of NIRS, under laboratory conditions, to chunks (artificially isolated particles or aggregates) of soil of average sizes between 0.04 and 8 mm, obtained in 5 different soils with contrasting features, and repacked in Petri dishes. NIRS measurements were performed when the soils were air-dry, and after rewetting to near-saturation. In virtually all cases, except at the finest chunk size in two soils, the near-infrared reflectance decreased regularly as chunk size increased. Near-saturation of the soils with deionized water resulted in further decreases in reflectance, which obliterated to varying extent the dependence of the reflectance on chunk size. For most cases, whether the soils were dry or near-saturated, computation of the first derivative of the NIR spectra, especially when preceded by moving-average or wavelet-based smoothing, resulted in transformed signals that were virtually independent of surface roughness in a number of distinct spectral regions. These observations suggest that in the range of soil chunk sizes considered, it might be possible practically to circumvent the dependence of NIRS on surface roughness.