Variogram Analysis of Hyperspectral Data to Characterize the Impact of Biotic and Abiotic Stress of Maize Plants and to Estimate Biofuel Potential

A considerable challenge in applied agricultural use of reflection-based spectroscopy is that most analytical approaches are quite sensitive to radiometric noise and/or low radiometric repeatability. In this study, hyperspectral imaging data were acquired from individual maize leaves and the main objective was to evaluate a classification system for detection of drought stress levels and spider mite infestation levels across maize hybrids and vertical position of maize leaves. A second objective was to estimate biomass and biofuel potential (heating value) of growing maize plants. Stepwise discriminant analysis was used to identify the five spectral bands (440, 462, 652, 706, and 784 nm) that contributed most to the classification of three levels of drought stress (moderate, subtle, and none) across hybrids, leaf position, and spider mite infestation. Regarding the five selected spectral bands, average reflectance values and standard variogram parameters (