Hyperspectral determination of feed quality constituents in temperate pastures: Effect of processing methods on predictive relationships from partial least squares regression

Development of predictive relationships between hyperspectral reflectance and the chemical constituents of grassland vegetation could support routine remote sensing assessment of feed quality in standing pastures. In this study, partial least squares regression (PLSR) and spectral transforms are used to derive predictive models for estimation of crude protein and digestibility (quality), and lignin and cellulose (non-digestible fractions) from field-based spectral libraries and chemical assays acquired from diverse pasture sites in Victoria, Australia between 2000 and 2002. (cont)