The use of near-infrared reflectance spectroscopy (NIRS) to predict the composition of whole maize plants

Near-infrared reflectance spectroscopy (NIRS) was used to predict the chemical composition of whole maize plants (Zea mays L) in breeding programmes at INIA La Estanzuela, Uruguay. Four hundred samples (n = 400) were scanned from 400 to 2500nm in an MRS 6500 monochromator (NIRSystems, Silver Spring, MD, USA). Modified partial least squares (MPLS) regression was applied to scatter-corrected spectra (SNV and detrend). Calibration models for MRS measurements gave multivariate correlation coefficients of determination (R-2) and standard errors of cross-validation (SECV) of 0.72 (SECV 9.5), 0.96 (SECV 7.7), 0.98 (SECV 16.5), 0.96 (SECV 34.3), 0.98 (SECV 17.8) and 0.98 (SECV 6.1) for dry matter (DM), crude protein (CP), acid detergent fibre (ABF), neutral detergent fibre (NDF), in vitro organic matter digestibility (IVOMD) and ash in g k(-1) on a dry weight basis respectively. This paper shows the potential of NIRS to predict the chemical composition of whole maize plants as a routine method in breeding programmes and for farmer advice. (C) 2000 Society of Chemical Industry.