Near-infrared re¯ectance 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 2500 nm in an NIRS 6500 monochromator (NIRSystems, Silver Spring, MD, USA). Modi®ed partial least squares (MPLS) regression was applied to scatter-corrected spectra (SNV and detrend). Calibration models for NIRS measurements gave multivariate correlation coef®cients 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 ®bre (ADF), neutral detergent ®bre (NDF), in vitro organic matter digestibility (IVOMD) and ash in g kg À1 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.