Evaluation of near-infrared reflectance spectroscopy (NIRS) for predicting chemical composition of straw silage

Abstract

A representative population of 157 straw silages was used as database for studying the possibilities of NIRS to predict chemical composition. NIRS calibrations were developed by means of modified partial least-squares (MPLS) regression. NIRS analysis of dried straw silages provided accurate predictions of dry matter (DM), crude protein (CP), neutral detergent fibre (NDF), acid detergent fibre (ADF), hemicellulose, ash and lactic acid content as well as pH, with correlation coefficients of cross-validation (R2cv) of 0.87, 0.95, 0.85, 0.84, 0.88, 0.92, 0.85 and 0.96, respectively, and standard error of cross-validation (SECV) of 23, 6, 22, 20, 14, 23, 6, 16 g kg -1DM and 0.06 g kg-1DM, respectively. The NIRS technique could also accurately predict CP content, 0.91 (SECV: 7 g kg-1DM), DM content, 0.92 (SECV: 18 g kg-1DM) and pH, 0.94 (SECV: 0.09 g kg -1DM) of fresh straw silages.