The use of Near Infrared Reflectance Spectroscopy on dried samples to predict biological parameters of grass silage

This study was undertaken to explore the accuracy of Near Infrared Reflectance Spectroscopy (NIRS) for the prediction of in vivo OMD (%) and voluntary intake (g/kg W0.75) measured through sheep and cattle respectively. A population of 136 grass silages representing a wide range in chemical and biological parameters was used in this investigation. The dried milled silage samples were scanned at 2 nm intervals over the wavelength range 400–2500 nm and the optical data recorded as log 1/Reflectance (log 1/R). The paper examines three multivariate regression techniques: modified partial least squares (MPLS), principal component regression (PCR) and stepwise multiple linear regression (SMLR) and investigates the effect of spectral pretreatment using 1st and 2nd order derivatization with and without three scatter correction procedures: standard normal variate and detrending (SNV-D), normal multiplicative scatter correction (NMSC) and weighted multiplicative scatter correction (WMSC), to optimize accuracy of prediction. The optimum mathematical treatment was selected by minimizing the standard error of prediction (SEP) of a blind validation set using a calibration and validation set of 90 and 46 respectively. The optimum methods were for in vivo organic matter digestibility (OMD), the stepwise regression procedure using 1st derivatization with a scatter correction (SEP 2.4%, R2 0.87) and for intake the MPLS regression technique again using 1st derivatization and a scatter correction (SEP 4.77 g/kg W0.75, R2 0.79). Comparison of three wavelength ranges (1100–2500 nm, 700–2500 nm and 400–2500 nm) on the effect of calibration performance for OMD and intake showed little improvement from extending the range beyond 1100–2500 nm.