Potential of near infrared spectroscopy to predict the voluntary intake of grazed grass

Abstract

This study explored the accuracy of near infrared reflectance spectroscopy (NIRS) to predict the chemical composition and short-term voluntary intake rate of grazed grass. A population of 203 predominantly perennial ryegrass samples were used. Dried milled grass samples were scanned at 2 nm intervals over the wavelength range of 400–2500 nm, and the optical data recorded as log 1/reflectance (log 1/ R), in order to examine the potential of NIRS to provide accurate predictive equations for a range of chemical, biophysical and intake characteristics of the grass. The optimum mathematical treatment for each parameter was selected by minimising the standard error of cross-validation (SECV) to obtain the most accurate predictive equations. Accurate robust calibrations were developed for dried milled grass for prediction of total nitrogen (N), water-soluble carbohydrate (WSC), acid detergent fibre (ADF), and neutral fibre detergent (NDF) (g/kg DM), with SECV of 1.07, 5.05, 5.22 and 10.4, respectively, and corresponding coefficient of determination (1−VR) of 0.97, 0.99, 0.93 and 0.95, respectively. However, equations formed for the range of biophysical parameters: pre-grazing sward height (PSSH), residual grazing sward height (RSSH), herbage mass, bulk density, biting depth, biting rate, intake per bite and intake/h were not as accurate with SECV values of 0.61, 26.6, 14.8, 0.24, 16.9, 4.53, 0.131 and 0.402, respectively, and 1−VR values of 0.61, 0.77, 0.66, 0.73, 0.75, 0.13, 0.60, and 0.71, respectively. NIRS analysis of dried grass samples provides accurate predictions of chemical composition, but poor prediction of the biophysical and short-term intake rate characteristics of grazed grass.