NIRS for predicting Brown Swiss heifer diet composition on mixed pastures in the Amazon region

Source: PubMed Central Open Access, NCBI / U.S. National Library of Medicine

This study evaluated the use of near-infrared spectroscopy (NIRS) to predict the chemical composition of diets consumed by heifers grazing on mixed pastures. A total of 96 diet samples were collected from eight Brown Swiss heifers, dried at 60 °C for 48 h, and analysed for crude protein (CP), ash, neutral detergent fiber (NDF), acid detergent fiber (ADF), and in vitro dry matter digestibility (IVDMD). Samples were scanned using a Unity Scientific near-infrared spectrometer over the 1100–2500 nm wavelength range at 1 nm resolution. Prediction models were developed using partial least squares regression in UCAL software. Excellent calibration results were obtained for CP and NDF, with determination coefficients () of 0.99 and 0.94, respectively. Ash and ADF showed good predictive accuracy (= 0.85 and 0.86), while IVDMD predictions were moderate (= 0.74). These findings demonstrate that NIRS is a rapid, precise, and reliable tool for estimating key nutritional parameters in heifers’ mixed pasture diets, supporting its use for efficient forage quality monitoring. Abs1