Use of Near Infrared Reflectance (NIR) Spectroscopy to Predict Chemical Composition of Forages in Broad-Based Calibration Models

The objective of the study was to evaluate the potential of near infrared reflectance (NIR) spectroscopy as a rapid method to predict the chemical composition of forage in broad-based calibration models. In total, 650 samples representing a wide range of chemical characteristics, phenological states and origins were scanned in an NIR instrument. The coefficient of determination in calibration (R²) and standard error in cross validation (SECV) for the NIR calibration models were as follows: dry matter 0.95 (SECV: 0.7%), crude protein 0.98 (SECV: 0.98%), ash 0.90 (SECV: 0.99%), in vitro organic matter digestibility 0.90 (SECV: 3.6%), acid detergent fiber 0.95 (SECV: 2.0%) and neutral detergent fiber 0.86 (SECV: 5.4%) on a dry matter basis. The results demonstrated the potential of NIR to predict the chemical composition of different forage plant species ; however, it is suggested that the technique could be used as a routine procedure to apply in breeding programs only if calibration is done for each species, season and particular conditions.