RESEARCH - USE OF NEAR INFRARED REFLECTANCE (NIR) SPECTROSCOPY TO PREDICT CHEMICAL COMPOSITION OF FORAGES IN BROAD-BASED CALIBRATION MODELS (Uso de la espectroscopía de reflectancia en el infrarrojo cercano (NIR) para predecir la composición química de forrajes en modelos de calibración amplia)

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