NIRS potential use for the determination of natural resources quality from dehesa (acorn and grass) in Montanera system for Iberian pigs

espanolLa tecnologia NIRS se utilizo como alternativa a los metodos convencionales para determinar el contenido de nutrientes en bellotas y pastos de la dehesa. Materia seca (MS), contenido en grasa (G), proteina total (TP), almidon, compuestos fenolicos totales (FT), α-tocoferol, γ-tocoferol, acidos grasos, fibra neutro detergente (FND), actividad antioxidante total (AAT) y energia total (ET) fueron determinadas por metodos convencionales para el posterior desarrollo de las ecuaciones de prediccion del NIRS. Se han realizado todos los espectros NIR de cada una de las muestras para todos los parametros estudiados obteniendo un modelo predictivo y una validacion externa. Se han obtenido buenas ecuaciones de prediccion para la humedad, contenido en grasa, proteina total, energia total y γ –tocoferol en muestras de bellotas obteniendo un alto coeficiente de correlacion (1-VR) y un bajo error estandar de prediccion (SEP) (1-VR=0.81, SEP=2.62; 1-VR=0.92, SEP=0.54; 1-VR=0.86, SEP=0.47; 1-VR=0.84, SEP=0.2; 1-VR=0.88, SEP=5.4, respectivamente), asi como la proteina total, NDF, α-tocoferol y contenido de acido linolenico en muestras de pasto (1-VR=0.9, SEP=1.99; 1-VR=0.87, SEP=4.13; 1-VR=0.76, SEP=10.9; 1-VR=0.82, SEP=0.6, respectivamente). Por lo tanto, estos modelos de prediccion podrian ser utilizados para determinar la composicion nutricional de los recursos naturales de la Montanera. EnglishNIRS technology has been used as an alternative to conventional methods to determinate the content of nutrients of acorns and grass from dehesa ecosystem. Dry matter (DM), crude fat (CF), crude protein (CP), starch, total phenolic compounds (TP), α-tocopherol, γ-tocopherol, fatty acids, neutral detergent fiber (NDF), total antioxidant activity (TAA) and total energy (TE) were determined by conventional methods for later development of NIRS predictive equations. The NIR spectrum of each sample was collected and for all studied parameters, a predictive model was obtained and external validated. Good prediction equations were obtained for moisture, crude fat, crude protein, total energy and γ-tocopherol in acorns samples, with high coefficients of correlation (1-VR) and low standard error of prediction (SEP) (1-VR=0.81, SEP=2.62; 1-VR=0.92, SEP=0.54; 1-VR=0.86, SEP=0.47; 1-VR=0.84, SEP=0.2; 1-VR=0.88, SEP=5.4, respectively) and crude protein, NDF, α-tocopherol and linolenic acid content in grass samples (1-VR=0.9, SEP=1.99; 1-VR=0.87, SEP=4.13; 1-VR=0.76, SEP=10.9; 1-VR=0.82, SEP=0.6, respectively). Therefore, these prediction models could be used to determinate the nutritional composition of Montanera natural resources.