NIRS 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
