Investigating the potential of Sentinel-2 configuration to predict the quality of Mediterranean permanent grasslands in open woodlands

The assessment of pasture quality in permanent grasslands is essential for their conservation and management, as it can contribute to making real-time decisions livestock management. In this study, we assessed the potential Sentinel-2 configuration predict forage high diverse Mediterranean open woodlands. We evaluated performance Partial Least Squares Regression (PLS) models crude protein (CP), neutral detergent fibre (NDF), acid (ADF) enzyme digestibility organic matter (EDOM) by using three different reflectance datasets: (i) laboratory measurements dry ground samples re-sampled (Spec-lab) (ii) field in-situ canopy resampled (Spec-field); (iii) Bottom Of Atmosphere imagery. For datasets, CP content showed moderate predictive ability. Mean R2test = 0.68 were obtained Spec-lab data, mean decreased 0.11 with Spec-field 0.18 when was used. Statistics NDF worse predictions than those CP: produced 0.64 RPDtest 1.73. values 0.50 1.54 BOA marginally better (mean 0.48, 1.43). ADF EDOM, only made acceptable results. Bands from red-edge region, especially band 5, SWIR regions highest contribution estimating NDF. 2, blue 4, red also seem be important. implementation spectroscopy combination imagery proved feasible produce maps develop larger datasets. This study contributes increasing knowledge applicability