Pasture Quality Monitoring Based on Proximal and Remote Optical Sensors: A Case Study in the Montado Mediterranean Ecosystem

Permanent dryland pastures are the basis of animal feed in extensive grazing systems. Seasonality and inter-annual climatic variability, associated with shallow, acidic, not very fertile soils, result low productivity rapid degradation pasture quality, which requires supplementation feed. In this study, carried out a biodiverse field Mediterranean region southern Portugal, vegetation index (NDVI, Normalized Difference Vegetation Index) obtained from measurements performed by proximal optical sensor (PS) satellite images (RS) was used to assess quality parameters (pasture moisture content, PMC, crude protein, CP, neutral detergent fiber, NDF). The monitoring throughout 2021/2022 growing season. Significant correlations were between NDVI PS RS (R2 0.84) reference values laboratory protocols: PMC 0.88 0.78, respectively), CP 0.67 0.63, NDF 0.50 0.46, respectively). This case study also demonstrated spatial temporal variability vegetative vigour and, consequently, Montado, characteristic ecosystem. These results show pertinence these technologies supporting decision-making process farm manager, namely, estimate needs animals critical phases, especially after spring production peak before autumn peak.