Estimating the areal yield of forage nutritive components in a Mediterranean Sulla (Hedysarum coronarium L.) sward using UAV multispectral imagery

Accurate information on pasture nutritive resources is essential for improving grazing management and supporting precision livestock systems, particularly in Mediterranean environments characterized by strong seasonal variability and heterogeneous pasture conditions. In this study, UAV multispectral imagery was evaluated for estimating the areal yield of key forage quality components in a Mediterranean pasture dominated by Hedysarum coronarium L. over two growing seasons under pre- and post-grazing conditions. Forage biomass and laboratory-derived quality traits were collected from 28 georeferenced plots across four sampling dates. Crude protein (CP), neutral detergent fibre (NDF) on an organic matter basis, acid detergent fibre (ADF), digestible NDF after 48 h incubation, undigested NDF after 240 h incubation and ash content were converted into areal yields (g m −2 ) by integrating forage quality concentration with dry biomass availability. UAV multispectral surveys were performed using DJI Mavic 3 Multispectral and MicaSense Altum-PT sensors, and 30 vegetation indices were evaluated through empirical single-index regression models. Among the tested vegetation indices, EVI2 provided the most consistent and interpretable relationships for fibre-related components yields, whereas green-based indices such as GI and GRVI were particularly informative for CP and ash yields. Calibration and location-grouped hold-out validation showed that UAV-derived spectral responses associated with canopy greenness, red–green contrast and structural development were associated with spatial variability in biomass-weighted forage nutritive component yields. Spatial prediction maps highlighted pronounced within-field heterogeneity and revealed clear differences between pre- and post-grazing conditions, particularly for protein and fibre-related components. Overall, the results highlight the potential of UAV multispectral imagery for estimation and spatial mapping forage nutritive component yields in Mediterranean grazing systems. The proposed approach may contribute to the future development of precision grazing strategies by providing spatially explicit information on pasture nutritional heterogeneity using simple and interpretable spectral models.