Forage is among the essential ecosystem services provided by tropical savannas. Expected changes in climate and land use may cause a strong decline in herbaceous forage provision and thus make it advisable to monitor its dynamics. Spectroscopy offers promising tools for fast and non-destructive estimations of forage variables, yet suffers from unfavourable measurement conditions during the tropical growing period such as frequent cloud cover and high humidity. This study aims to test whether spatio-temporal information on the quality (metabolisable energy content, ME) and quantity (green biomass, BM) of West African forage resources can be correlated to in situ measured reflectance data. We could establish robust and independent models via partial least squares regression, when spectra were preprocessed using second derivative transformation (ME: max. adjusted R2 in validation (adjR2VAL) = 0.83, min. normalised root mean square error (nRMSE) = 7.3%; BM: max. adjR2VAL = 0.75, min. nRMSE = 9.4%). Reflectance data with a reduced spectral range (350–1075 nm) still rendered satisfactory accuracy.
Our results confirm that a strong correlation between forage characteristics and reflectance of tropical savanna vegetation can be found. For the first time in field spectroscopy studies, forage quality is modelled as ME content based on 24-h in vitro gas production in the Hohenheim gas test system and crude protein concentration of BM. Established spectral models could help to monitor forage provision in space and time, which is of great importance for an adaptive livestock management.