Estimation of Biomass and N Uptake in Different Winter Cover Crops from UAV-Based Multispectral Canopy Reflectance Data

Cover crops are known to provide beneficial effects agricultural systems such as a reduction in nitrate leaching, erosion control, and an increase soil organic matter. The monitoring of cover crops’ growth (e.g., green area index (GAI), nitrogen (N) uptake, or dry matter (DM)) using remote sensing techniques allows us identify the physiological processes involved optimise management decisions. Based on data two-year trial (2018, 2019) Kiel, Northern Germany, multispectral sensor Sequoia (Parrot) was calibrated selected parameters winter oilseed radish, saia oat, spring vetch, rye sole combined mixtures. Two simple ratios (SRred, SRred edge) two normalised difference indices (NDred, NDred were calculated tested for their predicting power. Furthermore, advantage species/mixture–individual compared universal models analysed. best predicted GAI, DM, N uptake (R2: 0.60, 0.53, 0.45, respectively) model approach. canopy oat vetch estimated by species–individual models, achieving higher R2 than with model. Comparing mixture–individual revealed low relative error differences below 3%. findings current study serve tool rapid inexpensive estimation that determine environmental services.