Assessing relationships of cover crop biomass and nitrogen content to multispectral imagery

Cover crops provide valuable roles in sustainable agriculture, provided they produce enough biomass. To accurately measure their services to field management, spatial estimates would be useful to producers. This study used multispectral drone imagery to produce maps of normalized difference vegetation index (NDVI), normalized difference red edge index (NDRE), and a digital surface model (DSM) of cover crop plots on sandy, Mid-Atlantic soils. Cover crops included cereal rye (Secale cereale), mixtures of rye and crimson clover (Trifolium incarnatum), and mixtures of rye and hairy vetch (Vicia villosa). Their biomass was sampled in the spring of 2019, 2020, and 2021, dried, weighed, and analyzed for total nitrogen (N) content. Measurements of NDVI became saturated (i.e., reached a linear plateau) at 3.86 Mg biomass ha-1, NDRE at 5.72 Mg biomass ha-1, and the DSM at 5.11 Mg biomass ha-1. The measured N content became saturated at 80.9, 139.1, and 75 kg N ha-1 for NDVI, NDRE, and the DSM, respectively. Based on log transformations, NDVI was a stronger predictor of biomass and N, but not C:N. The NDRE was important for biomass, N, and C:N, while the DSM interactions with cover crop species helped predict both the N content and C:N of cover crop tissues. Accumulated growing degree days was important as an individual variable for biomass and N and as an interaction with cover crop species. Drone-derived NDVI, along with GDD, were strong predictors of biomass. As an individual variable, normalized difference red edge index was useful for predicting biomass, total N, and C:N. The digital surface model could predict N and C:N as an interaction with cover crop types.