Cover crops have the potential to reduce nitrate (NO 3) losses while improving soil quality, yet achieving uniform cover crop establishment can be challenging in the US Midwest. Understanding the variability of cover crop biomass and nitrogen (N) uptake at the fieldscale is an important step in determining potential effects on the following cash crop and benefits to water quality, but efficient and nondestructive methods are lacking. The objective of this study was to evaluate a lightweight unmanned aerial vehicle (UAV) mounted with a multispectral sensor in estimating cover crop (grass species) biomass and N uptake prior to cover crop termination at four commercial fields in Illinois during the 2017 growing season. Two fields had triticale (× Triticosecale Wittmack) before corn (Zea mays L.) and two had cereal rye (Secale cereale L.) before soybean (Glycine max [L.] Merr.). Forty ground-truth biomass samples (1 m 2) were collected on the day of each UAV flight across each field. Linear relationships were established between cover crop biomass and N uptake and four vegetation indices (VIs; Normalized Difference Vegetation Index [NDVI], Green Ratio Vegetation Index [GRVI], Green Normalized Difference Vegetation Index [GNDVI], and Triangular Vegetation Index [TVI]). The four VIs performed similarly in estimating cover crop biomass and N uptake (R 2 range, 0.42 to 0.93; RMSE range, 9.4% to 27.2% of the range of biomass or N uptake). A high degree of within-field variability for NDVI was observed at all fields, with biomass and N uptake at soybean fields ranging from 0 to 1,790 kg ha-1 and 0 to 48.5 kg ha-1 , respectively, and at corn fields 0 to 840 kg ha-1 and 0 to 31.5 kg ha-1 , respectively. Because cover crop biomass is often estimated based on hand samples, we also simulated the effects of biomass sampling number (2, 5, 10, or 15) on the probability of reaching different accuracy levels for estimating field means for different field sizes. Under the growing conditions of this single study year and relatively modest biomass accumulation (<1,400 kg ha-1), results from this preliminary study provide evidence that UAVs are a viable technique to obtain relatively rapid, nondestructive estimates of biomass and N uptake of two grass cover crops at vegetative stage prior to termination at the field-scale in the US Midwest. This approach could help effectively utilize scarce conservation resources, but further work is needed to evaluate other cover crop species under a wider range of growth conditions.

More on-farm research is necessary to determine the practical benefits and drawbacks of cover crops at the field-scale. The objective of this study was to advance the use of unmanned aerial vehicle (UAV) platforms for evaluating the effects of cover crop biomass on crop growth and grain yield in two corn (Zea mays L.) fields and two soybean [Glycine max (L.) Merr.] fields in Illinois. Experiments were 17-29 ha in size with cover crop and non-cover crop treatment strips replicated four times. Flights were conducted with a multispectral sensor at three early-to midseason crop growth stages. On the same day, 40 biomass samples were collected to ground-truth reflectance data. Results indicated that normalized difference vegetation index (NDVI) could predict crop biomass (V3-V10 in corn, V5-R1 in soybean) with moderate accuracy (R 2 = .40-.64) using an exponential model in corn and a linear regression model in soybean. Cover crops significantly (p < .1) reduced early-to mid-season corn and soybean NDVI at several sampling events, yet no yield penalty was detected across fields. Correlations between cover crops, crop growth, and grain yield were low and inconsistent when using NDVI maps and estimated biomass and N uptake maps. This study highlights an opportunity for utilizing highresolution datasets in on-farm experiments to investigate the impact of cover crops on crop growth and yield on a field-specific basis. INTRODUCTIONCorn (Zea mays L.)-soybean [Glycine max (L.) Merr.] rotations are productive cropping systems in the U.S. Midwest, but they are associated with environmental costs including nitrate losses and a decline in soil quality (Moore, Wiedenhoeft, Kaspar, & Cambardella, 2014;Ruffo, Bullock, & Bollero, 2004). Cover crops can provide important ecological benefits and are widely promoted by agricultural and conservation groups to reduce nutrient pollution and soil degradation, thereby Abbreviations: NDVI, normalized difference vegetation index; UAV, unmanned aerial vehicle.