Nitrogen Fertilizer Effects on Hemp Biomass Production Detected by Drone-based Spectral Imaging

The recent introduction of hemp (Cannabis sativa L., <0.3% Δ9-tetrahydrocannabinol) to the United States has been met with a limited understanding of cultivation practices and environmental monitoring techniques. Aerial imaging can contribute to site-specific management and improve hemp production by monitoring crop growth and health in response to agricultural inputs. Drone-based spectral imaging was deployed with the objective of identifying a spectral signature for floral hemp variety ‘Wife’; detecting differences in plant size, yield, and spectral reflectance in response to nitrogen (N) fertilizer application rates; and assessing field-level variation in crop health and yield observable by aerial imaging to advance hemp management decisions. We conducted an in-field N experiment to test the effects of six N application rates (0, 56, 112, 168, 224, and 280 kg·ha−1) on the high-cannabinoid flower variety ‘Wife’ from 2020 to 2022. A quadcopter with a multispectral sensor collected images from an altitude of 61 m between final fertilization and harvest. Each plant canopy was defined in the image and evaluated for size and reflectance as Normalized Difference Vegetation Index (NDVI) and Green Normalized Difference Vegetation Index (GNDVI). The N application rate of 224 kg·ha−1 N resulted in significant increase in hemp biomass from 112 and 56 kg·ha−1, whereas significant increases in floral yield and canopy area were observed just at 112 and 56 kg·ha−1 N. The N application rate of 224 kg·ha−1 N produced significantly greater NDVI values compared with those of the application rate of 112 kg·ha−1 N, whereas GNDVI was significantly greater at 224 kg·ha−1 N when compared with N rates less than 168 kg·ha−1 N. Canopy area and plant indices consistently showed strong positive linear correlation with aboveground biomass. This study revealed that drone-based aerial imaging can be an effective tool for monitoring crop growth and health while informing N management decisions in hemp cropping systems.