ASHS 2025 Conference

Hemp (Cannabis sativa L.) is a remarkably versatile crop with extensive applications in food, fiber, and medicine, offering environmentally sustainable and highly productive raw materials across various industries. Historically cultivated primarily for fiber, modern dual-purpose hemp varieties now present enhanced economic opportunities by enabling the simultaneous harvesting of seeds for grain and stems for fiber. Nitrogen (N) fertilization significantly influences key growth parameters, including plant height, stem diameter, biomass accumulation, and seed yield. However, conventional nitrogen assessment methods are invasive and labor-intensive. To address these challenges, multispectral drone imaging has emerged as a non-destructive alternative, leveraging correlations between nitrogen levels and leaf chlorophyll content to enable rapid monitoring of critical physiological indicators such as assimilation rates, stomatal conductance, and transpiration rates. In 2024, an experiment was conducted at North Carolina A0.70), chlorophyll content and BNDVI (R² = 0.55), stomatal conductance and NDVI (R² = 0.82), and transpiration rate and MCARI (R² = 0.56). In contrast, negative correlations were observed with SIPI2 (R² = 0.69), TGI (R² = 0.39), and additional SIPI2 indices (R² = 0.54 and R² = 0.39, respectively). This study highlights the potential of integrating drone-based remote sensing and machine learning for efficient, non-destructive monitoring in hemp cultivation. By advancing precision agriculture practices, these technologies offer promising pathways to enhance productivity, optimize nitrogen management, and promote sustainability in hemp cultivation.