Herbage Mass

Herbage mass estimation, crucial for optimizing agricultural practices and environmental management, focuses on accurately determining the amount of plant biomass in a given area. Current research emphasizes the development of automated, non-destructive methods, leveraging computer vision techniques like structure-from-motion photogrammetry and deep learning algorithms, including neural networks and unsupervised learning approaches, to analyze images from various sources (ground-level cameras, drones). These advancements aim to replace labor-intensive manual sampling, enabling more efficient and precise assessments of herbage yield and composition for improved fertilizer management and livestock production.