Deep learning classification of INSV-associated weeds in Monterey county using a curated RGB image dataset.

ABSTRACT: Weeds, defined by their ecological and economic impact rather than taxonomy, present a major challenge to agriculture by competing with crops for limited resources and serving as vectors for disease. In Monterey County, California, one of the most productive farming regions in the United States, Sonchus oleraceus (annual sowthistle) and Malva parviflora (little mallow) have been linked to over $150 million in crop losses due to their role in spreading Impatiens Necrotic Spot Virus (INSV). As precision agriculture becomes more important in high-value production systems, deep learning and image-based classification offer promising tools for early weed detection and disease prevention. To address the absence of region-specific image datasets, this study presents the first curated, high-resolu

SUBMITTER: Sharma AK 

PROVIDER: S-EPMC12749732 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature