disease-detection
Disease detection in plant science refers to the identification and diagnosis of pathogens, infections, and physiological disorders affecting plant health using methods ranging from visual inspection to molecular and sensor-based technologies. Early and accurate detection is critical for preventing the spread of disease across crops and ecosystems, enabling timely intervention before significant damage occurs. Advances in imaging, genomics, and machine learning are transforming how researchers and growers monitor plant health at scale with greater precision.
Soil In-situ Enrichment Coupled with RPA-CRISPR/Cas12b for Rapid an...
Strawberry wilt can wipe out entire crops silently through the soil, and this new tool lets farme...
Bridging Artificial Intelligence, Machine Learning with Green Nanot...
Fungal diseases silently devastate the tomatoes, wheat, and potatoes in farms near you — this res...
Development of a PCR-Cas12a-LFD visual detection system for highly ...
Faster, easier pathogen detection means farmers can catch crop-killing infections before they spr...
Efficient deep learning framework for arecanut disease detection us...
Arecanut palms supply the betel nut used in products consumed by hundreds of millions of people a...
