plant-disease-detection
Plant disease detection encompasses the methods and technologies used to identify, diagnose, and monitor diseases affecting plants, ranging from traditional visual inspection to advanced imaging, molecular diagnostics, and machine learning-based tools. Early and accurate detection is critical in plant science because diseases caused by pathogens such as fungi, bacteria, viruses, and nematodes can devastate crops, reduce yields, and threaten food security. Rapid detection enables timely intervention, supports resistance breeding programs, and helps researchers understand host-pathogen interactions at the molecular level.
Field-deployable CRISPR-cas variants for rapid on-site detection of...
Faster disease detection means farmers and growers can catch outbreaks before they spread, protec...
Discovery of Viroids and Viroid-Like RNAs in Plants.
Viroids are responsible for devastating crop diseases worldwide, and finding new ones earlier cou...
Machine learning is reshaping how farmers predict yields and catch disease
AI tools trained on field data are getting good enough to flag disease on a crop plant before vis...
Application of digital PCR and CRISPR/Cas13a-based fluorescent assa...
Cotton fields in Texas are under threat from a spreading virus that's quietly cutting yields, and...
Development of a Recombinase Polymerase Amplification-CRISPR/Cas12a...
Cacao trees can silently harbor a virus for entire growing seasons with zero visible symptoms, me...
Machine learning tools are reshaping how farmers predict yields and...
The algorithms being tested on commercial farms today will likely shape the disease-warning apps ...
Fuzzy logic beats standard AI at spotting new tomato diseases
The tomato plants wilting or spotting in your backyard garden could someday get diagnosed by an a...