🦠 microbiology
Taxonomy-agnostic hyperspectral-morphological phenotyping of fungal pathogen chemical-stress responses using machine learning
This study demonstrates that a taxonomy-agnostic workflow integrating hyperspectral imaging, quantitative morphology, and machine learning can accurately predict the crop-of-isolation (coffee vs. cacao) of *Colletotrichum* fungal isolates based on their standardized chemical-stress response fingerprints, offering a rapid, DNA-free method for high-throughput antifungal screening.
Baek, I., Lim, S., Lovelace, A., Oh, S., Kazem-Rostami, M., Ngo, H., Kim, M., Meinhardt, L., Kandpal, L., Cha, M., Hwang (…)2026-02-17