Image-based honey bee larval viral and bacterial diagnosis using machine learning.

ABSTRACT: Honey bees are essential pollinators of ecosystems and agriculture worldwide. With an estimated 50-80% of crops pollinated by honey bees, they generate approximately $20 billion annually in market value in the U.S. alone. However, commercial beekeepers often face an uphill battle, losing anywhere from 40 to 90% of their hives yearly, often by brood diseases caused by bacterial, viral, and fungal pathogens. Accurate diagnosis of brood diseases, especially distinguishing European Foulbrood (EFB) from viral infections with a superficial resemblance to EFB (EFB-like disease), remains challenging. Incorrect diagnoses often lead to prophylactic antibiotic treatment across entire apiaries, exacerbating antibiotic resistance, disrupting native gut microbiota, and increasing susceptibility to oppor

SUBMITTER: Copeland DC 

PROVIDER: S-EPMC12370910 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature