Accurate prediction of huanglongbing occurrence in citrus plants by machine learning-based analysis of symbiotic bacteria.

ABSTRACT: Huanglongbing (HLB), the most prevalent citrus disease worldwide, is responsible for substantial yield and economic losses. Phytobiomes, which have critical effects on plant health, are associated with HLB outcomes. The development of a refined model for predicting HLB outbreaks based on phytobiome markers may facilitate early disease detection, thus enabling growers to minimize damages. Although some investigations have focused on differences in the phytobiomes of HLB-infected citrus plants and healthy ones, individual studies are inappropriate for generating common biomarkers useful for detecting HLB on a global scale. In this study, we therefore obtained bacterial information from several independent datasets representing hundreds of citrus samples from six continents and used these dat

SUBMITTER: Liu HQ 

PROVIDER: S-EPMC10258322 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature