AraDQ: an automated digital phenotyping software for quantifying disease symptoms of flood-inoculated Arabidopsis seedlings.

ABSTRACT:

Background

Plant scientists have largely relied on pathogen growth assays and/or transcript analysis of stress-responsive genes for quantification of disease severity and susceptibility. These methods are destructive to plants, labor-intensive, and time-consuming, thereby limiting their application in real-time, large-scale studies. Image-based plant phenotyping is an alternative approach that enables automated measurement of various symptoms. However, most of the currently available plant image analysis tools require specific hardware platform and vendor specific software packages, and thus, are not suited for researchers who are not primarily focused on plant phenotyping. In this study, we aimed to develop a digital phenotyping tool to enhance the speed, accuracy, and reliability

SUBMITTER: Lee JH 

PROVIDER: S-EPMC10943777 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature