A comparison of ImageJ and machine learning based image analysis methods to measure cassava bacterial blight disease severity.

ABSTRACT:

Background

Methods to accurately quantify disease severity are fundamental to plant pathogen interaction studies. Commonly used methods include visual scoring of disease symptoms, tracking pathogen growth in planta over time, and various assays that detect plant defense responses. Several image-based methods for phenotyping of plant disease symptoms have also been developed. Each of these methods has different advantages and limitations which should be carefully considered when choosing an approach and interpreting the results.

Results

In this paper, we developed two image analysis methods and tested their ability to quantify different aspects of disease lesions in the cassava-Xanthomonas pathosystem. The first method uses ImageJ, an open-source platform widely used in the b

SUBMITTER: Elliott K 

PROVIDER: S-EPMC9210806 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature