Detecting Plant Infections: Prospects for Chlorophyll Fluorescence Imaging

Abstract

Phytopathogens are a significant challenge to agriculture and food security. In this regard, methods for the early diagnosis of plant diseases, including optical methods, are being actively developed. This review focuses on one of the optical diagnostic methods, chlorophyll fluorescence (ChlF) imaging. ChlF reflects the activity of photosynthetic processes and responds subtly to environmental factors, which makes it an excellent tool for the early detection of stressors, including the detection of pathogens at a pre-symptomatic stage of disease. In this review, we analyze the peculiarities of changes in ChlF parameters depending on the type of pathogen (viral, bacterial, or fungal infection), the terms of disease progression, and its severity. The main mechanisms responsible for the changes in ChlF parameters during the interaction between pathogen and host plant are also summarized. We discuss the advantages and limitations of ChlF imaging in pathogen detection compared to other optical methods and ways to improve the sensitivity of ChlF imaging in the early detection of pathogens.

Code and data availability

This is a review article on chlorophyll fluorescence imaging for plant pathogen detection. The supplied blocks contain no public phenotype datasets, plant images, author analysis code, trained models, or supplements with such assets; the paper only summarizes and cites prior experimental studies.

No evidence-backed public reproduction asset is currently recorded.