Articles
Development of an automated picture-taking system and an image analysis method for monitoring infection kinetics in a foliar pathogenic fungus
Published : 1 December 2023
Abstract
To understand plant-pathogen interactions, we need efficient quantification of the traits associated with the infectious process. Among these traits, the latent period is of particular importance, yet, it is often poorly assessed because its measure relies on imprecise and over-infrequent visual observations. To overcome these limitations, we have developed an automated system for monitoring infection and lesion growth by taking zenith photographs under controlled conditions. An image analysis pipeline coded in ImageJ and R is used to identify lesions and estimate their growth. This method enables us to monitor each lesion individually and to quantify three characteristics linked to infectious potential: infection efficiency, lesion size and latency. This method was developed to monitor infections caused by a biotrophic fungus responsible for poplar rust, Melampsora larici-populina, on a miniaturized well-box device (simultaneous monitoring of 1536 samples). Our method can be easily adapted to a variety of situations, including the monitoring of fungal growth in Petri dishes.
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