title: Image-based phenotyping of plant disease symptoms.
abstract: Plant diseases cause significant reductions in agricultural productivity worldwide. Disease symptoms have deleterious effects on the growth and development of crop plants, limiting yields and making agricultural products unfit for consumption. For many plant-pathogen systems, we lack knowledge of the physiological mechanisms that link pathogen infection and the production of disease symptoms in the host. A variety of quantitative high-throughput image-based methods for phenotyping plant growth and development are currently being developed. These methods range from detailed analysis of a single plant over time to broad assessment of the crop canopy for thousands of plants in a field and employ a wide variety of imaging technologies. Application of these methods to the study of plant disease offers the ability to study quantitatively how host physiology is altered by pathogen infection. These approaches have the potential to provide insight into the physiological mechanisms underlying disease symptom development. Furthermore, imaging techniques that detect the electromagnetic spectrum outside of visible light allow us to quantify disease symptoms that are not visible by eye, increasing the range of symptoms we can observe and potentially allowing for earlier and more thorough symptom detection. In this review, we summarize current progress in plant disease phenotyping and suggest future directions that will accelerate the development of resistant crop varieties.
authors.affiliation: Donald Danforth Plant Science Center , Saint Louis, MO, USA.
authors.forename: Andrew M
authors.initials: AM
authors.lastname: Mutka
authors.affiliation: Donald Danforth Plant Science Center , Saint Louis, MO, USA.
authors.forename: Rebecca S
authors.initials: RS
authors.lastname: Bart
keywords: host; imaging; pathogen; phenotyping; plant disease