New paper on automated quantification and classification of post-harvest damage – webinar postponed to 22 September

In a new publication, Emina Mulaosmanovic and co-authors describe the use of phenotyping technologies to detect post-harvest damage on leaves.

Examples of leaf lesion segmentation using the LiMu program

Plants are exposed to factors which cause tissue damage, like environmental stress (abiotic), herbivores (biotic), and mechanical injury from agricultural practices or poor handling.
The aim of the paper was to develop a method for detection and quantification of damage on leaf scale. Lesions were detected by staining detached leaves with trypan blue. For automated quantification and classification of stained areas the authors developed an image analysis pipeline, combining established digital image processing methods. With this method, effects of different biotic and abiotic factors to plant tissue, and mechanical damage can be studied, and plant cultivars can be screened for plant susceptibility to specific pathogens. Cell damage due to interactions of plant cultivar, pathogen strain and environmental factors can be assessed at different time points from inoculation to generation of first visible infection symptoms using the proposed approach.

NB! The webinar to discuss this paper is postponed until 22 September at 14:00 CET:

Anyone interested is welcome to join, no preregistration needed!