ScabyNet, a user-friendly application for detecting common scab in potato tubers using deep learning and morphological traits.

Common scab (CS) is a major bacterial disease causing lesions on potato tubers, degrading their appearance and reducing their market value. To accurately grade scab-infected potato tubers, this study introduces "ScabyNet", an image processing approach combining color-morphology analysis with deep learning techniques. ScabyNet estimates tuber quality traits and accurately detects and quantifies CS severity levels from color images. It is presented as a standalone application with a graphical user interface comprising two main modules. One module identifies and separates tubers on images and estimates quality-related morphological features. In addition, it enables the extraction of tubers as standard tiles for the deep-learning module. The deep-learning module detects and quantifies the scab infection into five severity classes related to the relative infected area. The analysis was performed on a dataset of 7154 images of individual tiles collected from field and glasshouse experiments. Combining the two modules yields essential parameters for quality and disease inspection. The first module simplifies imaging by replacing the region proposal step of instance segmentation networks. Furthermore, the approach is an operational tool for an affordable phenotyping system that selects scab-resistant genotypes while maintaining their market standards.

Resistance to Streptomyces turgidiscabies in potato involves an early and sustained transcriptional reprogramming at initial stages of tuber formation.

Common scab, caused by species from the bacterial genus Streptomyces, is an important disease of potato (Solanum tuberosum) crops worldwide. Early tuberization is a critical period for pathogen infection; hence, studies of host gene expression responses during this developmental stage can be important to expand our understanding of the infection process and to identify putative resistance genes. In an infection experiment with the highly susceptible potato cultivar Saturna and the relatively resistant cultivar Beate, transcription profiles were obtained by RNA sequencing at two developmental stages: the early hook stage and the early tuber formation stage. Our results indicate that 'Beate' mounts an early and sustained response to infection by S. turgidiscabies, whereas the defence response by 'Saturna' ceases before the early tuber formation stage. Most pronounced were the putative candidate defence-associated genes uniquely expressed in 'Beate'. We observed an increase in alternative splicing on pathogen infection at the early hook stage for both cultivars. A significant down-regulation of genes involved in the highly energy-demanding process of ribosome biogenesis was observed for the infected 'Beate' plants at the early hook stage, which may indicate an allocation of resources that favours the expression of defence-related genes.