Abstract

Clubroot is a devastating disease caused by the protist Plasmodiophora brassicae Woronin. After root hair colonization, the clubroot pathogen induces clubs that block water uptake, leading to dehydration and death. The study of the severity of plant diseases is very important. It allows us to characterize the level of resistance of plant germplasm and to classify the virulence of pathogen strains or isolates. Lately, the use of learning machines and automatization has expanded to plant pathology. Fast, reliable and unbiased methods are always necessary, and with clubroot disease indexing this is not different. From this perspective, we discuss why this is the case and how we could achieve this long overdue task for clubroot disease.

Highlights

  • Centre de Recherche et D’Innovation sur les Végétaux (CRIV), Université Laval, Quebec City, QC G1V 0A6, Canada

  • This differential system has been effective for detecting predominant pathotypes of P. brassicae in Canadian fields and to study the virulence of single spore isolates (SSI), it does not discriminate between virulent and avirulent strains of P. brassicae against the resistance in CR varieties or cultivars

  • Selecting the appropriate growing conditions of the sample population is essential in selecting the suitable digital software, because obtaining the right images for analysis is a tradeoff between the growth environment and its throughput

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Summary

Clubroot Disease Index and Plasmodiophora brassicae Pathotyping

The management of clubroot disease relies on the use of clubroot-resistant (CR) varieties. 30 P. brassicae pathotypes have been identified in Canada using the CCD [8] This differential system has been effective for detecting predominant pathotypes of P. brassicae in Canadian fields and to study the virulence of single spore isolates (SSI), it does not discriminate between virulent and avirulent strains of P. brassicae against the resistance in CR varieties or cultivars. This has been addressed by the novel differential system. The foregoing drawbacks demand an objective visualization technique with the highest accuracy and reproducibility

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