Low-cost phenotyping system unveils key insights into quantitative disease resistance in wild tomatoes

Quantitative illness resistance (QDR) is a posh however sturdy type of plant illness resistance that gives partial safety towards a broad vary of pathogens. Not like qualitative resistance, pushed by main resistance (R) genes, QDR is polygenic and manifests in numerous methods, equivalent to delayed lesion improvement or lowered an infection frequency.

Understanding QDR’s underlying genetic and regulatory mechanisms has lengthy been a problem, hindered by the necessity for superior phenotyping know-how and complicated knowledge evaluation.

A research revealed in Plant Phenomics on 5 Aug 2024, provides a roadmap for breeding extra disease-resilient tomato varieties.

The analysis crew investigated quantitative illness resistance (QDR) in 4 wild tomato species—S. habrochaites, S. lycopersicoides, S. pennellii, and S. pimpinellifolium—towards Sclerotinia sclerotiorum utilizing the “Navautron” automated phenotyping system. This method repeatedly captured photographs of contaminated leaves, and a segmentation algorithm was used to quantify parameters like an infection frequency (IF), lag-phase length, lesion doubling time (LDT), and the world below the illness progress curve (AUDPC).

Statistical fashions, together with generalized least squares and generalized linear fashions, had been utilized to account for variability. The research revealed vital phenotypic range in QDR throughout the species. S. pimpinellifolium had the shortest lag section (36.2 hours), whereas S. habrochaites and S. pennellii exhibited longer lag phases (roughly 59 hours).

Lesion progress evaluation confirmed that S. pimpinellifolium and S. pennellii had the quickest lesion growth, with doubling instances of 11 hours, whereas S. habrochaites and S. lycopersicoides had slower progress charges, as much as 36 and 41 hours, respectively.

An infection frequency additionally different, with S. habrochaites displaying the bottom charge (80%) in comparison with increased charges in S. lycopersicoides and S. pennellii (93%–95%). Additional, intraspecific variation was assessed, revealing that S. pennellii displayed a variety of lag phases amongst its accessions, whereas S. lycopersicoides was extra constant.

An evaluation of lesion progress in S. pennellii accessions highlighted genotype-dependent resistance, with LA1941 exhibiting the bottom an infection charge and LA1809 the very best severity. Correlation evaluation indicated that QDR parameters, equivalent to lag section and LDT, are largely unbiased.

These findings underscore the complicated interaction between genetic background and QDR, with implications for breeding disease-resistant crops.

In line with the research’s senior researcher, Dr. Remco Stam, “Unlocking the potential of QDR in crop breeding has been a long-standing challenge. Our study showcases a cost-effective phenotyping system that can provide high-resolution data crucial for understanding and utilizing QDR traits in wild crop relatives.”

The research underscores the ability of low-cost, high-efficiency phenotyping programs in plant pathology analysis. By breaking down QDR into distinct mechanisms, scientists can extra successfully breed crops that aren’t solely resistant but in addition able to enduring various environmental stresses. These developments supply hope for sustainable agriculture, the place vegetation can defend themselves towards illnesses with out heavy reliance on fungicides or main R-genes.