Discriminating wheat genotypes for barley yellow dwarf virus tolerance through multivariate integration of chlorophyll fluorescence and agronomic traits

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Abstract

Barley yellow dwarf virus (BYDV; Luteovirus pavhordei ) is one of the most economically important viral pathogens of wheat, causing substantial losses in plant growth, physiology, and grain yield. This study evaluated the combined effects of wheat genotype, BYDV infection, and their interaction on agronomic performance and photosynthetic physiology using an integrative multivariate approach. The experiment employed a completely randomized design with four genotypes and two conditions (with and without virus), using controlled inoculation via aphids and infection confirmation by RT-PCR. Growth and yield components, as well as chlorophyll fluorescence variables, were measured, enabling co-analysis using multivariate analysis of variance, canonical discriminant analysis, and principal component analysis to explore patterns of association. The results revealed marked effects of genotype and viral infection on the set of variables, as well as differential responses among genotypes. BYDV infection altered the photosynthetic apparatus, with enhanced energy dissipation mechanisms and reduced photosynthetic efficiency, lowering agronomic performance. Multivariate analyses enabled the identification of association patterns among variables and the discrimination of genotypes based on their tolerance levels to the BYDV. Tolerant genotypes maintained photosynthetic efficiency, accompanied by vegetative growth and yield stability. In contrast, intolerant genotypes exhibited stronger photoprotective responses, greater impairment of PSII photochemistry, and more pronounced reductions in agronomic performance. Overall, this study demonstrates that viral infection reorganizes the relationships among physiological and productive processes, highlighting the importance of integrative approaches for better understanding plant–virus interactions and further supporting breeding programs.

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