Abstract

The objective of this study is to evaluate the potential of airborne spore monitoring for predicting the severity of foliar diseases in winter wheat by developing variety-dependent disease models that account for variety susceptibility and applying a statistical procedure that accommodates the hierarchical structure of panel data. The experiments were conducted in the fields of the FSBSI Federal Research Center of Biological Plant Protection on plots sown with five winter wheat varieties exhibiting varying susceptibility to foliar diseases, while the processing of the data was carried out in 2025–2026. The concentration of spores in the air was estimated using a portable spore trap. Along with air sampling, visual assessments of the development of major fungal pathogens on plants were performed. The hypothesis of variety-specific susceptibility was tested using moderation analysis. The analysis revealed a relationship between leaf disease severity and the number of detected spores, with the strength of correlation varying depending on the pathogen species and variety susceptibility. Using pairwise comparisons of regression slopes for each variety, it was demonstrated that the development of Blumeria graminis depends primarily on spore concentration levels and climatic conditions rather than on variety identity. In contrast, for Puccinia striiformis, Puccinia triticina, and Pyrenophora tritici-repentis, variety susceptibility/resistance was shown to exert a statistically significant influence on disease development. These findings will serve as the foundation for a novel phytosanitary monitoring methodology, which is essential for generating forecasts and informing decision-making regarding plant protection measures.

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