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Summary: Grapevine downy mildew, caused by the oomycete Plasmopara viticola (P. viticola, Berk. & M. A. Curtis; Berl. & De Toni), is a global threat to Eurasian wine grapes Vitis vinifera. Although resistant grapevine varieties are becoming more accessible, P. viticola populations are rapidly evolving to overcome these resistances. We aimed to uncover avirulence genes related to Rpv3.1‐mediated grapevine resistance.We sequenced the genomes and characterized the development of 136 P. viticola strains on resistant and sensitive grapevine cultivars. A genome‐wide association study was conducted to identify genomic variations associated with resistant‐breaking phenotypes.We identified a genomic region associated with the breakdown of Rpv3.1 grapevine resistance (avrRpv3.1 locus). A diploid‐aware reassembly of the P. viticola INRA‐Pv221 genome revealed structural variations in this locus, including a 30 kbp deletion. Virulent P. viticola strains displayed multiple deletions on both haplotypes at the avrRpv3.1 locus. These deletions involve two paralog genes coding for proteins with 800–900 amino acids and signal peptides. These proteins exhibited a structure featuring LWY‐fold structural modules, common among oomycete effectors. When transiently expressed, these proteins induced cell death in grapevines carrying Rpv3.1 resistance, confirming their avirulence nature.This discovery sheds light on the genetic mechanisms enabling P. viticola to adapt to grapevine resistance, laying a foundation for developing strategies to manage this destructive crop pathogen. [ABSTRACT FROM AUTHOR]

This paper presents an innovative approach for supplier selection (SS) within the Tunisian dairy industry, with a specific focus on sustainability and resilience. The proposed method is a hybrid model that integrates multi-criteria decision-making (MCDM) with fuzzy logic. Initially, twelve distinct criteria are identified, categorized into social, environmental, economic, and resilience indexes through a combination of literature review and expert input. To establish the importance of these criteria, a fuzzy analytic hierarchy process (FAHP) is employed to calculate their weights. These weights are then integrated into a new method called fuzzy multi-attribute border approximation area comparison (FMABAC) to rank the suppliers. The methodology aims to provide decision-makers with a more intuitive means of expressing their preferences and evaluating supplier criteria, ultimately identifying the most effective dairy farmers. The research concludes by evaluating the results through two sensitivity analyses: one involving varying criteria weights and the other involving a comparative assessment with alternative fuzzy MCDM techniques. [ABSTRACT FROM AUTHOR]