ARTIFICIAL INTELLIGENCE FOR IDENTIFICATION OF RESISTANCE TO MILDEW IN GRAPEVINE GERMPLASM

• Grant number: 24/21385-2
• Support Opportunities: Regular Research Grants
• Start date: April 01, 2026
• End date: March 31, 2029
• Field of knowledge: Agronomical Sciences - Agronomy - Crop Science
• Principal Investigator: Mara Fernandes Moura Furlan
• Grantee: Mara Fernandes Moura Furlan
• Principal researcher abroad: Katja Herzog
• Institution abroad: Julius Kühn-Institut, Darmstadt , Germany
• Host Institution: Instituto Agronômico (IAC). Agência Paulista de Tecnologia dos Agronegócios (APTA). Campinas , SP, Brazil
• City of the host institution: Campinas
• Associated researchers: Marcel Bellato Spósito ; Nagarjun Malagol ; Oliver Trapp

Abstract

The grapevine is one of the oldest cultivated species in the world. Although it is an exotic species in Brazil, its cultivation has been made possible mainly due to genetic improvement, allowing the development of genotypes resistant to the tropical climate. Despite these advances, grapevine genetic improvement still presents limitations, mainly regarding the long cycle required, to which the incorporation of technologies such as next-generation sequencing (NGS), image-based phenotyping, genome-wide association, and genomic selection can bring significant benefits, increasing its efficiency, reducing time and increasing the expected genetic gains. These tools in technological development are constantly improving, reaching the era of artificial intelligence today. In this project, we aim to use these technologies for the early evaluation and selection of grapevine cultivars through advanced artificial intelligence tools for the early identification and selection of cultivars resistant to downy mildew, which is caused by the biotrophic oomycete Plasmopara viticola, one of the most important diseases for the crop. (AU)