Specific rootstocks for Arabica coffee cultivars in areas free from nematode infestation

• Grant number: 25/10378-8
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: September 01, 2025
• End date: August 31, 2026
• Field of knowledge: Agronomical Sciences - Agronomy - Crop Science
• Principal Investigator: Alex Mendonça de Carvalho
• Grantee: Ricardo Campinas Gonçalves
• Host Institution: Faculdade de Ciências Agrárias. Universidade Estadual Paulista (UNESP). Campus do Vale do Ribeira. Registro , SP, Brazil

Abstract

Grafting coffee plants was optimized for growing plants in areas infested by nematodes, especially those of the genera Meloidogyne and Pratylenchus. The successful strategy was supported by the only rootstock - Apoatã IAC 2258 - registered with the Ministry of Agriculture, Livestock and Food Supply. The project aims to identify C. canephora rootstocks that positively influence the productive potential of Arabica coffee cultivars in areas free of the pathogen.The experiment was installed in December 2021, at the Campus of the São Paulo State University "Júlio de Mesquita Filho" - UNESP, in Registro-SP. The spacing adopted was 3.0 x 0.70 m. The experiment was installed in a randomized block experimental design, with five replications, plots of thirty plants and subplots of 5 plants, totaling 450 useful plants per experiment, 375 grafted and 75 on ungrafted stock, in addition to 198 plants of the cultivar Obatã IAC 1669-20, used in the experimental border. The following characteristics will be evaluated: productivity, vegetative vigor, uniformity of maturation, percentage of shriveled fruits, physical analysis of the grains and analysis of leaf nitrogen. Statistical analyses will be performed using the Sisvar computer program (Ferreira 2000). The average data of the evaluated characteristics will be subjected to analysis of variance using the F test, with the averages compared using the Skott Knott test at 5% probability. The experimental data will be analyzed together using principal component analysis using the Statistica®11 software. (AU)