Specific rootstocks for Arabica coffee cultivars in an area free from nematode infestation

• Grant number: 23/17955-5
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: May 01, 2024
• End date: April 30, 2025
• Field of knowledge: Agronomical Sciences - Agronomy - Crop Science
• Principal Investigator: Alex Mendonça de Carvalho
• Grantee: João Gabriel Ferreira de Oliveira
• Host Institution: Faculdade de Ciências Agrárias. Universidade Estadual Paulista (UNESP). Campus do Vale do Ribeira. Registro , SP, Brazil

Abstract

Grafting on coffee trees 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 Supply. The aim of the project is to identify C. canephora rootstocks that positively influence the productive potential of Arabica coffee cultivars in areas free from the pathogen. The experiment was installed in December 2021, on the Campus of the Universidade Estadual Paulista "Júlio de Mesquita Filho" - UNESP, in Registro-SP. The spacing adopted was 3.0 x 0.70m. The experiment was carried out in a randomized block design, with five replications, plots of thirty plants and subplots of 5 plants, totaling 450 useful plants per experiment, 375 of which were grafted and 75 were free plants, in addition to 198 plants of the cultivar Obatã IAC. 1669-20, used in experimental borders. The characteristics will be evaluated: stem diameter, plant height, number of plagiotropic branches, number of nodes on plagiotropic branches, productivity, vegetative vigor, uniformity of maturation, percentage of hatched fruits and fissured grain nature. Statistical analyzes will be carried out using the Sisvar computer program (Ferreira 2000). The average data of the characteristics evaluated will be subjected to analysis of variance using the F test, with the means compared using the Skott Knott test at 5% probability. The experimental data will be analyzed jointly through principal component analysis using the Statistica®11 software.