Agronomic performance of Coffea arabica cultivars in the Vale do Ribeira Paulista region

• Grant number: 21/04745-7
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: October 01, 2021
• End date: September 30, 2022
• Field of knowledge: Agronomical Sciences - Agronomy - Crop Science
• Principal Investigator: Alex Mendonça de Carvalho
• Grantee: Sofia Santos Bonifácio
• Host Institution: Faculdade de Ciências Agrárias. Universidade Estadual Paulista (UNESP). Campus do Vale do Ribeira. Registro , SP, Brazil

Abstract

On the world stage, coffee is among the most commercialized and profitable products, representing a source of income for several countries. The species Coffea arabica L stands out in coffee growing in Brazil, having great importance for the economy, with an outstanding contribution to the Brazilian trade balance. Given this economic importance, the objective of the project is to evaluate the performance of 12 cultivars of C. arabica in the Vale do Ribeira Paulista, through agronomic characteristics, in order to generate information that contributes to the technical recommendation of cultivars for the region. The Arabica coffee experiment was installed in February 2018, at the Experimental Campus of the São Paulo State University "Júlio de Mesquita Filho" - UNESP, in Registro-SP. The spacing adopted was 3.0 x 0.60 m. The experiment was installed in a randomized block design, with three replications, and plots of 10 plants, with eight central plants being considered as a useful plot. The characteristics will be evaluated: productivity, percentage of cherries, greens and raisins / dried fruits, percentage of churches fruits physical classification of coffee, sensory attributes of drink, vegetative vigor, the incidence of cercosporiosis in coffee leaves, incidence and severity of rust, the incidence of minor bug on the leaves of coffee trees. Statistical analyzes will be performed using the computer program Sisvar (Ferreira 2000). The average data, of the evaluated characteristics, will be subjected to analysis of variance by the F test, with the averages compared by the Skott Knott test at 5% probability. The experimental data will be analyzed together by means of principal component analysis using the software Statistica®11.(AU)