Reproductive Development of Coffea arabica Cultivars in the Ribeira Paulista Valley Region

• Grant number: 22/11627-3
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: November 01, 2022
• End date: July 31, 2023
• Field of knowledge: Agronomical Sciences - Agronomy - Crop Science
• Principal Investigator: Alex Mendonça de Carvalho
• Grantee: Lucas Miranda de França
• 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 the coffee industry in Brazil, having great importance for the economy, with a prominent 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 Universidade Estadual Paulista "Júlio de Mesquita Filho" - UNESP, in Registro-SP. The spacing adopted was 3.0 x 0.60m. The experiment was installed in a randomized block design, with three replications, and plots of 10 plants, with the eight central plants being considered as a useful plot. The following characteristics will be evaluated: productivity, percentage of cherry, green and raisin/dried fruits, percentage of hollow fruits, physical classification of the coffee, sensory attributes of the drink, vegetative vigor,. Statistical analyzes will be performed using the Sisvar computer program (Ferreira 2000). The average data of the evaluated characteristics will be submitted to analysis of variance by the F test, and the averages will be compared by the Skott Knott test at 5% probability. The experimental data will be jointly analyzed through principal component analysis using the Statistica®11 software.