Relations among yield and fruit quality of sweet orange Citrus sinensis (L.) Osbeck varieties, tree spacing and meteorological variables in Northern São Paulo State

• Grant number: 08/10814-7
• Support Opportunities: Scholarships in Brazil - Post-Doctorate
• Effective date (Start): July 01, 2009
• Effective date (End): March 31, 2010
• Field of knowledge: Agronomical Sciences - Agronomy - Crop Science
• Principal Investigator: Eduardo Sanches Stuchi
• Grantee: Eduardo Augusto Girardi
• Host Institution: Estação Experimental de Citricultura de Bebedouro (EECB). Fundação de Pesquisas Agroindustriais de Bebedouro (FUPAB). Bebedouro , SP, Brazil

Abstract

Citriculture is a major economical activity in the State of São Paulo, Brazil. Northern São Paulo represents 30% of total citrus production, with fruits that present highly desirable physical and chemical properties to the juice industry. Nowadays, several devastating diseases and climatic changes face the citrus industry and lead to the migration of new orchards to other citrus areas. Higher plant densities are also recommended to increase yield in this context. This research project will evaluate the relations among yield and fruit quality of sweet orange [Citrus sinensis (L.) Osbeck] varieties, tree spacing and meteorological variables, especially water deficit, in Northern São Paulo State. The work will be divided in two experiments. In the first one, the relations will be evaluated for 31 sweet orange varieties budded on 'Swingle' citrumelo [Poncirus trifoliata (L.) Raf. X Citrus paradisi MacFaden]. In the second one, relations of 'Pêra' sweet orange budded on 'Cleópatra' mandarin (Citrus reshni Hort. ex Tanaka) will be evaluated in the tree spacings (m) 7 x 2, 7 x 3, 7 x 4, 7 x 5 e 7 x 6. Both experiments were installed in Bebedouro, SP, respectively in 1990 and 1986, and evaluation period will comprise harvests of 1990 to 2007 and 1989 to 2003, respectively. Data collected are plant growth variables, annual yield, fruit quality indexes, and meteorological variables from the locality. Statistical analyses include, in this order, analysis of variance and mean comparison of treatments, calculation of the simple determination coefficients for correlation among variables, calculation of multiple linear regression models for significant variables, and evaluation of multivariate models as alternative statistic approach. We expect to provide models for sweet orange production estimation in Northern São Paulo, and improved understanding of climatic influence on citrus genotypes and tree spacing could support citrus industry planning in the State.