Agronomic performance of highland rice progenies cultivated in the Vale do Ribeira paulista region

• Grant number: 18/04591-7
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: August 01, 2018
• End date: July 31, 2020
• Field of knowledge: Agronomical Sciences - Agronomy - Crop Science
• Principal Investigator: Alex Mendonça de Carvalho
• Grantee: Carlos Issao Kanno
• Host Institution: Universidade Estadual Paulista (UNESP). Campus de Registro. Registro , SP, Brazil

Abstract

Foods such as rice and beans are primary sources of nutrients, being among the most important foods in the diet of the Brazilian population. The Ribeira Valley in the State of São Paulo has some of the highest concentrations of Atlantic Forest in the state besides unique soil and climatic conditions that provide adequate development to the rice crop. In this sense, researches that seek the maintenance and creation of important genotypes grown regionally are strategies for the development of culture, besides strengthening the regional economy. Based on the assumption, the present work aims to characterize and evaluate the elite progenies of Embrapa Arroz e Feijão, with subsequent selection and extraction of superior genotypes for the Ribeira Valley region. The evaluation and characterization of the genotypes will occur at the Experimental Farm of the State University of São Paulo, Campus Experimental de Registro. The following evaluations will be carried out: plant emergence time, flowering period and panicle maturation, plant height, leaf length, lodging degree, total weight of fresh shoot matter, total shoot dry matter weight , stem diameter, mass of 100 grains, total number of grains per panicle, number of pomegranate grains and pips per panicle, harvest index, panicle length, incidence of major diseases, yield and yield of genotypes, number of stems / m², number of panicles / m², useful tillering. The phenotypic correlations between all the evaluated characteristics (two to two) and also the correlation between the thermal sum and productivity, obtained through the Selegen-REML / BLUP program (Resende, 2007) will also be estimated. The mean data of the evaluated characteristics will be submitted to analysis of variance by the F test and the means compared by the Skott Knott test at 5% probability using the Sisvar computational program.