Índice de seleção e análise de fatores na predição de ganhos genéticos em Coffea canephora var. conilon

O café é um dos produtos primários de maior valor no mercado mundial. O Brasil é o terceiro maior produtor de Coffea canephora do mundo e acordo com os dados da CONAB (2003), o estado do Espírito Santo é o maior produtor brasileiro com 65,56% da produção total. Neste trabalho, foi realizado o estudo...

Nível de Acesso:openAccess
Publication Date:2003
Main Author: Ferreira, Adésio lattes
Orientador/a: Cecon, Paulo Roberto
Format: Dissertação
Language:por
Published: Universidade Federal de Viçosa
Áreas de Conhecimento:
Online Access:http://www.locus.ufv.br/handle/123456789/10483
Citação:FERREIRA, Adésio. Índice de seleção e análise de fatores na predição de ganhos genéticos em Coffea canephora var. conilon. 2003. 132 f. Dissertação (Mestrado em Genética e Melhoramento) - Universidade Federal de Viçosa, Viçosa. 2003.
Resumo inglês:Coffee is one of the most pricey raw products on the world market. Brazil is worldwide the third greatest producer of Coffea canephora and according to data of CONAB (2003), the nation’s top producer is the State of Espírito Santo with 65,56% of the total output.. In this study, the behavior of 40 Coffea canephora var. conilon genotypes was studied at two production sites, Marilândia and Sooretama, in Espírito Santo. Our objective was to outline strategies of a breeding program that identifies superior genotypes which combine a set of favorable attributes, to be used “per se” or in hybridization programs. Based on the estimation of genetic and environmental parameters, the 40 genotypes were evaluated in relation to the “per se” behavior. Favorable conditions for breeding were found. Direct and indirect selection strategies were not efficient for the 14 evaluated characteristics since this species improvement program aimed to obtain materials with simultaneous characters in search of rational gains. In this sense, “supercharacteristics” were obtained by the factor analysis technique: SIEVE (Factor1), BENEF/CYCLE (Factor2), QUALITY 1(Factor3) and QUALITY 2 (Factor4) in Marilândia; and SIEVE (Factor1), BENEF/CHOCHO (Factor2) and QUALITY 1 (Factor3) in Sooretama. At both sites, the use of the technique turned out to be inefficient for a simultaneous selection of yield and “supercharacteristics”. In view of the results, the selection index theory was used to work with the characteristics Yield, Cycle, and Moisture, and with the “supercharacteristics” obtained by factor analysis. This brought forth well-balanced forecast “supercharacteristics”. gains for all characteristics and