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vol.38 número1FORMAÇÃO DE GRUPOS HETRÓTICOS EM PSIDIUM GUAJAVA L. PELAS REDES NEURAIS ARTIFICIAISAVALIAÇÃO DA QUALIDADE FÍSICO-QUÍMICA DE POLPAS DE FRUTA CONGELADAS COMERCIALIZADAS NA CIDADE DE CUIABÁ-MT índice de autoresíndice de assuntospesquisa de artigos
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Revista Brasileira de Fruticultura

versão impressa ISSN 0100-2945versão On-line ISSN 1806-9967

Resumo

FERREIRA, RULFE TAVARES et al. INTRAPOPULATION RECURRENT SELECTION IN SOUR PASSION FRUIT BY MIXED MODELS. Rev. Bras. Frutic. [online]. 2016, vol.38, n.1, pp.158-166. ISSN 0100-2945.  http://dx.doi.org/10.1590/0100-2945-260/14.

Passion fruit belongs to the family Passifloraceae, and the genus is Passifloraregarded the most economically important. The aim of this study was to estimate parameters and genotypic values by REML/BLUP method in level of progenies. A total of 27 half-sib progenies of the sour passion fruit derived from the second cycle of recurrent selection conducted in UENF, selected by the selection index were evaluated. The characteristics evaluated were: number of fruits (NF), total fruit mass (TFM) and fruit average mass (FAM). Breeding values were estimated by the Software SELEGEN using the procedure REML/BLUP. In the estimates of genetic parameters by REML, both characteristics directly linked to production and thus considered the most important (NF and TFM) showed average heritability estimates of progenies of 0.395 and 0.439, respectively. The selection and BLUP estimates of earnings by the coefficient of coincidence revealed agreement of the results of the selection among the progenies, showing that for all traits the same 8 progenies are superior to the three characteristics simultaneously. The REML/BLUP methodology was adequate for evaluation, allowing to obtain estimates of genetic and phenotypic parameters revealed that the possibility of successful selection of superior progenies, simultaneously with gains of 18.02%, 23.08% and 9.65% for NF, TFM and FAM, respectively.

Palavras-chave : Passiflora edulis Sims; mixed models; recurrent selection.

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