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Registro Completo |
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
26/11/2018 |
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Data da última atualização: |
26/11/2018 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
VOLPATO, L.; SIMOQUELI, G. F.; ALVES, R. S.; ROCHA, J. R. do A. S. de C.; DEL CONTE, M. V.; RESENDE, M. D. V. de; CARNEIRO, P. C. S.; SILVA, F. L. da. |
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Afiliação: |
Leonardo Volpato, UFV; Guilherme Ferreira Simiqueli, UFV; Rodrigo Silva Alves, UFV; João Romero do Amaral Santos de Carvalho Rocha, UFV; Murilo Viotto Del Conte, UFV; MARCOS DEON VILELA DE RESENDE, CNPF; Pedro Crescêncio Souza Carneiro, UFV; Felipe Lopes da Silva, UFV. |
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Título: |
Selection of inbred soybean progeny (Glycine max): an approach with population effect. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
Plant Breeding, v. 137, n. 6, p. 865-872, Dec. 2018. |
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DOI: |
10.1111/pbr.12648 |
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Idioma: |
Inglês |
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Conteúdo: |
To meet the growing demand of the soybean consumer market, cultivars increasingly early, productive and resistant to biotic and abiotic stress are sought. Several populations are obtained in soybean breeding programmes, but progeny are selected without being weighted for their respective population effect. As a consequence, progeny originating from high?merit populations may be discarded too early. Given this scenario, this study proposes to employ the selection index with progeny and population effect via best linear unbiased prediction (SIPP?BLUP) for the genetic selection of early and productive soybean progeny. A total of 180 progeny derived from three populations were evaluated for yield?related traits. Genetic gains from selection, Spearman correlation and coincidence index were used to check the efficiency of the models with and without the population effect. The SIPP?BLUP index achieved greater selection accuracy and was efficient in the identification and future selection of early soybean progeny. Therefore, this study demonstrates that soybean breeding programmes should consider the population effect via SIPP?BLUP in progeny selection to obtain future lines that really contribute to genetic gain. |
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Palavras-Chave: |
Breeding values; Earlier-maturing progeny; Enotype × environment interaction; Ganho genético; Genetic gain; Interação genótipo x ambiente; Mixed models; Modelos mistos. |
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Thesagro: |
Glycine Max; Rendimento; Semente; Soja. |
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Thesaurus Nal: |
Accuracy; Seed yield; Soybeans. |
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Categoria do assunto: |
G Melhoramento Genético |
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Marc: |
LEADER 02361naa a2200397 a 4500
001 2100054
005 2018-11-26
008 2018 bl uuuu u00u1 u #d
024 7 $a10.1111/pbr.12648$2DOI
100 1 $aVOLPATO, L.
245 $aSelection of inbred soybean progeny (Glycine max)$ban approach with population effect.$h[electronic resource]
260 $c2018
520 $aTo meet the growing demand of the soybean consumer market, cultivars increasingly early, productive and resistant to biotic and abiotic stress are sought. Several populations are obtained in soybean breeding programmes, but progeny are selected without being weighted for their respective population effect. As a consequence, progeny originating from high?merit populations may be discarded too early. Given this scenario, this study proposes to employ the selection index with progeny and population effect via best linear unbiased prediction (SIPP?BLUP) for the genetic selection of early and productive soybean progeny. A total of 180 progeny derived from three populations were evaluated for yield?related traits. Genetic gains from selection, Spearman correlation and coincidence index were used to check the efficiency of the models with and without the population effect. The SIPP?BLUP index achieved greater selection accuracy and was efficient in the identification and future selection of early soybean progeny. Therefore, this study demonstrates that soybean breeding programmes should consider the population effect via SIPP?BLUP in progeny selection to obtain future lines that really contribute to genetic gain.
650 $aAccuracy
650 $aSeed yield
650 $aSoybeans
650 $aGlycine Max
650 $aRendimento
650 $aSemente
650 $aSoja
653 $aBreeding values
653 $aEarlier-maturing progeny
653 $aEnotype × environment interaction
653 $aGanho genético
653 $aGenetic gain
653 $aInteração genótipo x ambiente
653 $aMixed models
653 $aModelos mistos
700 1 $aSIMOQUELI, G. F.
700 1 $aALVES, R. S.
700 1 $aROCHA, J. R. do A. S. de C.
700 1 $aDEL CONTE, M. V.
700 1 $aRESENDE, M. D. V. de
700 1 $aCARNEIRO, P. C. S.
700 1 $aSILVA, F. L. da
773 $tPlant Breeding$gv. 137, n. 6, p. 865-872, Dec. 2018.
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Registro original: |
Embrapa Florestas (CNPF) |
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