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Registro Completo |
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Biblioteca(s): |
Embrapa Algodão. |
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Data corrente: |
26/01/2023 |
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Data da última atualização: |
30/01/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
PEIXOTO, M. A.; EVANGELISTA, J. S. P. C.; COELHO, I. F.; CARVALHO, L. P. de; FARIAS, F. J. C.; TEODORO, P. E.; BHERING, L. L. |
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Afiliação: |
MARCO ANTÔNIO PEIXOTO, UNIVERSIDADE FEDERAL DE VIÇOSA; JENIFFER SANTANA PINTO COELHO EVANGELISTA, UNIVERSIDADE FEDERAL DE VIÇOSA; IGOR FERREIRA COELHO, UNIVERSIDADE FEDERAL DE VIÇOSA; LUIZ PAULO DE CARVALHO, CNPA; FRANCISCO JOSE CORREIA FARIAS, CNPA; PAULO EDUARDO TEODORO, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL; LEONARDO LOPES BHERING, UNIVERSIDADE FEDERAL DE VIÇOSA. |
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Título: |
Genotype selection based on multiple traits in cotton crops: the application of genotype by yield trait biplot. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Acta Scientiarum. Agronomy, v. 44, e54136, 2022. |
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ISSN: |
1807-8621 |
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DOI: |
10.4025/actasciagron.v44i1.54136 |
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Idioma: |
Inglês |
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Conteúdo: |
ABSTRACT - In cotton crops, the cotton seed yield significantly contributes with the success of any cultivar. However, other traits are considered when an ideotype is pointed out in the selection, such as the fiber quality traits. The aim of this study was to applied genotype by yield*trait (GYT) biplot to a multi-environment trial data of cotton genotypes and selected the best genotypes. For this end, thirteen genotypes from nineteen trials were assessed. Seven traits were evaluated [cotton seed yield (SY), fiber percentage (FP), fiber length (FL), fiber uniformity (FU), short fiber index (SFI), fiber strength (FS), and elongation (EL)] and residual error variances structures [identity variance (IDV) and diagonal (Diag)] were tested by bayesian information criterion. After, the REML/BLUP approach was applied to predict the genetic values of each trait and the selective accuracy were measured from the prediction. Then, the GYT-biplot were applied to the data. For SP and SFI traits, the model with Diag residual variance was indicated, whereas for SY FL, FU, FS, and EL traits the model with IDV residual variance demonstrated the best fit to the data. Values of accuracy were higher than 0.9 for all traits analyzed. In the GYT-biplot acute angles were find for all traits relations, which means high correlation between the yield*traits combination. Besides that, the correlation still can be seen in the GYT-biplot, as shown by the magnitudes of the angles between the pairs Yield*FU-Yield*FS and Yield*FS-Yield*EL. Also, the GYT-biplot indicates the genotype G4 with the best performance for Yield*FS, Yield*SFI, Yield*FU, Yield*FL, and Yield*FP combined. The genotypes G4, G1, G13, G8, and G9 represent those genotypes with yield advantage over the other cultivars. Then, the genotype G4 combines all desirable characteristics and demonstrate have large potential in the cotton breeding. The GYT approach were valuable and were highly recommended in cotton breeding programs for selection purpose in a multivariate scenario. MenosABSTRACT - In cotton crops, the cotton seed yield significantly contributes with the success of any cultivar. However, other traits are considered when an ideotype is pointed out in the selection, such as the fiber quality traits. The aim of this study was to applied genotype by yield*trait (GYT) biplot to a multi-environment trial data of cotton genotypes and selected the best genotypes. For this end, thirteen genotypes from nineteen trials were assessed. Seven traits were evaluated [cotton seed yield (SY), fiber percentage (FP), fiber length (FL), fiber uniformity (FU), short fiber index (SFI), fiber strength (FS), and elongation (EL)] and residual error variances structures [identity variance (IDV) and diagonal (Diag)] were tested by bayesian information criterion. After, the REML/BLUP approach was applied to predict the genetic values of each trait and the selective accuracy were measured from the prediction. Then, the GYT-biplot were applied to the data. For SP and SFI traits, the model with Diag residual variance was indicated, whereas for SY FL, FU, FS, and EL traits the model with IDV residual variance demonstrated the best fit to the data. Values of accuracy were higher than 0.9 for all traits analyzed. In the GYT-biplot acute angles were find for all traits relations, which means high correlation between the yield*traits combination. Besides that, the correlation still can be seen in the GYT-biplot, as shown by the magnitudes of the angles between the pairs Yield*F... Mostrar Tudo |
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Thesagro: |
Algodão; Análise Estatística; Genótipo; Gossypium Hirsutum. |
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Thesaurus Nal: |
Cotton; Cultivars; Genotype; Seed cotton. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1151251/1/Genotype-selection-based-multiple-2022.pdf
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Marc: |
LEADER 02957naa a2200313 a 4500
001 2151251
005 2023-01-30
008 2022 bl uuuu u00u1 u #d
022 $a1807-8621
024 7 $a10.4025/actasciagron.v44i1.54136$2DOI
100 1 $aPEIXOTO, M. A.
245 $aGenotype selection based on multiple traits in cotton crops$bthe application of genotype by yield trait biplot.$h[electronic resource]
260 $c2022
520 $aABSTRACT - In cotton crops, the cotton seed yield significantly contributes with the success of any cultivar. However, other traits are considered when an ideotype is pointed out in the selection, such as the fiber quality traits. The aim of this study was to applied genotype by yield*trait (GYT) biplot to a multi-environment trial data of cotton genotypes and selected the best genotypes. For this end, thirteen genotypes from nineteen trials were assessed. Seven traits were evaluated [cotton seed yield (SY), fiber percentage (FP), fiber length (FL), fiber uniformity (FU), short fiber index (SFI), fiber strength (FS), and elongation (EL)] and residual error variances structures [identity variance (IDV) and diagonal (Diag)] were tested by bayesian information criterion. After, the REML/BLUP approach was applied to predict the genetic values of each trait and the selective accuracy were measured from the prediction. Then, the GYT-biplot were applied to the data. For SP and SFI traits, the model with Diag residual variance was indicated, whereas for SY FL, FU, FS, and EL traits the model with IDV residual variance demonstrated the best fit to the data. Values of accuracy were higher than 0.9 for all traits analyzed. In the GYT-biplot acute angles were find for all traits relations, which means high correlation between the yield*traits combination. Besides that, the correlation still can be seen in the GYT-biplot, as shown by the magnitudes of the angles between the pairs Yield*FU-Yield*FS and Yield*FS-Yield*EL. Also, the GYT-biplot indicates the genotype G4 with the best performance for Yield*FS, Yield*SFI, Yield*FU, Yield*FL, and Yield*FP combined. The genotypes G4, G1, G13, G8, and G9 represent those genotypes with yield advantage over the other cultivars. Then, the genotype G4 combines all desirable characteristics and demonstrate have large potential in the cotton breeding. The GYT approach were valuable and were highly recommended in cotton breeding programs for selection purpose in a multivariate scenario.
650 $aCotton
650 $aCultivars
650 $aGenotype
650 $aSeed cotton
650 $aAlgodão
650 $aAnálise Estatística
650 $aGenótipo
650 $aGossypium Hirsutum
700 1 $aEVANGELISTA, J. S. P. C.
700 1 $aCOELHO, I. F.
700 1 $aCARVALHO, L. P. de
700 1 $aFARIAS, F. J. C.
700 1 $aTEODORO, P. E.
700 1 $aBHERING, L. L.
773 $tActa Scientiarum. Agronomy$gv. 44, e54136, 2022.
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Registro original: |
Embrapa Algodão (CNPA) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Amazônia Ocidental. Para informações adicionais entre em contato com cpaa.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Amazônia Ocidental. |
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Data corrente: |
20/02/2000 |
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Data da última atualização: |
05/01/2015 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
Internacional - A |
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Autoria: |
NELSON, B. W.; MESQUITA, R.; PEREIRA, J. L. G.; SOUZA, S. G. A. de; BATISTA, G. T.; COUTO, L. B. |
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Afiliação: |
INPA; Embrapa Amazonia Ocidental; INPE. |
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Título: |
Allometric regressions for improved estimate of secondary forest biomass in the central Amazon. |
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Ano de publicação: |
1999 |
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Fonte/Imprenta: |
Forest Ecology and Management, v. 117, n. 1, p. 149-167, 1999. |
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Idioma: |
Inglês |
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Conteúdo: |
Estimates of the sequestering of carbon by secondary of forests - wich occupy almost half the deforested area of the Brazilian Amazon - will be improved by the use of accurate allometric relationships for non-destructive measurement of standing biomass and by an evaluation of the suitability of existing equations for application in secondary forest. Species-specific and mixed-species regressions for estimating total above-ground dry weight (DW) were therefore developed using eight abundant secondary forest tree species in the central Amazon. Using only DBH as the input variable, the species-specific equations estimated DW of individual trees an average error of 10%-15%. For the mixed-species equations, developed using 132trees from seven of the wight species (excluding Cecropia, average error in estimating DW of individual trees was 19.8% using only DBH and 15.0% using DBH plus specific density of the wood (SD). Average SD for each species can be substituted without increasing the error of the estimate. Adding total tree hight (H) as an input variable provided only a slight reduction in error to 14.0%. Previously plublished mixed-species biomass regression models, based on primary and secondary forest trees of the Amazon, were also cross-valited against the trees of this study. Two of these models, based on primary forest plots and using only DBH as an input, overstimated biomass by 10%-60% for central Amazonian secondary of forest trees in the size range 5cm-25cm. The overstimate was greatest for the larger trees. Including Cecropia in the test group will make the overstimate even greater. Those published equation using DBH, H. and SD as inputs, wheter from secondary or primary forest plots, showed better agreement with the sample-derived regressions and lower average erros in estimation of individual tree dry weights. MenosEstimates of the sequestering of carbon by secondary of forests - wich occupy almost half the deforested area of the Brazilian Amazon - will be improved by the use of accurate allometric relationships for non-destructive measurement of standing biomass and by an evaluation of the suitability of existing equations for application in secondary forest. Species-specific and mixed-species regressions for estimating total above-ground dry weight (DW) were therefore developed using eight abundant secondary forest tree species in the central Amazon. Using only DBH as the input variable, the species-specific equations estimated DW of individual trees an average error of 10%-15%. For the mixed-species equations, developed using 132trees from seven of the wight species (excluding Cecropia, average error in estimating DW of individual trees was 19.8% using only DBH and 15.0% using DBH plus specific density of the wood (SD). Average SD for each species can be substituted without increasing the error of the estimate. Adding total tree hight (H) as an input variable provided only a slight reduction in error to 14.0%. Previously plublished mixed-species biomass regression models, based on primary and secondary forest trees of the Amazon, were also cross-valited against the trees of this study. Two of these models, based on primary forest plots and using only DBH as an input, overstimated biomass by 10%-60% for central Amazonian secondary of forest trees in the size range 5cm-25cm. The overs... Mostrar Tudo |
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Palavras-Chave: |
Amazonas; Brasil; Manaus; Secondary forest. |
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Thesagro: |
Biomassa; Carbono; Floresta Tropical Úmida. |
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Thesaurus NAL: |
biomass; carbon; tropical rain forests. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02669naa a2200301 a 4500
001 1668672
005 2015-01-05
008 1999 bl uuuu u00u1 u #d
100 1 $aNELSON, B. W.
245 $aAllometric regressions for improved estimate of secondary forest biomass in the central Amazon.
260 $c1999
520 $aEstimates of the sequestering of carbon by secondary of forests - wich occupy almost half the deforested area of the Brazilian Amazon - will be improved by the use of accurate allometric relationships for non-destructive measurement of standing biomass and by an evaluation of the suitability of existing equations for application in secondary forest. Species-specific and mixed-species regressions for estimating total above-ground dry weight (DW) were therefore developed using eight abundant secondary forest tree species in the central Amazon. Using only DBH as the input variable, the species-specific equations estimated DW of individual trees an average error of 10%-15%. For the mixed-species equations, developed using 132trees from seven of the wight species (excluding Cecropia, average error in estimating DW of individual trees was 19.8% using only DBH and 15.0% using DBH plus specific density of the wood (SD). Average SD for each species can be substituted without increasing the error of the estimate. Adding total tree hight (H) as an input variable provided only a slight reduction in error to 14.0%. Previously plublished mixed-species biomass regression models, based on primary and secondary forest trees of the Amazon, were also cross-valited against the trees of this study. Two of these models, based on primary forest plots and using only DBH as an input, overstimated biomass by 10%-60% for central Amazonian secondary of forest trees in the size range 5cm-25cm. The overstimate was greatest for the larger trees. Including Cecropia in the test group will make the overstimate even greater. Those published equation using DBH, H. and SD as inputs, wheter from secondary or primary forest plots, showed better agreement with the sample-derived regressions and lower average erros in estimation of individual tree dry weights.
650 $abiomass
650 $acarbon
650 $atropical rain forests
650 $aBiomassa
650 $aCarbono
650 $aFloresta Tropical Úmida
653 $aAmazonas
653 $aBrasil
653 $aManaus
653 $aSecondary forest
700 1 $aMESQUITA, R.
700 1 $aPEREIRA, J. L. G.
700 1 $aSOUZA, S. G. A. de
700 1 $aBATISTA, G. T.
700 1 $aCOUTO, L. B.
773 $tForest Ecology and Management$gv. 117, n. 1, p. 149-167, 1999.
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Embrapa Amazônia Ocidental (CPAA) |
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