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Registro Completo |
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
09/08/2019 |
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Data da última atualização: |
12/02/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
SANTOS, P. R. dos; OLIVEIRA, T. R. A. de; SKEEN, P.; NASCIMENTO, M. R.; COSTA, K. D. da S.; ARAÚJO, E. R.; PEREIRA, H. S.; COSTA, A. F. da. |
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Afiliação: |
PAULO RICARDO DOS SANTOS, UNIVERSIDADE ESTADUAL DO NORTE FLUMINENSE; TAMARA REBECCA ALBUQUERQUE DE OLIVEIRA, UNIVERSIDADE ESTADUAL DO NORTE FLUMINENSE; PAOLA SKEEN, UNIVERSIDAD NACIONAL DE COLOMBIA, Bogotá; MAXWEL RODRIGUES NASCIMENTO, UNIVERSIDADE ESTADUAL DO NORTE FLUMINENSE; KLEYTON DANILO DA SILVA COSTA, INSTITUTO FEDERAL DE ALAGOAS, Piranhas-AL; EMMANUELLE RODRIGUES ARAÚJO, IPA; HELTON SANTOS PEREIRA, CNPAF; ANTONIO FELIX DA COSTA, IPA. |
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Título: |
GGE Biplot and REML/BLUP based-analysis of yield stability and adaptability for common beans in multi-environment trials. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
Revista Brasileira de Ciências Agrárias, v. 14, n. 2, e5657, 2019. |
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ISSN: |
1981-0997 |
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DOI: |
10.5039/agraria.v14i2a5657 |
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Idioma: |
Inglês |
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Conteúdo: |
Prior to releasing new varieties, one of the most common aims in breeding is to study genotype by environmental interactions. Using the analysis obtained from these initial processes, a multitude of varieties based on their relative performance through different environments is produced. Herein we assessed the link-up between GGE Biplot and REML/BLUP based methods in a commercial panel of 32 bean genotypes, which included 17 carioca bean genotypes and 15 black bean genotypes. The assessment was conducted during 2009 in four different locations of Pernambuco State, Brazil. Regarding the locations, São João and Araripina showed to be highly representative and non-discriminatory, while Arcoverde was the most discriminatory and well-represented favoring the selection of widely adapted genotypes. The selection of genotypes was consistent by using both methods and the final conclusion shows outstanding performance. Considering a high yield stability and adaptability, the following genotypes showed outstanding performance: the black types included CNFP (11995, 11983, 11985 and 11991), and the carioca types are CNFC (11951 and 11954). Understanding genotype by environmental interactions enabled us to identify potential genotypes for releasing. |
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Thesagro: |
Feijão; Genótipo; Hereditariedade; Interação Genética; Melhoramento Genético Vegetal; Phaseolus Vulgaris. |
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Thesaurus Nal: |
Beans; Genotype-environment interaction; Heritability. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/200517/1/CNPAF-2019-rbca.pdf
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Marc: |
LEADER 02300naa a2200337 a 4500
001 2111224
005 2020-02-12
008 2019 bl uuuu u00u1 u #d
022 $a1981-0997
024 7 $a10.5039/agraria.v14i2a5657$2DOI
100 1 $aSANTOS, P. R. dos
245 $aGGE Biplot and REML/BLUP based-analysis of yield stability and adaptability for common beans in multi-environment trials.$h[electronic resource]
260 $c2019
520 $aPrior to releasing new varieties, one of the most common aims in breeding is to study genotype by environmental interactions. Using the analysis obtained from these initial processes, a multitude of varieties based on their relative performance through different environments is produced. Herein we assessed the link-up between GGE Biplot and REML/BLUP based methods in a commercial panel of 32 bean genotypes, which included 17 carioca bean genotypes and 15 black bean genotypes. The assessment was conducted during 2009 in four different locations of Pernambuco State, Brazil. Regarding the locations, São João and Araripina showed to be highly representative and non-discriminatory, while Arcoverde was the most discriminatory and well-represented favoring the selection of widely adapted genotypes. The selection of genotypes was consistent by using both methods and the final conclusion shows outstanding performance. Considering a high yield stability and adaptability, the following genotypes showed outstanding performance: the black types included CNFP (11995, 11983, 11985 and 11991), and the carioca types are CNFC (11951 and 11954). Understanding genotype by environmental interactions enabled us to identify potential genotypes for releasing.
650 $aBeans
650 $aGenotype-environment interaction
650 $aHeritability
650 $aFeijão
650 $aGenótipo
650 $aHereditariedade
650 $aInteração Genética
650 $aMelhoramento Genético Vegetal
650 $aPhaseolus Vulgaris
700 1 $aOLIVEIRA, T. R. A. de
700 1 $aSKEEN, P.
700 1 $aNASCIMENTO, M. R.
700 1 $aCOSTA, K. D. da S.
700 1 $aARAÚJO, E. R.
700 1 $aPEREIRA, H. S.
700 1 $aCOSTA, A. F. da
773 $tRevista Brasileira de Ciências Agrárias$gv. 14, n. 2, e5657, 2019.
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Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Mandioca e Fruticultura. Para informações adicionais entre em contato com cnpmf.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Mandioca e Fruticultura. |
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Data corrente: |
21/12/2022 |
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Data da última atualização: |
21/12/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
JESUS, O. N. de; LIMA, L. K. S.; SOARES, T. L.; SILVA, L. N. da; SANTOS, C. S. dos; SAMPAIO, S. R.; OLIVEIRA, E. J. de. |
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Afiliação: |
ONILDO NUNES DE JESUS, CNPMF; LUCAS KENNEDY SILVA LIMA; TALIANE LEILA SOARES, UNIVERSIDADE ESTADUAL DE FEIRA DE SANTANA; LUANA NASCIMENTO DA SILVA, UNIVERSIDADE ESTADUAL DE FEIRA DE SANTANA; CIDALIA SOUZA DOS SANTOS, UNIVERSIDADE FEDERAL DO RECÔNCAVO; SIDNARA RIBEIRO SAMPAIO, UNIVERSIDADE FEDERAL DO RECÔNCAVO; EDER JORGE DE OLIVEIRA, CNPMF. |
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Título: |
Phenotypic diversity and alternative methods for characterization and prediction of pulp yield in passion fruit (Passiflora spp.) germplasm. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Scientia Horticulturae, v. 292, n.27, 110573, January 2022. |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract The present study provides an assessment of the genetic variability of different genotypes of Passiflora using physical and chemical descriptors and digital image analysis to quantify leaf, flower and fruit coloration as well as to develop and validate mathematical models for the prediction of passion fruit pulp weight without seeds by regression analysis. A total of 132 Passiflora genotypes belonging to different species were evaluated. Eleven quantitative physical and chemical descriptors were submitted to principal component and cluster analysis. The coloration was determined through RGB color space by digital images analysis. The equations were developed through multiple linear regression and cross-validation was used to validate the models. The first principal component (50.6% of total variance) was associated with fruit weight, diameter and length and peel weight, while the second (22.4%) was associated with fruit weight, fruit length, peel weight, peel thickness, soluble solids, fruit length/fruit diameter ratio and fruit length and diameter. Physical and chemical descriptors showed significant diversity among genotypes. In the cluster analysis, the genotypes BGP007 and BGP009 were most closely related, while BGP349 and BGP177 were distinct. The analysis of coloration using digital images allowed detecting greater variability in the color of leaves, flowers, fruits, and pulp. The analysis of digital images is a practical method for ascertaining the color of plant parts in the field or laboratory. The high phenotypic diversity detected in the present study can be used in passion fruit breeding programs through hybridizations. Regression analysis of physical traits revealed five models that could be used to estimate the pulp weight in two equations (13 and 15), which showed the highest R2 values and lowest RMSE and MAE. This model can be reliably adopted for estimation of the pulp weight without seeds of passion fruits (P. edulis Sims). MenosAbstract The present study provides an assessment of the genetic variability of different genotypes of Passiflora using physical and chemical descriptors and digital image analysis to quantify leaf, flower and fruit coloration as well as to develop and validate mathematical models for the prediction of passion fruit pulp weight without seeds by regression analysis. A total of 132 Passiflora genotypes belonging to different species were evaluated. Eleven quantitative physical and chemical descriptors were submitted to principal component and cluster analysis. The coloration was determined through RGB color space by digital images analysis. The equations were developed through multiple linear regression and cross-validation was used to validate the models. The first principal component (50.6% of total variance) was associated with fruit weight, diameter and length and peel weight, while the second (22.4%) was associated with fruit weight, fruit length, peel weight, peel thickness, soluble solids, fruit length/fruit diameter ratio and fruit length and diameter. Physical and chemical descriptors showed significant diversity among genotypes. In the cluster analysis, the genotypes BGP007 and BGP009 were most closely related, while BGP349 and BGP177 were distinct. The analysis of coloration using digital images allowed detecting greater variability in the color of leaves, flowers, fruits, and pulp. The analysis of digital images is a practical method for ascertaining the color of p... Mostrar Tudo |
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Thesagro: |
Maracujá. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02651naa a2200205 a 4500
001 2150211
005 2022-12-21
008 2022 bl uuuu u00u1 u #d
100 1 $aJESUS, O. N. de
245 $aPhenotypic diversity and alternative methods for characterization and prediction of pulp yield in passion fruit (Passiflora spp.) germplasm.$h[electronic resource]
260 $c2022
520 $aAbstract The present study provides an assessment of the genetic variability of different genotypes of Passiflora using physical and chemical descriptors and digital image analysis to quantify leaf, flower and fruit coloration as well as to develop and validate mathematical models for the prediction of passion fruit pulp weight without seeds by regression analysis. A total of 132 Passiflora genotypes belonging to different species were evaluated. Eleven quantitative physical and chemical descriptors were submitted to principal component and cluster analysis. The coloration was determined through RGB color space by digital images analysis. The equations were developed through multiple linear regression and cross-validation was used to validate the models. The first principal component (50.6% of total variance) was associated with fruit weight, diameter and length and peel weight, while the second (22.4%) was associated with fruit weight, fruit length, peel weight, peel thickness, soluble solids, fruit length/fruit diameter ratio and fruit length and diameter. Physical and chemical descriptors showed significant diversity among genotypes. In the cluster analysis, the genotypes BGP007 and BGP009 were most closely related, while BGP349 and BGP177 were distinct. The analysis of coloration using digital images allowed detecting greater variability in the color of leaves, flowers, fruits, and pulp. The analysis of digital images is a practical method for ascertaining the color of plant parts in the field or laboratory. The high phenotypic diversity detected in the present study can be used in passion fruit breeding programs through hybridizations. Regression analysis of physical traits revealed five models that could be used to estimate the pulp weight in two equations (13 and 15), which showed the highest R2 values and lowest RMSE and MAE. This model can be reliably adopted for estimation of the pulp weight without seeds of passion fruits (P. edulis Sims).
650 $aMaracujá
700 1 $aLIMA, L. K. S.
700 1 $aSOARES, T. L.
700 1 $aSILVA, L. N. da
700 1 $aSANTOS, C. S. dos
700 1 $aSAMPAIO, S. R.
700 1 $aOLIVEIRA, E. J. de
773 $tScientia Horticulturae$gv. 292, n.27, 110573, January 2022.
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Embrapa Mandioca e Fruticultura (CNPMF) |
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