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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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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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Registro original: |
Embrapa Mandioca e Fruticultura (CNPMF) |
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