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| 19. |  | MATOS, A. P. de. Produção Integrada de Abacaxi. In: MATOS, A. P. de; BORGES, A. L.; OLIVEIRA, D. de A.; SANTOS, G. R. dos; CAMPOS, G. A.; GEBLER, L.; SANCHES, N. F.; SOUTO, R. F.; CORDEIRO, Z. J. M. (Ed.). Produção integrada de fruteiras tropicais. Cruz das Almas: Embrapa Mandioca e Fruticultura, 2012. p.25-68. Publicação online.| Biblioteca(s): Embrapa Mandioca e Fruticultura. |
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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: |
12/07/2013 |
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Data da última atualização: |
19/05/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
JESUS, O. N. de; FREITAS, J. P. de; DANTAS, J. L.; OLIVEIRA, E. J. de. |
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Afiliação: |
ONILDO NUNES DE JESUS, CNPMF; J. P. DE FREITAS; J. L. DANTAS; EDER JORGE DE OLIVEIRA, CNPMF. |
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Título: |
Use of morpho-agronomic traits and DNA profiling for classification of genetic diversity in papaya. |
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Ano de publicação: |
2013 |
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Fonte/Imprenta: |
Genetics and Molecular Research, v.1, n.2, Mar. 2013. |
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ISSN: |
1676-5680 |
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Idioma: |
Inglês |
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Conteúdo: |
We examined the genetic diversity of papaya (Carica papaya) based on morph-agronomic and molecular data. Twenty-seven genotypes grown in Brazil were analyzed with 11 AFLP primer combinations, 23 ISSR markers, 22 qualitative and 30 quantitative descriptors. For the joint analyses, we used the Gower algorithm (Joint Gower) and the average value of the individual dissimilarity matrix for each type of data (Average-Joint Gower); 359 AFLP and 52 ISSR polymorphic bands were found. Approximately 29.2 and 7.7% of the AFLP and ISSR bands, respectively, were genotype-specific and may therefore be used for papaya variety protection. Although there was a significant correlation between the qualitative and quantitative descriptor dissimilarity matrices (r = 0.43), the morph-agronomic data were not highly correlated with the molecular data. Moreover, correlation between AFLP and ISSR dissimilarity matrices was nearly null (r = -0.01). Joint Gower analysis of all data showed high correlations, especially for AFLP markers, most likely due to the larger number of bands, generating a strong bias in the diversity estimates. The Joint-Average-Gower analysis allowed a better balance between the correlations for the continuous and the discrete variables. The results generated by clustering analysis distinguished 5 genetically distinct groups. While we found that papaya genotypes are significantly variable for many traits, we observed that Joint-Average-Gower analysis allowed for genotype clustering based on the most widely used criterion for classifying papaya genotypes, which is fruit type ('Formosa' or 'Solo'). This information helps provide an accurate estimate of the genetic diversity and structure of papaya germplasm, which will be used for further breeding strategies. MenosWe examined the genetic diversity of papaya (Carica papaya) based on morph-agronomic and molecular data. Twenty-seven genotypes grown in Brazil were analyzed with 11 AFLP primer combinations, 23 ISSR markers, 22 qualitative and 30 quantitative descriptors. For the joint analyses, we used the Gower algorithm (Joint Gower) and the average value of the individual dissimilarity matrix for each type of data (Average-Joint Gower); 359 AFLP and 52 ISSR polymorphic bands were found. Approximately 29.2 and 7.7% of the AFLP and ISSR bands, respectively, were genotype-specific and may therefore be used for papaya variety protection. Although there was a significant correlation between the qualitative and quantitative descriptor dissimilarity matrices (r = 0.43), the morph-agronomic data were not highly correlated with the molecular data. Moreover, correlation between AFLP and ISSR dissimilarity matrices was nearly null (r = -0.01). Joint Gower analysis of all data showed high correlations, especially for AFLP markers, most likely due to the larger number of bands, generating a strong bias in the diversity estimates. The Joint-Average-Gower analysis allowed a better balance between the correlations for the continuous and the discrete variables. The results generated by clustering analysis distinguished 5 genetically distinct groups. While we found that papaya genotypes are significantly variable for many traits, we observed that Joint-Average-Gower analysis allowed for genotype clusteri... Mostrar Tudo |
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Palavras-Chave: |
Genetic variability; Melhoramento genético; Variabilidade genética. |
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Thesagro: |
Carica Papaya; Mamão. |
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Thesaurus NAL: |
Algorithms; Genetic resources. |
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Categoria do assunto: |
G Melhoramento Genético |
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Marc: |
LEADER 02537naa a2200253 a 4500
001 1961948
005 2023-05-19
008 2013 bl uuuu u00u1 u #d
022 $a1676-5680
100 1 $aJESUS, O. N. de
245 $aUse of morpho-agronomic traits and DNA profiling for classification of genetic diversity in papaya.$h[electronic resource]
260 $c2013
520 $aWe examined the genetic diversity of papaya (Carica papaya) based on morph-agronomic and molecular data. Twenty-seven genotypes grown in Brazil were analyzed with 11 AFLP primer combinations, 23 ISSR markers, 22 qualitative and 30 quantitative descriptors. For the joint analyses, we used the Gower algorithm (Joint Gower) and the average value of the individual dissimilarity matrix for each type of data (Average-Joint Gower); 359 AFLP and 52 ISSR polymorphic bands were found. Approximately 29.2 and 7.7% of the AFLP and ISSR bands, respectively, were genotype-specific and may therefore be used for papaya variety protection. Although there was a significant correlation between the qualitative and quantitative descriptor dissimilarity matrices (r = 0.43), the morph-agronomic data were not highly correlated with the molecular data. Moreover, correlation between AFLP and ISSR dissimilarity matrices was nearly null (r = -0.01). Joint Gower analysis of all data showed high correlations, especially for AFLP markers, most likely due to the larger number of bands, generating a strong bias in the diversity estimates. The Joint-Average-Gower analysis allowed a better balance between the correlations for the continuous and the discrete variables. The results generated by clustering analysis distinguished 5 genetically distinct groups. While we found that papaya genotypes are significantly variable for many traits, we observed that Joint-Average-Gower analysis allowed for genotype clustering based on the most widely used criterion for classifying papaya genotypes, which is fruit type ('Formosa' or 'Solo'). This information helps provide an accurate estimate of the genetic diversity and structure of papaya germplasm, which will be used for further breeding strategies.
650 $aAlgorithms
650 $aGenetic resources
650 $aCarica Papaya
650 $aMamão
653 $aGenetic variability
653 $aMelhoramento genético
653 $aVariabilidade genética
700 1 $aFREITAS, J. P. de
700 1 $aDANTAS, J. L.
700 1 $aOLIVEIRA, E. J. de
773 $tGenetics and Molecular Research$gv.1, n.2, Mar. 2013.
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