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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. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Mandioca e Fruticultura. |
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Data corrente: |
11/05/2020 |
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Data da última atualização: |
15/07/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
CARMO, C. D. do; SOUSA, M. B. e; PEREIRA, J. dos S.; CEBALLOS, H.; OLIVEIRA, E. J. de. |
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Afiliação: |
CÁTIA DIAS DO CARMO; MASSAINE BANDEIRA E SOUSA; JOCILENE DOS SANTOS PEREIRA; HERNÁN CEBALLOS; EDER JORGE DE OLIVEIRA, CNPMF. |
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Título: |
Identification of waxy cassava genotypes using fourier-transform near-infrared spectroscopy. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Crop Science, 1-13, 2020. |
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ISSN: |
0011-183X |
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Idioma: |
Inglês |
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Conteúdo: |
High?throughput phenotyping tools that allow the early and accurate evaluation of important agronomic traits have gained space in current breeding programs. The aim of this study was to evaluate the potential of Fourier?transform near?infrared spectroscopy (FT?NIRS) to identify cassava (Manihot esculenta Crantz) clones with waxy starch (i.e., amylose?free) by screening leaves rather than roots, and to validate prediction models for classifying these phenotypes. We analyzed the spectra of 162 waxy and 180 nonwaxy genotypes from five different growing environments. The mean FT?NIRS spectra and principal component analysis (PCA) were used to investigate the potential for grouping the data. For classification, five supervised pattern recognition techniques were tested: Bayesian generalized linear model (BGLM), high?dimensional discriminant analysis (HDDA), partial least squares?discriminant analysis (PLS?DA), parallel random forest (PRANDF), and support vector machines with linear kernel (SVM). The mean spectra and the PCA did not allow discrimination of the genotypes based on starch classification. The SVM and BGLM showed the highest classification accuracy in cross?validation (.86?.87), with higher concordance rates (.88?.83), sensitivity (.87?.85) and specificity (.88). The BGLM and SVM models also obtained better indices in the external validation, with high accuracy (.85) and correct classification of 93% of the waxy genotypes. Thus, performing early selection of root characteristics based on the indirect selection of variables extracted from leaf spectra is a good potential strategy for more efficient breeding of the waxy phenotype. MenosHigh?throughput phenotyping tools that allow the early and accurate evaluation of important agronomic traits have gained space in current breeding programs. The aim of this study was to evaluate the potential of Fourier?transform near?infrared spectroscopy (FT?NIRS) to identify cassava (Manihot esculenta Crantz) clones with waxy starch (i.e., amylose?free) by screening leaves rather than roots, and to validate prediction models for classifying these phenotypes. We analyzed the spectra of 162 waxy and 180 nonwaxy genotypes from five different growing environments. The mean FT?NIRS spectra and principal component analysis (PCA) were used to investigate the potential for grouping the data. For classification, five supervised pattern recognition techniques were tested: Bayesian generalized linear model (BGLM), high?dimensional discriminant analysis (HDDA), partial least squares?discriminant analysis (PLS?DA), parallel random forest (PRANDF), and support vector machines with linear kernel (SVM). The mean spectra and the PCA did not allow discrimination of the genotypes based on starch classification. The SVM and BGLM showed the highest classification accuracy in cross?validation (.86?.87), with higher concordance rates (.88?.83), sensitivity (.87?.85) and specificity (.88). The BGLM and SVM models also obtained better indices in the external validation, with high accuracy (.85) and correct classification of 93% of the waxy genotypes. Thus, performing early selection of root chara... Mostrar Tudo |
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Thesagro: |
Mandioca. |
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Thesaurus Nal: |
Cassava. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02233naa a2200205 a 4500
001 2122196
005 2020-07-15
008 2020 bl uuuu u00u1 u #d
022 $a0011-183X
100 1 $aCARMO, C. D. do
245 $aIdentification of waxy cassava genotypes using fourier-transform near-infrared spectroscopy.$h[electronic resource]
260 $c2020
520 $aHigh?throughput phenotyping tools that allow the early and accurate evaluation of important agronomic traits have gained space in current breeding programs. The aim of this study was to evaluate the potential of Fourier?transform near?infrared spectroscopy (FT?NIRS) to identify cassava (Manihot esculenta Crantz) clones with waxy starch (i.e., amylose?free) by screening leaves rather than roots, and to validate prediction models for classifying these phenotypes. We analyzed the spectra of 162 waxy and 180 nonwaxy genotypes from five different growing environments. The mean FT?NIRS spectra and principal component analysis (PCA) were used to investigate the potential for grouping the data. For classification, five supervised pattern recognition techniques were tested: Bayesian generalized linear model (BGLM), high?dimensional discriminant analysis (HDDA), partial least squares?discriminant analysis (PLS?DA), parallel random forest (PRANDF), and support vector machines with linear kernel (SVM). The mean spectra and the PCA did not allow discrimination of the genotypes based on starch classification. The SVM and BGLM showed the highest classification accuracy in cross?validation (.86?.87), with higher concordance rates (.88?.83), sensitivity (.87?.85) and specificity (.88). The BGLM and SVM models also obtained better indices in the external validation, with high accuracy (.85) and correct classification of 93% of the waxy genotypes. Thus, performing early selection of root characteristics based on the indirect selection of variables extracted from leaf spectra is a good potential strategy for more efficient breeding of the waxy phenotype.
650 $aCassava
650 $aMandioca
700 1 $aSOUSA, M. B. e
700 1 $aPEREIRA, J. dos S.
700 1 $aCEBALLOS, H.
700 1 $aOLIVEIRA, E. J. de
773 $tCrop Science, 1-13, 2020.
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Registro original: |
Embrapa Mandioca e Fruticultura (CNPMF) |
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| Registros recuperados : 7 | |
| 1. |  | CARASSAI, I. J.; NABINGER, C.; VARELLA, A. C.; VIEIRA, P. C.; TISCHLER, M. R.; GORELIK, D. B.; ROCHA, R. T. da. Modeling responses of annual ryegrass as a function of nitrogen fertilization. In: MACHADO, C. F.; WADE, M.; SILVA, S. C. da; AGNUSDEI, M.; CARVALHO, P. de F.; MORRIS, S.; BESKOW, W. (Ed.). An overview of research on pastoral-based systems in the Southern part of South America: international workshop. Tandil: Universidad Nacional del Centro de la Provincia de Buenos Aires, 2010. p. 55-57.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Pecuária Sul. |
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| 2. | | SANTANA, M. M.; SAVIAN, J. V.; BARTH NETO, A.; SILVA, B. de A.; VIEIRA, P. C.; TISCHLER, M. R.; SCHONS, R. M. T.; CEZIMBRA, I. M.; GENRO, T. C. M.; BERNDT, A.; BAYER, C.; CARVALHO, P. C. de F. Effect of herbage intake on methane emission by grazing sheep. In: LIVESTOCK, CLIMATE CHANGE AND FOOD SECURITY CONFERENCE, 2014, Madrid. Conference abstract book... [Paris]: INRA, 2014. p. 75.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Pecuária Sudeste; Embrapa Pecuária Sul. |
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| 3. | | CEZIMBRA, I. M.; NUNES, P. A. de A.; SOUZA FILHO, W. de; TISCHLER, M. R.; GENRO, T. C. M.; BAYER, C.; SAVIAN, J. V.; BONNET, O. J. F.; SOUSSANA, J.-F.; CARVALHO, P. C. de F. Potential of grazing management to improve beef cattle production and mitigate methane emissions in native grasslands of the Pampa biome. Science of the Total Environment, v. 780, 146582, Aug. 2021.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Pecuária Sul. |
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| 4. | | TRINDADE, J. K. da; PINTO, C. E.; NEVES, F. P.; MEZZALIRA, J. C.; BREMM, C.; GENRO, T. C. M.; TISCHLER, M. R.; NABINGER, C.; GONDA, H. L.; CARVALHO, P. C. F. Forage allowance as a target of grazing management: implications on grazing time and forage searching. Rangeland Ecology & Management, Wheat Ridge, v. 65, n. 4, p. 382-393, July 2012.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
| Biblioteca(s): Embrapa Pecuária Sul. |
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| 5. | | SAVIAN, J. V.; CEZIMBRA, I. M.; S FILHO, W.; BONNET, O. J. F.; BARTH NETO, A.; SCHONS, R. M. T.; TISCHLER, M. R.; NUNES, P. A. A.; ALMEIDA, G. M.; ARAÚJO, B.; BARRO, R.; GENRO, T. C. M.; BERNDT, A.; BARIONI, L. G.; BAYER, C.; CARVALHO, P. C. de F. Methane emission efficiency as a function of grazing management in Southern Brazilian grazing systems. In: GLOBAL SCIENCE CONFERENCE ON CLIMATE-SMART AGRICULTURE, 3., 2015, Montpellier. Food security adaptation mitigation: Parallel session L1: regional dimensions. Paris: CSA-Cirad, 2015. p. 152.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Agricultura Digital. |
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| 6. | | SAVIAN, J. V.; CEZIMBRA, I. M.; S FILHO, W.; BONNET, O. J. F.; BARTH NETO, A.; SCHONS, R. M. T.; TISCHLER, M. R.; NUNES, P. A. A.; ALMEIDA, G. M.; ARAÚJO, B.; BARRO, R.; GENRO, T. C. M.; BERNDT, A.; BARIONI, L. G.; BAYER, C.; CARVALHO, P. C. de F. Methane emission efficiency as a function of grazing management in Southern Brazilian grazing systems. In: GLOBAL SCIENCE CONFERENCE ON CLIMATE-SMART AGRICULTURE, 3., 2015, Montpellier. Food security adaptation mitigation: poster session 1: regional dimensions. Paris: CSA-Cirad, 2015. p. 151.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Pecuária Sul. |
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| 7. | | CEZIMBRA, I. M.; BONNET, O. J. F.; TISCHLER, M. R.; SANTANA, M. M.; ARAUJO, B.; DUTRA, V. S.; HEGUABURU, A. F.; SAVIAN, J. V.; MASS, L. B.; KOHMANN, M. M.; GENRO, T. C. M.; BERNDT, A.; BAYER, C.; CARVALHO, P. C. DE F. Grazing intensity and methane emissions by growing heifers in the Pampa rangeland - Southern Brazil. In: LIVESTOCK, CLIMATE CHANGE AND FOOD SECURITY CONFERENCE, 2014, Madrid. Conference abstract book... [Paris]: INRA, 2014. p. 33.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Pecuária Sudeste; Embrapa Pecuária Sul. |
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| Registros recuperados : 7 | |
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| Nenhum registro encontrado para a expressão de busca informada. |
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