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Registro Completo |
Biblioteca(s): |
Embrapa Pecuária Sudeste. |
Data corrente: |
21/05/2019 |
Data da última atualização: |
13/03/2023 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
SANTOS, I. G. dos; CRUZ, C. D.; NASCIMENTO, M.; FERREIRA, R. de P. |
Afiliação: |
Iara Gonçalves dos Santos, UFV; Cosme Damião Cruz, UFV; Moysés Nascimento, UFV; REINALDO DE PAULA FERREIRA, CPPSE. |
Título: |
Selection index as a priori information for using artificial neural networks to classify alfalfa genotypes. |
Ano de publicação: |
2019 |
Fonte/Imprenta: |
Genetics and Molecular Research, v. 18, n. 2, gmr18221, 2019. |
DOI: |
doi.org/10.4238/gmr18221 |
Idioma: |
Inglês |
Conteúdo: |
The efficiency of a selection index generally depends on the quality of the variance matrixes, which demands controlled experiments. Using Artificial Neural Networks (ANNs) trained from a selection index is advantageous for selecting genotypes since an ANN has the capacity to classify genotypes in an automated way. We propose the use of ANNs for the selection of alfalfa genotypes, based on a selection index. Data were collected from 77 alfalfa genotypes evaluated based on nine traits from four cuttings. The traits were divided into forage yield and nutritive value groups. In order for the ANNs to learn the classification pattern, the Tai index was used, which allows secondary traits to be included in the index to improve the gains of the main traits. An index was established for each group of traits, and based on the index scores the genotypes were subdivided into four classes (optimal, good, medium, and bad). After testing different topologies, ANNs were established for each index, according to the apparent error rates. The chosen ANNs were efficient in classifying the genotypes since the highest apparent error rate reached 15%, meaning that the ANNs efficiently captured the data pattern. Considering the ANN classification for both groups of traits, there was a high degree of agreement with the classification obtained from the Tai index, as expected. Even in the cuttings where the ANNs presented the worst performance, their potential to classify alfalfa genotypes was clear, because the wrong classifications were placed in groups close to the correct ones. This ensured that the best genotypes did not run the risk of being discarded, since they would not classified in the group of bad genotypes. The ANNs that were developed have good potential for use in alfalfa breeding programs. MenosThe efficiency of a selection index generally depends on the quality of the variance matrixes, which demands controlled experiments. Using Artificial Neural Networks (ANNs) trained from a selection index is advantageous for selecting genotypes since an ANN has the capacity to classify genotypes in an automated way. We propose the use of ANNs for the selection of alfalfa genotypes, based on a selection index. Data were collected from 77 alfalfa genotypes evaluated based on nine traits from four cuttings. The traits were divided into forage yield and nutritive value groups. In order for the ANNs to learn the classification pattern, the Tai index was used, which allows secondary traits to be included in the index to improve the gains of the main traits. An index was established for each group of traits, and based on the index scores the genotypes were subdivided into four classes (optimal, good, medium, and bad). After testing different topologies, ANNs were established for each index, according to the apparent error rates. The chosen ANNs were efficient in classifying the genotypes since the highest apparent error rate reached 15%, meaning that the ANNs efficiently captured the data pattern. Considering the ANN classification for both groups of traits, there was a high degree of agreement with the classification obtained from the Tai index, as expected. Even in the cuttings where the ANNs presented the worst performance, their potential to classify alfalfa genotypes was clear,... Mostrar Tudo |
Palavras-Chave: |
Computational intelligence; Tai index. |
Thesagro: |
Medicago Sativa. |
Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/197607/1/gmr18221-selection-index-priori-information-using.pdf
|
Marc: |
LEADER 02470naa a2200205 a 4500 001 2109207 005 2023-03-13 008 2019 bl uuuu u00u1 u #d 024 7 $adoi.org/10.4238/gmr18221$2DOI 100 1 $aSANTOS, I. G. dos 245 $aSelection index as a priori information for using artificial neural networks to classify alfalfa genotypes.$h[electronic resource] 260 $c2019 520 $aThe efficiency of a selection index generally depends on the quality of the variance matrixes, which demands controlled experiments. Using Artificial Neural Networks (ANNs) trained from a selection index is advantageous for selecting genotypes since an ANN has the capacity to classify genotypes in an automated way. We propose the use of ANNs for the selection of alfalfa genotypes, based on a selection index. Data were collected from 77 alfalfa genotypes evaluated based on nine traits from four cuttings. The traits were divided into forage yield and nutritive value groups. In order for the ANNs to learn the classification pattern, the Tai index was used, which allows secondary traits to be included in the index to improve the gains of the main traits. An index was established for each group of traits, and based on the index scores the genotypes were subdivided into four classes (optimal, good, medium, and bad). After testing different topologies, ANNs were established for each index, according to the apparent error rates. The chosen ANNs were efficient in classifying the genotypes since the highest apparent error rate reached 15%, meaning that the ANNs efficiently captured the data pattern. Considering the ANN classification for both groups of traits, there was a high degree of agreement with the classification obtained from the Tai index, as expected. Even in the cuttings where the ANNs presented the worst performance, their potential to classify alfalfa genotypes was clear, because the wrong classifications were placed in groups close to the correct ones. This ensured that the best genotypes did not run the risk of being discarded, since they would not classified in the group of bad genotypes. The ANNs that were developed have good potential for use in alfalfa breeding programs. 650 $aMedicago Sativa 653 $aComputational intelligence 653 $aTai index 700 1 $aCRUZ, C. D. 700 1 $aNASCIMENTO, M. 700 1 $aFERREIRA, R. de P. 773 $tGenetics and Molecular Research$gv. 18, n. 2, gmr18221, 2019.
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Registro original: |
Embrapa Pecuária Sudeste (CPPSE) |
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Registros recuperados : 360 | |
82. | ![Imagem marcado/desmarcado](/consulta/web/img/desmarcado.png) | SANTOS, C. A. F.; CAVALCANTI, J.; PAINI, J. N.; CRUZ, C. D. Correlacoes canonicas entre componentes primarios e secundarios da producao de graos em guandu (Cajanus cajan (L.) Millsp.). Revista Ceres, Viçosa, MG, v. 41, n. 236, p. 459-464, 1994.Tipo: Artigo em Periódico Indexado | Circulação/Nível: Nacional - B |
Biblioteca(s): Embrapa Semiárido. |
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86. | ![Imagem marcado/desmarcado](/consulta/web/img/desmarcado.png) | SHIMOYA, A.; CRUZ, C. D.; FERREIRA, R. de P.; PEREIRA, A. V.; CARNEIRO, P. C. S. Divergência genética entre acessos de um banco de germoplasma de capim-elefante. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 37, n. 7, p. 971-980, jul. 2002 Título em inglês: Genetic divergence among accessions of a germplasm bank of elephantgrass.Biblioteca(s): Embrapa Unidades Centrais. |
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87. | ![Imagem marcado/desmarcado](/consulta/web/img/desmarcado.png) | FERRAO, M. A. G.; VIEIRA, C.; CRUZ, C. D.; CARDOSO, A. A. Divergência genética em feijoeiro em condições de inverno tropical. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 37, n. 8, p. 1089-1098, ago. 2002 Título em inglês: Genetic divergency on Common bean under tropical winter conditions.Biblioteca(s): Embrapa Unidades Centrais. |
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88. | ![Imagem marcado/desmarcado](/consulta/web/img/desmarcado.png) | RAMOS, S. R. R.; QUEIROZ, M. A. de; CASALI, V. W. D.; CRUZ, C. D. Divergencia genetica em germoplasma de abobora procedente de diferentes areas do Nordeste. Horticultura Brasileira, Brasília, DF, v. 18, n. 3, p. 195-199, nov. 2000.Tipo: Artigo em Periódico Indexado | Circulação/Nível: Nacional - B |
Biblioteca(s): Embrapa Semiárido. |
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89. | ![Imagem marcado/desmarcado](/consulta/web/img/desmarcado.png) | MOURA, W. de M.; CASALI, V. W. D.; CRUZ, C. D.; LIMA, P. C. de. Divergência genética em linhagens de pimentão em relação a eficiência nutricional de fósforo. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 34, n. 2, p. 217-24, fev. 1999 Título em inglês: Genetic divergence of phosphorus nutritional efficiency in sweet pepper lines.Biblioteca(s): Embrapa Unidades Centrais. |
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93. | ![Imagem marcado/desmarcado](/consulta/web/img/desmarcado.png) | COIMBRA, R. R.; MIRANDA, G. V.; CRUZ, C, D.; SILVA, D. J. H.; VILELA, R. A. Development of a Brazilian maize core collection. Genetics and Molecular Biology, Ribeirão Preto, v. 32, n. 3, p. 538-545, 2009.Tipo: Artigo em Periódico Indexado | Circulação/Nível: B - 1 |
Biblioteca(s): Embrapa Milho e Sorgo. |
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94. | ![Imagem marcado/desmarcado](/consulta/web/img/desmarcado.png) | LEAO, P. C. de S.; CRUZ, C. D.; MOTOIKE, S. Y. Diversidade genética de acessos de uvas de mesa baseada em caracteres morfo-agronômicos. In: CONGRESSO BRASILEIRO DE RECURSOS GENÉTICOS; WORKSHOP EM BIOPROSPECÇÃO E CONSERVAÇÃO DE PLANTAS NATIVAS DO SEMI-ÁRIDO, 3.; WORKSHOP INTERNACIONAL SOBRE BIOENERGIA E MEIO AMBIENTE, 2010, Salvador. Bancos de germoplasma: descobrir a riqueza, garantir o futuro: anais. Brasília, DF: Embrapa Recursos Genéticos e Biotecnologia, 2010. 1 CD-ROM. (Embrapa Recursos Genéticos e Biotecnologia. Documentos, 304). Editora técnica Clara Oliveira Goedert.Tipo: Resumo em Anais de Congresso |
Biblioteca(s): Embrapa Semiárido. |
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95. | ![Imagem marcado/desmarcado](/consulta/web/img/desmarcado.png) | LEDO, F. J. da S.; CASALI, V. W. D.; CRUZ, C. D.; PEREIRA, P. R. G. Diversidade genética em cultivares de alface, por meio de análise multivariada. In: CONGRESSO BRASILEIRO DE OLERICULTURA, 39., 1999, Tubarão, SC. A olericultura no Mercosul: resumos. Tubarão: SOB, 1999. R161. 1 p.Tipo: Resumo em Anais de Congresso |
Biblioteca(s): Embrapa Acre. |
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98. | ![Imagem marcado/desmarcado](/consulta/web/img/desmarcado.png) | VIEIRA, J. V.; NASCIMENTO, W. M.; CRUZ, C. D.; MIRANDA, J. E. C. Estimativas de parâmetros genéticos em uma população de cenoura do tipo Brasília, para caracteres de qualidade de sementes. Informativo ABRATES, Curitiba, v. 11, n. 2, p. 306, set. 2001. Resumo.Biblioteca(s): Embrapa Hortaliças. |
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