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Registro Completo |
Biblioteca(s): |
Embrapa Soja. |
Data corrente: |
01/07/2015 |
Data da última atualização: |
14/04/2016 |
Tipo da produção científica: |
Artigo em Anais de Congresso |
Autoria: |
DIAS, B. F.; GRAÇA, J. P.; GHIZONI, P. A.; UEDA, T. E.; SALVADOR, M. C.; ABELHA, A. C.; OLIVEIRA, M. C. N.; NUNES, E. O.; HOFFMANN-CAMPO, C. B. |
Afiliação: |
UNOPAR; CNPq; UNOPAR; UEL; CNPq; UNOPAR; MARIA CRISTINA NEVES DE OLIVEIRA, CNPSO; ESTELA OLIVEIRA NUNES, CNPSo; CLARA BEATRIZ HOFFMANN CAMPO, CNPSO. |
Título: |
Desempenho de Helicoverpa armigera em genótipos de soja com diferentes perfis de metabólitos secundários. |
Ano de publicação: |
2015 |
Fonte/Imprenta: |
In: CONGRESSO BRASILEIRO DE SOJA, 7.; MERCOSOJA, 2015, Florianópolis. Tecnologia e mercado global: perspectivas para soja: anais. Londrina: Embrapa Soja, 2015. |
Páginas: |
4 p. |
Descrição Física: |
1 CD-ROM. |
Idioma: |
Português |
Thesagro: |
Lagarta; Praga de planta; Soja. |
Thesaurus Nal: |
Helicoverpa armigera; Insect larvae; Plant pests; Soybeans. |
Categoria do assunto: |
O Insetos e Entomologia |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/126064/1/R.-81-DESEMPENHO-DE-Helicoverpa-armigera-EM-GENOTIPOS-DE-SOJA-COM.PDF
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Marc: |
LEADER 00956nam a2200289 a 4500 001 2019034 005 2016-04-14 008 2015 bl uuuu u00u1 u #d 100 1 $aDIAS, B. F. 245 $aDesempenho de Helicoverpa armigera em genótipos de soja com diferentes perfis de metabólitos secundários.$h[electronic resource] 260 $aIn: CONGRESSO BRASILEIRO DE SOJA, 7.; MERCOSOJA, 2015, Florianópolis. Tecnologia e mercado global: perspectivas para soja: anais. Londrina: Embrapa Soja$c2015 300 $a4 p.$c1 CD-ROM. 650 $aHelicoverpa armigera 650 $aInsect larvae 650 $aPlant pests 650 $aSoybeans 650 $aLagarta 650 $aPraga de planta 650 $aSoja 700 1 $aGRAÇA, J. P. 700 1 $aGHIZONI, P. A. 700 1 $aUEDA, T. E. 700 1 $aSALVADOR, M. C. 700 1 $aABELHA, A. C. 700 1 $aOLIVEIRA, M. C. N. 700 1 $aNUNES, E. O. 700 1 $aHOFFMANN-CAMPO, C. B.
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Registro original: |
Embrapa Soja (CNPSO) |
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Registro Completo
Biblioteca(s): |
Embrapa Arroz e Feijão. |
Data corrente: |
14/01/2019 |
Data da última atualização: |
26/10/2020 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
CARNEIRO, A. R. T.; SANGLARD, D. A.; AZEVEDO, A. M.; SOUZA, T. L. P. O. de; PEREIRA, H. S.; MELO, L. C. |
Afiliação: |
ANNA REGINA TIAGO CARNEIRO, UNIVERSIDADE FEDERAL DE MINAS GERAIS; DEMERSON ARRUDA SANGLARD, UNIVERSIDADE FEDERAL DE MINAS GERAIS; ALCINEI MISTICO AZEVEDO, UNIVERSIDADE FEDERAL DE MINAS GERAIS; THIAGO LIVIO PESSOA OLIV DE SOUZA, CNPAF; HELTON SANTOS PEREIRA, CNPAF; LEONARDO CUNHA MELO, CNPAF. |
Título: |
Fuzzy logic in automation for interpretation of adaptability and stability in plant breeding studies. |
Ano de publicação: |
2019 |
Fonte/Imprenta: |
Scientia Agricola, v. 76, n. 2, p. 123-129, Mar./Apr. 2019. |
ISSN: |
1678-992X |
DOI: |
10.1590/1678-992X-2017-0207 |
Idioma: |
Inglês |
Conteúdo: |
The methods of Annicchiarico (1992) and Cruz et al. (1989) are widely used in phenotypic adaptability and stability analyses in plant breeding. In spite of the importance of these methodologies, their parameters are difficult to interpret. The aim of this research was to develop fuzzy controllers to automate the decision-making process employed by adaptability and stability studies following the methods adopted by Annicchiarico (1992) and Cruz et al. (1989) and check their efficiency using experimental data from common bean cultivars. Fuzzy controllers have been developed based on the Mamdani inference system proposed by these two methods of adaptability and stability studies. For the first fuzzy controller parameters were considered favorable environments and the recommendation index for unfavorable environments obtained by Annicchiarico's method (1992). For the second controller the parameters considered were the general mean (Bo), coefficient of regression of unfavorable environments (B1) and coefficient of favorable environments (B1i + B2i) and the coefficient of determination of the method of Cruz et al. (1989). To check the performance of these drivers yield data from field trials on 18 common bean cultivars grown in 11 environments were used. The controllers were developed from established routines in the R software and, using the inference system based on the methods proposed by Annicchiarico (1992) and Cruz et al. (1989), classified the 18 genotypes appropriately in accordance with the criteria for each method. Thus, the methods used are effective, and are prescribed for decision-making automation in yield adaptability and stability studies pertaining to recommendation of cultivars. MenosThe methods of Annicchiarico (1992) and Cruz et al. (1989) are widely used in phenotypic adaptability and stability analyses in plant breeding. In spite of the importance of these methodologies, their parameters are difficult to interpret. The aim of this research was to develop fuzzy controllers to automate the decision-making process employed by adaptability and stability studies following the methods adopted by Annicchiarico (1992) and Cruz et al. (1989) and check their efficiency using experimental data from common bean cultivars. Fuzzy controllers have been developed based on the Mamdani inference system proposed by these two methods of adaptability and stability studies. For the first fuzzy controller parameters were considered favorable environments and the recommendation index for unfavorable environments obtained by Annicchiarico's method (1992). For the second controller the parameters considered were the general mean (Bo), coefficient of regression of unfavorable environments (B1) and coefficient of favorable environments (B1i + B2i) and the coefficient of determination of the method of Cruz et al. (1989). To check the performance of these drivers yield data from field trials on 18 common bean cultivars grown in 11 environments were used. The controllers were developed from established routines in the R software and, using the inference system based on the methods proposed by Annicchiarico (1992) and Cruz et al. (1989), classified the 18 genotypes appropriately in... Mostrar Tudo |
Palavras-Chave: |
Computational intelligence. |
Thesagro: |
Feijão; Genótipo; Interação Genética; Melhoramento Genético Vegetal; Phaseolus Vulgaris. |
Thesaurus NAL: |
Beans; Genotype-environment interaction; Plant breeding. |
Categoria do assunto: |
G Melhoramento Genético |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/190352/1/CNPAF-2019-SciAgrc.pdf
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Marc: |
LEADER 02682naa a2200313 a 4500 001 2103793 005 2020-10-26 008 2019 bl uuuu u00u1 u #d 022 $a1678-992X 024 7 $a10.1590/1678-992X-2017-0207$2DOI 100 1 $aCARNEIRO, A. R. T. 245 $aFuzzy logic in automation for interpretation of adaptability and stability in plant breeding studies.$h[electronic resource] 260 $c2019 520 $aThe methods of Annicchiarico (1992) and Cruz et al. (1989) are widely used in phenotypic adaptability and stability analyses in plant breeding. In spite of the importance of these methodologies, their parameters are difficult to interpret. The aim of this research was to develop fuzzy controllers to automate the decision-making process employed by adaptability and stability studies following the methods adopted by Annicchiarico (1992) and Cruz et al. (1989) and check their efficiency using experimental data from common bean cultivars. Fuzzy controllers have been developed based on the Mamdani inference system proposed by these two methods of adaptability and stability studies. For the first fuzzy controller parameters were considered favorable environments and the recommendation index for unfavorable environments obtained by Annicchiarico's method (1992). For the second controller the parameters considered were the general mean (Bo), coefficient of regression of unfavorable environments (B1) and coefficient of favorable environments (B1i + B2i) and the coefficient of determination of the method of Cruz et al. (1989). To check the performance of these drivers yield data from field trials on 18 common bean cultivars grown in 11 environments were used. The controllers were developed from established routines in the R software and, using the inference system based on the methods proposed by Annicchiarico (1992) and Cruz et al. (1989), classified the 18 genotypes appropriately in accordance with the criteria for each method. Thus, the methods used are effective, and are prescribed for decision-making automation in yield adaptability and stability studies pertaining to recommendation of cultivars. 650 $aBeans 650 $aGenotype-environment interaction 650 $aPlant breeding 650 $aFeijão 650 $aGenótipo 650 $aInteração Genética 650 $aMelhoramento Genético Vegetal 650 $aPhaseolus Vulgaris 653 $aComputational intelligence 700 1 $aSANGLARD, D. A. 700 1 $aAZEVEDO, A. M. 700 1 $aSOUZA, T. L. P. O. de 700 1 $aPEREIRA, H. S. 700 1 $aMELO, L. C. 773 $tScientia Agricola$gv. 76, n. 2, p. 123-129, Mar./Apr. 2019.
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Embrapa Arroz e Feijão (CNPAF) |
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