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Registro Completo |
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
14/01/2019 |
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Data da última atualização: |
26/10/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
CARNEIRO, A. R. T.; SANGLARD, D. A.; AZEVEDO, A. M.; SOUZA, T. L. P. O. de; PEREIRA, H. S.; MELO, L. C. |
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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. |
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Título: |
Fuzzy logic in automation for interpretation of adaptability and stability in plant breeding studies. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
Scientia Agricola, v. 76, n. 2, p. 123-129, Mar./Apr. 2019. |
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ISSN: |
1678-992X |
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DOI: |
10.1590/1678-992X-2017-0207 |
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Idioma: |
Inglês |
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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 |
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Palavras-Chave: |
Computational intelligence. |
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Thesagro: |
Feijão; Genótipo; Interação Genética; Melhoramento Genético Vegetal; Phaseolus Vulgaris. |
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Thesaurus Nal: |
Beans; Genotype-environment interaction; Plant breeding. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/190352/1/CNPAF-2019-SciAgrc.pdf
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Marc: |
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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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| 1. |  | CARNEIRO, A. R. T.; SANGLARD, D. A.; AZEVEDO, A. M.; SOUZA, T. L. P. O. de; PEREIRA, H. S.; MELO, L. C. Fuzzy logic in automation for interpretation of adaptability and stability in plant breeding studies. Scientia Agricola, v. 76, n. 2, p. 123-129, Mar./Apr. 2019.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
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