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Registro Completo |
Biblioteca(s): |
Embrapa Trigo. |
Data corrente: |
14/04/2016 |
Data da última atualização: |
15/04/2016 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
REBONATTO, A.; SALVADORI, J. R.; LAU, D. |
Afiliação: |
ADRIANE REBONATTO; JOSÉ ROBERTO SALVADORI, UPF; DOUGLAS LAU, CNPT. |
Título: |
Temporal changes in cereal aphids (Hemiptera: Aphididae) populations in northern Rio Grande do Sul, Brazil. |
Ano de publicação: |
2015 |
Fonte/Imprenta: |
Journal of Agricultural Science, Toronto, v. 7, n. 10, p. 71-78, 2015. |
ISSN: |
1916-9760 |
DOI: |
10.5539/jas.v7n10p71 |
Idioma: |
Inglês |
Palavras-Chave: |
Afídeos; Insetos. |
Thesagro: |
Cereal; Rhopalosiphum Padi; Schizaphis Graminum; Triticum Aestivum. |
Thesaurus Nal: |
Metopolophium dirhodum; Sitobion avenae. |
Categoria do assunto: |
O Insetos e Entomologia |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/142322/1/ID43653-2015JASv7n10p71.pdf
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Marc: |
LEADER 00780naa a2200253 a 4500 001 2043382 005 2016-04-15 008 2015 bl uuuu u00u1 u #d 022 $a1916-9760 024 7 $a10.5539/jas.v7n10p71$2DOI 100 1 $aREBONATTO, A. 245 $aTemporal changes in cereal aphids (Hemiptera$bAphididae) populations in northern Rio Grande do Sul, Brazil.$h[electronic resource] 260 $c2015 650 $aMetopolophium dirhodum 650 $aSitobion avenae 650 $aCereal 650 $aRhopalosiphum Padi 650 $aSchizaphis Graminum 650 $aTriticum Aestivum 653 $aAfídeos 653 $aInsetos 700 1 $aSALVADORI, J. R. 700 1 $aLAU, D. 773 $tJournal of Agricultural Science, Toronto$gv. 7, n. 10, p. 71-78, 2015.
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Registro original: |
Embrapa Trigo (CNPT) |
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Registro Completo
Biblioteca(s): |
Embrapa Algodão. |
Data corrente: |
21/11/2018 |
Data da última atualização: |
21/11/2018 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 2 |
Autoria: |
CARVALHO, L. P. de; TEODORO, P. E.; BARROSO, L. M. A.; FARIAS, F. J. C.; MORELLO, C. de L.; NASCIMENTO, M. |
Afiliação: |
LUIZ PAULO DE CARVALHO, CNPA; PAULO EDUARO TEODORO, UFMS - CHAPADÃO DO SUL, MS; LAÍS MAYARA AZEVEDO BARROSO, UFV; FRANCISCO JOSE CORREIA FARIAS, CNPA; CAMILO DE LELIS MORELLO, CNPA; MOYSÉS NASCIMENTO, UFV. |
Título: |
Artificial neural networks classify cotton genotypes for fiber length. |
Ano de publicação: |
2018 |
Fonte/Imprenta: |
Crop Breeding and Applied Biotechnology, v. 18, p. 200-204, 2018. |
ISSN: |
1518-7853 |
DOI: |
10.1590/1984-70332018v18n2n28 |
Idioma: |
Inglês |
Conteúdo: |
Fiber length is the main trait that needs to be improved in cotton. However, the presence of genotypes x environments interaction for this trait can hinder the recommendation of genotypes with greater length fibers. The aim of this study was to evaluate the adaptability and stability of the fibers length of cotton genotypes for recommendation to the Midwest and Northeast, using artificial neural networks (ANNs) and Eberhart and Russell method. Seven trials were carried out in the states of Ceará, Rio Grande do Norte, Goiás and Mato Grosso do Sul. Experimental design was a randomized block with four replications. Data were submitted to analysis of adaptability and stability through the Eberhart & Russell and ANNs methodologies. Based on these methods, the genotypes BRS Aroeira, CNPA CNPA 2009 42 and CNPA 2009 27 has better performance in unfavorable, general and favorable environment, respectively, for having fiber length above the overall mean of environments and high phenotypic stability. |
Palavras-Chave: |
Inteligência artificial. |
Thesagro: |
Algodão; Genótipo; Gossypium Hirsutum; Gossypium Hirsutum Marie Galante. |
Thesaurus NAL: |
Artificial intelligence; Cotton; Genotype-environment interaction. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/186613/1/Artificial-neural-networks.pdf
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Marc: |
LEADER 01921naa a2200301 a 4500 001 2099791 005 2018-11-21 008 2018 bl uuuu u00u1 u #d 022 $a1518-7853 024 7 $a10.1590/1984-70332018v18n2n28$2DOI 100 1 $aCARVALHO, L. P. de 245 $aArtificial neural networks classify cotton genotypes for fiber length.$h[electronic resource] 260 $c2018 520 $aFiber length is the main trait that needs to be improved in cotton. However, the presence of genotypes x environments interaction for this trait can hinder the recommendation of genotypes with greater length fibers. The aim of this study was to evaluate the adaptability and stability of the fibers length of cotton genotypes for recommendation to the Midwest and Northeast, using artificial neural networks (ANNs) and Eberhart and Russell method. Seven trials were carried out in the states of Ceará, Rio Grande do Norte, Goiás and Mato Grosso do Sul. Experimental design was a randomized block with four replications. Data were submitted to analysis of adaptability and stability through the Eberhart & Russell and ANNs methodologies. Based on these methods, the genotypes BRS Aroeira, CNPA CNPA 2009 42 and CNPA 2009 27 has better performance in unfavorable, general and favorable environment, respectively, for having fiber length above the overall mean of environments and high phenotypic stability. 650 $aArtificial intelligence 650 $aCotton 650 $aGenotype-environment interaction 650 $aAlgodão 650 $aGenótipo 650 $aGossypium Hirsutum 650 $aGossypium Hirsutum Marie Galante 653 $aInteligência artificial 700 1 $aTEODORO, P. E. 700 1 $aBARROSO, L. M. A. 700 1 $aFARIAS, F. J. C. 700 1 $aMORELLO, C. de L. 700 1 $aNASCIMENTO, M. 773 $tCrop Breeding and Applied Biotechnology$gv. 18, p. 200-204, 2018.
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