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 | Acesso ao texto completo restrito à biblioteca da Embrapa Caprinos e Ovinos. Para informações adicionais entre em contato com cnpc.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Caprinos e Ovinos. |
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Data corrente: |
17/02/2020 |
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Data da última atualização: |
01/12/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
MONTENEGRO, A. R.; SILVA, L. P. da; LOBO, R. N. B. |
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Afiliação: |
ASSIS RUBENS MONTENEGRO, Universidade Federal do Ceará (UFC) - Fortaleza, CE, Brazil; LUCIANO PINHEIRO DA SILVA, Universidade Federal do Ceará (UFC) - Fortaleza, CE, Brazil; RAIMUNDO NONATO BRAGA LOBO, CNPC. |
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Título: |
Effect of different mating systems on population structure and genetic progress of a simulated small flock. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
International Journal of Environmental Sciences and Natural Resources, v. 21, n. 1, e556051, 2019. |
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DOI: |
10.19080/IJESNR.2019.21.556051 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: Strategies to promote genetic progress or preserve genetic diversity in small populations may change due to population size. Higher inbreeding coefficients are associated to the use of breeding values predicted by mixed model methodology, which tends to score better animals within the best families. The reduced effective population size makes herds more susceptible to genetic drift and inbred matings. We compared three methodologies/software on simulated data that reproduced small-closed populations: Mate Selection (evolutionary differential), Gencont (Lagrange Multipliers) and SGRmate (linear programming). Algorithms optimized the objective function in order to achieve the higher genetic progress, but with an inbreeding coefficient of less than 10%, selecting the necessary number of sires and forming the reproductive pairs, except for Gencont, whose objective function was only to minimize the coancestry. All software generated populations with similar genetic progress. Mate Selection generated populations with the highest levels of inbreeding coefficients, similar to RANDOM, which presented best controlled mating between relatives. Gencont produced populations with intermediate levels of inbreeding. SGRmate maintained lowest levels of inbreeding due to higher number of sires selected and equal proportionality in combination of the pairs. Use of linear programming (SGRmate) was more efficient in maintaining the genetic diversity of small-closed populations |
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Palavras-Chave: |
Animal population; Breeding programs; Differential evolutionary algorithm; Mating optimization; Optimal genetic contribution; Optimization methods. |
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Thesaurus Nal: |
Animal genetics; Computer software; Linear programming; Selection criteria. |
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Categoria do assunto: |
G Melhoramento Genético |
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Marc: |
LEADER 02435naa a2200277 a 4500
001 2120327
005 2020-12-01
008 2019 bl uuuu u00u1 u #d
024 7 $a10.19080/IJESNR.2019.21.556051$2DOI
100 1 $aMONTENEGRO, A. R.
245 $aEffect of different mating systems on population structure and genetic progress of a simulated small flock.$h[electronic resource]
260 $c2019
520 $aAbstract: Strategies to promote genetic progress or preserve genetic diversity in small populations may change due to population size. Higher inbreeding coefficients are associated to the use of breeding values predicted by mixed model methodology, which tends to score better animals within the best families. The reduced effective population size makes herds more susceptible to genetic drift and inbred matings. We compared three methodologies/software on simulated data that reproduced small-closed populations: Mate Selection (evolutionary differential), Gencont (Lagrange Multipliers) and SGRmate (linear programming). Algorithms optimized the objective function in order to achieve the higher genetic progress, but with an inbreeding coefficient of less than 10%, selecting the necessary number of sires and forming the reproductive pairs, except for Gencont, whose objective function was only to minimize the coancestry. All software generated populations with similar genetic progress. Mate Selection generated populations with the highest levels of inbreeding coefficients, similar to RANDOM, which presented best controlled mating between relatives. Gencont produced populations with intermediate levels of inbreeding. SGRmate maintained lowest levels of inbreeding due to higher number of sires selected and equal proportionality in combination of the pairs. Use of linear programming (SGRmate) was more efficient in maintaining the genetic diversity of small-closed populations
650 $aAnimal genetics
650 $aComputer software
650 $aLinear programming
650 $aSelection criteria
653 $aAnimal population
653 $aBreeding programs
653 $aDifferential evolutionary algorithm
653 $aMating optimization
653 $aOptimal genetic contribution
653 $aOptimization methods
700 1 $aSILVA, L. P. da
700 1 $aLOBO, R. N. B.
773 $tInternational Journal of Environmental Sciences and Natural Resources$gv. 21, n. 1, e556051, 2019.
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Registro original: |
Embrapa Caprinos e Ovinos (CNPC) |
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Biblioteca |
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Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
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Registro Completo
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Biblioteca(s): |
Embrapa Uva e Vinho. |
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Data corrente: |
15/10/2021 |
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Data da última atualização: |
15/10/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
LIMA, M. dos S.; PEREIRA, G. E.; FEDRIGO, I. M. T. |
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Afiliação: |
MARCOS DOS SANTOS LIMA, Department of Food Technology, Federal Institute of Sertão Pernambucano, Campus Petrolina, BR 407 km 08 RdJardim São Paulo, Petrolina, PE 56314-522, Brazil; GIULIANO ELIAS PEREIRA, CNPUV; ISABELA MAIA TOALDO FEDRIGO, Department of Food Science and Technology, Federal University of Santa Catarina, Admar Gonzaga Rd., 1346, Itacorubi, Florianópolis, SC 88034-001, Brazil. |
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Título: |
Artifcial neural network: a powerful tool in associating phenolic compounds with antioxidant activity of grape juices. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Food Analytical Methods, 14 oct. 2021. Online. |
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DOI: |
10.1007/s12161-021-02144-8 |
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Idioma: |
Inglês |
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Conteúdo: |
In vitro techniques are essential to assess the antioxidant potential of foods, although methods with diferent action mechanisms make troublesome data analysis. This article describes the use of artifcial neural network (ANN) to associate phenolic compounds with antioxidant activity in vitro (AOX) of grape juices. A multilayer perceptron (MLP) ANN was obtained with 28 phenolics quantifed, as input layers, and AOX measuring by DPPH, ABTS, FRAP, H2O2, and β-carotene/linoleic acid bleaching assay (βCLA) methods, as output layers. To improve discussion in food sciences, the ANN results were compared with Pearson?s correlation and principal component analysis (PCA), methods largely used in food studies. Pearson?s technique showed correlations between antioxidant methods and some of the phenolic compounds, but with limitations. PCA proved to be a more powerful method than Pearson?s correlation, as it positively associated 13 phenolics with four out of fve antioxidant methods. The MLP-ANN allowed simultaneous association of 19 individual phenolics, while a single hidden layer predicted 15 phenolics with simultaneous action in all AOX methods. The power of association was: ANN>PCA>Pearson. It was evidenced that ANN is a powerful tool for screening antioxidants in diferent AOX systems, which is applicable in health interests. |
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Palavras-Chave: |
Antioxidant methods; Bioactivity; Grape polyphenol. |
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Thesaurus NAL: |
Chemometrics. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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URL: |
https://www.alice.cnptia.embrapa.br/alice/bitstream/doc/1135356/1/SantosLima2021-Article-ArtificialNeuralNetworkAPowerf.pdf
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Marc: |
LEADER 02004naa a2200205 a 4500
001 2135356
005 2021-10-15
008 2021 bl uuuu u00u1 u #d
024 7 $a10.1007/s12161-021-02144-8$2DOI
100 1 $aLIMA, M. dos S.
245 $aArtifcial neural network$ba powerful tool in associating phenolic compounds with antioxidant activity of grape juices.$h[electronic resource]
260 $c2021
520 $aIn vitro techniques are essential to assess the antioxidant potential of foods, although methods with diferent action mechanisms make troublesome data analysis. This article describes the use of artifcial neural network (ANN) to associate phenolic compounds with antioxidant activity in vitro (AOX) of grape juices. A multilayer perceptron (MLP) ANN was obtained with 28 phenolics quantifed, as input layers, and AOX measuring by DPPH, ABTS, FRAP, H2O2, and β-carotene/linoleic acid bleaching assay (βCLA) methods, as output layers. To improve discussion in food sciences, the ANN results were compared with Pearson?s correlation and principal component analysis (PCA), methods largely used in food studies. Pearson?s technique showed correlations between antioxidant methods and some of the phenolic compounds, but with limitations. PCA proved to be a more powerful method than Pearson?s correlation, as it positively associated 13 phenolics with four out of fve antioxidant methods. The MLP-ANN allowed simultaneous association of 19 individual phenolics, while a single hidden layer predicted 15 phenolics with simultaneous action in all AOX methods. The power of association was: ANN>PCA>Pearson. It was evidenced that ANN is a powerful tool for screening antioxidants in diferent AOX systems, which is applicable in health interests.
650 $aChemometrics
653 $aAntioxidant methods
653 $aBioactivity
653 $aGrape polyphenol
700 1 $aPEREIRA, G. E.
700 1 $aFEDRIGO, I. M. T.
773 $tFood Analytical Methods, 14 oct. 2021. Online.
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Embrapa Uva e Vinho (CNPUV) |
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