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Registro Completo |
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
16/05/2022 |
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Data da última atualização: |
16/05/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
SOUSA, I. C. de; NASCIMENTO, M.; SANT’ANNA, I. de C.; CAIXETA, E. T.; AZEVEDO, C. F.; CRUZ, C. D.; SILVA, F. L. da; ALKIMIM, E. R.; NASCIMENTO, A. C. C.; SERÃO, N. V. L. |
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Afiliação: |
ITHALO COELHO DE SOUSA, IOWA STATE UNIVERSITY; MOYSÉS NASCIMENTO, UFV; ISABELA DE CASTRO SANT’ANNA, IAC; EVELINE TEIXEIRA CAIXETA MOURA, CNPCa; CAMILA FERREIRA AZEVEDO, UFV; COSME DAMIÃO CRUZ, UFV; FELIPE LOPES DA SILVA, UFV; EMILLY RUAS ALKIMIM, UFMT; ANA CAROLINA CAMPANA NASCIMENTO, UFV; NICK VERGARA LOPES SERÃO, IOWA STATE UNIVERSITY. |
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Título: |
Marker effects and heritability estimates using additive-dominance genomic architectures via artificial neural networks in Coffea canephora. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Plos One, v. 17, n.1, e0262055, 2022. |
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DOI: |
https://doi.org/10.1371/journal.pone.0262055 |
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Idioma: |
Inglês |
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Conteúdo: |
Many methodologies are used to predict the genetic merit in animals and plants, but some of them require priori assumptions that may increase the complexity of the model. Artificial neural network (ANN) has advantage to not require priori assumptions about the relationships between inputs and the output allowing great flexibility to handle different types of complex non-additive effects, such as dominance and epistasis. Despite this advantage, the biological interpretability of ANNs is still limited. The aim of this research was to estimate the heritability and markers effects for two traits in Coffea canephora using an additive-dominance architecture ANN and to compare it with genomic best linear unbiased prediction (GBLUP). The data used consists of 51 clones of C. canephora varietal Conilon, 32 of varietal group Robusta and 82 intervarietal hybrids. From this, 165 phenotyped individuals were genotyped for 14,387 SNPs. Due to the high computational cost of ANNs, we used Bagging decision tree to reduce the dimensionality of the data, selecting the markers that accumulated 70% of the total importance. An ANN with three hidden layers was run, each varying from 1 to 40 neurons summing 64,000 neural networks. The network architectures with the best predictive ability were selected. The best architectures were composed by 4, 15, and 33 neurons in the first, second and third hidden layers, respectively, for yield, and by 13, 20, and 24 neurons, respectively for rust resistance. The predictive ability was greater when using ANN with three hidden layers than using one hidden layer and GBLUP, with 0.72 and 0.88 for yield and coffee leaf rust resistance, respectively. The concordance rate (CR) of the 10% larger markers effects among the methods varied between 10% and 13.8%, for additive effects and between 5.4% and 11.9% for dominance effects. The narrow-sense (h2a ) and dominance-only (h2a ) heritability estimates were 0.25 and 0.06, respectively, for yield, and 0.67 and 0.03, respectively for rust resistance. The ANN was able to estimate the heritabilities from an additive-dominance genomic architectures and the ANN with three hidden layers obtained best predictive ability when compared with those obtained from GBLUP and ANN with one hidden layer. MenosMany methodologies are used to predict the genetic merit in animals and plants, but some of them require priori assumptions that may increase the complexity of the model. Artificial neural network (ANN) has advantage to not require priori assumptions about the relationships between inputs and the output allowing great flexibility to handle different types of complex non-additive effects, such as dominance and epistasis. Despite this advantage, the biological interpretability of ANNs is still limited. The aim of this research was to estimate the heritability and markers effects for two traits in Coffea canephora using an additive-dominance architecture ANN and to compare it with genomic best linear unbiased prediction (GBLUP). The data used consists of 51 clones of C. canephora varietal Conilon, 32 of varietal group Robusta and 82 intervarietal hybrids. From this, 165 phenotyped individuals were genotyped for 14,387 SNPs. Due to the high computational cost of ANNs, we used Bagging decision tree to reduce the dimensionality of the data, selecting the markers that accumulated 70% of the total importance. An ANN with three hidden layers was run, each varying from 1 to 40 neurons summing 64,000 neural networks. The network architectures with the best predictive ability were selected. The best architectures were composed by 4, 15, and 33 neurons in the first, second and third hidden layers, respectively, for yield, and by 13, 20, and 24 neurons, respectively for rust resistance. T... Mostrar Tudo |
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Palavras-Chave: |
Rede neural artificial. |
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Thesagro: |
Coffea Canephora; Marcador Genético. |
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Thesaurus Nal: |
Dominance (genetics); Neural networks. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1143026/1/Marker-effects-and-heritability.pdf
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Marc: |
LEADER 03240naa a2200301 a 4500
001 2143026
005 2022-05-16
008 2022 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1371/journal.pone.0262055$2DOI
100 1 $aSOUSA, I. C. de
245 $aMarker effects and heritability estimates using additive-dominance genomic architectures via artificial neural networks in Coffea canephora.$h[electronic resource]
260 $c2022
520 $aMany methodologies are used to predict the genetic merit in animals and plants, but some of them require priori assumptions that may increase the complexity of the model. Artificial neural network (ANN) has advantage to not require priori assumptions about the relationships between inputs and the output allowing great flexibility to handle different types of complex non-additive effects, such as dominance and epistasis. Despite this advantage, the biological interpretability of ANNs is still limited. The aim of this research was to estimate the heritability and markers effects for two traits in Coffea canephora using an additive-dominance architecture ANN and to compare it with genomic best linear unbiased prediction (GBLUP). The data used consists of 51 clones of C. canephora varietal Conilon, 32 of varietal group Robusta and 82 intervarietal hybrids. From this, 165 phenotyped individuals were genotyped for 14,387 SNPs. Due to the high computational cost of ANNs, we used Bagging decision tree to reduce the dimensionality of the data, selecting the markers that accumulated 70% of the total importance. An ANN with three hidden layers was run, each varying from 1 to 40 neurons summing 64,000 neural networks. The network architectures with the best predictive ability were selected. The best architectures were composed by 4, 15, and 33 neurons in the first, second and third hidden layers, respectively, for yield, and by 13, 20, and 24 neurons, respectively for rust resistance. The predictive ability was greater when using ANN with three hidden layers than using one hidden layer and GBLUP, with 0.72 and 0.88 for yield and coffee leaf rust resistance, respectively. The concordance rate (CR) of the 10% larger markers effects among the methods varied between 10% and 13.8%, for additive effects and between 5.4% and 11.9% for dominance effects. The narrow-sense (h2a ) and dominance-only (h2a ) heritability estimates were 0.25 and 0.06, respectively, for yield, and 0.67 and 0.03, respectively for rust resistance. The ANN was able to estimate the heritabilities from an additive-dominance genomic architectures and the ANN with three hidden layers obtained best predictive ability when compared with those obtained from GBLUP and ANN with one hidden layer.
650 $aDominance (genetics)
650 $aNeural networks
650 $aCoffea Canephora
650 $aMarcador Genético
653 $aRede neural artificial
700 1 $aNASCIMENTO, M.
700 1 $aSANT’ANNA, I. de C.
700 1 $aCAIXETA, E. T.
700 1 $aAZEVEDO, C. F.
700 1 $aCRUZ, C. D.
700 1 $aSILVA, F. L. da
700 1 $aALKIMIM, E. R.
700 1 $aNASCIMENTO, A. C. C.
700 1 $aSERÃO, N. V. L.
773 $tPlos One$gv. 17, n.1, e0262055, 2022.
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Registro original: |
Embrapa Café (CNPCa) |
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Registro Completo
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Biblioteca(s): |
Embrapa Roraima. |
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Data corrente: |
07/05/2024 |
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Data da última atualização: |
07/05/2024 |
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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: |
NINSIN, K. D; SOUZA, P. G. C.; AMARO, G. C.; AIDOO, O. F.; BARRY, E. J. D. V.; SILVA, R. S. da; OSEI-OWUSU, J.; DOFUOR, A. K.; ABLORMETI, F. K.; HEVE, W. K.; EDUSEI, G.; AGBOYI, L. K.; BESEH, P.; BOAFO, H. A.; BORGEMEISTER, C.; SÉTAMOU, M. |
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Afiliação: |
KODWO DADZIE NINSIN, SCHOOL OF NATURAL AND ENVIRONMENTAL SCIENCES; PHILIPE GUILHERME CORCINO SOUZA, INSTITUTO FEDERAL DE CIÊNCIA E TECNOLOGIA DO TRIÂNGULO MINEIRO; GEORGE CORREA AMARO, CPAF-RR; OWUSU FORDJOUR AIDOO, SCHOOL OF NATURAL AND ENVIRONMENTAL SCIENCES; EDMOND JOSEPH DJIBRIL VICTOR BARRY, UNIVERSIDADE FEDERAL DOS VALES DO JEQUITINHONHA E MUCURI; RICARDO SIQUEIRA DA SILVA, UNIVERSIDADE FEDERAL DOS VALES DO JEQUITINHONHA E MUCURI; JONATHAN OSEI-OWUSU, UNIVERSITY OF ENVIRONMENT AND SUSTAINABLE DEVELOPMENT; ABOAGYE KWARTENG DOFUOR, SCHOOL OF NATURAL AND ENVIRONMENTAL SCIENCES; FRED KORMLA ABLORMETI, COUNCIL FOR SCIENTIFIC AND INDUSTRIAL RESEARCH; WILLIAM K. HEVE, SCHOOL OF NATURAL AND ENVIRONMENTAL SCIENCES; GEORGE EDUSEI, SCHOOL OF NATURAL AND ENVIRONMENTAL SCIENCES; LAKPO KOKU AGBOYI, CENTRE FOR AGRICULTURE AND BIOSCIENCES INTERNATIONAL; PATRICK BESEH, PLANT PROTECTION AND REGULATORY SERVICES DIRECTORATE; HETTIE ARWOH BOAFO, CENTRE FOR AGRICULTURE AND BIOSCIENCES INTERNATIONAL; CHRISTIAN BORGEMEISTER, UNIVERSITY OF BONN; MAMOUDOU SÉTAMOU, UNIVERSITY- KINGSVILLE. |
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Título: |
Risk of spread of the Asian citrus psyllid Diaphorina citri Kuwayama (Hemiptera: Liviidae) in Ghana. |
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Ano de publicação: |
2024 |
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Fonte/Imprenta: |
Bulletin of Entomological Research, 2024. |
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DOI: |
https://doi.org/10.1017/S0007485324000105 |
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Idioma: |
Inglês |
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Conteúdo: |
The impact of invasive species on biodiversity, food security and economy is increasingly noticeable in various regions of the globe as a consequence of climate change. Yet, there is limited research on how climate change affects the distribution of the invasive Asian citrus psyllid Diaphorina citri Kuwayama (Hemiptera:Liviidae) in Ghana. Using maxnet package to fit the Maxent model in R software, we answered the following questions; (i) what are the main drivers for D. citri distribution, (ii) what are the D. citri-specific habitat requirements and (iii) how well do the risk maps fit with what we know to be correctly based on the avail- able evidence?. We found that temperature seasonality (Bio04), mean temperature of warmest quarter (Bio10), precipitation of driest quarter (Bio17), moderate resolution imaging spectro- radiometer land cover and precipitation seasonality (Bio15), were the most important drivers of D. citri distribution. The results follow the known distribution records of the pest with potential expansion of habitat suitability in the future. Because many invasive species, includ- ing D. citri, can adapt to the changing climates, our findings can serve as a guide for surveil- lance, tracking and prevention of D. citri spread in Ghana. |
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Palavras-Chave: |
Asian citrus psyllid; Maxnet; Species distribution modeling. |
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Thesaurus NAL: |
Climate change; Diaphorina citri. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1164104/1/risk-of-spread-of-the-asian-citrus-psyllid-diaphorina-citri-kuwayama-hemiptera-liviidae-in-ghana.pdf
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Marc: |
LEADER 02344naa a2200373 a 4500
001 2164104
005 2024-05-07
008 2024 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1017/S0007485324000105$2DOI
100 1 $aNINSIN, K. D
245 $aRisk of spread of the Asian citrus psyllid Diaphorina citri Kuwayama (Hemiptera$bLiviidae) in Ghana.$h[electronic resource]
260 $c2024
520 $aThe impact of invasive species on biodiversity, food security and economy is increasingly noticeable in various regions of the globe as a consequence of climate change. Yet, there is limited research on how climate change affects the distribution of the invasive Asian citrus psyllid Diaphorina citri Kuwayama (Hemiptera:Liviidae) in Ghana. Using maxnet package to fit the Maxent model in R software, we answered the following questions; (i) what are the main drivers for D. citri distribution, (ii) what are the D. citri-specific habitat requirements and (iii) how well do the risk maps fit with what we know to be correctly based on the avail- able evidence?. We found that temperature seasonality (Bio04), mean temperature of warmest quarter (Bio10), precipitation of driest quarter (Bio17), moderate resolution imaging spectro- radiometer land cover and precipitation seasonality (Bio15), were the most important drivers of D. citri distribution. The results follow the known distribution records of the pest with potential expansion of habitat suitability in the future. Because many invasive species, includ- ing D. citri, can adapt to the changing climates, our findings can serve as a guide for surveil- lance, tracking and prevention of D. citri spread in Ghana.
650 $aClimate change
650 $aDiaphorina citri
653 $aAsian citrus psyllid
653 $aMaxnet
653 $aSpecies distribution modeling
700 1 $aSOUZA, P. G. C.
700 1 $aAMARO, G. C.
700 1 $aAIDOO, O. F.
700 1 $aBARRY, E. J. D. V.
700 1 $aSILVA, R. S. da
700 1 $aOSEI-OWUSU, J.
700 1 $aDOFUOR, A. K.
700 1 $aABLORMETI, F. K.
700 1 $aHEVE, W. K.
700 1 $aEDUSEI, G.
700 1 $aAGBOYI, L. K.
700 1 $aBESEH, P.
700 1 $aBOAFO, H. A.
700 1 $aBORGEMEISTER, C.
700 1 $aSÉTAMOU, M.
773 $tBulletin of Entomological Research, 2024.
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