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Registro Completo |
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
03/12/2019 |
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Data da última atualização: |
03/12/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
ANDRADE, L. R. B. de; SOUSA, M. B. e; OLIVEIRA, E. J. de; RESENDE, M. D. V. de; AZEVEDO, C. F. |
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Afiliação: |
Luciano Rogério Braatz de Andrade, UFV; Massaine Bandeira e Sousa, Universidade Federal do Recôncavo da Bahia; EDER JORGE DE OLIVEIRA, CNPMF; MARCOS DEON VILELA DE RESENDE, CNPF; Camila Ferreira Azevedo, UFV. |
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Título: |
Cassava yield traits predicted by genomic selection methods. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
PLoS One, v. 14, n. 11, e0224920, Nov. 2019. 22 p. |
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DOI: |
10.1371/journal.pone.0224920 |
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Idioma: |
Inglês |
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Conteúdo: |
Genomic selection (GS) has been used to optimize genetic gains when phenotypic selection is considered costly and difficult to measure. The objective of this work was to evaluate the efficiency and consistency of GS prediction for cassava yield traits (Manihot esculenta Crantz) using different methods, taking into account the effect of population structure. BLUPs and deregressed BLUPs were obtained for 888 cassava accessions and evaluated for fresh root yield, dry root yield and dry matter content in roots in 21 trials conducted from 2011 to 2016. The deregressed BLUPs obtained for the accessions from a 48K single nucleotide polymorphism dataset were used for genomic predictions based on the BayesB, BLASSO, RR-BLUP, G-BLUP and RKHS methods. The accessions? BLUPs were used in the validation step using four cross-validation strategies, taking into account population structure and different GS methods. Similar estimates of predictive ability and bias were identified for the different genomic selection methods in the first cross-validation strategy. Lower predictive ability was observed for fresh root yield (0.4569 ?RR-BLUP to 0.4756?RKHS) and dry root yield (0.4689 ?G-BLUP to 0.4818?RKHS) in comparison with dry matter content (0.5655 ? BLASSO to 0.5670 ?RKHS). However, the RKHS method exhibited higher efficiency and consistency in most of the validation scenarios in terms of prediction ability for fresh root yield and dry root yield. The correlations of the genomic estimated breeding values between the genomic selection methods were quite high (0.99?1.00), resulting in high coincidence of clone selection regardless of the genomic selection method. The deviance analyses within and between the validation clusters formed by the discriminant analysis of principal components were significant for all traits. Therefore, this study indicated that i) the prediction of dry matter content was more accurate compared to that of yield traits, possibly as a result of the smaller influence of non-additive genetic effects; ii) the RKHS method resulted in high and stable prediction ability in most of the validation scenarios; and iii) some kinship between the validation and training populations is desirable in order for genomic selection to succeed due to the significant effect of population structure on genomic selection predictions. MenosGenomic selection (GS) has been used to optimize genetic gains when phenotypic selection is considered costly and difficult to measure. The objective of this work was to evaluate the efficiency and consistency of GS prediction for cassava yield traits (Manihot esculenta Crantz) using different methods, taking into account the effect of population structure. BLUPs and deregressed BLUPs were obtained for 888 cassava accessions and evaluated for fresh root yield, dry root yield and dry matter content in roots in 21 trials conducted from 2011 to 2016. The deregressed BLUPs obtained for the accessions from a 48K single nucleotide polymorphism dataset were used for genomic predictions based on the BayesB, BLASSO, RR-BLUP, G-BLUP and RKHS methods. The accessions? BLUPs were used in the validation step using four cross-validation strategies, taking into account population structure and different GS methods. Similar estimates of predictive ability and bias were identified for the different genomic selection methods in the first cross-validation strategy. Lower predictive ability was observed for fresh root yield (0.4569 ?RR-BLUP to 0.4756?RKHS) and dry root yield (0.4689 ?G-BLUP to 0.4818?RKHS) in comparison with dry matter content (0.5655 ? BLASSO to 0.5670 ?RKHS). However, the RKHS method exhibited higher efficiency and consistency in most of the validation scenarios in terms of prediction ability for fresh root yield and dry root yield. The correlations of the genomic estimated br... Mostrar Tudo |
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Palavras-Chave: |
Genomic predictions; Heredity. |
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Thesagro: |
Mandioca; Melhoramento Genético Vegetal. |
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Thesaurus Nal: |
Cassava; 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/205981/1/2019-M.Deon-PO-Cassava.pdf
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Marc: |
LEADER 03091naa a2200253 a 4500
001 2115740
005 2019-12-03
008 2019 bl uuuu u00u1 u #d
024 7 $a10.1371/journal.pone.0224920$2DOI
100 1 $aANDRADE, L. R. B. de
245 $aCassava yield traits predicted by genomic selection methods.$h[electronic resource]
260 $c2019
520 $aGenomic selection (GS) has been used to optimize genetic gains when phenotypic selection is considered costly and difficult to measure. The objective of this work was to evaluate the efficiency and consistency of GS prediction for cassava yield traits (Manihot esculenta Crantz) using different methods, taking into account the effect of population structure. BLUPs and deregressed BLUPs were obtained for 888 cassava accessions and evaluated for fresh root yield, dry root yield and dry matter content in roots in 21 trials conducted from 2011 to 2016. The deregressed BLUPs obtained for the accessions from a 48K single nucleotide polymorphism dataset were used for genomic predictions based on the BayesB, BLASSO, RR-BLUP, G-BLUP and RKHS methods. The accessions? BLUPs were used in the validation step using four cross-validation strategies, taking into account population structure and different GS methods. Similar estimates of predictive ability and bias were identified for the different genomic selection methods in the first cross-validation strategy. Lower predictive ability was observed for fresh root yield (0.4569 ?RR-BLUP to 0.4756?RKHS) and dry root yield (0.4689 ?G-BLUP to 0.4818?RKHS) in comparison with dry matter content (0.5655 ? BLASSO to 0.5670 ?RKHS). However, the RKHS method exhibited higher efficiency and consistency in most of the validation scenarios in terms of prediction ability for fresh root yield and dry root yield. The correlations of the genomic estimated breeding values between the genomic selection methods were quite high (0.99?1.00), resulting in high coincidence of clone selection regardless of the genomic selection method. The deviance analyses within and between the validation clusters formed by the discriminant analysis of principal components were significant for all traits. Therefore, this study indicated that i) the prediction of dry matter content was more accurate compared to that of yield traits, possibly as a result of the smaller influence of non-additive genetic effects; ii) the RKHS method resulted in high and stable prediction ability in most of the validation scenarios; and iii) some kinship between the validation and training populations is desirable in order for genomic selection to succeed due to the significant effect of population structure on genomic selection predictions.
650 $aCassava
650 $aPlant breeding
650 $aMandioca
650 $aMelhoramento Genético Vegetal
653 $aGenomic predictions
653 $aHeredity
700 1 $aSOUSA, M. B. e
700 1 $aOLIVEIRA, E. J. de
700 1 $aRESENDE, M. D. V. de
700 1 $aAZEVEDO, C. F.
773 $tPLoS One$gv. 14, n. 11, e0224920, Nov. 2019. 22 p.
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Registro original: |
Embrapa Florestas (CNPF) |
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Biblioteca |
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Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
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Registro Completo
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Biblioteca(s): |
Embrapa Semiárido. |
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Data corrente: |
29/01/2000 |
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Data da última atualização: |
19/04/2022 |
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Tipo da produção científica: |
Circular Técnica |
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Autoria: |
OLIVEIRA, M. C. de; BERNARDINO, F. A. |
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Afiliação: |
MARTINIANO CAVALCANTE DE OLIVEIRA, CPATSA; FRANCISCO ATAÍDE BERNARDINO, CPATSA. |
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Título: |
Melancia forrageira, um novo recurso alimentar para a pecuária das regiões secas do Nordeste do Brasil. |
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Ano de publicação: |
2000 |
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Fonte/Imprenta: |
Petrolina: Embrapa Semi-Árido, 2000. |
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Páginas: |
17 p. |
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Série: |
(Embrapa Semi-Árido. Circular técnica, 49). |
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Idioma: |
Português |
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Conteúdo: |
Especificações técnicas. Variedades. Composição química. Período de dormência. Tipos de solo. Métodos de plantio. Manejo e tratos culturais. Cultivos de sequeiro ou irrigação. Adubação. Produtividade. Conservação e estocagem dos frutos. Sementes. Eficiência no uso da melancia. Capacidade de suporte. Ganho de peso. Produção de leite. |
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Palavras-Chave: |
Alimentacao animal; Brasil; Feed crops; Forage watermelon; Forraging; Melancia de cavalo; Melancia de porco; Melancia forrageira; Melancia-de-cavalo; Melancia-de-porco; Nordeste; Northeast; Pernambuco; Petrolina; Productivity; Regiao Nordeste; Species; Watermelon. |
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Thesagro: |
Adubação; Alimento Animal; Alimento Para Animal; Citrullus Lanatus; Citrullus Vulgaris; Composição Química; Dormência; Espécie; Forragem; Manejo; Melancia; Nutrição Animal; Pastagem; Planta Forrageira; Produção animal; Produtividade; Semente. |
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Thesaurus NAL: |
animal feeding; animal nutrition; Animal production; Brazil; chemical composition; crop management; dormancy; fertilizers; forage; seeds; watermelons. |
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Categoria do assunto: |
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L Ciência Animal e Produtos de Origem Animal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/CPATSA/8764/1/CTE49.pdf
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Marc: |
LEADER 02179nam a2200697 a 4500
001 1134099
005 2022-04-19
008 2000 bl uuuu u0uu1 u #d
100 1 $aOLIVEIRA, M. C. de
245 $aMelancia forrageira, um novo recurso alimentar para a pecuária das regiões secas do Nordeste do Brasil.
260 $aPetrolina: Embrapa Semi-Árido$c2000
300 $a17 p.
490 $a(Embrapa Semi-Árido. Circular técnica, 49).
520 $aEspecificações técnicas. Variedades. Composição química. Período de dormência. Tipos de solo. Métodos de plantio. Manejo e tratos culturais. Cultivos de sequeiro ou irrigação. Adubação. Produtividade. Conservação e estocagem dos frutos. Sementes. Eficiência no uso da melancia. Capacidade de suporte. Ganho de peso. Produção de leite.
650 $aanimal feeding
650 $aanimal nutrition
650 $aAnimal production
650 $aBrazil
650 $achemical composition
650 $acrop management
650 $adormancy
650 $afertilizers
650 $aforage
650 $aseeds
650 $awatermelons
650 $aAdubação
650 $aAlimento Animal
650 $aAlimento Para Animal
650 $aCitrullus Lanatus
650 $aCitrullus Vulgaris
650 $aComposição Química
650 $aDormência
650 $aEspécie
650 $aForragem
650 $aManejo
650 $aMelancia
650 $aNutrição Animal
650 $aPastagem
650 $aPlanta Forrageira
650 $aProdução animal
650 $aProdutividade
650 $aSemente
653 $aAlimentacao animal
653 $aBrasil
653 $aFeed crops
653 $aForage watermelon
653 $aForraging
653 $aMelancia de cavalo
653 $aMelancia de porco
653 $aMelancia forrageira
653 $aMelancia-de-cavalo
653 $aMelancia-de-porco
653 $aNordeste
653 $aNortheast
653 $aPernambuco
653 $aPetrolina
653 $aProductivity
653 $aRegiao Nordeste
653 $aSpecies
653 $aWatermelon
700 1 $aBERNARDINO, F. A.
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Registro original: |
Embrapa Semiárido (CPATSA) |
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