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Registro Completo |
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Biblioteca(s): |
Embrapa Suínos e Aves. |
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Data corrente: |
13/12/2023 |
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Data da última atualização: |
29/12/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
METTENLEITER, T. C.; MARKOTTER, W.; CHARRON, D. F.; ADISASMITO, W. B.; ALMUHAIRI, S.; BEHRAVESH, C. B.; BILIVOGUI, P.; BUKACHI, S. A.; CASAS, N.; BECERRA, N. C.; CHAUDHARY, A.; ZANELLA, J. R. C.; CUNNINGHAM, A. A.; DAR, O.; DEBNATH, N.; FARAG, E.; GAO, G. F.; HAYMAN, D. T. S.; KHAITSA, M.; KOOPMANS, M. P. G.; MACHALABA, C.; MACKENZIE, J. S.; MORAND, S.; SMOLENSKIY, V.; ZHOU, L. |
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Afiliação: |
JANICE REIS CIACCI ZANELLA, CNPSA. |
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Título: |
The one health high? level expert panel (OHHLEP). |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
One Health Outlook, v. 5, n. 18, 2023. |
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DOI: |
https://doi.org/10.1186/s42522-023-00085-2 |
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Idioma: |
Inglês |
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Palavras-Chave: |
Covid 19; Doenças infecciosas emergentes; Pandemia; Prevenção de doenças; Saúde coletiva; Saúde mundial. |
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Thesagro: |
Animal; Ecossistema; Saúde Pública; Zoonose. |
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Thesaurus Nal: |
Disease prevention; Ecosystems; Pandemic; Public health; World Health Organization; Zoonoses. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1159676/1/final10270.pdf
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Marc: |
LEADER 01600naa a2200601 a 4500
001 2159676
005 2023-12-29
008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1186/s42522-023-00085-2$2DOI
100 1 $aMETTENLEITER, T. C.
245 $aThe one health high? level expert panel (OHHLEP).$h[electronic resource]
260 $c2023
650 $aDisease prevention
650 $aEcosystems
650 $aPandemic
650 $aPublic health
650 $aWorld Health Organization
650 $aZoonoses
650 $aAnimal
650 $aEcossistema
650 $aSaúde Pública
650 $aZoonose
653 $aCovid 19
653 $aDoenças infecciosas emergentes
653 $aPandemia
653 $aPrevenção de doenças
653 $aSaúde coletiva
653 $aSaúde mundial
700 1 $aMARKOTTER, W.
700 1 $aCHARRON, D. F.
700 1 $aADISASMITO, W. B.
700 1 $aALMUHAIRI, S.
700 1 $aBEHRAVESH, C. B.
700 1 $aBILIVOGUI, P.
700 1 $aBUKACHI, S. A.
700 1 $aCASAS, N.
700 1 $aBECERRA, N. C.
700 1 $aCHAUDHARY, A.
700 1 $aZANELLA, J. R. C.
700 1 $aCUNNINGHAM, A. A.
700 1 $aDAR, O.
700 1 $aDEBNATH, N.
700 1 $aFARAG, E.
700 1 $aGAO, G. F.
700 1 $aHAYMAN, D. T. S.
700 1 $aKHAITSA, M.
700 1 $aKOOPMANS, M. P. G.
700 1 $aMACHALABA, C.
700 1 $aMACKENZIE, J. S.
700 1 $aMORAND, S.
700 1 $aSMOLENSKIY, V.
700 1 $aZHOU, L.
773 $tOne Health Outlook$gv. 5, n. 18, 2023.
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Registro original: |
Embrapa Suínos e Aves (CNPSA) |
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Classificação |
Cutter |
Registro |
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Registro Completo
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
10/01/2023 |
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Data da última atualização: |
10/01/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
BARTH, E.; RESENDE, J. T. V. de; MARIGUELE, K. H.; RESENDE, M. D. V. de; SILVA, A. L. B. R. da; RU, S. |
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Afiliação: |
ENEIDE BARTH, EMPRESA DE PESQUISA AGROPECUÁRIA E EXTENSÃO RURAL DE SANTA CATARINA; JULIANO TADEU VILELA DE RESENDE, UNIVERSIDADE ESTADUAL DE LONDRINA; KENY HENRIQUE MARIGUELE, EMPRESA DE PESQUISA AGROPECUÁRIA E EXTENSÃO RURAL DE SANTA CATARINA; MARCOS DEON VILELA DE RESENDE, CNPCa; ANDRÉ LUIZ BISCAIA RIBEIRO DA SILVA, AUBURN UNIVERSITY; SUSHAN RU, AUBURN UNIVERSITY. |
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Título: |
Multivariate analysis methods improve the selection of strawberry genotypes with low cold requirement. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Scientific Reports, v. 12, 11458, 2022. |
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Páginas: |
12 p. |
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DOI: |
https://doi.org/10.1038/s41598-022-15688-4 |
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Idioma: |
Inglês |
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Conteúdo: |
Methods of multivariate analysis is a powerful approach to assist the initial stages of crops genetic improvement, particularly, because it allows many traits to be evaluated simultaneously. In this study, heat-tolerant genotypes have been selected by analyzing phenotypic diversity, direct and indirect relationships among traits were identified, and four selection indices compared. Diversity was estimated using K-means clustering with the number of clusters determined by the Elbow method, and the relationship among traits was quantified by path analysis. Parametric and non-parametric indices were applied to selected genotypes using the magnitude of genotypic variance, heritability, genotypic coefficient of variance, and assigned economic weight as selection criteria. The variability among materials led to the formation of two non-overlapping clusters containing 40 and 154 genotypes. Strong to moderate correlations were found between traits with direct effect of the number of commercial fruit on the mass of commercial fruit. The Smith and Hazel index showed the greatest total gains for all criteria; however, concerning the biochemical traits, the Mulamba and Mock index showed the highest magnitudes of predicted gains. Overall, the K-means clustering, correlation analysis, and path analysis complement the use of selection indices, allowing for selection of genotypes with better balance among the assessed traits. |
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Thesaurus NAL: |
Genotype; Multivariate analysis; Plant selection guides; Strawberries. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1150840/1/Multivariate-analysis-methods.pdf
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Marc: |
LEADER 02202naa a2200253 a 4500
001 2150840
005 2023-01-10
008 2022 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1038/s41598-022-15688-4$2DOI
100 1 $aBARTH, E.
245 $aMultivariate analysis methods improve the selection of strawberry genotypes with low cold requirement.$h[electronic resource]
260 $c2022
300 $a12 p.
520 $aMethods of multivariate analysis is a powerful approach to assist the initial stages of crops genetic improvement, particularly, because it allows many traits to be evaluated simultaneously. In this study, heat-tolerant genotypes have been selected by analyzing phenotypic diversity, direct and indirect relationships among traits were identified, and four selection indices compared. Diversity was estimated using K-means clustering with the number of clusters determined by the Elbow method, and the relationship among traits was quantified by path analysis. Parametric and non-parametric indices were applied to selected genotypes using the magnitude of genotypic variance, heritability, genotypic coefficient of variance, and assigned economic weight as selection criteria. The variability among materials led to the formation of two non-overlapping clusters containing 40 and 154 genotypes. Strong to moderate correlations were found between traits with direct effect of the number of commercial fruit on the mass of commercial fruit. The Smith and Hazel index showed the greatest total gains for all criteria; however, concerning the biochemical traits, the Mulamba and Mock index showed the highest magnitudes of predicted gains. Overall, the K-means clustering, correlation analysis, and path analysis complement the use of selection indices, allowing for selection of genotypes with better balance among the assessed traits.
650 $aGenotype
650 $aMultivariate analysis
650 $aPlant selection guides
650 $aStrawberries
700 1 $aRESENDE, J. T. V. de
700 1 $aMARIGUELE, K. H.
700 1 $aRESENDE, M. D. V. de
700 1 $aSILVA, A. L. B. R. da
700 1 $aRU, S.
773 $tScientific Reports$gv. 12, 11458, 2022.
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Embrapa Café (CNPCa) |
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