Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Beatriz C D Cuyabano"'
Autor:
Aurélie Vinet, Sophie Mattalia, Roxane Vallée, Christine Bertrand, Anne Barbat, Julie Promp, Beatriz C. D. Cuyabano, Didier Boichard
Publikováno v:
Genetics Selection Evolution, Vol 56, Iss 1, Pp 1-15 (2024)
Abstract Background In the current context of climate change, livestock production faces many challenges to improve the sustainability of systems. Dairy farming, in particular, must find ways to select animals that will be able to achieve sufficient
Externí odkaz:
https://doaj.org/article/1a00e9ff629c485eafa2e30f1c3c28a1
Publikováno v:
Genetics Selection Evolution, Vol 56, Iss 1, Pp 1-13 (2024)
Abstract Background Genetic merit, or breeding values as referred to in livestock and crop breeding programs, is one of the keys to the successful selection of animals in commercial farming systems. The developments in statistical methods during the
Externí odkaz:
https://doaj.org/article/ec1f6251d5304a51a51a5c9650d51522
Autor:
Aurélie Vinet, Sophie Mattalia, Roxane Vallée, Christine Bertrand, Beatriz C. D. Cuyabano, Didier Boichard
Publikováno v:
Genetics Selection Evolution, Vol 55, Iss 1, Pp 1-17 (2023)
Abstract Background Heat stress negatively influences cattle welfare, health and productivity. To cope with the forecasted increases in temperature and heat waves frequency, identifying high-producing animals that are tolerant to heat is of capital i
Externí odkaz:
https://doaj.org/article/d9baaa2c1838420db64c3d77c1a3ec91
Autor:
Miguel A. Raffo, Beatriz C. D. Cuyabano, Renaud Rincent, Pernille Sarup, Laurence Moreau, Tristan Mary-Huard, Just Jensen
Publikováno v:
Frontiers in Plant Science, Vol 13 (2023)
Individuals within a common environment experience variations due to unique and non-identifiable micro-environmental factors. Genetic sensitivity to micro-environmental variation (i.e. micro-environmental sensitivity) can be identified in residuals,
Externí odkaz:
https://doaj.org/article/c60a1fc60aa7490092618c1ec0e86540
Publikováno v:
Genetics Selection Evolution, Vol 50, Iss 1, Pp 1-21 (2018)
Abstract Background Genomic models that link phenotypes to dense genotype information are increasingly being used for infering variance parameters in genetics studies. The variance parameters of these models can be inferred using restricted maximum l
Externí odkaz:
https://doaj.org/article/252e2ce3eb754ff18afc325fdc9c80f6
Publikováno v:
Animals
Volume 9
Issue 9
Animals : an Open Access Journal from MDPI
Animals, Vol 9, Iss 9, p 672 (2019)
Volume 9
Issue 9
Animals : an Open Access Journal from MDPI
Animals, Vol 9, Iss 9, p 672 (2019)
Simple Summary Commercial genotyping has become accessible at a relatively low cost and nowadays it is widely used by breeders to predict production and economic traits. Many studies explored the benefits of using DNA information in breeding programs
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c5e74fc5d322fd3a65ea00b1f4c8b3b
Publikováno v:
Genetics, Selection, Evolution : GSE
Genetics Selection Evolution
Genetics Selection Evolution, BioMed Central, 2018, 50 (1), pp.41. ⟨10.1186/s12711-018-0411-0⟩
Cuyabano, B C D, Sørensen, A C & Sørensen, P 2018, ' Understanding the potential bias of variance components estimators when using genomic models ', Genetics Selection Evolution, vol. 50, no. 1, 41 . https://doi.org/10.1186/s12711-018-0411-0
Genetics Selection Evolution, Vol 50, Iss 1, Pp 1-21 (2018)
Genetics Selection Evolution
Genetics Selection Evolution, BioMed Central, 2018, 50 (1), pp.41. ⟨10.1186/s12711-018-0411-0⟩
Cuyabano, B C D, Sørensen, A C & Sørensen, P 2018, ' Understanding the potential bias of variance components estimators when using genomic models ', Genetics Selection Evolution, vol. 50, no. 1, 41 . https://doi.org/10.1186/s12711-018-0411-0
Genetics Selection Evolution, Vol 50, Iss 1, Pp 1-21 (2018)
Background Genomic models that link phenotypes to dense genotype information are increasingly being used for infering variance parameters in genetics studies. The variance parameters of these models can be inferred using restricted maximum likelihood
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f28ac17bfd66dc96f4009a45af286aa
http://europepmc.org/articles/PMC6080367
http://europepmc.org/articles/PMC6080367
Publikováno v:
Castro Dias Cuyabano, B, Su, G, Rosa, G J M, Lund, M S & Gianola, D 2015, ' Bootstrap study of genome-enabled prediction reliabilities using haplotype blocks across Nordic Red cattle breeds ', Journal of Dairy Science, vol. 98, no. 10, pp. 7351-63 . https://doi.org/10.3168/jds.2015-9360
This study compared the accuracy of genome-enabled prediction models using individual single nucleotide polymorphisms (SNP) or haplotype blocks as covariates when using either a single breed or a combined population of Nordic Red cattle. The main obj
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c964c19b3418511a126e9f4002d076cb
https://pure.au.dk/portal/da/publications/bootstrap-study-of-genomeenabled-prediction-reliabilities-using-haplotype-blocks-across-nordic-red-cattle-breeds(46e46f67-aad6-4491-b7d4-8bc4b9fbc7e2).html
https://pure.au.dk/portal/da/publications/bootstrap-study-of-genomeenabled-prediction-reliabilities-using-haplotype-blocks-across-nordic-red-cattle-breeds(46e46f67-aad6-4491-b7d4-8bc4b9fbc7e2).html
Publikováno v:
Animals (2076-2615). Feb2023, Vol. 13 Issue 4, p659. 61p.
Autor:
Aurélie Vinet, Sophie Mattalia, Roxane Vallée, Christine Bertrand, Beatriz C. D. Cuyabano, Didier Boichard
Publikováno v:
Genetics Selection Evolution
Genetics Selection Evolution, 2023, 55 (1), pp.4. ⟨10.1186/s12711-023-00779-1⟩
Genetics Selection Evolution, 2023, 55 (1), pp.4. ⟨10.1186/s12711-023-00779-1⟩
Background Heat stress negatively influences cattle welfare, health and productivity. To cope with the forecasted increases in temperature and heat waves frequency, identifying high-producing animals that are tolerant to heat is of capital importance
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::46f658b9a7e8d5f6c72515f3c7160550