Health-related outcomes of genetic polymorphism of bovine β-casein variants: A systematic review of randomised controlled trials

Autor: Davor Daniloski, Todor Vasiljevic, Noel A. McCarthy, Tom F. O'Callaghan, Nathan M.D. Cunha, Sinead McParland

Publikováno v: Trends in Food Science & Technology. 111:233-248

Background A number of randomised in vivo trials have to date investigated the health impacts of the genetic variants A1 and A2 of bovine β-casein. The primary difference between these two genetic variants is the mutation leading to an amino acid ex

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::276031cfa2e2315394351834bb71d57f
https://doi.org/10.1016/j.tifs.2021.02.073

Predicting the dry matter intake of grazing dairy cows using infrared reflectance spectroscopy analysis

Autor: Sinead McParland, Emer Kennedy, M. Williams, Tommy M. Boland, B. Lahart, Frank Buckley, N. Galvin, Brian C. McCarthy, T. Condon

Publikováno v: Journal of Dairy Science. 102:8907-8918

The objective of this study was to compare mid-infrared reflectance spectroscopy (MIRS) analysis of milk and near-infrared reflectance spectroscopy (NIRS) analysis of feces with regard to their ability to predict the dry matter intake (DMI) of lactat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b18267bdde135f5a74d82247205f65f9
https://doi.org/10.3168/jds.2019-16363

How herd best linear unbiased estimates affect the progress achievable from gains in additive and nonadditive genetic merit

Autor: Sinead McParland, M.M. Kelleher, Donagh P. Berry, F.L. Dunne, Siobhan W. Walsh

Publikováno v: Journal of Dairy Science. 102:5295-5304

peer-reviewed Sustainable dairy cow performance relies on coevolution in the development of breeding and management strategies. Tailoring breeding programs to herd performance metrics facilitates improved responses to breeding decisions. Although her

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::744713ca8202c5c4f7d0051d8a8f360b
https://doi.org/10.3168/jds.2018-16119

Predicting cow milk quality traits from routinely available milk spectra using statistical machine learning methods

Autor: Maria Frizzarin, A. Lynch, Thomas Brendan Murphy, Donagh P. Berry, Isobel Claire Gormley, Alessandro Casa, Sinead McParland

Publikováno v: Journal of dairy science. 104(7)

Numerous statistical machine learning methods suitable for application to highly correlated features, as those that exist for spectral data, could potentially improve prediction performance over the commonly used partial least squares approach. Milk

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f0e87e41985eca0f30ceed45956f929
https://pubmed.ncbi.nlm.nih.gov/33865578

Improving robustness and accuracy of predicted daily methane emissions of dairy cows using milk mid‐infrared spectra

Autor: Cécile Martin, Matthiew Bell, Eric Froidmont, Amélie Vanlierde, Hélène Soyeurt, Nicolas Gengler, Michael Kreuzer, Björn Kuhla, Sinead McParland, Frédéric Dehareng, Peter Lund

Publikováno v: Journal of the Science of Food and Agriculture
Journal of the Science of Food and Agriculture, Wiley, 2020, 101 (8), pp.3394-3403. ⟨10.1002/jsfa.10969⟩
Vanlierde, A, Dehareng, F, Gengler, N, Froidmont, E, McParland, S, Kreuzer, M, Bell, M J, Lund, P, Martin, C, Kuhla, B & Soyeurt, H 2021, ' Improving robustness and accuracy of predicted daily methane emissions of dairy cows using milk mid-infrared spectra ', Journal of the Science of Food and Agriculture, vol. 101, no. 8, pp. 3394-3403 . https://doi.org/10.1002/jsfa.10969

International audience; BACKGROUND A robust proxy for estimating methane (CH4) emissions of individual dairy cows would be valuable especially for selective breeding. This study aimed to improve the robustness and accuracy of prediction models that e

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a01ce460f14d67f0d58ad2ec98055e99
https://hal.inrae.fr/hal-03104053