Use of rumination time in health risk assessment of prepartum dairy cows

Autor: Santos, M.G.S., Antonacci, N., Van Dorp, C., Mion, B., Tulpan, D., Ribeiro, E.S. ^*

Publikováno v: In Journal of Dairy Science October 2024 107(10):8343-8365

Comparison of imputation methods for missing production data of dairy cattle

Autor: You, J., Ellis, J.L., Adams, S., Sahar, M., Jacobs, M., Tulpan, D.

Publikováno v: In animal December 2023 17 Supplement 5

Genetic evaluation of heat tolerance in Holsteins using test-day production records and NASA POWER weather data

Autor: Rockett, Paige L. ^*, Campos, I.L., Baes, C.F., Tulpan, D., Miglior, F., Schenkel, F.S. ^*

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Machine learning classification of breeding protocol descriptions from Canadian Holsteins

Autor: Alcantara, L M, Schenkel, F S, Lynch, C, Oliveira Junior, G A, Baes, C F, Tulpan, D

Publikováno v: Alcantara, L M; Schenkel, F S; Lynch, C; Oliveira Junior, G A; Baes, C F; Tulpan, D (2022). Machine learning classification of breeding protocol descriptions from Canadian Holsteins. Journal of dairy science, 105(10), pp. 8177-8188. American Dairy Science Association 10.3168/jds.2021-21663

Dairy farmers are motivated to ensure cows become pregnant in an optimal and timely manner. Although timed artificial insemination (TAI) is a successful management tool in dairy cattle, it masks an animal's innate fertility performance, likely reduci

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6746baffb5ec3a190c73d19dc361e08f
https://boris.unibe.ch/172666/1/1-s2.0-S0022030222004866-main.pdf

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