Genetic parameters for methane emission traits in Australian dairy cows.


Journal

Journal of dairy science
ISSN: 1525-3198
Titre abrégé: J Dairy Sci
Pays: United States
ID NLM: 2985126R

Informations de publication

Date de publication:
Jan 2021
Historique:
received: 19 03 2020
accepted: 07 08 2020
pubmed: 3 11 2020
medline: 12 2 2021
entrez: 2 11 2020
Statut: ppublish

Résumé

Methane is a greenhouse gas of high interest to the dairy industry, with 57% of Australia's dairy emissions attributed to enteric methane. Enteric methane emissions also constitute a loss of approximately 6.5% of ingested energy. Genetic selection offers a unique mitigation strategy to decrease the methane emissions of dairy cattle, while simultaneously improving their energy efficiency. Breeding objectives should focus on improving the overall sustainability of dairy cattle by reducing methane emissions without negatively affecting important economic traits. Common definitions for methane production, methane yield, and methane intensity are widely accepted, but there is not yet consensus for the most appropriate method to calculate residual methane production, as the different methods have not been compared. In this study, we examined 9 definitions of residual methane production. Records of individual cow methane, dry matter intake (DMI), and energy corrected milk (ECM) were obtained from 379 animals and measured over a 5-d period from 12 batches across 5 yr using the SF

Identifiants

pubmed: 33131823
pii: S0022-0302(20)30865-1
doi: 10.3168/jds.2020-18565
pii:
doi:

Substances chimiques

Greenhouse Gases 0
Methane OP0UW79H66

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

539-549

Informations de copyright

The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Auteurs

C M Richardson (CM)

Agriculture Victoria Research, AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia; School of Applied Systems Biology, La Trobe University, Bundoora, Victoria 3083, Australia. Electronic address: caeli.richardson@agriculture.vic.gov.au.

T T T Nguyen (TTT)

Agriculture Victoria Research, AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia.

M Abdelsayed (M)

DataGene Ltd., AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia.

P J Moate (PJ)

Agriculture Victoria Research, Ellinbank, Victoria 3820, Australia; Centre for Agricultural Innovation, School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Parkville, Victoria 3052, Australia.

S R O Williams (SRO)

Agriculture Victoria Research, Ellinbank, Victoria 3820, Australia.

T C S Chud (TCS)

Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada N1G 2W1.

F S Schenkel (FS)

Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada N1G 2W1.

M E Goddard (ME)

Centre for Agricultural Innovation, School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Parkville, Victoria 3052, Australia.

I van den Berg (I)

Agriculture Victoria Research, AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia.

B G Cocks (BG)

Agriculture Victoria Research, AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia; School of Applied Systems Biology, La Trobe University, Bundoora, Victoria 3083, Australia.

L C Marett (LC)

Agriculture Victoria Research, Ellinbank, Victoria 3820, Australia.

W J Wales (WJ)

Agriculture Victoria Research, Ellinbank, Victoria 3820, Australia.

J E Pryce (JE)

Agriculture Victoria Research, AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia; School of Applied Systems Biology, La Trobe University, Bundoora, Victoria 3083, Australia.

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Classifications MeSH