Farm-level nutritional factors associated with milk production and milking behavior on Canadian farms with automated milking systems.

formulation nutrition pellet robotic milking

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:
02 Feb 2024
Historique:
received: 25 10 2023
accepted: 01 01 2024
medline: 5 2 2024
pubmed: 5 2 2024
entrez: 4 2 2024
Statut: aheadofprint

Résumé

The objective of this study was to describe nutritional strategies utilized on Canadian dairy farms with automated milking systems (AMS), both at the feed bunk and the concentrate offered at the AMS, as well as to determine what dietary components and nutrients, as formulated, were associated with milk production and milking behaviors on those farms. Formulated diets, including ingredients and nutrient content, and AMS data were collected from April 1, 2019, until September 30, 2020, on 160 AMS farms (Eastern Canada [East] = 8, Ontario [ON] = 76, Quebec [QC] = 22, and Western Canada [West] = 54). Both partial mixed ration (PMR) and AMS concentrate samples were collected from May 1 to September 30, 2019, on 169 farms (East = 12, ON = 63, QC = 42, West = 52). AMS milking data were collected for 154 herds. For each farm (n = 160), milk recording data were collected and summarized by farm to calculate average milk yield and components. Multivariable regression models were used to associate herd-level formulated nutrient composition and feeding management practices with milk production and milking behavior. Milk yield (37.0 ± 0.3 kg/d) was positively associated with the PMR ether extract (EE) concentration (PMR % EE; +0.97 kg/d per percentage point (p.p.) increase) and with farms that fed barley silage as their major forage source on farm (n = 16; +2.18 kg/d) compared with haylage (n = 42), while farms that fed corn silage (n = 96; +1.23 kg/d) tended to produce more milk than farms that fed haylage. Greater milk fat content (4.09 ± 0.28%) was associated with greater PMR-to-AMS concentrate ratio (+0.02 p.p. per unit increase) and total diet net energy for lactation (+0.046 p.p. per 0.1 Mcal/kg increase), but lesser % non-fiber carbohydrates (NFC) of the PMR (-0.016 p.p. per p.p. increase of % NFC). Milk protein content (3.38 ± 0.14%) was positively associated with forage % of the PMR (+0.003 p.p. per p.p. increase of % forage) and total diet % starch (+0.009 p.p. per p.p. increase of % starch), but negatively associated with farms feeding corn silage (-0.1 p.p. compared with haylage) as their major forage. Greater milking frequency (2.77 ± 0.40 milkings/d) was observed on farms with free-flow cow traffic systems (+0.62 milkings/d) and positively associated with feed push-up frequency (+0.013 milkings/d per additional feed push-up), while being negatively associated with PMR NFC content and % forage of the total ration (-0.017 milkings/d per p.p. increase of % forage). Lastly, greater milking refusal frequency (1.49 ± 0.82 refusals/d) was observed on farms with free-flow cow traffic systems (+0.84 refusals/d) and farms feeding barley silage (+0.58 refusals/d) than guided flow and farms feeding either corn silage or haylage, respectively. These data give insight into the ingredients, nutrient formulations and type of diets fed on AMS dairy farms across Canada and the association of those factors with milk production and milking behaviors.

Identifiants

pubmed: 38310965
pii: S0022-0302(24)00065-1
doi: 10.3168/jds.2023-24355
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

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 license (http://creativecommons.org/licenses/by/4.0/).

Auteurs

B J Van Soest (BJ)

Department of Animal Bioscience, University of Guelph, Guelph ON, Canada, N1G1Y2.

R D Matson (RD)

Department of Animal Bioscience, University of Guelph, Guelph ON, Canada, N1G1Y2.

D E Santschi (DE)

Lactanet, Sainte-Anne-de-Bellevue, QC, Canada, H9X3R4.

T F Duffield (TF)

Department of Population Medicine, University of Guelph, Guelph ON, Canada, N1G1Y2.

M A Steele (MA)

Department of Animal Bioscience, University of Guelph, Guelph ON, Canada, N1G1Y2.

K Orsel (K)

Faculty of Veterinary Medicine, University of Calgary, Calgary, AB, Canada, T2N4Z6.

E A Pajor (EA)

Faculty of Veterinary Medicine, University of Calgary, Calgary, AB, Canada, T2N4Z6.

G B Penner (GB)

Department of Animal and Poultry Science, University of Saskatchewan, Saskatoon, SK, Canada, S7N5A8.

T Mutsvangwa (T)

Department of Animal and Poultry Science, University of Saskatchewan, Saskatoon, SK, Canada, S7N5A8.

T J DeVries (TJ)

Department of Animal Bioscience, University of Guelph, Guelph ON, Canada, N1G1Y2. Electronic address: tdevries@uoguelph.ca.

Classifications MeSH