Impact of dry-off management in robotic milking systems on milking behavior, milk yield, and somatic cell count.

dc.contributor.authorFrance, A.E.
dc.contributor.authorDufour, S.
dc.contributor.authorKelton, D.F.
dc.contributor.authorBarkema, H.W.
dc.contributor.authorKurban, D.
dc.contributor.authorDeVries, T.J.
dc.date.accessioned2020-09-21T19:56:42Z
dc.date.available2020-09-21T19:56:42Z
dc.date.copyright20-Jun
dc.date.created20-Jun
dc.date.issued20-Jun
dc.degree.departmentDairy at Guelphen
dc.degree.departmentDepartment of Animal Biosciencesen
dc.descriptionOral Presentation at the 2020 ADSA Annual Meeting (online).en
dc.description.abstractThe objective of this study was to determine the effect of dry-off management of cows milked in automatic milking systems (AMS) on milk yield, milking behavior, and SCC. In 5 commercial dairy farms in Quebec, Canada, 341 cows were assigned to 1 of 4 treatments for 2-wk before dry off: 1) reduced milking (RM: 2x/d or if expected to yield 17 kg/milking; n = 95), 2) reduced feeding (RF: 0.75 kg AMS pellet/d for wk 1, 0.5 kg AMS pellet/d for wk 2; n = 98), 3) reduced both feeding and milking (RB: n = 73), and 4) a control (C: n = 75) group. Non-reduced milking allowed up to 6 milkings/d or as often as a cow was expected to yield 6 kg/milking. Non-reduced feeding allocated up to 2 kg/d of AMS pellet. From the AMS software, feed and milking behavior data were collected, as well as milk yield and SCC. Data on milk yield, milking frequency, and SCC were analyzed using mixed-effect linear regression models. The RB group had the lowest milk yield 3 d before dry-off, and was different from the C group (19.3 vs. 22.4 kg/d; SE = 1.08; P = 0.01). The RB group also differed from the C group in their reduction in total milk yield over the 2-wk treatment period (−4.9 vs. −1.8 kg; SE = 0.91; P = 0.02), indicating that this was the most efficient way to decrease milk yield before dry-off. Milking frequency was greater (SE = 0.09; P < 0.001) in the RF (2.25 ×/d) and C (2.65 ×/d) groups compared with the RM (1.60 ×/d) and RB (1.51 ×/d) groups. There was a difference (P < 0.001) in milking frequency between the RF and C groups, indicating that reducing feeding without altering milking frequency before dry-off may also decrease the motivation for cows to visit the AMS. There were no differences between groups (P > 0.24) for milking frequency or yield in the next lactation. SCC was not different (P > 0.35) between groups in the week before dry-off nor in the first month after calving. Overall, these data suggest that reducing both milking frequency and feed quantity in the AMS is the most efficient method to decrease milk yield before dry-off, without negatively influencing milking frequency or yield in the next lactation, as well as without affecting SCC.en_US
dc.description.sponsorshipMastitis Network, Dairy Research Cluster 3, Lactanet, Dairy Farmers of Ontario, Canadian Agricultural Partnership, Dairy Farmers of Canada, Novalait, Canadaen_US
dc.identifier.citationA. France, et al. Impact of dry-off management in robotic milking systems on milking behavior, milk yield, and somatic cell count. J. Dairy Sci. 103 (Suppl. 1). p. 151, 390, 2020.
dc.identifier.urihttps://hdl.handle.net/10214/21312
dc.language.isoenen_US
dc.publisher2020 American Dairy Science Association® Annual Meetingen_US
dc.relation.ispartofseriesDaG_ADSA2020;22
dc.rightsThis material is for personal viewing only. The corresponding author's explicit authorization is mandatory for any other use, unless another statement attached to a specific document clearly states a different level of permission.
dc.rights.licenseAll items in the Atrium are protected by copyright with all rights reserved unless otherwise indicated.
dc.subjectdry-offen_US
dc.subjectrobotic milkingen_US
dc.subjectudder healthen_US
dc.titleImpact of dry-off management in robotic milking systems on milking behavior, milk yield, and somatic cell count.en_US
dc.typePresentationen
dc.typeVideoen

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
82241_ArianeFrance.mp4
Size:
22.72 MB
Format:
Unknown data format
Description:
A.E. France Oral Presentation ADSA 2020

Collections