Hostname: page-component-586b7cd67f-rcrh6 Total loading time: 0 Render date: 2024-11-22T13:03:10.906Z Has data issue: false hasContentIssue false
  • English
  • Français

Response profiles of dairy cows to a single 24-h milking interval in relation with milk proteolysis, udder expansion and immune traits

Published online by Cambridge University Press:  18 October 2018

C. Charton Open the ORCID record for C. Charton [Opens in a new window] ,
H. Larroque ,
S. Pochet ,
P. Germon ,
G. Lequeux  and
J. Guinard-Flament
C. Charton
Affiliation:
PEGASE, Agrocampus-Ouest, INRA, F-35590 Saint-Gilles Cedex, France GenPhySE, Université de Toulouse, INRA, INPT, ENVT, Chemin de Borde Rouge, F-31326 Castanet-Tolosan Cedex, France
H. Larroque
Affiliation:
GenPhySE, Université de Toulouse, INRA, INPT, ENVT, Chemin de Borde Rouge, F-31326 Castanet-Tolosan Cedex, France
S. Pochet
Affiliation:
URTAL, INRA UR342, F-39801Poligny, France
P. Germon
Affiliation:
ISP, INRA, Université de Tours, UMR 1282, F-37380 Nouzilly, France
G. Lequeux
Affiliation:
LABOCEA, 10 rue Claude Bourgelat, F-36306 Fougères Cedex, France
J. Guinard-Flament*
Affiliation:
PEGASE, Agrocampus-Ouest, INRA, F-35590 Saint-Gilles Cedex, France
*
†E-mail: [email protected]
Get access

Abstract

An extended milking interval of 24 h (24-h milking interval (24h-MI)) constitutes the acute phase of cow adaptation to once-daily milking (ODM). A recent trial including 724 24h-MI challenges demonstrated that milk yield responses to this acute phase of ODM are highly variable (from+22% to −52% of milk yield when switching to the 24h-MI, mean=−25.3%) and that factors such as stage of lactation parity and milk yield level influenced cows’ responses but did not account for all individual variability. Additional traits related to physiological, immune and behavioural adaptation were measured on a subset (96 observations) of this data set. This study aimed to determine (1) the relationship of these traits with cows’ milk yield responses, (2) their ability – combined with previously identified traits – to help predict milk yield responses to 24h-MI (adaptive profiles). The 24h-MI challenge consisted of three successive periods: one control week of twice-daily milking (cTDM), one single day of 24h-MI and then 13 days of TDM (pTDM). Milk yield responses to the 24h-MI (corrected for effects of stage of lactation, parity, milk yield level and milk yield) were related to physiological traits measured during cTDM (milk flow rate, presence or absence of interleukin-8) and to their changes during the 24h-MI (absolute increase in milk flow rate and relative udder distension). Analysis of associations between milk yield responses, stage of lactation, parity, milk yield level, proteolysis, udder expansion and immune traits found three adaptive cow profile clusters. Cows in cluster 1 had a less compliant udder than cows in cluster 2, and they lost more milk during the 24h-MI than cluster-2 and cluster-3 cows. After resuming twice daily-milking (TDM), cluster-2 cows fully recovered the milk they had lost during the 24h-MI. On the opposite, cluster-3 cows did not recover the milk they lost, likely due to udder inflammation during cTDM, as suggested by elevated concentrations of interleukin-8 in their milk. These results combining new traits with stage of lactation, parity and milk yield level constitute a first step towards predicting individual cow responses to a 24h-MI.

Keywords

once-daily milkingacute phaseadaptationindividual responsesphysiological traits
Type
Research Article
Information
animal , Volume 13 , Issue 6 , June 2019 , pp. 1224 - 1233
Copyright
© The Animal Consortium 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Albaaj, A, Marnet, PG, Hurtaud, C and Guinard-Flament, J 2018. Adaptation of dairy cows to increasing degrees of incomplete milk removal during a single milking interval. Journal of Dairy Science 101, 8492–8504.Google Scholar
Brandsma, S 1978. The relation between milking, residual milk and milk yield. Annual Meeting National Mastitis Council, Inc. National Mastitis Council, Inc. Retrieved on 15 December 2017 from http://agris.fao.org/agris-search/search.do?recordID=US19810679375.Google Scholar
Bruckmaier, RM and Blum, JW 1998. Oxytocin release and milk removal in ruminants. Journal of Dairy Science 81, 939–949.Google Scholar
Bugaud, C, Buchin, S, Coulon, JB, Hauwuy, A and Dupont, D 2001. Influence of the nature of alpine pastures on plasmin activity, fatty acid and volatile compound composition of milk. Lait 81, 401–414.Google Scholar
Charton, C, Guinard-Flament, J, Lefebvre, R, Barbey, S, Gallard, Y, Boichard, D and Larroque, H 2018. Genetic parameters of milk production traits in response to a short once-daily milking period in crossbred Holstein × Normande dairy cows. Journal of Dairy Science 101, 2235–2247.Google Scholar
Charton, C, Larroque, H, Robert-Granié, C, Pomiès, D, Leclerc, H, Friggens, NC and Guinard-Flament, J 2016. Individual responses of dairy cows to a 24-hour milking interval. Journal of Dairy Science 99, 3103–3113.Google Scholar
Chen, R, Yang, Z, Ji, D, Mao, Y, Chen, Y, Li, Y, Wu, H, Wang, X and Chang, L 2011. Polymorphisms of the IL8 gene correlate with milking traits, SCS and mRNA level in Chinese Holstein. Molecular Biology Reports 38, 4083–4088.Google Scholar
Claesson, O, Hansson, A, Gustafsson, N and Brannang, E 1959. Once-daily milking compared with twice daily milking. Acta Agriculturae Scandinavica 9, 38–59.Google Scholar
Datta, N and Deeth, HC 2003. Diagnosing the cause of proteolysis in UHT milk. LWT – Food Science and Technology 36, 173–182.Google Scholar
Davis, SR, Farr, VC and Stelwagen, K 1999. Regulation of yield loss and milk composition during once-daily milking: a review. Livestock Production Science 59, 77–94.Google Scholar
Davis, SR, Turner, SA, Obolonkin, V, Tiplady, K, Spelman, RJ and Phyn, CVC 2015. Lactation traits associated with short- and long-term once-daily milking performance in New Zealand crossbred dairy cattle. Journal of Dairy Science 98, 6094–6107.Google Scholar
Ferris, CP, Frost, JP, Mayne, CS, McCoy, MA and Kilpatrick, DJ 2008. A comparison of the direct and residual response of dairy cows to once or twice-daily milking, in late lactation. Livestock Science 114, 305–314.Google Scholar
Gleeson, DE, O’Brien, B, Boyle, L and Earley, B 2007. Effect of milking frequency and nutritional level on aspects of the health and welfare of dairy cows. Animal 1, 125–132.Google Scholar
Gorewit, RC, Wachs, EA, Sagi, R and Merrill, WG 1983. Current concepts on the role of oxytocin in milk ejection. Journal of Dairy Science 66, 2236–2250.Google Scholar
Guinard-Flament, J, Gallard, Y and Larroque, H 2011. Lactose in blood plasma and the ability of dairy cows to tolerate once-daily milking in terms of milk loss and milk recovery. Journal of Dairy Science 94, 3446–3454.Google Scholar
Hayhoe, FGJ and Flemans, RJ 1970. Atlas en couleurs de cytologie hématologique, 2nd edition. Flammarion, Paris, France.Google Scholar
Holmes, C, Kamote, H, Mackenzie, D and Morel, P 1996. Effects of a decrease in milk yield, caused by once-daily milking or by restricted feeding, on the somatic cell count in milk from cows with or without subclinical mastitis. Australian Journal of Dairy Technology 51, 8–11.Google Scholar
IDF 29-1 ISO 17997-1 2004. Milk – determination of casein – nitrogen content – part 1: indirect method. International Dairy Federation, Brussels, Belgium.Google Scholar
Innocente, N, Biasutti, M and Blecker, C 2011. HPLC profile and dynamic surface properties of the proteose–peptone fraction from bovine milk and from whey protein concentrate. International Dairy Journal 21, 222–228.Google Scholar
INRA 2010. Alimentation des bovins, ovins et caprins. Besoins des animaux – valeur des aliments. Tables INRA 2007, mise à jour 2010. Quae, Versailles, France.Google Scholar
Lê, S, Josse, J and Husson, F 2008. FactoMineR: an R package for multivariate analysis. Journal of Statistical Software 25, 1–18.Google Scholar
Le, TX, Datta, N and Deeth, HC 2006. A sensitive HPLC method for measuring bacterial proteolysis and proteinase activity in UHT milk. Food Research International 39, 823–830.Google Scholar
Lenth, R 2014. lsmeans: least-squares means. R package version 2.12. Retrieved on 14 April 2015 from http://CRAN.R-project.org/package=lsmeans.Google Scholar
Mayer, H, Bruckmaier, R and Schams, D 1991. Lactational changes in oxytocin release, intramammary pressure and milking characteristics in dairy cows. Journal of Dairy Research 58, 159–169.Google Scholar
Miller, RH, Fulton, LA, Erez, B, Williams, WF and Pearson, RE 1995. Variation in distances among teats of holstein cows: implications for automated milking1,2. Journal of Dairy Science 78, 1456–1462.Google Scholar
Pfeilsticker, HU, Bruckmaier, RM and Blum, JW 1995. Interruption of machine milking in dairy cows: effect on intramammary pressure and milking characteristics. Journal of Dairy Research 65, 559–566.10.1017/S0022029900031289Google Scholar
Rainard, P, Riollet, C, Berthon, P, Cunha, P, Fromageau, A, Rossignol, C and Gilbert, FB 2008. The chemokine CXCL3 is responsible for the constitutive chemotactic activity of bovine milk for neutrophils. Molecular Immunology 45, 4020–4027.Google Scholar
Rathore, AK 1976. Sources of variation in the milk flow rate and its relationships with milk yield, milk composition, age and stage of lactation in dairy cows. British Veterinary Journal 132, 90–94.Google Scholar
R Core Team 2014. The R foundation for statistical computing: a language and environment for statistical computing, Version 3.0.2. Vienna, Austria.Google Scholar
Rollema, H, Visser, S and Poll, J 1983. Spectrophotometric assay of plasmin and plasminogen in bovine-milk. Milchwissenschaft 38, 214–217.Google Scholar
Schaar, J 1985. Plasmin activity and proteose-peptone content of individual milks. Journal of Dairy Research 52, 369–378.Google Scholar
Stelwagen, K, Davis, SR, Farr, VC, Prosser, CG and Sherlock, RA 1994. Mammary epithelial cell tight junction integrity and mammary blood flow during an extended milking interval in goats. Journal of Dairy Science 77, 426–432.Google Scholar
Stelwagen, K, Farr, VC, McFadden, HA, Prosser, CG and Davis, SR 1997. Time course of milk accumulation-induced opening of mammary tight junctions, and blood clearance of milk components. American Physiology 273, 379–386.Google Scholar
Stelwagen, K, Phyn, CVC, Davis, SR, Guinard-Flament, J, Pomiès, D, Roche, JR and Kay, JK 2013. Invited review: reduced milking frequency: milk production and management implications. Journal of Dairy Science 96, 3401–3413.Google Scholar
Stelwagen, K, Politis, I, White, JH, Zavizion, B, Prosser, CG, Davis, SR and Farr, VC 1994. Effect of milking frequency and somatotropin on the activity of plasminogen activator, plasminogen, and plasmin in bovine milk. Journal of Dairy Science 77, 3577–3583.Google Scholar
Tančin, V, Ipema, B, Hogewerf, P and Mačuhová, J 2006. Sources of variation in milk flow characteristics at udder and quarter levels. Journal of Dairy Science 89, 978–988.Google Scholar
van Asselt, AJ, Sweere, APJ, Rollema, HS and de Jong, P 2008. Extreme high-temperature treatment of milk with respect to plasmin inactivation. International Dairy Journal 18, 531–538.Google Scholar
Supplementary material: File

Charton et al. supplementary material

Charton et al. supplementary material 1

Download Charton et al. supplementary material(File)
File 26.5 KB