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Review: Metabolic challenges in lactating dairy cows and their assessment via established and novel indicators in milk

  • J. J. Gross (a1) and R. M. Bruckmaier (a1)

Abstract

The increasing lactational performance of dairy cows over the last few decades is closely related to higher nutritional requirements. The decrease in dry matter intake during the peripartal period results in a considerable mobilisation of body tissues (mainly fat reserves and muscle mass) to compensate for the prevailing lack of energy and nutrients. Despite the activation of adaptive mechanisms to mobilise nutrients from body tissues for maintenance and milk production, the increased metabolic load is still a risk factor for animal health. The prevalence of production diseases, particularly subclinical ketosis is high in the early lactation period. Increased β-hydroxybutyrate (BHB) concentrations further depress gluconeogenesis, feed intake and the immune system. Despite a variety of adaptation responses to nutrient and energy deficit that exists among dairy cows, an early and non-invasive detection of developing metabolic disorders in milk samples would be useful. The frequent and regular milking process of dairy cows creates the ability to obtain samples at any stage of lactation. Routine identification of biomarkers accurately characterising the physiological status of an animal is crucial for decisive strategies. The present overview recapitulates established markers measured in milk that are associated with metabolic health of dairy cows. Specifically, measurements of milk fat, protein, lactose and urea concentrations are evaluated. Changes in the ratio of milk fat to protein may indicate an increased risk for rumen acidosis and ketosis. The costly determination of individual fatty acids in milk creates barriers for grouping of fatty acids into saturated, mono- and polyunsaturated fatty acids. Novel approaches include the potential of mid-IR (MIR) based predictions of BHB and acetone in milk, although the latter are not directly measured, but only estimated via indirect associations of concomitantly altered milk composition during (sub)clinical ketosis. Although MIR-based ketone body concentrations in milk are not suitable to monitor the metabolic status of the individual cow, they provide an estimate of the overall herd or specific groups of animals earlier in a particular stage of lactation. Management decisions can be made earlier and animal health status improved by adjusting diet composition.

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References

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Bobe, G, Young, JW and Beitz, DC 2004. Invited review: Pathology, etiology, prevention and treatment of fatty liver in dairy cows. Journal of Dairy Science 87, 31053124.
Bradford, BJ, Yuan, K, Farney, JK, Mamedova, LK and Carpenter, AJ 2015. Invited review: Inflammation during the transition to lactation: new adventures with an old flame. Journal of Dairy Science 98, 66316650.
Broderick, GA and Clayton, MK 1997. A statistical evaluation of animal and nutritional factors influencing concentrations of milk urea nitrogen. Journal of Dairy Science 80, 29642971.
Bruckmaier, RM and Gross, JJ 2017. Lactational challenges in transition dairy cows. Animal Production Science 57, 14711481.
Brunner, N, Groeger, S, Canelas Raposo, J, Bruckmaier, RM and Gross, JJ 2019. Prevalence of subclinical ketosis and production diseases in dairy cows in Central and South America, Africa, Asia, Australia and New Zealand, and Eastern Europe. Translational Animal Science 3, 1927.
Chapinal, N, Carson, M, Duffield, TF, Capel, M, Godden, S, Overton, M, Santos, JE and LeBlanc, SJ 2011. The association of serum metabolites with clinical disease during the transition period. Journal of Dairy Science 94, 48974903.
De Marchi, M, Bittante, G, Dal Zotto, R, Dalvit, C and Cassandro, M 2008. Effect of Holstein Friesian and Brown Swiss breeds on quality of milk and cheese. Journal of Dairy Science 91, 40924102.
De Marchi, M, Toffanin, V, Cassandro, M and Penasa, M 2014. Invited review: Mid-infrared spectroscopy as phenotyping tool for milk traits. Journal of Dairy Science 97, 11711186.
Denis-Robichaud, J, Dubuc, J, Lefebvre, D and DesCôteaux, L 2014. Accuracy of milk ketone bodies from flow-injection analysis for the diagnosis of hyperketonemia in dairy cows. Journal of Dairy Science 97, 33643370.
de Roos, AP, van den Bijgaart, HJ, Hørlyk, J and de Jong, G 2007. Screening for subclinical ketosis in dairy cattle by Fourier transform infrared spectrometry. Journal of Dairy Science 90, 17611766.
Duffield, TF, Lissemore, KD, McBride, BW and Leslie, KE 2009. Impact of hyperketonemia in early lactation dairy cows on health and production. Journal of Dairy Science 92, 571580.
Geishauser, T, Leslie, K, Tenhag, J and Bashiri, A 2000. Evaluation of eight cow-side ketone tests in milk for detection of subclinical ketosis in dairy cows. Journal of Dairy Science 83, 296299.
Gottardo, P, Penasa, M, Righi, F, Lopez-Villalobos, N, Cassandro, M and De Marchi, M 2017. Fatty acid composition of milk from Holstein-Friesian, Brown Swiss, Simmental and Alpine Grey cows predicted by mid-infrared spectroscopy. Italian Journal of Animal Science 16, 380389.
Goulden, JDS 1964. Analysis of milk by infra-red absorption. Journal of Dairy Research 31, 273284.
Grelet, C, Bastin, C, Gelé, M, Davière, JB, Johan, M, Werner, A, Reding, R, Fernandez Pierna, JA, Colinet, FG, Dardenne, P, Gengler, N, Soyeurt, H and Dehareng, F 2016. Development of Fourier transform mid-infrared calibrations to predict acetone, β-hydroxybutyrate, and citrate contents in bovine milk through a European dairy network. Journal of Dairy Science 99, 48164825.
Griinari, JM, Dwyer, DA, McGuire, MA, Bauman, DE, Palmquist, DL and Nurmela, KV 1998. Trans-Octadecenoic acids and milk fat depression in lactating dairy cows. Journal of Dairy Science 81, 12511261.
Gross, J, van Dorland, HA, Bruckmaier, RM and Schwarz, FJ 2011a. Performance and metabolic profile of dairy cows during a lactational and deliberately induced negative energy balance by feed restriction with subsequent realimentation. Journal of Dairy Science 94, 18201830.
Gross, J, van Dorland, HA, Bruckmaier, RM and Schwarz, FJ 2011b. Milk fatty acid profile related to energy balance in dairy cows. Journal of Dairy Research 78, 479488.
Gross, JJ, Schwarz, FJ, Eder, K, van Dorland, HA and Bruckmaier, RM 2013. Liver fat content and lipid metabolism in dairy cows during early lactation and during a mid-lactation feed restriction. Journal of Dairy Science 96, 50085017.
Heuer, C, Schukken, YH and Dobbelaar, P 1999. Postpartum body condition score and results from the first test day milk as predictors of disease, fertility, yield, and culling in commercial dairy herds. Journal of Dairy Science 82, 295304.
Huber, K, Dänicke, S, Rehage, J, Sauerwein, H, Otto, W, Rolle-Kampczyk, U and von Bergen, M 2016. Metabotypes with properly functioning mitochondria and anti-inflammation predict extended productive life span in dairy cows. Scientific Reports 6, 24642.
Jensen, HB, Poulsen, NA, Andersen, KK, Hammershøj, M, Poulsen, HD and Larsen, LB 2012. Distinct composition of bovine milk from Jersey and Holstein-Friesian cows with good, poor, or noncoagulation properties as reflected in protein genetic variants and isoforms. Journal of Dairy Science 95, 69056917.
Jensen, RG, Ferris, AM and Lammi-Keefe, CJ 1991. The composition of milk fat. Journal of Dairy Science 74, 32283243.
Kay, JK, Weber, WJ, Moore, CE, Bauman, DE, Hansen, LB, Chester-Jones, H, Crooker, BA and Baumgard, LH 2005. Effects of week of lactation and genetic selection for milk yield on milk fatty acid composition in Holstein cows. Journal of Dairy Science 88, 38863893.
Kleen, JL, Hooijer, GA, Rehage, J and Noordhuizen, JP 2003. Subacute ruminal acidosis (SARA): a review. Journal of Veterinary Medicine. Series A: Physiology, Pathology, Clinical Medicine 50, 406414.
Koeck, A, Jamrozik, J, Schenkel, FS, Moore, RK, Lefebvre, DM, Kelton, DF and Miglior, F 2014. Genetic analysis of milk β-hydroxybutyrate and its association with fat-to-protein ratio, body condition score, clinical ketosis, and displaced abomasum in early first lactation of Canadian Holsteins. Journal of Dairy Science 97, 72867292.
Laeger, T, Metges, CC and Kuhla, B 2010. Role of beta-hydroxybutyric acid in the central regulation of energy balance. Appetite 54, 450455.
McArt, JA, Nydam, DV and Overton, MW 2015. Hyperketonemia in early lactation dairy cattle: A deterministic estimate of component and total cost per case. Journal of Dairy Science 98, 20432054.
McLaren, CJ, Lissemore, KD, Duffield, TF, Leslie, KE, Kelton, DF and Grexton, B 2006. The relationship between herd level disease incidence and a return over feed index in Ontario dairy herds. Canadian Veterinary Journal 47, 767773.
McParland, S and Berry, DP 2016. The potential of Fourier transform infrared spectroscopy of milk samples to predict energy intake and efficiency in dairy cows. Journal of Dairy Science 99, 40564070.
Miglior, F, Sewalem, A, Jamrozik, J, Lefebvre, DM and Moore, RK 2006. Analysis of milk urea nitrogen and lactose and their effect on longevity in Canadian dairy cattle. Journal of Dairy Science 89, 48864894.
Nousiainen, J, Shingfield, KJ and Huhtanen, P 2004. Evaluation of milk urea nitrogen as a diagnostic of protein feeding. Journal of Dairy Science 87, 386398.
Oetzel, GR 2004. Monitoring and testing dairy herds for metabolic disease. Veterinary Clinics of North America: Food Animal Practice 20, 651674.
Ospina, PA, Nydam, DV, Stokol, T and Overton, TR 2010. Evaluation of nonesterified fatty acids and beta-hydroxybutyrate in transition dairy cattle in the northeastern United States: critical thresholds for prediction of clinical diseases. Journal of Dairy Science 93, 546554.
Overton, TR, McArt, JAA and Nydam, DV 2017. A 100-year review: metabolic health indicators and management of dairy cattle. Journal of Dairy Science 100, 1039810417.
Palmquist, DL, Beaulieu, AD and Barbano, DM 1993. ADSA foundation symposium: milk fat synthesis and modification. Feed and animal factors influencing milk fat composition. Journal of Dairy Science 76, 17531771.
Palmquist, DL and Jenkins, TC 2017. A 100-year review: fat feeding of dairy cows. Journal of Dairy Science 100, 1006110077.
Raboisson, D, Mounié, M and Maigné, E 2014. Diseases, reproductive performance, and changes in milk production associated with subclinical ketosis in dairy cows: a meta-analysis and review. Journal of Dairy Science 97, 75477563.
Roche, JR, Kolver, ES and Kay, JK 2005. Influence of precalving feed allowance on periparturient metabolic and hormonal responses and milk production in grazing dairy cows. Journal of Dairy Science 88, 677689.
Santschi, DE, Lacroix, R, Durocher, J, Duplessis, M, Moore, RK and Lefebvre, DM 2016. Prevalence of elevated milk β-hydroxybutyrate concentrations in Holstein cows measured by Fourier-transform infrared analysis in dairy herd improvement milk samples and association with milk yield and components. Journal of Dairy Science 99, 92639270.
Schwarz, D 2018. Quality assurance tools in milk-testing laboratories – the view of an instrument manufacturer. In ICAR Technical Series No. 23: Cooperation, Networking and Global Interactions in the Animal Production Sector (ed. Bryant J, Burke M, Cook R, Harris B, Mosconi C and Wickham B), Proceedings of the ICAR Conference, 10–11 February 2018, Auckland, New Zealand, pp. 23–29.
Solano, J, Galindo, F, Orihuela, A and Galina, CS 2004. The effect of social rank on the physiological response during repeated stressful handling in Zebu cattle (Bos indicus). Physiology & Behavior 82, 679683.
Sordillo, LM, Contreras, GA and Aitken, SL 2009. Metabolic factors affecting the inflammatory response of periparturient dairy cows. Animal Health Research Reviews 10, 5363.
Stoop, WM, Bovenhuis, H, Heck, JML and van Arendonk, JAM 2009. Effect of lactation stage and energy status on milk fat composition of Holstein-Friesian cows. Journal of Dairy Science 92, 14691478.
Tsenkova, R, Atanassova, S, Toyoda, K, Ozaki, Y, Itoh, K and Fearn, T 1999. Near-infrared spectroscopy for dairy management: measurement of unhomogenized milk composition. Journal of Dairy Science 82, 23442351.
Tyburczy, C, Lock, AL, Dwyer, DA, Destaillats, F, Mouloungui, Z, Candy, L and Bauman, DE 2008. Uptake and utilization of trans octadecenoic acids in lactating cows. Journal of Dairy Science 91, 38503861.
van Haelst, YNT, Beeckman, A, van Knegsel, ATM and Fievez, V 2008. Short communication: elevated concentrations of oleic acid and long-chain fatty acids in milk fat of multiparous subclinical ketotic cows. Journal of Dairy Science 91, 46834686.
Vanlierde, A, Soyeurt, H, Gengler, N, Colinet, FG, Froidmont, E, Kreuzer, M, Grandl, F, Bell, M, Lund, P, Olijhoek, DW, Eugène, M, Martin, C, Kuhla, B and Dehareng, F 2018. Short communication: development of an equation for estimating methane emissions of dairy cows from milk Fourier transform mid-infrared spectra by using reference data obtained exclusively from respiration chambers. Journal of Dairy Science 101, 76187624.
Zarrin, M, Wellnitz, O, van Dorland, HA, Gross, JJ and Bruckmaier, RM 2014. Hyperketonemia during lipopolysaccharide-induced mastitis affects systemic and local intramammary metabolism in dairy cows. Journal of Dairy Science 97, 35313541.
Zbinden, RS, Falk, M, Münger, A, Dohme-Meier, F, van Dorland, HA, Bruckmaier, RM and Gross, JJ 2017. Metabolic load in dairy cows kept in herbage-based feeding systems and suitability of potential markers for compromised well-being. Journal of Animal Physiology and Animal Nutrition 101, 767778.

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Review: Metabolic challenges in lactating dairy cows and their assessment via established and novel indicators in milk

  • J. J. Gross (a1) and R. M. Bruckmaier (a1)

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