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Opportunities and limitations of milk mid-infrared spectra-based estimation of acetone and β-hydroxybutyrate for the prediction of metabolic stress and ketosis in dairy cows

Published online by Cambridge University Press:  20 April 2020

Monica O. Caldeira ,
Denisa Dan ,
Anna-Lena Neuheuser ,
Remo Stürmlin ,
Christoph Weber ,
Daniel L. Glauser ,
Martin Stierli ,
Urs Schuler ,
Juerg Moll  and
Silvia Wegmann
...Show all authors
Monica O. Caldeira
Affiliation:
Veterinary Physiology, Vetsuisse Faculty University of Bern, Switzerland
Denisa Dan
Affiliation:
Veterinary Physiology, Vetsuisse Faculty University of Bern, Switzerland
Anna-Lena Neuheuser
Affiliation:
Veterinary Physiology, Vetsuisse Faculty University of Bern, Switzerland
Remo Stürmlin
Affiliation:
Veterinary Physiology, Vetsuisse Faculty University of Bern, Switzerland
Christoph Weber
Affiliation:
Veterinary Physiology, Vetsuisse Faculty University of Bern, Switzerland
Daniel L. Glauser
Affiliation:
Suisselab AG, Zollikofen, Switzerland
Martin Stierli
Affiliation:
Suisselab AG, Zollikofen, Switzerland
Urs Schuler
Affiliation:
Qualitas AG, Zug, Switzerland
Juerg Moll
Affiliation:
Qualitas AG, Zug, Switzerland
Silvia Wegmann
Affiliation:
Qualitas AG, Zug, Switzerland
Rupert M. Bruckmaier
Affiliation:
Veterinary Physiology, Vetsuisse Faculty University of Bern, Switzerland
Josef J. Gross*
Affiliation:
Veterinary Physiology, Vetsuisse Faculty University of Bern, Switzerland
*
Author for correspondence: Josef J. Gross, Email: josef.gross@vetsuisse.unibe.ch
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Abstract

Subclinical (SCK) and clinical (CK) ketosis are metabolic disorders responsible for big losses in dairy production. Although Fourier-transform mid-infrared spectrometry (FTIR) to predict ketosis in cows exposed to great metabolic stress was studied extensively, little is known about its suitability in predicting hyperketonemia using individual samples, e.g. in small dairy herds or when only few animals are at risk of ketosis. The objective of the present research was to determine the applicability of milk metabolites predicted by FTIR spectrometry in the individual screening for ketosis. In experiment 1, blood and milk samples were taken every two weeks after calving from Holstein (n = 80), Brown Swiss (n = 72) and Swiss Fleckvieh (n = 58) cows. In experiment 2, cows diagnosed with CK (n = 474) and 420 samples with blood β-hydroxybutyrate [BHB] <1.0 mmol/l were used to investigate if CK could be detected by FTIR-predicted BHB and acetone from a preceding milk control. In experiment 3, correlations between data from an in farm automatic milk analyser and FTIR-predicted BHB and acetone from the monthly milk controls were evaluated. Hyperketonemia occurred in majority during the first eight weeks of lactation. Correlations between blood BHB and FTIR-predicted BHB and acetone were low (r = 0.37 and 0.12, respectively, P < 0.0001), as well as the percentage of true positive values (11.9 and 16.6%, respectively). No association of FTIR predicted ketone bodies with the interval of milk sampling relative to CK diagnosis was found. Data obtained from the automatic milk analyser were moderately correlated with the same day FTIR-predicted BHB analysis (r = 0.61). In conclusion, the low correlations with blood BHB and the small number of true positive samples discourage the use of milk mid-infrared spectrometry analyses as the only method to predict hyperketonemia at the individual cow level.

Keywords

β-hydroxybutyrateacetoneketosismid-infrared spectrometrymilk
Type
Research Article
Information
Journal of Dairy Research , Volume 87 , Issue 2 , May 2020 , pp. 196 - 203
Copyright
Copyright © Hannah Dairy Research Foundation 2020

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References

Bastin, C, Théron, L, Lainé, A and Gengler, N (2016) On the role of mid-infrared predicted phenotypes in fertility and health dairy breeding programs. Journal of Dairy Science 99, 4080–4094.CrossRefGoogle ScholarPubMed
Bauman, DE and Currie, WB (1980) Partitioning of nutrients during pregnancy and lactation: a review of mechanisms involving homeostasis and homeorhesis. Journal of Dairy Science 63, 1514–1529.CrossRefGoogle ScholarPubMed
Berge, AC and Vertenten, G (2014) A field study to determine the prevalence, dairy herd management systems, and fresh cow clinical conditions associated with ketosis in western European dairy herds. Journal of Dairy Science 97, 2145–2154.CrossRefGoogle ScholarPubMed
Bruckmaier, RM and Gross, JJ (2017) Lactational challenges in transition dairy cows. Animal Production Science 57, 1471–1481.CrossRefGoogle Scholar
Brunner, N, Canelas Raposo, J, Groeger, S, Bruckmaier, RM and Gross, JJ (2019) Prevalence of subclinical ketosis and production diseases in dairy cows in central and South America, Africa, Asia, Australia, New Zealand, and Eastern Europe. Translational Animal Science 3, 84–92.CrossRefGoogle ScholarPubMed
Butler, ST, Marr, AL, Pelton, SH, Radcliff, RP, Lucy, MC and Butler, WR (2003) Insulin restores GH responsiveness during lactation-induced negative energy balance in dairy cattle: effects on expression of IGF-I and GH receptor 1A. Journal of Endocrinology 176, 205–217.CrossRefGoogle ScholarPubMed
Buttchereit, N, Stamer, E, Junge, W and Thaller, G (2010) Evaluation of five lactation curve models fitted for fat:protein ratio of milk and daily energy balance. Journal of Dairy Science 93, 1702–1712.CrossRefGoogle ScholarPubMed
Chandler, TL, Pralle, RS, Dórea, JRR, Poock, SE, Oetzel, GR, Fourdraine, RH and White, HM (2018) Predicting hyperketonemia by logistic and linear regression using test-day milk and performance variables in early-lactation Holstein and jersey cows. Journal of Dairy Science 101, 2476–2491.CrossRefGoogle ScholarPubMed
Chapinal, N, LeBlanc, SJ, Carson, ME, Leslie, KE, Godden, S, Capel, M, Santos, JEP, Overton, MW and Duffield, TF (2012) Herd-level association of serum metabolites in the transition period with disease, milk production, and early lactation reproductive performance. Journal of Dairy Science 95, 5676–5682.CrossRefGoogle ScholarPubMed
Contreras, GA, Strieder-Barboza, C and Raphael, W (2017) Adipose tissue lipolysis and remodeling during the transition period of dairy cows. Journal of Animal Science and Biotechnology 8, 41.CrossRefGoogle ScholarPubMed
Dehareng, F, Delfosse, C, Froidmont, E, Soyeurt, H, Martin, C, Gengler, N, Vanlierde, A and Dardenne, P (2012) Potential use of milk mid-infrared spectra to predict individual methane emission of dairy cows. Animal: An International Journal of Animal Bioscience 6, 1694–1701.CrossRefGoogle ScholarPubMed
De Marchi, M, Fagan, CC, O'Donnell, CP, Cecchinato, A, Dal Zotto, R, Cassandro, M, Penasa, M and Bittante, G (2009) Prediction of coagulation properties, titratable acidity, and pH of bovine milk using mid-infrared spectroscopy. Journal of Dairy Science 92, 423–432.CrossRefGoogle ScholarPubMed
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, 1171–1186.CrossRefGoogle ScholarPubMed
de Roos, APW, van den Bijgaart, HJCM, Hørlyk, J and de Jong, G (2007) Screening for subclinical ketosis in dairy cattle by Fourier transform infrared spectrometry. Journal of Dairy Science 90, 1761–1766.CrossRefGoogle ScholarPubMed
Duffield, TF, Kelton, DF, Leslie, KE, Lissemore, KD and Lumsden, JH (1997) Use of test day milk fat and milk protein to detect subclinical ketosis in dairy cattle in Ontario. The Canadian Veterinary Journal 38, 713–718.Google ScholarPubMed
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, 571–580.CrossRefGoogle Scholar
Galvão, KN, Flaminio, MJBF, Brittin, SB, Sper, R, Fraga, M, Caixeta, L, Ricci, A, Guard, CL, Butler, WR and Gilbert, RO (2010) Association between uterine disease and indicators of neutrophil and systemic energy status in lactating Holstein cows. Journal of Dairy Science 93, 2926–2937.CrossRefGoogle ScholarPubMed
Grelet, C, Bastin, C, Gelé, M, Davière, J-B, 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, 4816–4825.CrossRefGoogle ScholarPubMed
Gross, J, van Dorland, HA, Bruckmaier, RM and Schwarz, FJ (2011 a) Performance and metabolic profile of dairy cows during a lactational and deliberately induced negative energy balance with subsequent realimentation. Journal of Dairy Science 94, 1820–1830.CrossRefGoogle ScholarPubMed
Gross, J, van Dorland, HA, Bruckmaier, RM and Schwarz, FJ (2011 b) Milk fatty acid profile related to energy balance in dairy cows. Journal of Dairy Research 78, 479–488.CrossRefGoogle ScholarPubMed
Gross, JJ and Bruckmaier, RM (2015) Repeatability of metabolic responses to a nutrient deficiency in early and mid lactation and implications for robustness of dairy cows. Journal of Dairy Science 98, 8634–8643.CrossRefGoogle ScholarPubMed
Gross, JJ and Bruckmaier, RM (2019 a) Invited review: metabolic challenges and adaptation during different functional stages of the mammary gland in dairy cows: perspectives for sustainable milk production. Journal of Dairy Science 102, 2828–2843.CrossRefGoogle ScholarPubMed
Gross, JJ and Bruckmaier, RM (2019 b) Review: metabolic challenges in lactating dairy cows and their assessment Via Established and novel indicators in milk. Animal: An International Journal of Animal Bioscience 13(S1), s75–s81.CrossRefGoogle ScholarPubMed
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, 295–304.CrossRefGoogle ScholarPubMed
Hillreiner, M, Flinspach, C, Pfaffl, MW and Kliem, H (2016) Effect of the ketone body beta-hydroxybutyrate on the innate defense capability of primary bovine mammary epithelial cells. PLoS One 11, e0157774.CrossRefGoogle ScholarPubMed
Ingvartsen, KL, Dewhurst, RJ and Friggens, NC (2003) On the relationship between lactational performance and health: is it yield or metabolic imbalance that cause production diseases in dairy cattle? A position paper. Livestock Production Science 83, 277–308.CrossRefGoogle Scholar
Kessel, S, Stroehl, M, Meyer, HHD, Hiss, S, Sauerwein, H, Schwarz, FJ and Bruckmaier, RM (2008) Individual variability in physiological adaptation to metabolic stress during early lactation in dairy cows kept under equal conditions. Journal of Animal Science 86, 2903–2912.CrossRefGoogle ScholarPubMed
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, 7286–7292.CrossRefGoogle ScholarPubMed
Laeger, T, Metges, CC and Kuhla, B (2010) Role of β-hydroxybutyric acid in the central regulation of energy balance. Appetite 54, 450–455.CrossRefGoogle ScholarPubMed
LeBlanc, SJ (2012) Interactions of metabolism, inflammation, and reproductive tract health in the postpartum period in dairy cattle. Reproduction in Domestic Animals 47, 18–30.CrossRefGoogle ScholarPubMed
LeBlanc, SJ, Leslie, KE and Duffield, TF (2005) Metabolic predictors of displaced abomasum in dairy cattle. Journal of Dairy Science 88, 159–170.CrossRefGoogle ScholarPubMed
Lee, J-Y and Kim, I-H (2006) Advancing parity is associated with high milk production at the cost of body condition and increased periparturient disorders in dairy herds. Journal of Veterinary Science 7, 161–166.CrossRefGoogle ScholarPubMed
Maurice-Van Eijndhoven, MHT, Soyeurt, H, Dehareng, F and Calus, MPL (2013) Validation of fatty acid predictions in milk using mid-infrared spectrometry across cattle breeds. Animal: An International Journal of Animal Bioscience 7, 348–354.CrossRefGoogle ScholarPubMed
McArt, JAA, Nydam, DV and Oetzel, GR (2012) Epidemiology of subclinical ketosis in early lactation dairy cattle. Journal of Dairy Science 95, 5056–5066.CrossRefGoogle ScholarPubMed
McDermott, A, Visentin, G, De Marchi, M, Berry, DP, Fenelon, MA, O'Connor, PM, Kenny, OA and McParland, S (2016) Prediction of individual milk proteins including free amino acids in bovine milk using mid-infrared spectroscopy and their correlations with milk processing characteristics. Journal of Dairy Science 99, 3171–3182.CrossRefGoogle ScholarPubMed
McParland, S, Banos, G, Wall, E, Coffey, MP, Soyeurt, H, Veerkamp, RF and Berry, DP (2011) The use of mid-infrared spectrometry to predict body energy status of Holstein cows. Journal of Dairy Science 94, 3651–3661.CrossRefGoogle ScholarPubMed
Morales Piñeyrúa, JT, Fariña, SR and Mendoza, A (2018) Effects of parity on productive, reproductive, metabolic and hormonal responses of Holstein cows. Animal Reproduction Science 191, 9–21.CrossRefGoogle ScholarPubMed
Mulligan, FJ and Doherty, ML (2008) Production diseases of the transition cow. The Veterinary Journal 176, 3–9.CrossRefGoogle ScholarPubMed
Nielsen, NI, Friggens, NC, Chagunda, MGG and Ingvartsen, KL (2005) Predicting risk of ketosis in dairy cows using in-line measurements of β-hydroxybutyrate: a biological model. Journal of Dairy Science 88, 2441–2453.CrossRefGoogle ScholarPubMed
Ospina, PA, Nydam, DV, Stokol, T and Overton, TR (2010) Association between the proportion of sampled transition cows with increased nonesterified fatty acids and β-hydroxybutyrate and disease incidence, pregnancy rate, and milk production at the herd level. Journal of Dairy Science 93, 3595–3601.CrossRefGoogle ScholarPubMed
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, 10398–10417.CrossRefGoogle ScholarPubMed
Raboisson, D, Mounié, M, Khenifar, E and Maigné, E (2015) The economic impact of subclinical ketosis at the farm level: tackling the challenge of over-estimation due to multiple interactions. Preventive Veterinary Medicine 122, 417–425.CrossRefGoogle ScholarPubMed
Rutten, MJM, Bovenhuis, H, Heck, JML and van Arendonk, JAM (2011) Predicting bovine milk protein composition based on Fourier transform infrared spectra. Journal of Dairy Science 94, 5683–5690.CrossRefGoogle ScholarPubMed
Schultz, LH (1968) Ketosis in dairy cattle. Journal of Dairy Science 51, 1133–1140.CrossRefGoogle ScholarPubMed
Seifi, HA, LeBlanc, SJ, Leslie, KE and Duffield, TF (2011) Metabolic predictors of post-partum disease and culling risk in dairy cattle. The Veterinary Journal 188, 216–220.CrossRefGoogle ScholarPubMed
Soyeurt, H, Dardenne, P, Dehareng, F, Lognay, G, Veselko, D, Marlier, M, Bertozzi, C, Mayeres, P and Gengler, N (2006) Estimating fatty acid content in cow milk using mid-infrared spectrometry. Journal of Dairy Science 89, 3690–3695.CrossRefGoogle ScholarPubMed
Suthar, VS, Canelas-Raposo, J, Deniz, A and Heuwieser, W (2013) Prevalence of subclinical ketosis and relationships with postpartum diseases in European dairy cows. Journal of Dairy Science 96, 2925–2938.CrossRefGoogle ScholarPubMed
Urdl, M, Gruber, L, Obritzhauser, W and Schauer, A (2015) Metabolic parameters and their relationship to energy balance in multiparous Simmental, Brown Swiss and Holstein cows in the periparturient period as influenced by energy supply pre- and post-calving. Journal of Animal Physiology and Animal Nutrition 99, 174–189.CrossRefGoogle ScholarPubMed
van der Kolk, JH, Gross, JJ, Gerber, V and Bruckmaier, RM (2017) Disturbed bovine mitochondrial lipid metabolism: a review. Veterinary Quarterly 37, 262–273.CrossRefGoogle Scholar
van Knegsel, ATM, van der Drift, SGA, Horneman, M, de Roos, APW, Kemp, B and Graat, EAM (2010) Short communication: ketone body concentration in milk determined by Fourier transform infrared spectroscopy: value for the detection of hyperketonemia in dairy cows. Journal of Dairy Science 93, 3065–3069.CrossRefGoogle ScholarPubMed
Wallén, SE, Prestløkken, E, Meuwissen, THE, McParland, S and Berry, DP (2018) Milk mid-infrared spectral data as a tool to predict feed intake in lactating Norwegian Red dairy cows. Journal of Dairy Science 101, 6232–6243.CrossRefGoogle ScholarPubMed
Zarrin, M, Wellnitz, O, van Dorland, HA and Bruckmaier, RM (2014) Induced hyperketonemia affects the mammary immune response during lipopolysaccharide challenge in dairy cows. Journal of Dairy Science 97, 330–339.CrossRefGoogle ScholarPubMed
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, 767–778.CrossRefGoogle ScholarPubMed
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