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Sermyagin A.A., Lashneva I.A., Kositsin A.A., Ignatieva L.P., Artemieva O.A., Sölkner J., Zinovieva N.A. Differential somatic cell count in milk as criteria for assessing cows’ udder health in relation with milk production and components. Sel'skokhozyaistvennaya Biologiya [Agricultural Biology], 2021, Vol. 56, № 6, p. 1183-1198.
(how to cite this article)

doi: 10.15389/agrobiology.2021.6.1183eng

UDC: 636.2:619:637.04

Acknowledgements:
We express our gratitude to the company Foss Electric LLC (Russia branch, Moscow) for the information support provided in the implementation of these studies, with personal thanks to the Head of the Dairy Farming and Feed Division Irina Elizarova and the service engineer Denis Karlin.
Supported financially by the Russian Foundation for Basic Research in the framework of scientific project No. 20-316-90050 for the analysis of somatic cell count in cows’ milk and by the Russian Science Foundation project No. 21-76-20046 for studying extended milk component composition based on infrared spectrometry

 

DIFFERENTIAL SOMATIC CELL COUNT IN MILK AS CRITERIA FOR ASSESSING COWS’ UDDER HEALTH IN RELATION WITH MILKPRODUCTION AND COMPONENTS

A.A. Sermyagin1 ✉, I.A. Lashneva1, A.A. Kositsin1, L.P. Ignatieva1,
O.A. Artemieva1, J. Sölkner2, N.A. Zinovieva1

1Ernst Federal Research Center for Animal Husbandry,60, pos. Dubrovitsy, Podolsk District, Moscow Province, 142132 Russia, e-mail alex_sermyagin85@mail.ru (✉ corresponding author), lashnevaira@gmail.com, ksicins@gmail.com, ignatieva-lp@mail.ru, vijmikrob@mail.ru, n_zinovieva@mail.ru);
2Universität für Bodenkultur,1180 Wien, Österreich, Gregor-Mendel-Straße 33, e-mail johann.soelkner@boku.ac.at

ORCID:
Sermyagin A.A. orcid.org/0000-0002-1799-6014
Artemieva O.A. orcid.org/0000-0001-7706-4182
Lashneva I.A. orcid.org/0000-0003-4276-8782
Sölkner J. orcid.org/0000-0002-1517-5829
Kositsin A.A. orcid.org/0000-0001-8484-4902
Zinovieva N.A. orcid.org/0000-0003-4017-6863
Ignatieva L.P. orcid.org/0000-0003-2625-6912

Received September 30, 2021

The somatic cell count in cow's milk is used to control the inflammatory infection process and to assess the likelihood of subclinical and clinical mastitis. In the article, within the framework of experimental design of observations in a dairy cattle herd, the possibility in the cows’ mammary gland monitoring status, based on the total somatic cell count determination and proportion for lymphocytes and polymorphonuclear neutrophils (PMN) in raw milk is shown for the first time in Russia. The obtained results confirm the relationship between somatic cell count (SCC) and daily milk yield for lactating animals. The aim of this work is to assess the relationship between the number of somatic cells in milk and their differentiation by species with milk production, milk component traits, and the risk of progressing subclinical and clinical mastitis in Holsteinized Black-and-White cows. The work was carried out from June 2020 to May 2021 (an experimental herd of Holsteinized Black-and-White cattle, PZ Ladozhsky — a branch of the Ernst Federal Research Center for Animal Husbandry, Krasnodar Territory). The total sample in a data set was 313 animals; the number of milk lactation records was 1931. The analysis of milk components was carried out using an automatic analyzer CombiFoss 7 DC (FOSS, Denmark) based on express methods of infrared spectroscopy and flow cytometry. The following milk traits were studied: daily milk yield, percentage of fat, protein, casein, lactose, dry matter, dry skimmed milk residue, traces of acetone and beta-hydroxybutyrate (BHB), freezing point and acidity, fatty acids (FA), SCC, DSCC (fraction of lymphocytes and PMN in the total amount of cells). In order to indirectly assess the mammary gland condition of cows, animals in the herd were conditionally divided into four groups: A — SCC ≤ 200 thousand cells per ml, DSCC ≤ 70 %; B — SCC ≤ 200 thousand cells per ml, DSCC > 70 %; C — SCC > 200 thousand cells per ml, DSCC > 70 %; D — SCC > 200 thousand cells per ml, DSCC ≤ 70 %. Also, the following animal gradation was applied regardless of the probability of mastitis: two groups with DSCC ≤ 70 and DSCC > 70 %; four subgroups with SCC ≤ 200, 201-500, 501-1000 and ≥ 1001 thousand cells per ml. We used logarithmic (normalized) SCC scores according to G.R. Wiggans et al. (1987) approach. The individual economic value of the daily milk yield of cows was determined. For assessing effects of environmental factors and their elimination on daily milk component traits, the equation of generalized linear models (GLM) was used. Estimates of phenotypic means for milk features were obtained by the GLM-equation using the least squares method. The pairwise comparison between means was performed using Tukey’s test. Principal component analysis (PCA) was used to study the variability of milk composition depending on their formation in the animal organism in order to determine the most significant parameters that determine the productivity of dairy cows. Healthy individuals and animals with suspected mastitis (predisposed to the onset of infection) (groups A and B) had desirable features of milk production, the daily milk yield was 25.7-27.7 kg, the average economic efficiency of milk production was 714-744 rubles per day per cow. Cows assigned to groups C (subclinical or clinical forms of active mastitis) and revealed as D (chronic mastitis) had the milk component traits superior to other groups with a relatively lower daily milk yield. Animals with high SCC values as well as with a chronic form of mastitis were most susceptible to metabolic disorders or ketosis, regardless of DSCC. An increase in the fat percentage in milk by 0.18-0.37 % (p ≤ 0.001) for animals with SCC ≥ 1001 thousand cells per ml led to rise the share of saturated FA by 1.1-1.4 percentage points (p.p.), palmitic FA — by 0.4-1.2 p.p., medium-chain FA — by 1.0-1.4 p.p. An increase in the normalized scores of SCC by one point (limits from 1 to 10) led to a decrease in the daily milk yield by 0.6 kg, lactose percentage — by 0.062 p.p. and an increase in fat and protein by 0.090 and 0.055 p.p., respectively. Analysis of the main components revealed clear clusters for the protein and fat milk fractions, urea and fatty acids, acetone and BHB, freezing point and pH values, SCC and DSCC. A separate group included the daily milk yield and lactose percentage (together with ketone bodies) traits not related to other milk composition traits, thereby indicating the independent nature of the variability of these features. Further study of the relationship between the milk components synthesis in mammary gland and animal physiological status will make it possible to clarify the direction of selection in dairy cattle and define the genetic determination of milk production traits.

Keywords: milk, cow, somatic cell count, milk yield, fat, protein, fatty acids, acetone, BHB, mastitis, ketosis.

 

REFERENCES

  1. Hanuš O., Samková E., Křížová L., Hasoňová L., Kala R. Role of fatty acids in milk fat and the influence of selected factors on their variability — a review. Molecules, 2018, 23(7): 1636 CrossRef
  2. Zaalberg R.M., Shetty N., Janss L., Buitenhuis A.J. Genetic analysis of Fourier transform infrared milk spectra in Danish Holstein and Danish Jersey. Journal of Dairy Science, 2019, 102(1): 503-510 CrossRef
  3. Carvalho-Sombra T.C.F., Fernandes D.D., Bezerra B.M.O., Nunes-Pinheiro D.C.S. Systemic inflammatory biomarkers and somatic cell count in dairy cows with subclinical mastitis. Veterinary and Animal Science, 2021, 11: 100165 CrossRef
  4. Pillai S.R., Kunze E., Sordillo L.M., Jayarao B.M. Application of differential inflammatory cell count as a tool to monitor udder health. Journal of Dairy Science, 2001, 84(6): 1413-1420 CrossRef
  5. Rivas A.L., Quimby F.W., Blue J., Coksaygan O. Longitudinal evaluation of bovine mammary gland health status by somatic cell counting, flow cytometry, and cytology. Journal of Veterinary Diagnostic Investigation, 2001, 13(5): 399-407 CrossRef
  6. Pilla R., Malvisi M., Snel G., Schwarz D., König S., Czerny C.-P., Piccinini R. Differential cell count as an alternative method to diagnose dairy cow mastitis. Journal of Dairy Science, 2013, 96(3): 1653-1660 CrossRef
  7. Sordillo L.M., Shafer-Weaver K., DeRosa D. Immunobiology of the mammary gland. Journal of Dairy Science, 1997, 80(8): 1851-1865 CrossRef
  8. Oviedo-Boyso J., Valdez-Alarcón J.J., Cajero-Juárez M., Ochoa-Zarzosa A., López-Meza J.E., Bravo-Patiño A., Baizabal-Aguirre V.M. Innate immune response of bovine mammary gland to pathogenic bacteria responsible for mastitis. Journal of Infection, 2007, 54(4): 399-409 CrossRef
  9. Halasa T., Kirkeby C. Differential somatic cell count: value for udder health management. Frontiers in Veterinary Science, 2020, 7: 609055 CrossRef
  10. Lee C., Wooding F., Kemp P. Identification, properties, and differential counts of cell populations using electron microscopy of dry cows secretions, colostrum and milk from normal cows. Journal of Dairy Research, 1980, 47(1): 39-50 CrossRef
  11. Schwarz D., Diesterbeck U.S., König S., Brügemann K., Schlez K., Zschöck M., Wolter W. Czerny C.P. Flow cytometric differential cell counts in milk for the evaluation of inflammatory reactions in clinically healthy and subclinically infected bovine mammary glands. Journal of Dairy Science,2011, 94(10): 5033-5044 CrossRef
  12. Schwarz D., Diesterbeck U.S., König S., Brügemann K., Schlez K., Zschöck M., Wolter W., Czerny C.-P. Microscopic differential cell counts in milk for the evaluation of inflammatory reactions in clinically healthy and subclinically infected bovine mammary glands. Journal of Dairy Research, 2011, 78(4): 448-455 CrossRef
  13. Pilla R., Schwarz D., König S., Piccinini R. Microscopic differential cell counting to identify inflammatory reactions in dairy cow quarter milk samples. Journal of Dairy Science, 2012, 95(8): 4410-4420 CrossRef
  14. Paape M.J., Mehrzad J., Zhao X., Detilleux J., Burvenich C. Defense of the bovine mammary gland by polymorphonuclear neutrophil leukocyte. Journal of Mammary Gland Biology and Neoplasia, 2002, 7(2): 109-121 CrossRef
  15. Schwarz D. Differential somatic cell count — a new biomarker for mastitis screening. Proc. of the 40th ICAR Biennial Session held in Puerto Varas, Chile, 24-28 October 2016. ICAR, Rome, Italy, 2017: 105-113.
  16. Damm M., Holm C., Blaabjerg M., Novak Bro M., Schwarz D. Differential somatic cell count—a novel method for routine mastitis screening in the frame of dairy herd improvement testing programs. Journal of Dairy Science, 2017, 100(6): 4926-4940 CrossRef
  17. Sermyagin A.A., Gladyr E.A., Kharzhau A.A., Plemyashov K.V., Tyurenkova E.N., Reyer H., Wimmers K., Brem G., Zinovieva N.A. 167 Genetic and genomic estimation for somatic cell score in relation with milk production traits of Russian Holstein dairy cattle. Journal of Dairy Science, 2017, 95(4): 82-83 CrossRef
  18. Naryshkina E.N., Sermyagin A.A., Vinogradova I.V., Khripyakova E.N. V sbornike: Puti prodleniya produktivnoi zhizni molochnykh korov na osnove optimizatsii razvedeniya, tekhnologii soderzhaniya i kormleniya zhivotnykh. Materialy mezhdunarodnoi nauchno-prakticheskoi konferentsii [In: Ways to prolong the productive life of dairy cows by the optimization of breeding, keeping and feeding technologies. Materials of the international scientific and practical conference]. Dubrovitsy, 2015: 69-73 (in Russ.).
  19. Wiggans G.R., Shook G.E.A Lactation measure of somatic cell count. Journal of Dairy Science, 1987, 70(12): 2666-2672 CrossRef
  20. StatSoft, Inc. STATISTICA (data analysis software system), version 12. (2014). www.statsoft.com.
  21. Chasovshchikova M.A., Gubanov M.V. Vestnik KrasGAU, 2021, 9(174): 132-137 CrossRef (in Russ.).
  22. Sermyagin A.A., Belous A.A., Kornelaeva M.V., Filipchenko A.A., Kisel' E.E., Bukarov N.G., Ermilov A.N., YAnchukov I.N., Zinov'eva N.A. V knige: Plemennaya rabota v zhivotnovodstve Moskovskoi oblasti i g. Moskvy (2017 g.) [In: Pedigree work in animal husbandry in the Moscow region and Moscow (2017)]. Moscow, 2018: 11-22 (in Russ.).
  23. Lashneva I.A., Sermyagin A.A. Dostizheniya nauki i tekhniki APK, 2020, 34(3): 46-50 CrossRef (in Russ.).
  24. Santschi D.E., Lacroix R., Durocher J., Duplessis M., Moore R.K., Lefebvre D.M. Prevalence of elevated milk b-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, 2016, 99(11): 9263-9270 CrossRef
  25. Schwarz D., Lipkens Z., Piepers S., De Vliegher S. Investigation of differential somatic cell count as a potential new supplementary indicator to somatic cell count for identification of intramammary infection in dairy cows at the end of the lactation period. Preventive Veterinary Medicine, 2019, 172: 104803 CrossRef
  26. Schwarz D., Kleinhans S., Reimann G., Stückler P., Reith F., Ilves K., Pedastsaar K., Yan L., Zhang Z., Valdivieso M., Barreal M.L., Fouz R. Investigation of dairy cow performance in different udder health groups defined based on a combination of somatic cell count and differential somatic cell count. Preventive Veterinary Medicine, 2020, 183: 105123 CrossRef
  27. Schwarz D., Santschi D.E., Durocher J., Lefebvre D.M. Evaluation of the new differential somatic cell count parameter as a rapid and inexpensive supplementary tool for udder health management through regular milk recording. Preventive Veterinary Medicine, 2020, 181: 105079 CrossRef
  28. Fursova K., Sorokin A., Sokolov S., Dzhelyadin T., Shulcheva I., Shchannikova M., Nikanova D., Artem’eva O., Zinovieva N., Brovko F. Virulence Factors and Phylogeny of Staphylococcus aureus associated with bovine mastitis in Russia based on genome sequences. Frontiers in Veterinary Science, 2020, 7: 135 CrossRef

 

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