A comprehensive assessment of the quality of raw cow's milk based on somatic cell count and the presence of mesophilic aerobic and facultative anaerobic microorganisms as indicators of the safety and processing properties of raw milk
DOI:
https://doi.org/10.31073/onehealthjournal2026-III-04Keywords:
somatic cells, mesophilic aerobic and facultative anaerobic microorganisms (MAFAnM), cow's milk, species, automated TEMPO® method, correlation analysis, Student's t-testAbstract
This study conducted a comparative evaluation of methods for determining the somatic cell count and the number of mesophilic aerobic and facultative anaerobic microorganisms (MAFAnM) in raw cow's milk. The aim of the study was to establish the analytical agreement, accuracy, and reproducibility of results obtained by different methods, as well as to justify the feasibility of using the TEMPO® automated system as an alternative method for microbiological control.
The study material consisted of 39 samples of raw cow's milk collected in 2025 from clinically healthy Black-and-White and Red dairy cows aged 4–8 years on private farms in various regions of Ukraine. Somatic cell counts were determined using two microscopic methods in accordance with the requirements of ISO 13366-1:2008: by counting cells in smears across fifty fields of view and in ten parallel strips. The number of total aerobic bacteria was determined using two independent methods: an automated fluorometric method using the TEMPO® system and a reference method of deep plating on Plate Count Agar medium in accordance with ISO 4833-1:2013.
Statistical analysis of the results was performed using Student's paired t-test and Pearson's correlation analysis. It was found that the mean values of somatic cell counts obtained by different methods were 301,795 and 294,641 cells/cm³, respectively, and for MAFAnM—43,041 and 43,513 CFU/cm³. The calculated t-test values (t = 1.80 for somatic cells and t = –1.32 for MAFAnM) did not exceed critical values (p > 0.05), indicating the absence of statistically significant differences between the methods. The Pearson correlation coefficient was r = 1.0 for somatic cells and r = 0.9996 for MAFAnM (p < 0.05), indicating a strong direct linear relationship and high consistency of results.
The research demonstrated that TEMPO® automated system provides results for the detection of mesophilic aerobic and facultative anaerobic microorganisms (MAFAnM) in raw milk that are statistically equivalent to the reference method, with high accuracy and reproducibility and minimal human influence. The use of this system is recommended for implementation in production laboratories as a rapid and reliable tool for monitoring the microbiological parameters of raw milk.
References
Ryzhkova T. (2023). Comparative evaluation of methods for determining the number of mesophilic aerobic and facultative anaerobic microorganisms and coliforms in cow and goat milk and brined cheese. Agrarian Bulletin of the Black Sea Region; 107, 96–104. doi.: 10.37000/abbsl.2023.107.17
Fonseca M., Kurban D., Roy J. P., Santschi D. E., Molgat E., Dufour S. (2025). Usefulness of differential somatic cell count for udder health monitoring: Association of differential somatic cell count and somatic cell score with quarter-level milk yield and milk components. Journal of Dairy Science; 108(4), 3003–3016. doi.: 10.3168/jds.2024-25402
Desidera F., Skeie S. B., Devold T. G., Inglingstad R. A., Porcellato D. (2025). Fluctuations in somatic cell count and their impact on individual goat milk quality throughout lactation. Journal of Dairy Science; 108, 2291–2304. doi.: 10.3168/jds.2024-25310
Nagy S. A., Csabai I., Varga T., Poth-Szebenyi B., Gabor G., Solymosi N. (2025). Neural network-aided milk somatic cell count increase prediction. Veterinary Sciences; 12(5), 420. doi.: 10.3390/vetsci12050420
Besteiro R., Fouz R., Dieguez F. J. (2025). Influence of heat stress on milk production, milk quality, and somatic cell count in Galicia (NW Spain). Animals; 15(7), 945. doi.: 10.3390/ani15070945
Smistad M., Inglingstad R. A., Vatne M. K., Franklin F. V., Hansen B. G., Skeie S., Porcellato D. (2025). Somatic cell count in dairy goats II: Udder health monitoring at goat and herd level. BMC Veterinary Research; 21(1), 157. doi.: 10.1186/s12917-025-04556-8
Ermetin O., Okuyucu I. C., Kul E. (2025). Effect of somatic cell count on fertility and milk yield traits during different lactation periods in Holstein cows. Turkish Journal of Agriculture: Food Science and Technology; 13(5), 1285–1291. doi.: 10.24925/turjaf.v13i5.1285-1291.7633
Fonseca M., Kurban D., Roy J. P., Santschi D. E., Molgat E., Yang D. A., Dufour S. (2025). Usefulness of differential somatic cell count for udder health monitoring: Identifying referential values for differential somatic cell count in healthy quarters and quarters with subclinical mastitis. Journal of Dairy Science; 108(4), 3917–3928. doi.: 10.3168/jds.2024-25403
Pan L., Chen X., Han D., Li N., Chen D., Wang J., Huo X. (2025). Machine learning-based clinical mastitis detection in dairy cows using milk electrical conductivity and somatic cell count. Frontiers in Veterinary Science; 12, 1671186. doi.: 10.3389/fvets.2025.1671186
Mikulec N., Spoljaric J., Plavljanic D., Lovric N., Ostaric F., Gajdos J., Kljusuric K., Sarim M., Zdolec N., Kazazic S. (2024). MALDI-TOF mass spectrometry-based identification of aerobic mesophilic bacteria in raw unpreserved and preserved milk. Processes; 12(4), 731. doi.: 10.3390/pr12040731
Miftari H., Nikolovska Nedelkoska D., Rampanti G., Harasym J., Ferrocino I., Ferati I., Cardinali F., Orkusz A., Milanovic V., Franciosa I., Garofalo C., Aquilanti L., Osimani A. (2026). A taste of North Macedonia: Seasonal variation in the microbiota, physico-chemical traits, and morpho-textural profile of a traditional brined raw goat's milk cheese. Food Research International; 231, 118806. doi.: 10.1016/j.foodres.2026.118806
Sadvari V. Y., Shevchenko L. V., Slobodyanyuk N. M., Tupitska O. M., Gruntkovskyi M. S., Furman S. V. (2024). Microbiome of craft hard cheeses from raw goat milk during ripening. Regulatory Mechanisms in Biosystems; 15(3), 483–489. doi.: 10.15421/022468
Zhao X., Zheng N., Zhang Y., Wang J. (2025). The role of milk urea nitrogen in nutritional assessment and its relationship with dairy cow phenotypes: A review. Animal Nutrition; 20, 33–41. doi.: 10.1016/j.aninu.2024.08.007
Vranje P., Popovic M., Jevtic M. (2015). Raw milk consumption and health. Srpski Arhiv za Celokupno Lekarstvo; 143(1–2), 87–92. doi.: 10.2298/SARH1502087P
Li Y., Jia H., Zheng Y., Sun X., Zhang Y., Liu W., Zhang W., Jiang Y., Zhao Q., Guo L. (2025). The nutritional composition and multi-omics analysis of raw milk from Normande and Holstein cows. Food Frontiers; 6(6), 3042–3058. doi.: 10.1002/fft2.70115
Yang Y., Wu X., Xu Y., Shuang Q., Xia Y. N. (2025). Influence of feeding systems on the microbial community and flavor characteristics of raw milk: A comparative analysis. Journal of Dairy Science; 108(5), 4693–4708. doi.: 10.3168/jds.2024-25959
Mykhailiutenko S. M., Kuzmenko L. M., Gutyj B. V., Mykhailiutenko Y. E. (2025). Seasonal fluctuations in individual milk parameters in free-range cows. Ukrainian Journal of Veterinary and Agricultural Sciences; 8(1), 85–89. doi.: 10.32718/ujvas8-1.12
Kotelevich V., Guralska S., Honcharenko V. (2023). Actual problems of the quality and safety of milk and dairy products. Naukovyi Visnyk Veterynarnoi Medytsyny; 1(180), 24–39. doi.: 10.33245/2310-4902-2023-180-1-24-39
Nuzzi C., Pasinetti S., Bassi I., Bello V. (2026). On the applicability of speckle pattern imaging combined with AI for raw milk classification. Measurement; 258, 119246. doi.: 10.1016/j.measurement.2025.119246
Curci D., Sundaram T. S., Ghidini S., Arioli F. (2025). What we know about per- and polyfluoroalkyl contamination levels in milk: A review from the last decade. Foods; 14(13), 2274. doi.: 10.3390/foods14132274
Kukeyeva A., Abdrakhmanov T., Yeszhanova G., Bakisheva Z., Kemeshov Z. (2023). The use of a homeopathic preparation in the treatment of subclinical mastitis in cows. Open Veterinary Journal; 13(8), 991–1002. doi.: 10.5455/OVJ.2023.v13.i8.5
Micules N., Spoljaric J., Plavljanic D., Darrer M., Ostaric F., Kljusuris J., Sarin K., Zdolec N., Kazazic S. (2025). Microbiota composition in raw drinking milk from vending machines: A case study in Croatia. Fermentation; 11(2), 55. doi.: 10.3390/fermentation11020055
Yuan H., Han S., Zhang S., Xue Y., Zhang Y., Lu H., Wang S. (2022). Microbial properties of raw milk throughout the year and their relationships to quality parameters. Foods; 11(19), 3077. doi.: 10.3390/foods11193077
International Organization for Standardization. (2008). Milk—Enumeration of somatic cells—Part 1: Microscopic method (Reference method) (ISO 13366-1:2008 | IDF 148-1:2008). https://www.iso.org/standard/40259.html
International Organization for Standardization. (2013). Microbiology of the food chain—Horizontal method for the enumeration of microorganisms—Part 1: Colony count at 30 °C by the pour plate technique (ISO 4833-1:2013). https://www.iso.org/standard/53728.html
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 One Health Journal
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
