Mastitis is one of the most common health problems in dairy farming and affects milk quality, milk quantity and animal welfare (Halasa et al., 2007; Hogeveen et al., 2019). SCC is a parameter that is often used for (sub)clinical mastitis diagnosis and, therefore, this parameter is used to improve udder health. A rapid increase in SCC in milk signals inflammation of the udder (Sharma et al., 2011). Cell counting is therefore relevant in monitoring animal health and triggering proper farm management decisions (Schukken et al., 2003). SCC insights at the Lely Astronaut are gathered via the Milk Quality Control-Cell Count (MQC-C).
The Lely Milk Quality Control Cell Count (MQC-C)
The Lely MQC-C is an additional feature on the Lely Astronaut and makes it possible to detect mastitis at an early stage. The device takes a milk sample and adds a reagent liquid to the sample. A cell count indication is then generated based on the viscosity of the sample. This test is based on the same principle as a California Mastitis Test. In this test, milk samples are collected and, after adding reagent, the mixture can thicken. The more (inflammatory) cells present in the milk, the thicker the mixture becomes.
The MQC-C performs a test every three milkings (with smart sampling). However, should the test result in a high SCC (> 250,000 cells/ml), the MQC-C takes a sample of every milking to generate a more detailed udder health profile. The MQC-C test is a screening tool, meaning it indicates suspicion of a disease. The intermediate time of measurements via a laboratory can be up to 6 weeks. Measuring SCC frequently with the help of the MQC-C helps in monitoring udder health at cow level (Deng et al., 2020).
Rapid detection of (sub)clinical mastitis
Close monitoring of individual cow udder health is essential for identification of cows in the early stages of an intramammary infection, as well as timely initiation of treatment and assessment of recovery. With the Lely Astronaut, a farmer can rely on online sensor systems for the identification of milk of cows with an intramammary infection (Sørensen et al., 2016).
Research revealed that the performance of a mastitis detection system improves when SCC information is added to a detection model using conductivity information (Kamphuis et al., 2008; Kaşikçi et al., 2012). Lely Horizon (report 10, 12 and 23) combines the information from all milk sensors on the Astronaut (conductivity, colour, temperature, milking speed, milk production, milk times, dead milk times, fat and protein indications) and processes this information in (udder) health tasks. The farmer is notified of any changes in good time, which results in better recovery times since the cows in the early stages of an intramammary infection can be identified quickly.
The MQC-C is a great tool for screening cows suspected of having intramammary infection since timely initiation of treatment is important for good recovery.
Deng, Z., Hogeveen, H., Lam, T. J. G. M., van der Tol, R., & Koop, G. (2020). Performance of Online Somatic Cell Count Estimation in Automatic Milking Systems. Frontiers in Veterinary Science, 7(April). https://doi.org/10.3389/fvets.2020.00221
Halasa, T., Huijps, K., Østerås, O., & Hogeveen, H. (2007). Economic effects of bovine mastitis and mastitis management: A review. The Veterinary Quarterly, 29(1), 18–31. https://doi.org/10.1080/01652176.2007.9695224
Hogeveen, H., Steeneveld, W., & Wolf, C. A. (2019). Production Diseases Reduce the Efficiency of Dairy Production : A Review of the Results, Methods, and Approaches Regarding the Economics of Mastitis. Annual Review of Resource Economics, 11, 289–312. https://doi.org/10.1146/annurev-resource-100518-093954
Kamphuis, C., Sherlock, R., Jago, J., Mein, G., & Hogeveen, H. (2008). Automatic Detection of Clinical Mastitis Is Improved by In-Line Monitoring of Somatic Cell Count. Journal of Dairy Science, 91(12), 4560–4570. https://doi.org/10.3168/jds.2008-1160
Kaşikçi, G., Çetin, Ö., Bingöl, E. B., & Gündüz, M. C. (2012). Relations between electrical conductivity, somatic cell count, California mastitis test and some quality parameters in the diagnosis of subclinical mastitis in dairy cows. Turkish Journal of Veterinary and Animal Sciences, 36(1), 49–55. https://doi.org/10.3906/VET-1103-4
Schukken, Y. H., Wilson, D. J., Welcome, F., Garrison-Tikofsky, L., & Gonzalez, R. N. (2003). Monitoring udder health and milk quality using somatic cell counts. Veterinary Research, 34, 579–596. https://doi.org/10.1051/vetres
Sharma, N., Singh, N. K., & Bhadwal, M. S. (2011). Relationship of Somatic Cell Count and Mastitis :An Overview. Journal of Animal Sciences, 24(3), 429–438. https://doi.org/https://doi.org/10.5713/ajas.2011.10233
Sørensen, L. P., Bjerring, M., & Løvendahl, P. (2016). Monitoring individual cow udder health in automated milking systems using online somatic cell counts. Journal of Dairy Science, 99(1), 608–620. https://doi.org/10.3168/jds.2014-8823