Viscosity method in robotic milking system for detection of somatic cell count in milk

Abstract

The objective of this study was to evaluate performance of automated measurement of whole milk somatic cell count (SCC) by the viscosity method. Gel viscosity of mixture from a small portion of whole milk and SCC indicator reagent was assumed to be related to the number of somatic cells in milk. The principle of detection was based on the length of the time necessary for the magnet to pass through the mixture. One farm with a milking robot equipped with an in-built processor for viscosity detection and permanent use was selected. Viscosity SCC data of 111 dairy cows were obtained from the management system of the milking robot for 4 consecutive days around the milk recording test-day. Whole milk samples from all cows were sent to the accredited dairy laboratory for detection of SCC by the fluoro-opto-electronic method (reference method). To characterize the performance of automated measurement of the viscosity method used to detect cows with high SCC (more than 200 000 cells•ml-1), measured by the reference method, the Cohen's kappa for all milking sessions was calculated. Qualitative agreement of SCC measurement by the viscosity method for the values below 100 000 or above 500 000 cells•ml-1 shows a reliable result already at one separate milking, whereas for the values between 100 000 and 500 000 cells•ml-1 an affirmation that SCC is more than 200 000 cells•ml-1 can be based on a calculated mean over 3 to 5 consecutive milkings (kappa = 0.81 ± 0.09).Quantitative agreement of the SCC results of the viscosity method is only moderate when compared to the laboratory method results. Viscosity method in robotic milking system for detection of milk somatic cell count as a possible tool for the evaluation of the cow udder health status is objective, informative, and has relatively low costs.

Sensitivity and Specificity for the Detection of Clinical Mastitis by Automatic Milking Systems in Bavarian Dairy Herds

“…Another sensor technique gaining importance in AMSs is the in-line measurement of SCC. These sensor systems use a defined milk sample volume and can determine SCC by either automated counting of stained, fluorescent nuclei [ 21 ] or by automated CMT [ 22 ]. Despite some non-infectious-related influences on SCC, such as breed [ 23 , 24 ], it is a commonly used gold standard for detecting udder health problems [ 13 ].…”