Assessment of subclinical mastitis diagnostic accuracy by differential cell count in individual cow milk

• Published in: Italian journal of animal science Vol. 18; no. 1; pp. 460 - 465
• Main Authors: Zecconi, Alfonso, Vairani, Diego, Cipolla, Micaela, Rizzi, Nicoletta, Zanini, Lucio
• Format: Journal Article
• Language: English
• Published: Bologna Taylor & Francis 02.01.2019; Taylor & Francis Ltd; Taylor & Francis Group
• Subjects: Accuracy; Cow's milk; differential somatic cell count; Herd management; Mastitis; Milk; Milking; Reviews; somatic cell count; subclinical mastitis
• ISSN: 1828-051X; 1594-4077; 1828-051X
• DOI: 10.1080/1828051X.2018.1533391

The progressive decrease of mean SCC in dairy herds worldwide is affecting SCC accuracy as a subclinical mastitis marker. This evidence supports studies aiming to apply differential cell count (DSCC) as a tool to identify mastitis. Two of the major obstacles to apply DSCC were the unavailability of high-throughput milk analysers and the cost of these analyses. Recently availability of high-throughput milk analysers, able to perform a partial DSCC on milk, allowed designing a study aiming to identify subclinical mastitis in individual milk samples. This paper reports the result of this first Italian study performed under field conditions. The study considered 4386 milk test records from four dairy herds with different size, management and milking management. DSCC data were analysed by ROC procedure. This procedure allows identifying the threshold giving the highest accuracy and the highest combined value for sensitivity and specificity, among all the possible thresholds. Among the different ways used to classify milk samples, the analysis applied to days in milk (three classes) showed the highest mean values for sensitivity plus specificity, and the value for accuracy was very close to the highest one observed. At the time of submission, this is the first paper available on peer-reviewed scientific journals reporting the evaluation of DSCC as a marker for subclinical mastitis on individual milk samples collected during routine milk test. The results will help the improvement of mastitis diagnosis and will help dairy farmers to increase the levels of herd management and efficiency. Highlights At the time of submission, this is the first paper available on peer-reviewed scientific journals on the evaluation of DSCC as a marker for subclinical mastitis on individual milk samples. The analysis of data showed as DSCC has not consistent performances, confirming the presence of confounding factors such as parity and days in milk. The thresholds calculated on samples classified by days in milk (three classes) showed to have the overall best test performances with an accuracy of 82.3%.