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Effectiveness of mastitis detection index for cow monitoring and abnormal milk detection in milking robots

Ivars Lūsis, V. Antāne, Armins Laurs

发表年份
2017
引用次数
13
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摘要

The aim of the study was to evaluate the effectiveness of the Mastitis Detection index (MDi) for detection of cows with a high somatic cell count (SCC) during milking in the milking box of the DeLaval milking robot. The MDi takes conductivity, milking intervals and blood presence into consideration. All these factors and SCC dynamics were analyzed in 20 cows during a three-week period. The MDi was compared between the experimental group (cows with initial MDi 1.4 or more, n = 10) with the control group (cows with initial MDi from 1.0 to 1.3, n = 10). Results have indicated that the MDi and milk conductivity in the experimental group were significantly (p < 0.05) higher compared with the control group cows (mean (SD) 1.40 (0.29) vs 1.06 (0.06) and 4634 (469.4) vs 4562 (366.9) Scm -1 ). There were significantly longer milking intervals (12 hours and more), and consequently less number of the milking sessions per day in the experimental group (2.3 (0.74) vs 2.6 (0.72) (p < 0.05). In total, the experimental group has significantly higher log 2 SCC 3.4 (1.53) vs 2.4 (1.45). To characterize the overall effectiveness of the MDi for detection of cows with SCC above 200 000 cells ml -1 of milk the Cohen`s kappa from 430 milking sessions were calculated and the agreement was found to be less than moderate (kappa = 0.28 0.048). Besides that, the threshold values of the MDi for automatic divert of abnormal milk were modeled. If the threshold is set as high as 2.0, the SCC of diverted milk would be around 422 000 cells ml -1 and total amount of diverted milk would be 2.3 % of all milk production. At the same time, the bulk tank SCC would be as low as 155 000 cellsml -1 . Any lover threshold would increase the amount of diverted milk, however, the somatic cell count in the bulk tank would decrease even lower.

关键词

MilkingMastitisIndex (typography)RobotComputer scienceArtificial intelligenceBiologyAnimal scienceMicrobiology

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