Short communication: Cow- and quarter-level milking indicators and their associations with clinical mastitis in an automatic milking system

Abstract

The aim of this study was to assess associations of cow-, udder-, and quarter-level factors with the risk of clinical mastitis (CM) in cows managed using an automatic milking system. The primary hypothesis was that quarter peak milk flow rate (QPMF) is associated with increased risk of CM. A retrospective, case-control study was undertaken using data from a 1,549 cow farm using 20 automatic milking system units. All data from cows milked during March to December 2015 was available for analysis. Cases (n = 82) were defined as cows diagnosed with their first case of CM between 24 and 300 d in milk in the current lactation. Healthy control cows (n = 6/case) were randomly matched based on identical parity, existence of milk records during the day in milk period corresponding to the 15-d window before case diagnosis, average conductivity of <5.5 mS/cm in that window, and no history of CM in the current lactation. Logistic regression was used to estimate effects of parity, quarter position, day in milk at diagnosis of CM, average of QPMF 15 d before CM diagnosis, udder milk yield, and milking interval on the probability of CM. Of the 6 predictor variables included in the model, only milking interval was significantly associated with the increased risk of quarter CM. We concluded that in a high-production, freestall-housed North American herd using automatic milking system, milking interval, but not QPMF, was associated with risk of CM.

Short communication: Teat-end shape and udder-level milking characteristics and their associations with machine milking-induced changes in teat tissue condition

“…Data from electronic on-farm milk meters that routinely measure milking characteristics have been established as measures of parlor performance (Reid and Stewart, 2007;Treichler and Reid, 2013), premilking udder preparation (Watters et al, 2012(Watters et al, , 2015, and assessment of liner performance . In addition, recent case-control studies have investigated the association of milking characteristics with the risk of clinical mastitis (Guarín and Ruegg, 2016;Penry et al, 2017a). However, the association with machine milking-induced short-term changes remains to be investigated.…”

Identifying changes in the milking rubber of milking machines during testing and under industrial conditions

“…This is another factor that increases the danger of infection of teats when using poor-quality milking rubber, in addition to the increased bacterial insemination. It was established in [9] that using the milking rubber that had lost its primary technological indicators such as elasticity, elasticity, integrity, etc., increases the likelihood of slipping off of the suspension part of the machine. An incomplete milking increases the propensity of teats to accept new infectious agents.…”

Development of a new clinical mastitis detection method for automatic milking systems

“…Previous studies have shown that the use of only EC in different detection algorithms was unable to achieve the ISO (2007) standard Se (>70%) and Sp (>99%) for CM detection (Khatun et al, 2017). In the past decade, many attempts have been made to improve the Se and Sp of CM detection using AMS data; however, they were not successful enough to detect at quarter level, and the search for an improved automated mastitis detection system continues (Claycomb et al, 2009;Hogeveen et al, 2010;Penry et al, 2017). Moreover, in a pasture-based AMS, where cows are less visible to the farmers compared with an indoor farming system, checking multiple alerts (either automatic or nonautomatic) to improve Se and Sp for detection of mastitis requires an increase in workload .…”

“…This might be explained by the effect of temperature, fat content, or milk fraction on EC measurements (Nielen et al, 1992;Bruckmaier et al, 2004). The decreasing trend (<0.429 mS/cm per hour, opposite to EC) of the ECH for the CM alert might be related to milking interval as mastitic cows are prone to have longer milking intervals, allowing longer harboring of the pathogens causing infection (Hogeveen et al, 2001;Hammer et al, 2012;Penry et al, 2017). Similar to a recent report by another group, our study did not find strong CM prediction ability of PF, which is considered an important breeding parameter (Penry et al, 2017).…”

“…The decreasing trend (<0.429 mS/cm per hour, opposite to EC) of the ECH for the CM alert might be related to milking interval as mastitic cows are prone to have longer milking intervals, allowing longer harboring of the pathogens causing infection (Hogeveen et al, 2001;Hammer et al, 2012;Penry et al, 2017). Similar to a recent report by another group, our study did not find strong CM prediction ability of PF, which is considered an important breeding parameter (Penry et al, 2017). The correlation of the parameters included in the final model ranged from −0.32 to 0.71, and PF was moderately correlated with MF (r = 0.76), but using the backward elimination procedure it was not included in the final multivariable model.…”