Milk-flow data collected routinely in an automatic milking system: an alternative to milking-time testing in the management of teat-end condition?

Pathogen-specific patterns of milking traits in automatic milking systems

Early detection of intramammary infection (IMI) can improve animal health and welfare in dairy herds. The implementation of sensors and automatic milking systems (AMS) in dairy production inherently increases the amount of available data and hence also the potential for new approaches to mastitis management. To utilize the full potential of data from AMS and auxiliary sensors, a better understanding of physiological and pathological changes in milking traits associated with different udder pathogens may be imperative. This observational study aimed to investigate pathogen-specific patterns in milking traits recorded in AMS. The milking traits included; online somatic cell count (OCC), electrical conductivity (EC), milk yield (MY), and average milk flow rate (AMF). Data were collected for a study period of 2 years and included 101 492 milkings from 237 lactations in 169 cows from one farm. Measurements of OCC were recorded at cow-level and data on EC, MY, and AMF were obtained at quarter-level. In addition to the data obtained from the AMS, altogether 5756 quarter milk samples (QMS) were collected. Milk samples were obtained monthly for bacteriological culturing. We included findings of 13 known mastitis pathogens to study pathogen-specific patterns in milking traits. These patterns were compared with those in a baseline group consisting of cows that did not have any positive milk culture results throughout the lactation period. Patterns of the milking traits are described for all positive samples both across 305 d in milk (DIM), and in the 15-d period before a positive bacteriological sample. The association between a positive sample and the milking traits (ln(OCC), EC-IQR; the ratio between the quarter with the highest and the quarter with the lowest level of EC, and MY) for the 15 d before the detection of a pathogen was assessed using mixed effects linear regression models. All pathogens were associated with alterations in the level and variability of ln(OCC) relative to lactations with no positive bacteriological samples. A positive sample for Staph. aureus was associated with increased values for MY during the 15 d before a positive diagnosis. It is biologically plausible to interpret changes in OCC and EC-IQR as consequences of an intramammary infection (IMI), while higher MY in bacteriologically-positive cows is most likely linked to the increased risk of infection in high-yielding cows. In this study, the most notable changes in the traits (OCC and EC-IQR) were observed for Staph. aureus and Strep. dysgalactiae, followed by Strep. simulans, Strep. uberis, and Lactococcus lactis. Even if we did not detect significant associations between positive bacteriology and EC-IQR, visual assessment and descriptive statistics indicated that there might be differences suggesting that it could be an informative trait for detecting infection when combined with OCC and possibly other relevant traits using machine learning algorithms.

Complex Relationships between Milking-Induced Changes in Teat Structures and Their Pre-Milking Dimensions in Holstein Cows

The study aimed to explore the relationship between teat structure dimensions and their short-term reaction to milking, to find the optimal dimensions of teat structures in relation to milking-induced teat tissue changes. Teat structures (teat length, canal length, thickness at barrel and apex, wall and cistern width) were measured by ultrasonography before and after milking for 38 Holstein cows at the beginning, middle, and end of lactation. We found that milking-induced changes in teat structures significantly depended on their pre-milking size. Furthermore, we observed that some teat structures and their changes were interconnected, and some did not affect each other. For example, changes in the barrel thickness and cistern width were affected by all structures, while the canal and apex did not influence each other. We deduced that more favorable changes were observed for teats of medium length, medium barrel and apex thickness, with teat canals of medium length, but with wider cisterns and thinner walls. The results of this study may help improve research in the area of milking-induced changes in teat morphology. Our findings could help understand potential health risks to animals in relation to teat morphology, milking equipment, and machine settings.

The prevalence of Campylobacter spp., Listeria monocytogenes and Shiga toxin-producing Escherichia coli in Norwegian dairy cattle farms; a comparison between free stall and tie stall housing systems

Aims

This study explored how dairy farm operating systems with free‐stall or tie‐stall housing and cow hygiene score influence the occurrence of zoonotic bacteria in raw milk.

Methods and Results

Samples from bulk tank milk (BTM), milk filters, faeces, feed, teats and teat milk were collected from 11 farms with loose housing and seven farms with tie‐stall housing every second month over a period of 11 months and analysed for the presence of STEC by culturing combined with polymerase chain reaction and for Campylobacter spp. and L. monocytogenes by culturing only. Campylobacter spp., L. monocytogenes and STEC were present in samples from the farm environment and were also detected in 4%, 13% and 7% of the milk filters, respectively, and in 3%, 0% and 1% of BTM samples. Four STEC isolates carried the eae gene, which is linked to the capacity to cause severe human disease. L. monocytogenes were detected more frequently in loose housing herds compared with tie‐stalled herds in faeces (p = 0.02) and feed (p = 0.03), and Campylobacter spp. were detected more frequently in loose housing herds in faeces (p < 0.01) and teat swabs (p = 0.03). An association between cow hygiene score and detection of Campylobacter spp. in teat milk was observed (p = 0.03).

Conclusion

Since some samples collected from loose housing systems revealed a significantly higher (p < 0.05) content of L. monocytogenes and Campylobacter spp. than samples collected from tie‐stalled herds, the current study suggests that the type of housing system may influence the food safety of raw milk.

Significance and Impact of the Study

This study highlights that zoonotic bacteria can be present in raw milk independent of hygienic conditions at the farm and what housing system is used. Altogether, this study provides important knowledge for evaluating the risk of drinking unpasteurized milk.

Vacuum Dynamics as an Alternative Method for Detection of Bimodal Milk Ejection in Dairy Cows

Simple Summary

We investigated the relationship between vacuum dynamics and milk flow curve characteristics using portable vacuum and milk flow recording devices, respectively, for the assessment of bimodal milk flow curves in dairy cows. For this purpose, we analyzed 241 vacuum and milk flow curve recordings that we collected concomitantly during eight milking center evaluations on five New York dairy farms. We found that vacuum dynamics could be a suitable measure to assess bimodal milk flow curves in dairy cows.

Abstract

The primary objective of our study was to assess the ability of a vacuum recorder to detect the presence of bimodal milk flow curves in dairy cows compared with a portable milk flow meter. In a cross-sectional study, 241 individual cow milking observations were analyzed. We simultaneously collected (1) individual cow vacuum events during milking using portable vacuum recorders, and (2) individual cow milk flow curves by attaching a portable milk flow meter to the same milking unit. Presence of bimodality was assessed with the vacuum recorder visually (BIM_VA) and with the gold standard method of a milk flow meter through automatic detection (BIM_LA). Kappa statistics revealed moderate agreement between BIM_VA and BIM_LA [κ, 95% confidence intervals (95% CI) = 0.59 (0.46–0.71)]. Diagnostic test statistics for BIM_VA for detection of bimodality indicated moderate performance for sensitivity [0.65 (0.52–0.76)] and positive predictive value [0.71 (0.58–0.82)] and high values for specificity [0.92 (0.87–0.95)] and negative predictive value [0.93 (0.84–0.93)]. We conclude that milking vacuum dynamics are a suitable measure to assess bimodal milk flow curves in dairy cows.

Feasibility of the use of deep learning classification of teat-end condition in Holstein cattle

Infections with pathogenic bacteria entering the mammary gland through the teat canal are the most common cause of mastitis in dairy cows; therefore, sustaining the integrity of the teat canal and its adjacent tissues is critical to resist infection. The ability to monitor teat tissue condition is a key prerequisite for udder health management in dairy cows. However, to date, routine assessment of teat condition is limited to cow-side visual inspection, making the evaluation a time-consuming and expensive process. Here, we demonstrate a digital teat-end condition assessment by way of deep learning. A total of 398 digital images from dairy cows' udders were collected on 2 commercial farms using a digital camera. The degree of teat-end hyperkeratosis was scored using a 4-point scale. A deep learning network from a transfer learning approach (GoogLeNet; Google Inc., Mountain View, CA) was developed to predict the teat-end condition from the digital images. Teat-end images were split into training (70%) and validation (15%) data sets to develop the network, and then evaluated on the remaining test (15%) data set. The areas under the receiver operator characteristic curves on the test data set for classification scores of normal, smooth, rough, and very rough were 0.778 (0.716-0.833), 0.542 (0.459-0.608), 0.863 (0.788-0.906), and 0.920 (0.803-0.986), respectively. We found that image-based teat-end scoring by way of deep learning is possible and, coupled with improvements in image acquisition and processing, this method can be used to assess teat-end condition in a systematic and efficient manner.

Review: Milking machine settings, teat condition and milking efficiency in dairy cows

Because of technical limitations, an impact of machine milking on the teat tissue cannot be avoided. The continuance of this impact during and after milking depends on a variety of factors related to the physiological regulation of milk ejection, as well as the different production systems and milking machine settings. Milking machine settings aim to achieve a high milking performance, that is, short machine-on time at a maximum of milk harvest. However, a high milking performance level is often related to an impact on the teat tissue caused by vacuum or liner compression that can lead to pathological dimensions of congestion of the tissue or hyperkeratosis as a long-term effect. Toward the end of milking a decrease of milk flow rate causes a raise of mouthpiece and teat end vacuum levels and hence an increase of the impact on the teat tissue and the risk of tissue damage. The mechanical stress by the milking machine activates a cascade of cellular mechanisms that lead to an excessive keratin growth and thickening of the keratin layer. Consequently, a complete closure of the teat canal is disabled and the risk of bacterial invasion and intramammary infection increases. Another consequence of high vacuum impact is fluid accumulation and congestion in the tissue of teat tip and teat basis because of an obstruction in venous return. The present review paper provides an overview of the available scientific information to describe the interaction between different levels and types of system vacuum, mouthpiece chamber vacuum, teat end (claw) vacuum, liner pressure, and the risk of short-term and long-term impacts on the teat tissue.

Large-scale cross-sectional study of relationships between somatic cell count and milking-time test results in different milking systems

Milking-time testing (MTT) is a method for evaluating the vacuum conditions in the teatcup during milking. The purpose is to evaluate the possible impact of the milking and milking equipment on udder health and milk quality. The method is commonly implemented by herd health advisory services, but results are interpreted empirically due to lack of scientific documentation on relationships between MTT result variables and objective measures of udder health. The current study was conducted to increase our understanding of associations between cow-level differences in composite milk somatic cell count (CMSCC) and MTT results in dairy cows milked in 3 different milking systems; automatic milking systems (AMS), milking parlors, and pipeline milking systems. Data from 7069 cows (predominantly Norwegian Red breed) in 1009 herds were used in a cross-sectional study. Multilevel linear regression models with a random intercept at herd level were used to describe relationships between CMSCC (on logarithmic scale) and the following MTT explanatory variables: average vacuum level in the short milk tube and mouthpiece chamber in the main milking and overmilking periods, the duration of these two periods, and vacuum stability, measured by sudden vacuum drops in the short milk tube. The models were corrected for the herd effect, mastitis history and differences in milk yield, lactation stage and parity between cows. Separate models were run for AMS, milking parlors, and pipeline milking systems, because this approach allowed for comparison between systems and for evaluation of the herd effect independently of milking system. The models described 8-10 % of the variation in CMSCC, indicating that MTT could only explain a relatively small proportion of a large total variation in CMSCC. In most observations, vacuum levels in the short milk tube during main milking were within the range recommended by the International Organization for Standardization. The results from our multivariable models showed decreasing CMSCC with increasing vacuum level in the short milk tube during the main milking period in AMS and milking parlors. Similarly, decreasing CMSCC was also associated with increasing duration of the main milking period in all 3 systems. These relationships are important for the interpretation of MTT results under practical conditions; finding high vacuum levels and long milking durations in a MTT is not associated with elevated CMSCC. In AMS herds, we also found indications that the relationships were different for cows where a case of mastitis had been treated before the MTT.