Herd factors influencing free fatty acid concentrations in bulk tank milk.

Free fatty acid (FFA) concentrations can be elevated in raw milk due to improper handling and management at the dairy farm, and high concentrations of FFA can lead to off flavors in milk. This study aimed to describe how the herd production system, milking system, feeding and technological factors impact on FFA concentrations in bulk tank milk. FFA concentrations in bulk milk samples from 259 organic and 3326 conventional herds were analyzed by FT-IR during one year. The FFA content was significantly lower in bulk milk from organic than conventional herds. This was most evident during the summer half-year when the organic cows graze pasture. Bulk milk from automatic milking systems (AMS) and tie-stalls contained greater concentrations of FFA than any other milking parlor systems. In AMS, high milking frequency was found to be the most significant contributor to elevated FFA content in milk. Moreover, a strong interaction was found between milking interval and production system (organic vs. conventional). The technical factors, pre-cooling, onset time for cooling after milk inlet, contact between milk and agitation also impacted on the FFA concentration, whereas other technical factors including centrifugal pump type, length and height of pumping line and type of AMS manufacturer were found to be without significant effect on FFA. Feeding variables, based on feeding plans and evaluation, only explained a small part of the variation in bulk milk FFA. Overall, this study demonstrated that AMS compared to other milking system contributes significantly to increased FFA concentration in bulk tank milk, and within AMS high milking frequency contributes to increased FFA concentration.

Short communication: Genetic variation in choice consistency for cows accessing automatic milking units.

Dairy cows milked in automatic milking systems (AMS) with more than 1 milking box may, as individuals, have a preference for specific milking boxes if allowed free choice. Estimates of quantitative genetic variation in behavioral traits of farmed animals have previously been reported, with estimates of heritability ranging widely. However, for the consistency of choice in dairy cows, almost no published estimates of heritability exist. The hypothesis for this study was that choice consistency is partly under additive genetic control and partly controlled by permanent environmental (animal) effects. The aims of this study were to obtain estimates of genetic and phenotypic parameters for choice consistency in dairy cows milked in AMS herds. Data were obtained from 5 commercial Danish herds (I-V) with 2 AMS milking boxes (A, B). Milking data were only from milkings where both the present and the previous milkings were coded as completed. This filter was used to fulfill a criterion of free-choice situation (713,772 milkings, 1,231 cows). The lactation was divided into 20 segments covering 15d each, from 5 to 305d in milk. Choice consistency scores were obtained as the fraction of milkings without change of box [i.e., 1.0 - µ(box change)] for each segment. Data were analyzed for one part of lactation at a time using a linear mixed model for first-parity cows alone and for all parities jointly. Choice consistency was found to be only weakly heritable (heritability=0.02 to 0.14) in first as well as in later parities, and having intermediate repeatability (repeatability coefficients=0.27 to 0.56). Heritability was especially low at early and late lactation states. These results indicate that consistency, which is itself an indication of repeated similar choices, is also repeatable as a trait observed over longer time periods. However, the genetic background seems to play a smaller role compared with that of the permanent animal effects, indicating that consistency could also be a learned behavior. We concluded that consistency in choices are quantifiable, but only under weak genetic control.

L-lactate dehydrogenase and N-acetyl-beta-D-glucosaminidase activities in bovine milk as indicators of non-specific mastitis.

Systematic factors affecting the activities of L-lactate dehydrogenase (LDH) and N-acetyl-beta-D-glucosaminidase (NAGase) and somatic cell count (SCC), the association between the activities of LDH and NAGase and SCC with respect to udder health status, and the ability of LDH and NAGase to classify cows in udder health categories for early detection of mastitis were studied. A dataset of records from 74 Danish Holstein, 76 Danish Red and 47 Jersey cows on one research farm was used. Cows were grouped into healthy and clinically mastitic. A healthy cow was defined as having no veterinary treatment and SCC<100,000 cells/ml. A clinically infected cow was one receiving veterinary treatment after showing clinical signs of mastitis and SCC >800,000 cells/ml. Breed, month of production, and days in milk significantly influenced (P<0.001) LDH activity, NAGase activity and SCC in both healthy and clinically mastitic cows. In healthy cows, LDH activity, NAGase activity and SCC started at a high level immediately after calving and decreased to low levels approximately 30-40 d post partum. All the three parameters increased due to clinical mastitis. NAGase activity had numerically higher variation in healthy cows than in clinically mastitic cows (CV=56.2% v. CV=53.5%). The relationship between LDH activity and SCC was stronger in milk from clinically mastitic than from healthy cows (r=0.76 v. r=0.48 and r=0.67 v. r=0.44 for correlation of observed values and residuals, respectively). LDH activity had higher sensitivity than NAGase activity (73-95% v. 35-77%) while specificities were in a similar range (92-99%). Further, sensitivities for LDH activity were more robust to changes in the threshold value than those for NAGase activity. Opportunities for automated, in-line real-time mastitis detection are discussed.

Visual scoring of milk mixed with blood.

Sorting of normal and abnormal milk at time of milking is done visually for conventional milking systems, but more concrete standards are needed when milking is done in automatic milking systems (AMS). Several panel tests were carried out to find out how different consumer groups, milkers and advisors look at and respond to the visual appearance of milk mixed with blood, in order to set a limit for what they think is acceptable. It is concluded from the test panel results that milk samples with 0.4% or more of blood all will be scored as pink and samples with 0.1% blood (about 6 microM-haemoglobin or 100 mg/l) can be visually detected if they are compared with milk samples without blood. The consumer group scored fewer of the samples with 0-1% blood as normal than did the professional groups. The test panel scored 65% of the samples with 1% blood as normal when milk was presented in a black strip cup, which is the reference method when foremilking takes place in a conventional parlour. Only 2% of the milk samples with 2% blood (about 120 microM-haemoglobin or 2000 mg/l) were scored as normal in a black strip cup and should consequently be detected by conventional as well as automatic systems. One model of AMS was tested for its ability to detect and separate milk coloured by blood. The model separated milk with > or = 6 microM-haemoglobin. Milk mixed with blood injected into the milk stream for a short time at the beginning of milking was not separated. We lack data on how blood is naturally expelled into milk and in what amount. We propose that cow composite milk with > 6 microM-haemoglobin should be separated because at this level milk will have a red tinge.

Visual appearance and CMT score of foremilk of individual quarters in relation to cell count of cows milked automatically.

The objectives of the study were: to evaluate the interaction between visual appearance and California mastitis test (CMT) score of the foremilk in relation to the cell count of the milk; to evaluate the consequences of sorting milk according to these criteria; and to explore whether visual appearance and CMT score of foremilk depended on the time interval between milkings. Measuring somatic cell count (SCC) in composite milk only and discarding milk above certain thresholds will not ensure that milk from all cows with visually abnormal foremilk is withheld from delivery. Low thresholds of SCC will reduce the frequency of cows with abnormal milk but increase the discarding of milk from cows with visually normal foremilk. CMT score of foremilk differentiated better between cows with high and low SCC in composite milk than visual inspection of foremilk. CMT scores of foremilk decreased with increasing interval between milkings within cow, whereas the visual appearance was independent of the interval. We propose that visual appearance of the foremilk should be kept as a criterion for sorting milk at time of milking. For test purposes, the use of visual appearance of foremilk for differentiation between normal and abnormal milk has to be done on multiple milkings. Additionally, CMT scoring of foremilk improves correct classification of normal and abnormal quarters and especially when including data from the previous milking.