Technical note: Effects of attachment of hind teats before cleaning and attachment of front teats on milking characteristics in automatic milking systems

Milking characteristics differ between the 4 quarters of a dairy cow udder. In particular, milking time is mostly prolonged in hind quarters compared with front quarters because of the usually higher amount of stored milk. The standard milking routine (STDMR) in both conventional and automatic milking systems (AMS) consists of teat preparation of all 4 quarters, followed by attachment of the 4 teat cups, regardless of the distribution of milk between quarters. In the current study, an alternative teat preparation and milking routine (ALTMR) in AMS was tested, which consisted of cleaning and starting the milking of hind teats before cleaning and attachment of front teats. The hypothesis was based on the fact that hind quarters have usually a longer milking time than front quarters. Starting the milking of hind quarters while the front teats are being cleaned may reduce the difference in the end of milking between front and hind quarters and thus reduce total milking time. Both routines were tested on 5 Swedish dairy farms equipped with AMS in a 4-wk experiment in which treatments were alternated weekly. Total milk yield did not differ between treatments. Machine-on time (MOT) was longer in ALTMR than in STDMR because the difference in milking time between hind and front quarters was less than the time needed to prepare the front teats. However, the longer MOT in ALTMR was compensated by a shorter total preparation time, including the attachment of the first teat cup, as only the hind teats (instead of all 4 teats) were cleaned before milking was started. This resulted in a similar total milking time from start of cleaning of the first quarter until the end of milking of the last quarter in both treatments. Because of the prolonged MOT, average milk flow rate was lower in ALTMR than STDMR. Peak flow rate was higher in ALTMR than STDMR, but only in teat cups 1 (first attached, hind quarter) and 3 (third attached, front quarter), whereas main milk flow was higher in ALTMR than STDMR in both front quarters. In conclusion, splitting teat cleaning and the start of milking between hind and front quarters does not prolong total milking time, including teat cleaning. The partially positive effect on peak and main milk flow indicates that the ALTMR is a suitable milking routine in AMS. In herds with a greater difference of milk stored in hind compared with front quarters, a reduced total milking time can be expected for ALTMR.     

Comparison of functional aspects in two automatic milking systems and auto-tandem milking parlors

Milk yield, milking frequency, intermilking interval, teat-cup attachment success rate, and length of the milking procedure are important functional aspects of automatic milking systems (AMS). In this study, these variables were compared for 2 different models of AMS (AMS-1, with free cow traffic, and AMS-2, with selectively guided cow traffic) and auto-tandem milking parlors (ATM) on 4 farms each. Data on milking-stall visits and milkings of 20 cows were recorded on 3 successive days by means of video observations. Data were evaluated with mixed-effects models. Milk yield did not differ among the 3 milking systems. Milking frequency in the AMS was 2.47/d [95% confidence interval (CI) = (2.38, 2.56)], and was significantly higher than the 2 milkings/d in ATM. Milking frequency was lower for cows with a higher number of days in milk (DIM) in AMS-1 [change of −0.057/10 DIM, CI = (−0.070, −0.044)], but remained constant for cows with varying DIM in AMS-2 [change of −0.003/10 DIM, CI = (−0.034, 0.027)]. As a consequence, milking frequency was higher in early lactation [by 0.603, CI = (0.102, 1.103)] and lower in late lactation in AMS-1 than in AMS-2 [by −0.397, CI = (−0.785, −0.008)]. The intermilking interval showed the opposite pattern. Teat-cup attachment was more successful in AMS-1 than in AMS-2 (98.4 vs. 94.3% of the milkings), with some variation among farms (range: AMS-1 96.2 to 99.5%; AMS-2 91.5 to 96.1%). The length of the entire milking process did not differ among the milking systems [454 s, CI = (430, 478)], although the preparation phase was longer [changes in comparison with ATM: in AMS-1 by a factor of 2.90, CI = (2.30, 3.65), and in AMS-2 by 5.15, CI = (4.09, 6.48)] and the actual milking phase was shorter in both AMS-1 and AMS-2 than in ATM [changes in comparison with ATM: in AMS-1 by a factor of 0.76, CI = (0.62, 0.94), and in AMS-2 by 0.75, CI = (0.60, 0.93)]. The admission [changes in comparison with ATM: in AMS-1 by a factor of 2.56, CI = (1.55, 4.22), and in AMS-2 by 3.07, CI = (1.86, 5.08)] and preparation phases lasted longer in AMS-2 than in AMS-1, whereas the time required by the cows to leave the milking stall did not differ among the systems [changes in comparison with ATM: in AMS-1 by a factor of 0.89, CI = (0.55, 1.44), and in AMS-2 by 1.02, CI = (0.63, 1.66)]. In conclusion, different technical approaches to automatic milking led to differences in teat-cup attachment success rates, in the duration of several phases of the milking process, and in milking frequency. The capacity of an AMS could be further improved by shortening the preparation phase and reducing the proportion of failed milkings.     

Comparing technical efficiency of farms with an automatic milking system and a conventional milking system

Changing from a conventional milking system (CMS) to an automatic milking system (AMS) necessitates a new management approach and a corresponding change in labor tasks. Together with labor savings, AMS farms have been found to have higher capital costs, primarily because of higher maintenance costs and depreciation. Therefore, it is hypothesized that AMS farms differ from CMS farms in capital:labor ratio and possibly their technical efficiency, at least during a transition learning period. The current study used actual farm accounting data from dairy farms in the Netherlands with an AMS and a CMS to investigate the empirical substitution of capital for labor in the AMS farms and to determine if the technical efficiency of the AMS farms differed from the CMS farms. The technical efficiency estimates were obtained with data envelopment analysis. The 63 AMS farms and the 337 CMS farms in the data set did not differ in general farm characteristics such as the number of cows, number of hectares, and the amount of milk quota. Farms with AMS have significantly higher capital costs (€12.71 per 100 kg of milk) than CMS farms (€10.10 per 100 kg of milk). Total labor costs and net outputs were not significantly different between AMS and CMS farms. A clear substitution of capital for labor with the adoption of an AMS could not be observed. Although the AMS farms have a slightly lower technical efficiency (0.76) than the CMS farms (0.78), a significant difference in these estimates was not observed. This indicates that the farms were not different in their ability to use inputs (capital, labor, cows, and land) to produce outputs (total farm revenues). The technical efficiency of farms invested in an AMS in 2008 or earlier was not different from the farms invested in 2009 or 2010, indicating that a learning effect during the transition period was not observed. The results indicate that the economic performance of AMS and CMS farms are similar. What these results show is that other than higher capital costs, the use of AMS rather than a CMS does not affect farm efficiency and that the learning costs to use an AMS are not present as measured by any fall in technical efficiency.     

Short-term effect of transition from conventional to automated milking on teat skin and teat end condition

A higher milking frequency, as a consequence of milking with an automated milking system, incorporates a threat to teat condition. To study the effect of transition from conventional to automated milking on teat skin and teat end condition, 40 lactating Holstein-Friesian cows and heifers from a high yielding dairy herd were randomly allocated to either a conventional or an automated milking system group. In the latter group, automated milking was initiated during the study period, while conventional milking was continued in the control group. Teat skin and teat end condition were evaluated weekly on quarter level for all animals from 5 wk before until 8 wk after transition. A high emollient iodine teat dip was used on all cows during the study period. Teat skin condition of the animals in the automated milking system group was consistent from before and during milking with the automated milking system. Rear teats had a better skin and end condition than front teats. Evolution of teat end condition over time between the automated and conventional milking groups was not statistically different. Heifers, however, seemed to be more sensitive to the change than multiparous cows, as their teat end condition slightly decreased.     

The relationship between milking interval and somatic cell count in automatic milking systems

The aim of this study was to explore whether, during automatic milking, milking interval or its variation is related to somatic cell count (SCC), even when corrected for effects of production, lactation stage, and parity. Data on milking interval and production level were available from the automatic milking systems of 151 farms. Data on SCC, parity, and lactation stage were derived from dairy herd improvement records of the same farms. Mainly due to incomplete records, data of 100 farms were used in the final analysis. For every cow, only 1 test day was used in the final analysis. Milking interval, the coefficient of variation of milking interval, production rate, the difference in production rate between short- and long-term, parity, days in milk, and some biologically relevant interactions were used in a linear mixed model with farm as random variable to assess their association with log10-transformed SCC. None of the interactions was significantly related to SCC, whereas all main effects were, and thus, stayed in the final model. The effect of milking interval was, although significant, not very strong, which shows that the effect of milking interval on SCC is marginal when corrected for the other variables. The variation in milking intervals was positively related with SCC, showing that the variation in milking interval is even more important than the milking interval itself. In the end, this study showed only a limited association between milking interval and SCC when milking with an automatic milking system.     

Increased teat wall thickness in response to machine milking

Transiently increased teat wall thickness in response to machine milking has been documented by various methods, including ultrasound. However, correlative ultrasonography and histology to detect the origin of this phenomenon is lacking. The first goal of the present study was to evaluate and compare milking-related changes of the teat tissue in 2 breeds of dairy cows (11 Simmental and 3 Holstein) using B-mode ultrasonography. Additionally, the observed changes were compared with ultrasonographic findings in a Holstein cow with periparturient udder edema. Finally, corresponding histological sections of the Simmental teats were analyzed and compared with those from a lactating nonmilked Angus cow. We hypothesized that the mechanical load of both stretching by the vacuum during phases of open teat cup liner and compression by the closed liner during machine milking results in a transient congestion of blood vessels in the teat wall. The barrel of 1 front teat of each cow was scanned immediately before and after machine milking (system vacuum: 42 kPa; pulsation rate: 60 cycles/min; pulsation ratio: 65:35). Shortly after milking (33 ± 6 min), the Simmentals were slaughtered, and their scanned teat was immediately removed and processed for investigation by light microscopy. Ultrasonography after milking revealed anechoic tubular structures mainly in the inner half of the teat wall. Histological examination revealed these structures to be thick-walled veins. The left front and hind teats of the nonmilked lactating cow, collected and prepared identically to those from the Simmental cows, showed the same histological features. Ultrasonographic measurements showed that the diameter of these veins significantly increased after milking compared with matching images before milking. This effect was most pronounced in the Holstein cows. Similarly, these veins were very prominent in the periparturient cow. However, neither the milked cows, including the periparturient cow, nor the lactating nonmilked cow provided any evidence of edematous extravasation on ultrasonography or histology. These findings corroborated our hypothesis that the increase in size of thick-walled veins in the teat tissue is the main reason for the thickening of the teat walls in response to machine milking.     

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

Machine milking-induced changes in teat tissue condition, such as congestion and edema, have been associated with teat canal openness, penetrability, and thus susceptibility to new intramammary infections and diminished animal well-being. The primary objective of this study was to investigate the association of teat-end shape and machine milking-induced short-term changes in teat tissue condition. Our secondary objective was to study the association of udder-level milking characteristics and short-term changes. Data from 125 Holstein cows were analyzed in a longitudinal prospective cohort study. Cows were housed in freestall pens with sand bedding, fed a total mixed ration, and milked 3 times per day. Teat-end shape was classified into 3 categories: pointed, flat, and round. Udder-level milking characteristics were obtained from electronic on-farm milk meters. Short-term changes in teat tissue condition after machine milking were assessed visually. Multivariable generalized mixed model analysis showed an association between teat-end shape and short-term changes. Compared with teats with round teat-end shape, the odds ratio (95% confidence interval) for short-term changes was 1.68 (0.53–5.31) and 0.03 (0.004–0.19) in teats with pointed and flat teat-end shape, respectively. There was an association between milking characteristics and short-term changes such that higher milk flow rate during the first 15 s of milking decreased the likelihood of short-term changes. The adjusted probability of short-term changes for a milking observation of a mid-lactation cow and an average first 15-s milk flow rate of 0.5 and 1.5 kg/min was 53.0% (42.8–63.8) and 32.9% (15.2–57.3), respectively. Our results suggest that teat-end shape may be one of the risk factors that contribute to machine milking-induced short-term changes. Milking characteristics (e.g., first 15-s milk flow rate) may have the potential as a measure to indirectly monitor teat tissue changes associated with machine milking on a daily basis, though further research is needed to validate this hypothesis and to establish thresholds that could serve as on-farm guidelines.     

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

This study investigated the potential for accurate detection of clinical mastitis (CM) in an automatic milking system (AMS) using electronic data from the support software. Data from cows were used to develop the model, which was then tested on 2 independent data sets, 1 with 311 cows (same farm but from a different year) and 1 with 568 cows (from a different farm). In addition, the model was used to test how well it could predict CM 1 to 3 d before actual clinical diagnosis. Logistic mixed models were used for the analysis. Twelve measurements were included in the initial model before a backward elimination, which resulted in the following 6 measurements being included in the final model: quarter-level milk yield (MY; kg), electrical conductivity (EC; mS/cm), average milk flow rate (MF; kg/min), occurrence of incompletely milked quarters in each milking session (IM; yes or no), MY per hour (MYH; kg/h), and EC per hour (ECH; mS/cm/h) between successive milking sessions. The other 6 measurements tested but not included in the final model were peak milk flow rate (kg/min), kick-offs (yes or no) in each milking session, lactation number, days in milk (d), blood in milk (yes or no), and a calculated mastitis detection index used by DeLaval (DelPro software; DeLaval International AB, Tumba, Sweden). All measurements were assessed to determine their ability to detect CM as both individual variables and combinations of the 12 above-mentioned variables. These were assessed by producing a receiver operating characteristic curve and calculating the area under the curve (AUC) for each model. Overall, 9 measurements (i.e., EC, ECH, MY, MYH, MF, IM, peak flow rate, lactation number, and mastitis detection index) had significant mastitis detection ability as separate predictors. The best mastitis prediction was possible by incorporating 6 measurements (i.e., EC, ECH, MY, MYH, MF, and IM) as well as the random cow and quarter effects in the model, resulting in 90% sensitivity and 91% specificity with excellent AUC (0.96). Assessment of the model was found to produce robust results (AUC >0.9) in different data sets and could detect CM with reductions in sensitivity and specificity with increasing days before actual diagnosis. This study demonstrated that improved mastitis status prediction can be achieved by using multiple measurements, and new indexes based on that are expected to result in improved accuracy of mastitis alerts, thereby improving the detection ability and utility on farm.     

Effect of automatic milking systems on milk yield in a hot environment

A comparative study was performed to evaluate differences in milk yield between an automatic milking system (AMS) and a conventional herringbone milking parlor system. Two herds of Italian-Friesian cows were reared in the same barn, located in the Po Valley in northern Italy. Twenty-five primiparous cows and 10 multiparous cows were milked with an AMS, while at the same time 29 primiparous and 9 multiparous were milked twice daily in a milking parlor on the other side of the barn. A selection gate allowed cows to access the AMS only if the interval from last milking was >5 h. Multiparous cows in the AMS yielded more milk than multiparous cows in the milking parlor (34.2 ± 0.7 vs. 29.4 ± 0.6 kg/d). There was no difference in milk yield between primiparous cows in the AMS and in the milking parlor (28.9 ± 0.4 vs. 28.8 ± 0.3 kg/d). Milking frequency in the AMS was significantly higher in primiparous (2.8 ± 0.03) than in multiparous cows (2.5 ± 0.04). The hot season negatively affected milk yield; the milk yield reduction was higher for cows milked with the AMS (−4.5 ± 0.6 kg/d) than in the milking parlor (−3.0 ± 0.8 kg/d). In the AMS, milking frequency decreased during the hot season in primiparous cows (−0.3 ± 0.1). We concluded that a positive AMS effect on milk yield is possible, but that steps must be taken to alleviate the discomfort involved with attracting cows to the AMS.     

Effects of cleaning duration and water temperature on oxytocin release and milk removal in an automatic milking system

Four different methods of teat preparation during milking in an automatic milking system were studied in 2 experiments on Red Holstein/German Fleckvieh cross-breed cows. Milking routines used were milking: 1) without premilking teat preparation; 2) with one cleaning cycle (58 to 60 s) with cold (13 to 15 degrees C) water; 3) with one cleaning cycle with warm water (30 to 32 degrees C); or 4) with 2 cleaning cycles (122 s) with warm water. In experiment 1, milking characteristics were evaluated and milking routines were randomly assigned to 62 cows during 3 measuring periods of 24 h each. In experiment 2, 10 randomly selected cows were assigned to the same milking routines during 4 d and blood samples for oxytocin (OT) determination were taken during milking in addition to milk flow recording. Milk production, peak flow rate, total, and quarter milk yields showed no differences among treatments. Premilking preparation with cold water compared with warm water showed no differences in OT release, milk yield, peak flow rate, main milking time, average flow rate, or time until main milk flow. Baseline OT concentrations were consistently low. At the start of teat cup attachment without premilking teat preparation OT concentrations remained on the basal level but were elevated in all other treatments. By 30 s from the start of milking, OT concentrations were markedly increased in all treatments and were no longer different between treatments. In conclusion, the teat cleaning device used in the automatic milking system, either with warm or cold water, was suitable to induce milk ejection in cows before the start of milking.     

Association of quarter milking measurements and cow-level factors in an automatic milking system

The primary aim of this observational study, in a single herd milked using multiple automatic milking system units, was to describe associations of quarter milk yield variability and quarter peak milk flow rate with cow-level factors. Information from the current lactation of 1,549 primiparous and multiparous cows was collected from January to December 2015. Data from each individual milking used in the analysis included quarter milk yield (QMY), udder milk yield, quarter peak milk flow rate (QPMF), quarter average milk flow rate (QAMF), quarter milking time, and milking interval. Milking interval and milk yield were used to calculate milk production rate (kg/h) at the quarter and udder levels. We investigated associations between QPMF and milking interval, QPMF and days in milk, and QMY and QAMF. A strong association between QPMF and both QAMF and milking interval was observed. A moderate association was found between QPMF and stage of lactation. However, QMY was not a useful indicator of QPMF because of the weak association observed between these variables. In this study, rear quarter QPMF was significantly increased by 3% compared with front quarter QPMF (1.45 vs 1.41 kg/min). Quarter milk yield was calculated as a percentage contribution of total udder milk yield per 10-d in milk window and ranked from lowest to highest contribution. Quarter contribution to udder milk yield showed a high level of variability, with 39% of animals having all 4 quarters change contribution rank at least once during part of or the whole lactation. Only 14% of cows were observed to have no change in quarter rank. When quarter contribution was assessed, irrespective of physical position of quarter within the udder, the percent of highest to lowest contribution across the lactation was relatively stable. The standard deviation of quarter milk production rate for each cow was regressed against the same cow's peak udder milk production rate, within a lactation, to ascertain whether quarter milk production rate variance could be used to predict peak udder milk production rate. Knowledge of the intra-udder quarter milk production rate standard deviation for an individual cow is not useful in predicting peak udder milk production rate. Quarter milking time appears to be a useful indicator to predict the optimal order of teatcup attachment. Analysis from this large, single-herd population indicates that QPMF is associated with the cow-level factors milking interval and days in milk, and that intra-udder QMY is highly variable.     

Feeding patterns and performance of cows in controlled cow traffic in automatic milking systems

Two groups of dairy cows monitored from 3 to 19 wk postpartum were subjected to 2 different cow traffic routines in an automatic milking system with control gates and an open waiting area. Using different time settings in the control gates, the groups of cows were separated by average milking frequency; cows in the high milking frequency routine had a minimum of 4 h between milkings (MF₄) and were milked 3.2 ± 0.1 times daily, whereas cows in the low milking frequency routine had at least 8 h between milkings (MF₈) and were milked 2.1 ± 0.1 times daily. Cows in the 2 groups were switched to the opposite milking frequency control for wk 18 and 19. The increased milking frequency resulted in a higher milk yield of about 9% through 16 wk of early lactation Although the higher milk yield was not significant when measured as energy-corrected milk, significant interactions of milking frequency and study period for milk yield and energy-corrected milk yield were consistent with a yield response when cows were milked more frequently. Meal criteria estimated for each individual cow were used to group feeding visits into meals. During MF₄, cows fed in fewer meals per day and had longer meals than during MF₈. The control gates were used efficiently, with only a few passages not resulting in actual meals. Although the voluntary meal intervals seemed to be short, the average milking frequency was far below that theoretically possible. This was explained by individual differences in milking frequency and long intervals from when a cow was redirected in a control gate until it arrived in the milking unit. A wide individual range in the voluntary interval between the first and the second meal in the milking cycle suggests that fixed time limits for control gates set on group level have no justifiable biological basis. It was also concluded that primiparous cows were well adapted to the automatic milking system after 2 wk in the barn.     

Milk cortisol concentration in automatic milking systems compared with auto-tandem milking parlors

Milk cortisol concentration was determined under routine management conditions on 4 farms with an auto-tandem milking parlor and 8 farms with 1 of 2 automatic milking systems (AMS). One of the AMS was a partially forced (AMSp) system, and the other was a free cow traffic (AMSf) system. Milk samples were collected for all the cows on a given farm (20 to 54 cows) for at least 1 d. Behavioral observations were made during the milking process for a subset of 16 to 20 cows per farm. Milk cortisol concentration was evaluated by milking system, time of day, behavior during milking, daily milk yield, and somatic cell count using linear mixed-effects models. Milk cortisol did not differ between systems (AMSp: 1.15 ± 0.07; AMSf: 1.02 ± 0.12; auto-tandem parlor: 1.01 ± 0.16 nmol/L). Cortisol concentrations were lower in evening than in morning milkings (1.01 ± 0.12 vs. 1.24 ± 0.13 nmol/L). The daily periodicity of cortisol concentration was characterized by an early morning peak and a late afternoon elevation in AMSp. A bimodal pattern was not evident in AMSf. Finally, milk cortisol decreased by a factor of 0.915 in milking parlors, by 0.998 in AMSp, and increased by a factor of 1.161 in AMSf for each unit of ln(somatic cell count/1,000). We conclude that milking cows in milking parlors or AMS does not result in relevant stress differences as measured by milk cortisol concentrations. The biological relevance of the difference regarding the daily periodicity of milk cortisol concentrations observed between the AMSp and AMSf needs further investigation.     

Milk leakage--an increased risk in automatic milking systems

Milk leakage (ML), or milk observed dripping or flowing from one or more teats between milkings, has been associated with increased risk of udder infections and mastitis in dairy cows. Preliminary observations indicate that ML might occur more often in automatic milking systems (AMS) than in conventional milking systems (CMS), but comparative data on the incidence of ML in AMS or in CMS are not available. Therefore, the occurrence of ML at various observation periods was studied in one AMS with cows housed in a free-stall barn in comparison to CMS with cows housed either in a free-stall barn or a tie-stall barn and milked at regular intervals in a herringbone milking parlor. Relationships between ML and other cow and management factors were also examined. In each of 2 yr, all cows (n = 230 total; 46 cows present both years) were observed at 2-h intervals during six 24-h periods. At least one ML occurred in 39.0 (AMS) vs. 11.2% (CMS) of individual cows and in 16.2 (AMS) vs. 2.9% (CMS) of 24-h cow days studied. Milk leakage was not related to milk production, parity, stage of lactation, or estrous status. However, in the AMS, 62% of primiparous and 28% of multiparous cows leaked milk at least once. Milk leakage occurred more often in rear than in forequarters. Cows were usually lying down when ML was observed, but intervals from previous milking varied, especially in AMS. In AMS, about one-fifth of the ML observations occurred < or = 4 h after milking, and half of those were associated with disturbances at the previous milking. Milk flow rate was higher in quarters leaking milk than in other quarters. Strategies to reduce milk leakage in AMS may be important to minimize potential risks of udder disease.     

Effects of an automatic postmilking teat dipping system on new intramammary infections and iodine in milk

A technology of automatically applying a postmilking teat dip via the milking machine prior to machine detachment was compared to manual postmilking teat dipping with a teat dip cup for effects on new IMI and iodine content in milk. One hundred twenty Holstein cows were experimentally challenged in a 22-wk trial with Streptococcus agalactiae and Staphylococcus aureus and 148 Holstein cows were experimentally challenged with Streptococcus uberis in another 22-wk trial. The bacterial suspensions were applied to teats of all of the cows after premilking udder preparation and immediately prior to milking machine attachment. In both trials, cows were divided among four treatments: no postmilking teat dipping; manual postmilking teat dipping with a proven efficacious iodophor teat dip; manual postmilking teat dipping with an iodophor teat dip formulated for an automatic postmilking teat dipping system; and automatically postmilking teat dipping via milking machines with an iodophor teat dip formulated for the automatic postmilking teat dipping system. The postmilking teat dipping treatments reduced new Staph. aureus IMI by 64.5, 76.5, and 88.2%; new Strep. agalactiae IMI by 61.5, 77.8, and 94.4%; and new Strep. uberis IMI by 63.5, 82.5, and 93.8%, respectively, against the treatment of no postmilking teat dipping. The treatment applying the postmilking teat dip automatically via milking machines had the lowest number of new IMI caused by the three pathogens. Teat end and teat skin condition were characterized as normal at the end of the study with no differences between treatments. There were no differences with regard to iodine content in milk between treatments.     

Type of teat cup liner and cluster ventilation affect vacuum conditions in the liner and milking performance in dairy cows

The optimal milking cluster should milk as gently as possible to minimize the mechanical effect on the teat tissue at an optimal milking performance and milk quality. The objective of this study was to investigate the influence of liner shape (round vs. triangular) and type of cluster ventilation (claw vs. mouthpiece chamber; MPC) on milking performance and vacuum at the teat end and in the MPC. Our hypothesis was that liner shape and cluster ventilation affect milking performance and MPC vacuum. Six Holstein Friesian cows were milked twice daily over 12 d with a bucket milker, using 4 different cluster types that combined liner shape and type of cluster ventilation at 3 different system vacuum settings (35, 42, and 50 kPa) in an incomplete randomized block design. Milk flow and vacuum in the MPC, at the teat end (measured in the short milk tube), and in the short pulse tube were continuously recorded during milking. Milk flow was higher, and hence main milking time was shorter, with the round than with the triangular liners. The MPC vacuum was lower in round than triangular liners, which was caused by higher air leakage between teat and liner barrel in the triangular liners. The MPC vacuum, as well as its cyclic fluctuations, increased at the end of milking (immediately before cluster detachment) in all cluster types, with the highest amplitude of fluctuation in the triangular liners with MPC ventilation. The MPC ventilation reduced the MPC vacuum in both liner types at the end of milking, and also in triangular liners during peak milk flow. Despite the observed differences of MPC vacuum, the ventilation type did not affect milking performance. However, milking with triangular MPC-ventilated liners caused an increased proportion of foamed milk, which could potentially have a negative effect on milk quality.     

Analysis of feeding and drinking patterns of dairy cows in two cow traffic situations in automatic milking systems

With increasing possibilities for obtaining online information for individual cows, systems for individual management can be developed. Feeding and drinking patterns from automatically obtained records may be valuable input information in these systems. With the aim of evaluating appropriate mixed-distribution models for feeding and drinking events, records of 30 fresh cows from visits at feeding stations (n = 83,249) and water bowls (n = 67,525) were analyzed. Cows were either allowed a high-milking (HF) or a low-milking (LF) frequency by being subjected to controlled cow traffic with minimum milking intervals of 4 and 8 h, respectively. Milking frequency had significant effects on feeding patterns. The major part (84 to 98%) of the random variation in feeding patterns of the cows was due to individual differences between cows. It can be concluded that cows develop consistent feeding and drinking patterns over time that are characteristic for each individual cow. Based on this consistency, patterns of feeding and drinking activities have valuable potential for purposes of monitoring and decision making in individual control management systems. Use of a Weibull distribution to describe the population of intervals between meals increased the statistical fit, predicted biologically relevant starting probabilities, and estimated meal criteria that were closer to what has been published by others.     

The effect of two traffic situations on the behavior and performance of cows in an automatic milking system

Two cow traffic situations were tested sequentially in an automatic milking system (AMS) for effects on cow behavior, effective use of the barn, and milking capacity. The first situation was forced cow traffic: 63 cows had to pass through the AMS to go from the lying area to the feeding area. The second was semiforced cow traffic: 67 cows (60 cows from before) had free access to a forage feeding area at one end of the barn but could only access an area with concentrate feeders by passing through the AMS. Behavior of all cows was monitored as well as for two subsets of cows present in both situations: 8 cows with low frequency vs. 7 cows with high frequency of visits to the AMS. In each situation, cows were observed for 72 h. Cow locations and behavior were noted at 10-min intervals for all cows and individually for the selected cows. In semiforced traffic, the herd readily used the freely accessible forage feeding area, ate longer (17.4% of the day vs. 15.1 +/- 0.59%), and stood less in freestalls (9.0 vs. 11.8 +/- 0.30%) than when cow traffic was forced. Nonmilking visits to the AMS tended to decrease, whereas milking visits remained unchanged in the semiforced situation. The subset of cows that visited the AMS more often had fewer nonmilking visits (1.8 vs. 4.2 +/- 0.7) in the semiforced traffic situation whereas cows with low frequency of visits to the AMS had a nonsignificant increase (1.5 vs. 1.0) in nonmilking visits. Cows that visited the AMS frequently used the forage feeding area and the lying area next to it more than low frequency cows and use of those areas increased further during the semiforced situation. The semiforced cow traffic was deemed more desirable than forced cow traffic both for cows and for the capacity of the automatic milking system.     

Graduate Student Literature Review: Detecting health disorders using data from automatic milking systems and associated technologies

This review synthesizes a range of research findings regarding behavioral and production responses to health disorders and subsequent illness detection for herds using automatic (robotic) milking systems (AMS). We discuss the effects of health disorders on cow behavior and production, specifically those variables that are routinely recorded by AMS and associated technologies. This information is used to inform the resultant use of behavior and production variables and to summarize and critique current illness detection studies. For conventional and AMS herds separately, we examined research from the past 20 yr and those variables recorded automatically on-farm that may respond to development of illness and lameness. The main variables identified were milk yield, rumination time, activity, and body weight, in addition to frequency of successful, refused, and fetched (involuntary) milkings in AMS herds. Whether making comparisons within cow or between sick and healthy cows, consistent reductions in activity, rumination time, and milk yield are observed. Lameness, however, had obvious negative effects on milk yield but not necessarily on rumination time or activity. Finally, we discuss detection models for identifying lameness and other health disorders using routinely collected data in AMS, specifically focusing on their scientific validation and any study limitations that create a need for further research. Of the current studies that have worked toward disease detection, many data have been excluded or separated for isolated models (i.e., fresh cows, certain lactation groups, and cows with multiple illnesses or moderate cases). Thus, future studies should (1) incorporate the entire lactating herd while accounting for stage of lactation and parity of each animal; (2) evaluate the deviations that cows exhibit from their own baseline trajectories and relative to healthy contemporaries; (3) combine the use of several variables into health alerts; and (4) differentiate the probable type of health disorder. Most importantly, no model or software currently exists to integrate data and directly support decision-making, which requires further research to bridge the gap between technology and herd health management.     

Milk quality on Danish farms with automatic milking systems

The bulk-milk quality of 98 Danish farms with automatic milking systems was analyzed from 1 yr before introduction of automatic milking until 1 yr after. Bulk-milk total bacterial count, spores of anaerobes, somatic cell count (SCC), and freezing point increased when automatic milking was introduced and the frequency of milk-quality failures almost doubled. Milk-quality failures were most frequent in the first 3 mo after the start of automatic milking. The increase in spores of anaerobes indicated that the increase in total bacterial count originated partly from contamination of milk from the teat surface and partly from lack of cleaning of the milking equipment or cooling of the milk. The increase in bulk-milk SCC indicated that milk from clinically infected cows and cows with high cell counts was not diverted to the same degree, milking automatically rather than milking conventionally. A self-monitoring program including survey of the bulk-milk quality was established to help farmers in the transition period going from conventional to automatic milking. The program was introduced on 84 farms. Farms on the self-monitoring program reduced bulk-milk cell count. Application of the program did not reduce the frequency of high total bacterial counts and freezing points of the bulk milk to the level of conventional milking. However, the program reduced the overall frequency of milk-quality failures.