Effect of liner design,pulsator setting,and vacuum level on bovine teat tissue changes and milking characteristics as measured by ultrasonography

: Friesian-type dairy cows were milked with different machine settings to determine the effect of these settings on teat tissue reaction and on milking characteristics. Three teat-cup liner designs were used with varying upper barrel dimensions (wide-bore WB = 31.6 mm; narrow-bore NB = 21.0 mm; narrow-bore NB1 = 25.0 mm). These liners were tested with alternate and simultaneous pulsation patterns, pulsator ratios (60:40 and 67:33) and three system vacuum levels (40, 44 and 50 kPa). Teat tissue was measured using ultrasonography, before milking and directly after milking. The measurements recorded were teat canal length (TCL), teat diameter (TD), cistern diameter (CD) and teat wall thickness (TWT).Teat tissue changes were similar with a system vacuum level of either 50 kPa (mid-level) or 40 kPa (low-level). Widening the liner upper barrel bore dimension from 21.0 mm (P < 0.01) or 25.0 mm (P < 0.001) to 31.6 mm increased the magnitude of changes in TD and TWT after machine milking. Milk yield per cow was significantly (P < 0.05) higher and cluster-on time was reduced (P < 0.01) with the WB cluster as compared to the NB1 cluster. Minimum changes in teat tissue parameters were achieved with system vacuum level of 40 kPa and 50 kPa using NB and WB clusters, respectively. Similar changes in teat tissue and milk yield per cow were observed with alternate and simultaneous pulsation patterns. Widening pulsator ratio from 60:40 to 67:33 did not have negative effects on changes in teat tissue and had a positive effect on milk yield and milking time. Milk liner design had a bigger effect on teat tissue changes and milking characteristics than pulsation settings.     

Effect of vacuum level on milking efficiency, somatic cell counts (SCC) and teat end wall thickness in ewes of Greek mountain Boutsiko breed

The aim of this work was to determine the effect of vacuum level of machine milking on milk yield, milk composition, milking efficiency, somatic cells counts (SCC), and teat end thickness of the Greek mountain breed Boutsiko ewes. Seventy two ewes after a suckling period of 45 ± 5 days were divided into three equal groups of 24 animals for level of milk production, prolificacy and lactation number. The overall experiment lasted 14 weeks. All groups were milked with a pulsation rate of 120/min, pulsator ratio of 50/50, and three vacuum levels of 38, 44 and 50 kPa, respectively, were applied for the three groups. Every two weeks, in a.m. and p.m. milking, measurements were taken for machine milk (MM) and machine stripped milk (MSM), milk composition, SCC, milk emission characteristics (only in a.m. milking) and teat end wall thickness (TEWT) before and after milking. The results have shown that the lower vacuum level of 38 kPa increased (P < 0.05) the percentage of machine milk (82.9%). There were no significant differences among the groups for milk composition, milk flow rate and SCC, but there was a difference in log SCC (P < 0.05) between 38 and 50 kPa. The teat end wall thickness was lower at the lower vacuum level (38 kPa) after milking, and increased (P < 0.001) as the vacuum level was raised to 50 kPa. The findings of this study suggest that with a lower vacuum level of 38 kPa, the ewes are milked better than those with 44 or 50 kPa. Also, the irritation of teats is considerably reduced, while no differences were seen regarding the health of the udder.     

Analysis of factors affecting milking claw vacuum levels using a simulated milking device

Bovine mastitis is typically caused by microbial infection of the udder, but the factors responsible for this condition are varied. One potential cause is the milking system, and although previous studies have investigated various methods for inspecting these devices, most have not assessed methods for evaluating the milking units. With this in mind, we analyzed the factors that affect the vacuum inside the milking claw by using a simulated milking device and by measuring milking claw vacuum when adjusting the flow rate in five stages. The factors analyzed in each milking system were the vacuum pressure settings (high and low line system) , milk tube length (200‐328 cm), aperture diameter (14‐22.2 mm), constricted aperture diameter (12 mm), tubing configurations, lift formation (0‐80 cm), claw type (bottom and top flow) and use or non‐use of a milk sampler. The study findings demonstrated that all of these variables had a significant impact on claw vacuum and suggest that a diagnostic method using a simulated milking device should be considered when inspecting modern milking systems.     

Milking performance evaluation and factors affecting milking claw vacuum levels with flow simulator

Milking performance of milking machines that matches the production capability of dairy cows is important in reducing the risk of mastitis, particularly in high‐producing cows. This study used a simulated milking device to examine the milking performance of the milking system of 73 dairy farms and to analyze the factors affecting claw vacuum. Mean claw vacuum and range of fluctuation of claw vacuum (claw vacuum range) were measured at three different flow rates: 5.7, 7.6 and 8.7 kg/min. At the highest flow rate, only 16 farms (21.9%) met both standards of mean claw vacuum ≥35 kPa and claw vacuum range ≤ 7 kPa, showing that milking systems currently have poor milking performance. The factors affecting mean claw vacuum were claw type, milk‐meter and vacuum shut‐off device; the factor affecting claw vacuum range was claw type. Examination of the milking performance of the milking system using a simulated milking device allows an examination of the performance that can cope with high producing cows, indicating the possibility of reducing the risk of mastitis caused by inappropriate claw vacuum.     

New aspects of the physiology of milking with special reference to the teat smooth musculature in teat rubber-free extraction

The following frequencies of change between 30 kPa milking vacuum and atmospheric pressure were used in a milking experiment with single-space cups: 0.05 Hz, 0.1 Hz, 0.2 Hz, 0.35 Hz, 0.5 Hz, 0.65 Hz, 0.8 Hz, and 0.95 Hz. Milking cup pressure and instantaneous milk flow rate through the teat canal were repetitively recorded ten times per second. Four clearly distinguishable and reproducible forms of flow rate oscillations were observed across several sucking phases together with four equally distinguishable and reproducible forms of profiles of a variable milk flow rate within one sucking phase. The occurrence of those differentiated forms of milk flow was found to be correlated primarily with both the sucking phase frequency applied and the average milk flow rate. These findings seem to be indicative of active control of teat canal diameter or milk flow rate by the unstriated teat musculature.     

A case study of improving milking cow performance and milking system performance with using a flow simulator

Efforts to improve dairy performance have been focused on increasing milk productivity of cows through improved feeding systems and genetic potential. However, methods for evaluating milking system performance based on milk productivity have not yet been established. Milking system performance was evaluated by measuring the claw vacuum at five flow rates (1.9–8.7 kg/min) produced using a flow simulator for a single eight‐swing milking parlor with a high‐line system. Based on these results, a double eight‐parallel milking parlor with a low‐line system was installed and tested. Farmers can take data obtained from evaluations of milking system performance into account for future management decisions, such as renewing the milking system. By renewing the milking system, average milking productivity, somatic cell linear score (LS) of bulk milk, and LS of each cow were significantly improved in the year after installing the new system (p < .01). In addition to checking conventional milking systems, this novel diagnostic method using a flow simulator can be used for checking new installations and also for proposing renovations.     

Sensors and management support in high-technology milking

Two directions can be distinguished in the development of high-tech milking equipment: 1) high-capacity milking parlors with a high throughput of cows per person per hour and 2) automatic milking systems in which manual labor is replaced by a milking robot. High-capacity milking parlors are developed in such a way that one operator is able to milk many cows, partly by automation and partly by optimization of available labor. In such parlors, one operator can milk up to 125 cows per hour. This means that there are only a few seconds available for udder preparation. In an automatic milking system, a robot takes over all manual labor during milking. Currently available systems have one robot arm working with one milking stall (one-stall system) or one robot arm working with more milking stalls (multiple-stall systems). Cows have to go to the automatic milking system voluntarily. Therefore, there is a large variation in milking intervals. Moreover, a large variation between milkings and between cows was observed in milk flow rate, machine-on time and udder preparation time. Both developments in high-tech milking have effects on the milk ejection. The small amount of time dedicated to udder preparation in high-capacity milking parlors has negative effects on the milk ejection, among others leading to more bimodal milk flow curves and longer machine-on time. In automatic milking systems, the variation in time between udder preparation and cluster attachment and in milking frequency might have an effect on milk ejection. Lactation physiology can play a role in solving the questions around milk ejection in high-tech milking systems. The introduction of high-tech milking systems makes decision support systems using sensors necessary. These systems should assist in detection of abnormal milk and mastitis. To a lesser extent, diseased cows need to be brought to the attention of the dairy farmer. Some sensors are currently available for this purpose, but they do not fulfill all demands. In the near future other sensors might be developed. It is important that this development is demand driven and not technology driven. Lactation physiology can play an important role in the determination of milk components useful for automatic detection.     

Association of automatic milking systems milking frequency in primiparous and multiparous cows with their yield and milkability

The aim of the study was to determine the association of automatic milking systems milking frequency (≤2.40, 2.41–2.80 and >2.80 times/day) in primiparous and multiparous cows with their daily milk yield and milkability. The analysis included of the milk production level and the interaction between milking frequency per day and daily milk yield. Regardless of the daily production level, most primiparous cows were milked 2.41–2.80 times/day and most multiparous cows >2.80 times/day. Higher daily milk yield and a more favourable effect of increasing milking frequency on this parameter were observed in multiparous cows, with an increase from 29.7?kg (milking frequency ≤2.40 times/day) to 31.1?kg milk (>2.80 times/day). In primiparous cows, this increase was smaller and amounted to 0.8?kg milk (from 29.2 to 30.0?kg).     

Influence of milking technique, milking hygiene and environmental hygiene parameters on the microbial contamination of milking machines

It was the aim of this study to investigate the effect of various factors of the milking technique, milking hygiene and environment on microbial contamination of the milking machine. In 31 dairy herds, the degree of bacterial contamination was examined by taking swabs at four locations (teat cup liner, claw, short and long milk tube) before the milking procedure was started using a standardized protocol (DIN ISO 6887-1:1999). Furthermore, the total germ count was determined in the first milk entering the bulk tank as well as in the bulk tank milk following milking. For each farm, the quality of the milking process and the condition of the milking machine as well as of various environmental factors were recorded. A subjective evaluation of the status of the milking cluster or other parts of the milking machine ("good" or "moderate-poor") gave more information about bacterial contamination than the determination of age and type of material used. A temperature of the rinsing water of < 42 degrees C increased the contamination with Pseudomonas spp. and coliform bacteria. Milking clusters kept out of the cluster pick-up between milking had a higher risk of microbial contamination. Various methods of teat cleaning before milking or of postmilking teat disinfection did not affect the contamination of the milking machine and the bulk tank milk with environmental bacteria. Furthermore, type of bedding material affected bacterial contamination of milking clusters and bulk tank milk. In conclusion, our results suggest that the microbial contamination of the milking machine is not only influenced by the sanitation pro-     

Estimates of genetic parameters for milkability from automatic milking

Genetic parameters were estimated by restricted maximum likelihood with a multi-trait animal model for three milkability traits with serial data from an automatic milking system from a research farm (401 dairy cows) collected between September 2000 and June 2003 (320834 milkings). Furthermore, daily values for milk yield and milkability were formed from all single milkings resulting in 104 132 records and, subsequently, an estimation of genetic parameters was carried out based on these daily values.The resulting estimated heritability coefficients (based on daily values) are h² = 0.55, h² = 0.55 and h² = 0.39 for average milk flow, maximum milk flow and milking time, respectively. The heritabilities are at a high level and thus breeding for good milkability makes sense. The genetic correlations between the three milkability traits are near unity with r_g = 0.98 between average and maximum milk flow, r_g = − 0.89 between average milk flow and milking time and r_g = − 0.86 between maximum milk flow and milking time. Thus it may be sufficient to record only one of these traits in performance tests. The genetic correlations between milk yield and average milk flow, maximum milk flow and milking time are r_g = 0.51, r_g = 0.44 and r_g = − 0.23, respectively.In future, serial data on milkability, already existing on many farms with automatic milk yield recording, should be used to greater extent for selective breeding with the aim of achieving good milkability.     

Duovac 300--udder health and milking routines. A field experiment (author's transl)]

The effect on udder health and milking routine of two Alfa Laval milking units, the Duovac 300 with a normal (380 mm Hg) and a low (250 mm Hg) vacuum phase and the standard HP 100 unit with only the normal (380 mm Hg) vacuum phase, was investigated on six dairy farms. A total of 197 cows were involved in the study. Each herd was divided into two groups which were as similar as possible in terms of age, stage of parturition and milk yield. One group was milked with the Duovac unit, while the other was milked with the HP 100 units for a test period of 100 days. No differences in cell counts from the cow samples, the presence of subclinical mastitis or clinical condition of the teats were observed between the two test groups. The total milking machine time for the Duovac units was longer than for the HP 100 units. However, the time spent in the normal vacuum phase (380 mm Hg) for the Duovac units was shorter than the total milking machine time for the HP 100 units (380 mm Hg). The Duovac units had the shortest machine stripping time, but the "waiting time" for the milkers (the time between the various operations) was longer. These time studies showed that the number of cows milked per hour by one man using four or five Duovac units was equal to or greater than the number of cows milked per hour by one man using three HP 100 units. It was recommended that no more than three HP 100 units be managed by one man.     

Epidemiological Analyses of the Associations between bovine udder health and milking machine and milking management

This paper presents data from 158 dairy herds in northern Norway. The influence of the milking machine and milking management on the prevalence of subclinical mastitis and herd cell counts was calculated from a least squares model by a backward elimination procedure. It was shown that 16–45% of the herd udder health variation found at the start of the programme could be associated with milking machine and milking management variables. The following variables were found to be of significance: number of clusters in the herd, vaccum, function and vaccum regulator, undulation of pipeline, limping of pulsator, rate of pulsator, type of claw-piece, hygienic/-technical condition of liner, preparation time, air admission during application of teat cups, overmilking and machine-on time.     

Coping capacity of dairy cows during the change from conventional to automatic milking

In conventional milking systems, dairy cows are driven to the milking stall twice or thrice daily, whereas in automatic milking systems (AMS), the cows enter the milking stall voluntarily. In this study, noninvasive methods were used to analyze the physiological reaction of 17 cows toward the changeover from conventional to automatic milking. Milk yield and composition were analyzed. Heart rate was recorded continuously, and feces was sampled twice daily to determine cortisol metabolites (11, 17-dioxoandrostanes) for a period of 2 wk. During the first visit to the AMS (without milking), heart rate was elevated compared with parlor milking by 35 +/- 3 beats per minute (bpm) above basal heart rate (P < 0.05). Heart rate during the first milking in AMS (eighth visit) was already similar to the heart rate previously measured during milking in the parlor (18.1 +/- 2.2 bpm above basal level). Concentration of fecal cortisol metabolites was unchanged during the change-over compared with parlor milking. A decreased (P < 0.05) milk yield of 68 +/- 7% relative to previous parlor yield during the first AMS milking indicated a disturbance of milk ejection in most cows. Individual yields ranged from 8 to 96% of the previous parlor yield. To examine the relationship between adrenal cortex sensitivity and the coping process, an ACTH challenge experiment was performed after the changeover period. Cows that released more cortisol after ACTH injection, indicating a higher adrenal cortex sensitivity, had a less enhanced heart rate and a near normal milk ejection during the first AMS milkings (P < 0.05). In conclusion, the reactions toward the changeover to AMS milking varied widely within cows. Adaption to the AMS was easier in animals with a higher adrenal cortex sensitivity to ACTH.     

Effects of pre‐partum milking of dairy cows on calcium metabolism at start of milking and at calving

This experiment studied the effect of pre‐partal milk removal on calcium metabolism at start of milking and at calving. Nine cows of the Swedish Red breed were milked for 1–7 days pre‐partum. The average milk yield at the first milking was 4.8 l, and the average yield the last day prior to calving was 13.4 l. Five cows were used as control cows and were only milked post‐partum. Samples of plasma and urine were taken to determine the effect of pre‐partum milking and calving on levels of calcium, magnesium, parathyroid hormone and plasma C‐terminal crosslinked telopeptide of type 1‐collagen (CTx), used as a marker of bone resorption. Pre‐partum milking resulted in a decrease in plasma calcium that was evident 2 days after the first milking. Parathyroid hormone increased at the same time, and CTx started to increase from 24 h after the first milking. There were no effects on plasma magnesium or urinary output of calcium or magnesium. The first week after calving, there were no differences between pre‐partum milked cows and control cows in plasma or urine variables, or in milk yield. In conclusion, pre‐partum milking activated the calcium‐restoring mechanisms but did not improve calcium status at calving.     

Effects of Machine‐milking on the Bacterial Flora of Teat Duct and Mammary Gland of Ewes

In total, 308 paired‐samples of teat duct material and milk, were collected before and 50–70 min after machine‐milking, from 30 ewes. Samples were processed bacteriologically. For analysis of results, we compared changes in bacterial isolation following milking, for duct and milk samples; statistical significance was assessed by the Sign Test. Bacteria were isolated from 18 (6%) duct and 19 (6%) milk samples collected before the milking procedure; respective figures after it, were 81 (26%) and 33 (11%). In 77 (25%) cases, bacteriological findings in the two duct samples of each pair were different; in seven cases bacteria were isolated only before, whilst in 70 cases bacteria were isolated only after milking (P < 0.005); respective results for milk samples were 26 (8%): 6 and 20 cases (P = 0.693). The majority of bacterial isolates were staphylococci, accounting for 63% of 99 isolates. The milking procedure predisposes to entrance of bacteria into the teat duct; however, increased bacterial isolation from the teat did not result to increased mammary infections, likely as a consequence of defence mechanisms present in healthy teats.     

Current aspects of the use of automated milking systems

Automatic milking systems offer not only a marked improvement of the working conditions in dairy farms but also they may be able to improve the quality of life of the dairy farmer, the health and performance status of the cow and the milk quality. The current stage of development of automatic milking systems indicates that there are still some deficiencies in fulfilling the requirements of the milk hygiene regulations, the early identification of health problems and allowing veterinary measures. This paper details some aspects of cow and udder health and milk quality under the condition of automatic milking systems by discussing actual problems and potential future advantages.     

Effect of setting a maximum milking time,from peak lactation,on production,milking time and udder health

Abstract

AIM: To examine the effect of setting a maximum milking time, from peak lactation until drying-off, on production, duration of milking, and udder health of dairy cows.

METHODS: Forty cows were assigned in twin-pairs to be either milked until cups were removed at a milk flow-rate threshold of 0.35 kg/minute (Control), or until cups were removed at a milk flow-rate threshold of 0.35 kg/minute, or maximum time, whichever came first (MaxT). The maximum time was set by determining the milking time of the 70th percentile cow when ranked from fastest to slowest, irrespective of yield. The milking routine was typical of that practised on dairy farms in New Zealand, and involved no pre-milking preparation. The study began at peak lactation (68 (SD 7) days in milk; DIM) and continued for 26 weeks. Duration of milking and milk yield were measured for each milking. Composition of milk was determined from weekly herd tests, and milk quality from fortnightly somatic cell counts (SCC). Completeness of milking and teat condition were assessed during the study. The bacterial status of quarter milk samples was determined at the beginning and end of the study, and all treated cases of clinical mastitis recorded. ANOVA was used to examine the effect of treatment group on variables of interest.

RESULTS: Total milk, fat and protein yields during the study period did not differ between treatments. On average, 30.3% of the morning and 27.6% of the afternoon milkings of MaxT cows reached the maximum time at which cups were removed, and were therefore shortened. While the average milking time of the slowest-milking cow was longer for the Control compared with MaxT group in Weeks 1–18, the average milking time did not differ between treatments. There was no difference in overall SCC, and the incidence of clinical mastitis, or the percentage of infected quarters at drying-off, was similar for the MaxT and Control cows.

CONCLUSION: The results show that setting a maximum milking time can reduce the milking time of slower-milking cows in a herd without compromising overall herd production and udder health.

CLINICAL RELEVANCE: Although the numbers of cows in the study were small there was no evidence of a major increase in SCC, or subclinical or clinical mastitis when a maximum milking time was set for slower-milking cows.     

The relationship between responsiveness of first-lactation heifers to humans and the behavioral response to milking and milk production measures

The human–animal relationship can influence how an animal responds to situations involving humans and affect animal well-being and production. The objectives of this research were to (1) determine if there is a relationship between the behavioral reactivity of New Zealand dairy heifers toward humans and the behavioral response to cluster placement during milking and milk production measures and (2) determine if this relationship changes as heifers become habituated to the milking process. A total of 150 primiparous heifers were randomly selected from 3 commercial dairy farms. Approximately 1 month before calving, 2 behavioral tests, avoidance distance in response to an approaching human and exit speed from a restraint, were performed on 50 heifers at each farm. For each heifer, behavioral observations were recorded during the morning milking period (during the first and sixth weeks of lactation). Behaviors recorded during cluster placement at milking included flinching, stepping, and/or kicking (FSK). Milk yields, milking durations, and average milk flow rates were recorded for each individual heifer during the first and sixth weeks of lactation. Avoidance distance and exit speed were positively correlated (P < 0.001). The FSK response during cluster placement was negatively (P < 0.01) correlated with exit speed during week 6 of lactation, but there was no relationship (P > 0.05) between avoidance distance and FSK. Avoidance distance was positively (P < 0.005) correlated with milk flow rates during weeks 1 and 6 of lactation and milk yields (P < 0.01) during week 6 of lactation. However, there was no relationship (P > 0.05) between exit speed and milk yields, durations, or flow rates. Furthermore, the FSK response was negatively (P < 0.05) correlated with milk yield during weeks 1 and 6 of lactation. Therefore, the behavioral response of heifers toward humans and the milking process appears to be related to milk production measures.     

Comparison of weigh-suckle-weigh and machine milking for measuring ewe milk production.

Thirteen crossbred ewes were used to compare weigh-suckle-weigh (WSW) and machine milking (MM) methods for determining milk production of ewes that were rearing single or twin lambs. At parturition, ewes were 13 mo of age and produced six single lambs and seven pairs of twin lambs. Milk production estimates were initiated on d 6 of lactation and a 3-d rotation of the two techniques was implemented. On d 6, milk production was measured using WSW; on d 7, MM was used. No measurement was made on d 8. The 3-d rotation was repeated 20 times throughout a 63-d lactation, resulting in 20 point estimates of milk production for each method of measurement for each ewe. The WSW procedure consisted of a 3-h period in which lambs were withheld from suckling their dams. This was followed by a suckling period, a second 3-h withholding period, and a second suckling period. Differences in pre- and postsuckling lamb weights of the second suckling period were defined as milk consumption and, indirectly, 3-h milk production. The MM procedure included an administration of 10 IU of oxytocin (i.v.), followed by evacuation of the udder with a machine using commercially available sheep milking equipment, and the milk was discarded. Lambs were withheld from suckling the ewes for a 3-h period, followed by a repetition of the oxytocin and machine milking procedures. Milk from the second milking was weighed. Milk production estimates determined using the WSW and MM techniques were similar (P = .42). Average 3-h milk production was 340 and 351 g for WSW and MM, respectively. Machine milking provides a reliable tool in evaluating the milk-producing ability of ewes that are rearing single or twin lambs.     

Effect of an automatic milking system on milking traits

Recent studies in Japan of the effect of automatic milking systems (AMS) on the behavior of dairy cows have confirmed the labor-saving aspect of AMS, but have not solved some of the problems affecting milking traits. The influence of AMS on milking was examined in 39 Holstein cows at Iwate Agricultural Research Center from June 1998 to December 1999, by measuring and recording the yield per milking, milking finish time, milking frequency, and daily yield of milking. Four milking traits were analyzed separately as the objective variable in a linear model, with parity, days in milking, month after installation of the AMS as independent variables. Primiparous cows milked more frequently in the middle and late stage of lactation, yielded less per milking and less per day in the early stage of lactation than multiparous cows with the AMS. Lower frequencies were observed at noon and midnight for cleaning of the bulk tank. By contrast, higher milking frequency in the forenoon was shown. The yield per milking rose and declined, following a normal lactation curve. However, milking frequency rose slowly, and declined gradually in the late stage of lactation. After installing a one-way gate, the cows milked more frequently, with a lower yield per milking and a greater daily milk yield, than before installation.