Identifying strategies to enhance the milking and operator efficiency of herringbone and rotary parlor systems in Ireland.

International trends of increasing dairy herd sizes coupled with scarcity of labor has necessitated the enhancement of labor efficiency for dairy production systems. This study quantified the effects of infrastructure, automation, and management practices on the milking and operator efficiency of herringbone and rotary parlors used on pasture-based farms in Ireland. Data from 592 milkings across 26 farms (16 herringbones and 10 rotaries) was used. The metrics of cows milked per hour (cows/h), cows milked per operator per hour (cows/h per operator) and liters of milk harvested per hour (L/h) described milking efficiency. The metrics of total process time per cow (TPT, s/cow), milk process time per cow (MPT, s/cow), work routine time (WRT, s/cow), cluster time (CT, s/cluster), and attachment time per cow (ATC, s/cow) described operator efficiency. Automations investigated were backing gates, cluster flush, plant wash, cluster removers (ACRs), feeders, entry gates, rapid-exit, and teat spray. Additional operator presence at milking was also investigated. Herringbone and rotary parlors were assigned to quartiles from their cows/h per operator values to examine infrastructure, automations, and management practices variations. Fourth quartile herringbones based on cows/h per operator values (Q4) averaged 93 cows/h per operator using average system sizes of 24 clusters with 5 parlor automations. Q4 rotaries averaged 164 cows/h per operator using average system sizes of 47 clusters and an average CT of 13 s/cluster. Cows/h per operator values for Q4 herringbone and rotary parlors were 82% and 54% higher, respectively, than values observed on Q1 parlors, indicating the considerable potential to improve efficiency. To determine if infrastructure, automations, or additional operators at milking significantly affected operator efficiencies, general linear mixed models were developed. For parlor infrastructure, additional clusters had greater significance on operator efficiencies (MPT) for herringbones (-1.3 s/cow) as opposed to rotaries (-0.2 s/cow). Hence, increases in system size was likely to result in improved efficiencies for herringbones but less so for rotaries. For automations, ACRs significantly reduced herringbone TPT, CT, and WRT values by 13.3 s/cow, 18.9 s/cluster, and 32.6 s/cow, respectively, whereas rapid-exit significantly lowered CT by 18.6 s/cluster. We found no significant effect on rotary TPT, MPT, CT, or WRT values from the use of automatic teat sprayers. An additional operator at milking was found to significantly reduce herringbone TPT but not MPT or CT. For rotaries, a second operator had no significant effect on TPT, MPT, CT, or WRT values. We documented strong negative correlations between operator efficiencies (TPT, MPT) and milking efficiency (cows/h) for both herringbone (-0.91, -0.84) and rotaries (-0.98, -0.89). Strong negative correlations between the herringbone automation count and TPT (-0.80), MPT (-0.72), and CT (-0.75) suggested highly automated parlors were likely to achieve greater operator efficiencies than less automated parlors. The strong negative correlation (-0.81) between rotary milking efficiency (cows/h) and CT suggested lower CT values (i.e., rotation speed) resulted in increased milking efficiency. In conclusion, our study quantified the effects of parlor infrastructure, automation, and management practices on the milking and operator efficiency of herringbone and rotary parlors.

The effects of seasonality, management, infrastructure, and automation on the milking efficiency of herringbone and rotary milking parlors in Ireland.

The objective of this study was to document the milking efficiency of a sample of Irish dairy farms and to understand the effects of (1) seasonality, (2) management practices, (3) parlor infrastructure, and (4) parlor automations on milking efficiency metrics. A novel methodology based on empirical data from video cameras, infrastructure surveys, and milk yield data allowed for the accurate computation of milking efficiency metrics and quantification of the effects of seasonality, number of operators, and parlor automations on milking efficiency across 2 parlor types. The data for this study were collected over 2 periods: period 1 (July 28, 2020, to October 23, 2020, peak-late production) and period 2 (April 12, 2021, to May 19, 2021, early-peak production) from a sample of 16 herringbone and 10 rotary commercial Irish dairy farms. Milking efficiency was evaluated on each farm using 3 key performance indicators: (1) cows milked per hour (cows/h), (2) cows milked per operator per hour (cows/h per operator), and (3) liters of milk harvested per hour (L/h). Milking efficiency key performance indicators were calculated using "total process time," defined as the time between the first cow entering the holding yard and the end of the cleaning process. Average herd sizes for herringbone and rotary farms were 180 and 425 cows, respectively. Average system sizes for herringbone and rotary farms were 20 and 50 clusters, respectively. For herringbone farms, the average milking efficiency was 94 cows/h, 73 cows/h per operator, and 1,012 L/h, whereas rotary farms achieved an average milking efficiency of 170 cows/h, 132 cows/h per operator, and 1,534 L/h. Parlor size was strongly correlated with milking efficiency (cows/h) for herringbone parlors (0.91) but was only moderately correlated for rotary parlors (0.50). Hence, we documented the effect of parlor size on milking efficiency is relative to parlor type. Cluster utilization values on herringbone farms were 5 cows/cluster per h, 4 cows/cluster per operator per h, and 51 L/cluster per h, which were 67%, 33%, and 65% greater than rotary farms, respectively. We found for both herringbone and rotary farms hourly cow throughput (cows/h, cows/h per operator) were greatest during period 1 and that the volume of milk harvested per hour (L/h) was greatest for period 2. Thus, we documented an inverse seasonal relationship between hourly rates of cows milked and milk harvested. We observed that for herringbone farms, milking efficiency (cows/h, L/h) had a strong positive correlation (0.75, 0.74) with the levels of automation use. However, the minimal variation in automations used among rotary farms made it difficult to evaluate their effect on milking efficiency. Similarly, we found that the effect of automations on milking efficiency was dependent on parlor type. On average, a second operator at milking for both herringbone (H) and rotary (R) farms increased values for cows/h (+19%, H; +34%, R) and L/h (+21%, H; +12%, R) but lowered values for cows/h per operator (-35%, H; -12%, R). The holistic methodology applied in this study allowed us to add novel data to the literature by quantifying the effects of seasonality, the number of operators present at milking, and parlor automation use on milking efficiency across 2 parlor types.

Factors affecting energy efficiency in herringbone and rotary milking parlours.

The United Nations Sustainable Development Goals aim to double the productivity of small-medium food producers (2015-2030), while food demand is estimated to increase by 60 % by 2050. The objectives of this paper were to identify and quantify the relationship between energy efficiency and milking efficiency, identify the main energy consuming processes associated with milking, and investigate whether milking efficiency, energy efficiency or the relationship between them varies depending on parlour type. Energy and milking efficiency data from 26 pasture-based dairy farms in the Republic of Ireland were analysed (17 herringbone, nine rotary). Energy consumption was monitored continuously on the herringbone farms and for two distinct, seven-day periods (observation periods 1 and 2) for the rotary farms. Milking performance was monitored for all 26 farms during these periods. During the observation periods, the rotary farms achieved superior energy efficiency (29.85 Wh kgMilk-1) and milking efficiency (152 cows/hour) than the herringbone farms (32.83 Wh kgMilk-1, 97 cows/hour). Moderate correlations existed between milking efficiency (cows/hour) and energy efficiency (Wh kgMilk-1) for rotary (r = -0.58, R2 = 0.34) and herringbone (r = -0.44, R2 = 0.19). These results indicated that higher levels of milking efficiency were moderately correlated with improved energy efficiency.

Comparison of selected parameters of automated milking in dairy cattle barns equipped with a concentrate feeding system.

Automatic milking systems (AMSs) give cows relative freedom to choose the time and frequency of milking throughout the day. Feeding stations also may improve the management of farms. Combining milking robots and feeding stations (FS) may improve milking efficiency and milk yield. Therefore, combining AMS and FS may be beneficial for farmers. The objective of the research was to compare selected automatic milking parameters (daily indices per cow) registered by an AMS in relation to selected features including the presence of concentrate feeding stations. We analysed 931 cows born in 2013-14, in lactations 1-8. In total, we collected data from 357 318 milking days. The following parameters were examined: milking frequency (n/24 h), number of rejected milking (n/24 h), the average number of nipple attempts (n/milking), milking speed (kg/min), time spent in the milking box (s/24 h), milk yield (kg/24 h), milking efficiency (kg/min), rumination time (min/24 h), and concentrate intake (kg) per 100 kg of milk produced. The statistical analysis was conducted using a multi-factor analysis of variance. The analysis confirmed a statistical effect of the concentrate feeding system on most of the investigated traits, except for nipple attempts, box time and rumination time. In cows in barns with an FS, the following parameters were statistically higher compared to cows in non-FS barns: milking frequency (3.04 vs 2.73n/24 h), number of rejected milking (2.24 vs 1.51n/24 h), milking speed (2.98 vs 2.64 kg/min), milk yield (33.48 vs 30.14 kg/24 h), milking efficiency (1.80 vs 1.67 kg/min), and concentrate intake per 100 kg of milk produced (14.67 vs 12.67 kg). The study results indicate that using feeding stations in combination with an AMS can increase milking efficiency, hence the milk output from a milking robot.

Effect of milk flow-rate switch-point settings on milking duration and udder health throughout lactation.

The objective of this study was to quantify the effects of different milk flow-rate switch-point settings on milking duration, somatic cell count (SCC), strip milk, teat condition, and milk yield in a grass-based system in a long-term experiment. Much work has already been conducted providing strong support for significant reduction in milking duration without effects on yield through increasing the flow-rate switch-point at which vacuum to the milking cluster ceases and the cluster is removed from the cow by means of a retracting cord. However, in practice many farms have not adopted this labor-saving technology on the basis that it may increase milk SCC. Recent research on commercial Irish dairy herds identified the contagious mastitis-causing pathogen Staphylococcus. aureus as the most prevalent pathogen detected. Staph. aureus could have a cyclical shedding pattern which would inhibit detection at certain time points. Therefore, to reliably assess the effect of milk flow-rate switch-points on SCC, a long-term study was required, consisting of multiple observations on cow-level SCC. The present study filled this gap in knowledge by informing on any effect that ceasing milking at different flow rates may have on milking duration and SCC levels, particularly with regard to spring calving grass-based systems. Four treatments, consisting of milk flow-rate switch-points increasing from 0.2 kg/min to 0.8 kg/min in steps of 0.2 kg/min, were deployed for 31 wk to cows at the Teagasc Research Centre at Moorepark, Ireland. The effect of treatment on daily milking duration was significant. The milking duration for a milk flow-rate switch-point of 0.8 kg/min was 95 s (14%) shorter than for 0.2 kg/min. We did not find a significant effect of increasing the milk flow-rate switch-point from 0.2 to 0.8 kg/min on milk yield or SCC in this long-term study. We did find a significant effect of week of experiment on milk SCC, whereby the SCC of the cows on the experiment increased similarly among treatment groups as lactation progressed. A significant reduction in dead time (time from cluster attachment to reach a milk flow rate of 0.2 kg/min) was also noted as the milk flow-rate switch-point increased. On average, reductions in dead time contributed 12% to the overall reductions in milking duration. Similarly, reductions in low flow time (time from a flow rate of 0.2 kg/min to cluster detachment at the end of milking) contributed 26% to the overall reductions in milking duration. Reductions in dead time and low flow time played a greater role in reducing p.m. milking duration rather than a.m. milking duration due to the milking interval practiced on the research farm.

Optimal Parameters to Milk Murciano-Granadina Goats in Mid and Low-Line Milking Parlours.

Recent short-term studies on Murciano-Granadina goats have established that the optimal parameters to set up the milking machines are different according to the milk pipes height. Two groups of 52 fresh goats each were employed in 2 different experiments to confirm during an entire lactation period the best combinations of system vacuum pulsation rate and pulsator ratio in low-line and mid-line milking parlours. The experiment performed in the low-line milking parlour included one group milked with 40 KPa vacuum system level, 90 puls/min pulsation rate and 60/40 pulsation and a second group milked with 38 KPa vacuum system level, 90 puls/min pulsation rate and 60/40 pulsation ratio. The experiment carried out in mid-line included one group milked with 40 KPa vacuum system level, 90 puls/min pulsation rate and 60/40 pulsation ratio and a second group milked with 40 KPa vacuum system level, 120 puls/min pulsation rate and 60/40 pulsation ratio. Variables studied included milking efficiency, milk composition, cortisol, SCC and intramammary infections, teat-end oedema after milking and vacuum dynamics during milking. Considering the results of an entire lactation period, it was confirmed that when milking in mid-line, the combination of 40 KPa system vacuum, 90 cycles/min pulsation rate and 60/40 pulsator ratio showed optimal results of the above-mentioned variables. On the other hand, the use of 40 KPa in a low-line system increased the milk cortisol values (0.34 ± 0.1 vs. 0.44 ± 0.1 ng/mL) without any other advantage. Thus, the recommendation is to use a combination of 38 KPa system vacuum, 90 cycles/min pulsation rate and 60/40 pulsator ratio to enhance animal welfare.

Effect of milk flow rate switch-point settings on cow comfort and milking duration.

Automatic cluster removers (ACR) operate by ceasing vacuum to the cluster and detaching the milking unit from the udder by means of a retracting cord once the milk flow has decreased to a predefined level (i.e., the milk flow rate switch-point). There is a large body of literature on this topic indicating that increasing the flow rate switch-point (e.g., from 0.2 kg/min to 0.8 kg/min at the udder level) is effective in reducing milking duration while having little effect on milk yield or milk somatic cell count (SCC). However, despite these findings many farms still use a switch-point of 0.2 kg/min because it is believed that emptying the udder completely at each milking is a prerequisite for good dairy cow management, especially in relation to maintaining a low milk SCC. However, there may be additional undocumented benefits in terms of cow comfort to increasing the milk flow rate switch-point, because the low milk flow period at the end of milking is a high-risk time for inducing teat-barrel congestion. The objective of this study was to quantify the effect of 4 milk flow rate switch-point settings on cow comfort, milking duration, and milk yield. In this study, we applied 4 treatments consisting of different milk flow rate switch-points to cows in a crossover design in a spring calving grass based dairy herd in Ireland. The treatments were (1) MFR0.2, where the cluster was removed at a milk flow rate of 0.2 kg/min; (2) MFR0.4, where the cluster was removed at 0.4 kg/min; (3) MFR0.6, where the cluster was removed at 0.6 kg/min, and (4) MFR0.8, where the cluster was removed at 0.8 kg/min. Milking parameters were recorded by the parlor software and leg movements (i.e., kicks or steps) during milking were recorded with an accelerometer. These data were used as a proxy for cow comfort during milking. The results of this study showed significant differences in cow comfort across treatments, as indicated by cow stepping during milking, for a.m. milkings, but these differences were not detected for p.m. milkings, possibly because a.m. milkings were longer than p.m. milkings due to a 16:8 h milking interval on the research farm. Differences tended to distinguish the 2 lower-flow switch-point settings with greater leg movement against the 2 higher-flow switch-point settings with less leg movement during milking. The effect of treatment (milk flow rate switch-point) on daily milking duration was significant. The milk duration for MFR0.8 was 89 s (14%) shorter than MFR0.2. There was no significant effect of treatment on SCC in this study.

Bimodal milk flow and overmilking in dairy cattle: risk factors and consequences.

To maximise the return on capital invested in the milking parlour, the largest number of cows should be milked gently and completely in the shortest possible time. Bimodal milk flow and overmilking negatively influence the efficiency of the milk removal process and teat health. This observational study had the objective of investigating the prevalence of bimodal milk flow and overmilking, determining which individual and farm-related variables are associated with these occurrences, and determining the association of overmilking and bimodal milk flow with milk yield and with short- and long-term teat changes. Twenty-one farms were visited once during the study period, wherein the milking routine was timed, the teat condition was assessed, and dynamic evaluation of the milking vacuum was performed. A total of 606 vacuum graphic records were obtained, with an average of 29 ± 3 records per farm, in order to indirectly evaluate the milk flow and thus determine the occurrence of bimodal milking and overmilking time. The average percentage of bimodality per farm was 41.7%. The median overmilking time was 59 seconds, and on average, 78.3% of the cows in a herd were overmilked longer than 30 seconds. An association was found at cow level between the occurrence of bimodal milk flow and days in milk, the total stimulation time, parity, and the preparation lag time. The increase in the mean total stimulation time and the number of passes during preparation were associated with a decrease in the proportion of bimodality in the herd. Parity, reattachment of the milking unit and milking in manual mode were associated with an increase in overmilking time of an individual cow. The presence of a clogged air bleed hole in the claw and the reduction of the cluster removal milk flow threshold were associated with an increase in the herd's median overmilking time. The average milk flow decreased with the increase in overmilking time and with the occurrence of bimodal milk flow. An association was also found between the occurrence of bimodal milk flow and decreased milk yield. A mean of 78.4% of cows per farm had short-term teat changes in at least one teat, and 33.6% of evaluated cows per farm displayed at least one teat with hyperkeratosis. These results emphasise the association of bimodality and overmilking on milking efficiency and reinforce the importance of the milkers' actions and the functioning of the milking parlour for its prevention.

Forecasting Milking Efficiency of Dairy Cows Milked in an Automatic Milking System Using the Decision Tree Technique.

In barns equipped with an automatic milking system, the profitability of production depends primarily on the milking efficiency of a cow (ME; kg/min) defined as cow milk yield per minute of box time. This study was carried out on 1823 Polish Holstein−Friesian cows milked by the automatic milking system (AMS) in 20 herds. Selected milking parameters recorded by the AMS were analyzed in the research. The aim of the study was to forecast ME using two statistical techniques (analysis of variance and decision trees). The results of the analysis of variance showed that the average ME was 1.67 kg/min. ME was associated with: year of AMS operation (being the highest in the first year), number of cows per robot (the highest in robots with 61−75 cows), lactation number (highest for multiparas), season of calving (the highest in spring), age at first calving (>36 months), days in milk (151−250 days) and finally, rear quarter to total milk yield ratio (the highest between 51% and 55%). The decision tree predicted that the highest ME (2.01 kg/min) corresponded with cows that produced more than 45 kg of milk per day, were milked less than four times/day, had a short teatcup attachment time (<7.65 s) and were milked in robots that had an occupancy lower than 56 cows.

Short communication: Increasing the teatcup removal settings of the last milking quarter did not reduce box time in a pasture-based automatic milking system.

This research followed our previous experimental and simulation work on the effect of different teatcup removal settings based on the rolling average milk flowrate and on milking duration at the quarter and udder levels. The aims of this experiment were to (1) quantify the differences in quarter milking duration in a pasture-based automatic milking system and (2) test the effect of increasing the milk flowrate at which teatcups are removed on the last milking quarter on udder milking duration, box time, milk production rate, and somatic cell count (SCC). Milking duration is an important component of efficiency and profitability in conventional and automatic milking systems. Additionally, quarters within an udder have significantly different milk yields and milking durations. This study used data from April to May 2018 of a pasture-based automatic milking system to evaluate quarter milking duration differences between quarters of an udder. Subsequently, we experimentally evaluated the use of 2 percentage-based teatcup removal settings applied to the last milking quarter (i.e., the last quarter with a teatcup still attached) on milking duration, box time, milk production rate, and SCC. The teatcup removal settings were at 30 or 50% of the last quarter's rolling average milk flowrate, while the other quarters remained at the 30% level. The selection of the quarter that would receive the more aggressive teatcup removal setting was determined by identifying the last quarter with a teatcup attached in every milking. Sixty-nine cows were divided into 2 groups that each received 1 of the 2 treatments for a 1-wk period and then switched to the other treatment for a second week. For the months of April and May 2018, quarter milking duration was significantly different between the quarter with the longest and the second longest milking duration within an udder. The quarter with the longest milking duration was milked on average 49 s longer than the quarter with second longest milking duration. However, in 36% of the milkings, the quarter with the longest milking duration was different from that of the previous milking. In the experimental part of this study, we saw no differences in milking duration, box time, milk production rate, or SCC between the 30 and 50% teatcup removal setting applied to the last milking quarter. Further research on using a variation of this percentage-based setting to target the quarter with the average longest milking duration or using an absolute milk flowrate switch-point or a maximum milking duration setting on the last quarter for reducing cow milking duration and box time is warranted.

Effects of simulated quarter and udder teat cup removal settings on strip milk and milking duration in dairy cows.

The aim of this study was to estimate the amount of milk left in quarters and udders and the milking duration for a variety of teat cup removal strategies. A combination of empirical data and simulated quarter and udder teat cup removal settings were used to make these estimates. Milking duration is an important factor in both automatic and conventional milking systems because it directly influences milking efficiency and hence can affect farm profitability. Strategies investigated in the literature to reduce milking duration include the application of different milk flow rate switch-points (milk flow rate at which the milking unit or teat cup is removed). Applying these milk flow rate switch-points can affect the amount of milk that is not harvested (strip milk). We are not aware of previous research analyzing strip milk yield and milking duration at the quarter level, across a range of quarter and udder milk flow rate switch-points. Quarter-level average milking duration decreased by 2 min, and strip milk increased 1.3 kg as quarter milk flow rate switch-point was increased from 0.2 kg/min to 1.0 kg/min. Using an end of milking criterion of removal of the teat cup at 50% of the quarter's rolling average milk flow rate resulted in a 0.4-min reduction in milking duration and a 0.08-kg increase in strip milk per quarter, compared with removal of the teat cup at 30% of the quarter's rolling average milk flow rate. Udder-level average milking duration decreased by 1.4 min, and strip milk increased by 0.76 kg (0.19 kg per quarter) as udder milk flow rate switch-point was increased from 0.2 kg/min to 1.0 kg/min. A 0.8-min reduction in cow milking duration and a 0.27-kg increase in strip milk at the udder level (0.08 kg per quarter) resulted when changing udder milk flow rate switch-point from 30% of the udder rolling average to 50% of the udder rolling average milk flow rate. This study provides quantitative estimates of the effect of teat cup milk flow rate switch-points on milking duration and strip milk yield.

Effect of teatcup removal settings on milking efficiency and milk quality in a pasture-based automatic milking system.

In automatic milking systems (AMS), it is important to maximize the amount of milk harvested per day to increase profitability. One strategy to achieve this goal is to reduce the time it takes to milk each cow. Several studies in conventional milking systems have shown that milking time can be reduced by increasing the milk flow rate at which the teatcup is removed. One study analyzed the effect of increasing the milk flow switch point on milking time in a confinement AMS. No research has been conducted on teatcup removal settings in pasture-based automatic milking systems. Furthermore, not all AMS remove the teatcups based on absolute milk flow rate (kg/min); hence, it is important to study alternative strategies. The aim of this experiment was to measure the effect of 3 novel teatcup removal strategies on box time (time in the AMS), milking time, somatic cell count (SCC), and milk production rate of cows milked in a pasture-based automatic milking system. Each teatcup removal strategy in this study was applied for a period of 1 wk to 1 of 3 groups of cows and then switched to the following group until cows had transitioned through all treatments. The teatcup removal strategies consisted of removing the teatcup when the quarter flow rate fell below 20% of the quarter rolling average milk flow rate (TRS20), when quarter milk flow rate was below 30% of the rolling average milk flow rate (TRS30), and when quarter milk flow rate dropped below 50% of the rolling average milk flow rate (TRS50). A limit prevented teatcup removal if the calculated milk flow rate for teatcup removal was above 0.5 kg/min. This limit was in place for all treatments; however, it only affected the TRS50 treatment. The TRS30 strategy had 9-s shorter milking time and 11-s shorter box time than the TRS20 removal strategy. The TRS50 strategy had 8-s shorter milking time and 9-s shorter box time than the TRS20 teatcup removal strategy. There was no significant difference in milking time or box time between the TRS30 and TRS50 teatcup removal strategies, probably due to the large variability in milk flow rate at teatcup removal. The TRS20 and TRS30 strategies did not differ in SCC or milk production rate. The 0.5 kg/min limit, which affected roughly 25% of milkings in the TRS50 treatment, may have distorted the effect that this setting had on milk time, box time, milk production rate, or SCC. The difference in box time for the TRS30 and TRS50 strategies could allow for more than 3 extra milkings per day.

Genetic analyses of novel temperament and milkability traits in Norwegian Red cattle based on data from automatic milking systems.

The number of dairy cows milked in automatic milking systems (AMS) is steadily increasing in Norway. Capacity and efficiency of AMS are highly dependent on the individual cow's milking efficiency, such as milking speed and occupation time in the milking robot. Cows meet new challenges in herds utilizing AMS. Consequently, new or revised traits may be needed for genetic evaluation of dairy cattle. The AMS records relevant information on an individual cow basis. The aims of this study were to estimate genetic parameters of new automatically recorded milkability and temperament traits. Data from 77 commercial herds with Norwegian Red dairy cattle were analyzed by mixed linear animal models. The final data set contained 1,012,912 daily records from 4,883 cows in first to ninth lactation. For variance component estimation, univariate and bivariate models were used. Daily records of box time (BT), average flow rate (FR), kilograms of milk per minute of box time (MEF), handling time (HT), log-transformed HT, milking frequency, and milking interval were analyzed with repeatability models. Among these traits, FR, BT, and MEF showed the highest heritabilities of 0.48, 0.27, and 0.22, respectively, whereas heritability of log-transformed HT, HT, milking frequency, and milking interval was low (0.02-0.07). Unsuccessful milkings expressed as rejected milkings, incomplete milkings (IM), milkings with kick-offs (KO), and teat not found also showed low heritabilities (0.002-0.06). Due to low frequency, KO, rejected milkings, IM, and teat not found were also analyzed as proportions per lactation, which resulted in slightly higher heritability estimates. Genetic correlations were favorable and intermediate to strong between BT, HT, MEF, and FR with absolute values above 0.50. Intermediate and favorable correlations were found for IM and KO with BT, HT, MEF, and FR. Cow milkability in AMS can be improved by selection for reduced number of unsuccessful milkings, faster FR, increased MEF, and shorter BT and HT. Our results confirm that automatically recorded data on milkability and temperament can be valuable sources of information for routine genetic evaluations and that milking efficiency in AMS can be genetically improved.

Effects of automatic cluster removal and feeding during milking on milking efficiency, milk yield and milk fat quality.

In order to increase milking efficiency, the effects of two different cluster take-off levels (200 and 800 g/min) and feeding vs. not feeding during milking were tested in a Latin square design study including 32 cows. Milk yield, milking time, milk flow and milking interval were measured and milk samples were analysed for gross composition, sodium and potassium concentration, free fatty acid (FFA) content, milk fat globule (MFG) size, MFG membrane (MFGM) material and fatty acid composition. Residual milk was harvested to evaluate udder emptying. Increasing the take-off level from 200 to 800 g/min at the whole udder level decreased milking time and increased harvest flow. Udder emptying decreased slightly, but there were no effects on milk yield, FFA content or MFGM. There were interactive effects of take-off level and feeding during milking on content of fatty acids C4:0, C6:0, C16:0, C18:3(n-3) and C20:0. Feeding during milking increased milk yield per day and decreased milking interval. Sodium and potassium concentrations in milk were unaffected by treatments, indicating no loss of tight junction integrity. From these results, it is clear that feeding during milking should be used to increase milk yield and improve milking efficiency, regardless of take-off level used, and that the effect of feeding is more pronounced when a low take-off level is used. Feeding seemed to counteract the effects of the low take-off level on milking time and milking interval. Low take-off levels can therefore be used in combination with feeding.

Analysis of milking characteristics in New Zealand dairy cows.

The objective of this study was to describe the variation in milking characteristics, and factors associated with these traits, in grazing dairy cows milked without premilking stimulation. Milk yield, duration, and average and maximum milk flow rate data were collected from 38 farms in New Zealand at 2 time points (spring and autumn) during the 2010 to 2011 season. Subsequently, a second data set, allowing the generation of daily milk flow profiles, was collected from 2 farms in the 2011 to 2012 season. Corresponding animal data, such as breed, date of birth, and ancestry information, were extracted from the New Zealand Dairy Industry Good Animal Database (New Zealand Animal Evaluation Ltd., Hamilton, New Zealand). Residual milking duration (deviation from the regression line of milk yield on milking duration) was calculated, allowing the identification of fast-milking cows independent of milk yield. Variance components for the milking characteristics traits were estimated using an animal linear mixed model. The average milk yield was 10 kg/milking and the average milking duration was 360 s. The average milk flow rate was 1.8 kg/min and maximum milk flow 3.3 kg/min, with 44% of milk flow curves being classified as bimodal. Primiparous animals exhibited different milk flow profiles, with a lower maximum flow, than multiparous animals, possibly due to differences in cisternal capacity. Residual milking duration was shortest (-10s) in mid-lactation (121-180 d) and was 13s longer for Jersey compared with Friesian cows; however, it was 19s shorter when adjusted for energy content. Residual milking duration had a negligible genetic correlation (-0.07) with milk yield, indicating that selection for cows with shorter residual milking duration should have a negligible effect on milk yield. A heritability of 0.27 indicated that residual milking duration could be valuable as part of a breeding program. Knowledge of the distribution of milking durations for a given milk yield allows farmers to choose appropriate cluster-on time when using a maximum milking time strategy to improve milking efficiency.