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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.

Targeted reproductive management (TRM) aims to improve the fertility efficiency of the dairy herd by applying group-level management strategies based on expected reproductive performance. Key to the utility of TRM is the accuracy with which an animal's reproductive performance can be predicted. Automatic milking systems (AMS) allow for the collection of data relating to milk quantity, quality, and robot visit behavior throughout the transition period. In addition to this, auxiliary data sources such as rumination and activity monitors, as well as historical cow-level data are often readily available. The utility of this data for the prediction of fertility has not been previously explored. The objective of this study was first, to assess the accuracy with which the likelihood of expression of oestrus between 22 and 65 d in milk (DIM) and conception to first insemination between 22 and 80 DIM could be predicted using data collected by AMS from 1 to 21 DIM. Our second objective was to assess the change in model performance following the addition of 2 auxiliary data sources. Using data derived solely from the AMS (RBT data set) a binary random forest classification model was constructed for both outcomes of interest. The performance of these models was compared with models constructed using AMS data in conjunction with 2 auxiliary sources (RBT+ data set). Expression of oestrus was classified with an area under the receiver operator curve (AUC-ROC) of 0.6 and 0.65, conception to first insemination with an AUC-ROC of 0.56 and 0.62 for the RBT and RBT+ data sets respectively. No statistically significant improvement in classification accuracy was achieved by the addition of auxiliary data sources. This is the first study to report the utility of data collected by AMS for the prediction of reproductive performance. Though the performance described is comparable with previously reported models, their utility for the implementation of TRM is limited by poor classification accuracy within key sub-groups. Of note within this study is the failure of the addition of auxiliary data sources to increase the accuracy of prediction over models built using AMS data alone. We discuss the advantages and limitations the integration of additional data sources imposes on model training and deployment and suggest alternative methods to improve performance while preserving model parsimony., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Simple Summary: The purpose of this study was to objectively evaluate the degree of damage to Holstein cows in Korea caused by summer heat stress. It was also established that the milk and rumen characteristics changed under heat stress depending on the difference in the Holstein cows' parity. As a result of the study, it was confirmed that the summer weather in Korea adversely affects the milk yield, milk fat, milk protein, somatic cells, rumen activity, and rumen temperature of Holstein cows. Additionally, a correlation was found between the degree of heat stress experienced by Holstein cows based on parity. With AMSs and rumen biosensors, this study could provide farms with advice on improving milk yields in Holstein dairy cows. The results of this study suggest that the metabolic mechanisms of each of these factors are needed in Korea to understand how they contribute to the maximum improvements in milk yield and characteristics. This survey investigated, using robotic milking and rumen sensors, the effects of an adjusted temperature–humidity index (THI) in different geographical areas on milk yield, fat and protein, rumen temperature, and activity in lactating Holstein cows. We additionally explored the effect of parity on milk and rumen temperature and activity under different THI levels during the summer. From January to September 2020, four farms (276 dairy cows) were subjected to the use of robot milking machines, and two farms (162 dairy cows) to the use of rumen sensors. For the temperature and humidity data, the THI was calculated on the basis of the data from the Korea Meteorological Administration (KMA). The data were analyzed using the GLM procedure of SAS. Milk yield and milk protein decreased (p < 0.05), and milk fat increased (p < 0.05) at all farms during the summer, from July to August, when the temperature and humidity were high (THI = 72–79). Milk yields were the highest in the fifth, sixth, seventh, and eighth parities, and the lowest in the fourth (p < 0.05). Milk fat concentration was the highest in the fourth parity and the lowest in the first parity (p < 0.05). In the first parity, the highest levels of milk protein and lactose were seen (5.24% and 4.90%, respectively). However, milk protein concentration was the lowest in the third parity, and the lactose concentration was the lowest in the fifth, sixth, seventh, and eighth parities. According to the rumen sensor, the rumen temperature of the dairy cows at the two farms also continued to increase (p < 0.05) from July to August, and then decreased (p < 0.05) in September. However, the activity in the rumen was increased (p < 0.05) from July to September. In the second parity, the highest rumen temperature (39.02 °C) was observed, while the lowest value (38.28 °C) was observed in the third parity. The highest value of rumen activity (12.26 mg) was observed in the second parity and the lowest value (11.31 mg) in the fourth parity. These data, taken together, confirm that a high THI during summer conditions negatively affects milk yield, milk protein content, and rumen temperature and activity in lactating Holstein cows. It is also demonstrated that various parities affect milk characteristics and the rumen environment in the summer season. [ABSTRACT FROM AUTHOR]

This survey investigated, using robotic milking and rumen sensors, the effects of an adjusted temperature–humidity index (THI) in different geographical areas on milk yield, fat and protein, rumen temperature, and activity in lactating Holstein cows. We additionally explored the effect of parity on milk and rumen temperature and activity under different THI levels during the summer. From January to September 2020, four farms (276 dairy cows) were subjected to the use of robot milking machines, and two farms (162 dairy cows) to the use of rumen sensors. For the temperature and humidity data, the THI was calculated on the basis of the data from the Korea Meteorological Administration (KMA). The data were analyzed using the GLM procedure of SAS. Milk yield and milk protein decreased (p < 0.05), and milk fat increased (p < 0.05) at all farms during the summer, from July to August, when the temperature and humidity were high (THI = 72–79). Milk yields were the highest in the fifth, sixth, seventh, and eighth parities, and the lowest in the fourth (p < 0.05). Milk fat concentration was the highest in the fourth parity and the lowest in the first parity (p < 0.05). In the first parity, the highest levels of milk protein and lactose were seen (5.24% and 4.90%, respectively). However, milk protein concentration was the lowest in the third parity, and the lactose concentration was the lowest in the fifth, sixth, seventh, and eighth parities. According to the rumen sensor, the rumen temperature of the dairy cows at the two farms also continued to increase (p < 0.05) from July to August, and then decreased (p < 0.05) in September. However, the activity in the rumen was increased (p < 0.05) from July to September. In the second parity, the highest rumen temperature (39.02 °C) was observed, while the lowest value (38.28 °C) was observed in the third parity. The highest value of rumen activity (12.26 mg) was observed in the second parity and the lowest value (11.31 mg) in the fourth parity. These data, taken together, confirm that a high THI during summer conditions negatively affects milk yield, milk protein content, and rumen temperature and activity in lactating Holstein cows. It is also demonstrated that various parities affect milk characteristics and the rumen environment in the summer season.

The introduction of heifers into the automatic milking system (AMS) can be associated with considerable stress for both animals and farm employees, as completely inexperienced heifers initially do not independently enter the unknown milking robot. This study investigated whether training heifers on an AMS phantom provides the possibility of preparing heifers for the following lactation at the AMS. For this purpose, 77 Holstein-Friesian heifers were randomly assigned to one of 2 experimental groups: control (CON) or phantom (PHAN). Four weeks before calving, the PHAN group was given free access to the phantom, which was similar to the actual milking robot, so that they could explore it and be positively conditioned by feeding concentrate in the phantom. The heifers of the CON group had no contact with the phantom or the AMS before the first milking at the AMS. The milking frequency per animal per day was recorded, and the proportion of animals that had to be fetched for milking was determined, to evaluate how the animals accepted the AMS after calving. To assess the stress level of the animals before and after introduction into the AMS, fecal cortisol concentrations and rumination times of the animals were measured. Additionally, lactation performance characteristics (milk yield, milk flow, electrical conductivity of milk, and milk composition) were recorded for 77 animals. The animals trained on the phantom showed a higher milking frequency (DIM 7: 2.70 ± 0.14 visits/d) than the control animals (DIM 7: 2.41 ± 0.14 visits/d) between the 4th and 10th day of lactation. In addition, between d 1 and d 5, the proportion of animals that had to be fetched for milking was lower in PHAN (DIM 1: 35.18 ± 4.16%) than in CON (DIM 1: 48.03 ± 4.46%). The PHAN heifers had unexpectedly high fecal cortisol levels (1 wk prepartum: 43.50 ± 0.93 ng/g of feces), although not considerably elevated compared with CON (1 wk prepartum: 40.76 ± 1.05 ng/g of feces). Training on the phantom had no appreciable influence on rumination time and lactation performance parameters. The increased number of milking visits and the reduced proportion of animals that had to be fetched into the AMS for milking indicate that training on the phantom prepares the animals well for being milked in the AMS. Therefore, training heifers on the phantom offers the possibility to facilitate the start into early lactation for the animals, providing a valuable contribution to improvement of animal welfare. [ABSTRACT FROM AUTHOR]

The aim of this study was to demonstrate the noninferiority of a novel teat disinfectant based on copper and zinc (ZkinCu; Copper Andino, Santiago de Chile, Chile) compared with a previously proven glycolic acid active disinfectant (OceanBlu; DeLaval, Kansas City, MO) as a positive control, with respect to the incidence of new intramammary infections under natural challenge conditions on a commercial robotic dairy farm. This study was conducted in 6 robotic pens of approximately 60 milking cows each. The pens were randomly assigned to 1 of the 2 studied disinfectants. Throughout the 8 wk study, the same pre- and post-milking teat disinfectant was used in each pen. The same milking procedures were used in each robot throughout the study. Pre-milking hygiene consisted of applying the disinfectant (OceanBlu or ZkinCu) with the robotic arm. The same product was applied on the teats after milking. At the beginning of the study, all quarters of all study cows were sampled. In successive samplings (wk 2, 4, 6, and 8), composite milk samples were collected on farm to determine SCC. Once composite SCC results were available (2 d) and based on an SCC of ≥100,000 cells/mL, quarter milk samples underwent bacteriological culture. Clinical mastitis was identified by study personnel. Intramammary infection in biweekly quarter milk samples was determined based on composite SCC levels (≥100,000 cells/mL) and the presence of bacteria. A new IMI was defined as a quarter in which the organism isolated was not present in the previous bacteriological sample, or the previous composite SCC sample was <100,000 cells/mL. Clinical mastitis samples were also considered to be new IMI. The trial was designed as a positive control field trial, in which the objective was to show noninferiority of ZkinCu versus the control (OceanBlu). The overall crude incidences of new IMI for 2 wk at risk were 4.9 and 7.3% for the ZkinCu and OceanBlu groups, respectively. The predominant organisms recovered from quarters with new IMI were Streptococcus uberis , Corynebacterium spp., and coagulase-negative staphylococci in both the ZkinCu and OceanBlu groups. The risk of infection in the OceanBlu group was higher (β = 0.644; 95% confidence interval = 0.05–1.22). The interaction of treatment by week was not significant. The new IMI rate estimates (95% confidence interval) for ZkinCu and OceanBlu were 1.7% (0.8–2.5) and 3.2% (1.7–4.7), respectively. One novel aspect of this study is that it was one of the first commercial noninferiority trials to evaluate a new pre- and post-milking teat disinfectant in a dairy herd with an automatic milking system. The experimental teat disinfectant ZkinCu, evaluated in this field trial with naturally occurring IMI, showed noninferiority relative to the positive control for the prevention of new IMI. This study was conducted in a herd with an automatic milking system, and the results are applicable to herds with similar characteristics. Additional studies are needed to ensure reproducibility under different management conditions. [ABSTRACT FROM AUTHOR]

The transition period is a pivotal time in the production cycle of the dairy cow. It is estimated that between 30% and 50% of all cows experience metabolic or infectious disease during this time. One of the most common and economically consequential effects of disease during the transition period is a reduction in early lactation milk production. This has led to the utilisation of deviation from expected milk yield in early lactation as a proxy measure for transition health. However, to date, this analysis has been used exclusively for the retrospective assessment of transition cow health. Statistical models capable of predicting deviations from expected milk yield may allow producers to proactively manage animals predicted to suffer negative deviations in early lactation milk production. The objective of this retrospective cohort study was first, to explore the accuracy with which cow-level production and behaviour data collected on automatic milking systems (AMS) from 1–3 days in milk (DIM) can predict deviation from expected 30-day cumulative milk yield in multiparous cows. And second, to assess the accuracy with which predicted yield deviations can classify cows into groups which may facilitate improved transition management. Production, rumination, and physical activity data from 31 commercial AMS were accessed. A 3-step analytical procedure was then conducted. In Step 1, expected cumulative yield for 1–30 DIM for each individual cow-lactation was calculated using a mixed effect linear model. In Step 2, 30-Day Yield Deviation (YD) was calculated as the difference between observed and expected cumulative yield. Lactations were then assigned to one of three groups based on their YD, RED Group (0% YD). In Step 3, yield, rumination, and physical activity data from days 1–3 in lactation were used to predict YD using machine learning models. Following external validation, YD was predicted across the test data set with a mean absolute error of 9%. Categorisation of animals suffering large negative deviations (RED group) was achieved with a specificity of 99%, sensitivity of 35%, and balanced accuracy of 67%. Our results suggest that milk yield, rumination and physical activity patterns expressed by dairy cows from 1–3 DIM have utility in the prediction of deviation from expected 30-day cumulative yield. However, these predictions currently lack the sensitivity required to classify cows reliably and completely into groups which may facilitate improved transition cow management. [ABSTRACT FROM AUTHOR]

The adoption of innovative processes, such as the automatic milking system (AMS), in the production of typical PDO cheeses, such as Parmigiano Reggiano, needs to be evaluated and tested, to verify its influence on milk quality and the typicality of the product. The present research was aimed to study the effect of the introduction of the AMS on the cheesemaking characteristics of the milk and the ripening process and the sensory properties of the Parmigiano Reggiano PDO cheese. Six cheesemaking trials were performed and, in each trial, two different separated pools of milk were submitted to the cheesemaking process in parallel, one from AMS and the other from a traditional milking parlor (TMP). AMS milk, in comparison with TMP one, showed higher content of lactose and calcium and lower contents of somatic cells, thermophilic lactic acid bacteria and chloride. Nevertheless, these changes were too small to influence the efficiency of the cheesemaking process and the cheese composition and its sensory profile. Moreover, cheeses made with AMS milk fully complied with the sensory characteristics of Parmigiano Reggiano cheese PDO, as defined by the PDO rules.

The objective of this study was to determine the effect of the rumination time on milk yield and composition as well as methane emission during lactation in high-yielding dairy cows fed a partial mixed ration based on maize silage without pasture access. A total of 365 high-yielding Polish Holstein-Friesian multiparous dairy cows were included in the study covering 24 to 304 days of lactation. Methane emission, rumination time, and milk production traits were observed for the period of 12 months. Next, the data from the cows were assigned to three groups based on daily rumination time: low rumination up to 412 min/day (up to 25th rumination percentile), medium rumination from 412 to 527 min/day (between the 25th and 75th percentile), and high rumination above 527 min/day (from the 75th percentile). Rumination time had no effect on milk yield, energy-corrected milk yield, or fat and protein-corrected milk yield. High rumination time had an effect on lower fat concentration in milk compared with the medium and low rumination groups. The highest daily CH4 production was noted in low rumination cows, which emitted 1.8% more CH4 than medium rumination cows and 4.2% more than high rumination cows. Rumination time affected daily methane production per kg of milk. Cows from the high rumination group produced 2.9% less CH4 per milk unit compared to medium rumination cows and 4.6% in comparison to low rumination cows. Similar observations were noted for daily CH4 production per ECM unit. In conclusion, a longer rumination time is connected with lower methane emission as well as lower methane production per milk unit in high-yielding dairy cows fed a maize silage-based partial mixed ration without pasture access.

Abstract Background Having a poor teat-end condition is associated with increased mastitis risk, hence avoiding milking machine settings that have a negative effect on teat-end condition is important for successful dairy production. Milking-time testing (MTT) can be used in the evaluation of vacuum conditions during milking, but the method is less suited for herds using automatic milking systems (AMS) and relationships with teat end condition is poorly described. This study aimed to increase knowledge on interpretation of MTT in AMS and to assess whether milk-flow data obtained routinely by an AMS can be useful for the management of teat-end health. A cross-sectional study, including 251 teats of 79 Norwegian Red cows milked by AMS was performed in the research herd of the Norwegian University of Life Sciences. The following MTT variables were obtained at teat level: Average vacuum level in the short milk tube during main milking (MTVAC), average vacuum in the mouthpiece chamber during main milking and overmilking, teat compression intensity (COMPR) and overmilking time. Average and peak milk flow rates were obtained at quarter level from the AMS software. Teat-end callosity thickness and roughness was registered, and teat dimensions; length, and width at apex and base, were measured. Interrelationships among variables obtained by MTT, quarter milk flow variables, and teat dimensions were described. Associations between these variables and teat-end callosity thickness and roughness, were investigated. Results Principal component analysis showed clusters of strongly related variables. There was a strong negative relationship between MTVAC and average milk flow rate. The variables MTVAC, COMPR and average and peak milk flow rate were associated with both thickness and roughness of the callosity ring. Conclusions Quarter milk flow rate obtained directly from the AMS software was useful in assessing associations between milking machine function and teat-end condition; low average milk flow rates were associated with a higher likelihood of the teat having a thickened or roughened teat-end callosity ring. Since information on milk flow rate is readily available from the herd management system, this information might be used when evaluating causes for impaired teat-end condition in AMS.

The objective of this experiment was to establish the effect of low-concentrate (LC) and high-concentrate (HC) supplementation in the early and late periods of lactation on milk production and cow traffic in a pasture-based automatic milking (AM) system. In total, 40 cows (10 primiparous and 30 multiparous) were randomly assigned to one of the two treatments. The experimental periods for the early and late lactation trials extended from 23 February to 12 April 2015 and 31 August to 18 October 2015, respectively (49 days in each trial period). The early lactation supplement levels were 2.3 and 4.4 kg/cow per day for LC and HC, respectively, whereas the late lactation supplement levels were 0.5 and 2.7 kg/cow per day for LC and HC, respectively. Variables measured included milking frequency, milking interval, milking outcome and milking characteristics, milk yield/visit and per day, wait time/visit and per day, return time/visit and the distribution of gate passes. As the herd was seasonal (spring) calving, the experimental periods could not run concurrently and as a result no statistical comparison between the periods was conducted. There was no significant effect of treatment in the early lactation period on any of the milk production, milking characteristics or cow traffic variables. However, treatment did significantly affect the distribution of gate passes, with the HC cows recording significantly more gate passes in the hours preceding the gate time change such as hours 7 (P

The research topic is relevant due to a high rate of the implementation of milking robots (automatic milking system, AMS) in Western Europe and in the Middle Urals. As of January 1, 2016, 21 milking robot systems of six different brands of foreign production were installed in the region. Milking robotics is used in small, medium and large enterprises (by the number of personnel), in contrast to Western Europe, where it is mainly used on the farms of family type. The article examines the socioeconomic causes of the introduction of robotics, as well as the impact of the use of robots to the economic indicators of milk production. The expert survey has revealed as the main reasons for the introduction of robotics, a desire to reduce the risks of personnel (45.5 %) and a shortage of staff (18.2 %). The analysis of the utilization efficiency of fixed assets in all organizations introduced robots has shown both a decrease of capital productivity after the introduction of milking robots for 15–60 % or more, and the reduce of the profit rate in 9 out of 11 of the analysed organizations because of the high capital intensity of robotics projects. The analysis of labour indicators and the net cost of milk is carried out in 45.5 % of organizations, where we have obtained the consistent results of the use of robotics. The authors have analysed the direct costs for the production of 1 quintal of milk. In a group of 5 companies, on a robotic farm, it is 5.1 % lower than in a conventional farm. The complexity of the production of milk on a robotic farm is lower by 48.7 %, and labour productivity per person is higher on 95.3 % than on conventional farms. The results of the study can be used as the recommendations for agricultural organizations to use robotics milking to reduce the deficit of staff and to minimize the impact of personnel risks on production results. The growth of the importance of the reasons for the introduction of milking robots and a high capital intensity of import robotics can justify the need for a national milking robotics.

With increasing intensification of the dairy sector in many countries and with the introduction of automatic milking, exercise paddocks combined with full indoor feeding, as an alternative to production pasture, are being used as a compromise between farm economics and cow welfare. This study examined whether there are production benefits for high-producing dairy cows in an alternative system that uses pasture at a level of approximately 50% of the total roughage intake in the diet. In an automatic milking system with 12-h night access to the outdoor environment, we compared milk production and behavior of cows in 2 systems: an exercise paddock combined with ad libitum grass silage indoor feeding and a production pasture combined with a restricted daytime grass silage ration. There were 20 cows in the former and 21 cows in the latter system, with the treatments running in parallel. The experiment started in late June with no complete darkness during the night, and lasted for 12 wk, with 5.6 h of darkness at the end. We therefore also explored the effect of night length on milk production and behavior parameters. All cows showed strong motivation for going outdoors and grazing when pasture access was given in early evening, but after a few hours both groups went to the barn and did not return to the pasture area during the remaining night. As the season progressed and nights became longer, cows on the exercise paddock treatment reduced time spent outdoors and grazing time, whereas they increased time spent resting outdoors. The group on exercise paddock had a greater milk yield (kg of milk) over the experimental period than the production pasture group. The latter group also showed a greater drop in milk yield over the duration of the trial. Thus, for cows milked in an automatic milking system and offered nighttime outdoor access, no milk production benefits were observed in offering production pasture with restricted indoor silage allowance instead of an exercise paddock with ad libitum silage. We therefore suggest that automatic milking farmers with similar production levels and automatic milking-management systems as in the present experiment, who wish to include grazed grass as part of the dairy cow diet, should ensure that cows have pasture access in the afternoon and evening. [ABSTRACT FROM AUTHOR]

In this study, we hypothesized that differences of automatic milking systems (AMS) variables in dairy cows during estrus and through diverse stages of lactation can be suggested as alternative indicators to support the pregnancy in dairy farms using automatic milking systems. The key objectives were: (1) to determine the variation of automatic milking system indicators during lactation and to estimate the relationship with reproduction status in dairy cows; (2) to test the hypothesis that milking traits of cows can be influenced by estrus and conceiving, and can be used as a predictor of the likelihood of reproductive success in dairy herds. Estrus synchronization was performed in 368 healthy Lithuanian Black and White cows. All cows (n = 368) were synchronized and inseminated for the first time on the 91st day in milk (DIM). Cows not pregnant (17.39%) were synchronized and inseminated again at 132 DIM. After the first insemination pregnant (n = 304) cows were identified as group 1, after the second insemination pregnant (n = 58) cows – as group 2. Overall, 12 01 713 records of udder quarters in cows from 5 to 305 DIM were evaluated. The results revealed the reduction in milk yield during estrus 11.05% on 91 DIM and 13.89% on 132 DIM (P < 0.001) and an increment in milk flow traits in cows after 91 DIM (P < 0.05), also a slight decline in milk flow traits on 132 DIM. Furthermore, milking frequency (MF) of cows decreased significantly (P < 0.001) after conceiving. The interval between milkings (MI) increased (40.30%) during estrus of cows in group 1 (P < 0.001), and thereafter gradually increased, however in group 2 there was a temporary increment (6.06%) on the 91 DIM and steady rise (42.13%) on 132 DIM was noticed. The results highlight that changes in AMS indicators of cows may be considered as an additional tool for improvement of reproductive management in dairy herds, but further research-based studies are necessary before practical application. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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

• Demand for dairy products increases constantly. • New tools and techniques need to be implemented in the production. • Using automatic milking and feeding stations improves dairy production. • Optimization of the use of different tools and techniques is crucial for production. • Combining different techniques may improve milking efficiency and milk yield. 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. [ABSTRACT FROM AUTHOR]

Highlights • Automatic milking with outdoor time restricted to mornings and evenings was used. • Outdoor management systems with exercise vs. production pasture were compared. • Milk yield was maintained at a similar high level in both treatments. • Milking frequency was higher for animals with an exercise paddock. • Time spent outdoors was higher for animals with a production pasture. Abstract Although pasture is low-cost feed, many farmers find it difficult to maintain high milk yield when using pasture for high-yielding dairy cows in automatically milked herds. Therefore, a seven-week experiment with 40 cows in early to mid-lactation was performed to evaluate a management model for including pasture in the diet without jeopardizing milk production. Within a part-time grazing system with morning and evening outdoor access, we compared a group with ad libitum grass silage indoors combined with access to a small grass-covered permanent paddock for exercise and recreation (group EX) with a group offered production pasture at a high allowance per cow and day combined with restricted grass silage allowance at night (group PROD). Both groups had the same outdoor access times and the same concentrate allowance based on pre-experimental milk yield. Milk yield and milking frequency were recorded daily in the automatic milking unit. Milk recordings and samplings for determination of milk composition took place weekly and outdoor behaviour of cows was recorded during pasture access hours on six observation days, evenly distributed over the experimental period. During the experiment, average metabolisable energy concentration was higher in the grass silage offered both groups than in pasture herbage. However, our results showed no significant difference in daily milk yield between treatments. Furthermore, no significant differences between treatments were found in energy-corrected milk, milk fat production, or body weight change. Milk protein production was, however, significantly higher in group PROD. In early lactation, no difference in milking frequency was observed between treatments while for cows in mid- to late lactation, milking frequency was significantly higher in group EX than group PROD. Over the entire experiment, group EX cows spent significantly less time outdoors than group PROD. In conclusion, offering high yielding dairy cows in automatic milking systems high-quality pasture at a high allowance for a few hours in morning and afternoon appears to be an interesting alternative to exercise paddock with full indoor feeding, as it can reduce costs for supplementary silage, facilitate natural behaviour, and encourage cows to spend more time outdoors, while maintaining milk production at a level comparable to that of full indoor feeding. [ABSTRACT FROM AUTHOR]

The objectives of this cross-sectional study were to describe housing and management practices on farms using automatic milking systems (AMS) in 2 states of the upper Midwest and to evaluate the association of various housing and management factors with 3 measures of animal welfare: prevalence of lameness, severe hock lesions, and dirty cows. Fifty-four farms were visited once to collect facility measurements and observations, interview the dairy producer, and score cows for locomotion, hock lesions, and hygiene. Median number of AMS units/farm was 2 (interquartile range = 1; range = 1 to 8). Factors concerning labor were the most commonly cited reason by dairy producers for making the transition to the AMS; additional commonly cited factors were an improvement in lifestyle and human health. Number of cows fetched per AMS, or manually brought to the AMS if not milked voluntarily, was 4.7 ± 2.3 cows/AMS per day (8% of cows) for free traffic flow farms and 3.3 ± 1.8 cows/AMS per day (5% of cows) for guided traffic flow farms. Cow resting surface was significantly associated with prevalence of lameness and severe lameness. Farms with sand-bedded freestalls (17.2%) and bedded packs (17.4%) had significantly lower lameness prevalence (score ≥3 on a 1 to 5 scale, with 1 = normal locomotion) than farms with mattress freestalls (30.5%), waterbeds (25.0%), and mattresses with access to pasture (22.6%). Farms with mattresses and access to pasture had similar lameness prevalence to farms with waterbeds, but were lower than farms with mattresses only. A somewhat similar result was found for severe lameness prevalence (score ≥4 on a 1 to 5 scale, with 1 = normal locomotion); farms with sand-bedded freestalls (2.8%), bedded packs (0.0%), and mattress freestalls with access to pasture (1.5%) had significantly lower prevalence than farms with mattresses (7.1%) or waterbeds (10.8%). Severe hock lesion prevalence (score = 3 on a 1 to 3 scale, with 1 = normal, 3 = swelling) in herds with sand-bedded freestalls, waterbeds, and bedded packs were similar and significantly lower than the prevalence in mattress-based freestalls. Cows housed in sand-bedded freestalls had significantly lower prevalence of dirty cows (score = 3 or 3.5 on a 1 to 5 scale, with 1 = clean) than those housed on mattresses and waterbeds, and had significantly lower prevalence of severely dirty cows (score = 4, 4.5 or 5 on a 1 to 5 scale, with 1 = clean) than all other housing systems except waterbeds, which was similar. Manure removal system (manual, automatic, or slatted floor) was significantly associated with prevalence of severely dirty cows; farms with manual scraping had lower prevalence of severely dirty cows than farms where alley scraping was practiced automatically or slatted floors were used. Dairy producers using AMS appeared to be successful with a variety of facility designs and management practices. Cow resting surface in AMS herds was associated with some animal health and welfare measurements. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The objective of this study was to identify housing and management factors associated with productivity on automatic milking system (AMS) dairy farms measured as daily milk yield/AMS and daily milk yield/ cow. Management, housing, and lameness prevalence data were collected from 33 AMS farms in Minnesota and Wisconsin during a farm visit. All farms in the study used free-flow cow traffic. Mixed model analysis of cross-sectional data showed that farms with automatic feed push-up via a robot produced more milk per AMS/day and per cow/day than farms where feed was pushed up manually. New versus retrofitted facility, freestall surface, manure removal system, and the number of AMS units/pen were not associated with daily milk yield per AMS or per cow. Cow comfort index (calculated as number of cows lying down in stalls divided by total number of cows touching a stall) was positively associated with daily milk yield/cow. Prevalence of lameness and severe lameness, number of cows per full-time employee, depth of the area in front of the AMS milking station, and length of the exit lane from the AMS milking station were not associated with daily milk yield per AMS or per cow. Multivariable mixed model analysis of longitudinal AMS software data collected daily over approximately an 18-mo period from 32 of the farms found a positive association between daily milk yield/AMS and average age of the cows, cow milking frequency, cow milking speed, number of cows/ AMS, and daily amount of concentrate feed offered/ cow in the AMS. Factors negatively associated with daily milk yield/AMS were number of failed and refused cow visits to the AMS, treatment time (the time spent preparing the udder before milking and applying a teat disinfectant after milking), and amount of residual concentrate feed/cow. Similar results were also found for daily milk yield on a per cow basis; however, as it would be expected, average days in milk of the herd were also negatively associated with daily milk yield/ cow. These findings indicate that several management and cow factors must be managed well to optimize AMS productivity. [ABSTRACT FROM AUTHOR]

The objective of this experiment was to establish the effect of low-concentrate (LC) and high-concentrate (HC) supplementation in the early and late periods of lactation on milk production and cow traffic in a pasture-based automatic milking (AM) system. In total, 40 cows (10 primiparous and 30 multiparous) were randomly assigned to one of the two treatments. The experimental periods for the early and late lactation trials extended from 23 February to 12 April 2015 and 31 August to 18 October 2015, respectively (49 days in each trial period). The early lactation supplement levels were 2.3 and 4.4 kg/cow per day for LC and HC, respectively, whereas the late lactation supplement levels were 0.5 and 2.7 kg/cow per day for LC and HC, respectively. Variables measured included milking frequency, milking interval, milking outcome and milking characteristics, milk yield/visit and per day, wait time/visit and per day, return time/visit and the distribution of gate passes. As the herd was seasonal (spring) calving, the experimental periods could not run concurrently and as a result no statistical comparison between the periods was conducted. There was no significant effect of treatment in the early lactation period on any of the milk production, milking characteristics or cow traffic variables. However, treatment did significantly affect the distribution of gate passes, with the HC cows recording significantly more gate passes in the hours preceding the gate time change such as hours 7 (P<0.01), 15 (P<0.05), 20, 21 (P<0.001), and 22 (P<0.05), whereas the LC treatment recorded significantly more gate passes in the hours succeeding the gate time change, such as time points 2 (P<0.01) and 10 (P<0.05). There was a significant effect of treatment in late lactation, with HC having a greater milk yield (P<0.01), milking duration and activity/day (P<0.05), while also having a significantly shorter milking interval (P<0.05) and return time/visit (P<0.01). The distribution of gate passes were similar to the early lactation period, with HC also recording a significantly greater number of gate passes during the early morning period (P<0.01) when visitations were at their lowest. Any decision regarding the supplementing of dairy cows with concentrates needs to be examined from an economic perspective, to establish if the milk production and cow traffic benefits displayed in late lactation outweigh the cost of the concentrate; thereby ensuring that the decision to supplement is financially prudent. [ABSTRACT FROM PUBLISHER]

Background: Having a poor teat-end condition is associated with increased mastitis risk, hence avoiding milking machine settings that have a negative effect on teat-end condition is important for successful dairy production. Milking-time testing (MTT) can be used in the evaluation of vacuum conditions during milking, but the method is less suited for herds using automatic milking systems (AMS) and relationships with teat end condition is poorly described. This study aimed to increase knowledge on interpretation of MTT in AMS and to assess whether milk-flow data obtained routinely by an AMS can be useful for the management of teat-end health. A cross-sectional study, including 251 teats of 79 Norwegian Red cows milked by AMS was performed in the research herd of the Norwegian University of Life Sciences. The following MTT variables were obtained at teat level: Average vacuum level in the short milk tube during main milking (MTVAC), average vacuum in the mouthpiece chamber during main milking and overmilking, teat compression intensity (COMPR) and overmilking time. Average and peak milk flow rates were obtained at quarter level from the AMS software. Teat-end callosity thickness and roughness was registered, and teat dimensions; length, and width at apex and base, were measured. Interrelationships among variables obtained by MTT, quarter milk flow variables, and teat dimensions were described. Associations between these variables and teat-end callosity thickness and roughness, were investigated. Results: Principal component analysis showed clusters of strongly related variables. There was a strong negative relationship between MTVAC and average milk flow rate. The variables MTVAC, COMPR and average and peak milk flow rate were associated with both thickness and roughness of the callosity ring. Conclusions: Quarter milk flow rate obtained directly from the AMS software was useful in assessing associations between milking machine function and teat-end condition; low average milk flow rates were associated with a higher likelihood of the teat having a thickened or roughened teat-end callosity ring. Since information on milk flow rate is readily available from the herd management system, this information might be used when evaluating causes for impaired teat-end condition in AMS. [ABSTRACT FROM AUTHOR]

The probability of raising milk discharge for cows during early hours after milking under affection of the milking problems exceeding threshold limits of nervous impulses sensitivity that can motivate more emission in blood of the hormones intensifying metabolism and milk discharging procedure in an animal organism is made. Finding this order enables to offer a scientific description to different efficiency of milking cows by hand and by milking machines. It offers a new scientific way in enhancing and improving milking equipment which milking has to be done by doing severe massage of nipples and an udder. This will enable scientists to explain the major ways of better controlling lactation function of an animal, so milk increase yield, we find out milking motives are important, explanation of ways and frequency of milking, improving of the automatic milking systems of animals with deteriorating milking problems. [ABSTRACT FROM AUTHOR]

Robotic milking reduces labor demands on dairy farms of all sizes and offers a more flexible lifestyle for farm families milking up to 250 cows. Because milking is voluntary, barn layouts that encourage low-stress access by providing adequate open space near the milking stations and escape routes for waiting cows improve milking frequency and reduce fetching. Because lame cows attend less often, preventing lameness with comfortable stalls, clean alley floors, and effective foot bathing warrants special emphasis in robotic dairies. Variable milking intervals create challenges for foot bathing, sorting and handling, and dealing with special-needs cows. Appropriate cow routing and separation options at the milking stations are needed to address these challenges and ensure that the expected labor savings are realized. Protocols and layout and gating should make it possible for a herd worker to complete all handling tasks alone. Free traffic and guided traffic systems yield similar results when excellent management is applied or when the number of cows is well below capacity. In less ideal circumstances, guided traffic and the use of commitment pens result in longer standing times and stress, particularly for lower ranking cows, and poor management with free traffic results in more labor for fetching. [ABSTRACT FROM AUTHOR]

The heart rate variability (HRV) parameters of dairy cows were monitored during parlour (PARL) and the later installed automatic (AMS) milking on a small-scale commercial dairy farm in Hungary. The aim of the study was to assess stress in relation to the type of milking and the frequency of human interaction. Parlour milking involved regular moving and crowding of the animals with frequent human interaction, which were much less frequent in automatic milking. The first phase of the study was conducted prior to the changeover [n = 27] and the second two months afterwards [n = 19 (of the cows from the first phase)]. Heart rate (HR) was recorded by the Polar RS800 CX recording system. HRV parameters indicative of sympathovagal balance were calculated for periods of lying and standing in the barn, waiting before milking and milking, respectively. Morning and evening faecal glucocorticoid concentrations were also measured. Fear of humans was tested by an avoidance distance test. Baseline HRV parameters showed no difference (P > 0.05) between the two systems. In the periods before, during and after milking a higher sympathetic tone was detected in cows in the PARL phase. Mean faecal glucocorticoid concentrations were higher at the time of parlour milking. The avoidance distance did not differ between the two phases. The results suggest that automatic milking might be less stressful for cows than parlour milking, possibly due to the shorter duration of restraint after milking and the less frequent human interaction. [ABSTRACT FROM AUTHOR]

The objective of the studies reported in this research communication was to investigate differences in composition and enzymatic activities in bulk milk samples provided from Swedish dairy farms with different management systems, i.e. automated (AMS) and conventional milking systems (CMS). A bulk milk sample was collected from each of 104 dairy farms, 51 using AMS and 53 using CMS, located in the same geographical region. Sampling took place within two consecutive days during the indoor period (October). Milk samples were analysed for contents of total fat and protein, free fatty acids (FFA), caseins and whey proteins, somatic cell count (SCC), pH, plasmin and plasminogen derived activities, and total proteolysis. Our results showed a lower protein content and higher SCC in bulk milk from AMS herds compared with milk from CMS herds. Plasmin, plasminogen and total plasmin/ plasminogen derived activities were lower in milk from AMS herds but despite this, total casein and the ß-casein fraction as % of total protein were lower in milk from AMS herds than in milk from herds using CMS. Total proteolysis was higher in milk from AMS herds, suggesting that other proteases than plasmin, e.g. cellular and bacterial proteases, contributed to the degradation of casein. This was supported by a positive correlation between SCC and total proteolysis (P < 0·01), as well as a negative correlation between total proteolysis and ß-casein fraction (P < 0·05). In conclusion, comparing the quality of bulk milk from commercial dairy herds using AMS and CMS, respectively, several differences were observed, suggesting a significant effect from management system. [ABSTRACT FROM PUBLISHER]