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Innovation and implementation of new technology in farming is considered important to meet challenges for agriculture to increase sustainability and improve efficiency in production. Less emphasise has been on how the farmers experience the new technology. This paper responds to this gap and explores how Automatic Milking Systems (AMS) influence farmers’ job satisfaction. The research questions are: Are there differences in the experienced level of job satisfaction between AMS farmers and farmers applying Conventional Milking Systems (CMS)? Which factors determine the level of job satisfaction in dairy farming? Do these factors vary on AMS farms compared to CMS farms? The empirical data is based on a survey to a sample of dairy farmers with AMS and CMS. The results show that the most important factors which influence job satisfaction positively are common for AMS and CMS; Increased income, new cowshed, there is a successor present, farmer wants to continue farming. Contrary, higher education and being a male reduces job satisfaction. Further, the results show that AMS farmers are more satisfied with their working day, their occupational safety and their working environment. Other factors which influence job satisfaction for dairy farmers are; Less paper work, working together, considering technological competence less important, being appreciated, considering economic competence less important, increasing milk quota, loneliness and health worries. However, these factors can to a varying degree be explained from an AMS/CMS perspective, even though they differ between the two technologies.

When a farm that was using a conventional milking system introduces an automatic milking system (AMS) possible risk factors can affect milk quality. The aim of the study was to investigate the influence of milking with automatic milking systems on milk quality variables over a long time-period post-installation. Bulk milk total bacterial count (BMTBC) and somatic cell count (BMSCC) were analysed and compared from 2 years before introduction of automatic milking until 4 years after. Differences regarding these quality parameters were contrasted using t-test and one-way analysis of variance (ANOVA) and post hoc comparisons were performed. A significant increase in BMTBC was observed during the first three months after introduction of AMS, counts then declined to equivalent levels pre-AMS installation, from 25,000 to 50,000 cfu mL−1. Although differences were significant for the first two years post-installation, they became non-significant during the following two years. The difference in BMSCC was not statistically significant between pre and post-AMS installation time periods, but by grouping data into annual periods, significantly higher values of BMSCC were found during the first year after introduction. Nevertheless, these values decreased over time and even showed a significant improvement in the third year with respect to pre-introduction. The data show that the installation of AMS had a marked impact on milk quality. However, as soon as farmers become accustomed to managing the new equipment and the adaption of cows is real, a level of milk quality which can be maintained over time is achievable. SI

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

The effect of Temperature Humidity Index (THI) on dairy cows’ willingness to be on pasture was examined. Information for 2 years regarding weather, milk production, and time for voluntarily passing a gate between the barn and pasture of cows milked with an automatic milking system was studied. When the THI exceeded 72 during the day, more cows spent time on pasture compared to when the THI was less than 72 (27.0% vs. 19.2% of cows on pasture, respectively). However, the time of day influenced the proportion of cows on pasture, and when the THI exceeded 72, more cows were on pasture at night and less during the afternoon compared to days when the THI was less than 72. In conclusion, even under Swedish conditions, THI might have an effect on cows’ behaviour. However, when the cows have free access to roughage and pasture, an increased THI does not affect milk production.

Milkability and udder conformation traits of Swedish Holstein (SH) and Swedish Red (SR) cows from 93 herds with automatic milking systems or conventional milking parlors were used to study genetic relationships to lactation average somatic cell score (LSCS) and incidence of clinical mastitis (CM). Estimated genetic correlations between measures of milking speed (average flow rate, milking time and box time) and LSCS ranged between 0.29 and 0.57 and showed that high milking speed is associated with increasing LSCS. Regressions indicated a curvilinear relationship. Genetic correlations between milking speed and CM showed similar values as for LSCS in SH cows, but were inconsistent in SR cows. Shallow udder and strong fore udder attachment were consistently correlated with good udder health. The unfavorable relationships between milking speed and udder health traits should be considered together with a few udder conformation traits when selecting for better milkability.

Automatic milking systems (AMS) allow recording of alternative milkability measures. Our objectives were to estimate genetic parameters for teat cup attachment failures (AtF), incomplete milkings (...

Most of the available scientific literature concerning claw vacuum drops and fluctuations (identical to teat-end vacuum) during machine milking has been published in the 1960s and 1970s. Fewer studies have been carried out more recently on modern types of dairy cows, and milking machines, and have been evaluated with modern statistical methods and software. Based on the accessible information, there are indications that reduced milking performance, leading to long machine-on time mainly as a consequence of a combination of vacuum drops and different types of fluctuations, may influence udder health in a negative way although scientific proofs are scarce. Based on an ISO note, the claw vacuum should remain within a range of 32–42 kPa during peak milk flow to ensure fast, complete and gentle milking. This range of vacuum pressure allows adequate liner movement and a sufficient pressure on the teat during the massage (d-) phase is guaranteed. Thus, liner slips caused by too low claw vacuum are avoided. On the other hand, the teat-end vacuum should not be much higher than 42 kPa as it can cause damage of teat tissue mainly during periods of low milk flow when it is almost identical with the system vacuum. Depending on the used system of milk transport through the tubes, the teat-end vacuum drops to some extent, intensified during periods of high milk flow and reduced during periods of low or absent milk flow at the start and end of milking. Hence, a general increase of system vacuum throughout milking is not suitable, as high teat-end vacuum acting on the teat during milking phases with low milk flow rates have to be avoided. However, a reduction of machine-on time and high vacuum load on the teat during low milk flow can potentially be achieved by early cluster removal, before complete cessation of milk flow. Ideally, this goal can be reached at quarter milking (as used in automatic milking systems) where each teatcup is individually removed based on the milk flow of the individual teat, and milking at very low or no milk flow can easily be avoided.

Dairy farming is an ancient occupation. Traditionally, cows have been manually milked while tethered in stalls or stanchions. In the latter half of the 20th century as machine milking emerged, the parlor milking system has become more popular, especially among larger dairy farms. The transition from manual milking to automatic milking systems as well as the transition from stanchion to parlor milking systems involved a dramatic change in milking tasks. These transitions have resulted in changing patterns of occupational exposure to risk factors for work-related musculoskeletal disorders among dairy workers. However, aspects of the milking task such as sanitization of teats, stripping milk from teats, and attachment and detachment of milking equipment have remained relatively the same. Work-related musculoskeletal symptoms have been reported in the low back, shoulders, hands/wrists, and knees. Research that has measured exposures to risk factors for work-related musculoskeletal disorders among dairy farm workers has been limited, especially when using ergonomic tools to directly measure exposure, such as electrogoniometry or electromyography. Self-reported exposure measures have been most commonly used. The interventions that have been tested to reduce exposure to risk factors for work-related musculoskeletal disorders include assisted lift-hold devices, use of lighter-weight equipment, adjustable flooring, and use of rubber mats. However, research evaluating potential solutions to reduce dairy farm worker exposure to risk factors for musculoskeletal disorders is scarce. Future research efforts should further characterize hazards while simultaneously testing viable solutions that fit within the business model of the dairy farm industry.

The performance of dairy calves allowed to suckle freely (FS) until eight weeks of age in a cubicle system with automatic milking was compared to automatic teat-feeding with low milk (LM) or high milk (HM) substitute allowances. Weight gain and feed intake of FS (n = 13), LM (n = 23) and HM (n = 22) calves were recorded until two weeks after abrupt weaning, and their behaviour was studied during weaning. FS calves had higher weight gain, but much lower solid feed intake until weaning, than LM and HM calves and their advantage in weight remained throughout the study despite very low post-weaning gain. During the first 24 hours after weaning, FS calves displayed more behavioural signs of stress. However, at 72 hours after weaning, behaviour was similar for all treatments. Methods to stimulate solid feed intake before weaning need to be developed to draw advantage of the FS system.

This study aimed to analyse the sources of variation of milking speed assessed through automatic computerised devices included in milking machines, to study the relationships between this trait and milking speed assessed through stopwatch and to develop statistical procedures useful for converting automatic device milking time into stopwatch milking time in order to obtain a fast, simple and cheap collection of milking time records for genetic evaluation purposes. A total of 571 records of stopwatch milking time (SMT), device milking time (DMT) and milk yield at milking were collected in 23 herds of the Trentino Alto Adige region in Italy equipped with two types of automatic milking devices. After log-transformation of SMT (lnSMT) and DMT (lnDMT) and a preliminary analysis of sources of variation of lnDMT, dataset was partitioned into two mutually exclusive subsets: a calibration one, used for statistical analysis, and a validation one, used as test set to validate the prediction models. This procedure was replicated 6 times in order to repeat the cross validation accordingly. Three conversion models have been compared, based on different combinations of the effects of lnDMT, milking device and herd within milking device on lnSMT. Solutions of the models have been applied for each replicate to the validation dataset for estimating lnSMT and the soundness of conversion equations have been evaluated considering the correlation between estimated and actual lnSMT and bias and precision of estimates. Milking time assessed through different procedures resulted in differences between methods for both mean and distribution, and these suggested the need of developing statistical procedures aimed to the conversion of DMT into SMT before their use in sire evaulation. The soundness of the models tended to slightly increase with the increase in the number of effects considered. The correlation between estimated and actual SMT was in the range of 0.80 to 0.86, the estimated bias was close to 0 for all models and the precision, i.e. the average standard deviation of the difference between estimated and actual SMT, in the range of 8-9% of the mean of actual SMT. In conclusion, conversion equations proposed for joining the two sources of information performed satisfactorily, giving rise to SMT accurate estimates, which were not distorted and fairly precise. The use of such equations can support the integration of automatically acquired milking time records into breeding schemes, which is advisable for increasing the number of sires progeny tested and the accuracy of breeding values estimated.

Detection of mastitis and reliability of alarms were evaluated in eight herds with automatic milking. Herds were visited once to gather milk samples and the farmers followed up alarms for 15 to 30 days. Sensitivity of detecting quarters with SCC over the threshold value of 200,000 or 1,000,000 cells/ml was 18.0 to 42.9% in Group A, based on electrical conductivity (EC) and 5.5 to13.0% in Group B, based on EC and milk colour. Specificity was over 97.0%. In Group A, 6/17 of the EC alarms were false positives. None of the seven EC alarms in Group B was false positive. On the day that the farmer observed clinical mastitis, more than half of the quarters received alarms, but only milk from some quarters was automatically diverted. In total 58.4% (Group A) and 26.8% (Group B) of cows had alarms based on EC, and 84.1% (

In this trial, the effects of the forage feeding frequency on the waiting time prior to milking and the cowshed facility utilization by cows milked in an automatic milking unit (AMU) were studied. The feeding frequency was increased from two times per day to six times per day. It was found that the average waiting time per visit for cows using the AMU was reduced from 755 s to 351 s when the feeding frequency was increased. The daily number of visits (milking visit, failed milking visit and not qualified visit) to the AMU was not affected by the change in feeding frequency. It was also found that increasing the feeding frequency had a positive effect on utilization of the cowshed facilities, such as the occupation of the feeding fence, and on the cowshed facilities in the waiting area (cubicles) of the AMU.

Spolders, M., Meyer, U., Flachowsky, G. and Coenen, M. 2004. Comparison of resting and feeding behaviour for cows milked by an automatic milking system versus by a milking parlour. J. Appl. Anim. Res., 25: 69–80. This study deals with the influence of an automatic milking system on animal behaviour (especially feed intake, lying behaviour and stress condition) as compared to a conventional milking parlour. These influences were studied in three experiments with German Holstein dairy cows kept in a cubicle house. Harmonized with the milking procedures, roughage intake was spread more evenly over the day when cows were milked automatically. After feeding, roughage intake of cows milked automatically varied in a narrow range (0.5 to 0.8 kg per cow per hour) than for cows milked in the parlour (0.45 to 1.1 kg per cow per hour). An effect of feeding time on feed intake was observed for both milking systems. Fewer cows rested in the cubicles per hour when they were milked automatically. The high rankin...

To assess the impact of automatic milking systems (AMS) on the different aspects of milk production a research projectinvolving both commercial and experimental dairy farms with different AMS and different management was started. Thispaper reports the results of a follow-up study on primiparous cows focused on assessing some markers to be used tomonitor udder and teat health. Heifers were included after calving and sampled for at least 12 months. Quarter milk samplesand teat measurements were taken to assess: intramammary infection (IMI) frequencies, somatic cell counts (SCC),teat thickness changes, teat skin and apex conditions. The study included 28 cows in herd A and 27 in herd B for a totalnumber of 2344 samples. Overall, teat apex and skin conditions were maintained along the lactation. Teat skin conditionstended to decrease because of the accumulated number of milkings while lactation proceeded, but at a largelyacceptable level in both herds. Teat apex conditions showed a decrease. Teat thickness changes displayed different patternsin the two herds, probably because of the different type of AMS, but in both cases a trend to decrease in thicknesscould be observed. The application of AMS in herd B, free from contagious pathogens, did not influence the frequency ofIMI and the SCC. In herd A, characterized by the presence of Staphylococcus aureus IMI, the frequency of IMI showeda progressive increase, very likely as a consequence of the spread of infections during milking. Teat skin had no associationwith the frequency of IMI. Teat thickness changes outside values considered as physiological proved to be associatedwith decreased conditions in the teat apex score in herd A, but not in herd B. However, a decrease in teat apex scoreproved to be associated with an increase in IMI frequency in both herds. The results of this field trial confirm that AMShave no negative impact on IMI incidence, SCC and teat tissue conditions when the initial cow health status and overallherd management are good. In the presence of contagious pathogens, and when cows have more than 300 days in milk(DIM) the frequency of negative outcomes significantly increases and the proper control measures should be taken.

Four cow routing treatments related to fully automatic milking were compared consecutively in one group of 24 Holstein Friesian cows. The objective of the experiment was to investigate how cow traffic towards the automatic milking system (AMS) should be routed and whether a preselection or a waiting area in front of the AMS should be used. The treatments were (1) free routing with selection of cows in the AMS (FREE); (2) free routing with a preselection system in front of the AMS (FREE_SS); (3) free routing with a preselection system and a waiting area in front of the AMS (FREE_WA); and (4) one-way gates resulting in forced routing with preselection and a waiting area in front of the AMS (FORCED_WA). Evaluation of the treatments revealed that FREE may be questionable with regard to the cows' visiting frequency to the AMS and that the use of a waiting area in combination with free routing (FREE_WA) may slow down the passing through the AMS. FORCED_WA may be the best option in relation to the cows' use of the AMS, but this traffic system seems to postpone or even thwart the feeding. The treatment that appears to give the best results is FREE_SS. The type of AMS visit appeared to have a marked influence on the cows' subsequent behaviour. Cows returned to the AMS sooner after non-milking visits and failed attachments ( P

The application of Automatic Milking Systems (AMS) represents a substantial innovation in dairy cattle. The introduction of this new technology puts some questions about cow management. A correct and regular flow of animals through the milking unit appears fundamental to improve efficiency of AMS, animal welfare and performances.

The aim of this study was to determine the characteristics of the dairy farms that installed an automatic milking system (AMS). A survey of 38 dairy farms with AMS, in Galicia (Spain), collected information on quantitative and qualitative variables. Following elimination of redundant variables, categorical principal component analysis identified 4 factors accounting for 43.7% of the total variance. Using these factors, the farms studied were subjected to hierarchical cluster analysis which differentiated 4 types of farms: (A) farms with more leisure and quality of life where the AMS covered the expectations of farmers (29%); (B) farms that removed cows more often due to AMS and farmers with more stress (34%); (C) farms with little leisure and farmers with no successor (21%); (D) large farms with many fulltime employees (FTE) where the AMS had covered farmer’s expectations the least (11%). Generally the farms were based on a family structure with a high percentage of FTE. With the adoption of AMS these farms sought to increase milk production, save labour and have more flexibility. With 87% of farms with free cow traffic the activity that took the most of the farmer’s time was fetching cows for milking (1 h/day). Nearly 58% of farmers were completely satisfied with their AMS, although this value reached 91% in farms with herd sizes below the average which were better adapted to the use of one AMS. The authors are grateful for the financial support granted by the Autonomous Government of Galicia through the Directorate General for Research & Development (PGIDT/PGIDIT Project, Ref: 07MRU013291PR) SI