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The aim of the study was to analyse the effect of milking frequency during the first month after first calving on milk yield and milking parameters of the cows over the remainder of the first lactation and in subsequent lactations. The study was performed in 25 automatic milking system (AMS) herds located in Poland. The animal material under study was classified into one of five groups based on average daily milking frequency in the first month after calving (MFF): MFF1 – less than 2 times, MFF2 – between 2 and 2.5 times, MFF3 – between 2.5 and 3 times, MFF4 – between 3 and 3.5 times, MFF5 – between 3.5 and 4 times per day. Using a multivariate analysis of variance, statistical analysis showed that most of the studied factors and the interactions between them had a highly significant effect on the analysed milk yield and milking traits. The cows whose average milking frequency during the first month was lower than two, were culled in large numbers from the herd during the first lactation. The highest proportion of cows culled after the first lactation was noted in group MFF1 (68.47%) and the lowest in group MFF5 (35.29%), with the culling level after the first lactation averaging 48.59% for all the groups under analysis. The present study showed that the initial milking frequency of primiparous cows is particularly important under AMS. Therefore, farmers should give particular attention to the cows that are unwilling to visit the milking robot during that period.

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

Changes in milk quality after the introduction of automatic milking systems (AM-systems) on dairy farms in TheNetherlands, Germany and Denmark were examined and the data were compared with milk quality results of farms withconventional milking technology. After introduction, a small, but significant increase in total bacterial count, somatic cellcount, freezing point and free fatty acids was observed. The highest levels for total plate count and cell count are foundin the first six months after introduction. After this period the milk quality slightly improves to a more stable level.Risk factors related with milk quality concern general farm characteristics, animal health, AM-system, cleaning and cooling,housing, management skills of the farmer and the hygiene on the farm. Total plate count was significantly relatedto milk yield of the herd, cleaning of the area around the AM-system and the overall hygiene on the farm. Bulk milksomatic cell count appeared to be significantly related to milk yield of the herd and the number of milkings before replacementof the liners. An increased milking frequency is not the only explanation of increased free fatty acid levels. Technicalfactors related to free fatty acids mainly concerned the air inlet in the teat cups, bubbling (excessive air inlet) and a toolong post run time of the milk pump. However, several questions regarding the causes of increased free fatty acid levelsremained unclear.

A total of four feeding experiments were designed to study the response of dairy cows to two different milking systems:a conventional auto-tandem milking parlor, and an automatic milking system (AMS, milking robot). The results were analyzedindependent of the different feeding factors, because they were the same for all animals in both milking systems.The results, separately analyzed for first-lactating and multiparous cows, can be summarized as follows:First-lactating cows visited the automatic milking system more often (2.6 up to 3.5 times per day) than multiparous cows(2.5 up to 2.9 times per day), but the increased milking frequency did not positively affect milk yield. Although multiparouscows had a substantially higher FCM-yield (29.4 kg/day on average) than heifers (26.0 kg/day on average), they only wentto the automatic milking system on average 2.6 times per day. The amount of time needed for first-lactating and multiparouscows to get used to the automatic milking system did not show a difference. They learned to visit the automaticmilking system voluntarily after one week. During the course of lactation, differences in milking frequency were detectedbetween first-lactating and multiparous cows. The milking frequency of multiparous cows was observed to be almost constantduring the entire lactation, on average 2.5 times per day. However, first-lactating cows increase the milking frequencyfrom the beginning (2.3 times per day) to the end of lactation (2.9 times per day), when the lactation is divided into threeperiods of 100 days each. The automatic milking system affects uncorrected milk yield positively. The increase of milk yieldamounted up to 5.7% for primiparous cows in contrast to the multiparous cows with an increase of milk yield up to 3.1%.But all these differences proved not to be significant. The FCM-yield for primiparous cows (25.8 kg/day and 26.0 kg/day)and for multiparous cows (30.3 kg/day and 29.4 kg/day) were lower than the uncorrected milk yield, because the milk fatcontent was significantly lower for cows milked in the AMS (4.03% in the AMS compared to 4.36% in the milking parlor).But there were no differences in the FCM-yield and the milk fat content between first-lactating and multiparous cows.

The results of two experimental programs financed to the Istituto Sperimentale per la Zootecnia are presented. The objective of the two Italian programs was the verify if automatic milking is a suitable practice for Italian dairy system. Results are summarised and compared to those obtained in other international projects. Results refer to animal behaviour, milk yield, milk quality an animal welfare. In a trial comparing cows milked with an automatic milking system and cows milked in a milking parlour, we observed that when the temperature and humidity are very high cows reduce their activity, have lower milking frequency and milk yield than in cold seasons. In comparison to milking parlour, automatic milking system did not increase milk yield which was affected significantly by season, stage of lactation, parity, season per treatment and parity per treatment. The causes of the negative results obtained by this group and by other international groups are discussed. We also presented the results obtained in four trials thereby four appetizers or flavourings were tested to improve efficiency of automatic milking system. Comparing the two milking systems, automatic milking determined a worsening of milk quality, but from these data is not possible to exclude the possibility to use automatic milking for Grana Padano and Parmigiano Reggiano-type cheeses. Animal welfare is not negatively influenced by automatic milking system, which has the potentiality to improve the control and care of cows.

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.

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.

The introduction of the automatic milking system (AMS) offers an opportunity to avoid the hard routine of traditional milking parlour (MP), but requires an evaluation on cow health and physiology, particularly during early lactation.

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 the study was to investigate the effect of feeding frequency on milk production, dry matter intake (DMI) and cow behaviour on two dairy farms with conventional and automatic milking systems (AMS) in different environmental conditions. Cows on two farms were monitored. On the first farm, 96 primiparous cows were milked in a herringbone parlor while on the second a group of nearly 50 cows were milked in two AMS with a forced traffic. On each farm, treatments consisted of two different frequencies of total mixed ration (TMR) delivery (2 vs 3 on the conventional farm; 1 vs 2 on the AMS farm) replicated in two different periods of the year with THI of 72.6 and 60.7, respectively. The behaviour of the cows was monitored by continuous video recording. Statistical analysis was performed separately for the two farms. Increasing the frequency of TMR deliveries did not result in any variation in DMI but significantly improved milk yield on both farms. The increase in feeding frequency at the bunk in the AMS farm mitigated the negative effect of hot conditions on production with a 7.6% increase in milk yield. Feeding frequency did not influence cow behaviour on either farm. Hot conditions showed a depressive effect on DMI (nearly 8% on both farms) compared with thermoneutral conditions but caused a reduction in milk yield (an average 17%) only on the farm with multiparous high-producing cows milked automatically. In the hot period, cows on both farms showed a reduction in daily lying time and an increase in daily standing time.

This review gives an overview of the mathematical modelling of lactation curves in dairy cattle. Over the last ninety years, the development of this field of study has followed the main requirements of the dairy cattle industry. Non-linear parametric functions have represented the preferred tools for modelling average curves of homogeneous groups of animals, with the main aim of predicting yields for management purposes. The increased availability of records per individual lactations and the genetic evaluation based on test day records has shifted the interest of modellers towards more flexible and general linear functions, as polynomials or splines. Thus the main interest of modelling is no longer the reconstruction of the general pattern of the phenomenon but the fitting of individual deviations from an average curve. Other specific approaches based on the modelling of the correlation structure of test day records within lactation, such as mixed linear models or principal component analysis, have been used to test the statistical significance of fixed effects in dairy experiments or to create new variables expressing main lactation curve traits. The adequacy of a model is not an absolute requisite, because it has to be assessed according to the specific purpose it is used for. Occurrence of extended lactations and of new productive and functional traits to be described and the increase of records coming from automatic milking systems likely will represent some of the future challenges for the mathematical modelling of the lactation curve in dairy cattle.

Several options have been suggested in the literature for “inviting” the lactating cows to a milking unit, minimizing the interference with the activities of the cows during the day (eating, drinki...

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

Because a human observer is typically not present during milking process when automatic milking systems (AMS) are used, human observation is replaced by mastitis detection systems consisting of sen...