Concentrate composition for Automatic Milking Systems — Effect on milking frequency

In barns with an automatic milking system (AMS), both the milking frequency and the number of nighttime milkings vary between cows. A low milking frequency might indicate problems in gaining access to the milking unit. Also, nighttime lighting in the waiting area of the AMS and in the milking unit increases exposure to light at night and could suppress nocturnal melatonin synthesis. These effects could result in increased stress, suppressed immune response, and poor udder health. A total of 125 cows (14-16/farm) on 8 farms with AMS were selected based on their average milking frequency. Eight to 10 saliva samples per cow were taken over the course of 4 days, and cortisol, IgA and melatonin concentrations were determined. Somatic cell counts (SCC) were determined in milk samples. Milking frequency had no significant relationship with mean cortisol and IgA levels, but a higher milking frequency tended to be associated with lower SCC levels. Nocturnal melatonin levels tended to be negatively associated with the number of nighttime milkings. In conclusion, no indication of increased stress or reduced immune defense was found in relation to milking frequency on farms with an AMS.

Milk production may be reduced before dry-off to decrease the risk of cows developing intramammary infections during the dry period. Such reductions in milk may be possible in automated milking systems (AMS) where milking frequency and feed allocation at the AMS can be controlled at the cow level. This study investigated the effect of dry-off management of cows milked in AMS on milk yield, milking behavior, and somatic cell count (SCC). Using a 2 × 2 factorial arrangement of treatments, applied from d 14 to 1 before dry-off, 445 cows from 5 commercial dairy farms in Quebec, Canada, were assigned within farm to either (1) reduced feed [RF; allowed a maximum of 0.75 kg/d of AMS pellet for the first week (14 to 8 d before dry-off) of treatment, and 0.50 kg/d for the second week (7 to 1 d before dry-off) of treatment], or (2) nonreduced feed (NF; allowed up to 2 kg/d of AMS pellet), and either (1) reduced milking (RM; reduced to 2 milkings/d or as many times as required to yield 17 kg/milking), or (2) nonreduced milking (NM; allowed up to 6 AMS milkings/d) and no maximum production. Feed and milking behavior data, as well as milk yield and SCC were collected from the AMS software. The RF cows had lower AMS feed delivered during the treatment period, as per the experimental design. Across the treatment period, the NF-NM cows had the highest milking frequency (2.7 times/d), followed by the RF-NM cows (2.4 times/d), and then both of the RM groups (1.8 times/d), which did not differ from each other. All cows, except the NF-NM cows, were gradually milked less frequently as dry-off approached. Across the entire 2-wk treatment period before dry-off, cows with RM allowance experienced a higher reduction in milk yield compared with the cows with no milking allowance restrictions (-4.8 vs. -3.6 kg). Similarly, cows with a RF allocation tended to have a higher reduction in milk yield than cows with NF (-4.6 vs. -3.7 kg). As result, those cows with both reduced milking permissions and feed allocation at the AMS experienced the greatest drop in milk production before dry-off. There were no differences between treatments for milking frequency or yield in the next lactation. Somatic cell score (calculated from SCC) was not different between treatments in the 2-wk or day before dry-off, nor in the first month after calving. Overall, these data suggest that reducing both milking frequency and feed quantity in the AMS is the most efficient method to decrease milk yield before dry-off, without negatively influencing milking frequency or yield in the next lactation, as well as without affecting milk quality.

Devices used by automated milking systems are similarly accurate in estimating milk yield and in collecting a representative milk sample compared with devices used by farms with conventional milk recording

Adoption of automated milking systems (AMS) has increased exponentially around the world in recent years. The objective of this observational study was to evaluate how producer perception of changes in cow-average milk yield and somatic cell count (SCC) compared with the actual changes in their herds after the introduction of AMS in Canadian commercial dairy herds. Data were collected (in 2014 and 2015) through a survey of 97 Canadian dairy herds that shifted to AMS from 2000 to 2014. Producers were asked their perception about milk yield and SCC changes (increase, decrease, or no change) after AMS introduction. Actual herd performance data were obtained from dairy herd improvement organizations. Differences between the 12-mo rolling herd-average milk yield (kg/cow per year) and SCC (cells/mL) at the closest test 2 yr after transitioning to AMS and at the last test before the transition were calculated and compared with the producer perception answers. After AMS adoption, milking herd size, milk yield, SCC, and number of AMS units per herd averaged (± standard deviation) 99.8 ± 54.4 cows, 9,619 ± 1,354 kg/cow per year, 248,825 ± 97,286 cells/mL, and 1.9 ± 1.1 units, respectively. On average, after AMS introduction, herd size, milk yield, and culling rate increased by 11.3 cows, 441 kg/cow per year, and 1.3%, respectively, and calving interval decreased by 7 d. For producers who perceived an increase, actual milk yield and SCC increases averaged (mean ± standard deviation) +534 ± 1,003 kg/cow per year and +56,679 ± 66,662 cells/mL, respectively. Alternatively, for producers who perceived a decrease, actual milk yield and SCC decreases averaged −984 ± 658 kg/cow per year and −26,976 ± 94,099 cells/mL, respectively. An actual milk yield change of +83.1 ± 1,113.3 kg/cow per year and an SCC change of +6,135 ± 72,609 cells/mL were observed in the herds in which the dairy producers perceived no change with the AMS introduction. Hence, dairy producers were, on average, able to discern their actual milk yield and SCC changes after AMS adoption. However, the proportions of dairy producers who accurately perceived their actual milk yield and SCC changes after AMS introduction were 39.4% for milk yield (increase: 36.3%; decrease: 100.0%; and no change: 45.5%) and 46.7% for SCC (increase: 50.0%; decrease: 39.0%; and no change: 54.1%). From these results, we concluded that several dairy producers distorted their actual milk yield and SCC changes or were not fully aware of those changes.

The objective of this study was to determine how training dairy heifers (first-lactation cows before their first calving) on an automated milking system (AMS) before parturition affects their adaptation and performance when milked on the AMS. Thirty pregnant Holstein dairy heifers were enrolled in the study 23 ± 5.2 d (mean ± SD) before their expected calving date in dry cow pens located away from the AMS. Heifers were paired by expected calving date and allocated into 1 of 2 treatments within pair (16 pairs initially enrolled): control (CON; no training; n = 16 heifers completed) and training (TRN; this included exposure to AMS environment, concentrate, and mechanical arm and noises; n = 14 heifers completed). The TRN heifers were trained to the AMS over 4 d, 14 ± 5.1 d before their actual calving date, with 3 training sessions/d. All heifers calved in individual maternity pens and were then moved to the free-traffic AMS pen between 3 and 7 DIM to be milked by the AMS, with a fetch pen adjacent to the entrance of the AMS. Milking activity (visits, milkings), behavior (feeding, rumination), and production were recorded for the first 21 d on the AMS. Ease of entry was scored from 0 to 6 (0 = no assistance to 6 = heavy assistance), kicking from 0 to 3 (0 = no kicking to 3 = >2 kicking events), and milk letdown from 0 to 3 (0 = normal letdown to 3 = no letdown) for the first 6 milkings on the AMS across the first 2 d. Time spent around the AMS was recorded on d 1, 3, 7, 14, and 21 of milking on the AMS, and any time spent in the fetch pen was recorded for all 21 d. The TRN cows had a better (lower) ease of entry score (2.87 vs. 4.26) and milk letdown score (0.35 vs. 0.70) during the first 6 milkings. The TRN cows had more total visits to the AMS (6.1/d vs. 5.0/d), voluntary visits (5.6/d vs. 4.2/d), and voluntary milkings (2.6/d vs. 2.2/d) on the AMS across the 21-d period, compared with CON cows. The CON cows had more fetches (1.0/d vs. 0.8/d) to the AMS across the 21-d period and spent more time in the fetch pen (18.7 min/d vs. 14.6 min/d) compared with TRN cows. The improved adaptation for TRN cows may have contributed to a higher milk yield (32.8 kg/d vs. 30.6) compared with CON cows. Overall, these results demonstrate that training before calving improved adaptation and performance of cows milked on an AMS compared with cows without previous exposure to the AMS, and its concentrate and mechanics exposure within, before their first AMS milking.

The objective of this study was to evaluate the adaptation of mid-lactating Holstein cows regarding their introduction at the automatic milking system (AMS) and its effect on behaviour and milk performance. From a herd of 400 milking cows, a group of twenty-eight mid-lactating Holstein cows were monitored in the transition from the conventional milking system (twice daily) to the free-traffic automatic milking system. After 37 days from the full transition to the AMS, cows were retrospectively divided into two groups according to the average number of milking visits during the first week of AMS: 1) milking visits < 2 (MV-LOW) and 2) milking visits < 2 (MV-HIGH). Number of milking visits, milk yield, milk quality and rumination and eating time were recorded. In the first week, MV-HIGH cows had an average of milking visits higher compared to the MV-LOW cows (2.44 vs. 1.67 ± 0.06 n°/d, respectively). Starting from the similar milk production in the pre-AMS period, milk yield after the introduction of AMS (from 0 to 37 days) was higher in the MV-HIGH than in the MV-LOW cows (36.91 vs. 30.94 ± 2.11 kg/d, respectively), but with lower fat, protein and lactose percentage. The first week of AMS was characterized by a marked increase in milk yield in the MV-HIGH cows (+30.98 %) and a decrease in the MV-LOW cows (-11.60 %) compared to the pre-AMS. The time spent for eating was also greater in the MV-HIGH compared to the MV-LOW cows. Even though MV-LOW cows increased the milk production over the first week of AMS, these cows had always a lower increase in milk yield compared with the MV-HIGH cows until 37 days of AMS. These results suggest that the adaptability of the cows to the automatic milking system may also depend on the individual behaviour of cows and not only on the environment around them. Therefore, it is necessary to apply new livestock management strategies, when AMS (as a free-traffic system) is going to displace the milking parlour in order to better fine-tune the adaptation of cows (especially for heifers) and also to select cows that respond best to the robotic milking system.

Finances and returns for robotic dairies.

Robotic milking-farmer experiences and adoption rate in Jæren, Norway

To maintain a predominantly pasture-based system, the large herd milked by automatic milking rotary would be required to walk significant distances. Walking distances of greater than 1-km are associated with an increased incidence of undesirably long milking intervals and reduced milk yield. Complementary forages can be incorporated into pasture-based systems to lift total home grown feed in a given area, thus potentially ‘concentrating’ feed closer to the dairy. The aim of this modelling study was to investigate the total land area required and associated walking distance for large automatic milking system (AMS) herds when incorporating complementary forage rotations (CFR) into the system. Thirty-six scenarios consisting of 3 AMS herds (400, 600, 800 cows), 2 levels of pasture utilisation (current AMS utilisation of 15.0 t dry matter [DM]/ha, termed as moderate; optimum pasture utilisation of 19.7 t DM/ha, termed as high) and 6 rates of replacement of each of these pastures by grazeable CFR (0%, 10%, 20%, 30%, 40%, 50%) were investigated. Results showed that AMS cows were required to walk greater than 1-km when the farm area was greater than 86 ha. Insufficient pasture could be produced within a 1 km distance (i.e. 86 ha land) with home-grown feed (HGF) providing 43%, 29%, and 22% of the metabolisable energy (ME) required by 400, 600, and 800 cows, respectively from pastures. Introduction of pasture (moderate): CFR in AMS at a ratio of 80:20 can feed a 400 cow AMS herd, and can supply 42% and 31% of the ME requirements for 600 and 800 cows, respectively with pasture (moderate): CFR at 50:50 levels. In contrast to moderate pasture, 400 cows can be managed on high pasture utilisation (provided 57% of the total ME requirements). However, similar to the scenarios conducted with moderate pasture, there was insufficient feed produced within 1-km distance of the dairy for 600 or 800 cows. An 800 cow herd required 140 and 130 ha on moderate and high pasture-based AMS system, respectively with the introduction of pasture: CFR at a ratio of 50:50. Given the impact of increasing land area past 86 ha on walking distance, cow numbers could be increased by purchasing feed from off the milking platform and/or using the land outside 1-km distance for conserved feed. However, this warrants further investigations into risk analyses of different management options including development of an innovative system to manage large herds in an AMS farming system.

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.

An automatic milking system (AMS) uses a robot to attach the teatcups and can be continuously available for cows to present themselves to be milked with minimal human intervention. Milking in an AMS is therefore a continuous rather than a batch process, and the conventional practice of cleaning a milking system after each batch of cows has been milked is not applicable.Milk flow through an AMS is different in scale and in temporal distribution from that in a conventional system. These differences in flow patterns may be significant for hygiene. It has been suggested by Verheij (1992), for example, that milk will flush away much of the residue of the previous milking and that microbial growth will be retarded because of the bacteriostatic properties of fresh milk. Ordolff & Bölling (1992) reported experiments in which batches of milk were passed through a milking installation that was said to simulate an AMS. Their main conclusion was that milk residues left in the system for up to 60 min did not increase the bacterial contamination of the next batch of milk. However, the practical relevance of this conclusion is not clear because the design of the simulated AMS was not specified, so it can not be compared to a practical AMS. Moreover, mixtures of fresh and UHT milk were used, with unknown consequences. The purpose of the experiment reported in this paper was to strengthen the evidence on which to base recommendations for effective cleaning procedures for AMS.The bacterial count of milk that had been passed through a system was used as the indicator of the cleanliness of the system. It was apparent from previous work by Ordolff & Bölling (1992) that this would produce results that varied widely. The experiment was therefore designed to be as simple as possible. In particular, a simple, easily defined laboratory rig was used rather than an AMS.

The objective of this study was to describe the association between the milking frequency and milk production and to determine the effect of milking intervals on the functional properties of the udder of cows in automatic milking systems. Thousand eight milking recordings were enrolled in the study, in total, 106 Holstein cows were observed. The results of studies showed that at a daily milk yield per cow of 22.0 ± 0.6 (means ± SD) kg, the milking frequency was 2 times (13.5 % of the total number of milkings), 32.7 ± 0.4 kg – 3 times (57.2 %), 37.7 ± 0.6 kg – 4 times (28.0 %), 51.3 ± 4.1 kg – 5 times (1.3 %). An increase in the daily milk yield due to a reduction in the milking interval has been established (p<0.001). However, milk yield per milking has the opposite tendency (p<0.001). The average and maximum milk flow rates increased with an increase in the milking interval and reached the highest values in the interval of 7.50–8.99 hours – 2.36 and 3.36 kg/min, respectively (p<0.001). Cows with a low indicator of maximum milk flow rate (3.01 ± 0.06 kg/min) had greater milk production (36.6 ± 0.47 kg). With an increase in the milking interval from 4.50–5.99 to 7.50–8.99 hours, it was accompanied by a decrease in the latency period milk flow in the quarters of the udder, when the milking interval reached 9.00–10.49 and 10.50–11.99 hours, the latency period milk flow increased.

Oxytocin release and milk removal after delayed or long-lasting teat cup attachment during automatic milking

Automatic milking system (AMS) brings a change in approach to ensure the data reliability in the official milk recording (MR). The AMS is equipped with flowmeter. AMS software provides the daily milk yield (DMY) and average of the last 7 daily milk yields (AVG7) for MR. Classic MR uses DMY. AVG7 could be more reliable value. Origin of both records (DMY and AVG7) is from AMS flowmeter. The aim of paper was to compare the values of milk yield of cows from daily (DMY) and the extended records (AVG7) from AMS for objective assess of lactations to be used in cattle breeding. Study (2013) with 2 AMS herds (DeLaval and Lely Astronaut): herd 1 – Holstein (H) dairy cows; herd 2 – Czech Fleckvieh (CF) dairy cows. There were following milk records: n = 521 DeLaval (H); n = 567 Lely Astronaut (CF); 70 (H) and 68 (CF) dairy cows. MR samples were analyzed on: fat content; crude protein; somatic cell count. Correlations between AVG7 and DMY were: 0.888 (H); 0.898 (CF, both P ≤ 0.001). There were insignificant differences (P > 0.05; −0.07 ± 3.29 kg for H and 0.28 ± 3.3 kg for CF) between AVG7 and DMY for both robots. The same is valid for differences in the production of milk components. According to this comparison experiment the AVG7 of AMS is a suitable equivalent for the DMY regarding official MR for assessment of lactations.

The research and development described in this thesis was directed towards the technical and managerial integration of the milking robot into the dairy farm. First a concept and tools for the milking robot dairy farm were developed. A set of parameters was introduced which represents the individual cow's production and behaviour pattern in addition to herd and automatic milking system capacity characteristics. Then, a series of three field tests was conducted to validate the automatic milking system management concept, and the tools for its implementation. The aim was to assign an individual milking frequency and concentrates supplementation regime to each dairy cow in a loose housing system. Attention was focused on the implementation of an individual production and behaviour-based strategy, using cow traffic, milking frequency and individual concentrates allocation as the control tools. in all field tests, the milking robot was available for milking and concentrates allocation for 24 hours a day. The cows visited voluntarily a selection unit which was installed before the milking robot, where an on-line milking and concentrates allocation decision was made. In the first and second field tests, cows were milked between two to five times daily, based on daily fixed and pre-determined milking frequency and concentrates allocation. In the third field test the daily milking frequency, two to six times daily, and concentrates allocation were based on frequent evaluation of cow behaviour and production performance. The methods and results described can be used as management guidelines for the loose housing milking robot dairy farm.