Benchmarking of farms with automated milking systems in Canada and associations with milk production and quality

Farm-level nutritional factors associated with milk production and milking behavior on Canadian farms with automated milking systems

The objective of this study was to describe the nutritional strategies used on Canadian dairy farms with automated milking systems (AMS), both at the feed bunk and the concentrate offered at the AMS, as well as to determine what dietary components and nutrients, as formulated, were associated with milk production and milking behaviors on those farms. Formulated diets (including ingredients and nutrient content) and AMS data were collected from April 1, 2019, until September 30, 2020, on 160 AMS farms (eastern Canada [East] = 8, Ontario [ON] = 76, Quebec [QC] = 22, and western Canada [West] = 54). Both partial mixed ration (PMR) and AMS concentrate samples were collected from May 1 to September 30, 2019, on 169 farms (East = 12, ON = 63, QC = 42, West = 52). We collected AMS milking data for 154 herds. For each farm (n = 161), milk recording data were collected and summarized by farm to calculate average milk yield and components. Multivariable regression models were used to associate herd-level formulated nutrient composition and feeding management practices with milk production and milking behavior. Milk yield (mean ± SD = 37.0 ± 0.3 kg/d) was positively associated with the PMR ether extract (EE) concentration (+0.97 kg/d per percentage point [p.p.] increase) and with farms that fed barley silage as their major forage source (n = 16; +2.18 kg/d) as compared with haylage (n = 42), whereas farms that fed corn silage (n = 96; +1.23 kg/d) tended to produce more milk than farms that fed haylage. Greater milk fat content (4.09 ± 0.28%) was associated with a greater PMR-to-AMS concentrate ratio (+0.02 p.p. per unit increase) and total diet net energy for lactation (+0.046 p.p. per 0.1 Mcal/kg increase), but a lesser percentage of NFC of the PMR (-0.016 p.p. per p.p. increase of NFC percentage). Milk protein content (3.38 ± 0.14%) was positively associated with the forage percentage of the PMR (+0.003 p.p. per p.p. increase of forage percentage) and the total diet starch percentage (+0.009 p.p. per p.p. increase of starch percentage), but was negatively associated with farms feeding corn silage (-0.1 p.p. compared with haylage) as their major forage. Greater milking frequency (2.77 ± 0.40 milkings/d) was observed on farms with free-flow cow traffic systems (+0.62 milkings/d) and was positively associated with feed push-up frequency (+0.013 milkings/d per additional feed push-up), but negatively associated with PMR NFC content and forage percentage of the total ration (-0.017 milkings/d per p.p. increase of forage percentage). Lastly, greater milking refusal frequency (1.49 ± 0.82 refusals/d) was observed on farms with free-flow cow traffic systems (+0.84 refusals/d) and farms feeding barley silage (+0.58 refusals/d) than with guided flow and farms feeding either corn silage or haylage, respectively. These data give insight into the ingredients, nutrient formulations and type of diets fed on AMS dairy farms across Canada and the association of those factors with milk production and milking behaviors.

Farm-level risk factors associated with increased milk β-hydroxybutyrate and hyperketolactia prevalence on farms with automated milking systems

The objectives of this study were to determine the farm-level hyperketolactia (HKL) prevalence, as diagnosed from milk β-hydroxybutyrate (BHB) concentration, on dairy farms milking with an automatic milking system (AMS) and to describe the farm-level housing, management, and nutritional risk factors associated with increased farm-average milk BHB and the within-herd HKL prevalence in the first 45 DIM. Canadian AMS farms (n = 162; eastern Canada n = 8, Quebec n = 23, Ontario n = 75, western Canada n = 55) were visited once between April to September 2019 to record housing and herd management practices. The first test milk data for each cow under 45 DIM were collected, along with the final test of the previous lactations for all multiparous cows, from April 1, 2019 to September 30, 2020. The first test milk BHB was then used to classify each individual cow as having HKL (milk BHB ≥ 0.15 mmol/L) at the time of testing. Milk fat and protein content, milk BHB, and HKL prevalence were summarized by farm and lactation group (all, primiparous, and multiparous). During this same time period, formulated diets for dry and lactating cows, including ingredients and nutrient composition, and AMS milking data were collected. Data from the AMS were used to determine milking behaviors and milk production of each herd during the first 45 DIM. Multivariable regression models were used to associate herd-level housing, feeding management practices, and formulated nutrient composition with first test milk BHB concentrations and within-herd HKL levels separately for primiparous and multiparous cows. The within-herd HKL prevalence for all cows was 21.8%, with primiparous cows having a lower mean prevalence (12.2 ± 9.2%) than multiparous cows (26.6 ± 11.3%). Milk BHB concentration (0.095 ± 0.018 mmol/L) and HKL prevalence for primiparous cows were positively associated with formulated prepartum DMI and forage content of the dry cow diet while being negatively associated with formulated postpartum DMI, the major ingredient in the concentrate supplemented through the AMS, and the PMR-to-AMS concentrate ratio. However, multiparous cows' milk BHB concentration (0.12 ± 0.023 mmol/L) and HKL prevalence were positively associated with the length of the previous lactation, milk BHB at dry off, prepartum diet nonfiber carbohydrate content, and the major forage fed on farm, while tending to be negatively associated with feed bunk space during lactation. This is the first study to determine the farm-level risk factors associated with herd-level prevalence of HKL in AMS dairy herds, thus helping optimize management and guide diet formulation to promote the reduction of HKL prevalence.

Farmers' Perceptions on Implementing Automatic Milking Systems in Large USA Dairies: Decision-Making Process, Management Practices, Labor, and Herd Performance

Automatic Milking System (AMS) installations are increasing in the USA despite the higher investment cost than conventional systems. Surveys on AMSs conducted outside the USA focused on small-medium herds, specific regions, or aspects of AMS milking. This study described farmers' perceptions about the decision-making process of adopting an AMS in the USA's large dairies (≥7 AMS boxes) regarding changes in technology, housing, management practices, labor, herd performance, and health. After being contacted, 27 of 55 farmers from large AMS herds completed the survey. The main reasons for adopting an AMS were labor costs, cows' welfare, and herd performance. Most farms constructed new barns, used a free-flow traffic system, and changed their feed management. Increases in water and energy use were perceived by 42% and 62% of farmers, respectively. Farmers estimated decreases in labor costs of over 21%, and AMS employees worked 40-60 h/week. Milk production increases were reported by 58%, with 32% observing higher milk fat and protein content. Easier sick cow detection, better mastitis management, and improvements in pregnancy rates were reported. Thus, farmers transitioning to AMSs perceived altered resource utilization, labor cost savings, and improvements in employee quality of life, animal welfare, and farm management. While 54% of respondents would recommend an AMS to other farms, 38% suggested considering additional aspects prior to adoption.

Associations of cow- and herd-level factors during the dry period with indicators of udder health in early-lactation cows milked by automated milking systems

This observational study aimed to determine the association of cow-level factors and herd-level housing and management practices during the dry period with indicators of udder health in early-lactation cows in automated milking system (AMS) herds. Data were collected from 166 commercial AMS dairy farms (mean ± standard deviation = 116 ± 111 milking cows; range = 39 to 1,200) across Canada between October 2018 and September 2020. Information on herd demographics, housing, and management practices was obtained on each farm using 2 surveys. On each farm, we selected all cows that had available Dairy Herd Improvement (DHI) somatic cell count (SCC) data for their last milk test before dry-off (>250 d in milk) and their first milk test after calving (5-45 d in milk). Data from 14,007 cows were included after excluding cows with a dry period of <30 d and >120 d. Using the SCC data, we calculated for each cow the somatic cell score (SCS) for the last milk test before dry-off (PreSCS) and the first milk test after calving (PostSCS), which we then averaged per herd at a test-day level. Intramammary infection (IMI) was estimated using cow SCC data. Each cow was classified as not infected (SCC <200,000 cells/mL) or infected (SCC ≥200,000 cells/mL) at her last milk test before dry-off and her first milk test after calving. Based on this classification, cows were further categorized as never infected, always infected, new IMI, or cured IMI. At the cow level, a higher PostSCS was associated with longer dry periods. The odds of having a new IMI were higher for cows of higher parity and that had lower 305-d milk yield before dry-off. Cows with lower parity were more likely to cure an IMI. At the herd level, a higher 305-d milk yield before dry-off was associated with a lower incidence of new IMI and a higher incidence of cured IMI. Separating cows into a different pen as preparation for dry-off tended to be associated with a lower PostSCS and incidence of new IMI. At dry-off, herds that used teat sealants and blanket antibiotic dry cow therapy also had lower PostSCS. During the dry period, housing cows in different groups was associated with a higher PostSCS and a lower incidence of cured IMI, while housing cows in both pack pens and stalls compared with only pack pens was associated with a lower incidence of new IMI. Finally, placing cows onto the AMS to be milked one or more days after calving tended to be associated with a lower PostSCS compared with placing them in the AMS within the first day postpartum. In summary, indicators of udder health in early-lactation cows in AMS herds were associated with several cow-level factors and herd-level housing and management practices before dry-off, at dry-off, during the dry period, and at the beginning of lactation. Thus, if some of the associations identified are causal, AMS producers may be able to improve udder health through modifications of housing and management practices.

Increased Cattle Feeding Precision from Automatic Feeding Systems: Considerations on Technology Spread and Farm Level Perceived Advantages in Italy

Automation reduces the impact of farming on climate change and helps farmers adapt to its financial impact. Automatic feeding systems (AFSs) increase the ruminant's feeding precision and ease operators' workload. Such systems exist on a spectrum, requiring varied levels of operator support and installation complexity. A recent survey on farmers pointed out that those already running an AFS and those willing to buy one appreciate its ease of use, the resulting animal welfare, and the resulting overall benefits (increased production, farm profitability, and reduced feed waste). Whether technologically complex or not, studies have confirmed the benefits that farmers perceive to be underlying the remarkable reduction in the environmental impact of feeding operations (AFSs are electrically powered), the increase in animal welfare resulting from reduced conflicts around accessing the feed bunk, and the constant availability of fresh feed. However, their introduction should follow accurate and holistic structural and economic planning for existing and newly built facilities. The availability of public subsidies plays an essential role in pushing farmers to adopt the most modern digital technologies, whose benefits may even increase when farmers couple them with interconnected sensors to monitor animals' physiological states.

Implementation of Technical and Technological Progress in Dairy Production

The involvement of people and technical devices is a characteristic feature of technological processes in agriculture. Human access to modernized and more efficient technical equipment determines the differentiation of the proportions of the contributions of human labor and technical equipment to the implementation of production technology on farms. Taking into account the data on manual and machine work inputs, the methodology of determining the technological index level (TL) was presented. The aim of the present study was to present the scope of use of the technological index level to assess the effects of technological progress in the dairy production system, with particular emphasis on cow milking. For the value range of the technological index level (0–100%), changes in the milkman’s work efficiency were presented based on research carried out on farms equipped with milking equipment at different levels of technical advancement. Moreover, the course of changes in electricity and water consumption per liter of milk was determined in association with the technological index level. The issue of simultaneous implementation of various forms of progress was developed based on the example of milking cows with a milking robot. Five categories (ranges) of cows’ milk yield were distinguished and compared with the current yields of cows in the European Union. On this basis, a discussion was initiated on the factors that facilitate and limit the implementation of technical and technological progress in dairy production.

Farm-level factors associated with lameness prevalence, productivity, and milk quality in farms with automated milking systems

Impaired locomotion (lameness) may negatively affect the ability and desire of cows to milk voluntarily, which is a key factor in success of automated milking systems (AMS). The objective of this study was to identify factors associated with herd-level lameness prevalence and associations of lameness and other farm-level factors with milking activity, milk yield, and milk quality in herds with AMS. From April to September 2019, 75 herds with AMS in Ontario, Canada, were visited, and data on barn design and farm management practices were collected. Data from AMS were collected, along with milk recording data, for the 6-mo period before farm visits. Farms averaged 98 ± 71 lactating cows, 2.3 ± 1.5 robot units/farm, 43.6 ± 9.4 cows/robot, 36.4 ± 4.9 kg/d of milk, a milking frequency of 3.01 ± 0.33 milkings/d, and a herd average geometric mean SCC of 179.3 ± 74.6 (× 1,000) cells/mL. Thirty percent of cows/farm (minimum of 30 cows/farm) were scored for body condition (1 = underconditioned to 5 = over conditioned) and locomotion (1 = sound to 5 = lame; clinically lame ≥3 out of 5 = 28.3 ± 11.7%, and severely lame ≥4 out of 5 = 3.0 ± 3.2%). Clinical lameness (locomotion score ≥3) was less prevalent on farms with sand bedding, with increased feed bunk space per cow, and on farms with non-Holstein breeds versus Holsteins, and tended to be less prevalent with lesser proportion of underconditioned cows (with body condition score ≤2.5). Severe lameness occurrence (farms with any cows with locomotion score ≥4) was associated with a greater proportion of underconditioned cows and in farms with stalls with greater curb heights. Herd average milk yield/cow per day increased with lesser prevalence of clinical lameness (each 10-percentage-point decrease in clinical lameness prevalence was associated with 2.0 kg/cow per day greater milk yield) and greater milking visit frequency per day, and tended to be greater with increased feed push-up frequency. Lesser herd average somatic cell count was associated with lesser clinical lameness prevalence, herd average days in milk, and proportion of overconditioned cows, and somatic cell count tended to be lesser for farms with sand bedding versus those with organic bedding substrates. The results highlight the importance of minimizing lameness prevalence, using of sand bedding, ensuring adequate feed access and feed bunk space, and maintaining proper cow body condition to optimize herd-level productivity and milk quality in AMS herds.

Comparing steam-flaked and pelleted barley grain in a feed-first guided-flow automated milking system for Holstein cows

Provision of a palatable feed in automated milking systems (AMS) is considered an essential motivating factor to encourage voluntary visits to the milking stall. Although the quantity and composition of AMS concentrates have been previously investigated, the form of the concentrate has not been extensively evaluated. The objective of this study was to evaluate the effects of feeding pelleted (PB; 132.9 ± 56 DIM, 47.4 ± 9.51 kg/d milk yield) versus steam-flaked barley (SFB; 133.0 ± 63 DIM, 40.5 ± 8.23 kg/d milk yield) in an AMS on dry matter intake, AMS visits, milk and milk component yield, and partial mixed ration (PMR) feeding behavior. Twenty-nine Holstein cows of varying parities were enrolled in this study. Cows were housed in freestall housing with a feed-first guided-flow barn design; 7 cows were housed in a separate freestall pen to enable individual PMR intake and feeding behavior monitoring. This study was conducted as a 2-way crossover, with two 21-d periods in which each cow received the same basal PMR but was offered 2 kg/d (dry matter basis) of PB or SFB in the AMS. Cows receiving the SFB had fewer voluntary AMS visits (2.71 vs. 2.90 ± 0.051, no./d), tended to have a longer interval between milkings (541.7 vs. 505.8 ± 21.02 min), spent more time in the holding pen before entering the AMS (139.9 vs. 81.2 ± 11.68 min/d), and had lower total box time (19.7 vs. 21.4 ± 0.35 min/d) than cows fed PB. Despite changes in AMS attendance, there were no differences for average milk (44.0 kg/d), fat (1.62 kg/d), and protein (1.47 kg/d) yields or AMS concentrate intake (2.02 kg/d). These behavioral changes indicate that offering SFB as an alternative to PB may reduce motivation for cows to voluntarily enter the AMS.