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.

Genomic Selection for Dairy Cattle Behaviour Considering Novel Traits in a Changing Technical Production Environment

Cow behaviour is a major factor influencing dairy herd profitability and is an indicator of animal welfare and disease. Behaviour is a complex network of behavioural patterns in response to environmental and social stimuli and human handling. Advances in agricultural technology have led to changes in dairy cow husbandry systems worldwide. Increasing herd sizes, less time availability to take care of the animals and modern technology such as automatic milking systems (AMSs) imply limited human-cow interactions. On the other hand, cow behaviour responses to the technical environment (cow-AMS interactions) simultaneously improve production efficiency and welfare and contribute to simplified "cow handling" and reduced labour time. Automatic milking systems generate objective behaviour traits linked to workability, milkability and health, which can be implemented into genomic selection tools. However, there is insufficient understanding of the genetic mechanisms influencing cow learning and social behaviour, in turn affecting herd management, productivity and welfare. Moreover, physiological and molecular biomarkers such as heart rate, neurotransmitters and hormones might be useful indicators and predictors of cow behaviour. This review gives an overview of published behaviour studies in dairy cows in the context of genetics and genomics and discusses possibilities for breeding approaches to achieve desired behaviour in a technical production environment.

Scientific Productions on Precision Livestock Farming: An Overview of the Evolution and Current State of Research Based on a Bibliometric Analysis

The interest in precision livestock farming (PLF)-a concept discussed for the first time in the early 2000s-has advanced considerably in recent years due to its important role in the development of sustainable livestock production systems. However, a comprehensive bibliometric analysis of the PLF literature is lacking. To address this gap, this study analyzed documents published from 2005 to 2021, aiming to understand the historical influences on technology adoption in livestock farming, identify future global trends, and examine shifts in scientific research on this topic. By using specific search terms in the Web of Science Core Collection, 886 publications were identified and analyzed using the bibliometrix R-package. The analysis revealed that the collection consisted mostly of research articles (74.6%) and reviews (10.4%). The top three core journals were the Journal of Dairy Science, Computers and Electronics in Agriculture, and Animals. Over time, the number of publications has steadily increased, with a higher growth rate in the last five years (29.0%) compared to the initial period (13.7%). Authors and institutions from multiple countries have contributed to the literature, with the USA, the Netherlands, and Italy leading in terms of publication numbers. The analysis also highlighted the growing interest in bovine production systems, emphasizing the importance of behavioral studies in PLF tool development. Automated milking systems were identified as central drivers of innovation in the PLF sector. Emerging themes for the future included "emissions" and "mitigation", indicating a focus on environmental concerns.

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.

Forecasting the milk yield of cows on farms equipped with automatic milking system with the use of decision trees

The purpose of this paper was to utilize the decision trees technique to determine the factors responsible for high monthly milk yield in Polish Holstein-Friesian cows from 27 herds equipped with milking robots. The applied statistical method-the decision tree technique-showed that the most important factors responsible for monthly milk yield of dairy cows using robots were, in descending order of importance: milking frequency, lactation number, month of milking, and type of lying stall. At the same time, it has been ascertained that the highest monthly milk yield (47.24 kg) can be expected from multiparous cows kept in barns with a deep bedding that were milked more frequently than three times per day. On the other hand, the lowest milk production (13.56 kg) was observed among dairy cows milked less frequently than two times a day, with an average number of milked quarters lower than 3.97. The application of the decision trees technique allows a breeder to select appropriate levels of environmental factors and parameters that will help to ensure maximized milk production.

Minimally Invasive Markers of Stress and Production Parameters in Dairy Cows before and after the Installation of a Voluntary Milking System

Automatic milking systems (AMS) are a low-labour alternative to conventional parlours, with previous studies demonstrating that cows vary in their ability to cope with the change to AMS. Cortisol expression can be combined with other measures to assess stress: saliva and hair have the advantage of requiring minimally invasive sampling. No work has investigated the long-term impact of introduction of AMS. The aims of the study were to assess short-term and chronic stress associated with a change in milking system by measuring salivary and hair cortisol levels and to assess the impact on health and production parameters. Cows from one farm changing their milking system were recruited to the study and sampled for saliva (n = 10) and hair (n = 12) before and after installation. Cortisol levels were measured using a salivary cortisol enzyme immunoassay kit. Body condition, lameness and milk parameters of the whole herd were regularly assessed. Salivary cortisol showed no diurnal pattern but was affected by lameness and gestation. Non-lame cows showed a reduction in salivary cortisol after AMS introduction (p < 0.001). Hair cortisol levels increased after AMS, but it was unclear if this change was seasonal. Milk yield increased by 13% and somatic cell count reduced by 28%. Body condition score was consistently good, but lameness remained high throughout the study. Production values alone do not represent high welfare. The high lameness and associated cortisol levels suggest that cow stress requires consideration when changing milking systems.

Designing Automated Milking Dairy Facilities to Maximize Labor Efficiency

As automatic milking systems grow in popularity in North America, questions about how to design the barn to improve labor efficiency arise. Multiple considerations such as cow flow traffic type, robot positioning within the pen, the number of cows per pen, and how cows are managed around the robots must be discussed during the barn planning period. This article focuses on barn design and pen layout to maximize labor efficiency in herds with single-box automatic milking systems.

Robotic milking: Technology, farm design, and effects on work flow

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.

Changes in milking parameters with robotic milking

Abstract. The aim of this present study is to describe changes occurring during the milking of cows in various periods following the introduction of an AMS (automatic milking system). The following cow milking parameters were analysed: milkings per cow per day, milking yield, milking speed and milking duration. An increase in milk yield in AMS barns has been found to be possible, but it is affected by a number of factors related to cow milking performance. Milk yield was observed to gradually grow with time after the installation of the robots. Older cows in their third and fourth lactations achieved higher milking parameter values as compared to cows in their first and second lactations. The average milk yield for the whole period was on a similar level, but, due to the fact that the duration of lactation in herd B was more than 100 days longer, that herd achieved a higher milk yield. The use of AMSs in barns enables farmers to monitor cow performance traits and study the relationships between them; farmers should try to select for traits ensuring high performance and directly related to milk yield. This study found a positive relationship between milking duration and milk yield. On the other hand, a highly negative relationship was found between milking duration and milking speed, which means that these parameters should be closely monitored. This study found that the optimal number of milkings per cow per day was in the range of 2.6 to 2.8 milkings a day with a 2.6 kg min−1 milking speed.

Milking permission and milking intervals in a pasture-based automatic milking system

In a pasture-based, automatic milking system, a proportion of milking events occur with milking intervals (MI) >16 h (extended MI). Additionally, cows necessarily walk longer distances than in indoor-based systems. The decision to milk a cow is based on milking permission criteria, which are generally based on time since last milking but can often take into account expected yield as well. Any cow arriving at the dairy and that does not receive milking permission is drafted to a pasture allocation, but it is not known whether milking refusal influences total time of return and therefore MI. Data from a 33-day period from the FutureDairy pasture-based, automatic milking system research farm using a prototype robotic rotary were analysed to investigate the hypothesis that a greater proportion of milking events occurring with extended MI would correspond to cows that had experienced a previous milking refusal. If this were the case then management practices could be implemented to deal with cows that visit the dairy soon after the last milking event. Results indicate that one-third of milking events had extended MI, although only 16% of them had a previous milking refusal. The average refusal took place 3 h after the last milking event and caused extended MI in >60% of the cases. This indicated that although attention should be placed on cows that returned to the dairy before milking permission (because they were likely to have an extended MI), milking refusals were not the main cause of extended MI. Therefore, cows that visit the dairy facility earlier than expected could be sorted to a feeding area close to the dairy, yet the greatest impact on overall MI will probably be achieved by reducing time spent in any one pasture allocation.

Associations of cow-level factors, frequency of feed delivery, and standing and lying behaviour of dairy cows milked in an automatic system

Deming, J. A., Bergeron, R., Leslie, K. E. and DeVries, T. J. 2013. Associations of cow-level factors, frequency of feed delivery, and standing and lying behaviour of dairy cows milked in an automatic system. Can. J. Anim. Sci. 93: 427–433. The objectives of this observational study were to quantify the standing and lying behaviour of dairy cows milked in an automatic milking system (AMS) and determine associations of this behaviour with cow-level factors (parity, stage of lactation, production, lameness) and feeding management (frequency of feed delivery). Ninety lactating Holstein cows (178±83 d in milk (DIM); parity: 2.1±1.9), kept in a free-stall barn in one of two pens, each with a free-traffic AMS, were monitored for a period of 70 d. To vary feeding management, in two consecutive 35-d periods, cows in each pen were delivered a total mixed ration (TMR), in a random order, once daily (at 0730) or twice daily (at 0730 and 1730). During the last 7 d of each period, standing and lying behaviour were recorded with data loggers, while milking information was recorded by the AMS. Cows were lameness (gait) scored twice each period. Cows lay down for 10.9±2.0 h d−1, produced an average of 34.7±8.7 kg d−1 of milk, and milked 2.6±0.6 times per day. Cows spent more time standing after milking (P=0.04) when fed once daily compared with twice daily. Lying duration tended to increase (P=0.06) when feed was delivered twice daily. Milk yield (P<0.001) and lying bout frequency (P=0.05) were negatively associated with DIM, while lying bout length (P=0.005) and total duration of lying (P=0.01) were positively associated with DIM. Cows with higher gait scores milked less frequently (P=0.04), and spent more time lying per day (P=0.008) and tended to have more lying bouts per day (P=0.06). Overall, the results of this observational study suggest that the standing and lying behaviour of AMS-milked cows may be influenced by feed delivery frequency, but are more consistently associated with stage of lactation and lameness.