Many cooling strategies are used to keep cows in thermal homeostasis; however, most of them are applied to the group level, commonly at the feed bunk or milking parlor. The variance of heat stress effects on animals are well known, but with more individualized management in dairy farms, group cooling opportunities are becoming restricted. It is known that dairy cattle are variable in their responses to an increase in heat load. Thus, the first objective of this study was to investigate the effect of 2 mandatory soakings at the exit of the milking parlor and free access to a voluntary soaking system compared with cows with access to a voluntary soaking system only, with no mandatory soakings. The second objective of this study was to assess the heat abatement capability of voluntary soaking of cows by assessing cow physiology, behavior, and milk production. Last, this study aimed to determine the individual use of the voluntary heat abatement system and its relationship with temperature-humidity index (THI). Fifteen mid-lactation Holstein cows were enrolled in this study and had free access to a motion-activated soaker (Cool Sense, Edstrom) located adjacent to the research pen for an 8-wk data collection period. Cows were paired according to parity, milk production, and body weight, and assigned a treatment with or without mandatory soakings twice per day. In the mandatory soaking treatment (MS), cows were soaked using a motion-activated soaker at the exit of the milking parlor and had free access to the voluntary soaker in the pen. Cows in the treatment without mandatory soakings (NMS) were not soaked at the exit of the milking parlor and had free access to the voluntary soaker in the pen. The effects of soaker treatment were analyzed using mixed linear models. The model included treatment, soaker uses per day, pair, mean daily THI, days in milk, daily milk yield, and interaction of treatment with mean daily THI. Study day was specified as a repeated measure, and cow as the subject, using an autoregressive structure. Also, we assessed the relationship of mean soaker use and THI against all variables. There was great individual variation in voluntary soaker use, ranging from 0 to 227 soakings/d (mean ± standard deviation, 13 ± 30 voluntary soakings/d). Treatment did not affect voluntary soaker use (MS, 12.4 ± 1.4 soakings/d; NMS, 14.8 ± 1.4 soakings/d), respiration rate (MS, 57.3 ± 0.4 breaths/min; NMS, 56.4 ± 0.4 breaths/min), or milk yield (MS, 36.5 ± 0.6 kg/d; NMS, 36.2 ± 0.6 kg/d). However, MS cows spent more time ruminating (MS, 558.6 ± 5.2 min/d; NMS, 543.4 ± 5.4 min/d). Temperature-humidity index had a positive relationship with voluntary soaker use and mean respiration rate. In conclusion, voluntary soaker use related positively to the THI, but no major productive, physiological, or behavioral differences were observed between soaking treatments. Furthermore, we found that voluntary soaker use is highly variable among cows and it was related positively to milk yield, where higher producing cows used the soaker more frequently.

Standards for data generation and collection are important for integration and for achieving data-driven actionable insights in dairy farming. Data integration and analysis are critical for advancing the dairy industry, enabling better decision-making, and improving operational efficiencies. This commentary paper discusses the challenges of and proposes pathways for standardizing data generation and collection based on insights from a multidisciplinary group of stakeholders. Drawing from a series of meetings of industry experts, academics, and farmers organized under the Dairy Brain Project’s Coordinated Innovation Network (CIN), we explore the benefits of creating uniform data generation and collection protocols to ensure compatibility and reliability across different data sources. Key insights include the importance of defining standardization at both farm and industry levels, the role of education and incentives, and the potential for using existing frameworks such as the International Committee for Animal Recording. Additionally, we highlight industry-specific case studies, including successful examples from Brazil such as GERAR, which focuses on reproductive performance data, and Labor Rural, which integrates data from multiple farms to provide valuable insights to farmers and milk processors. The paper concludes with recommendations for implementing these protocols and highlights the need to foster collaboration among stakeholders for the successful implementation and adoption of standardized data generation and collection protocols in the dairy industry.

This study evaluated the effects of an oral probiotic capsule containing a live culture of Megasphaera elsdenii NCIMB 41125 on performance, feeding behavior, rumen pH and VFA concentration, and development of dairy-beef crossbred calves. Thirty-one male dairy-beef crossbred calves (Holstein × Angus; mean ± SD; 45.3 ± 7.1 kg; 8.2 ± 2.0 d old) were enrolled in a blinded, 76-d randomized trial. Calves were randomly assigned to one of 3 treatments: placebo, probiotic capsule administration on d 15, or probiotic capsule on d 15 plus a second capsule on d 39 of the study. Calves were housed individually with ad libitum access to water and calf starter and were fed 7 L/d of milk replacer (1,050 g of powder/d) in 2 meals until d 41, then 3.5 L/d in 2 meals until weaning on d 56. Behavioral observations were recorded in 1-min intervals using a wall-mounted camera. Rumen fluid samples were collected on d 14, 35, 49, 58, and 70, and analyzed for pH and VFA. Upon euthanasia on d 77, forestomach weights were recorded and rumen papillae dimensions were measured. Mixed linear models were used for statistical analysis. Probiotic treatment resulted in greater daily solid feed DMI and ADG, particularly during weaning and postweaning periods. Additionally, probiotic-treated calves spent more time drinking water and tended to have lower rumen pH compared with control calves. Empty rumen weight and papillae area were greater in calves supplemented with the probiotic capsule on d 15 compared with the other treatments. These findings suggest that preweaning M. elsdenii supplementation enhances performance and rumen development in dairy-beef crossbred calves. However, the effects of timing and number of capsule applications on rumen development and calf performance should be further investigated. Further research should also investigate the probiotic's effect on the rumen microbiome and fermentation dynamics throughout the rearing period using detailed microbiome analysis.

The objective of this study was to evaluate the current perceptions and adoption practices of precision dairy technologies (PDT) by dairy farmers in the United States. A web-based survey was created and distributed to US dairy farmers via email, QR codes, and printed materials. Respondents disclosed herd size, farm characteristics, and if PDT were adopted. Furthermore, respondents used a 5-point Likert scale to assess PDT perceptions (1 = strong disagreement and 5 = strong agreement) and a 101-point visual analog scale to weigh between routine flexibility (0) and return on investment (100; ROI) when adopting a PDT. Data were summarized for descriptive purposes and a Kruskal-Wallis test was used to assess farmer perceptions and preferences toward PDT. A total of 81 respondents representing 48,289 dairy cows across 17 US states completed the survey, and 81.5% of survey respondents representing 47,208 cows indicated the adoption of at least one PDT. Among the PDT adopted by survey respondents, wearable technologies were the most common, with a 64.2% adoption rate. Non-adopters indicated that the cost of purchasing PDT was their main barrier to adoption. Furthermore, survey respondents agreed (median Likert score = 4) that PDT adoption can improve on-farm decision making and the services provided by consultants but requires significant time to analyze data. Lastly, respondents indicated a preference for technologies that maximize ROI over routine flexibility (median visual analog scale score = 67). These findings suggest that adoption of PDT among US dairy farmers increased in comparison to previous surveys. In addition, both adoption and non-adoption of PDT seem to be mostly driven by economic factors. Hence, highlighting the need for future research and analytic tools to evaluate the economic benefits and ROI of PDT adoption.