An increasing proportion of dairy farms are adopting automated milking systems (AMS). At the same time, the dairy industry is actively exploring strategies to reduce the water footprint of milk production. Automated milking systems have different cleaning procedures than traditional conventional milking systems (CMS), so the effect on water use is a potentially important consideration. Previous studies of AMS approximately a decade ago showed ∼50% more direct water use compared with CMS; however, those studies were based on older technology and compared different farms. The current study measured whole-farm water use partitioned into drinking (for consumption) and service water (for cleaning) on a dairy farm in Eastern Canada. The dairy farm milked 110 to 120 cows initially using CMS and then changing to AMS. Results showed that the pattern of water use changed with the AMS to increased peak drinking water and decreased peak service water use. Cows produced more milk and consumed more water with the AMS. Overall service water use per cow decreased from 30.9 ± 7.7 L·d-1 with the CMS to 22.5 ± 4.0 L·d-1 with the AMS, and overall service water use per unit of milk decreased from 0.98 ± 0.25 L·L-1 with the CMS to 0.68 ± 0.13 L·L-1 with the AMS. Daily service water use was also more consistent with the AMS (CV = 17.9%) versus the CMS (CV = 24.8%). With the AMS, the farm used significantly more water, produced significantly more milk, and achieved significantly better water use efficiency per liter of milk.

Canada's climate is warming faster than the global average, but the warming is unevenly distributed. This study analyzes historical and future climate change in dairy-producing regions across Canada to better understand how Canada's dairy cows are affected. Historical changes (i.e., 1960–2019) were assessed using temperature and humidity data from 29 weather stations across the country. The temperature–humidity index (THI) was used as an indicator of dairy cattle at risk of heat stress, and three THI metrics evaluated the frequency, severity, and duration of potential heat stress. Future scenarios were investigated using five global climate models to project daily THI under three Shared Socioeconomic Pathways (SSPs). Projections were grouped into three time periods (2020–2049, 2040–2069, and 2060–2089). Historical climate trends show an increase in temperature, humidity, and THI exceedance in most west coast and eastern Canada locations, affecting 84% of the national dairy herd. Future scenarios project that 90% of the national herd will experience a large increase in the frequency, severity, and duration of THI exceedance under all but the most optimistic SSP. These findings highlight the need for Canadian dairy farmers to consider heat-stress adaptation strategies.

The purpose of this study was to identify current practices and perceptions around trace element feeding for dairy cows through a Canadian dairy nutritionist survey. An online survey with 23 questions was used to collect data from Canadian dairy nutritionists with the help of professional associations and social media. The survey was active from November 2021 to April 2022. The first 7 questions collected descriptive information on respondents, and the subsequent 16 questions focused on trace element feeding. A total of 92 participants from all over Canada filled out the survey, and about 26% of Canadian herds and cows were represented by these respondents. The participants had diverse views on the importance of diet formulations for trace elements to optimize cow health and productivity, with perceptions varying from very important to not important. In comparison, macronutrients and selenium were consistently rated as very important by between 58% and 74% of respondents. Software reference values were used by 54%, 72%, and 73% of participants to estimate trace element concentrations of forages, cereals, and protein sources, respectively, highlighting the importance of regularly updating the feed library of the software. More than 60% of nutritionists participating in this study had intentionally formulated diets above trace element software recommendations, considered mineral interactions occurring in the rumen, and used a trace element source known for its better bioavailability (e.g., organic, chelate) when they formulated diets. Herds with more than 80 cows were more likely to be given trace element supplements known for their greater bioavailability. The most used supplement with enhanced bioavailability was selenium. In addition, different trace element feeding strategies pertaining to different stages of lactation and breeds were reported. This finding can be explained by the absence of clear recommendations on trace element feeding by breed. The participants who adjusted trace element feeding according to the stages of lactation considered the transition period as the most challenging period, and they identified the need for a source of trace element known for its greater bioavailability for this period. Further research should aim to identify environmental risk of trace element overfeeding using the One Health approach. Moreover, strategies to avoid trace element overfeeding should be evaluated.

The health, longevity, and performance of dairy cattle can be adversely affected by heat stress. This study evaluated the in-barn condition [i.e., temperature, relative humidity, and resulting temperature-humidity index (THI)] at 9 dairy barns with various climates and farm design-management combinations. Hourly and daily indoor and outdoor conditions were compared at each farm, including both mechanically and naturally ventilated barns. On-site conditions were compared with on-farm outdoor conditions, meteorological stations up to 125 km away, and NASA Power data. Canadian dairy cattle face periods of extreme cold and periods of high THI, dependent on the regional climate and season. The northernmost location (53°N) experienced about 75% fewer hours of THI >68 compared with the southernmost location (42°N). Milking parlors had higher THI than the rest of the barn during milking times. The THI conditions inside dairy barns were well correlated with THI conditions measured outside the barns. Naturally ventilated barns with metal roofs and without sprinklers fit a linear relationship (hourly and daily means) with a slope <1, indicating that in-barn THI exceeded outdoor THI more at lower THI and reached equality at higher THI. Mechanically ventilated barns fit nonlinear relationships, which showed the in-barn THI exceeded outdoor THI more at lower THI (e.g., 55–65) and approached equality at higher THI. In-barn THI exceedance was greater in the evening and overnight due to factors such as decreased wind speed and latent heat retention. Eight regression equations were developed (4 hourly, 4 daily) to predict in-barn conditions based on outdoor conditions, considering different barn designs and management systems. Correlations between in-barn and outdoor THI were best when using the on-site weather data from the study, but publicly available weather data from stations within 50 km provided reasonable estimates. Climate stations 75 to 125 km away and NASA Power ensemble data gave poorer fit statistics. For studies involving many dairy barns, the use of NASA Power data with equations for estimating average in-barn conditions in a population is likely appropriate especially when public stations have incomplete data. Results from this study show the importance of adapting recommendation on heat stress to the barn design and guide the selection of appropriate weather data depending on the aim of the study.

Light from the environment is important for vision and regulating various biological processes. Providing supplemental lighting in the stall area could allow for individually targeted or group-level control of light. This study aimed to determine whether dairy cattle had preferences for short-term exposure to white (full-spectrum) light-emitting diode (LED) light or no LED light, yellow-green or white LED light, and blue or white LED light in the stall area. In total, 14 lactating cows were housed in a free-stall pen with unrestricted access to 28 stalls. LED light was controlled separately for each side of the stall platform. Two combinations of light were tested per week, and each week consisted of three adaptation days and four treatment days. Lying behaviour and video data were recorded continuously using leg-mounted pedometers and cameras, respectively. Preference was assessed by the amount of time spent lying and the number of bouts under each light treatment. No differences occurred between treatments within each week for daily lying time and number of bouts. Similarly, no differences occurred between treatments within each time period. Further controlled studies of long-term exposure to different LED wavelengths and intensities are required to determine potential benefits on metabolic processes.

Perennial forage production exists in Ontario to support the livestock industry, but also provides nesting habitat for grassland birds such as the threatened Bobolink (Dolichonyx oryzivorus) and Eastern Meadowlark (Sturnella magna). Delaying hay harvest until July 15 or later allows most nestling birds to leave the nest, but the nutritional value of hay decreases substantially. This project estimated the nutritional and economic impact of delaying the first hay cut until after July 15 on beef and dairy production in Ontario, Canada. Forage crops were sampled across Ontario, analysis of nutritional value performed, and effects on production and economics modelled. 634 samples were collected over 13 weeks at 16 sites from May 21 to August 14 during 2014 and 2015. As expected, nutritional quality declined over the season. Crude protein decreased by 5.2%, total digestible nutrients by 7.7%, neutral detergent fibre digestibility (NDFd48) by 20.1%, while lignin increased by 3.5%, neutral detergent fibre by 13.1%, and acid detergent fibre by 9.9%. Estimated yearly milk production decreased 10.9 kg or C$7.87/dairy cow for each day of delay in harvest (2017 values). Estimated growth of backgrounding beef steers decreased 1.56 kg or C$5.49/head for each day of delay in harvest. This translated into lost revenue per acre for backgrounding steers of C$31 per acre and C$45 per acre for over wintering beef cows for a delay from mid-June to mid-July. Some agri-environmental incentives in Canada, US and Europe offset the reduced revenue due to lower quality forages. This analysis informs farmers about the cost of practices to benefit grassland birds and provides empirical data on how to structure stewardship incentives for these practices.

The blue water footprint (WF) is an indicator of freshwater required to produce a given end product. Determining the blue WF for milk production, the seasonal water use and the impact of water conservation are important sustainability considerations for the dairy industry in Ontario (Canada). In this study, a water footprint network (WFN) method was used to calculate the seasonal blue WF’s from in-barn water use data and the fat–protein-corrected milk (FPCM) production. Various water conservation options were estimated using the AgriSuite software. Results showed that the total water use (L of water·cow−1·d−1) and the average blue WF (L of water·kg−1 of FPCM) were 246.3 ± 6.8 L·cow−1·d−1 and 7.4 ± 0.2 L·kg−1, respectively. The total water use and the blue WF could be reduced to 182.7 ± 5.1 L·cow−1·d−1 (25.8% reduction) and 5.8 ± 0.1 L·kg−1 (21.6% reduction), respectively, through adaptive water conservation measures as the reuse of the plate cooler and milk house water. For example, conservation practices could reduce the milk house wash water use from 74.3 ± 8.8 L·cow−1·d−1 to 16.6 ± 0.1 L·cow−1·d−1 (77.7% overall reduction).

In Kuwait, dairy farming faces challenges due to its significant water demands. The current study assessed seasonal patterns of water use to estimate the blue water footprint (WF) and grey WF per kg of fat protein corrected milk (FPCM) for confined dairy farming systems in Kuwait. Blue and grey WFs were evaluated using data from three operational farms. The average blue WF (L·kg-1 FPCM) was estimated to be 54.5 ± 4.0 L·kg-1 in summer and 19.2 ± 0.8 L·kg-1 in winter. The average grey WF (generated from milk house wastewater) was assessed on bimonthly basis and determined based on its phosphate (PO4) concentration (82.2 ± 14.3 mg·L-1) which is the most limiting factor to be 23.0 ± 9.0 L·kg-1 FPCM d-1. The outcomes indicate that enhancing the performance of dairy cows and adopting alternative water management strategies can play a role in minimizing the impacts of confined dairy farming systems in Kuwait on water quality and quantity.

Standard life cycle assessment and economic analysis methods were used to determine the carbon footprint (CF) of milk production and financial performance of a representative sample of dairy farms in Ontario, Canada to assess if there is a trade-off between these two different sustainability measures. Across the 142 dairy farms, CF of milk varied by about 4-fold, from 0.441 to 1.732 CO2eq kg−1 FPCM, a much larger variation than estimated using spatially disaggregated statistical data. Emissions from enteric fermentation and those resulting from the production and supply of feed were the largest contributors to the CF of milk (44% and 36%, respectively). Dairy profits per cow averaged CA$4848 per year but ranged from CA$2530 to $7151 across sample farms. These financial returns were inversely correlated with the CF of milk production, suggesting that rather than a trade-off between GHG emissions intensity and economic performance, there is instead a synergy of the two sustainability indicators. Using a linear regression approach we find that a reduction in the CF of milk production can be achieved while simultaneously improving the profitability of dairy farms. This synergy was largely determined by farm characteristics related to livestock productivity (e.g. milk production per cow) and feeding practices (e.g. herd level total feed use and reliance on purchased feed). Our results suggest that in the absence of explicit GHG reduction policies targeting dairy farms, the main incentive for reducing farm-level GHG emissions could result from the economic pressure on farmers to increase their profitability per cow or per ha.