Three fact sheets on best practices to mitigate greenhouse gases in livestock, manure, and crop management were updated and are now available online at DairyResearch.ca. The fact sheets include the key results from Dairy Farmers of Canada’s (DFC) Life Cycle Assessment of Milk Production Update.
The fact sheets illustrate how the increased adoption of best practices helped lower the carbon footprint of milk production by 7.3% in five years.
The fact sheets reflect research outcomes from a large-scale project called the Farm-scale Assessment of Greenhouse Gas Mitigation Strategies in Dairy Livestock-Cropping-Systems funded under AAFC’s Agricultural Greenhouse Gases Program (AGGP), which was supported by DFC as well as study results from farm sustainability projects under Dairy Research Cluster 2.
New research supported by Agriculture and Agri-Food Canada (AAFC) and Dairy Farmers of Canada (DFC) under the Dairy Research Cluster 3 is identifying and testing methods to manage water use more efficiently on dairy farms, including drinking water used by dairy cattle. The five-year project led Drs. Andrew VanderZaag (AAFC) and Robert Gordon (University of Windsor) and a team of collaborators from across Canada called “Reducing the water footprint of milk production in current and future climates” has three major objectives:
Characterize in-barn water use and identify best management practices to reduce water use and increase efficiency;
Assess heat stress in dairy cows and evaluate abatement options in current and future climates; and,
Evaluate practical treatment methods for managing silage effluent.
The project builds on the results from a large water use and conservation project completed under the Dairy Research Cluster 2 (2013-2018) that measured the water footprint of milk production and identified ways for reducing it. The researchers are taking measurements of water use (in-barn and wastewater) and heat stress indicators on farms in Alberta, Ontario, Quebec and Nova Scotia. Dairy barns are being fitted with flow meters and the data collected will be compiled to develop region-specific water use benchmarks. They will incorporate the data into models to evaluate the effectiveness of different management practices to improve water use efficiency by region while factoring in energy use and the costs of different environmental best practices.
Minimizing heat stress to dairy cows is one of the biggest opportunities identified by the researchers to manage water use more efficiently on dairy farms and lower the water footprint. When cows experience heat stress, their feed intake drops, their water intake increases, and milk yield is decreased. These factors contribute to a higher water footprint value, in addition to negatively impact reproduction and cow health, leading to a loss of revenues for farmers.
The frequency and extent of heat stress episodes in Canada are expected to increase with climate change. To address this challenge on farms, the researchers are examining heat stress indicators like the Temperature Humidity Index (THI is a number that shows the combined effect of air temperature and humidity) in different barn types, designs and ventilation systems on test sites across the country. They will be evaluating different strategies to reduce the impact on the animals and water use.
Another important component of this research includes measuring and capturing dairy farm run-off containing a high pollutant load that can be harmful to the environment. The researchers are investigating low-cost treatment systems to collect the nutrient-rich runoff and will be testing new technologies to capture important nutrients like phosphorous from the wastewater.
The results from this national research will help provide science-based evidence to develop best management practices for climate change adaptation, lower the water footprint and improve environmental farm performance.
Quick Project Facts
Principal Investigators: Andrew VanderZaag (Agriculture and Agri-Food Canada (AAFC) – Ottawa) and Robert Gordon (University of Windsor)
Co-Investigators: Roland Kroebel (AAFC-Lethbridge), Merrin Macrae (University of Waterloo), Édith Charbonneau (Université Laval), Terra Jamieson (AAFC-Halifax), Ward Smith, Budong Qian (AAFC-Ottawa)
Collaborators: Tom Wright (Ontario Ministry of Agriculture, Food and Rural Affairs), Sean McGinn, Tim McAllister (AAFC-Lethbridge), Keith Reid (AAFC-Guelph), Ray Desjardins (AAFC-Ottawa), Tim Nelson (Livestock Research Innovation Corporation), John McCabe (Nova Scotia Department of Agriculture)
Total budget: $706,438
Funding partners: Cash contributions provided by Agriculture and Agri-Food Canada and Dairy Farmers of Canada.
Eight Canadian dairy farms are targeted for participation in this research project.
Resources on best practices to reduce water consumption on your dairy farm:
In the coming months, we will be featuring one of the 15 new Cluster 3 research projects in each blog, providing our followers the opportunity to learn more about the research underway, how it’s associated to dairy farmers’ research priorities, why it’s important for dairy innovation and provide more information about the scientists involved in the projects.
New research started in 2018 under the Dairy Research Cluster 3 is investigating ways to maximize the efficiency of robotic milking systems and optimize cow health within those systems. The project, led by Dr. Trevor DeVries of the University of Guelph, is very timely – about 11% of farms enrolled in a milk recording program in Canada use robots and the adoption of this technology continues to increase.
The scope of the new research is impressive. This is the first study of its kind to investigate robotic milking technologies on farms across all provinces, using data collected in collaboration with Lactanet. The research team includes top Canadian experts in the fields of dairy cattle health, farm management and nutrition, spanning across Canada: Drs. Greg Penner and Tim Mutsvangwa (University of Saskatchewan), Drs. Karin Orsel and Ed Pajor (University of Calgary), Dr. Todd Duffield (University of Guelph) and Richard Cantin, Débora Santschi and René Lacroix (Lactanet).
The research team will be identifying cow and herd-level factors that influence milk production, cow health and the efficiency of robot use in a large-scale sample of dairy farms. The information will be used to identify best management practices to help farmers using robotic systems produce milk more efficiently and maintain excellent dairy cow health, with a specific focus on health in early lactation and feeding practices in robotic barns, based on barn design and layout, for all stages of lactation.
“Considering the number of farms using robotic technology and the potential for growth, there are still gaps in our knowledge on the best strategies farmers can use to address some of the challenges we identified in the Dairy Research Cluster 2 research. This new research will build on those results,” said Dr. DeVries.
In the Dairy Research Cluster 2 project on automated milking systems, the researchers demonstrated that lower milk production and issues with cow health, especially in early lactation, impacted the profitability of adopting robotic systems. Lameness, for example, was one of the primary factors identified with an overall negative impact on milk yield per cow and per robot. Clinically lame cows (gait score of 3 out of 5 or greater) were 2 times more likely to be fetched and produced 1.6 kg of milk less per day than healthy cows and milked 0.3 fewer times per day. Severely lame cows (gait score of 4 out of 5 or greater) were most likely to turn into chronic fetch cows.
Over a 12-month period, this group of researchers will be collecting data on housing, feeding and management by farm and by robotic system, and extract milk recording data for each herd. The data will be analyzed to assess cow and herd level impacts on milk production, health and robot use.
“The extent of the dataset collected by farm and by region will allow us to assess robotic system performance. We will then be able to make some associations or differentiations and develop benchmarks dairy farmers can use if they are already milking with robots or are thinking about installing the technology on their farm. We look forward to developing some very practical independent information for Canadian dairy farmers that is science-based and supports their application of the technology in the most efficient way,” concluded DeVries.
Quick project facts
Project timeline: 2018-2022
Funding partners: AAFC, DFC, with an in-kind contribution from Lactanet
Number of farms involved: 200+
Number of students to be trained: 8+
The research team
Dr. Trevor DeVries (Professor and Canada Research Chair in Dairy Cattle Behaviour and Welfare) is the Principal Investigator, project coordinator, and the primary advisor for the Ph.D. student and undergraduate summer research assistants at the University of Guelph. Dr. DeVries will coordinate all the data collection, particularly the data collected in Ontario and Quebec.
Dr. Todd Duffield (Professor, Ontario Veterinary College) is a Collaborator and an advisory committee member to the Ph.D. student at the University of Guelph, and is assisting in project design, analysis, and interpretation.
Dr. Gregory Penner (Associate Professor in Nutritional Physiology) and Dr. Timothy Mutsvangwa (Professor of Ruminant Nutrition and Metabolism), University of Saskatchewan, are providing expertise in dairy cattle nutritional physiology. As Co-Investigator, Dr. Penner is responsible for advising the undergraduate summer research assistants who will collect data on farms in Saskatchewan and Manitoba. Both researchers will contribute to data interpretation and manuscript writing.
Dr. Karin Orsel (Associate Professor Veterinary Epidemiology, University of Calgary) as Co-Investigator, is responsible for advising the undergraduate summer research assistants who will collect data on farms in Alberta. Drs. Orsel and Dr. Pajor (Collaborator) will contribute to data interpretation and manuscript writing.
The project involves key collaborations from Lactanet: Richard Cantin, Débora Santschi and René Lacroix. They will provide assistance in the identification and recruitment of herds, expertise in data management, as well as provide access to their milk recording data (subject to producer agreement and consent to participate in the study).
Fifteen new research projects targeting dairy farm efficiency and sustainability, cow health and welfare, milk quality, and dairy and cardiometabolic health were announced under the Dairy Research Cluster 3 in July 2019. Joint industry and government commitments to the Dairy Research Cluster 3 total $16.5 million, including the contribution from major partners Agriculture and Agri-Food Canada, Dairy Farmers of Canada, Lactanet Canada and Novalait. Moreover, 1,300 individual dairy farms and 10 dairy processors will be investing their time in the proposed research activities by collaborating with the research teams.
A summary of each research project is now available online at dairyresearch.ca for download. The summaries contain the list of researchers working on the project, the amount invested in the project, the objectives, a brief overview, as well as the expected outcomes.
Copies of the summaries will be distributed at upcoming conferences where the Dairy Research Cluster kiosk is installed.
Dairy farmers looking for resources and tools associated with the prevention, management, and treatment of mastitis can access a number of information documents and videos available online through the Mastitis Network’s new website at www.mastitisnetwork.org.
A summary of results from the mastitis research program under the Dairy Research Cluster 2 (2013-2018) is available on dairyresearch.ca. The two-page summary includes a list of key outcomes and links to mastitis research projects conducted over the last five years. By clicking on the links in the document, you can learn more about the results of the project, knowledge translation and transfer tools developed to date, and the publications to inform and help dairy farmers manage the health of their animals.
On July 16, 2019, the Minister of Agriculture and Agri-Food Canada, the Honourable Marie-Claude Bibeau, announced an $11.4 million investment in a third Dairy Research Cluster to be led by Dairy Farmers of Canada (DFC). Joint industry and government commitments to the Dairy Research Cluster 3 total $16.5 million, including the contribution from major partners Lactanet Canada, Novalait, and Agriculture and Agri-Food Canada.
Investments will be made in 15 research projects targeted to address DFC’s strategic research priorities identified in the National Dairy Research Strategy and will cover dairy farm efficiency and sustainability, cow health and welfare, milk quality, and the health benefits of dairy products consumption.
The Dairy Research Cluster 3 (DRC3) builds on the success of the Dairy Research Cluster 1 and 2 (2010-2018) to stimulate productivity, sustainability, and profitability on farms, and to improve knowledge of the health benefits of milk and dairy products consumption.
A new video blog (VLOG) is available featuring Dr. Derek Haley of the University of Guelph reporting on his research findings in calf health, welfare and the use of automatic calf feeders. Funded under the Dairy Research Cluster 2 (2013-2018), Dr. Haley and his collaborators investigated the labour requirements, potential welfare benefits for calves and the ability to accelerate performance of pre-weaned calves housed in groups with automated feeders. Watch the VLOG of Derek reporting on his findings on the Dairy Research Cluster YouTube Channel here:
University of British Columbia Professor Marina (Nina) von Keyserlingk was recognized by the Hans Sigrist Foundation at the University of Bern, Switzerland, with the 2018 Hans Sigrist Prize for her outstanding academic contributions in the field of Sustainably Produced Food of Animal Origin.
“The search committee was unanimous in recognizing that she is truly outstanding when compared to others working in the same field” stated committee chair Professor Rupert Bruckmaier, Head of Veterinary Physiology at the University of Bern.
The foundation awards the Hans Sigrist Prize with an equivalent of $130,000 CAD research grant to a mid-career academic researcher to recognize research contributions to date and to encourage further outstanding work.
Dr. von Keyserlingk had held a NSERC Industrial Research Chair in Animal Welfare supported by the dairy sector, including Dairy Farmers of Canada, since 2008. Nina is recognized internationally for cutting-edge research on the care and housing of dairy cows and calves. She has been a pioneer in the use of behaviour (including especially automated measures) for the early detection and prediction of disease in animals. This work has focused on the use of changes in feeding and social behaviour as early indicators of disease, and has provided a basis for the rapid growth in new research focused on automated health assessments on farms.
Her work is also among the first in the field of animal welfare to incorporate qualitative methods when addressing animal welfare issues, such as interviews, focus groups and online crowd sourcing tools to understand perspectives of farmers, veterinarians and the public with regards to animal care and use. This work has motivated scientific research better targeted at perceived constraints and illustrates a new trend towards interdisciplinary research to address societal concerns around animal agriculture.
A new series of MOOCs on mastitis (MOOC is a Massive Online Open Course) is available free through the Université de Montréal. The series was designed by the Canadian Bovine Mastitis and Milk Quality Research Network (CBMQRN) and Université de Montréal as part of the NSERC CREATE in Milk Quality Program. The researchers brought together experts from more than 20 countries to produce the series to initiate graduate students to mastitis science and prepare them for their research programs. Dairy practitioners, teachers and other professionals with a solid scientific background can also enrol to advance their knowledge.
The first MOOC called, The mammary gland and its response to infection, has been available since November 2017. It contains basic knowledge on mammary gland anatomy and physiology, immune response, the role of genetics, and pathophysiology. Information can be found at: Mastitis MOOC 1.
The second MOOC, Mastitis Epidemiology and Diagnostic, presents methods of identification of mastitis infections and methods of diagnostics. Enrolment and information can be accessed at: Mastitis MOOC 2 .
A third MOOC entitled, Mastitis control and milk quality, will be available at a later time.
Authors: Dr. Ronaldo Cerri (University of British Columbia) and Meagan King, (Postdoc, University of Guelph)
Why are automated activity monitors (AAM) becoming more popular on Canadian dairy farms? DFC-funded research has shown that AAM can work just as well as synchronization programs while also predicting which cows will have better fertility.
Neck collars or leg pedometers are currently used on 10% of Canadian dairy farms as their main strategy for reproductive management (>50% of inseminations). Visual heat detection and timed AI are still used more than AAM, but this may change as hormone use is further scrutinized.
Two large field trials in Ontario and BC (funded by the Dairy Research Cluster 2, supervised by Dr. Ronaldo Cerri at the University of British Columbia and students Tracy Burnett, Augusto Madureira, and Liam Polsky) found that reproduction programs using AAM for heat detection are equally efficient as those relying heavily on synchronization protocols.
Breeding cows based on AAM data had similar pregnancy per AI and days open compared with a strict timed AI program (Presynch-Ovsynch). With goals to improve heat detection accuracy and the use of AAM data to make farm-level management decisions, Dr. Cerri’s research group studies how estrus events and intensity are related to ovulation, ovarian/uterine function, fertility, and performance in dairy reproduction programs.
The researchers also found that cows with high intensity heats and large changes in activity (during spontaneous and induced estrus) had greater pregnancy per AI and better fertility, compared to cows with low intensity heats who had more ovulation failure. Moreover, the top 25% highest-producing cows had heats with the lowest intensity and shortest duration. Older cows, those with low body condition, and those experiencing high temperature-humidity indices (above 65) showed less estrus behaviour as well.
In the BC field trial, each individual farm was a big source of variation in the performance of programs based on heat detection, likely because AAM are more prone to individual farm variations compared with established timed AI protocols. This means that the best reproductive program for each farm may differ based on their specific strengths, particularly whether they can better use AAM or injection-schedules properly and consistently. Anovular cows and those with poor leg health can also impair the performance of AAM reproductive programs.
Ultimately, differences in attitudes and preferences among Canadian dairy producers (highlighted in a nationwide survey by José Denis-Robichaud) should be considered when choosing the optimal reproduction management tools. For example, producers have differing views about reproduction hormones in terms of profitability and long-term effects on fertility. However, for farms already reaching 30 to 35% conception rates from breeding at estrus, doing that will still be more profitable than completing full synchronization protocols.