- Weight bias and stigma
- The role of protein in aging
- Bone health across the lifespan
- Nutritional needs of active women
To consult the program and register, visit DairyNutrition.ca.
This event is organized in collaboration with:
To consult the program and register, visit DairyNutrition.ca.
This event is organized in collaboration with:
On July 17, 2017, the DFC Board of Directors adopted its new National Strategy for Dairy Production Research Knowledge Translation and Transfer (download your copy at DairyResearch.ca). The goals are to facilitate collaboration and coordination for knowledge translation and transfer, maximize the effectiveness of the transfer of research results and aim to increase innovation on farms.
The strategy was adopted following a recommendation made by DFC’s Canadian Dairy Research Council (a DFC Board committee comprised of representatives of provincial dairy organizations and six members from its Board of Directors). The strategy will be in effect immediately.
Published based on the results of a five-year study led by the University of Guelph’s Dr. Claudia Wagner-Riddle and her collaborators under the Agriculture Greenhouse Gas Program (Agriculture and Agri-Food Canada), the contents target recommended management practices that can contribute to GHG reductions. The practices were validated by a group of Canadian scientific experts working in the field of dairy and the environment, including studies financed by DFC under the Dairy Research Cluster. Click on the titles below to download a copy.
For printed copies, contact email@example.com
Three easy-to-follow reference documents on lameness, body condition score, and hock, neck and knee injuries were distributed to over 6,000 dairy farmers in the past six months to provide resource material for the proAction animal care validation starting in the fall of 2017. The material was developed with extension, scientific and proAction experts and the outcomes based on scientific findings financed by DFC and its partners under the Dairy Research Cluster. Click on the titles below to download a copy.
For printed copies, contact firstname.lastname@example.org
Automatic milking systems (AMS) use has increased in the dairy industry in the last few years. Seven percent of all Canadian dairy farms were using some type of AMS in 2015 according to Statistics Canada. But like all new systems, there are benefits and challenges.
A research project investigating lameness in AMS farms (funded by the Dairy Research Cluster 2) led by PhD student Meagan King under the supervision of Dr. Trevor DeVries at the University of Guelph, the team found that one of the challenges of AMS herds was the identification of mildly lame cows. Lameness has an impact on the entire herd, and not just at the cow level. In fact, an increased lameness prevalence of the whole herd reduces overall production.
In the study, 41 robotic herds were surveyed and data about management, barn design, and lameness prevalence was collected. Researchers then looked at risk factors for lameness at the herd and cow-level, as well as factors related to productivity, efficiency, and cow behaviour.
They collected data by visiting 26 farms in Ontario and 15 farms in Alberta. Producers in each farm were asked about feeding, manure, and bedding management. Researchers recorded details regarding barn design and stocking density of cows relative to feed bunk space, lying stall availability, and the number of robots on each farm. They also scored a representative sample of cows at each farm for lameness (gait) to get an accurate estimate of their lameness prevalence, on a scale of 1 to 5 (1 being sound to 5 being extremely lame).
Increased prevalence of severe lameness is related to reduced milk production per cow and per robot. The researchers found that on average, less than 2% of the cows gait-scored were classified as severely lame (gait score of ≥4 out of 5). However, they found on average 26% of the cows gait-scored were moderately to severely lame (gait score of ≥3 out of 5). The majority of the lame cows they observed had a gait score of 3 out of 5.
In the AMS environments studied, cows with a slight, but noticeable limp, are fetched 2.2 times more, milked 0.3 times less per day, and produce 1.6 kg/day less milk than sound cows. The research also suggests that producers are doing a good job of identifying and treating severe lameness cases in their herd. But, the team found that producers have a harder time identifying the mild to moderate cases of lameness (which are labelled to ‘monitor’ under the proAction animal care assessment program).
Manure management had a significant impact on lameness prevalence on farms: herds that scraped manure from walking alleys more frequently had a lower prevalence of moderate lameness and lower rates of fetching cows. Cleaner floors improve the mobility of cows, which is important when those cows walk to a robot to be milked then back to their stalls or feeding area.
Stocking density affected production and lameness on farms: greater stocking density in lying stalls was related to higher severe lameness prevalence, and led to producers having to fetch more cows. Although a higher stocking density at the robot was associated with increased production per robot, it also reduced milking frequency per cow.
Cows with low body condition and cows of higher parity were more likely to be lame. This is consistent with other research: thin cows also have a thin digital cushion in their hooves, predisposing them to mechanical causes of lameness (i.e. sole ulcers).
These findings suggest that producers should manage, monitor and treat lameness early to improve animal care and prevent loss of production in AMS environments, similarly to other barn and stall types. Some ways to achieve this is to get trained to gait score cows and identify those mild cases of lameness and take corrective action. Producers should also be aware of cows’ body condition as thinner cows may have more underlying problems that should be investigated.
Producers with AMS should aim to keep floors clean to give cows an appropriate surface to walk on to and from the robot, as well as giving cows enough clean, comfortable, well-bedded resting space to maximize animal comfort, production potential and prevent lameness.
Resources and links
Meagan King is a PhD candidate in the Department of Animal Biosciences at the University of Guelph. Emilie Belage is an MSc graduate from the Department of Population Medicine at the University of Guelph and veterinary medicine student at Michigan State University.
Dairy Farmers of Canada (DFC) elected a new President during the organization’s Annual General Meeting in Edmonton on July 18 and 19. Wally Smith had completed the maximum three terms. After a vote by delegates, Pierre Lampron was elected as President, for a two-year term. Additionally, a new Executive Committee has been formed, comprised of David Wiens (Manitoba), Reint-Jan Dykstra (New Brunswick), Ralph Dietrich (Ontario), and Bruno Letendre (Quebec). Congratulations to Pierre Lampron on his election and to members of the new Executive Committee!
A series of six fact sheets are available at DairyResearch.ca that include Dairy Farmers of Canada’s dairy research investments for 2016-2017 and the impact of those investments on the dairy production sector, the health of Canadians and the economy. Read more about our success stories in Dairy genetics and genomics, Dairy cattle health, care and welfare, Sustainable milk production and Human nutrition and health.
Dr. Elsa Vasseur of McGill University has held the Chair on the Sustainable Life of Dairy Cattle at McGill University for over a year. Novalait has produced a new video providing an overview of the work underway on behalf of Canada’s dairy farmers! Click on the link to watch it now: Dr. Elsa Vasseur – Chair, Sustainable Life of Dairy Cattle.
Chair Investment: The total partner investment in this research is over $1.6 million for five years and includes investments from the the Natural Sciences and Engineering Research Council, Novalait, McGill University, Dairy Farmers of Canada and Valacta.
The research falls under three major themes. The Cow Comfort and Management theme will address tie-stall systems (given their current prominence) and examine solutions for the transition to freestall systems, for dairy farmers who wish to examine that option, from the point of view of animal comfort, management and potential economic benefits.
The Cow Longevity theme will assess the economic impact of risk factors for cow longevity related to management, housing, cow comfort and health, on the lifetime profit at the individual and herd level, and build decision-support tools to improve overall farm management, profit, and cow welfare and longevity, specifically by investigating i) Lifetime Profitability; ii) Rearing of Animals; and iii) Early Detection Indicators of Longevity.
The Environment and Society theme aims to understand, anticipate and prevent potential conflicts and solutions that would benefit both cow welfare and longevity (e.g., key practices and management systems identified in Research Themes 1 and 2), but that could counterbalance the overall sustainability of the farm and the farming system, by negatively affecting environmental impact and social acceptability.
The adoption of automatic milking systems (AMS) is increasing year after year across Canada. According to Dr. Ed Pajor, Anderson-Chisholm Chair in Animal Care and Welfare in the Faculty of Veterinary Medicine of the University of Calgary, “Canadian dairy producers want to know in advance what to expect if they make the transition to AMS.”
Dr. Pajor and his graduate student, Ms. Christine Tse, conducted a study funded under the Dairy Research Cluster program with producers who had already transitioned to this new system. They surveyed 200 Canadian dairy producers to document their perceptions of the effect of transitioning to AMS on their farm.
The average farm participating in this study had 51 lactating cows per milking robot and two AMS units per dairy farm. Almost all producers surveyed (81%) reported increased milk yield with little change in milk quality after transitioning to AMS. More than half (55%) of producers built a new barn and 47% said they changed housing systems.
For the majority of producers, their cleaning and feeding practices remained unchanged. Most producers perceived that all the information provided by the robots about each animal made it easier to detect lameness or illness in their cows.
Most producers noted lameness either decreased or stayed the same after introducing AMS, and detecting lame cows was facilitated by the automatic detection in AMS. They also noted having AMS allowed more time to observe cows, thus enhancing lameness detection. One potential note of caution is changing the housing system at the same time as transitioning to AMS seemed to lead to more reports of increased lameness. This suggests the change in cow locomotion after switching from tiestall to freestall in tandem with the installation of an AMS has a greater impact on lameness than simply introducing a new milking system.
The vast majority (87%) of producers reported either a decrease or no change in the rate of clinical mastitis, and about two-thirds of producers reported that the conception rate increased with AMS.
Almost all producers agreed that AMS improved their quality of life in terms of more flexibility, less physically-demanding work, and easier employee management.
“Overall, producers reported to us that the transition to AMS met their expectations and increased the profitability of their operation. In addition, they would recommend AMS to other producers,” affirmed Dr. Pajor.
Author: Shannon L. Tracey, Ph.D., Cross the “T” Consulting
Group housing of dairy calves is becoming more popular, and so are automatic milk feeders (AMF). Some of the reasons producers choose to use this new technology include: addressing calf health and welfare concerns; and reducing labour while still providing calves with enough milk to reach their growth potential. Automatic milk feeders also offer producers the option to monitor each calf’s milk intake, and thus more easily detect and identify calves that may be sick thanks to alarms integrated in the system.
One of the challenges producers face with automatic milking feeders is teaching calves to interact with and learn to use the feeders. Some calves have more difficulty learning to use them and this can cause a decrease in milk consumption and potentially lead to slow-growing or sick calves.
A study by the University of Guelph (financed under the Dairy Research Cluster program) aimed to compare how stall design and training methods affected calf interactions with the automatic milk feeders. Tanya Wilson, the graduate student leading the project under the supervision of Dr. Derek Haley, compared two types of stalls commonly installed with the feeders. The goal was to see if calves learned to use one type better than the other. Their initial hypothesis was that calves would take a longer time approaching solid stalls constructed of white plastic without some type of assistance, compared to a metal-gated stall design.
They enrolled 147 Holstein calves from the Elora Livestock Research and Innovation Center -Dairy facility. The calves were at least 4 days old when they were introduced to group-housing with AMF. They were assigned to one type of stall design and then trained to use the automatic milk feeders by the researchers by allowing them to suck on the trainer’s fingers and guiding them to the teat on the feeder. Some calves were trained on feeders with solid stalls (Figure 1) and others were trained on metal-gated stalls (Figure 2). Researchers recorded the behaviour of calves for 3 days using video cameras, and then used the data from the feeders to determine how long calves took to approach the feeders and how often and how much they drank.
What they found was that calves assigned to the gated-stall design took twice as long to approach the feeding stall compared to calves assigned to the solid sides. They took longer to lick or bite at the nipple, and it took them more time to drink voluntarily from the metal-gated feeders. Calves using the feeders with a solid stall design learnt much quicker to enter and use the nipple. Overall calves drank anywhere from 8 to 34 litres in the 72 hours they were observed. The researchers also found that how easily a calf learned during their initial training interacted with stall-design and affected milk intake in calves. Those trained on the gated-style feeder consumed an average of 3.18 litres less than calves trained on the solid-style feeder.
Thanks to this study, researchers have some evidence that specific features of automatic milk feeders can impact how well calves learn to use them, which in turn impacts how much milk they consume, with potential repercussions on calves’ health and welfare. Producers should be aware how stall design might affect their efforts for calf rearing and be mindful some calves may need more training for a more successful transition to feeding.
Authors: Emilie Belage, MSc., University of Guelph and Tanya Wilson, a Master of Science student in the Department of Population Medicine at University of Guelph
The field of genomics has the potential to not only improve the dairy industry at the herd level, but it has implications at national and global levels. A cutting-edge Canadian initiative, led by Dr. Filippo Miglior, of the University of Guelph, in collaboration with Dr. Paul Stothard, of the University of Alberta, seeks to understand how genomics impact feed efficiency and reduce methane production in dairy cattle in a 10-year project launched in 2015. Thanks to the relationship between producers and researchers involved in this project, the researchers and industry expect producers will be able to select for more efficient, less costly animals, while preserving the environment for future generations.
What is genomics?
Genomics is the study of the entirety of genes in a living organism. It helps us understand how genes interact to produce growth and development in an animal or plant. In dairy cows, it helps producers identify which cows have desirable traits, like high production, good reproduction or longevity, which can be passed onto offspring.
Importance of genomics and feed efficiency for producers and the planet
Feed is one of the main costs on a dairy farm. Having cows that can convert feed into milk more efficiently is beneficial for the bottom-line and the environment: farmers can select and breed for cows that produce more milk with less feed. What this also means, is that fewer crops need to be grown to feed the same number of animals, potentially freeing cropland for other purposes. Cows that eat less also produce less manure and less methane, an important greenhouse gas (GHG). This is not only important for manure management, as there is less manure that needs to be stored, but it also has implications on the environmental footprint dairy farms have today. Food production that is environmentally sustainable is becoming more and more important for consumers. There is increased concern and awareness of how the agricultural sector contributes to GHG emissions like methane, and its role in global warming. Dairy farmers’ investment in this research is innovative – by selecting for cattle that produce less methane, dairy farmers can do their part in addressing climate change now and in the future.
Data collection for accuracy of predictions
To be able to select for the feed efficiency trait, investigators needed to collect a lot of different phenotypes (i.e. the observable characteristics) and genotypes (i.e. genetic constitution) from cattle to be able to distinguish which animals are more efficient at converting feed into milk. Using prediction equations, they can look at the genotype from a young animal and predict early on whether that animal will be feed efficient or not. Feed efficiency and methane emissions are expensive traits to measure. It requires highly specialized equipment to accurately measure these phenotypes. With the arrival of genomics, researchers can measure those traits on a small number of animals, and then extrapolate the results on all genotyped populations, which reduces the costs.
Researchers also need a large amount of data to make accurate predictions in genomics, which is why they are collaborating with other countries for this project. The funding provided by Genome Canada, in collaboration with dairy farm organizations and other funders, gives the Canadian dairy sector the ability to measure these phenotypes, but also has the input of expertise from other countries that are also collecting data on these traits, allowing Canada to test its prediction equations for accuracy. Thus, without genomics and without the data consolidation from other countries, it would be impossible to consider feed efficiency and methane emissions in genetic selection strategies.
Real-time farm involvement in the research
SunAlta Dairy in Ponoka, Alberta is a participating dairy in this project. The Brouwer family was in the middle of building a new free-stall barn for 450 cows and agreed to install the necessary research equipment that measures feed intake for each of the cows. By collaborating with researchers, the Brouwers are able to get a first-hand impression of the value of the research and the value of genomics. “It brings research to the farm so producers can see that the work researchers do has real-life applications and benefits. Producers get to observe these benefits first-hand”, says Dr. Filippo Miglior. Getting data from a commercial herd also allows “real-life” data to be included in the analyses. This allows investigators to get more data (since a commercial herd is often bigger than a research herd at a university research station), and gives them data from a different environment than a research herd, an environment where cows are managed in “real-time” on a dairy farm. Results from this type of research are therefore directly applicable to other commercial herds.
Future application of results for the Canadian dairy industry
Results from this research can also be applied to herd management. The plan is for selection indexes to be produced, so that farmers can select for animals that are more feed efficient and lower methane emitters. Genomic evaluation for the novel traits will be developed at the Canadian Dairy Network. This research group believes that the addition of those traits will increase the rate of genotyping of young females at the herd level for replacement decisions. The amount of time needed to collect data is significant, which explains the length of the project (10 years). However, the investment is so unique, producers will see results over the long term and for generations to come. The benefits of this research also align with the proAction environmental targets: reduce GHG emissions related to milk production, and the impact on land needed to produce milk. The usefulness of this research will become more relevant over time by breeding for dairy cows that are much more efficient than the ones we have today.