Position/Title: Adjunct Professor, Chief Scientific Officer and Vice President, Sector Innovation & Programs at Ontario Genomics
Phone: (519) 824-4120 ext. 53647
Office: ANNU 119
Growing up in Milan, Italy, Filippo had little exposure to dairy cows until he attended the University of Milan, where he studied animal science. While studying dairy cows in the Italian Alps, he became fascinated by dairy cow genetics. A scholarship brought him to the University of Guelph, where he was mentored by Ted Burnside, director of the Centre for Genetic Improvement of Livestock. Filippo is now Chief Scientific Officer and Vice President, Sector Innovation & Programs at Ontario Genomics, is a publicly-funded not-for-profit organization that works with companies, researchers, and policymakers to support the early stages of moving genomics technologies from the lab to solve real world problems in the clinic and industry.
- Laurea Degree in Animal Science, University of Milan (1986)
- Ph.D. in Animal Breeding, University of Guelph (1994)
Affiliations and Partnerships
- Secretary of WCGALP Permanent International Committee (since 2014)
- American Dairy Science Association (since 1992)
- Canadian Society of Animal Science (since 2013)
Awards and Honours
- ICAR Distinguished Award for scientific contribution to International Committee for Animal Recording (2011)
- J.L. Lush Award in Animal Breeding from American Dairy Science Association, recognizing outstanding research in animal genetics (2013)
- Canadian Society of Animal Science Technical Innovation in Enhancing Production of Safe Affordable Food Award (2016)
- Rockefeller Prentice Memorial Award in Animal Breeding and Genetics from American Society of Animal Science, recognizing an individual’s research excellence in breeding and genetics.
Filippo leads applied research projects with industry partners to improve dairy cow genetics, with budget exceeding over $13.6M advising a team of over 20 graduate students and researchers. Developing genetic tools that enhance important traits, such as production, fertility and disease resistance, increase profitability for farmers and producers. Breeding cattle with genetic resistance to diseases can help reduce antibiotic use and veterinary costs. Feeding cows more efficiently reduces feed costs, waste and methane gas emissions. With more than one billion cows in the world, measuring feed intake and methane emissions is very costly (monitoring one cow can cost up to $2,000). Filippo’s research compiles data from smaller-scale projects involving up to 10,000 cows in multiple countries. Extrapolating this data on a global scale allows researchers to estimate genetic markers for various traits and produce genetic evaluations.
Current Research Projects
Improving hoof health in dairy cows
Hoof lesions are one of the biggest problems facing the dairy industry. Genetics play a role in a cow’s susceptibility to developing hoof lesions due to infection or injury. Cows that are bred to resist digital dermatitis, the most common cause of hoof lesions in Canada, are less likely to develop the condition, which reduces the need for antibiotics and veterinary intervention. Genetic selection to improve disease resistance can help improve animal welfare and productivity. The Canadian Dairy Network will provide genetic evaluations for digital dermatitis by the end of 2017. This project is funded by Dairy Farmers of Canada, Canadian Dairy Network, Canadian Dairy Commission, Agriculture and Agri-food Canada, Alberta Milk and Ontario Genomics.
Improving feed efficiency
Filippo is leading a $10.3-million project with Genome Canada, Ontario Genomics, Genome Alberta, the Alberta Ministry of Agriculture, Canadian Dairy Network, and the Ontario Ministry of Research and Innovation. Working with international partners in Australia, Switzerland, Denmark, the United Kingdom and the United States, Filippo is developing genetic solutions to improve feed efficiency and reduce methane gas emissions. His aim is to enhance the way dairy cows digest their feed while maximizing milk production, and reducing feed waste and methane emissions.
Nutritional value of milk
Filippo is analyzing fine components in milk using infrared technology. This data can also help predict the fatty acid profile of milk, which can potentially be optimized using selective breeding. This can also be achieved through dietary changes, but the modified feed must be given continuously to produce the desired effect, whereas genetic selection produces permanent and cumulative results. This project is funded by Dairy Farmers of Canada, Canadian Dairy Network, Canadian Dairy Commission, and Agriculture and Agri-food Canada.
Graduate Student Information
Filippo takes great pride in training the next generation of scientists and industry experts. His graduate students have the opportunity to work with industry partners. They also attend meetings of the Dairy Cattle Breeding Genetics Committee that brings together students, researchers, faculty and industry representatives. Filippo encourages his students to not only attend conferences but also present their research. Conferences provide his students with the opportunity to network with other students and researchers in their field and gain feedback on their work.
Filippo enjoys working with students individually and in teams, and pairs them with postdocs so they can learn from each other. One of the most rewarding aspects of being a graduate student supervisor is seeing his students’ confidence grow as they develop their skills.
- 100-Year Review: Identification and Genetic Selection of Economically Important Traits in Dairy Cattle. F Miglior, A Fleming, F Malchiodi, LF Brito, P Martin, CF Baes. 2017. Journal of dairy science 100 (12), 10251-10271 https://authors.elsevier.com/a/1W4x350bFHl2t
- Selection indices in Holstein cattle of various countries. F Miglior, BL Muir, BJ Van Doormaal. 2005. Journal of dairy science 88 (3), 1255-1263
- Genetic analysis of milk urea nitrogen and lactose and their relationships with other production traits in Canadian Holstein cattle. F Miglior, A Sewalem, J Jamrozik, J Bohmanova, DM Lefebvre, RK Moore. 2007. Journal of Dairy Science 90 (5), 2468-2479
- Prediction of milk fatty acid content with mid-infrared spectroscopy in Canadian dairy cattle using differently distributed model development sets. A Fleming, FS Schenkel, J Chen, F Malchiodi, V Bonfatti, RA Ali, B Mallard, F Miglior. 2017. Journal of Dairy Science 100 (6), 5073-5081
- Genetic parameters for hoof health traits estimated with linear and threshold models using alternative cohorts. F Malchiodi, A Koeck, S Mason, AM Christen, DF Kelton, FS Schenkel, F Miglior. 2017. Journal of Dairy Science 100 (4), 2828-2836
- Using genomics to enhance selection of novel traits in North American dairy cattle. JP Chesnais, TA Cooper, GR Wiggans, M Sargolzaei, JE Pryce, F Miglior. 2016. Journal of dairy science 99 (3), 2413-2427