Flavio Schenkel Position/Title: CGIL Director, Professor - Animal Breeding, Genetics and Genomics email: [email protected] Phone: (519) 824-4120 ext. 58650 Office: ANNU 121 Personal Site Google Scholar Research Gate

Dr. Flavio Schenkel is a Full Professor in the Department of Animal Biosciences at University of Guelph, Canada, with research interests ranging from theoretical to applied genetics and genomics in livestock breeding. His current research focuses on the use of genomic information to enhance genetic evaluation of livestock species with emphasis on genomic selection and novel traits. Dr. Schenkel was a professor at a Federal University in Brazil from 1993 to 2000, and a Research Associate at University of Guelph from 2000 until he became an Assistant Professor in 2005. In 2009 Dr. Schenkel changed his status to an Associate Professor and in 2014 he became a Full Professor. Since 2006, Dr. Schenkel is a member of influential industry boards in Canada, including the DairyGen Council and the Dairy Cattle Genetic Evaluation Board of Lactanet. In 2013, Dr. Schenkel was appointed Director of the Centre for Genetic Improvement of Livestock at University of Guelph. In his scientific career, Dr. Schenkel published over 280 peer-reviewed scientific papers and has contributed to formation of numerous high qualified personnel, including the supervision of 28 graduate students and 21 post-doctoral fellows, and co-supervision of 39 graduate students. Dr. Schenkel also serves on several international journal editorial boards and maintains strong research collaboration with researchers in Brazil and USA, among other countries. Dr. Schenkel was awarded the prestigious Canadian Society of Animal Science Award in Technical Innovation in 2014, the American Dairy Science Association’s J.L. Lush Award in Animal Breeding in 2018, the University of Guelph’s Distinguished Researcher Award in 2018. More recently, Dr. Schenkel was one of the recipients of the 2023 University of Guelph Innovation of the Year Award and was awarded a University of Guelph Research Leadership Chair.

Dr. Schenkel is a faculty member of the Bioinformatics Program and a faculty affiliated to the One Health Program and the Dairy at Guelph Research Centre.

Dr. Schenkel is a former President of the Canadian Society of Animal Science.

               

 

Academic History

• Ph.D.   University of Guelph,  Guelph, Ontario,  Animal Breeding (Statistics and Quantitative Genetics minors),  1998
• M.Sc.   Federal University of Rio Grande do Sul,  Porto Alegre, Brazil,  Animal Breeding,  1991
• B.B.A.   Pontifical Catholic University of Rio Grande do Sul,  Porto Alegre, Brazil,  Business Administration,  1990
• B.Sc.   Federal University of Rio Grande do Sul,  Porto Alegre, Brazil,  Agronomy,  1987
• Other   Federal University of Rio Grande do Sul,  Porto Alegre, Brazil,  Specialization in Irrigation and Drainage,  1987

 

Affiliations and Partnerships

• Sigma Xi, The Scientific Research Honor Society, Research
• American Dairy Science Association
• American Society of Animal Science
• Canadian Society of Animal Science
• American Association for the Advancement of Science
• Brazilian Society of Animal Breeding

 

Awards and Honours       

2023:  University of Guelph Innovation of the Year Award.
2023:  University of Guelph Research Leadership Chair.
2018:  The ADSA J.L. Lush Award in Animal Breeding for outstanding research in the field of animal breeding.
2018:  The Ontario Agriculture College Alumni Distinguished Researcher Award, University of Guelph.
2014:  The CSAS Award in Technical Innovation in the Production of Safe and Affordable Food, Canadian Society of Animal Science.
1997:  Brian W. Kennedy Memorial Scholarship, Brian W. Kennedy Memorial.    
1997:  Ontario Graduate Scholarship, Ontario Ministry of Education.
1996:  Mary Edmunds Williams Scholarship, Mary Edmunds Williams.    
1995-1998:  Ph.D. Graduate Fellowship, Brazilian Federal Agency for Higher Studies (CAPES).   
1995:  Ontario Animal Breeders Scholarship, Ontario Animal Breeders.    
1994:  University of Guelph Graduate Scholarship, University of Guelph Graduate.    
1991:  Brossard award for achievements during undergraduate studies in Agronomy, Provincial Board of Education.    
1988-1991:  M.Sc. Graduate Scholarship, Brazilian National Council of Research (CNPq).

 

 

Research Impact

Dr. Schenkel’s research interests range from theoretical to applied genetics and genomics in livestock breeding. Current research focuses on the use of genomic information to enhance genetic evaluation of livestock species with emphasis on genomic selection. His research program has been supported by industry and governmental funds, including various funding agencies and expressive industry support funds. Dr. Schenkel has published over 198 peer-reviewed scientific papers. In Google Scholar, his h-index is currently 44 and the i10-index is 129 overall. In ResearchGate, his RG Score is 43.34.

Dr. Schenkel’s most significant research contributions while at the University of Guelph include:
- Pioneering research on genome-wide selection led to the implementation of the first official genomic evaluation in Holstein cattle in Canada by the Canadian Dairy Network (CND) in 2009. Along with USA, Canada was the first country in the world to officially implement genomic selection in dairy cattle.
- The genomic projects led to the creation of reference datasets of genotyped animals in all major Canadian dairy breeds, which facilitated the implementation of genomic selection in other smaller population-sized dairy breeds (Jersey, Brown Swiss and Ayrshire) and opened the opportunity for other genomic related research, such as fine mapping of QTL, genome-wide imputation, etc.
- Innovative research and development on genome-wide imputation from low to high density SNP panels with substantial impact on number of genotyped animals (especially cows) in the genomic evaluation in Canada. Imputation research contributed to implementation of genomic evaluation of dairy cattle with imputed genotypes in 2011 by the CDN.
- Several software applications were developed in recent years, which allowed for state of art research and development in genomics, such as QMSim (genome simulator software), Gebv (genomic breeding value prediction software), and FImpute (genome-wide imputation software), which have been used world-wide. Both Gebv and Fimpute are currently used in the routine genomic evaluations of dairy cattle in Canada by CDN.
- Investigation into the possible genetic background underlying the liability of Standardbred racehorses to atrial fibrillation (AF) strongly indicated a genetic predisposition to AF in the Standardbreds, with the arrhythmia particularly prevalent in one popular sire line. These findings will have substantial impact on the Canadian Standardbred racehorse industry and on future research efforts towards reducing the incidence of this arrhythmia.
- Development of national genetic evaluation for disease resistance, including mastitis and other 7 diseases (lameness, cystic ovarian disease, displaced abomasum, ketosis, metritis/uterine disease, milk fever and retained placenta). Routine genetic evaluation for mastitis resistance was implemented and for metabolic disorders is currently being implemented by CDN.

 

Main Research Projects (Current and Recent)

1. Integrating genomic approaches to improve dairy cattle resilience: A comprehensive goal to enhance Canadian dairy industry sustainability (Large scale applied research project competition- Genome Canada, Schenkel (Co-investigator), 2020 to 2024)

2. Increasing feed efficiency and reducing methane emissions through genomics: a new promising goal for the Canadian dairy industry (Large scale applied research project competition- Genome Canada, Schenkel (Co-applicant/Principle Investigator since January 2019), 2015 to 2021)

The overall goal of the project is to produce genomic predictions for Feed Efficiency (FE) and Methane Emissions (ME) that are ready for breeding application in Canada’s dairy cattle industry. These tools will enable producers to select cattle for improved FE and reduced ME, while still maintaining the high productivity, health and fertility of dairy cows.

3. Designing a reference population to accelerate genetic gains for novel traits in Canadian Holstein project (AAFC- Dairy cluster III Grant, Schenkel (Co-applicant/Principle Investigator since January 2019), 2018 to 2022)

The main objective of this project is to generate tools to maximize the rate of genetic progress for novel traits by designing an enlarged female reference population for genomic prediction of novel traits with ssGBLUP and to investigate the incorporation of additional “-omics” data in Canadian dairy cattle breeding programs.

4. Understanding the impact of cutting-edge genomic technologies and novel phenotypes on breeding strategies for optimum sustainable genetic progress in Canadian dairy cattle project (AAFC- Dairy cluster III Grant, Schenkel (Co-applicant), 2018 to 2022)

The development of novel traits (e.g. feed efficiency, methane emission, etc.), new genotyping technologies (e.g. genotyping by sequencing), and novel tools (e.g. gene editing) applied in the dairy industry is advancing at an unprecedented rate. Wide-spread application of these new technologies will fundamentally change the accuracy of breeding values and the selection strategies used for genetic evaluation of dairy cattle. While these novel traits, technologies and tools are expected to further increase accuracy of genetic evaluations, the medium and long-term effects of their implementation into routine breeding programs at a population level are largely unknown. There is a clear need to assess current and prospective breeding strategies, and to compare the benefits of various strategies and tools for genetic improvement and selection. Ideally, the use of these new technologies will help ensure sustainability, genetic diversity, and will help to further improve production efficiency. The objective of this proposal is to analyze and compare the benefits of various strategies and novel tools for breed improvement.

5. Breeding livestock for climate resilience: the capacity to maintain production and fitness in a changing climate (Canada First Research Excellence Fund, Schenkel (Principle investigator), 2017 to 2022)

This project is part of the CFREF Food from Thought - Agricultural Systems for a Healthy Planet project led by the University of Guelph.  The main goal of this project is to identify genes, as well as structural and regulatory regions of the genome of livestock species (with a focus on ruminant species such as beef and dairy cattle, sheep and goats), that are involved in adapting to different stressors triggered through climate change for allowing efficient selection for robust livestock tolerant to extreme temperatures and more productively efficient.        

6. Implementation of genomic selection to improve productivity and health traits in Ontario dairy goats (Gov-OMAFRA Agreement Research Programs, Schenkel (Principal Investigator), Ended)

The overarching objective of this project is to implement genomic selection in the dairy goat industry to promote faster genetic progress in production, conformation, reproduction and health traits in collaboration with Canadian Centre for Swine Improvement, leveraging from a previous genomic project. Specific objectives include increase the size of the reference population for the two major dairy goat breeds in Canada, named Alpine and Saanen; evaluate and validate prediction methods and corresponding genomic evaluation tools; achieve a better understanding of the genetic background of the traits of interest by estimating genetic parameters using genomic information and also performing GWAS studies; Increase the accuracies of genomic breeding values for various economically important traits by an increased reference population size and an optimized genomic evaluation model; transfer the genomic tools to Canadian Centre for Swine Improvement for the use by the dairy goat producers.

7. Genetic Improvement of Canadian Lamb Carcass Yield, Quality and Growth Traits (NSERC-CRD, Schenkel (Principal Investigator), Ended)

In the Canadian lamb industry, carcass yield and quality traits are of considerable importance because these relate directly supply chain production efficiency, economic profitability and consumer choice of domestic products. This study seeks to examine genetic bases of carcass yield, fat depth and conformation in commercial lambs, and consider genetic relationships with early growth, ultrasound measurements and other economically important production and reproduction traits. The goal is to find optimal selection methods to improve carcass yield, quality and growth in commercial lamb breeding programs. This will be accomplished by analysing carcass processing data that were recorded over at least 2.5 years from commercial lambs that are part of the Canadian Sheep Genetic Evaluation System (CSGES) hosted at CGIL.

8. Canada's ten thousand cow genomes project (AAFC- Dairy cluster II Grant, Schenkel (Principal Investigator), ended)

The general objective of the project is to increase the accuracy of genomic predictions by using additional knowledge from analyses conducted on a large genotyped cow population (Illumina 50k SNP panel) with high quality phenotypes, including some new traits of great interest (immune response, hoof health, feed efficiency and related traits, and milk spectral data), and imputed 777k genotypes and sequence SNP genotypes.

9. Development and testing of new methods for genomic evaluation in dairy cattle (AAFC- Dairy cluster II Grant, Schenkel (Principal Investigator), ended)

The main objective of this project is to improve the accuracy of genomic estimated breeding values (GEBV) for young bulls, heifers and cows by developing new genomic evaluation methods or testing promising ones. Over the next five years to achieve this will require prioritizing emerging methods based on their potential for increased predictive ability and their applicability to the Canadian context, and transfer the knowledge and results to CDN for national implementation.

10. Improving cow health and the nutraceutical value of milk with Infra-red technology (AAFC- Dairy cluster II Grant, Schenkel (Co-applicant), ended)

Milk laboratories quantify major milk components such as fat or protein using mid-infrared (MIR) spectrometry. These predictions are used for milk payment as well as for animal performance recording. Collecting MIR spectra is very efficient, and the data extracted from the spectra today is just a small portion of the whole information. The MIR spectrum is indeed a fingerprint of the whole milk composition; however, very little has been carried out so far to extract further information. The overall objective is to study the phenotypic and genetic variability of milk spectral data in order to improve cow robustness, nutritional quality of milk for human consumption and to develop a series of calibration equations for several milk components.

11. Computing hardware for big data editing, storage, and analysis . (NSERC- RESEARCH TOOLS AND INSTRUMENTS (RTI), Schenkel (Principal Investigator), ended)

The big data era of research has caused an avalanche of data that has buried the current computer storage and processing technology in the Department of Animal Biosciences at University of Guelph. This project will support the purchase of three high performance computer nodes, a storage server and a fabric network to integrate the new nodes and storage server to the computer nodes and storage currently available in the Department for interdisciplinary and collaborative research involving big data, a common feature of novel research in precision agriculture.

 

Graduate Student Information

As an advisor and teacher, Dr. Schenkel believes a professor should be a role model and a mentor, and enable each student to reach their individual potential. A good professor should teach students to be independent thinkers and responsible for their own learning and intellectual growth. If students learn something well, regardless of the discipline, they will be prepared to adapt to any circumstances and be productive members of society.

Currently Dr. Schenkel supervise or co-supervise the following graduate students, PDFs and research assistant:

 

Most Recent Publications

1. *Stephansen, Rasmus, Martin, Pauline, Manzanilla-Pech, Coralia, Gredler-Grandl, Birgit, Sahana, Goutam, Madsen, Per, . . . Lassen, Jan. (2023, December). Novel genetic parameters for genetic residual feed intake in dairy cattle using time series data from multiple parities and countries in North America and Europe. Journal of Dairy Science, 106(12), 9078-9094. doi:10.3168/jds.2023-23330 (Published)

2. Oliveira, Hinayah, Sweett, Hannah, Gunasegaram Narayana, Saranya, Fleming, Allison, Shadpour, Saeed, Malchiodi, Francesca, . . . Miglior, Filippo. (2023, December). Symposium Review: Development of genomic evaluation for methane efficiency in Canadian Holsteins. JDS Communications. (Accepted)

3. Alves, Kristen, Brito, Luiz F., Sargolzaei, Mehdi & Schenkel, Flavio S. (2023, November). Genome-wide association studies for epistatic genetic effects on fertility and reproduction traits in Holstein cattle. Journal of Animal Breeding and Genetics, 140(6), 624-637. doi:10.1111/jbg.12813 (Published)

4. Teissier, Marc, Brito, Luiz, Schenkel, Flavio, Bruni, Guido, Fresi, Pancrazio, Bapst, Beat, . . . Larroque, Helene. (2023, November). Genetic parameters for milk production and type traits in north American and European Alpine and Saanen dairy goat populations. JDS Communications. doi:10.3168/jdsc.2023-0389 (In Press)

5. *Sousa, Luis Paulo, Pinto, Luis Fernando, da Cruz, Valdecy Aparecida, Oliveira Jr, Gerson, Oliveira, Hinayah, Chud, Tatiane, . . . Brito, Luiz. (2023, November). Genome-wide association and functional genomic analyses for various hoof health traits in North American Holstein cattle. Journal of Dairy Science. doi:10.3168/jds.2023-23806 (In Press)

6. *Rockett, Paige, Campos, Ivan, Baes, Christine, Tulpan, Dan, Miglior, Filippo & Schenkel, Flavio. (2023, October). Genetic evaluation of heat tolerance in Holsteins using test-day production records and NASA POWER weather data. Journal of Dairy Science, 106(10), 6995-7007. doi:10.3168/jds.2022-22776 (Published)

7. Staaveren, Nienke van, Oliveira, Hinayah R. De, Houlahan, Kerry, Chud, Tatiane C. S., Oliveira Jr, Gerson A., Hailemariam, Dagnachew, . . . Baes, Christine F. (2023, September). The Resilient Dairy Genome Project – a general overview of methods and objectives related to feed efficiency and methane emissions. Journal of Dairy Science. doi:10.3168/jds.2022-22951 (Published)

8. Houlahan, Kerry, Schenkel, Flavio, Miglior, Filippo, Jamrozik, Janusz, Stephansen, Rasmus, González-Recio, Oscar, . . . Baes, Christine. (2023, September). Estimation of genetic parameters for feed efficiency traits using random regression models in dairy cattle. Journal of Dairy Science. doi:10.3168/jds.2022-23124 (Published)

9. Alves, Kristen, Brito, Luiz F. & Schenkel, Flavio S. (2023, September). Genomic prediction of fertility and calving traits in Holstein cattle based on models including epistatic genetic effects. Journal of Animal Breeding and Genetics, 140(5), 568-591. doi:10.1111/jbg.12810 (Published)

10. Freitas, Anielly P, Lima, Maria Lúcia P, Simili, Flávia F, Negrão, João A, Schenkel, Flavio S & Paz, Claudia Cristina P. (2023, September). Influence of handling in corrals on the temperament of different breeds of beef cattle raised in Brazil. Journal of Animal Science, 101. doi:10.1093/jas/skad300 (Published)

11. *Lynch C., Schenkel F. S., van Staaveren N., Miglior F., Kelton D. & Baes C. F. (2023, September). Investigating the potential for genetic selection of dairy calf disease traits using management data. Journal of Dairy Science. doi:10.3168/jds.2023-23780 (Published)

12. *Souza, Taiana, Pinto, Luis Fernando, da Cruz, Valdecy Aparecida, Oliveira, Hinayah, Pedrosa, Victor, Oliveira Jr, Gerson, . . . Brito, Luiz. (2023, August). A comprehensive characterization of longevity and culling reasons in Canadian Holstein cattle based on various systematic factors. Translational Animal Science, 7, txad102. doi:10.1093/tas/txad102 (Published)

13. Freitas, Anielly P, Lima, Maria Lúcia P, Simili, Flávia F, Schenkel, Flávio S, Faro, Lenira E, Santana, Mario L & Paz, Claudia Cristina P. (2023, August). Genetic parameters for behavioral and growth traits of Nellore cattle. Journal of Animal Science, 101. doi:10.1093/jas/skad280 (Published)

14. *Neustaeter, Anna, Brito, Luiz, Hanna, W. J. Brad, Baird, John D. & Schenkel, Flavio. (2023, July). Investigating the genetic background of Spastic Syndrome in North American Holstein cattle based on heritability, genome-wide association, and functional genomic analyses. Genes, 14(7), 1479. doi:10.3390/genes14071479 (Published)

15. *Id-Lahoucine, Samir, Casellas, Joaquim, Suárez-Vega, Aroa, Fonseca, Pablo A. S., Schenkel, Flavio S., Sargolzaei, Mehdi & Canovas, Angela. (2023, June). Unravelling transmission ratio distortion across the bovine genome: Identification of candidate regions for reproduction defects. BMC Genomics, 24(1), 383. doi:10.1186/s12864-023-09455-6 (Published)

16. Bolormaa, Sunduimijid, Haile-Mariam, Mekonnen, Marett, Leah C., Miglior, Filippo, Baes, Christine F., Schenkel, Flavio S., . . . Pryce, Jennie E. (2023, May). Use of dry-matter intake recorded at multiple time periods during lactation increases the accuracy of genomic prediction for dry-matter intake and residual feed intake in dairy cattle. Animal Production Science. doi:10.1071/AN23022 (Published)

17. *Kamalanathan, Stephanie, Houlahan, Kerry, Miglior, Filippo, Chud, Tatiane C.S., Seymour, Dave J., Hailemariam, Dagnachew, . . . Schenkel, Flavio S. (2023, April). Genetic analysis of methane emission traits in Holstein dairy cattle. Animals, 13(8), 1308. doi:10.3390/ani13081308 (Published)

18. *Id-Lahoucine, Samir, Casellas, Joaquim, Miglior, Filippo, Schenkel, Flavio S. & Cánovas, Angela. (2023, April). Parent-offspring genotyped trios unravelling genomic regions with gametic and genotypic epistatic transmission bias on the cattle genome. Frontiers in Genetics. doi:10.3389/fgene.2023.1132796 (Published)

19. van Staaveren, Nienke, Hyland, Emma, Houlahan, Kerry, Lynch, Colin, Miglior, Filippo, Kelton, David F., . . . Baes, Christine F. (2023, March). Recording of calf diseases for potential use in breeding programs: A case study on calf respiratory illness and diarrhea. Canadian Journal of Animal Science. doi:10.1139/cjas-2022-0112 (Published)

20. *Rockett, Page, Campos, Ivan, Baes, Christine, Miglior, Filippo, Tulpan, Dan & Schenkel, Flavio. (2022, December). Phenotypic analysis of heat stress in Holsteins using test-day production records and NASA POWER meteorological data. Journal of Dairy Science, 106(2), 1142-1158. doi:10.3168/jds.2022-22370 (Published)

21. *Martin, Audrey A.A., Id-Lahoucine, Samir, Fonseca, Pablo A.S., Rochus, Christina M., Alcantara, Lucas M., Tulpan, Dan, . . . Schenkel, Flavio S. (2022, December). Gametic incompatibility: Unravelling the genetics of non-random fertilization. Scientific reports, 12, 22314. doi:10.1038/s41598-022-26910-8 (Published)

22. *Id-Lahoucine, Samir, Casellas, Joaquim, Fonseca, Pablo A. S., Suarez-Vega, Aroa, Schenkel, Flavio & Cánovas, Angela. (2022, December). Deviations from Mendelian inheritance on bovine X-chromosome revealing recombination, sex-of-offspring effects and fertility-related candidate genes. Genes, 13(12), 2322. doi:10.3390/genes13122322 (Published)

23. *Campos, Ivan Lange de, Chud, Tatiane C. S., Junior, Gerson A. O., Baes, Christine F., Cánovas, Ángela & Schenkel, Flavio Schramm. (2022, December). Estimation of Genetic Parameters of Heat Tolerance for production traits in Canadian Holsteins cattle. Animals, 12(4), 3585. doi:10.3390/ani12243585 (Published)

24. *Massender, Erin, Oliveira, Hinayah R., Brito, Luiz F., Maignel, Laurence, Jafarikia, Mohsen, Baes, Christine F., . . . Schenkel, Flavio S. (2022, December). Genome-wide association study for milk production and conformation traits in Canadian Alpine and Saanen dairy goats. Journal of Dairy Science, 106(2), 1168-1189. doi:10.3168/jds.2022-22223 (Published)

25. *Gunasegaram Narayana, Saranya, de Jong, Ellen, Schenkel, Flavio, Fonseca, Pablo, Chud, Tatiane, Powell, Diana, . . . Barkema, Herman. (2022, November). Underlying genetic architecture of resistance to mastitis in dairy cattle: A systematic review and gene prioritization analysis of genome-wide association studies. Journal of Dairy Science, 106(1), 323-351. doi:10.3168/jds.2022-21923 (Published)

26. *Dou, Jinhuan, Sammad, Abdul, Cánovas, Angela, Schenkel, Flavio, Muniz, Maria Malane MagalhãesSammad, Abdul, Usman, Tahir, . . . Wang, Yachun. (2022, November). Identification of Novel mRNA Isoforms Associated with Acute Heat Stress Response Using RNA Sequencing Data in Sprague Dawley Rats. Biology, 11(12), 1740. doi:10.3390/biology11121740 (Published)

27. Shadpour, Saeed, Chud, Tatiane C. S., Hailemariam, Dagnachew, Oliveira, Hinayah R., Plastow, Graham, Stothard, Paul, . . . Schenkel, Flavio S. (2022, October). Predicting dry matter intake in Canadian Holstein dairy cattle using milk mid-infrared reflectance spectroscopy and other commonly available predictors via artificial neural networks. Journal of Dairy Science, 105(10), 8257-8271. doi:10.3168/jds.2021-21297 (Published)

28. *Alcantara, L.M., Schenkel, F.S., Lynch, C., Oliveira Junior, G.A., Baes, C.F. & Tulpan, D. (2022, October). Machine learning classification of hormonal synchronization protocols for Canadian Holsteins cows. Journal do Dairy Science, 105(10), 8177-8188. doi:10.3168/jds.2021-21663 (Published)

29. *Martin, Audrey A.A., de Oliveira Jr, Gerson, Madureira, Augusto M.L., Miglior, Filippo, LeBlanc, Stephen J., Cerri, Ronaldo L. A., . . . Schenkel, Flavio S. (2022, October). Reproductive tract size and position score: Estimation of genetic parameters for a novel fertility trait in dairy cows. Journal of Dairy Science, 105(10), 8189-8198. doi:10.3168/jds.2021-21651 (Published)

30. Shadpour, Saeed, Chud, Tatiane C. S, Hailemariam, Dagnachew, Plastow, Graham, Oliveira, Hinayah R., Stothard, Paul, . . . Schenkel, Flavio S. (2022, October). Predicting methane emission in Canadian Holstein dairy cattle using milk mid-infrared reflectance spectroscopy and other commonly available predictors via artificial neural networks. Journal of Dairy Science, 105(10), 8272-8285. doi:10.3168/jds.2021-21176 (Published)

31. Berton, Mariana Piatto, Pereira da Silva, Rosiane, Banchero, Georgget, Barreto Mourão, Gerson, Sterman Ferraz, Jose Bento, Schramm Schenkel, Flavio & Baldi, Fernando. (2022, September). Genomic integration to identify molecular biomarkers associated with indicator traits of gastrointestinal nematode resistance in sheep. Journal of Animal Breeding and Genetics, 139(5), 502-516. doi:10.1111/jbg.12682 (Published)

32. Bolormaa, Sunduimijid, MacLeod, Iona M., Khansefid, Majid, Marett, Leah C., Wales, William J., Miglior, Filippo, . . . Pryce, Jennie E. (2022, September). Sharing of either phenotypes or genetic variants can increase the accuracy of genomic prediction of feed efficiency. Genetics Selection Evolution, 54, 60. doi:10.1186/s12711-022-00749-z (Published)

33. *Dou, Jinhuan, Luo, Hanpeng, Sammad, Abdul, Lou, Wenqi, Wang, Di, Schenkel, Flavio, . . . Wang, Yachun. (2022, August). Epigenomics of rats' liver and its cross-species functional annotation reveals key regulatory genes underlying short term heat-stress response. Genomics. doi:10.1016/j.ygeno.2022.110449 (In Press)

34. *Campos, I. L., Chud, T. C. S, Oliveira, H. R., Baes, C. F., Cánovas, A. & Schenkel, F. S. (2022, June). Using publicly available weather station data to investigate the effects of heat stress on milk production traits in Canadian Holstein cattle. Canadian Journal of Animal Science, 102(2), 368–381. doi:10.1139/cjas-2021-0088 (Published)

35. *Massender, Erin, Brito, Luiz, Maignel, Laurence, Oliveira, Hinayah, Jafarikia, Mohsen, Baes, Christine, . . . Schenkel, Flavio. (2022, May). Single- and Multiple-Breed Genomic Evaluations for Conformation Traits in Canadian Alpine and Saanen Dairy Goats. Journal of Dairy Science, 105(7), 5985-6000. doi:10.3168/jds.2021-21713 (In Press)

36. Teissier, Marc, Brito, Luiz, Schenkel, Flavio, Bruni, Guido, Fresi, Pancrazio, Robert-Granie, Christèle & Larroque, Hélène. (2022, May). Genetic Characterization and Population Connectedness of North American and European Dairy Goats. Frontiers in Genetics. doi:10.3389/fgene.2022.862838 (In Press)

37. *Alcantara, Lucas M., Baes, Christine F., de Oliveira Junior, Gerson A. & Schenkel, Flavio S. (2022, May). Conformation traits of Holstein cows and their association with a Canadian economic selection index. Canadian Journal of Animal Science. doi:10.1139/cjas-2022-0013 (Published)

38. Chen, Shi-Yi, Schenkel, Flavio S., Melo, Ana L. P., Oliveira, Hinayah R., Pedrosa, Victor B., Araujo, Andre C., . . . Brito, Luiz F. (2022, April). Identifying pleiotropic variants and candidate genes for fertility and reproduction traits in Holstein cattle via association studies based on imputed whole genome sequence genotypes. BMC Genomics, 23, 331. doi:10.1186/s12864-022-08555-z (Published)

39. *Seymour, Dave, Cant, John P., Osborne, Vern R., Chud, Tatiane C. S., Schenkel, Flavio S. & Miglior, Filippo. (2022, April). A novel method of estimating 24-h corrected milk yields in automated milking systems. Animal - Open Space, 1(1), 100011. doi:10.1016/j.anopes.2022.100011 (Published)

40. *Massender, E, Brito, L, Maignel, L, Oliveira, H, Jafarikia, M, Baes, Christine, . . . Schenkel, Flavio. (2022, March). Single-Step Genomic Evaluation for Milk Production Traits in Canadian Alpine and Saanen Dairy Goats. Journal of Dairy Science, 105(3), 2393-2407. doi:10.3168/jds.2021-20558 (Published)

41. Liu, Rui, Hailemariam, Dagnachew, Yang, Tianfu, Miglior, Filippo, Schenkel, Flavio, Wang, Zhiquan, . . . Plastow, Graham. (2022, March). Predicting enteric methane emission in lactating Holsteins based on reference methane data collected by the GreenFeed system. Animals, 16(3), 100469. doi:10.1016/j.animal.2022.100469 (Published)

42. Araujo, A C, Carneiro, P L, Oliveira, H R, Schenkel, F, Veroneze, R & Daniela A L Lourenco, Luiz F Brito. (2022). A comprehensive comparison of haplotype-based single-step genomic predictions in livestock populations with different genetic diversity levels: a simulation study. Frontiers in Genetics, 12. doi:10.3389/fgene.2021.729867 (Published)

43. Fonseca, P, Schenkel, F & Canovas, A. (2022, January). Genome-wide association study using haplotype libraries and repeated measures model to identify candidate genomic regions for stillbirth in Holstein cattle. Journal of Dairy Science. doi:10.3168/jds.2021-20936 (Published)

44. Bolormaa, S, MacLeod, I, Khansefid, M, Marett, L, Wales, W, Nieuwhof, Gert, . . . Pryce, Jennie. (2022). Evaluation of updated Feed Saved breeding values developed in Australian Holstein dairy cattle. JDS Communications. doi:10.3168/jdsc.2021-0150 (In Press)

 

►  For a full list of publications, please visit Dr. Schenkel's Google Scholar page

 

►  Dr. Schenkel's Animal Breeders Pedigree

 

►  Dr. Schenkel's Education and Academic Timeline