Bolormaa et al., 2023. 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 63(10-11): 1113-1125
Pereira et al., 2023. Effects of additional gonadotropin-releasing hormone and prostaglandin F(2α) treatment to an estradiol/progesterone-based embryo transfer protocol for recipient lactating dairy cows. Journal of Dairy Science 106(2): 1414-1428
Kamalanathan et al., 2023. Genetic Analysis of Methane Emission Traits in Holstein Dairy Cattle. Animals 13(8): 1308
van Staaveren et al., 2023. Recording of calf health for potential use in breeding programs: A case study on calf respiratory illness and diarrhea. Canadian Journal of Animal Science 103(2): 192-203
Martin et al., 2022. Unravelling the genetics of non-random fertilization associated with gametic incompatibility. Scientific Reports 12: 22314
Rockett et al., 2022. 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
Campos et al., 2022. Estimation of Genetic Parameters of Heat Tolerance for Production Traits in Canadian Holsteins Cattle. Animals 12(24):3585
Bolormaa et al., 2022. Sharing of either phenotypes or genetic variants can increase the accuracy of genomic prediction of feed efficiency. Genetics Selection Evolution 54, 60
Shadpour et al. 2022. 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
Shadpour et al. 2022. 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
Alcantara et al. 2022. Machine learning classification of breeding protocol descriptions from Canadian Holsteins. Journal of Dairy Science 105(10): 8177-8188
Martin et al. 2022. 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
Madureira et al. 2022. Association between genomic daughter pregnancy rates and reproductive parameters in Holstein dairy cattle. Journal of Dairy Science 105(6): 5534-5543
Chen et al. 2022. 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(2022)
Campos et al. 2022. 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: 368-381
Madureira et al. 2021. Occurrence and greater intensity of estrus in recipient lactating dairy cows improve pregnancy per embryo transfer. Journal of Dairy Science 105(1): 877-888
Madureira et al. 2021. Plasma concentrations of progesterone in the preceding estrous cycle are associated with the intensity of estrus and fertility of Holstein cows. PlosOne 16(8): e0248453
Borchardt et al. 2021. Association of estrous expression detected by an automated activity monitoring system within 40 days in milk and reproductive performance of lactating Holstein cows. Journal of Dairy Science 104(8): 9195-9204.
Plenio et al. 2021. Application note: Validation of BovHEAT — An open-source analysis tool to process data from automated activity monitoring systems in dairy cattle for estrus detection. Computers and Electronics in Agriculture, 188:106323
Houlahan et al. 2021. Effects of Incorporating Dry Matter Intake and Residual Feed Intake into a Selection Index for Dairy Cattle Using Deterministic Modeling. Animals 11(4), 1157
Theses
Hoeksema, K. Residual Metabolizable Energy Intake, a Measure of Feed Efficiency in Preweaning Canadian Holstein Calves, and its Estimated Genetic Parameters. MSc thesis, May 2023, University of Guelph
Bongers, R. A genetic perspective on enzootic bovine leukosis resistance in Canadian Holstein cattle. MSc thesis, Jan 2023, University of Guelph
Rogers, K. Evaluating Consumer Behaviour, Attitudes and Emotions Surrounding Environmental Aspects of the Canadian Animal and Plant-based Dairy Industries. MSc Thesis, Nov 2022, University of Alberta
Bibek, D. Estimating Carbon Footprint and Environmentally Adjusted Productivity of Ontario Dairy Farms. MSc Thesis, Sept 2022, University of Guelph
Marques, J. The impact of plasma concentrations of progesterone during superovulation on estrous behaviour, and ovarian and early embryonic development in Holstein heifers. MSc Thesis, Aug 2022, University of British Columbia
Martin, AAA. Novel Approaches for the Genetic Improvement of Fertility and Reproduction in Dairy Cattle. PhD Thesis, Aug 2022, University of Guelph
Magalhães Alcantara, A. Applications of machine learning algorithms for the improvement of breeding programs in the dairy industry. PhD Thesis, Jun 2022, University of Guelph
Fong A. The Effect of Interleukin-10 Receptor Alpha on Bovine Mammary Epithelial Cells Infected with Mycobacterium avium subsp Paratuberculosis. MSc Thesis, Jan 2022, University of Guelph
Hyland E. Evaluating calf health recording and incidence of respiratory disease and diarrhea on Ontario dairy farms using producer recorded data. MSc Thesis, Jan 2022, University of Guelph
Kim J. Consumer preferences for the genomic selection for particular traits in breeding dairy cows in Canada. MSc Thesis, Sept 2021, University of Alberta
Houlahan K. Understanding the Genomic Architecture of Feed Efficiency and Implications of Selection for it in Dairy Cattle. PhD Thesis, Sept 2021, University of Guelph
The following papers were part of the Efficient Dairy Genome Project that formed a foundation for the current project
Richardson et al. 2020. Genetic parameters for methane emission traits in Australian dairy cows. J. Dairy Sci. 104, 539-549
Lam et al. 2020. Development and comparison of RNA-sequencing pipelines for more accurate SNP identification: practical example of functional SNP detection associated with feed efficiency in Nellore beef cattle. BMC Genomics 21: 703
Lam et al. 2020. Identification of functional candidate variants and genes for feed efficiency in Holstein and Jersey cattle breeds using RNA-sequencing. J. Dairy Sci. 104, 1928-1950
Hailemariam et al. 2020. Comparative analyses of enteric methane emissions, dry matter intake and milk somatic cell count in different residual feed intake categories of dairy cows. Can. J. Anim. Sci. 101(1)
Butty et al. 2020. High confidence copy number variants identified in Holstein dairy cattle from whole genome sequence and genotype array data. Sci. Rep. 10:8044
Brito et al. 2020. Invited review: Genetic mechanisms underlying feed utilization and implementation of genomic selection for improved feed efficiency in dairy cattle. Can. J. Anim. Sci. 100(4)
Seymour et al. 2020. The dynamic behavior of feed efficiency in primiparous dairy cattle. J. Dairy Sci. 103(2), 1528-1540
Worden et al. 2020. Do genomic innovations enable an economic and environmental win-win in dairy production? Agricultural Systems 181, 102807
Richardson et al. 2020. Determining the economic value of daily dry matter intake and associated methane emissions in dairy cattle. Animal 14(1), 171-179
Seymour et al. 2019. Invited review: Determination of large-scale individual dry matter intake phenotypes in dairy cattle. J. Dairy Sci. 102(9), 7655-7663
Butty et al. 2019. Optimizing Selection of the Reference Population for Genotype Imputation From Array to Sequence Variants. Front. Genet. 10
Soyeurt et al. 2019. Contribution of milk mid-infrared spectrum to improve the accuracy of test-day body weight predicted from stage, lactation number, month of test and milk yield. Livestock Science 227, 82-89
Kommadath et al. 2019. A large interactive visual database of copy number variants discovered in taurine cattle. GigaScience 8(6), giz073,
Boaitey et al. 2019. Environmentally friendly breeding, spatial heterogeneity and effective carbon offset design in beef cattle. Food Policy 84, 35-45
Bassi et al. 2019. “That’s the Way We’ve Always Done It”: A Social Practice Analysis of Farm Animal Welfare in Alberta. J Agric Environ Ethics 32, 335–354