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Calf diseases remain a challenge for dairy producers from both an economic and welfare perspective. Genetically selecting for disease resistance in calves is a promising approach that could contribute to sustainable dairy farming. Genetic evaluations, however, require well-defined and consistently recorded phenotypes to be successful. Therefore, this study aimed to understand the current state of calf disease recording on Ontario farms. Calf disease records of respiratory illness and diarrhea were available from the national milk recording organization (Lactanet Canada, Guelph, Ontario, Canada) from 2009 to 2020. A case study was conducted to describe calf disease diagnoses and recording practices by surveying a subset of 13 Ontario dairy producers. The percentage of milk recorded farms that recorded calf respiratory illness and calf diarrhea increased from 2.6% in 2009 to 11.1% in 2020. Potential sources of data loss were identified along the information chain from farm to genetic evaluation database. Clear definitions and thresholds to diagnose calf disease, standard operating procedures for data recording, as well as a data transfer pipeline, which includes exchange formats, are needed to facilitate the inclusion of calf health traits in genetic evaluations.

Recent issues in the dairy industry related to both animal and public health concerns are leading farmers away from the use of drugs, while placing more focus on animal health and welfare. Public demands are also shifting towards ensuring socially acceptable production practices in terms of good animal health and welfare. Such challenges are moving the focus in dairying from solely financial to a broader set of themes that, once addressed, will enhance the sustainability of dairying and provide a long-term competitive advantage for the Canadian industry. Furthermore, from a production standpoint, calf diseases, such as, diarrhea and respiratory disease (RD) have been associated with decreased first lactation production and growth rate, therefore decreasing an animal’s potential lifetime profitability. As part of a larger project aiming to add calf health traits to genetic evaluations in Canadian dairy cattle, this study provides the groundwork through the estimation of genetic parameters of two calf health traits, diarrhea and RD. Data were provided by Lactanet Canada, and included 20,594 calf records for diarrhea from 741 herds, and 48,927 calf records for RD from 1,412 herds, recorded between 2004 and 2021 across Canada. Total herd records ranged between 1 and 3,860 for RD with an average of 37 records per herd, while for diarrhea records ranged between 1 and 3,724 with an average of 28 records per herd. The results of this study will be used to optimally fit both diarrhea resistance and RD resistance into a novel resiliency index for use in national genetic evaluations in Canada.

Genetic improvement is a crucial tool to deal with the increasing demand for high quality, sustainably produced dairy. Breeding programs are based on genetic parameters, such as heritability and genetic correlations, for economically important traits in a population. In this study, we estimated population genetic parameters and genetic trends for 67 traits evaluated on heifers and first-lactation Canadian Holstein cows. The data consisted of approximately 500,000 records with pedigree information collected from 1980 to 2019. Genetic parameters were estimated using bivariate linear animal models under a Bayesian approach. Analyses for the 67 traits resulted in 2,211 bivariate combinations, from which the estimated genetic parameters are reported here. The most highly heritable traits were fat percent (0.66) and protein percent (0.69), followed by stature (0.47). Lowest heritabilities (0.01) were observed for disease-related traits, such as lameness and toe ulcer, and calf survival. The genetic correlations between gestation length, calf size, and calving ease measured on both heifer and cows were close to unity. On the other hand, traits such as body condition score and pin width, cystic ovaries and sole ulcer, rear teat placement, and toe ulcer were genetically unrelated. This study reports genetic parameters that have not been previously published for Canadian Holstein cows, and provides updates of those previously estimated. These estimates are useful for building new indexes, updating existing selection indexes, and for predicting correlated responses due to inclusion of novel traits in the breeding programs.

Estrus detection has become more difficult over the years due to decreases in the estrus expression of high-producing dairy cows, and increased herd sizes and animal density. Through the use of hormonal synchronization protocols, also known as timed artificial insemination (TAI) protocols, it is possible to alleviate some of the challenges associated with estrus detection. However, TAI masks cows' fertility performance, resulting in an unfair comparison of treated animals and innately fertile animals. Consequently, genetically inferior and superior cows show similar phenotypes, making it difficult to distinguish between them. As genetic programs rely on the collection of accurate phenotypic data, phenotypes collected on treated animals likely add bias to genetic evaluations. In this study, to assess the effect of TAI, the rank correlation of bulls for a given trait using only TAI records were compared with the same trait using only heat detection records. A total of 270,434 records from 192,539 animals split across heifers, first and second parity cows were analyzed for the traits: calving to first service, first service to conception, and days open. Results showed large reranking across all traits and parities between bulls compared based on either having only TAI records or only heat detection records, suggesting that a bias does indeed exist. Large reranking was also observed for both the heat detection and TAI groups among the top 100 bulls in the control group, which included all records. Furthermore, breeding method was added to the model to assess its effect on bull ranking. However, there were only minor changes in the rank correlations between scenario groups. Therefore, more complex methods to account for the apparent bias created by TAI should be investigated; for this, the method by which these data are collected needs to be improved through creating a standardized way of recording breeding codes. Though the results of this study suggest the presence of bias within current fertility evaluations, additional research is required to confirm the findings of this study, including looking at high-reliability bulls specifically, to determine if the levels of reranking remain. Future studies should also aim to understand the potential genetic differences between the fertility traits split via management technology, possibly in a multiple-trait analysis.

Fertility performance success on dairy farms starts with estrus detection, especially for artificial insemination programs. Detection of estrus has become more difficult over the years due to a decrease in estrus expression in high-producing dairy cows, with up to 60% of ovulations accompanied by no standing mount. In order to alleviate the pressure of estrus detection, management technologies have been developed, including automated detectors of standing heat, activity monitors, automated in-line systems measuring milk progesterone, and hormonal synchronization protocols (FTAI). To gauge the effectiveness of such technologies, records from 647,940 cows across 1,166 herds over the past ten years (total of 3,466,593 breeding records) from herd management software were analyzed. Across all herds, there were 5,804 breeding protocols, of which 2,046 were unique. Due to the wide range of breeding protocols, records were classified as HORMONES, FTAI, HEAT DETECTION and OTHERS. Breeding protocols were classified as HORMONES if they included any hormone treatment. FTAI was a stricter subset of HORMONES, which included only clear FTAI protocols. Protocols were classified as HEAT DETECTION if they were a clear heat detection protocol, with all remaining protocols classified as OTHERS. These classifications resulted in 3,258 protocols classified as HORMONES, of which 2,002 were FTAI, while a further 1,840 were classified as HEAT DETECTION. The remaining 706 codes were classified as OTHER and removed from this study. These classifications provided an initial overview of breeding methods conception rates, with results indicating significant differences (P < 0.05) between all protocol groups, as outlined in Table 1. Further analysis will be completed to indicate conception rates from the most commonly used breeding protocols across each of the protocol groups within the 1,192 herds. This work will help provide a better understanding of the expected conception rate of various management technologies on commercial farms.