Evaluation of a data-driven youngstock rearing quality system in Dutch dairy herds (2019-2022).

In recent years, the Netherlands exhibited an increased focus on improving youngstock rearing. Several data-driven tools were developed to assess and benchmark calf rearing practices based on key indicators, stimulate farmers to improve their youngstock rearing and reduce calf mortality. KalfOK is such a data-driven tool in which a farm-level overview with 15 indicators of youngstock rearing quality is communicated to participating farmers. In this study we assessed which farm characteristics are associated with A) a continuously high or low KalfOK score and B) frequent usage of KalfOK. Data from KalfOK and the identification and registration system were available for all participating herds over a period between 2019 and 2022 (Dataset A). Additionally, a sample of 324 dairy farmers, randomly selected from the entire Dutch dairy population (Dataset B), participated in a voluntary survey. Multivariable (logistic) regression models were used to A) identify differences in characteristics between farms with a continuously high- and farms with a continuously low KalfOK score and B) assess which farm characteristics were associated with frequent use of the KalfOK report. The results of analysis A showed multiple factors associated with having a low or high KalfOK score, including replacement rate, closed farming system, limited growth in herd size and the region where a farm was located. Sociological factors might also partly explain the difference between high and low scoring farms. Analysis B showed that approximately half of the surveyed farmers indicated that they do not frequently use their KalfOK overview in their calf rearing management. The KalfOK score of farmers who regularly use their KalfOK report was higher - and consequently better - compared to the KalfOK score of farmers who sometimes or never use KalfOK. Additionally, farmers using a milk robot and those discussing KalfOK regularly with their veterinarian, used KalfOK more often. Thirty four percent of the surveyed farmers made adjustments to their youngstock rearing management since the start of participation. The study's insights into patterns in KalfOK utilization and associations with farm characteristics provide valuable information for ongoing efforts to enhance calf rearing practices via the use of KalfOK. It is important to consider what is needed to convince farmers that do not use the KalfOK tool to frequently start using their KalfOK report. Future research incorporating sociological aspects can provide a more comprehensive understanding of other dynamics influencing calf rearing and contribute valuable insights for enhancing the effectiveness of programs like KalfOK in promoting calf health and welfare.

Carcass and efficiency metrics of beef cattle differ by whether the calf was born in a dairy or a beef herd.

Beef originates from the progeny of either dairy or beef dams. The objective of the present study was to identify contributing factors to the differences in the carcass merit of progeny from both dam types. This goal was achieved using slaughter records from 16,414 bucket-reared dairy animals (DXD), 5,407 bucket-reared dairy-beef animals (BXD), 42,102 suckle-reared animals from a beef × dairy F1 cross dam (BXF1), and 93,737 suckle-reared animals from a beef × beef cow (BXB). Linear mixed models were used to quantify the least squares means for carcass characteristics in the various progeny genotypes. Nuisance fixed effects adjusted for in the models were: animal heterosis and recombination loss, dam parity, age at slaughter, and contemporary group; age at slaughter was replaced as an independent variable with both carcass weight and carcass fat score where the dependent variable was age at slaughter. In a follow-up analysis, models were re-analyzed where the genetic merit of the sire was adjusted for; a further analysis set the genetic merit of the dam for the dependent variable to be identical for both the dairy and beef dams. The final analysis adjusted to a common sire and dam genetic merit facilitating the estimation of just differences in early-life rearing strategies. Irrespective of the genetic merit of the sire and dam, animals originating from beef herds had heavier and more conformed carcasses. BXB animals had a 67 kg heavier carcass, with a conformation score (scale 1 [poor] to 15 [excellent]) of 5 units greater compared with DXD animals. When the genetic merit of all dams was set to be equal, BXB animals were heavier and better conformed than BXD animals. When the genetic merit for both the sire and dam were set to be equal, carcasses of the BXB animals were 15 kg heavier, with a 0.69 unit superior conformation score compared with the DXD animals; this difference is due to early life experiences. In conclusion, the majority of the inferiority in carcass metrics of calves from dairy herds compared with beef herds is due to differences in the genetic merit of the parents. Nevertheless, even after adjusting the parents to the same genetic merit, progeny from dairy herds were still inferior to their contemporaries born in beef herds, due most likely to the persistence of early life experiences.

Development of an objective and uniform scoring method to evaluate the quality of rearing in Dutch dairy herds.

Young stock rearing is an essential part of dairy management, and it is important that the quality of rearing can be monitored and altered if necessary. In this study, a young stock rearing quality system (KalfOK) was developed with the aim to provide an objective and standardized means to evaluate and monitor the quality of young stock rearing in Dutch dairy herds. In the project, 201 dairy farmers participated. Twelve key indicators were defined that were related to calving and successful rearing, antimicrobial use, and herd health. For each of the key indicators, the value was calculated per herd and quarter of the year between January 2014 and April 2017. Benchmark values were determined to compare herd-specific results and for selection of threshold values. Each of the key indicators was graded when the value scored above the threshold. Combining the grades resulted in the herd-specific KalfOK score, which could vary between 0 and 100. Subsequently, 100 of the participating dairy herds were visited and the quality of young stock rearing was scored by a trained veterinarian. Using principal component analysis, the results of the herd health checks were combined into a factor score that represented the observed quality of young stock rearing during the visit. The amount of variance in observed quality of rearing during the herd health check that was explained by the key indicators in KalfOK was evaluated. Additionally, the validity of KalfOK to distinguish herds with an excellent or insufficient quality of young stock rearing was assessed by comparing the top and bottom 10% herds in the herd health check with the proportion of herds with a KalfOK score above or below a prespecified cutoff value. The results of the linear regression model showed that the key indicators included in KalfOK accounted for 56% of the variation in the score of the herd visits by a veterinarian. The moving average of the annual KalfOK score, which was the sum of the grades of all key indicators, was 77 points (25th percentile = 71, 75th percentile = 85 points). The combination of the sensitivity (88%, 95% confidence interval = 47-100%) and specificity (67%, 95% confidence interval = 54-78%) of KalfOK to correctly classify herds with an excellent quality of young stock rearing was highest when a cutoff value of 80 points was applied. Detection of dairy herds with an insufficient quality of young stock rearing was best at a cutoff value of 70 points (sensitivity 86%, 95% confidence interval = 42-100%; specificity 77%, 95% confidence interval = 66-86%). The KalfOK score that was based on routinely collected herd data provided an indication of the quality of young stock rearing in individual Dutch dairy farms. The KalfOK score illustrates how such data can be transferred into herd-specific information in support of animal health and welfare. Given the increasing availability of automatically assembled data, the development of similar monitoring tools seems a feasible option to enhance herd-specific management.