Cow-level prevalence and risk factors for estrus detection inaccuracy in seasonal calving pasture-based dairy cows

The generation interval and season of birth do not affect age at first calving, birth weight and calving interval of Mozambican Angoni cattle

The Angoni cattle breed's contribution to the country's economy is crucial, as it significantly contributes to animal draught power and meat supply, despite not being primarily used for milk production. Despite its importance, there is a lack of comprehensive research conducted to characterize this breed. This study aimed to investigate the impact of the generation interval (GI) and season of birth (SB) on key reproductive parameters, including age at first calving (AFC), birth weight (BW), and calving interval (CI) in angoni cattle. Data sourced from the Angónia Research Station (ARS) included records for 425 heifers' AFC, 1684 calves' BW, and 1272 cows' CI. The study calculated overall averages and explored the relationships between generation intervals, the season of birth, and the aforementioned reproductive traits. The mean values for AFC, BW, and CI were determined as 1475.40 days, 18.49 kg, and 634.62 days, respectively. The analysis revealed that both generation interval and season of birth exhibited weak relationships, and their influence did not yield significant effects on the reproductive traits under investigation (P > 0.05). The observed variability ranged from 0.37 to 0.46% for AFC, 0.10-0.01% for BW, and 0.11-0.26% for CI. In conclusion, this study determined that neither generation interval nor birth season significantly affected the age at first calving, birth weight, or calving interval in Angoni cattle.

Relationship between Milk Yield and Reproductive Parameters on Three Hungarian Dairy Farms

It is postulated that there is negative correlation between milk yield and reproductive performance. However, some studies definitely doubt this causality. The aim of our study was to investigate the relationship between milk production and fertility on three dairy farms. The production parameter was the milk yield (in kg), and fertility was expressed by the number of inseminations per conception (AI index), as well as by the length of the service period (in days). A total of 13 012 lactations from cows with their first three lactations completed were analysed. The number of inseminations was significantly correlated with the milk yield and with the studied farm (p < 0.0001), but its correlation with the lactation number was not significant (p = 0.9477). A similar relationship was found after evaluating the length of the service period. A multiplicative model showed that a 2000 kg milk increase extended the service period by 9% and increased the AI index by 13%. Thereafter, using quartiles of the cows, the service period of the highest-producing group rose by 41.5 days, and the AI index by almost 1, compared to the lowest quartile. Our results indicate a definitive decline in reproductive indicators parallel to an increase in milk production but did not prove an inevitable correlation.

Estimation of the true prevalence of inaccurate artificial inseminations in Irish milk recording dairy cows using a Bayesian latent class analysis

Inaccurate artificial insemination (IAI) refers to an artificial insemination (AI) that is performed when a cow is not in oestrus. IAIs have economic impacts on the dairy industry through of semen wastage or iatrogenic pregnancy loss. However, few studies have quantified the prevalence of IAIs in a population. The primary objective of this prospective study was to estimate the cow-level true prevalence of IAIs in Irish milk recording dairy herds using a latent class model with a Bayesian framework. Milk samples were collected at a milk recording laboratory from 576 dairy cows in 125 herds who had received an AI on the same day they were sampled for routine milk constituent analysis. Milk progesterone (MP4) analysis was conducted on these samples using radioimmunoassay to determine the progesterone concentration. Fertility data (i.e., subsequent calving date) was retrospectively obtained from the Irish National Cattle Breeding Federation for milk sampled cows and an apparent conception (AC) to the sample AI was determined based on an estimated gestational range of 270-290 days. Both tests (MP4 and AC) were used in a latent class model to estimate the true prevalence of IAI. For the MP4 test, a concentration of ≥ 5 ng/mL in whole milk was deemed to be test positive while for the AC test, a cow that did not conceive to the sampled AI was deemed test positive. Prior information for prevalence of IAI was obtained from a literature review while MP4 sensitivity (Se) and specificity (Sp) were obtained from expert opinion. Non-informative priors were used for the Se and Sp of the AC test. Posterior inferences (median and 95 % Bayesian probability intervals; BPI) were obtained using the 'rjags' package in the R statistical software. In the final model, median cow-level true prevalence of IAI was 4.4 % (BPI; 1.7-9.0 %). Median Se and Sp estimates for MP4, were 83.0 % (BPI; 65.0-96.2 %) and were 97.4 % (BPI; 94.6-99.6 %), respectively. Median Se and Sp estimates for AC, were 64.8 % (BPI; 44.5-88.6 %) and 49.8 % (BPI; 45.3-54.1 %), respectively. The present study estimates that the overall cow-level true prevalence of IAI in Irish dairy cows is relatively low. This is the first study to report the cow-level true prevalence of IAI using a Bayesian latent class model.