A dairy cow's lifetime resilience and her ability to recalve gain importance on dairy farms, as they affect all aspects of the sustainability of the dairy industry. Many modern farms today have milk meters and activity sensors that accurately measure yield and activity at a high frequency for monitoring purposes. We hypothesized that these same sensors can be used for precision phenotyping of complex traits such as lifetime resilience or productive life span. The objective of this study was to investigate whether lifetime resilience and productive life span of dairy cows can be predicted using sensor-derived proxies of first-parity sensor data. We used a data set from 27 Belgian and British dairy farms with an automated milking system containing at least 5 yr of successive measurements. All of these farms had milk meter data available, and 13 of these farms were also equipped with activity sensors. This subset was used to investigate the added value of activity meters to improve the model's prediction accuracy. To rank cows for lifetime resilience, a score was attributed to each cow based on her number of calvings, her 305-d milk yield, her age at first calving, her calving intervals, and the DIM at the moment of culling, taking her entire lifetime into account. Next, this lifetime resilience score was used to rank the cows within their herd, resulting in a lifetime resilience ranking. Based on this ranking, cows were classified in a low (last third), moderate (middle third), or high (first third) resilience category within farm. In total, 45 biologically sound sensor features were defined from the time series data, including measures of variability, lactation curve shape, milk yield perturbations, activity spikes indicating es-trous events, and activity dynamics representing health events (e.g., drops in daily activity). These features, calculated on first-lactation data, were used to predict the lifetime resilience rank and, thus, to predict the classification within the herd (low, moderate, or high). Using a specific linear regression model progressively including features stepwise selected at farm level (cutoff P-value of 0.2), classification performances were between 35.9 and 70.0% (46.7 ± 8.0, mean ± SD) for milk yield features only, and between 46.7 and 84.0% (55.5 ± 12.1, mean ± SD) for lactation and activity features together. This is, respectively, 13.7 and 22.2% higher than what random classification would give. Moreover, using these individual farm models, only 3.5 and 2.3% of cows were classified high when they were actually low, or vice versa, whereas respectively 91.8 and 94.1% of wrongly classified animals were predicted in an adjacent category. The sensor features retained in the prediction equation of the individual farms differed across farms, which demonstrates the variability in culling and management strategies across farms and within farms over time. This lack of a common model structure across farms suggests the need to consider local (and evidence-based) culling management rules when deve...

A blinded, negative controlled, randomized intervention study was undertaken to test the hypothesis that addition of meloxicam, a nonsteroidal anti-inflammatory drug, to antimicrobial treatment of mild to moderate clinical mastitis would improve fertility and reduce the risk of removal from the herd. Cows (n=509) from 61 herds in 8 regions (sites) in 6 European countries were enrolled. Following herd-owner diagnosis of mild to moderate clinical mastitis within the first 120 d of lactation in a single gland, the rectal temperature, milk appearance, and California Mastitis Test score were assessed. Cows were randomly assigned within each site to be treated either with meloxicam or a placebo (control). All cows were additionally treated with 1 to 4 intramammary infusions of cephalexin and kanamycin at 24-h intervals. Prior to treatment and at 14 and 21 d posttreatment, milk samples were collected for bacteriology and somatic cell count. Cows were bred by artificial insemination and pregnancy status was subsequently defined. General estimating equations were used to determine the effect of treatment (meloxicam versus control) on bacteriological cure, somatic cell count, the probability of being inseminated by 21 d after the voluntary waiting period, the probability of conception to first artificial insemination, the number of artificial insemination/conception, the probability of pregnancy by 120 or 200 d postcalving, and the risk of removal by 300 d after treatment. Cox's proportional hazards models were used to test the effect of treatment on the calving to first insemination and calving to conception intervals. Groups did not differ in terms of age, clot score, California Mastitis Test score, rectal temperature, number of antimicrobial treatments given or bacteria present at the time of enrollment, but cows treated with meloxicam had greater days in milk at enrollment. Cows treated with meloxicam had a higher bacteriological cure proportion than those treated with the placebo [0.66 (standard error=0.04) versus 0.50 (standard error=0.06), respectively], although the proportion of glands from which no bacteria were isolated posttreatment did not differ between groups. No difference was observed in the somatic cell count between groups pre- or posttreatment. The proportion of cows that underwent artificial insemination by 21 d after the voluntary waiting period was unaffected by treatment. Treatment with meloxicam was associated with a higher proportion of cows conceiving to their first artificial insemination (0.31 versus 0.21), and a higher proportion of meloxicam-treated cows were pregnant by 120 d after calving (0.40 versus 0.31). The number of artificial inseminations required to achieve conception was lower in the meloxicam compared with control cows (2.43 versus 2.92). No difference was observed between groups in the proportion of cows pregnant by 200 d after calving or in the proportion of cows that were culled, died, or sold by 300 d after calving (17% versus 21% for meloxicam versus control, respectively). ...

Milk yield dynamics during perturbations reflect how cows respond to challenges. This study investigated the characteristics of 62,406 perturbations from 16,604 lactation curves of dairy cows milked with an automated milking system at 50 Belgian, Dutch, and English farms. The unperturbed lactation curve representing the theoretical milk yield dynamics was estimated with an iterative procedure fitting a model on the daily milk yield data that was not part of a perturbation. Perturbations were defined as periods of at least 5 d of negative residuals having at least 1 day that the total daily milk production was below 80% of the estimated unperturbed lactation curve. Every perturbation was characterized and split in a development and a recovery phase. Based hereon, we calculated both the characteristics of the perturbation as a whole, and the duration, slopes, and milk losses in the phases separately. A 2-way ANOVA followed by a pairwise comparison of group means was carried out to detect differences between these characteristics in different lactation stages (early, mid-early, mid-late, and late) and parities (first, second, and third or higher). On average, 3.8 ± 1.9 (mean ± standard deviation) perturbations were detected per lactation in the first 305 d after calving, corresponding to an estimated 92.1 ± 135.8 kg of milk loss. Only 1% of the lactations had no perturbations. On average, 2.3 kg of milk was lost per day in the development phase, while the recovery phase corresponded to an average increase in milk production of 1.5 kg/d, and these phases lasted an average of 10.1 and 11.6 d, respectively. Perturbation characteristics were significantly different across parity and lactation stage groups, and early and mid-early perturbations in higher parities were found to be more severe with faster development rates, slower recovery rates, and higher milk losses. The method to characterize perturbations can be used for precision phenotyping purposes that look into the response of cows to challenges or that monitor applications (e.g., to evaluate the development and recovery of diseases and how these are affected by preventive actions or treatments).

In the first of a series of feature articles in Veterinary Record discussing the state of different sectors of the veterinary profession in the UK and what the future might hold, Jonathan Statham and Martin Green give their perspective on developments affecting the provision of cattle veterinary services.

. (2015) Reduction in daily milk yield associated with sub-clinical bovine herpes virus 1 infection. Veterinary Record, 177 (13 A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription.