To document and quantify drug use in white veal calves, an intensive livestock production system where multidrug resistance is abundantly present. Drug consumption data were prospectively collected on 15 white veal production cohorts (n = 5853 calves) in Belgium (2007–09). Treatment incidences (TIs) based on animal defined daily dose (ADD), prescribed daily dose (PDD) and used daily dose (UDD) were calculated. Risk factors were identified by linear regression. The average TI_ADD of antimicrobial treatments was 416.8 ADD per 1000 animals at risk. Predominantly, oral group antimicrobial treatments were used (95.8%). Of the oral group antimicrobial treatments, 12% and 88% were used for prophylactic or metaphylactic indications, respectively. The main indication for group and individual drug use was respiratory disease. The most frequently used antimicrobials (group treatments) were oxytetracycline (23.7%), amoxicillin (18.5%), tylosin (17.2%) and colistin (15.2%). Deviations from the leaflet dosage recommendations were frequently encountered, with 43.7% of the group treatments underdosed (often oxytetracycline and tylosin to treat dysbacteriosis). In 33.3% of the oral antimicrobial group treatments a combination of two antimicrobial preparations was used. Smaller integrations used more antimicrobials in group treatments than larger ones (P < 0.05); an integration is defined as a company that combines all steps of the production chain by having its own feed plant and slaughterhouse and by placing its calves in veal herds owned by producers that fatten these calves for this integration on contract. Producers used higher dosages than prescribed by the veterinarian in cohorts with a single caretaker (P < 0.01). The present study provided detailed information on the intensive antimicrobial use in the white veal industry. Reduction can only be achieved by reducing the number of oral group treatments.

Mortality and morbidity are hardly documented in the white veal industry, despite high levels of antimicrobial drug use and resistance. The objective of the present study was to determine the causes and epidemiology of morbidity and mortality in dairy, beef and crossbred white veal production. A total of 5853 calves, housed in 15 production cohorts, were followed during one production cycle. Causes of mortality were determined by necropsy. Morbidity was daily recorded by the producers.

Drivers of change in dairy herd health management include the significant increase in herd/farm size, quota removal (within Europe) and the increase in technologies to aid in dairy cow reproductive management. There are a number of key areas for improving fertility management these include: i) handling of substantial volumes of data, ii) genetic selection (including improved phenotypes for use in breeding programmes), iii) nutritional management (including transition cow management), iv) control of infectious disease, v) reproductive management (and automated systems to improve reproductive management), vi) ovulation / oestrous synchronisation, vii) rapid diagnostics of reproductive status, and viii) management of male fertility. This review covers the current status and future outlook of many of these key factors that contribute to dairy cow herd health and reproductive performance. In addition to improvements in genetic trends for fertility, numerous other future developments are likely in the near future. These include: i) development of new and novel fertility phenotypes that may be measurable in milk; ii) specific fertility genomic markers; iii) earlier and rapid pregnancy detection; iv) increased use of activity monitors; v) improved breeding protocols; vi) automated inline sensors for relevant phenotypes that become more affordable for farmers; and vii) capturing and mining multiple sources of “Big Data” available to dairy farmers. These should facilitate improved performance, health and fertility of dairy cows in the future.

Little is known on the effects of common calf diseases on mortality and carcass traits in the white veal industry (special-fed veal), a highly integrated production system, currently criticized for the intensive pro- and metaphylactic use of antimicrobials. The objective of the present study was to determine the impact of bovine respiratory disease (BRD), diarrhea, arthritis and otitis on the economically important parameters of mortality, hot carcass weight (HCW), carcass quality, fat cover and meat color. For this purpose, a prospective study on 3519 white veal calves, housed in 10 commercial herds, was conducted. Case definitions were based on clinical observation by the producers and written treatment records were used.

Unbalanced metabolic status in the weeks after calving predisposes dairy cows to metabolic and infectious diseases. Blood glucose, IGF-I, non-esterified fatty acids (NEFA) and β-hydroxybutyrate (BHB) are used as indicators of the metabolic status of cows. This work aims to (1) evaluate the potential of milk mid-IR spectra to predict these blood components individually and (2) to evaluate the possibility of predicting the metabolic status of cows based on the clustering of these blood components. Blood samples were collected from 241 Holstein cows on six experimental farms, at days 14 and 35 after calving. Blood samples were analyzed by reference analysis and metabolic status was defined by k-means clustering (k=3) based on the four blood components. Milk mid-IR analyses were undertaken on different instruments and the spectra were harmonized into a common standardized format. Quantitative models predicting blood components were developed using partial least squares regression and discriminant models aiming to differentiate the metabolic status were developed with partial least squares discriminant analysis. Cross-validations were performed for both quantitative and discriminant models using four subsets randomly constituted. Blood glucose, IGF-I, NEFA and BHB were predicted with respective R 2 of calibration of 0.55, 0.69, 0.49 and 0.77, and R 2 of cross-validation of 0.44, 0.61, 0.39 and 0.70. Although these models were not able to provide precise quantitative values, they allow for screening of individual milk samples for high or low values. The clustering methodology led to the sharing out of the data set into three groups of cows representing healthy, moderately impacted and imbalanced metabolic status. The discriminant models allow to fairly classify the three groups, with a global percentage of correct classification up to 74%. When discriminating the cows with imbalanced metabolic status from cows with healthy and moderately impacted metabolic status, the models were able to distinguish imbalanced group with a global percentage of correct classification up to 92%. The performances were satisfactory considering the variables are not present in milk, and consequently predicted indirectly. This work showed the potential of milk mid-IR analysis to provide new metabolic status indicators based on individual blood components or a combination of these variables into a global status. Models have been developed within a standardized spectral format, and although robustness should preferably be improved with additional data integrating different geographic regions, diets and breeds, they constitute rapid, cost-effective and large-scale tools for management and breeding of dairy cows.

In the present study, records on 115,291 heifers distributed in 113 herds were used to investigate the association between age at the first calving (AFC) and lactation performance, lactation curve, the length of the first calving interval (CI), calf birth weight (CBW), and the incidence of dystocia in Holstein heifers in Iran. Based on the AFC, the heifers were classified into eight classes: AFC of 541 to 690 d, 691 to 720 d, 721 to 750 d, 751 to 780 d, 781 to 810 d, 811 to 840 d, 841 to 900 d, and 901 to 1200 d (AFC1 to AFC8, respectively). Multiple regression mixed models were used to investigate the association between AFC and lactation curve parameters, partial and 305-d lactation performance, 100- and 305-d SCS, and the length of the first calving (CI) interval. The mean (SD) and median AFC across all heifers was 760.2 (74.01) and 750 d, respectively. Of 115,291 heifers included, 28,192 and 7,602 heifers were, respectively, ≤ 720 and > 900 d when calving for the first time. More than 44% of the heifers were at 691 to 750 d (23 to 25 months) of age when calving for the first time. An increased AFC was associated with increased partial and 305-d lactation performance, 100- and 305-d SCS, initial milk yield, milk production at the peak of lactation, upward and downward slopes of the lactation curve. The 305-d fat percentage was associated with AFC; however, there was no association between AFC and 305-d protein percentage. An increased AFC was also associated with decreased milk production persistency, delayed peak time, longer CI, and higher calf birth weight. Compared to heifers calving for the first time between 691 to 780 d (23 to 26 months) of age, both increasing and decreasing AFC were associated with increased risk of dystocia. Controlling AFC is an important management factor in achieving a lower risk of dystocia, higher lactation performance, lower SCS, and shorter length of the calving interval.