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An extended calving interval (CInt) by extending the voluntary waiting period (VWP) could be associated with altered metabolism in dairy cows. The aim of this study was first to evaluate the effects of VWP on metabolism and body condition during the first 305 days after the first calving in the experiment (calving 1), around the end of the VWP, and during pregnancy (280 d before calving 2). Second, the effects of the VWP on metabolism were determined from 2 wk before until 6 wk after calving 2. Third, individual cow characteristics were used to predict milk production and body condition of cows after different VWP. Holstein-Friesian cows (N=154, 41 primiparous (PP), 113 multiparous (MP)) were blocked for parity, milk production, and lactation persistency, randomly assigned to a VWP of 50, 125, or 200 days (VWP50, VWP125, or VWP200) and followed from calving 1 until 6 wk after calving 2. In the first 6 wk after calving 1 and from 2 wk before until 6 wk after calving 2, weekly plasma samples were analyzed for non-esterified fatty acids (NEFA), β-hydroxybutyrate, glucose, insulin, and insulin-like growth factor 1 (IGF-1). From wk 7 after calving 1 until 2 wk before calving 2, insulin and IGF-1 were analyzed every 2 wk. Fat- and protein-corrected milk (FPCM) and body weight (BW) gain were measured weekly. Cows were divided in two parity classes based on calving 1 (PP and MP) and remained in these classes after calving 2. During pregnancy, MP cows in VWP200 had greater plasma insulin and IGF-1 concentration and lower FPCM compared with MP cows in VWP125 (insulin: 18.5 vs 13.9 µU/mL, CI 13.0 - 19.7, P

Newborn calves are agammaglobulinemic and rely for their first immune protection almost completely on the transfer of immune constituents via colostrum. Inadequate colostrum management practices such as on-farm colostrum storage practices and colostrum feeding methods could affect immune components in colostrum and subsequently immune status of the newborn calf. We conducted a scoping review to identify all literature on the interactions between several colostrum management factors and immunological colostrum quality and passive transfer of immunity. Three major stages were defined: milking methods, colostrum treatment and storage, and administration procedures. Separate CAB Abstracts searches were performed for each of the subjects of interest. The search process was completed on November 9, 2020. Colostrum should be milked as soon as possible, as IgG concentration diminishes over time, probably due to dilution. To minimize bacterial contamination, it is advised to pasteurize colostrum in small batches at maximal 60°C for 30 or 60 min. Freeze/thawing of colostrum does not or only slightly affect IgG concentrations, as long as thawing is done au bain-marie and temperature does not exceed 40°C. In on-farm situations, it is difficult to determine the volume that should be fed as the variables contributing to the absorption of IgG by the newborn calf are many and include the quality of the colostrum, the bacterial contamination, the time interval between birth and first moment of feeding and the weight of the calf. Despite all knowledge regarding optimal colostrum management strategies, it remains challenging to predict the effects of certain colostrum management choices in field conditions. Therefore, we recommend measuring the colostral quality, weighing the newborn calf, adjusting the feeding volume accordingly to ensure optimal colostrum intake for each calf.

Colostrum feeding is essential for the transfer of passive immunity and health of newborn calves. Information on current colostrum management practices to reduce calf morbidity and mortality is important but lacking for Dutch dairy herds. We therefore conducted a survey to investigate colostrum management strategies on Dutch dairy farms. The survey was specifically focused on the most recently born calf and was returned by 107 respondents (response rate of 13.4%). The mean amount of colostrum fed at first feeding was 2.9 liters. Overall, 79% of farmers provided the calf with at least 6 liters of colostrum in up to three feedings. The majority of respondents (84%) claimed to provide the calf with colostrum for the first time within 2 h post-partum. Using ordinal logistic regression and Wilcoxon rank sum test, we found no differences in time to first colostrum feeding or total amount of colostrum fed between bull calves and heifer calves, respectively. Ordinal logistic regression showed no significant differences in time to first colostrum feeding or time between calving and removing the calf from the dam between AMS and conventional milking herds. Two sample T-test comparing the total volume of colostrum showed no significant difference between AMS and conventional milking herds. Time of day at which a calf was born affected both volume fed at first colostrum feeding and time until first colostrum feeding. Calves born between 00.00 and 06.00 were significantly at risk of receiving the first colostrum later as compared to calves born at other times. Calves born in the evening received on average a lower amount of colostrum at first feeding. Survey results on colostrum management on most Dutch dairy farms are in agreement with the advice to feed as soon as possible after parturition and to provide at least 6 liters within 24 h of age. The current study points at time of calving as a potential risk factor for sub-optimal colostrum feeding. Further research is necessary to determine the consequences of this observation.

Random effects regression models are routinely used for clustered data in etiological and intervention research. However, in prediction models, the random effects are either neglected or conventionally substituted with zero for new clusters after model development. In this study, we applied a Bayesian prediction modelling method to the subclinical ketosis data previously collected by Van der Drift et al. (2012). Using a dataset of 118 randomly selected Dutch dairy farms participating in a regular milk recording system, the authors proposed a prediction model with milk measures as well as available test-day information as predictors for the diagnosis of subclinical ketosis in dairy cows. While their original model included random effects to correct for the clustering, the random effect term was removed for their final prediction model. With the Bayesian prediction modelling approach, we first used non-informative priors for the random effects for model development as well as for prediction. This approach was evaluated by comparing it to the original frequentist model. In addition, herd level expert opinion was elicited from a bovine health specialist using three different scales of precision and incorporated in the prediction as informative priors for the random effects, resulting in three more Bayesian prediction models. Results showed that the Bayesian approach could naturally take the clustering structure of clusters into account by keeping the random effects in the prediction model. Expert opinion could be explicitly combined with individual level data for prediction. However in this dataset, when elicited expert opinion was incorporated, little improvement was seen at the individual level as well as at the herd level. When the prediction models were applied to the 118 herds, at the individual cow level, with the original frequentist approach we obtained a sensitivity of 82.4% and a specificity of 83.8% at the optimal cutoff, while with the three Bayesian models with elicited expert opinion, we obtained sensitivities ranged from 78.7% to 84.6% and specificities ranged from 75.0% to 83.6%. At the herd level, 30 out of 118 within herd prevalences were correctly predicted by the original frequentist approach, and 31 to 44 herds were correctly predicted by the three Bayesian models with elicited expert opinion. Further investigation in expert opinion and distributional assumption for the random effects was carried out and discussed.

Clinical ketosis (CK) and subclinical ketosis (SCK) are associated with lower milk production, lower reproductive performance, an increased culling of cows and an increased probability of other disorders. Quantifying the costs related to ketosis will enable veterinarians and farmers to make more informed decisions regarding the prevention and treatment of the disease. The overall aim of this study was to estimate the combined costs of CK and SCK using assumptions and input variables from a typical Dutch context. A herd level dynamic stochastic simulation model was developed, simulating 385 herds with 130 cows each. In the default scenario there was a CK probability of almost 1% and a SCK probability of 11%. The herds under the no risk scenario had no CK and SCK, while the herds under the high-risk scenario had a doubled probability of CK and SCK compared to the default scenario. The results from the simulation model were used to estimate the annual cash flows of the herds, including the costs related to milk production losses, treatment, displaced abomasum, mastitis, calf management, culling and feed, as well as the returns from sales of milk and calves. The difference between the annual net cash flows of farms in the no risk scenario and the default scenario provides the estimate of the herd level costs of ketosis. Average herd level costs of ketosis (CK and SCK combined) were €3,613 per year for a default farm and €7,371 per year for a high-risk farm. The costs for a single CK case were on average €709 (with 5 and 95 percentiles of €64 and €1,196, respectively), while the costs for a single SCK case were on average €150 (with 5 and 95 percentiles of €18 and €422, respectively) for the default farms. The differences in costs between cases occurred due to differences between cases (e.g., cow culled vs cow not culled, getting another disease vs not getting another disease).

Previous reports have shown that reproductive tract score (RTS) can predict reproduction outcomes in seasonally bred beef heifers, although the accuracy can vary. Some ultrasonographic measures of the female reproductive tract and pelvis area have also been associated with reproductive outcome in young heifers. The objectives of this study were to determine which transrectal ultrasound or pelvis measures taken at a single examination are independent predictors of reproductive failure and whether the RTS system can be optimized with this information. In this observational study, year-old beef heifers (n = 488) in 2 birth cohorts were followed from just before the first breeding until confirmation of pregnancy. A single pre-breeding examination included body condition score, RTS, ultrasound measures of the reproductive tract (length and diameter of the left and right ovaries, presence and diameter of a CL, largest follicle diameter and left uterus horn diameter) and transverse and vertical diameters of the pelvis. Additional farm records including dam parity, sire, birth weight and birth date, weaning weight, weaning date, prebreeding body weight, AI dates, and semen used were available. Breeding consisted of 50 days of AI, followed 5 to 7 days later by a 42-day bull breeding period. Pregnancy failure was defined as the failure to become pregnant after the AI and bull breeding periods, while anestrus was defined as the failure to be detected in estrus during the 50-day AI period. From the prebreeding data and farm records, independent predictors of pregnancy failure and anestrus were identified using stepwise reduction in multiple logistic regression models. Age at the onset of breeding was the only consistent independent predictor of pregnancy failure and anestrus in both cohorts of this study (P < 0.05). Body condition score, uterus horn diameter, absence of a CL, largest follicle of less than 13 mm, and pelvis area (PA) were the prebreeding examination variables that remained in prognostic models (P < 0.1). Combining either the model based on the 3 remaining ultrasound measures or RTS with PA provided more accurate prognostic models for pregnancy failure and anestrus than using RTS alone (P < 0.05). It is concluded that ultrasound measures have prognostic value for pregnancy failure in restricted bred yearling heifers as a result of their association with anestrus, and that smaller PA has additional prognostic value for poorly performing heifers.

Mammalian milk is not only a source of nutrition for the newborn, but also contains various components that regulate further development. For instance, milk is an abundant source of microRNAs (miRNAs), which are evolutionary conserved small non-coding RNAs that are involved in post-transcriptional regulation of target mRNA. MiRNAs present in milk can occur in extracellular vesicles (EVs), which are nanosized membrane vesicles released by many cell types as a means of intercellular communication. The membrane of EVs protects enclosed miRNAs from degradation and harbors molecules that allow specific targeting to recipient cells. Although several studies have investigated the miRNA content in milk EVs from individual species, little is known about the evolutionary conserved nature of EV-associated miRNAs among different species. In this study, we profiled the miRNA content of purified EVs from human and porcine milk. These data were compared to published studies on EVs from human, cow, porcine, and panda milk to assess the overlap in the top 20 most abundant miRNAs. Interestingly, several abundant miRNAs were shared between species (e.g., let-7 family members let-7a, let-7b, let-7f, and miR-148a). Moreover, these miRNAs have been implicated in immune-related functions and regulation of cell growth and signal transduction. The conservation of these miRNA among species, not only in their sequence homology, but also in their incorporation in milk EVs of several species, suggests that they are evolutionarily selected to regulate cell function in the newborn.

The first weeks of life are a critical period in the development of the newborn ruminant. Newborn ruminants are quite vulnerable since both on a farm as well as in nature they are exposed to various pathogens. Because they have a placental type that does not allow the transfer of large molecules from mother to fetus during pregnancy, ruminants are born without maternal antibodies. For their first immune defense, they depend almost entirely on the transfer of immune components through the first colostrum. Colostrum contains more nutrients than "regular" milk, and it especially contains more immunological components, such as immune cells and antibodies, also known as immunoglobulins. The first colostrum is one of the most important aspects for a healthy start of young ruminants. The general aim of this dissertation was to improve the knowledge about colostrum feeding strategies and immunological properties of colostrum, in order to better provide young ruminants with a proper neonatal immune system. Various aspects of colostrum are investigated, such handling of colostrum may influence the immunological and bacterial quality of the colostrum, how Dutch dairy farms implement colostrum management and whether the immune cells transferred with maternal colostrum are functional in the young animal.

Ketosis is a metabolic disorder that mainly occurs during the negative energy balance in early-lactation dairy cows. It is characterized by elevated concentrations of ketone bodies in blood (hyperketonemia), urine, and milk. The thesis of Saskia van der Drift covers investigations on etiologic factors, monitoring, treatment and genetics of dairy cow ketosis. Firstly, the role of the mobilization of muscle protein around parturition in the etiology of ketosis was studied. For that purpose, a method was developed to analyze the plasma concentration of 3-methylhistidine, a marker for muscle protein breakdown, by HPLC-mass spectrometry. Higher plasma 3-methylhistidine concentrations were associated with lower serum concentrations of the ketone body β-hydroxybutyrate (BHBA) in periparturient dairy cows (n = 34). This indicates that greater protein mobilization may reduce the risk to develop ketosis, probably because of a greater supply of glucogenic amino acids during negative energy balance. A large field study showed that the prevalence of ketosis (hyperketonemia) was 11.2% in early-lactation cows (n = 1678) in the Netherlands. On individual farms, the prevalence ranged from 0% to 80%. Farms participating in the study were visited on a regular test day. During these farm visits, all cows between 5 and 60 days in milk were sampled to perform the reference test for hyperketonemia (blood BHBA analysis). Data from this study were used to construct a statistical model for the routine detection of hyperketonemia at test days based on ketone body concentrations in milk (BHBA and acetone, analyzed by Fourier transform infrared spectrometry) and other available information, such as milk composition and parity. The developed model predicts the probability of hyperketonemia for each cow at the test day and subsequently estimates the prevalence of the disorder at the dairy farm. This enables routine monitoring of ketosis at test days and can contribute to the decision making on the feeding and management practices. It is common use to treat ketotic cows only when they show clinical signs, such as decreased feed intake and milk production loss. In practice, several treatment combinations are used, but evidence for the efficacy of the combined treatments was often lacking. Therefore, a clinical trial was performed with 31 cows with clinical ketosis to investigate the additive effect of a single glucocorticoid injection to oral propylene glycol treatment. Cows with clinical ketosis had a better recovery with a combined therapy of glucocorticoids and propylene glycol compared with treatment with propylene glycol only. Glucocorticoid injection resulted in higher blood glucose concentrations in ketotic cows without stimulation of muscle or fat mobilization in these animals. Finally, data from the before mentioned field study were combined with pedigree information to estimate the genetic variation and heritability of plasma BHBA, milk BHBA, and milk acetone concentrations in early-lactation cows. Heritability estimates for plasma and milk ketone body concentrations showed that variation exists in the susceptibility of cows to develop hyperketonemia and that selective breeding may contribute to a lower incidence of the disorder at the longer term

To achieve the optimal economic profit, the effort to increase milk production in a dairy cow has been generated. As a consequence of an increased milk production, it appears that the conception rate has been reported to decline during the last decade worldwide. For the optimal economics and to avoid effort for the lower conception rate in early lactation, the extension of calving interval has been suggested to be later than 12 to 13 months. However, the complexity of interactions and dynamics of factors influencing reproductive performance do influence seriously the determination of an economically optimal time to start and to stop insemination. The main objective of this thesis was to develop bio-economic models which support decision on inseminating dairy cows. The epidemiological data generated in, empirical, epidemiological studies were integrated in our simulation models. As a consequence, the first simulation model could be used to support decisions for the optimal time to start insmeination with taking more specific cow factors into account. Moreover, using the second simulation model, it was proven that the insemination number has an effect on the optimal time to stop inseminating.