The economic impact of subclinical ketosis at the farm level: Tackling the challenge of over-estimation due to multiple interactions

Improve animal health to reduce livestock emissions: quantifying an open goal

Greenhouse gas (GHG) emissions from livestock production must be urgently tackled to substantially reduce their contribution to global warming. Simply reducing livestock numbers to this end risks impacting negatively on food security, rural livelihoods and climate change adaptation. We argue that significant mitigation of livestock emissions can be delivered immediately by improving animal health and hence production efficiency, but this route is not prioritized because its benefits, although intuitive, are poorly quantified. Rigorous methodology must be developed to estimate emissions from animal disease and hence achievable benefits from improved health through interventions. If, as expected, climate change is to affect the distribution and severity of health conditions, such quantification becomes of even greater importance. We have therefore developed a framework and identified data sources for robust quantification of the relationship between animal health and greenhouse gas emissions, which could be applied to drive and account for positive action. This will not only help mitigate climate change but at the same time promote cost-effective food production and enhanced animal welfare, a rare win-win in the search for a sustainable planetary future.

Global losses due to dairy cattle diseases: A comorbidity-adjusted economic analysis

An economic simulation was carried out over 183 milk-producing countries to estimate the global economic impacts of 12 dairy cattle diseases and health conditions: mastitis (subclinical and clinical), lameness, paratuberculosis (Johne's disease), displaced abomasum, dystocia, metritis, milk fever, ovarian cysts, retained placenta, and ketosis (subclinical and clinical). Estimates of disease impacts on milk yield, fertility, and culling were collected from the literature, standardized, meta-analyzed using a variety of methods ranging from simple averaging to random-effects models, and adjusted for comorbidities to prevent overestimation. These comorbidity-adjusted disease impacts were then combined with a set of country-level lactational incidence and/or prevalence estimates, herd characteristics, and price estimates within a series of Monte Carlo simulations that estimated and valued the economic losses due to these diseases. It was estimated that total annual global losses are USD 65 billion (B). Subclinical ketosis, clinical mastitis, and subclinical mastitis were the costliest diseases modeled, resulting in mean annual global losses of approximately USD 18B, USD 13B, and USD 9B, respectively. Estimated global annual losses due to clinical ketosis, displaced abomasum, dystocia, lameness, metritis, milk fever, ovarian cysts, paratuberculosis, and retained placenta were estimated to be USD 0.2B, 0.6B, 0.6B, 6B, 5B, 0.6B, 4B, 4B, and 3B, respectively. Without adjustment for comorbidities, when statistical associations between diseases were disregarded, mean aggregate global losses would have been overestimated by 45%. Although annual losses were greatest in India (USD 12B), the USA (USD 8B), and China (USD 5B), depending on the measure of losses used (losses as a percent of GDP, losses per capita, losses as a percent of gross milk revenue), the relative economic burden of these dairy cattle diseases across countries varied markedly.

Alterations in the gut microbiota and its metabolites contribute to metabolic maladaptation in dairy cows during the development of hyperketonemia

Metabolic maladaptation in dairy cows after calving can lead to long-term elevation of ketones, such as β-hydroxybutyrate (BHB), representing the condition known as hyperketonemia, which greatly influences the health and production performance of cows during the lactation period. Although the gut microbiota is known to alter in dairy cows with hyperketonemia, the association of microbial metabolites with development of hyperketonemia remains unknown. In this study, we performed a multi-omics analysis to investigate the associations between fecal microbial community, fecal/plasma metabolites, and serum markers in hyperketonemic dairy cows during the transition period. Dynamic changes in the abundance of the phyla Verrucomicrobiota and Proteobacteria were detected in the gut microbiota of dairy cows, representing an adaptation to enhanced lipolysis and abnormal glucose metabolism after calving. Random forest and univariate analyses indicated that Frisingicoccus is a key bacterial genus in the gut of cows during the development of hyperketonemia, and its abundance was positively correlated with circulating branched-chain amino acid levels and the ketogenesis pathway. Taurodeoxycholic acid, belonging to the microbial metabolite, was strongly correlated with an increase in blood BHB level, and the levels of other secondary bile acid in the feces and plasma were altered in dairy cows prior to the diagnosis of hyperketonemia, which link the gut microbiota and hyperketonemia. Our results suggest that alterations in the gut microbiota and its metabolites contribute to excessive lipolysis and insulin insensitivity during the development of hyperketonemia, providing fundamental knowledge about manipulation of gut microbiome to improve metabolic adaptability in transition dairy cows.IMPORTANCEAccumulating evidence is pointing to an important association between gut microbiota-derived metabolites and metabolic disorders in humans and animals; however, this association in dairy cows from late gestation to early lactation is poorly understood. To address this gap, we integrated longitudinal gut microbial (feces) and metabolic (feces and plasma) profiles to characterize the phenotypic differences between healthy and hyperketonemic dairy cows from late gestation to early lactation. Our results demonstrate that cows underwent excessive lipid mobilization and insulin insensitivity before hyperketonemia was evident. The bile acids are functional readouts that link gut microbiota and host phenotypes in the development of hyperketonemia. Thus, this work provides new insight into the mechanisms involved in metabolic adaptation during the transition period to adjust to the high energy and metabolic demands after calving and during lactation, which can offer new strategies for livestock management involving intervention of the gut microbiome to facilitate metabolic adaptation.

A New Tool to Assess the Economic Impact of Q Fever on Dairy Cattle Farms

To support farmers in their decisions related to Q fever, a dedicated economic assessment tool is developed. The present work describes the calculator, its economic rationale, and the supporting assumptions. The calculator integrates a yearly compartmental model to represent population dynamism and the main interactions between disorders linked to Q fever, especially reproductive disorders (abortion, retained foetal membranes, purulent vaginal discharge and endometritis, extra services, and calving-conception delays). The effects of the nontangible cost of the disease on human health, the welfare of the animals, and the workload of farmers were not integrated into the model. The model shows high-level sensitivity to the prevalence of Q fever in the herd prevaccination and to the costs of abortion and extra days of calving-conception intervals. Breakeven points, i.e., cost values that allow us to achieve positive vaccination benefits, are also reported. For herds with moderate or high prevalence rates of Q fever prevaccination (>30%), a vaccination benefit is observed. The vaccine should be considered a type of insurance in herds with low prevalence rates of Q fever prevaccination (≤20%). The calculator was developed to aid decision-making at the farm level, and no conclusion can be extrapolated as a generic trend based on the present work.

The rumen microbiota contributed to the development of mastitis induced by subclinical ketosis

BACKGROUND

Mastitis is a serious disease which affects animal husbandry, particularly in cow breeding. The etiology of mastitis is complex and its pathological mechanism is not yet fully understood. Our previous research in clinical investigation has revealed that subclinical ketosis can increase the number of somatic cell counts (SCC) in milk, although the underlying mechanism remains unclear. Recent studies have further confirmed the significant role of mastitis.

RESULTS

In this study, we aimed to examine the SCC, rumen microbiota, and metabolites in the milkmen of cows with subclinical ketosis. Additionally, we conducted a rumen microbiota transplant into mice to investigate the potential association between rumen microbiota disturbance and mastitis induced by subclinical ketosis in dairy cows. The study has found that cows with subclinical ketosis have a higher SCC in their milk compared to healthy cows. Additionally, there were significant differences in the rumen microbiota and the level of volatile fatty acid (VFA) between cows with subclinical ketosis and healthy cows. Moreover, transplanting the rumen microbiota from subclinical ketosis and mastitis cows into mice can induce mammary inflammation and liver function damage than transplanting the rumen flora from healthy dairy cows.

CONCLUSIONS

In addition to the infection of mammary gland by pathogenic microorganisms, there is also an endogenous therapeutic pathway mediated by rumen microbiota. Targeted rumen microbiota modulation may be an effective way to prevent and control mastitis in dairy cows.

Milk β-hydroxybutyrate metrics and its consequences for surveillance of hyperketonaemia on commercial dairy farms

Dairy cows that are unable to adapt to a change in their metabolic status are at risk for hyperketonaemia (HK). Reported HK herd level prevalences range a lot and we hypothesized that this is partly due to differences in used tests and monitoring protocols. Insights in milk β-hydroxybutyrate (BHB) metrics can potentially explain why the reported incidences or prevalences vary between test strategies. Automated collection and repeated analyses of individual milk samples with the DeLaval Herd Navigator™ (HN) provides real-time data on milk BHB concentrations. We aimed to use that information to gain insight in BHB metrics measured in milk from 3 to 60 days in milk (DIM). Using different cut-offs (0.08, 0.10 and 0.15 mmol/L), 5 BHB metrics were determined. Furthermore, the impact of 4 arbitrary test protocols on the detected incidence of HK was assessed. We used HN data of 3,133 cows from 35 herds. The cumulative incidence of HK between 3 and 60 DIM varied between 30.5 and 76.7% for different cut-off values. We found a higher HK incidence for higher parity cows. The first elevated BHB concentrations were roughly found between one and two weeks after calving. For higher parity cows the maximum BHB concentrations were higher, the onset of HK was earlier after calving, and the number of episodes of HK was higher. It appeared that the sensitivity of a HK test protocol can be increased by increasing the testing frequency from once to twice a week. Also extending the number of days of the test window from 4-14 to 4-21 days enhances the chance to find cows experiencing HK. In conclusion, HN data provided useful insights in milk BHB metrics. The chosen cut-off value had a large effect on the reported metrics which explains why earlier reported incidences or prevalences vary such a lot. Differences in test period and sample selection also had a large impact on the observed HK incidence. We suggest to take this in consideration while evaluating whether HK is an issue on farm level and use a uniform protocol for benchmarking of HK between farms.

Sirtuin 3 mitigates oxidative-stress-induced apoptosis in bovine mammary epithelial cells

Ketosis is often accompanied by a reduction in milk production in dairy cows, but the molecular mechanism has not been fully elucidated. Ketotic cows possess systemic oxidative stress (OS), which may implicate apoptosis in mammary glands. Sirtuin 3 (SIRT3) is a vital regulator of cellular redox homeostasis and is under the control of AMP-activated protein kinase (AMPK) signaling in nonruminants. Thus, we aimed to investigate (1) the AMPK-SIRT3 and apoptosis status of mammary glands from ketotic cows, (2) the effect of SIRT3 on OS-induced apoptosis in bovine mammary epithelial cells (BMEC), and (3) the role of AMPK signaling on SIRT3-mediated effects on apoptosis. Mammary gland samples were reused from a previous study, which contained healthy and ketotic cows (both n = 15). BMEC were incubated with 0, 0.3, 0.6, or 0.9 mM H2O2 for 6 h with/without a 30 min incubation of an antioxidant MitoQ (1 μM). Then BMEC were incubated with SIRT3 overexpression adenovirus (Ad-SIRT3) for 6 h followed by a 6 h incubation with 0.6 mM H2O2. Finally, BMEC were treated with the AMPK inhibitor Compound C (Cd C,10 μM) for 30 min before the H2O2 challenge, or cells were initially treated with the AMPK agonist MK8722 (10 μM) for 30 min followed by a 30-h culture with/without si-SIRT3 and eventually the H2O2 exposure. Ketotic cows displayed higher levels of Bax, Caspase-3 and Bax/Bcl-2 but lower levels of Bcl-2 in mammary glands. H2O2 incubation displayed similar results, exhibiting a dose-dependent manner between the H2O2 concentration and the apoptosis degree. Mito Q pretreatment reduced cellular reactive oxygen species and rescued cells from apoptosis. Ketotic cows had a lower mammary protein abundance of SIRT3. Similarly, H2O2 incubation downregulated both mRNA and protein levels of SIRT3 in a dose- and time-dependent manner. Ad-SIRT3 infection lowered levels of cellular reactive oxygen species, Bax, Caspase-3 and Bax/Bcl-2 but increased levels of Bcl-2. TUNEL assays confirmed that Ad-SIRT3 infection mitigated H2O2-induced apoptosis. Both ketotic cows and H2O2-induced BMEC had lower levels of p-AMPK and p-AMPK/AMPK. Additionally, Cd C pretreatment decreased SIRT3 and Bcl-2 expression but increased levels of Bax and Caspase-3. Contrary to the inhibitor, MK8722 had opposite effects and reduced the percentage of apoptotic cells. However, these effects of MK8722 were reversed upon SIRT3 silencing. In conclusion, in vivo data confirmed that ketosis is associated with greater apoptosis and restricted AMPK-SIRT3 signaling in mammary glands; in vitro data indicated that SIRT3 mitigates OS-induced apoptosis via AMPK signaling. As such, there may be potential benefits for targeting the AMPK-SIRT3 axis to help counteract the negative effects of mammary glands during ketosis.

Review: Linking animal health measures in dairy cows to farm-level economic outcomes: a systematic literature mapping

Farm animal health is an area of increasing interest to both the public and industry stakeholders. There is an ongoing debate on whether improving animal health, and thereby increasing welfare, is profitable or not. Improving animal health often requires investments in the farm or increases labour costs. As a result, the impact of animal health on farm economy is particularly interesting. This study systematically maps and assesses the available evidence in the published scientific literature regarding the link between farms' economic outcomes on dairy cow health, with the aim of identifying knowledge gaps in this field of research. In total, 59 peer-reviewed articles were included using a broad range of animal health variables and economic outcomes. We found a heterogeneous body of evidence in terms of both methods, animal health measures (AHMs) and economic outcome measures used. None of the included studies makes explicit causal claims between AHMs and economic outcomes. The results suggest that common production diseases such as clinical mastitis and lameness, which are painful and affect cow health and welfare, are costly for farmers. We found a knowledge gap and lack of evidence on the impact of animal health interventions on farms' economic outcomes, as well as the long-term effects of such interventions. Future research should aim to investigate the causal links between animal health and economic outcomes.

Precision technologies for the management of reproduction in dairy cows

Precision livestock farming (PLF) utilizes information and communication technology (ICT) to continuously monitor, control, and enhance the productivity, reproduction, health, welfare, and environmental impact of livestock. Technological advancements have facilitated the seamless flow of information from animals to humans, enabling practical decision-making processes concerning health, reproduction management, and calving surveillance. With the increasing population of livestock per farm, it has become impractical for farmers to individually track every animal within these large groups. Historically, cattle management decisions heavily relied on human observation, judgment, and experience. However, it is impossible for a single individual to gather reliable audio-visual monitoring data round the clock. Presently, dairy cows exhibit subtler indicators of estrus, resulting in a substantial chance of missing an estrus cycle. Furthermore, calving complications sometimes go unnoticed on farms, resulting in a higher number of culled cattle. In addition, an increasing number of crossbred cows experience delayed return to estrus after calving due to low body condition scores (BCS). The decline in BCS during the dry period is associated with a reduced likelihood of pregnancy following the first and second postpartum inseminations. Precision technologies enable the monitoring and tracking of an individual cow's physiological behavior and reproductive parameters, thereby optimizing management practices and farm performance. Despite the exploration of various technologies, there are still some common challenges that need to be addressed, including battery lifespan, transmission range, specificity and sensitivity, storage capacity, and economic affordability. Nonetheless, the demand for these tools from farmers and researchers is growing, and the implementation of PLF in grazing systems can yield positive outcomes in terms of animal reproductive welfare and labor optimization. This review primarily focuses on the different aspects of reproduction management in dairy using sensors, automated cameras, and various computer software.

The Marginal Abatement Cost of Antimicrobials for Dairy Cow Mastitis: A Bioeconomic Optimization Perspective

Maintaining udder health is the primary indication for antimicrobial use (AMU) in dairy production, and modulating this application is a key factor in decreasing AMU. Defining the optimal AMU and the associated practical rules is challenging since AMU interacts with many parameters. To define the trade-offs between decreased AMU, labor and economic performance, the bioeconomic stochastic simulation model DairyHealthSim (DHS)© was applied to dairy cow mastitis management and coupled to a mean variance optimization model and marginal abatement cost curve (MACC) analysis. The scenarios included three antimicrobial (AM) treatment strategies at dry-off, five types of general barn hygiene practices, five milking practices focused on parlor hygiene levels and three milk withdrawal strategies. The first part of economic results showed similar economic performances for the blanked dry-off strategy and selective strategy but demonstrated the trade-off between AMU reduction and farmers' workload. The second part of the results demonstrated the optimal value of the animal level of exposure to AM (ALEA). The MACC analysis showed that reducing ALEA below 1.5 was associated with a EUR 10,000 loss per unit of ALEA on average for the farmer. The results call for more integrative farm decision processes and bioeconomic reasoning to prompt efficient public interventions.

Characteristics of Holstein cows predisposed to ketosis during the post-partum transition period

BACKGROUND

Ketosis is a common metabolic disorder during the post-partum transition period of dairy cattle. How the method of reproduction, parturition time, and calf birth weight affect the occurrence of ketosis on dairy herds remains elusive.

OBJECTIVES

This study investigated factors associated with the severity of ketosis.

METHODS

We divided 186 Holstein cows into three classifications based on the highest β-hydroxybutyrate (BHBA) concentration during the post-partum transition period, namely non-ketosis (<1.2 mmol/L, n = 94), subclinical ketosis (1.2-2.9 mmol/L, n = 58), and clinical ketosis (≥3.0 mmol/L, n = 34). We evaluated characteristics of cows associated with the severity of ketosis.

RESULTS

Ketosis was not associated with the method of reproduction, parturition time, pregnancy wastage, premature delivery, retained placenta, and type of calf. Cows calving in spring and especially summer were at higher risk of severe ketosis (p < 0.01). Cows with increased body condition score (BCS) at parturition, age, lactation number, and calving interval were more likely to develop severe ketosis (p < 0.05). Cows with clinical ketosis produced most milk (29.9 ± 1.0 kg) from days four to six, whereas cows without ketosis produced the least (21.3 ± 0.8 kg) (p < 0.001). Heavier calf birth weight resulted in high risk of severe ketosis (p < 0.01), due to increased milk yield during the early lactation.

CONCLUSIONS

The severity of ketosis is associated with the calving season, BCS at parturition, age, lactation number, calving interval, milk yield in the early lactation period, and calf birth weight. Nonetheless, it was not associated with the method of reproduction, parturition time, pregnancy wastage, premature delivery, retained placenta, and type of calf. This study is the first to investigate the associations between ketosis and calf birth weight. Our findings could help predict cows at risk of ketosis and take precautions.

Changes in the rumen microbiota community in ketosis cows during propylene glycol treatment

Ketosis, a common metabolic disorder in dairy cattle, occurs during early lactation and leads to higher concentrations of non-esterified fatty acids (NEFAs) and β-hydroxybutyrate (BHBA), and is generally believed to be caused by excessive negative energy balance (NEB). Propylene glycol (PG), a gluconeogenic precursor, has been proved to promote gluconeogenesis and alleviate NEB. Oral administration of PG is widely considered one of the most effective therapeutic options for treating ketosis. Thus, in this study, we assessed the effects of PG on rumen microbiota via 16S rDNA analysis. The results show that one dose (500 mL) of PG treatment could rapidly reduce the blood BHBA level in ketosis cows by increasing the level and proportion of propionate in the rumen. Meanwhile, PG also had certain effects on the rumen bacterial community. Compared with before treatment, the relative abundances of Prevotella, Succinivibrionaceae_UCG-001 and Prevotellaceae_UCG-001 increased significantly, while those of Christensenellaceae_R-7_group, Butyrivibrio and Saccharofermentans significantly decreased. LEfSe analysis revealed that after PG treatment, only Rikenellaceae_RC9_gut_group was enriched in the rumen fluid at the genus level. In conclusion, the present study indicates that ketosis is accompanied by alterations in the rumen microbiota community. PG treatment changes the composition of rumen microbiota to a healthier state and contributes to rapid recovery from ketosis. These results support the usage of PG for treating such metabolic diseases that challenge high-yield cows due to their minimized cost and maximized safety without any adverse events.

Invited Review: Ketosis Diagnosis and Monitoring in High-Producing Dairy Cows

This work reviews the current impact and manifestation of ketosis (hyperketonemia) in dairy cattle, emphasizing the practical use of laboratory methods, field tests, and milk data to monitoring this disease. Ketosis is a major issue in high-producing cows, easily reaching a prevalence of 20% during early postpartum when the negative energy balance is well established. Its economic losses, mainly related to decreasing milk yield, fertility, and treatment costs, have been estimated up to €250 per case of ketosis/year, which can double if associated diseases are considered. A deep relationship between subclinical or clinical ketosis and negative energy balance and related production diseases can be observed mainly in the first two months postpartum. Fourier transform infrared spectrometry methods gradually take place in laboratory routine to evaluates body ketones (e.g., beta-hydroxybutyrate) and probably will accurately substitute cowside blood and milk tests at a farm in avenir. Fat to protein ratio and urea in milk are largely evaluated each month in dairy farms indicating animals at risk of hyperketonemia. At preventive levels, other than periodical evaluation of body condition score and controlling modifiable or identifying non-modifiable risk factors, the ruminatory activity assessment during the peripartum seems to be a valuable tool at farms. We conclude that a technological advance progressively takes place to mitigate the effects of these metabolic diseases, which challenge the high-yielding cows.

An Estimate of the Effects from Precision Livestock Farming on a Productivity Index at Farm Level. Some Evidences from a Dairy Farms' Sample of Lombardy

This paper aimed at verifying if and to what extent the use of information technologies for dairy farming positively affects productivity of farmed herd. To do this we estimated the effects of precision farming on a productivity index at herd level, utilizing individual farms data of about 500 livestock farms. Farms are specialized in bovine milk production and are localized in Lombardy, that is one of the most important areas of Italian dairy farming. Using a two-stage treatment regression model, to solve the selection bias due to both observed and un-observed individual heterogeneity in the technology adoption, the study found a positive relationship between adopter status and the proxy of herd productivity.

Opportunities and limitations of milk mid-infrared spectra-based estimation of acetone and β-hydroxybutyrate for the prediction of metabolic stress and ketosis in dairy cows

Subclinical (SCK) and clinical (CK) ketosis are metabolic disorders responsible for big losses in dairy production. Although Fourier-transform mid-infrared spectrometry (FTIR) to predict ketosis in cows exposed to great metabolic stress was studied extensively, little is known about its suitability in predicting hyperketonemia using individual samples, e.g. in small dairy herds or when only few animals are at risk of ketosis. The objective of the present research was to determine the applicability of milk metabolites predicted by FTIR spectrometry in the individual screening for ketosis. In experiment 1, blood and milk samples were taken every two weeks after calving from Holstein (n = 80), Brown Swiss (n = 72) and Swiss Fleckvieh (n = 58) cows. In experiment 2, cows diagnosed with CK (n = 474) and 420 samples with blood β-hydroxybutyrate [BHB] <1.0 mmol/l were used to investigate if CK could be detected by FTIR-predicted BHB and acetone from a preceding milk control. In experiment 3, correlations between data from an in farm automatic milk analyser and FTIR-predicted BHB and acetone from the monthly milk controls were evaluated. Hyperketonemia occurred in majority during the first eight weeks of lactation. Correlations between blood BHB and FTIR-predicted BHB and acetone were low (r = 0.37 and 0.12, respectively, P < 0.0001), as well as the percentage of true positive values (11.9 and 16.6%, respectively). No association of FTIR predicted ketone bodies with the interval of milk sampling relative to CK diagnosis was found. Data obtained from the automatic milk analyser were moderately correlated with the same day FTIR-predicted BHB analysis (r = 0.61). In conclusion, the low correlations with blood BHB and the small number of true positive samples discourage the use of milk mid-infrared spectrometry analyses as the only method to predict hyperketonemia at the individual cow level.

Estimating the combined costs of clinical and subclinical ketosis in dairy cows

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).

Expert-based development of a generic HACCP-based risk management system to prevent critical negative energy balance in dairy herds

The objective of this study was to develop a generic risk management system based on the Hazard Analysis and Critical Control Point (HACCP) principles for the prevention of critical negative energy balance (NEB) in dairy herds using an expert panel approach. In addition, we discuss the advantages and limitations of the system in terms of implementation in the individual dairy herd. For the expert panel, we invited 30 researchers and advisors with expertise in the field of dairy cow feeding and/or health management from eight European regions. They were invited to a Delphi-based set-up that included three inter-correlated questionnaires in which they were asked to suggest risk factors for critical NEB and to score these based on 'effect' and 'probability'. Finally, the experts were asked to suggest critical control points (CCPs) specified by alarm values, monitoring frequency and corrective actions related to the most relevant risk factors in an operational farm setting. A total of 12 experts (40 %) completed all three questionnaires. Of these 12 experts, seven were researchers and five were advisors and in total they represented seven out of the eight European regions addressed in the questionnaire study. When asking for suggestions on risk factors and CCPs, these were formulated as 'open questions', and the experts' suggestions were numerous and overlapping. The suggestions were merged via a process of linguistic editing in order to eliminate doublets. The editing process revealed that the experts provided a total of 34 CCPs for the 11 risk factors they scored as most important. The consensus among experts was relatively high when scoring the most important risk factors, while there were more diverse suggestions of CCPs with specification of alarm values and corrective actions. We therefore concluded that the expert panel approach only partly succeeded in developing a generic HACCP for critical NEB in dairy cows. We recommend that the output of this paper is used to inform key areas for implementation on the individual dairy farm by local farm teams including farmers and their advisors, who together can conduct herd-specific risk factor profiling, organise the ongoing monitoring of herd-specific CCPs, as well as implement corrective actions when CCP alarm values are exceeded.

Palmitic Acid and β-Hydroxybutyrate Induce Inflammatory Responses in Bovine Endometrial Cells by Activating Oxidative Stress-Mediated NF-κB Signaling

Ketosis is a nutritional metabolic disease in dairy cows, and researches indicated that ketonic cows always accompany reproductive problems. When ketosis occurs, the levels of non-esterified fatty acids (NEFAs) and β-hydroxybutyrate (BHBA) in the blood increase significantly. Palmitic acid (PA) is a main component of saturated fatty acids composing NEFA. The aim of this study was to investigate whether high levels of PA and BHBA induce inflammatory responses and regulatory mechanisms in bovine endometrial cells (BEND). Using an enzyme-linked immunosorbent assay, quantitative real-time PCR, and western blotting, we evaluated oxidative stress, pro-inflammatory factors, and the nuclear factor (NF)-κB pathway in cultured BEND cells treated with different concentrations of PA, BHBA, pyrrolidinedithiocarbamate (PDTC, an NF-κB pathway inhibitor), and N-acetylcysteine (NAC, an antioxidant). The content of malondialdehyde was significantly higher, the content of glutathione was lower, and antioxidant activity-glutathione peroxidase, superoxide dismutase, catalase, and total antioxidant capacity-was lower in treated cells compared with control cells. PA- and BHBA-induced oxidative stress activated the NF-κB signaling pathway and upregulated the release of pro-inflammatory factors. Moreover, PA- and BHBA-induced activation of NF-κB-mediated inflammatory responses was inhibited by PDTC and NAC. High concentrations of PA and BHBA induce inflammatory responses in BEND cells by activating oxidative stress-mediated NF-κB signaling.

Farm-specific failure costs of production disorders in European organic dairy herds

On-farm decision support in animal health management requires a tailor-made failure costs (FCs) assessment of production disorders for the individual farm. In our study we defined a generic framework to estimate the FC of production disorders in dairy cows. We converted the framework to a practical tool in which the farm-specific FC of mastitis, ketosis, lameness and metritis were estimated for 162 organic dairy farms in four European countries. Along with the structure of the framework, the FC estimation required three distinct types of model input: performance input (related to herd performance parameters), consequential input (related to the consequences of the disorders) and economic input (related to price levels). Input was derived from official herd recordings (e.g. test-day records and animal health recordings) and farmers' responses (e.g. questionnaire replies). The average FC of mastitis, ketosis, lameness and metritis amounted to € 96, € 21, € 43 and € 10 per cow per year, respectively. The variation in FC outcomes was high among farmers and countries. Overall ranking of the disorders based on absolute values was the same for all countries, with mastitis being the costliest disorder followed in order by lameness, ketosis, and metritis. Farm specific estimates can be used to rank production related disorders in terms of their associated failure costs and thus provide valuable insights for herd health management. The practical calculation tool developed in this study should be considered by farmers or herd health advisors to support their animal health practices or advice.

Invited review: β-hydroxybutyrate concentration in blood and milk and its associations with cow performance

Hyperketonemia (HYK) is one of the most frequent and costly metabolic disorders in high-producing dairy cows and its diagnosis is based on β-hydroxybutyrate (BHB) concentration in blood. In the last 10 years, the number of papers that have dealt with the impact of elevated BHB levels in dairy cattle has increased. Therefore, this paper reviewed the recent literature on BHB concentration in blood and milk, and its relationships with dairy cow health and performance, and farm profitability. Most studies applied the threshold of 1.2 mmol/l of BHB concentration in blood to indicate HYK; several authors considered BHB concentrations between 1.2 and 2.9 mmol/l as subclinical ketosis, and values ⩾3.0 mmol/l as clinical ketosis. Results on HYK frequency (prevalence and incidence) and cow performance varied according to parity and days in milk, being greater in multiparous than in primiparous cows, and in the first 2 weeks of lactation than in later stages. Hyperketonemia has been associated with greater milk fat content, fat-to-protein ratio and energy-corrected milk, and lower protein and urea nitrogen in milk. The relationships with milk yield and somatic cell count are still controversial. In general, HYK impairs health of dairy cows by increasing the risk of the onset of other early lactation diseases, and it negatively affects reproductive performance. The economic cost of HYK is mainly due to impaired reproductive performance and milk loss. From a genetic point of view, results from the literature suggested the feasibility of selecting cows with low susceptibility to HYK. The present review highlights that milk is the most promising matrix to identify HYK, because it is easy to sample and allows a complete screening of the herd through BHB concentration predicted using mid-IR spectroscopy during routine milk recording. Further research is needed to validate accurate and convenient methods to discriminate between cows in risk of HYK and healthy animals in field conditions and to support farmers to achieve an early detection and minimise the economic losses.

Survey of ketolactia, determining the main predisposing management factors and consequences in Hungarian dairy herds by using a cow-side milk test

The aims of the survey were to determine the prevalence of ketosis in dairy herds by measuring the concentration of beta-hydroxybutyrate (BHBA) in milk by Keto-Test (Sanwa Kagaku Kenkyusho, Nagoya, Japan); risk factors and the relationship with postpartum diseases were investigated. 1667 early lactating (days in milk 0-75) cows were tested in 52 dairy herds in 2013 and 2014 years. In total, 29.3 per cent of samples were positive (BHBA_MILK ≥100 µmol/l), including 3.7 per cent high positives (BHBA_MILK ≥500 µmol/l). The prevalence was similar in herds with less than or more than 9000 kg milk yield (0.34 and 0.38, respectively, P=0.4); however, it was higher in the herds with more than 1000 cows than in smaller herds (<500 and 500-1000 cows) (0.46, P=0.03). The BHBA level in milk was in a non-linear positive relationship with parity (P=0.01), associated with retained placenta (P=0.0006), mastitis (P=0.02) and clinical ketosis (P<0.001). The results confirm the high prevalence of ketolactia in Hungarian dairy herds and its links to herd-related and cow-related risk factors and diseases occurring commonly in fresh cows.

A randomized controlled trial on the effect of incomplete milking during early lactation on ketonemia and body condition loss in Holstein dairy cows

Limiting milk production for a short period of time in early lactation could be a relevant strategy to prevent hyperketonemia (HYK). From December 2013 to March 2015, 838 multiparous Holstein cows from 13 herds were enrolled in a randomized controlled trial evaluating the effect of incomplete milking in early lactation on ketonemia and its effect on body condition score (BCS) loss. Cows were randomly assigned 4 wk before expected calving date to 1 of 2 treatment groups, (1) a conventional milking protocol (CON) for which cows were completely milked or (2) an incomplete milking protocol (INC) for which a maximum of 10 to 14 kg of milk/d were withdrawn during the first 5 d in milk (DIM). β-Hydroxybutyrate (BHB) concentrations were measured from blood samples collected on each cow 3 times at weekly intervals. Hyperketonemia was defined as BHB ≥1.4 mmol/L. Body condition score variation in the postcalving period was calculated by subtracting BCS assessed at wk 7 from BCS assessed at first week after calving. Effect of treatment on ketonemia and prevalence of HYK were evaluated for 4 specific time periods: 1 to 3, 4 to 7, 8 to 17, and 18 to 26 DIM. Effect of treatment on ketonemia was investigated using linear mixed models with natural logarithm of BHB measurements as outcome and treatment groups as fixed effect. Generalized linear mixed models with HYK as outcome, using logit link, and treatment groups as fixed effect were used to investigate effect of treatment on odds of HYK. A logistic regression model with BCS loss (<0.75 or ≥0.75) as outcome and treatment groups and herd as fixed effects was used to study effect of INC on odds of having BCS loss ≥0.75. A total of 813 lactations had complete data and were used for statistical analysis of ketonemia and HYK. A total of 709 lactations had complete data and were used for analysis of BCS loss. Geometric means of blood BHB concentrations during the 1 to 3, 4 to 7, 8 to 17, and 18 to 26 DIM periods were, respectively, 0.72 (95% confidence interval = 0.66, 0.80), 0.66 (0.60, 0.73), 0.90 (0.80, 1.01), and 0.93 (0.83, 1.05) mmol/L for INC, and 0.65 (0.59, 0.72), 0.79 (0.72, 0.87), 0.94 (0.84, 1.06), and 0.92 (0.82, 1.04) mmol/L for CON. Cows in INC group had lower ketonemia during the 4 to 7 DIM period. Predicted prevalence of HYK during the 1 to 3, 4 to 7, 8 to 17, and 18 to 26 DIM periods were, respectively, 2.8 (3.2, 15.1), 4.6 (2.0, 10.0), 13.4 (8.4, 20.0), and 23.0% (17.4, 29.7) for INC and 2.6 (2.5, 13.8), 10.7 (5.6, 19.3), 19.4 (13.0, 27.9), and 21.3% (16.0, 27.8) for CON. The INC treatment reduced the prevalence of HYK during the 4 to 7 and 8 to 17 DIM periods. No association was observed between INC and BCS loss in the postcalving period. Overall, the incomplete milking protocol was effective for reducing ketonemia and prevalence of HYK during the early postpartum period.

Estimating the economic impact of subclinical ketosis in dairy cattle using a dynamic stochastic simulation model

The objective of this study was to estimate the economic impact of subclinical ketosis (SCK) in dairy cows. This metabolic disorder occurs in the period around calving and is associated with an increased risk of other diseases. Therefore, SCK affects farm productivity and profitability. Estimating the economic impact of SCK may make farmers more aware of this problem, and can improve their decision-making regarding interventions to reduce SCK. We developed a dynamic stochastic simulation model that enables estimating the economic impact of SCK and related diseases (i.e. mastitis, metritis, displaced abomasum, lameness and clinical ketosis) occurring during the first 30 days after calving. This model, which was applied to a typical Dutch dairy herd, groups cows according to their parity (1 to 5+), and simulates the dynamics of SCK and related diseases, and milk production per cow during one lactation. The economic impact of SCK and related diseases resulted from a reduced milk production, discarded milk, treatment costs, costs from a prolonged calving interval and removal (culling or dying) of cows. The total costs of SCK were €130 per case per year, with a range between €39 and €348 (5 to 95 percentiles). The total costs of SCK per case per year, moreover, increased from €83 per year in parity 1 to €175 in parity 3. Most cows with SCK, however, had SCK only (61%), and costs were €58 per case per year. Total costs of SCK per case per year resulted for 36% from a prolonged calving interval, 24% from reduced milk production, 19% from treatment, 14% from discarded milk and 6% from removal. Results of the sensitivity analysis showed that the disease incidence, removal risk, relations of SCK with other diseases and prices of milk resulted in a high variation of costs of SCK. The costs of SCK, therefore, might differ per farm because of farm-specific circumstances. Improving data collection on the incidence of SCK and related diseases, and on consequences of diseases can further improve economic estimations.

Economic Synergy between Dry Cow Diet Improvement and Monensin Bolus Use to Prevent Subclinical Ketosis: An Experimental Demonstration Based on Available Literature

The prevention of subclinical ketosis (SCK) is based on maintaining adequate nutrition in dairy cows during the dry period and close to calving. Recently, an oral-route monensin bolus to prevent SCK was approved in Europe. The present study aims to define the allocation of resources for SCK management at the herd level and evaluate the profitability of administering monensin boluses in cows at risk for SCK. A stochastic model was used to calculate the total cost of SCK for a population with a given prevalence of cows at risk for SCK. This model included the ability of the farmer to correctly target and preventatively treat these cows at risk for SCK. The results clearly demonstrated economic synergy between two management practices. First, reducing the prevalence of cows at risk for SCK dramatically reduces the total cost of SCK and seems profitable in most situations. Second, monensin bolus use to reduce the occurrence of SCK in cows already at risk for SCK is cost-effective. The results also highlighted three economic strategies to manage SCK in the dairy industry in Europe. First, monensin bolus use throughout an entire herd when the prevalence of cows at risk for SCK is high is only profitable in the short-term as a tool to correct acute deterioration at the herd level. Second, decreasing the prevalence of cows at risk for SCK through adequate feeding in the dry period is of financial interest as a baseline strategy when prevalence is high, assuming moderate additional cost linked to the new diet. Third, monensin bolus use when the prevalence of cows at risk for SCK is low is also profitable as a long-term strategy when only cows at high risk for SCK (such as cows that are over-conditioned, old, or have a previous history of SCK-related disorders) are targeted for preventative treatment. Authors suggest to use the present results considering that farmers have a correct, but not perfect, ability to target animals to be preventively targeted with the monensin bolus. Further work is required to facilitate the early identification of cows at risk for SCK.

Challenges and priorities for modelling livestock health and pathogens in the context of climate change

Climate change has the potential to impair livestock health, with consequences for animal welfare, productivity, greenhouse gas emissions, and human livelihoods and health. Modelling has an important role in assessing the impacts of climate change on livestock systems and the efficacy of potential adaptation strategies, to support decision making for more efficient, resilient and sustainable production. However, a coherent set of challenges and research priorities for modelling livestock health and pathogens under climate change has not previously been available. To identify such challenges and priorities, researchers from across Europe were engaged in a horizon-scanning study, involving workshop and questionnaire based exercises and focussed literature reviews. Eighteen key challenges were identified and grouped into six categories based on subject-specific and capacity building requirements. Across a number of challenges, the need for inventories relating model types to different applications (e.g. the pathogen species, region, scale of focus and purpose to which they can be applied) was identified, in order to identify gaps in capability in relation to the impacts of climate change on animal health. The need for collaboration and learning across disciplines was highlighted in several challenges, e.g. to better understand and model complex ecological interactions between pathogens, vectors, wildlife hosts and livestock in the context of climate change. Collaboration between socio-economic and biophysical disciplines was seen as important for better engagement with stakeholders and for improved modelling of the costs and benefits of poor livestock health. The need for more comprehensive validation of empirical relationships, for harmonising terminology and measurements, and for building capacity for under-researched nations, systems and health problems indicated the importance of joined up approaches across nations. The challenges and priorities identified can help focus the development of modelling capacity and future research structures in this vital field. Well-funded networks capable of managing the long-term development of shared resources are required in order to create a cohesive modelling community equipped to tackle the complex challenges of climate change.

How Metabolic Diseases Impact the Use of Antimicrobials: A Formal Demonstration in the Field of Veterinary Medicine

Decreasing the use of antimicrobials has become a primary objective for both human and veterinary medicine in many countries. Medical prevention and good nutrition are seen as key parameters for reducing antimicrobial use. However, little consideration has been given to how metabolic diseases may influence the use of antimicrobials in humans and animals through limiting the prevalence and severity of infectious diseases. To quantify this relationship using the example of a common metabolic disease in dairy cows (subclinical ketosis, SCK), we constructed a stochastic model reporting the total quantity of curative antimicrobials for a given population with the prevalence of cows at risk for SCK. We considered the prevalence of SCK, the relative risk of the disease in cases of SCK compared to no SCK and the use of antimicrobials to treat SCK-induced infectious diseases. Reducing the percentage of cows at risk for SCK from 80% to 10% was associated with an average decrease in the use of antimicrobials of 11% (prevalence of SCK from 34% to 17%, respectively) or 25% (prevalence of SCK from 68% to 22%, respectively), depending on the relative risk to contract SCK if risk was present. For a large percentage of the cows at risk for SCK, using a preventive bolus of monensin reduced the use of curative antimicrobials to the same level that was observed when the percentage of cows at risk for SCK was low. The present work suggests similar approaches for obesity and diabetes.

Failure of Passive Immune Transfer in Calves: A Meta-Analysis on the Consequences and Assessment of the Economic Impact

Low colostrum intake at birth results in the failure of passive transfer (FPT) due to the inadequate ingestion of colostral immunoglobulins (Ig). FPT is associated with an increased risk of mortality and decreased health and longevity. Despite the known management practices associated with low FPT, it remains an important issue in the field. Neither a quantitative analysis of FPT consequences nor an assessment of its total cost are available. To address this point, a meta-analysis on the adjusted associations between FPT and its outcomes was first performed. Then, the total costs of FPT in European systems were calculated using a stochastic method with adjusted values as the input parameters. The adjusted risks (and 95% confidence intervals) for mortality, bovine respiratory disease, diarrhoea and overall morbidity in the case of FPT were 2.12 (1.43–3.13), 1.75 (1.50–2.03), 1.51 (1.05–2.17) and 1.91 (1.63–2.24), respectively. The mean (and 95% prediction interval) total costs per calf with FPT were estimated to be €60 (€10–109) and €80 (€20–139) for dairy and beef, respectively. As a result of the double-step stochastic method, the proposed economic estimation constitutes the first estimate available for FPT. The results are presented in a way that facilitates their use in the field and, with limited effort, combines the cost of each contributor to increase the applicability of the economic assessment to the situations farm-advisors may face. The present economic estimates are also an important tool to evaluate the profitability of measures that aim to improve colostrum intake and FPT prevention.