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In the Nordic countries of Denmark, Finland, and Sweden, a breeding value for Saved feed is targeted. Saved feed consists of two sub-traits, maintenance and metabolic efficiency, which are evaluated as residual feed intake. This study evaluated residual feed intake in relation to calculated economic values to set breeding goal. Residual feed intake typically is derived using phenotypic or genetic regression. However, when calculating economic value (EV) for residual feed intake, phenotypic and genetic residual feed intake save feed, and so are not relevant; yet, EV is important for the genetic progress of such traits. Thus, phenotypic regression coefficients were used to obtain the economic value of residual feed intake in the current simulation. The SimHerd model was used in this study to quantify the EV of RFI. The economic value of phenotypic residual feed intake ranged from 0.16 to 0.18 €/kg dry matter, corresponding to 0.16 to 0.18 €/Scandinavian feed unit (SFU – 1 SFU corresponds to 0.97 kg dry matter and 6.7 mega joule net energy) in the SimHerd simulation. Thus, the economic value of feed efficiency corresponded to the applied feed price in the simulations (0.18 €/SFU). By splitting phenotypic residual feed intake into two periods (before and after 84 days in milk), we showed that the simulation of biological changes during early lactation showed that the economic value was not dependent on (P > 0.05) residual feed intake being modelled as one or two periods. However, profit per annual cow differed significantly between simulations using one or two residual feed intake periods (P < 0.001). In conclusion, it is very important to select the appropriate the method to estimate breeding values for residual feed intake.

The aim of the study was to calculate economic values (EV) of breeding traits (production, reproduction, direct health, calving and survival traits) for the Polish dairy cattle breeds Polish Holstein (PH) and Polish Red (PR). EV are key elements in setting up economically based breeding goals for dairy cattle and they are crucial for optimizing breeding schemes. For deriving EV, a stochastic bio-economic model was used, which estimates EVs based on population-specific biological and economic characteristics. Because the bio-economic model considers correlations between different traits, a multiple regression approach was used to correct for any double counting of effects. The results showed that EVs for direct health traits and fertility differed between breeds. The biggest difference was observed for lameness (PH -1.44 €, PR -1.09 € per cow-year), ketosis (PH -0.94 €, PR -0.58 € per cow-year) and for cow conception rate (PH 1.94 €, PR 0.84 € per cow-year). The relative economic weights for production traits were estimated as 37.00 % (PH) and 34.30 % for (PR) and for fertility traits 15.10 % (PH and for 16.10 % (PR). Major economic differences between the relative weights were observed for cow mortality (22.70 % PH, 16.90 % PR). The results of our study showed that breeding the PH brings higher economic profit than breeding the PR. Total income per PR cow was equal to 1,623 € and for PH 2,970 €.

Dairy farmers can increase the number of dairy heifer calves born in their herd by using sexed semen. They can reduce the number of both dairy bull and heifer calves by using beef semen. Long before sexed semen became commercially available, it was believed that it would provide opportunities for increasing genetic level in both herds and populations. In this study, we studied the potential for increasing the genetic level of a herd by using beef semen in combination with sexed semen. We tested the hypothesis that the potential of increasing the genetic level and the overall net return would depend on herd management. To test this hypothesis, we simulated 7 scenarios using beef semen and sexed semen in 5 herds at different management levels. We combined the results of 2 stochastic simulation models, SimHerd and ADAM. SimHerd simulated the effects of the scenarios and management levels on economic outcomes (i.e., operational return) and on technical outcomes such as the parity distribution of the dams of heifer calves, but it disregarded genetic progress. The ADAM model quantified genetic level by using the dams' parity distributions and the frequency of sexed and beef semen to estimate genetic return per year. We calculated the annual net return per slot as the sum of the operational return and the genetic return, divided by the total number of slots. Net return increased up to €18 per slot when using sexed semen in 75% genetically superior heifers and beef semen in 70% genetically inferior, multiparous cows. The assumed reliability of selection was 0.84. These findings were for a herd with overall high management for reproductive performance, longevity, and calf survival. The same breeding strategy reduced net return by €55 per slot when management levels were average. The main reason for the large reduction in net return was the heifer shortage that arose in this scenario. Our hypothesis that the potential for beef semen to increase genetic level would be herd-specific was supported. None of the scenarios were profitable under Danish circumstances when the value of the increased genetic level was not included. A comparable improvement in genetic level could be realized by selectively selling dairy heifer calves rather than using beef semen.

It has been a challenge to avoid double counting when economic values (EV) of traits are derived for breeding goal traits when using stochastic herd simulation models. In this study multiple regression and model building with mediator variables representing other traits in the breeding goal were evaluated to avoid double counting. EV were derived from data simulated with the SimHerd dairy herd simulation model. Scenarios were simulated to represent dairy herds with low and high levels of metritis and cow mortality. The simulated data was analyzed statistically with the economic net return per cow-year as the dependent variable and either the incidences of metritis or the incidence of cow mortality as the independent variables. In the model with metritis we corrected for mediator variables representing the direct effects of metritis on milk yield, fertility and occurrence of other diseases. The EV was estimated as the marginal change in economic net return in response to a change in the trait of interest. To avoid the multiple regression models to correct the EV for structural herd effects (changes in distribution of parities and lactation stages) we used a single animal based indicator variable for each trait of interest, such as incidence rate of cow mortality 1–100 DIM in multiparous cows. The EV value of improving the trait ‘incidence rate of metritis 1–100 DIM in multiparous cows’ by 0.01 was estimated to be €0.93. The importance of avoiding double counting was demonstrated as the EV of metritis was overestimated by 82% when no mediator variables were included in the multiple regression analysis. And by ignoring structural herd effects for the EV of metritis we demonstrated an underestimation in the order of 9%. Further pitfall of underestimation was demonstrated for EV of cow mortality. The EV of improving the trait ‘incidence rate of cow mortality 1–100 DIM in multiparous cows’ by 0.01 was estimated to be €46.4. Correcting for the independent variation in mortality between simulation replicates within the individual scenarios was found to be important. The results of this study suggests a new method for designing simulation experiments and analyzing simulated herd effects for estimation of EV of traits in a breeding goal. This deals with a number of previous and new concerns of how to correct for double counting and at the same time still include the structural herd effects.

Veterinarians often express frustrations when farmers do not implement their advice, and farmers sometimes shake their heads when they receive veterinary advice which is practically unfeasible. This is the background for the development of a focused 3 page economic report created in cooperation between veterinarians, farmers, advisers and researchers. Based on herd specific key-figures for management, the report presents the short- and long-term economic effects of changes in 15 management areas. Simulations are performed by the dairy herd simulation model “SimHerd”. The aim is to assist the veterinarian in identifying the economically most favorable and feasible management improvements and thereby provide more relevant and prioritised advice to the farmer.In the developing process, a prototype of the advisory tool was tested by 15 veterinarians on 55 farms. After the test period, a selection of farmers were asked to take part in a qualitative evaluation questioning them whether they had implemented the action plans suggested on basis of the advisory tool and making them explain what made them agree or disagree on the results from this new advisory tool. The aim of this process was to evaluate the farmers’ receptiveness to advice based on these economic analyses. We found that the analysed advisory tool (the report) can be seen as a valuable help and support for some farmers when deciding whether to implement the action plans. However, certain reservations were recognised. The trustworthiness of the tool depends on whether the veterinarians are able to suggest to the farmer which specific management changes are needed to obtain the estimated effects and what the related expenses might be (costs). Without transparency of expenses, time-limits, work hours and so on, farmers may not be convinced by the tool.

In a recent data study using 2.4 million lactations of 1.5 million cows, it was reported that gestation of a female calf in the first parity increases cumulative milk production by approximately 445 kg over the first 2 lactations. The reported effect in this study is large and remarkable because it has not been found before. To our knowledge, the economic implications of this or any other sex bias have not been studied. The objective of the current study was to quantify the reported influence of fetal sex across lactations by using a simulation model of a dairy herd including youngstock. Two scenarios were evaluated and compared with a scenario in which cows and heifers were exclusively bred with conventional (nonsexed) semen. In the first scenario, sexed semen was used moderately—on 30% of all heifers and 30% of the first parity cows. A second scenario was studied in which sexed semen was used intensively—on all heifers and 50% of the first-parity cows. The simulated proportion of cows giving birth to 2 consecutive heifers increased from 23% when using exclusively conventional semen up to 31 and 48% when using sexed semen moderately and intensively, respectively. The proportion of cows having 2 consecutive bulls decreased from 27% (conventional semen only) to 20 and 8% when using sexed semen moderately and intensively, respectively. When incorporating the sex bias in the simulation model, the simulated milk yield in the scenario in which sexed semen was used moderately increased by 48 kg of energy-corrected milk (ECM) per cow/yr, compared with only 36 kg of ECM when not incorporating the sex bias in the model. For the scenario in which sexed semen was used intensively, milk yield increased by 66 and 99 kg of ECM when excluding and including the sex bias, respectively. The economic implications of the assumed sex bias were €4.0 and €9.9 per cow/yr, in the scenarios in which sexed semen was used moderately and intensively, respectively.

SimHerd is a computer model of a dairy herd. In more than a decade the model has been applied and further developed within the research in herd management and animal health economics in dairy herds. Analyses with the SimHerd model have been included in 2 doctoral theses, 9 PhD theses, 4 MSc theses and a total of 28 papers in scientific journals. Minor attempts for introducing the model as a herd health advisory tool has been carried out over the years. However, the model has not yet been used broadly as a herd health advisory tool, which mainly has been explained by the complexity of the model and the lack of user friendliness. This was challenged in the project supported by the Danish Law of Innovation during 2007 to 2009, where the specific aim was to develop a user friendly web application of the SimHerd model in collaboration between StrateKo, Danish Cattle Federation and Aarhus University.This aim was fulfilled at the end of 2009 by a beta version of a SimHerd web application tested by veterinary practitioners in real herd health advisory situation and approved as the core product for starting up in early 2010 a commercial spin-off company owned by NOVI Innovation and Aarhus University. The following describes experiences with developing a commercial herd health advisory tool based on the history of the research tool - SimHerd.

Udgivelsesdato: 2. marts 2010 Diseases to the cow's hoof, interdigital skin and legs are highly prevalent and of large economic impact in modern dairy farming. In order to support farmer's decisions on preventing and treating lameness and its underlying causes, decision support models can be used to predict the economic profitability of such actions. An existing approach of modelling lameness as one health disorder in a dynamic, stochastic and mechanistic simulation model has been improved in two ways. First of all, three underlying diseases causing lameness were modelled: digital dermatitis, interdigital hyperplasia and claw horn diseases. Secondly, the existing simulation model was set-up inwaythat it uses hyper-distributions describing diseases risk of the three lameness causing diseases. By combining information on herd level risk factors with prevalence of lameness or prevalence of underlying diseases among cows, marginal posterior probability distributions for disease prevalence in the specific herd are created in a Bayesian network. Random draws from these distributions are used by the simulation model to describe disease risk. Hereby field data on prevalence is used systematically and uncertainty around herd specific risk is represented. Besides the fact that estimated profitability of halving disease risk depended on the hyper-distributions used, the estimates differed for herds with different levels of diseases risk and reproductive efficiency.

Udgivelsesdato: November 2009 Cross sectional data on the prevalence of claw and (inter) digital skin diseases on 4854 Holstein Friesian cows in 50 Danish dairy herds was used in a Bayesian network to create herd specific probability distributions for the presence of lameness causing diseases.Parity and lactation stage are identified as risk factors on cow level, for the prevalence of the three lameness causing diseases digital dermatitits, other infectious diseases and claw horn diseases. Four herd level risk factors have been identified; herd size, the use of footbaths, a grazing strategy and total mixed ration. Besides, the data has been used to estimate the random effect of herd on disease prevalence and to find conditional probabilities of cows being lame, given the presence of the three diseases. By considering the 50 herds representative for the Danish population, the estimates for risk factors, conditional probabilities and random herd effects are used to formulate cow-level probability distributions of disease presence in a specific Danish dairy herd. By step-wise inclusion of information on cow- and herd-level risk factors, lameness prevalence and clinical diagnosis of diseases on cows in the herd, the Bayesian network systematically adjusts the probability distributions for disease presence in the specific herd. Information on population-, herd- and cow-level is combined and the uncertainty in inference on disease probability is quantified.

Udgivelsesdato: August 2008

In a cross-sectional study, performed between October 2002 and April 2003 on 55 Danish dairy herds with 6161 predominantly Holstein Friesian cows the prevalence of 9 hoof lesions was determined. All test-day yields (TDY) of kg energy corrected milk (ECM) in the lactation of diagnosis were recorded. For the purpose of including hoof lesions in a decision support model an attempt was made to aggregate the lesions into digital dermatitis (DD), other interdigital diseases (OID, infectious diseases other than DD) and hoof horn diseases (HHD, related to metabolic disorders and trauma). A division was made based on the stage of lactation in which the lesions were diagnosed; during the first 100 days in milk, between days 101 and 200 and between days 201 and 305. Associations between the presence of hoof lesions at trimming and milk production were analyzed by linear mixed modeling at the cow level, clustered within herd. The data of primiparous cows was analyzed separately from the multiparous cows. Based on the associations between TDY and the individual lesions aggregated into HHD, this aggregation as initially planned could not be justified and was therefore not maintained. For OID the value of early diagnosis was apparent; an early diagnosis and early treatment (

From an economic point of view, clinical lameness is considered to be one of the major health disorders in dairy cattle. The aim of this study was to establish the costs of lameness in different herds and to improve decision-making on prevention and control of clinical lameness. Economically feasible strategies of prevention and control were defined and the potential effects were calculated by a dynamic, stochastic and mechanistic Monte Carlo model, called SimHerd. The modelled risk factors on cow level for lameness were base-risk in the herd, parity, milk yield potential, disease interrelationship, disease recurrence and season. Milk yield reduction, reduced feed intake, weight loss, reduced conception rate and mortality were modeled as effects of lameness. To study the effect of herd differences on the efficacy of the preventive methods, four different herds representing different levels of reproductive management, conception rates and milk production were designed and compared to the default situation. The loss per first case of lameness was found to be €192 in the default herd that represents the modern, average Danish dairy herd. An increase of the margin per cow-year of €22.7 was the result of halving the risk of lameness in the default herd. Implementation of footbaths and rubber flooring increased margin per cow-year by €4.2 and €17, respectively. In a sensitivity analysis, 16 model parameters were changed to their lowest and highest value found in the literature. The model seemed most sensitive to the uncertainty of the effect of lameness on milk yield.