Optimising the number of replacement heifers needed will have positive economic and environmental consequences on herds that rear their own young stock. The number of heifers needed to be kept is closely related with the number of culled dairy cows in the herd. This study therefore looked at the variation that exists in culling rate and herd level factors associated with it. A dataset from 1903 dairy herds available included information at animal level (dates of culling, slaughter/death) and herd level (characteristics of reproduction, performance, health) over the years 2007 to 2010. The average culling rate for slaughter/death was used and was defined for each year as percentage of the herd size that died within 30 d after they were culled. The analysis of the association between average culling rate for slaughter/death and the characteristics of the herd was performed using a mixed model. The results showed that the average culling rate for slaughter/death was 25·4% and varied between 23% (2007) and 28% (2010). More than 70% of the herds have an average culling rate for slaughter/death of less than 30%, showing that there is room for lowering the average culling rate for slaughter/death. A higher average culling rate for slaughter/death is associated with a longer average calving interval, a higher average 305-d protein production, a higher average somatic cell count (SCC), a higher percentage of new high SCC, a more than 5% decrease in herd size, and herds that bought more than 1% of animals per year. A lower average culling rate for slaughter/death is associated with a longer average age, herds that bought less than 1% of animals per year and a more than 5% increase in herd size. In conclusion, the average culling rate for slaughter/death is associated with fertility, udder health and openness of the herd.

Many governments have signed up to greenhouse gas emission (GHGE) reduction programmes under their national climate change obligations. Recently, it has been suggested that the use of extended lactations in dairy herds could result in reduced GHGE. Dairy GHGE were modelled on a national basis and the model was used to compare emissions from lactations of three different lengths (305, 370 and 440 days), and a current ‘base’ scenario on the basis of maintaining current milk production levels. In addition to comparing GHGE from the average ‘National Herd’ under these scenarios, results were used to investigate how accounting for lactations of different lengths might alter the estimation of emissions calculated from the National Inventory methodology currently recommended by Intergovernmental Panel on Climate Change. Data for the three lactation length scenarios were derived from nationally recorded dairy performance information and used in the GHGE model. Long lactations required fewer milking cows and replacements to maintain current milk yield levels than short ones, but GHGEs were found to rise from 1214 t of CO2 equivalent (CE)/farm per year for lactations of 305 days to 1371 t CE/farm per year for 440-day lactations. This apparent anomaly can be explained by the less efficient milk production (kg milk produced per kg cow weight) found in later lactation, a more pronounced effect in longer lactations. The sensitivity of the model to changes in replacement rate, persistency and level of milk yield was investigated. Changes in the replacement rate from 25% to 20% and in persistency by −10% to +20% resulted in very small changes in GHGE. Differences in GHGE due to the level of milk yield were much more dramatic with animals in the top 10% for yield, producing about 25% less GHGE/year than the average animal. National Inventory results were investigated using a more realistic spread of lactation lengths than recommended for such calculations using emissions calculated in the first part of the study. Current UK emission calculations based on the National Inventory were 329 Gg of methane per year from the dairy herd. Using the national distribution of lactation lengths, this was found to be an underestimate by about 10%. This work showed that the current rise in lactation length or a move towards calving every 18 months would increase GHGE by 7% to 14% compared with the current scenario, assuming the same milk yield in all models. Increased milk yield would have a much greater effect on reducing GHGE than changes to lactation length, replacement rate or persistency. National Inventory methodology appears to underestimate GHGE when the distribution of lactation lengths is considered and may need revising to provide more realistic figures.

The objective of this study was to explore the importance of including genetic progress in milk yield when evaluating different reproductive strategies in a dairy herd by simulation modeling. The model used in this study was SimHerd V, a dynamic and mechanistic Monte Carlo simulation model of a dairy herd including young stock. A daily increasing trend describing genetic milk yield potential of the sire population was included in the model. The inaccuracy of assuming that replacement heifers have the same (milk yield) potential as the cows present in the herd was hereby dealt with. Improving estrus detection rate from 0.45 to 0.80 increased gross margin (GM) per cow-year by €20 when genetic progress was not included in the model. When genetic progress was included in the model, then the same improvement in estrus detection decreased the GM per cow-year by €7.4. This reduced effect was explained by a lower replacement rate in consequence of the improved estrus detection and thereby a slower genetic progress in the herd. There was a reduced effect of including genetic progress on GM when surplus heifers were sold selectively based on breeding values. Repeated insemination with sexed semen on the superior half of all heifers reduced GM by €8 per cow-year when genetic progress was not included and increased the GM by €16 per cow-year when genetic progress was included in the model. Including genetic progress reduced the losses caused by lower conception and estrus detection rates and had a minimal effect with regard to postponing first insemination. This study has proven that it is important to include genetic progress in decisions on reproduction strategies in a dairy herd.

The main aim was to assess the impact of mastitis on technical and economic results of a dairy herd under current Swedish farming conditions. The second aim was to investigate the effects obtained by withdrawing milk with high somatic cell count (SCC). A dynamic and stochastic simulation model, SimHerd, was used to study the effects of mastitis in a herd with 150 cows. Results given the initial incidence of mastitis (32 and 33 clinical and subclinical cases per 100 cow-years, respectively) were studied, together with the consequences of reducing or increasing the incidence of mastitis by 50%, modelling no clinical mastitis (CM) while keeping the incidence of subclinical mastitis (SCM) constant and vice versa. Six different strategies to withdraw milk with high SCC were compared. The decision to withdraw milk was based on herd-level information in three scenarios: withdrawal was initiated when the predicted bulk tank SCC exceeded 220 000, 200 000 or 180 000 cells/ml, and on cow-level information in three scenarios: withdrawal was initiated when the predicted SCC in an individual cow’s milk exceeded 1 000 000, 750 000 or 500 000 cells/ml. The accuracy with which SCC was measured and predicted was assumed to affect the profitability of withdrawing milk with high SCC and this was investigated by applying high, low or no uncertainty to true SCC. The yearly avoidable cost of mastitis was estimated at €8235, assuming that the initial incidence of mastitis could be reduced by 50%. This cost corresponded to 5% of the herd net return given the initial incidence of mastitis. Expressed per cow-year, the avoidable cost of mastitis was €55. The costs per case of CM and SCM were estimated at €278 and €60, respectively. Withdrawing milk with high SCC was never profitable because this generated a substantial amount of milk withdrawal that was not offset by a sufficient increase in the average price per delivered kg milk. It had the most negative impact on net return when high incidence of mastitis was simulated. Withdrawing milk with high SCC based on low-uncertainty information reduced the amount of withdrawn milk and thus resulted in less negative effect on net return. It was concluded that the current milk-pricing system makes it more profitable for farmers to sell a larger amount of milk with higher SCC than to withdraw milk with high SCC to obtain payment premiums, at least in herds with mastitis incidences within the simulated ranges.

Enteric and respiratory diseases are the most frequent health disorders of calves. They are associated with mortality or lower growth rate and induce treatment costs. Enteric and respiratory pathogens can be transmitted via contacts between calves, which depend on calf housing systems and management. This study aimed at describing the main calf housing systems across Europe and at assessing the consequences of such housing facilities in terms of risk for calf infectious diseases. This was done through the use of a questionnaire distributed to experts in epidemiology and cattle farming systems in each European country. A literature review was performed on the risk factors associated with calf infectious diseases transmission and targeted in the questionnaire. Answers from 14 countries were obtained. A wide range of housing systems were described. However, four main systems could be identified and ranked in ascending order of risk for neonatal diarrhoea and respiratory infectious diseases: individual pen until weaning, individual pen for 4 weeks, individual pen for 2 weeks, and collective pen from the separation of the calf with its dam. Although the housing systems are known to play a role in disease transmission, they are currently not fully described in literature concerning risk factors for calf infectious diseases. In a given farm, the risk assessment for calf infectious diseases should consider classical risk factors such as hygiene, feeding practices and air conditioning, on top of a precise description of the housing system.

The main aim of the present study was to examine the economic consequences of a reduction in the incidence of clinical mastitis (CM) at herd level under current Swedish farming conditions. A second objective was to ask whether the estimated cost of CM alters depending upon whether the model reflects the fact that in different stages of lactation, CM gives rise to different yield-loss patterns or postulates just one type of yield-loss pattern irrespective of when, during lactation, CM occurs. A dynamic and stochastic simulation model, SimHerd, was used to study the effects of CM in a herd with 150 cows (9000 kg of energy-corrected milk per cow-year). Four herd types, defined by production level and reproductive performance, were modelled to investigate possible interactions between herd type and response to a reduction in the risk of CM. Technical and economic results, given the initial incidence of CM (25.6 per 100 cow-years), were studied together with the consequences of reducing the initial risk of CM by 50% and 90% throughout lactation and the consequences of reducing the initial risk by 50% and 90% before peak yield. A conventional way of modelling yield losses – i.e. one employing a single yield-loss pattern irrespective of when, during the lactation period, the cow develops CM – was compared with a new modelling strategy in which CM was assumed to affect production differently depending on its lactational timing. The effect of the choice of reference level when estimating yield losses was investigated by comparing the results obtained using the potential yield of mastitic cows, had they not developed CM, with those obtained using the yield of non-mastitic cows. The yearly maximum avoidable cost of CM at herd level was estimated at €14 504, corresponding to 6.9% of the net return given the initial incidence of CM. Expressed per cow-year, the maximum avoidable cost was €97. The cost per case of CM was estimated at €428. Herd types all responded in a similar manner to the reduced relative risk of CM. There were no major differences in the results obtained using the new and the conventional modelling strategy, with the exception of the cost per case of CM. Similarities between the results obtained using the two methods were particularly evident when the mastitic cows’ own yield level, had they not developed CM, was used as the reference for production in healthy cows when yield losses were estimated. It was concluded that the conventional way of modelling yield losses is adequate and should, for the foreseeable future, be used in decision support systems.