Exploring individual responses to welfare issues in growing-finishing pig feeding behaviour.

The feeding behaviour of individual growing-finishing pigs can be continuously monitored using sensors such as electronic feeding stations (EFSs), and this could be further used to monitor pig welfare. To make accurate conclusions about individual pig welfare, however, it is important to know whether deviations in feeding behaviour in response to welfare issues are shown only on average or by each individual pig. Therefore, this study aimed (1) to quantify the individual variation in feeding behaviour changes in response to a range of welfare issues, and (2) to explain this individual variation by quantifying the responses to welfare issues for specific subgroups of pigs. We monitored four rounds of 110 growing-finishing pigs each (3-4 months per round). We collected feeding behaviour data using IVOG® EFSs and identified health issues and heat stress using climate sensors and twice-weekly health observations. For each pig, a generalised additive model was fitted, which modelled feeding behaviour through time and estimated the effect of each welfare issue that the pig had suffered from. The range of these effect estimates was compared between pigs to study the individual variation in responses. Subsequently, pigs were repeatedly grouped using physical and feeding characteristics, and, with meta-subset analysis, it was determined for each group whether a deviation in response to the welfare issue (i.e. their combined effect estimates) was present. We found that the range in effect estimates was very large, approaching normal distributions for most combinations of welfare issues and feeding variables. This indicates that most pigs did not show feeding behaviour deviations during the welfare issue, while those that did could show both increases and reductions. One exception was heat stress, for which almost all pigs showed reductions in their feed intake, feeding duration and feeding frequency. When looking at subgroups of pigs, it was seen that especially for lameness and tail damage pigs with certain physical characteristics or feeding strategies did consistently deviate on some feeding components during welfare issues (e.g. only relatively heavier pigs reduced their feeding frequency during lameness). In conclusion, while detection of individual pigs suffering from heat stress using feeding variables should be feasible, detection of (mild) health issues would be difficult due to pigs responding differently, if at all, to a given health issue. For some pigs with specific physical or behavioural characteristics, nevertheless, detection of some health issues, such as lameness or tail damage, may be possible.

Accounting for the economic risk caused by variation in disease severity in fungicide dose decisions, exemplified for Mycosphaerella graminicola on winter wheat.

A method is presented to calculate economic optimum fungicide doses accounting for the risk aversion of growers responding to variability in disease severity between crops. Simple dose-response and disease-yield loss functions are used to estimate net disease-related costs (fungicide cost plus disease-induced yield loss) as a function of dose and untreated severity. With fairly general assumptions about the shapes of the probability distribution of disease severity and the other functions involved, we show that a choice of fungicide dose which minimizes net costs, on average, across seasons results in occasional large net costs caused by inadequate control in high disease seasons. This may be unacceptable to a grower with limited capital. A risk-averse grower can choose to reduce the size and frequency of such losses by applying a higher dose as insurance. For example, a grower may decide to accept "high-loss" years 1 year in 10 or 1 year in 20 (i.e., specifying a proportion of years in which disease severity and net costs will be above a specified level). Our analysis shows that taking into account disease severity variation and risk aversion will usually increase the dose applied by an economically rational grower. The analysis is illustrated with data on Septoria tritici leaf blotch of wheat caused by Mycosphaerella graminicola. Observations from untreated field plots at sites across England over 3 years were used to estimate the probability distribution of disease severities at mid-grain filling. In the absence of a fully reliable disease forecasting scheme, reducing the frequency of high-loss years requires substantially higher doses to be applied to all crops. Disease-resistant cultivars reduce both the optimal dose at all levels of risk and the disease-related costs at all doses.

Exposure of uninfected poultry farms to HPAI (H7N7) virus by professionals during outbreak control activities.

With an extensive data set on visits made to control the H7N7 avian influenza epidemic in The Netherlands in 2003 we investigate the potential role of the persons involved in the control activities as vectors for disease transmission. We hypothesized that people can spread the virus on the same day mechanically, or till 10 days if they have become infected themselves. Taken into account was the estimated time of introduction of the virus into a poultry flock back-calculated from mortality data. We identified 19 visits from a person that went on the same day from an infected (source) farm to a (target) farm that was before infection and a further 197 visits were made to (target) farms that remained uninfected. Of the 19 visits, eight were made within 3 days before an infection started on the target farm. If we assume that these eight visits were the primary reason the visited farms became infected, then we can calculate an upper estimate for the probability of transmission by a person per visit of 0.037. In addition we identified visits were a person first visited an infected source farm and up to 10 days after visited a target farm that either remained uninfected or was before infection. Most visits to infected source farms were made just after infection. Animals on these farms were likely not yet symptomatic, thus escaping diagnosis. Such events may be difficult to prevent, although awareness of this possibility is already a major step towards prevention. Most of these visits involved tracing and screening and were made by a relatively small number of trained veterinarians. This makes it possible to focus training efforts specifically on these persons and make sure they stringently use the personal protective equipment and strictly follow the hygiene protocol, to protect them and prevent them from spreading the disease.

Disease-weather relationships for powdery mildew and yellow rust on winter wheat.

Key weather factors determining the occurrence and severity of powdery mildew and yellow rust epidemics on winter wheat were identified. Empirical models were formulated to qualitatively predict a damaging epidemic (>5% severity) and quantitatively predict the disease severity given a damaging epidemic occurred. The disease data used was from field experiments at 12 locations in the UK covering the period from 1994 to 2002 with matching data from weather stations within a 5 km range. Wind in December to February was the most influential factor for a damaging epidemic of powdery mildew. Disease severity was best identified by a model with temperature, humidity, and rain in April to June. For yellow rust, the temperature in February to June was the most influential factor for a damaging epidemic as well as for disease severity. The qualitative models identified favorable circumstances for damaging epidemics, but damaging epidemics did not always occur in such circumstances, probably due to other factors such as the availability of initial inoculum and cultivar resistance.