Development and validation of decision support methodology for control of barley yellow dwarf virus
About this project
The objective of the project was to develop an effective, user-friendly, field specific system for assessing the need to control the aphid vectors of BYDV. An existing regional scale trapping system is used to assess how many winged aphids carrying the virus enter crops in autumn (primary infection). A mathematical model was developed under MAFF funding to capture the effect of weather on the development, reproduction, movement and survival of aphids and this is used to determine how much secondary spread of the virus there has been from the initial foci. The model was tested against independent data collected at three sites. To assess how the regional risk translatesto a field-specific risk a major survey was done to examine the characteristics of fields, which make them prone to BYDV problems. The whole system is designed to fit within the DESSAC decision support system.
Epidemiology of BYDV in the UK
BYDV is transmitted only by aphids. The main vectors in the UK are the bird cherry - oat aphid (Rhopalosiphum padi) and the grain aphid (Sitobion avenae). PAV is the most common isolate but MAV and RPV are also present. Virus enters crops as a result of winged aphids flying in from reservoir hosts, which comprise many grass species. Direct transfer from previous crops or volunteers may also occur but this is not considered here. Spread of the virus is a result of offspring of the colonisers moving through the crop when conditions permit.
Measuring primary infection
Suction traps are used to record numbers of aerial bird cherry - oat aphids in autumn. Numbers alighting per unit area of crop are estimated from the significant relationship found between numbers in suction traps and numbers on sticky wire traps placed directly over crops. The proportion of these that comprises the colonising female form and the proportion carrying virus is estimated from past averages. Numbers of aphids per plant are calculated on the basis of planting density. The number of foci of infection is adjusted according to the expected number of within-crop flights made by alighting individuals on the basis of laboratory trials. A constant low rate of colonisation of grain aphid is assumed as numbers are below levels for reliable quantification using suction traps.
Modelling virus spread
The model unit is a single plant. Virus isolates are not distinguished. The model is temperature driven and aphids grow, reproduce, move and die on the basis of algorithms developed from experimentation within this project and from the literature. The effects of temperature on virus acquisition and inoculation efficiencies and latent periods are also accounted for. Rain and wind are not yet included as driving variables. Output is currently in the form of percentage plants infected. Yield and economic data are not yet incorporated. A sensitivity analysis identified the number of infectious winged aphid immigrants, dispersal rate of wingless aphids, low temperature aphid mortality and virus latent period in the plant as the most critical factors.
The model output for aphid and virus incidence was tested against independent data collected from small plots at three contrasting sites over two years for two of the sites and one year for the other. Subplots were sprayed at different times during the autumn and winter to halt further spread of BYDV, and BYDV incidence was assessed in spring. Aphid populations were simulated well in three of the five trials, but were lower than predicted in the other two. Final virus incidence was predicted well in the same three trials but its progress curve was not always predicted accurately
Over three growing seasons, 623 unsprayed cereal crops were surveyed in autumn for aphid abundance and in spring for BYDV incidence. Values for forty five categories of field characteristic were recorded and a multivariate analysis used to assess their relationships with aphids and BYDV. Aphid and virus incidences were strongly correlated. There was more BYDV (P<0.01) in earlier sown crops, crops closer to the sea, crops around which arable land was less dominant, and in east (MAV) and south west (PAV) facing crops.
Development of a decision support system (DSS)
The model will run under the DESSAC decision support system and there has been close liaison with the DESSAC team. The model needs to be greatly simplified in order to run fast enough within the DSS. Further quantification of aphid winter mortality is needed. There remain difficulties in monitoring colonising S. avenae. The next stage is to test the model on a commercial scale.
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