BYDV PREDICTOR: a simulation model to predict aphid arrival, epidemics of Barley yellow dwarf virus and yield losses in wheat crops in a Mediterranean-type environment

• Published in: Plant pathology 2009-02, Vol.58 (1), p.186-202
• Main Authors: Thackray, D.J, Diggle, A.J, Jones, R.A.C
• Format: Article
• Language: English
• Subjects: Agronomy. Soil science and plant productions; Aphididae; Barley yellow dwarf virus; Biological and medical sciences; BYDV-PAV; decision support system; decision support systems; Fundamental and applied biological sciences. Psychology; Phytopathology. Animal pests. Plant and forest protection; Plant viruses and viroids; Protozoa. Invertebrates; Rhopalosiphum padi; Triticum aestivum; virus/aphid vector pathosystem
• ISSN: 0032-0862; 1365-3059
• DOI: 10.1111/j.1365-3059.2008.01950.x

BYDV PREDICTOR, a simulation model, was developed to forecast aphid outbreaks and Barley yellow dwarf virus (BYDV) epidemics in wheat crops in the grainbelt region of southwest Australia, which has a Mediterranean-type climate. The model used daily rainfall and mean temperature to predict aphid (Rhopalosiphum padi) buildup in each locality before the commencement of the cereal-growing season in late autumn, and to forecast the timing of aphid immigration into crops. The introduction of BYDV by aphid immigrants, aphid buildup within the crop, spread of BYDV, and yield losses were predicted for different sowing dates. The model simulations were validated with 10 years' field data from five different sites in the grainbelt, representing a wide range of scenarios. When first aphid arrival dates ranging from 1 June to 2 September were compared with predictions, 65% of the variation between sites and years was explained. Progress curves for the predicted percentage of plants infected with the serotype BYDV-PAV closely resembled the starting point and shape of those recorded in 14 out of 18 scenarios. Sensitivity analysis confirmed that the combination of a high proportion of immigrants vectoring BYDV, early sowing of crops and early start to aphid arrival relative to sowing date led to the most BYDV spread and greatest yield loss. The model was incorporated into a decision support system used by farmers in targeting sprays against aphids to prevent virus spread in autumn and winter. BYDV PREDICTOR could serve as a template for modelling similar virus/aphid vector pathosystems in other regions of the world, especially those with Mediterranean-type climates.