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Accounting for the Economic Risk Caused by Variation in Disease Severity in Fungicide Dose Decisions, Exemplified for Mycosphaerella graminicola on Winter Wheat

First and fourth authors: Biomathematics and Bioinformatics, Rothamsted Research, Harpenden, Hertfordshire, AL5 2 JQ, UK; first author: Centre for Infectious Diseases Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands; second author: ADAS High Mowthorpe, Duggleby, Malton, North Yorkshire, YO17 8BP, UK; and third author: School of Biological Sciences, University of Reading, Reading RG6 6AS, UK.

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.

Additional keywords: disease risk.