Prediction of disease risk using site-specific estimates of weather variables

Abstract

To improve the implementation of weather-based disease risk models, a spatial interpolation method was investigated to provide weather estimates for specific sites. Two sites in the HortResearch horticultural weather station network, one in Marlborough and one in Hawke's Bay, were selected as validation sites. Interpolated weather data were estimated for these sites from November to March in 2003-04 and 2004-05, using actual weather data from nearby stations that were selected as natural neighbours using the geometrical technique, Voronoi tessellation. Wetness duration was also estimated using interpolated weather data as inputs to an empirical wetness model. Air temperature estimates were comparable to actual measurements but wetness duration was overestimated. When interpolated and actual data were used as inputs to the grape botrytis model, Bacchus, predicted risks were comparable to each other for short periods rather than the whole growing season. This suggests that risk of botrytis bunch rot could be predicted reliably at a specific site using the spatial interpolation method.