MODELING GRAPEVINE PHENOLOGY AGAINST WEATHER - CONSIDERATIONS BASED ON A LARGE DATA SET

Phenological data for 11 districts, 12 varieties and four seasons were modelled against averages of daily records of maximum and minimum tem peratures and wet bulb depression. Weather data were taken from the ne arest government weather station, which was commonly up to 10 km from the vineyard. The use of so-called 'heat degree day' methods (e.g. Win kler et al., 1974) were abandoned because the inherent correlation bet ween elapsed time and the value of an accumulation confounds regressio n procedures and interpretation; averages, rather than accumulations, were used as variates in all regressions. The model of budburst involv ed small district and year effects, and accounted for 94.5% of the var iation in the data. This demonstrated that off-site weather data can p rovide effective models. Models of flowering and harvest accounted for 89.2% and 92.5% of the variation in the data respectively, but involv ed large district and year effects. Averages of weather taken from 3 w eeks or more prior to all events were significantly associated with th e dates of those same events. The wet bulb depression provided signifi cant and useful variates in the model of budburst. In addition to othe r associations, the date of flowering was significantly associated wit h the weather conditions prior to budburst. Likewise, the date of harv est was significantly associated with weather conditions prior to both budburst and flowering. Budburst and harvest dates were also associat ed with averages of weather taken over the 10 days just before the eve nt. The variety of these associations encourages the use of a wider ra nge of variates than is common in phenological studies. The district a nd year effects in the case of the flowering and harvest models could result from the complicated effect of the canopy on vine microclimate, or the influence of short term weather events such as storms, or, in the case of harvest, they could result from imprecise definitions of m aturity. Time series methods are advocated as a means to cope better w ith short term weather events and also to facilitate physiological int erpretation of phenological models.