Temperature is one of the main factors affecting the flowering of Mediterranean trees. In the case of Olea europaea L., a low-temperature period prior to bud development is essential to interrupt dormancy. After that, and once a base temperature is reached, the plant accumulates heat until flowering starts. Different methods of obtaining the best-forecast model for the onset date of the O. europaea pollen season, using temperature as the predictive parameter, are proposed in this paper. An 18-year pollen and climatic data series (1982-1999) from Cordoba (Spain) was used to perform the study. First a multiple-regression analysis using 15-day average temperatures from the period prior to flowering time was tested. Second, three heat-summation methods were used, determining the the quantities heat units (HU): accumulated daily mean temperature after deducting a threshold, growing degree-days (GDD): proposed by Snyder [J Agric Meteorol 35:353-358 (1985)] as a measure of physiological time, and accumulated maximum temperature. In the first two, the optimum base temperature selected for heat accumulation was 12.5 degrees C. The multiple-regression equation for 1999 gives a 7-day delay from the observed date. The most accurate results were obtained with the GDD method, with a difference of only 4.7 days between predicted and observed dates. The average heat accumulation expressed as GDD was 209.9 degrees C days. The HU method also gives good results, with no significant statistical differences between predictions and observations.

No abstract

Data on predicted average and maximum airborne pollen concentrations and the dates on which these maximum values are expected are of undoubted value to allergists and allergy sufferers, as well as to agronomists. This paper reports on the development of predictive models for calculating total annual pollen output, on the basis of pollen and weather data compiled over the last 19 years (1982-2000) for Córdoba (Spain). Models were tested in order to predict the 2000 pollen season; in addition, and in view of the heavy rainfall recorded in spring 2000, the 1982-1998 data set was used to test the model for 1999. The results of the multiple regression analysis show that the variables exerting the greatest influence on the pollen index were rainfall in March and temperatures over the months prior to the flowering period. For prediction of maximum values and dates on which these values might be expected, the start of the pollen season was used as an additional independent variable. Temperature proved the best variable for this prediction. Results improved when the 5-day moving average was taken into account. Testing of the predictive model for 1999 and 2000 yielded fairly similar results. In both cases, the difference between expected and observed pollen data was no greater than 10%. However, significant differences were recorded between forecast and expected maximum and minimum values, owing to the influence of rainfall during the flowering period.

No abstract

The influence of meteorological factors on daily Urticaceae pollen counts were studied in Córdoba (southwest Spain) in 1996 and 1997. The daily Urticaceae pollen concentrations were obtained by using a Hirst-type volumetric sampler, and meteorological data were obtained from the Córdoba airport, located near the sampling site. The highest correlation between pollen concentration and meteorological parameters was obtained during non-rainy seasons. Temperature was found to be the most important meteorological parameter influencing pollen counts in spring, as temperature is the main reason for the increase of pollen concentration in the atmosphere. In autumn, humidity was another important parameter influencing pollen counts. Rain, however, did not appear to be significant. The influence of the pollen concentration of the 2 previous days and the pollen concentration of the previous day has been studied. During periods with low precipitation, the pollen concentration of the previous day was a useful predictor of Urticaceae pollen concentrations for the following day.