Predicting olive flowering phenology with phenoclimatic models
In plants, day length and temperature are the major climatic factors that affect the transition from a phenological phase to the next one. Non-linear models, such as growing degree hours (GDH), have been successfully used to calculate thermal time required for spring bud burst in deciduous fruit trees. In this experiment, temperature records and blooming dates of olive trees in different years and for 10 different sites in the Italian territory were recorded. Olive booming time was correlated to the amount of (GDH) accumulated from the date of bud rest onset, calculated as the day when the maximum negative chilling units accumulation was reached (UTAH Model), to full bloom. The GDH model was optimised generating 200 random sets of parameters (cardinal temperatures) and calculating for each set the best fit in terms of blooming date forecast. The best bloom prediction model resulted when a base temperature of 5°C, an optimum temperature of 33°C and a critical temperature of 33.1°C were used. Taking into account the rest-to-bloom period, the accuracy of the GDH model in predicting blooming time was high. An accurate early forecast of blooming time was obtained using an olive rest-to-bloom thermal time requirement of about 29.000 GDH.
Marra, F.P., Macaluso, L., Marino, G. and Caruso, T. (2018). Predicting olive flowering phenology with phenoclimatic models. Acta Hortic. 1229, 189-194
phenologycal models, thermal time, olive blooming forecasting, cardinal temperatures