evaluation of winter chill requirement models using the observed apple tree phenology data in kahriz (urmia, iran)

the flowering phase of apple trees is the most critical step in relation with low temperatures and frost events. therefore, forecasting the time of flowering is important. if a model can predict the exact time of flowering, it would be feasible to care for flowers agianst late spring freezing (lsf). in this study, we evaluated three temperature-base chilling models namely: chilling hours (ch), utah model (um) and dynamic model (dm) versus the observed phenological records of apple tree (13 years) in kahriz (urmia, iran). the said models were applied to explain their efficiency and ability for predicting apple phenological dates. the study was performed for apple cultivars in kahriz station by using phenological observations, daily minimum temperature and maximum screen temperature data (2002-2014). the winter chilling was determined by the three chilling models and remaining heat was estimated using the growing degree hour concept. the model results showed that the dynamic model (dm) performed the best results in explaining apple flowering phenology stage with rmse of lower than four days and relative errors less than 3%. meanwhile, the probability of lsf was estimated by statistical distributions. by comparing the probability of frost occurrence with the date of the predicted flowering date, the risk of frost damage on apple flowering was determined. the results demonstrated that early flowering varieties, which their flower buds are activated before 25th of march, are exposed to lsf risk, with probability of 50 percent.