Modelling cherry full bloom using 'space-for-time' across climatically diverse growing environments

A dataset of cherry full bloom dates across the full diversity of Australian growing regions was compiled and utilised for the first time. The primary data source was from growers located across Australia's major cherry growing districts. Records were of varying length and were used to investigate the potential of using data that substitute 'space-for-time' in phenology assessments. Full bloom timing for three cultivars, Bing, Lapins and Van, were collated. The data showed variation in full bloom time across the sites as well as inter-annual variability within sites. This highlighted the potential benefit of a predictive model for growers to better manage the flowering period. The performance of the sequential and the chill overlap models were evaluated using this data. Both models resulted in good statistical representation of the data with RMSE of 3.2 to 5.3 days and 3.3 to 5.4 days for the training and validating data, respectively. The parameterisations of the models differed with the sequential model estimating higher chilling requirement (65-68 CP) than the chill overlap model (46-48 CP). The sequential model estimated similar heat requirements between the cultivars, with Van marginally higher (7250-8000 GDH). The chill overlap model estimated a larger difference in the minimum heat requirement with Van higher (8223 GDH) than Bing and Lapins (6262 and 6486 GDH, respectively). Collation of grower records proved to be a valuable data source which, in the absence of funded programs, could be better utilised for further research that aligns outcomes with industry needs, such as decision support around polliniser varieties, design of growing systems and use of dormancy breakers to synchronise flowering for optimal fruit set and quality.