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Forecasting regional apple first flowering using the sequential model and gridded meteorological data with spatially optimized calibration

Lookup NU author(s): Dr Glyn Jones


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© 2022. China is one of the largest apple-producing countries in the world, with large orchards and diverse climates. Accurately forecasting the first-flowering time of apple trees can assist orchard managers in their deciding when to apply anti-freeze. The temperature-driven sequential model from previous studies can be used to forecast the flowering phenology of deciduous fruit trees. However, this model requires many years of observational data for calibration, so flowering forecasts based on traditional phenological models cannot be implemented in areas that lack such historical data. To overcome this problem, the present work combines a spatial rather than a temporal phenological survey method with 1-km-gridded temperature products to calibrate the chill and heat requirement parameters of the sequential model. We then use the model to forecast the first-flowering on a regional scale for Luochuan and Linyi, which are two main apple-producing areas of China. The results show that the proposed method accurately forecasts regional flowering. The root mean squared errors (RMSE) for Luochuan and Linyi were 4.7 and 4.4 days, respectively, and the normalized RMSEs were all less than 5.19%. We expect the proposed regional first-flowering forecast method to be an important aid to optimize orchard management.

Publication metadata

Author(s): Zhu Y, Yang G, Yang H, Guo L, Xu B, Li Z, Han S, Zhu X, Li Z, Jones G

Publication type: Article

Publication status: Published

Journal: Computers and Electronics in Agriculture

Year: 2022

Volume: 196

Print publication date: 01/05/2022

Online publication date: 18/03/2022

Acceptance date: 11/03/2022

ISSN (print): 0168-1699

ISSN (electronic): 1872-7107

Publisher: Elsevier BV


DOI: 10.1016/j.compag.2022.106869


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