Forecasting Different Phenological Phases of Apple Using Artificial Neural Network

Apple is one of the oldest trees in the world which is widely cultivated because of it’s highlycompatibility with various climatic conditions. In this study, we applied phenological statistics ofagricultural meteorology of Golmakan to anticipate different phonologic phases of apple usingintelligent neural network. At first the matrix of input data which is consisting of climatic parameterssuch as minimum temperature, maximum temperature, the mean of daily temperature, absoluteminimum temperature, and absolute maximum temperature has been established. The range oftemperature changes, growing days and timed chilling unit (in silver tip phase) had been prepared fordifferent phenological stages during 1999-2005; then the matrix of out coming data which, in fact,were the occurrence dates of different phenological stages of apple was prepared and the modeling ofdifferent phenological stages was performed by using neural network. In this study the accuracy ofmodel was examined by using RMSE index and by contrasting real and anticipation dates during 2years. For this purpose observed climatic and phenological data was also used in similar Figure at outof investigating zone. It’s also specified we could anticipate phenological stages of apple withacceptable accuracy using climatic parameters.

Keywords:

Phenology , Apple , Climate , Neural network