Apple leaf alternaria leaf spot leaf rate prediction system based on meteorological factors

The invention discloses a meteorological factor-based apple leaf alternaria leaf rate prediction system, which comprises the following steps of: acquiring historical apple leaf alternaria leaf rate information and meteorological information of a researched orchard and establishing a data set; performing correlation analysis on characteristic values and target values in the preprocessed data set to obtain main meteorological factors influencing the diseased leaf rate; and taking the obtained meteorological factors as features and the leaf rate as a target, establishing a prediction model by using a bidirectional long-short-term memory network sequential sequence prediction network method, predicting the leaf rate of alternaria leaf spot under the condition of known meteorological factors, and finally designing a system interface by using a PyQt interface development tool according to the prediction model to obtain a prediction system. According to the method, accurate prediction of the leaf rate of apple leaf