Abstract: There are many varieties of jujube in Xinjiang, so it is necessary to distinguish different varieties before processing.Aiming at the problems of low efficiency and high cost of manual classification and difficult to ensure the comprehensive quality of mechanical classification, a classification and identification method of jujube varieties based on Stacking model fusion was proposed.11 280 jujube images of 5 categories were collected and preprocessed to establish a data set.A model that three different convolution neural network（VGG 16,ResNet 50,DenseNet 121） as base learner and logistic regression as secondary learner were constructed.The comparative experiments were carried out between the integrated model and single neural network model, as well as the integrated model with different combinations of base learners.The results showed that the accuracy of the proposed Stacking model was 92.38%,which was improved by 4.60 percentage points compared with that of the best single model（88.30%）.This method can effectively improve the identification accuracy of jujube varieties and provide reference for Xinjiang jujube from manual sorting to automatic machine identification.