Apple variety identification by dielectric spectrum technology
In order to quickly,accurately and non-destructive identify apple varieties,promote the rapid development of the apple industry,and highlight the advantages of high-quality apple varieties,this paper adopted dielectric spectrum technology for apple variety identification.Three varieties of'Red Fuji'apples from Aksu region were selected as the research objects,and 120 ap-ple samples were collected using LCR digital testing equipment with dielectric spectrum data at 0-100 kHz as the original input parameters.Under the optimal frequency conditions of full frequency and continuous projection algorithm,a variety recognition model was established by using two methods:error backpropagation network and extreme learning machine.Further,the accuracy of the methods was analyzed and compared.The results show that the average accuracy of the established models is above 80%,and the classification accuracy of the two models under frequency optimization conditions can reach 90%.However,the above model methods contain redundant information which undermines the stability of the model.Based on this,an one-dimensional convolutional neural network variety classification model was designed.Compared with other models,the new model uses raw pa-rameters as input,and the average classification accuracy in the correction set and prediction set is 98.48%and 99.26%,re-spectively.The new model has better stability,simplifies model complexity,improves the accuracy and stability of apple classifi-cation,and is more suitable for identifying apple varieties.
variety identificationAksu applesdielectric spectrumfeature frequencyclassification model
万方数据
维普
