A PROPRIETARILY DEVELOPED BIONIC OLFACTORY SYSTEM USED FOR RAPID DETECTION OF DETERIORATED REFRIGERATED-STORED APPLES

Hui Tian, Wenshen Jia, Jie Ma, Jihua Wang, and Jianxiong Hao

Keywords

Electronic nose, sensor, principal component analysis, bake propagation neural network

Abstract

To reduce huge economic losses caused by apple deterioration to growers and dealers, a high-sensitivity, low-cost portable electronic nose detection system used for rapid detection and early-warning of apple deterioration was designed. The system comprises an electro- chemical sensor array, data collection and transmission module and human–machine interaction software. Firstly, data collected by the electronic nose was pre-processed with smoothing filtering proce- dures, then a non-destructive detection model for refrigerated-stored apples was constructed on the basis of bionic olfactory technology in combination with bionics, principal component analysis (PCA), algorithms of kernel principal component analysis (KPCA), back- propagation neural network (BPNN) and support vector machine (SVM). The experiment results show that seven-point smoothing filtering can produce better outcomes, and models on the basis of backpropagation (BP), SVW, PCA+SVM and KPCA+SVM all reach a correct recognition rate of more than 90%, with correct recognition rates of PCA+SVM being higher than those of BP, SVM and KPCA+SVM. This research provides significant reference value for research focusing on electronic nose applied in non-destructive rapid detection and early-warning of apples.

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