Applying Electronic Nose Based on Odour Classification and Identification Technology in Detecting the Shelf Life of Fresh Fruits

• Main Authors: Hongyan Shen, Jia Tao
• Format: Article
• Language: English
• Published: AIDIC Servizi S.r.l. 2018-10-01
• Series: Chemical Engineering Transactions
• Online Access: https://www.cetjournal.it/index.php/cet/article/view/9071

The purpose of this study is to improve the market competitiveness and food safety of fresh fruit products. To this end, the methods of literature analysis, comparative analysis and experimental detection were adopted and the electronic nose (e-nose) technology based on odour classification and identification was introduced to study the non-destructive testing (NDT) method for the shelf life of fresh fruits. Besides, according to the optimized e-nose sensor array, the support vector machine (SVM), BP neural network model and the chlorophyll prediction model for the shelf life detection of fresh fruits were established respectively to make spinach freshness grade discrimination and chlorophyll quantitative prediction by taking the spinach as example. Finally, the experimental results show that the e-nose technology based on odour classification and identification can better realize the shelf life detection of fresh fruit.