Age identification of Chinese rice wine using electronic nose
by Wei Ding; Peiyi Zhu; Ya Gu
International Journal of Computer Applications in Technology (IJCAT), Vol. 63, No. 3, 2020

Abstract: This paper is concerned with the identification of the age of Chinese rice wine. To address this problem, a new electronic nose system with the multivariate analysis method based on the artificial olfactory technique is developed. First, four features are extracted to represent the dynamic behaviour of the signal that is generated from the array of the Taguchi Gas Sensor (TGS) deployed in the volatile substance of the rice wine. Then, the Principal Component Analysis (PCA), the Linear Discriminant Analysis (LDA) and the error Back Propagation Neural Network (BPANN) are combined to build a model for the identification of the age of Chinese rice wine. The results show that the LDA model fails to distinguish the Chinese wine with a one-year age difference in the proposed electronic nose system, whose accuracy of training and prediction are 98.44% and 96.88%, respectively. By contrast, the optimised BPANN model is capable of identifying the age of the Chinese wine and achieves the accuracy of 100% in the training and the prediction sets. It is verified that the self-designed electronic nose with the optimised BPANN is valuable on the application of the age prediction of Chinese rice wine.

Online publication date:: Thu, 03-Sep-2020

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computer Applications in Technology (IJCAT):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com