Identification of chinese herbal medicines from zingiberaceae family using feature extraction and cascade classifier based on response signals from e-nose.

Lian Peng,Rudolf Bauer,Zhi-Yu Ren,Su-Rong Yan,Yong Liu,Ou Tao,Hui-Qin Zou,Yong-Hong Yan,Jia-Hui Li,Yu Han

doi:10.1155/2014/963035

Abstract

Identification of Chinese herbal medicines (CHMs) by human experience is often inaccurate because individual ability and external factors may influence the outcome. However, it might be promising to employ an electronic nose (E-nose) to identify them. This paper presents a rapid and reliable method for identification of ten different species of CHMs from Zingiberaceae family based on their response signals from E-nose. Ten Zingiberaceae CHMs were measured and their maximum response values were analyzed by principal component analysis (PCA). Result shows that E Zhu (Curcuma phaeocaulis Val.) and Yi Zhi (Alpinia oxyphylla Miq.) could not be distinguished completely by PCA. Two solutions were proposed: (i) using BestFirst+CfsSubsetEval (BC) method to extract more discriminative features to select sensors with higher contribution rate and remove the redundant signals; (ii) employing a novel cascade classifier with two stages to enhance the distinguishing-positive rate (DPR). Based on these strategies, six features were extracted and used in different stages of the cascade classifier with higher DPRs.

Highlights

Chinese herbal medicines (CHMs) are getting more and more international attention owing to their in vivo antitumor activities [1], alternative treatment for menopausal hot flushes [2], inhibition of cancer-related inflammation [3], and so on
This paper presents a two-stage cascade classifier with radial basis function (RBF) and random forests (RF) for distinguishing those different CHMs from Zingiberaceae family
The results of ANOVA and multivariance analysis showed that the suitable quantity of sample for measurement is 0.4 g and the particle size and incubation temperature mainly influence the responses of most Metal oxide semiconductor principal component analysis (PCA) (MOS) (MOS 2–MOS 12)

Summary

Introduction

Chinese herbal medicines (CHMs) are getting more and more international attention owing to their in vivo antitumor activities [1], alternative treatment for menopausal hot flushes [2], inhibition of cancer-related inflammation [3], and so on. Accurate medication of CHMs is an important issue as their global use is increasing rapidly. It is urgent and necessary to establish rapid, accurate, and convenient methods for CHMs identification. CHMs are authenticated by a human experience panel called macroscopic identification, which considers the morphologic characteristics (shape, color, etc.) and the organoleptic properties (odor, taste, etc.) through observing, touching, smelling, and tasting. In Pharmacopoeia of the People’s Republic of China, this macroscopic identification is still an important aspect of CHMs quality evaluation. Sha Ren (dried fructus of Amomum villosum Lour.) with large size and strong odor should be superior in quality. This method is expensive and time-consuming and inaccurate because of its low sensitivity and lack of quantitative information. Electronic nose (E-nose) is a rapid, reliable, and robust technology and could be employed as easy-to-use and cost-efficient technology

Methods

Results

Conclusion