| Title: | Qualitative and quantitative analysis on aroma characteristics of ginseng at different ages using E-nose and GC-MS combined with chemometrics |
| Author(s): | Cui S; Wang J; Yang L; Wu J; Wang X; |
| Address: | "Department of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, PR China. Department of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, PR China. Electronic address: jwang@zju.edu.cn. Department of Agriculture and Biological Engineering, University of Illinois at Urbana-Champaign, 332 AESB, MC-644, 1304 W. Pennsylvania Avenue, Urbana, IL 61801, USA" |
| DOI: | 10.1016/j.jpba.2014.08.030 |
| ISSN/ISBN: | 1873-264X (Electronic) 0731-7085 (Linking) |
| Abstract: | "Aroma profiles of ginseng samples at different ages were investigated using electronic nose (E-nose) and GC-MS techniques combined with chemometrics analysis. The bioactive ginsenoside and volatile oil content increased with age. E-nose performed well in the qualitative analyses. Both Principal Component Analysis (PCA) and Discriminant Functions Analysis (DFA) performed well when used to analyze ginseng samples, with the first two principal components (PCs) explaining 85.51% and the first two factors explaining 95.51% of the variations. Hierarchical Cluster Analysis (HCA) successfully clustered the different types of ginsengs into four groups. A total of 91 volatile constituents were identified. 50 of them were calculated and compared using GC-MS. The main fragrance ingredients were terpenes and alcohols, followed by aromatics and ester. The changes in terpenes, alcohols, aromatics, esters, and acids during the growth year once again confirmed the dominant role of terpenes. The Partial Least Squares (PLS) loading plot of gas sensors and aroma ingredients indicated that particular sensors were closely related to terpenes. The scores plot indicated that terpenes and its corresponding sensors contributed the most in grouping. As regards to quantitative analyze, 7 constituent of terpenes could be accurately explained and predicted by using gas sensors in PLS models. In predicting ginseng age using Back Propagation-Artificial Neural Networks (BP-ANN), E-nose data was found to predict more accurately than GC-MS data. E-nose measurement may be a potential method for determining ginseng age. The combination of GC-MS can help explain the hidden correlation between sensors and fragrance ingredients from two different viewpoints" |
| Keywords: | "Age Factors *Electronic Nose Gas Chromatography-Mass Spectrometry Ginsenosides/*analysis Odorants/*analysis Oils, Volatile/*analysis Panax/*chemistry Volatile Organic Compounds/analysis Electronic sensing Gc-ms Ginseng Volatile compounds Volatile oil cont;" |
| Notes: | "MedlineCui, Shaoqing Wang, Jun Yang, Liangcheng Wu, Jianfeng Wang, Xinlei eng Research Support, Non-U.S. Gov't England 2014/09/23 J Pharm Biomed Anal. 2015 Jan; 102:64-77. doi: 10.1016/j.jpba.2014.08.030. Epub 2014 Sep 6" |
