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    Aroma Characteristic Analysis of Amomi fructus from Different Habitats using Machine Olfactory and Gas Chromatography‑Mass Spectrometry

    Huaying Zhou2,3★, Dehan Luo2, Hamid Gholamhosseini4, Zhong Li5, Bin Han5, Jiafeng He2, Shumei Wang5★ Corresponding author

    1. 1Department of Communication, School of Information Engineering, Guangdong University of Technology.
    2. 2Department of Computer Science, College of Medical Information Engineering, Guangdong Pharmaceutical University.
    3. 3Department of Electrical and Electronic Engineering, School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand.
    4. 4Department of Traditional Chinese Medicine Resources, College of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, China.

    CORRESPONDENCE

    Huaying Zhou

    Department of Computer Science, College of Medical Information Engineering, Guangdong Pharmaceutical University.

    dehanluo@gdut.edu.cn

    Received: 30-12-2018; Revised: 12-02-2019.

    Volume 15, Issue 63 · pp. 392–401 · PUBLISHED 16 May 2019 · DOI: 10.4103/pm.pm_665_18

    View on Pharmacogn. Mag. original site ↗

    ABSTRACT

    Background: Amomi fructus (AF Lour.) has been used to treat digestive diseases in the context of Traditional Chinese Medicine. Its aroma characteristics have been attracted attention and are considered to be effective markers for determining AF from different habitats. Materials and Methods: In this article, the odor characteristics of AF from three different habitats were investigated and analyzed using gas chromatography‑mass spectrometry (GC‑MS) and an electronic nose (E‑nose). Results: It was found that the E‑nose in conjunction with principal component analysis as an analytic tool, showed good performance and achieved a total variance of 93.90% with the first two principal components. A total of 65 aroma constituents among three groups of AF were separated, identified, and calculated using GC‑MS. It was observed that the components and the contents were clearly different among the three groups. To confirm the interrelation between aroma constituents and sensors, the contents of 12 aroma ingredients and the response values of six sensors were selected to be trained and tested using the partial least squares. A satisfied quantitative prediction was presented that the contents of selected constituents were accurately predicted by corresponding E‑nose sensors with the most determination coefficient of calibration and determination coefficient of prediction of >90%. Conclusion: It was revealed that the E‑nose is capable of discriminating AF from different habitats, presenting an accurate, easy‑operating, and nondestructive reference approach.

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      Zhou, H., Luo, D., Gholamhosseini, H., Li, Z., Han, B., He, J., & Wang, S. (2019). Aroma Characteristic Analysis of Amomi fructus from Different Habitats using Machine Olfactory and Gas Chromatography‑Mass Spectrometry. Pharmacognosy Magazine, 15(63), 392–401. https://doi.org/10.4103/pm.pm_665_18