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采用电子鼻结合 GC-MS 对中国玛咖进行产地鉴别。

Origin identification of Chinese Maca using electronic nose coupled with GC-MS.

机构信息

Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, 214122, China.

Beijing Key Laboratory of the Innovative Development of Functional Staple and Nutritional Intervention for Chronic Diseases, China National Research Institute of Food and Fermentation Industries Co., LTD., Beijing, 100015, China.

出版信息

Sci Rep. 2019 Aug 21;9(1):12216. doi: 10.1038/s41598-019-47571-0.

Abstract

Maca (Lepidium meyenii Walp.), originated in the high Andes of Peru, is rich in nutrients and phytochemicals. As a new resource food in China, Maca suffers marketing disorders due to the limitation of basic research. Due to the close relationship of Maca quality and origin of place, it's of scientific, economic and social importance to set up a rapid, reliable and efficient method to identify Maca origin. In the present study, 303 Maca samples were collected from 101 villages of the main producing area in China. Using electronic nose and BP neutral network algorithm, a Maca odor database was set up to trace the origin. GC-MS was then employed to analyze the characteristic components qualitatively and semi-quantitatively. As a result, very significant differences (p < 0.01) were detected in the volatile components of Maca from different areas. This study not only constructs a network model to forecast the Maca origin, but also reveals the relationship between Maca odor fingerprints and origins.

摘要

玛咖(Lepidium meyenii Walp.)原产于秘鲁高海拔安第斯山脉,富含营养物质和植物化学物质。作为中国的一种新资源食品,由于基础研究的局限性,玛咖受到市场混乱的困扰。由于玛咖质量与产地的密切关系,建立一种快速、可靠、高效的玛咖产地鉴别方法具有重要的科学、经济和社会意义。本研究从中国主产区的 101 个村庄采集了 303 个玛咖样本。利用电子鼻和 BP 神经网络算法,建立了玛咖气味数据库,以追溯其产地。然后采用 GC-MS 对特征成分进行定性和半定量分析。结果表明,不同地区玛咖的挥发性成分存在非常显著的差异(p<0.01)。本研究不仅构建了一个网络模型来预测玛咖的产地,还揭示了玛咖气味指纹图谱与产地之间的关系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86ed/6704143/906d51292d88/41598_2019_47571_Fig1_HTML.jpg

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