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GC – MS combined with chemometric techniques for the quality control and original discrimination of C urcumae longae rhizome: Analysis of essential oils
Author(s) -
Hu Yichen,
Kong Weijun,
Yang Xihui,
Xie Liwei,
Wen Jing,
Yang Meihua
Publication year - 2014
Publication title -
journal of separation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.72
H-Index - 102
eISSN - 1615-9314
pISSN - 1615-9306
DOI - 10.1002/jssc.201301102
Subject(s) - rhizome , principal component analysis , chemistry , essential oil , herb , traditional medicine , mathematics , biology , statistics , botany , food science , medicinal herbs , medicine
Curcumae longae rhizome is a widely used traditional herb in many countries. Various geographical origins of this herb might lead to diversity or instability of the herbal quality. The objective of this work was to establish the chemical fingerprints for quality control and find the chemical markers for discriminating these herbs from different origins. First, chemical fingerprints of essential oil of 24 C . longae rhizome from four different geographical origins in C hina were determined by GC – MS . Then, pattern recognition techniques were introduced to analyze these abundant chemical data in depth; hierarchical cluster analysis was used to sort samples into groups by measuring their similarities, and principal component analysis and partial least‐squares discriminate analysis were applied to find the main chemical markers for discriminating these samples. Curcumae longae rhizome from G uangxi province had the highest essential oil yield (4.32 ± 1.45%). A total of 46 volatile compounds were identified in total. Consistent results were obtained to show that C . longae rhizome samples could be successfully grouped according to their origins, and turmerone, ar ‐turmerone, and zingiberene were the characteristic components for discriminating these samples of various geographical origins and for quality control. This finding revealed that fingerprinting analysis based on GC – MS coupled with chemometric techniques could provide a reliable platform to discriminate herbs from different origins, which is a benefit for quality control.