化学计量学
指纹(计算)
偏最小二乘回归
线性判别分析
模式识别(心理学)
鉴定(生物学)
质量(理念)
计算机科学
人工智能
近红外光谱
数据挖掘
主成分分析
数学
机器学习
物理
量子力学
生物
植物
作者
Wenlong Li,Haifan Han,Lu Zhang,Yan Zhang,Haibin Qu
标识
DOI:10.1631/jzus.b1500186
摘要
We have developed a set of chemometric methods to address two critical issues in quality control of a precious traditional Chinese medicine (TCM), Dong’e Ejiao (DEEJ). Based on near infrared (NIR) spectra of multiple samples, the genuine manufacturer of DEEJ, e.g. Dong’e Ejiao Co., Ltd., was accurately identified among 21 suppliers by the fingerprint method using Hotelling T2, distance to Model X (DModX), and similarity match value (SMV) as discriminate criteria. Soft independent modeling of the class analogy algorithm led to a misjudgment ratio of 6.2%, suggesting that the fingerprint method is more suitable for manufacturer identification. For another important feature related to clinical efficacy of DEEJ, storage time, the partial least squares-discriminant analysis (PLS-DA) method was applied with a satisfactory misjudgment ratio (15.6%) and individual prediction error around 1 year. Our results demonstrate that NIR spectra comprehensively reflect the essential quality information of DEEJ, and with the aid of proper chemometric algorithms, it is able to identify genuine manufacturer and determine accurate storage time. The overall results indicate the promising potential of NIR spectroscopy as an effective quality control tool for DEEJ and other precious TCM products.
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