主成分分析
偏最小二乘回归
化学计量学
线性判别分析
模式识别(心理学)
化学
傅里叶变换红外光谱
人工智能
傅里叶变换
生物系统
分析化学(期刊)
色谱法
统计
数学
计算机科学
工程类
生物
数学分析
化学工程
作者
Qimeng Fan,Chaoyin Chen,Yuping Lin,Chunmei Zhang,Binqiu Liu,Shenglan Zhao
标识
DOI:10.1016/j.molstruc.2013.07.039
摘要
Due to Rhizoma gastrodiae (Tianma) from different producing areas have vital difference in quality and physiological efficacy. This study focused on the classification and identification of Tianma from different producing areas using Fourier Transform Infrared (FT-IR) Spectroscopy coupled with chemometrics. Frequencies at 1800–600 cm−1 were exploited for both classification and identification. Principal component analysis (PCA) and Partial least squares-Discriminant analysis (PLS-DA) were used for classification and identification analysis of Tianma from different producing areas. Fourier Transform Infrared (FT-IR) Spectroscopy coupled with Principal component analysis (PCA) and Partial least squares-Discriminant analysis (PLS-DA) can successfully classify and identify Tianma from different producing areas. Taken together, the proposed methodology is a useful tool to identify Tianma from different producing areas.
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