杏仁苷
化学计量学
化学
偏最小二乘回归
主成分分析
指纹(计算)
色谱法
线性判别分析
食品科学
人工智能
统计
数学
计算机科学
医学
病理
替代医学
作者
Zhang Guo-qin,Huanhuan Li,Lili Sun,Yi Liu,Ying Cao,Xiaoliang Ren,Yanan Liu
出处
期刊:Journal of Chromatographic Science
[Oxford University Press]
日期:2022-03-22
卷期号:61 (2): 110-118
被引量:4
标识
DOI:10.1093/chromsci/bmac026
摘要
Bitter almond is a well-known and commonly used traditional Chinese medicine (TCM) for relieving coughs and asthma. However, the bioactive chemical composition of bitter almonds, especially their amygdalin content, which determines their quality for TCM use, is variable and this can cause problems with formulating and prescribing TCMs based on bitter almonds. Therefore, a simple method was developed to evaluate the compositional quality of bitter almonds from their appearance traits, based on a combination of chromatographic fingerprinting and chemometrics. Bitter almonds were analyzed by high-performance liquid chromatography (HPLC). Hierarchical cluster analysis (HCA) and principal components analysis (PCA) were applied to classify bitter almonds, which split the samples into two independent clusters. Three chemical markers (amygdalin, prunasin, and one unidentified component) were found by partial least squares-discriminant analysis (PLS-DA). What's more, a new PLS-DA model was reconstructed to confirm the obtained chemical markers from PLS-DA. Additionally, the appearance trait indices and amygdalin content of bitter almond were determined and the classification was confirmed by one-way analysis of variance. This method can easily determine the quality of bitter almonds from their appearance alone, high quality correlated closely with kernels that were larger, oblong in shape and heavier.
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