2020
DOI: 10.1016/j.jpba.2020.113127
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Multivariate quantitative analysis of quality trend based on non-volatile characteristic components in different Panax notoginseng samples using HPLC

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Cited by 12 publications
(4 citation statements)
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“…Principal component analysis (PCA) is a multivariate statistical method [ 16 ]. While preserving the original variable information as much as possible, the basic idea is to transform the original high-dimensional data into a low-dimensional feature variable of linearly independent through an orthogonal transformation.…”
Section: Methodsmentioning
confidence: 99%
“…Principal component analysis (PCA) is a multivariate statistical method [ 16 ]. While preserving the original variable information as much as possible, the basic idea is to transform the original high-dimensional data into a low-dimensional feature variable of linearly independent through an orthogonal transformation.…”
Section: Methodsmentioning
confidence: 99%
“…Panax notoginseng is a perennial herb belonging to the genus Panax anomaly Araliaceae that is widely used in traditional Chinese medicine. P. notoginseng contains a variety of chemical components including saponins, flavonoids, sterols, polysaccharides, amino acids, fatty acids, and various trace elements ( Li et al, 2020 ). Specifically, the root is beneficial to human health due to its anti-atherosclerotic, antioxidant, anti-inflammatory, anti-hyperlipidemic, hypoglycemic, neuroprotective, anti-coagulation, and anti-tumor properties ( Wang et al, 2016 ).…”
Section: Introductionmentioning
confidence: 99%
“…In order to increase the weight, nonmedicinal parts with less active ingredients are often added to the raw materials, such as the addition of stem and leaf powder in pure root powder of Panax notoginseng. 6 These adulterants often contained the same characteristic ingredients as authentic herbal medicines, making it difficult to discriminate them with conventional methods. In addition, its market value was mainly determined by the cultivation years and geographical origins.…”
Section: Introductionmentioning
confidence: 99%