scholarly journals Quality Evaluation of Scrophulariae Radix Processed by Different ‘Sweating’ Methods Based on Simultaneous Determination of Multiple Bioactive Constituents Combined with Grey Relational Analysis

Molecules ◽  
2016 ◽  
Vol 21 (7) ◽  
pp. 850 ◽  
Author(s):  
Shengnan Wang ◽  
Yujiao Hua ◽  
Li Xu ◽  
Lisi Zou ◽  
Xunhong Liu ◽  
...  
Keyword(s):  
Simultaneous Determination ◽  
Grey Relational Analysis ◽  
Quality Evaluation ◽  
Bioactive Constituents ◽  
Relational Analysis ◽  
Grey Relational

scholarly journals Quality Evaluation of Prunellae Spica Based on Simultaneous Determination of Multiple Bioactive Constituents Combined with Grey Relational Analysis

2017 ◽  
Vol 12 (7) ◽  
pp. 1934578X1701200
Author(s):  
Zi-Xiu Liu ◽  
Yu-Jiao Hua ◽  
Sheng-Nan Wang ◽  
Li-Si Zou ◽  
Xun-Hong Liu ◽  
...  
Keyword(s):  
Simultaneous Determination ◽  
Grey Relational Analysis ◽  
Dynamic Change ◽  
Bioactive Components ◽  
Pentacyclic Triterpene ◽  
Traditional Chinese Herbal Medicine ◽  
Relational Analysis ◽  
Grey Relational

Prunellae Spica (PS) is an important traditional Chinese herbal medicine (TCM) with massive consumption because of its therapeutical and seasoning effects. However, little attention has been paid to simultaneous analyze its bioactive components for quality control of PS based on its different growing habitats and different growth periods. In this study, the quality of PS was evaluated based on simultaneous determination of multiple bioactive components combined with grey relational analysis (GRA). A reliable method based on high-performance liquid chromatography tandem triple quadrupole mass spectrometry (HPLC-QTRAP-MS/MS) was established to simultaneously determine the contents of 21 components in PS, including 9 phenolic acids, 3 coumarins, 8 flavonoids and 1 pentacyclic triterpene. Furthermore, GRA was performed to evaluate the quality of PS samples according to the contents of these 21 components. The results showed that the quality of PS harvested on withering period, cultivated in Anhui was better than that of other PS samples. The proposed method is useful for the overall assessment on the quality of PS, and this study provides valuable information for revealing the dynamic change laws of metabolite accumulation in PS and choosing the most suitable harvesting time and genuine producing area of PS to obtain the best quality.

Vehicle Interior Sound Quality Evaluation Index Selection Scheme Based on Grey Relational Analysis

2020 ◽  
Vol 19 (03) ◽  
pp. 2050031
Author(s):  
Jian Pan ◽  
Xiaolin Cao ◽  
Dengfeng Wang ◽  
Jing Chen ◽  
Jiankun Yuan
Keyword(s):  
Grey Relational Analysis ◽  
Quality Evaluation ◽  
Hierarchical Cluster ◽  
Subjective Assessment ◽  
Sound Quality ◽  
Evaluation Index ◽  
Vehicle Interior ◽  
Selection Scheme ◽  
Relational Analysis ◽  
Grey Relational

In the process of vehicle interior sound quality research, the subjective assessment usually requires a lot of manpower, time and material resources. It is necessary to choose appropriate objective indexes to predict the subjective results. In this paper, a sound quality evaluation index analysis and selection scheme based on grey relational analysis (GRA) is designed. In order to make a reasonable prediction of the subjective indexes with the limited data, GRA of the objective indexes and subjective indexes is conducted. Because three subjective indexes are considered in our study, an indicator that can represent the three chosen subjective indexes is established for the subsequent analysis. Furthermore, the comprehensive ranking and the hierarchical cluster analysis (HCA) of the objective indexes are involved to make the selection of objective indexes easy and meaningful. Finally, the objective indexes are divided into five groups by HCA. According to the clustering results, four objective indexes including “fluctuation”, “sharpness”, “articulation index” and “roughness” are suitable for predicting and representing the subjective indexes to some degree. The scheme proposed in this paper lays the foundation for further optimization and control of vehicle interior sound quality. The method can also be applied to solve other similar multi-factor analysis and selection problems.

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