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A new strategy for statistical analysis-based fingerprint establishment: Application to quality assessment of Semen sojae praeparatum
Food Chemistry ( IF 8.5 ) Pub Date : 2018-03-16 , DOI: 10.1016/j.foodchem.2018.03.067
Hui Guo 1 , Zhen Zhang 1 , Yuan Yao 2 , Jialin Liu 1 , Ruirui Chang 2 , Zhao Liu 3 , Hongyuan Hao 3 , Taohong Huang 3 , Jun Wen 1 , Tingting Zhou 1
Affiliation  

Semen sojae praeparatum with homology of medicine and food is a famous traditional Chinese medicine. A simple and effective quality fingerprint analysis, coupled with chemometrics methods, was developed for quality assessment of Semen sojae praeparatum. First, similarity analysis (SA) and hierarchical clusting analysis (HCA) were applied to select the qualitative markers, which obviously influence the quality of Semen sojae praeparatum. 21 chemicals were selected and characterized by high resolution ion trap/time-of-flight mass spectrometry (LC-IT-TOF-MS). Subsequently, principal components analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were conducted to select the quantitative markers of Semen sojae praeparatum samples from different origins. Moreover, 11 compounds with statistical significance were determined quantitatively, which provided an accurate and informative data for quality evaluation. This study proposes a new strategy for “statistic analysis-based fingerprint establishment”, which would be a valuable reference for further study.



中文翻译:


基于统计分析的指纹图谱建立新策略:在酱油质量评价中的应用



黄豆是药食同源的名贵中药。开发了一种简单有效的质量指纹分析,结合化学计量学方法,用于酱油质量评估。首先采用相似性分析(SA)和层次聚类分析(HCA)筛选对酱油品质影响明显的定性标记。选择了 21 种化学品,并通过高分辨率离子阱/飞行时间质谱 (LC-IT-TOF-MS) 进行了表征。随后,通过主成分分析(PCA)和正交偏最小二乘判别分析(OPLS-DA)对不同产地的酱油样品进行定量标记物筛选。此外,还对11种具有统计学意义的化合物进行了定量测定,为质量评价提供了准确、翔实的数据。本研究提出了一种“基于统计分析的指纹建立”新策略,对进一步研究具有重要参考价值。

更新日期:2018-03-16
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