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基于超高效液相色谱-四极杆-静电场轨道阱质谱联用仪及电子感官技术对不同蒸制次数的华进行质量评价

Quality Evaluation of Hua Based on UPLC-Q-Exactive Orbitrap MS and Electronic Sensory Techniques with Different Numbers of Steaming Cycles.

作者信息

Wang Mengjin, Hu Jiayi, Hai Xiaoya, Cao Tianzhuo, Zhou An, Han Rongchun, Xing Lihua, Yu Nianjun

机构信息

Department of Biopharmaceuticals, College of Pharmacy, Anhui University of Chinese Medicine, Hefei 230012, China.

Anhui Province Key Laboratory of R&D of Chinese Medicine, Anhui Province Key Laboratory of Chinese Medicinal Formula, Hefei 230012, China.

出版信息

Foods. 2024 May 20;13(10):1586. doi: 10.3390/foods13101586.

Abstract

In this study, electronic sensory techniques were employed to comprehensively evaluate the organoleptic quality, chemical composition and content change rules for Hua (PCH) during the steaming process. The results were subjected to hierarchical cluster analysis (HCA), principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). These analyses revealed, from a sensory product perspective, overall differences in colour, odour and taste among the samples of PCH with different numbers of steaming cycles. Using the UPLC-Q-Exactive Orbitrap MS technique, 64 chemical components, including polysaccharides, organic acids, saponins and amino acids were detected in PCH before and after steaming. The sensory traits were then correlated with the chemical composition. From the perspectives of sensory traits, chemical composition, and multi-component index content, it was preliminarily deduced that carrying out five cycles of steaming and sun-drying was optimal, providing evidence for the quality evaluation of PCH during the steaming process.

摘要

在本研究中,采用电子感官技术对花(PCH)蒸制过程中的感官品质、化学成分及含量变化规律进行综合评价。将结果进行层次聚类分析(HCA)、主成分分析(PCA)和正交偏最小二乘判别分析(OPLS-DA)。这些分析从感官产品角度揭示了不同蒸制次数的PCH样品在颜色、气味和味道上的总体差异。采用超高效液相色谱-四极杆-静电场轨道阱质谱技术(UPLC-Q-Exactive Orbitrap MS),检测了蒸制前后PCH中的64种化学成分,包括多糖、有机酸、皂苷和氨基酸。然后将感官特征与化学成分进行关联。从感官特征、化学成分和多成分指标含量的角度,初步推断进行五次蒸晒循环是最佳的,为PCH蒸制过程中的质量评价提供了依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f14/11120622/0064fa4f1ee0/foods-13-01586-g001.jpg

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