基于化学计量法和指纹图谱对生姜不同处理方法的成分差异研究

目的 采用UPLC建立生姜Zingiber officinale在冷提、回流2种不同处理方法的指纹图谱，再利用化学计量学和灰度关联分析法对不同处理方法下的生姜进行成分差异研究，采用电子舌技术找寻与生姜风味相关的关键性成分。方法 利用UPLC建立生姜不同处理方法的指纹图谱，筛选共有峰，以Orbitrap-Exploris质谱对共有峰成分进行鉴定，再运用SIMCA、SPSS等软件进行化学计量学分析，通过层次聚类分析（hierarchical clustering analysis，HCA）、主成分分析（principal component analysis，PCA）、正交偏最小二乘-判别分析（orthogonal partial least squares-discriminant analysis，OPLS-DA）和灰度关联分析评价不同处理方法下生姜的成分差异。结果 从生姜指纹图谱中识别出10个共有峰，各批次的相似度在0.972～1.000；Orbitrap-Exploris质谱共鉴定出9个共有峰成分；HCA和PCA的结果显示，冷提法和回流法处理的生姜可以各自聚类，OPLS-DA确证了6-姜酚、8-姜酚、8-姜二酮、10-姜酚、1,4-去二氢-8-姜酚、1,4-去二氢-10-姜酚是不同处理方法下生姜差异性的关键性成分；灰度关联分析结果表明，冷提法处理生姜可以得到更多姜酚类，姜烯酚类成分；电子舌结果表明，处理方法对生姜的风味并无显著影响，而6-姜酚与生姜诸多味觉信息呈显著性相关。结论 利用UPLC指纹图谱结合化学计量学可以评估生姜的质量和风味物质的含量，可有效区分冷提法和回流法处理的生姜并筛选出差异性成分，为生姜的处理方式的选择提供了可靠的方法，并且利用电子舌技术得出6-姜酚是生姜味觉信息变化的关键性成分。

Compositional differences of different treatments of Zingiber officinale based on chemometric and fingerprinting methods

Objective UPLC was used to establish the fingerprints of Jiang (Zingiber officinale Rosc.) in two different treatments of cold extraction and reflux, and then chemometrics and gray correlation analysis were used to investigate the differences in the composition of Z. officinale under different treatments. Methods The fingerprints of different treatments of Z. officinale were established by UPLC, the common peaks were screened, the common peak components were identified by Orbitrap-Exploris mass spectrometry, and then chemometric analysis was performed by SIMCA and SPSS. Hierarchical Clustering Analysis (HCA), Principal Component Analysis (PCA), Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) and Grayscale Correlation Analysis were used to evaluate the compositional differences of Z. officinale under different treatment methods. Result Ten shared peaks were identified from the Z. officinale fingerprint profile, with similarities between 0.972 and 1.000 for each batch. Nine shared peak components were identified by Orbitrap-Exploris mass spectrometry. The results of HCA and PCA showed that Z. officinale treated by cold extraction and reflux methods could be clustered individually, and OPLS-DA confirmed that 6-gingerol, 6-gingerenol, 8-gingerdione, 8-gingerol, 1,4-desdihydro-8-gingerol, and 1,4-desdihydro-10-gingerol were the key components for the variability of Z. officinale under different treatments. The results of the gray-scale correlation analysis showed that the treatment of Z. officinale by cold extraction method could yield more curcumin, gingerolenic components. Conclusion UPLC fingerprinting combined with chemometrics can assess the quality and flavor content of Z. officinale, which can effectively distinguish between Z. officinale treated by cold extraction and reflux methods and screen out the differential components, providing a reliable method for the selection of Z. officinale treatment.