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采用 SBSE-GC-MS 和化学计量学技术自动、非靶向分析天然和碱化可可粉的挥发性成分。

Automatic and non-targeted analysis of the volatile profile of natural and alkalized cocoa powders using SBSE-GC-MS and chemometrics.

机构信息

Departamento de Tecnología de Alimentos, Universitat Politècnica de València, Camino de Vera, s/n, 46022 Valencia, Spain; Data Innovation, Quito, Ecuador; Agroindustrial and Food Engineering, Universidad de las Americas, Quito, Ecuador.

Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Modena, Italy.

出版信息

Food Chem. 2022 Sep 30;389:133074. doi: 10.1016/j.foodchem.2022.133074. Epub 2022 Apr 26.

Abstract

A total of 56 key volatile compounds present in natural and alkalized cocoa powders have been rapidly evaluated using a non-target approach using stir bar sorptive extraction gas chromatography mass spectrometry (SBSE-GC-MS) coupled to Parallel Factor Analysis 2 (PARAFAC2) automated in PARADISe. Principal component analysis (PCA) explained 80% of the variability of the concentration, in four PCs, which revealed specific groups of volatile characteristics. Partial least squares discriminant analysis (PLS-DA) helped to identify volatile compounds that were correlated to the different degrees of alkalization. Dynamics between compounds such as the acetophenone increasing and toluene and furfural decreasing in medium and strongly alkalized cocoas allowed its differentiation from natural cocoa samples. Thus, the proposed comprehensive analysis is a useful tool for understanding volatiles, e.g., for the quality control of cocoa powders with significant time and costs savings.

摘要

采用搅拌棒吸附萃取气相色谱-质谱联用(SBSE-GC-MS)结合平行因子分析 2(PARAFAC2)的非靶向方法,快速评估了天然和堿化可可粉中存在的 56 种关键挥发性化合物。主成分分析(PCA)在四个 PCs 中解释了浓度的 80%可变性,这揭示了挥发性特征的特定组。偏最小二乘判别分析(PLS-DA)有助于确定与不同堿化程度相关的挥发性化合物。化合物之间的动态关系,如乙酰苯酮的增加和甲苯和糠醛的减少,使得可以将中堿和强堿化可可与天然可可样品区分开来。因此,所提出的综合分析是理解挥发性化合物的有用工具,例如,可用于具有显著时间和成本节省的可可粉质量控制。

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