Analysis and Differentiation of the Volatile Compounds in Red and White Wines Using Desiccated Headspace Gas Chromatography-Mass Spectrometry Coupled with Chemometrics

Advances in microbial analysis: based on volatile organic compounds of microorganisms in food

In recent years, microbial volatile organic compounds (mVOCs) produced by microbial metabolism have attracted more and more attention because they can be used to detect food early contamination and flaws. So far, many analytical methods have been reported for the determination of mVOCs in food, but few integrated review articles discussing these methods are published. Consequently, mVOCs as indicators of food microbiological contamination and their generation mechanism including carbohydrate, amino acid, and fatty acid metabolism are introduced. Meanwhile, a detailed summary of the mVOCs sampling methods such as headspace, purge trap, solid phase microextraction, and needle trap is presented, and a systematic and critical review of the analytical methods (ion mobility spectrometry, electronic nose, biosensor, and so on) of mVOCs and their application in the detection of food microbial contamination is highlighted. Finally, the future concepts that can help improve the detection of food mVOCs are prospected.

Quality assessment of fried licorice based on fingerprints and chemometrics

Fried licorice is obtained by frying licorice without using any auxiliary materials, and it is widely used both as food and medicine in China. To explore the influence of licorice origin on the quality of fried licorice, a method based on fingerprinting and chemometrics was developed. Twenty batches of licorice were selected from four locations. The reference chromatograms of each location were established via similarity analysis. Chemometric methods, such as cluster, principal component, and orthogonal partial least squares discriminant analyses were used to evaluate the changes in the composition of fried licorice, predict its origin, and reflect its quality. Mass spectrometry was used to identify the chemical components. Finally, an origin prediction function was established via discriminant analysis to trace the origin of licorice. The model was demonstrated to be stable, reliable, and accurate in predicting licorice origin and to provide a reference for origin traceability.