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

• Published in: Food chemistry 2023-08, Vol.418, p.135950-135950, Article 135950
• Main Authors: Fan, Minxia, Rakotondrabe, Tojofaniry Fabien, Chen, Guilin, Guo, Mingquan
• Format: Article
• Language: English
• Subjects: Amino Acids; Biosensor; biosensors; carbohydrates; Electronic Nose; fatty acid metabolism; food chemistry; Food Microbiology; headspace analysis; Ion Mobility Spectrometry; microbial contamination; Microbial volatile organic compounds; Solid phase microextraction; Solid Phase Microextraction - methods; spectroscopy; Spoilage microorganism; volatile organic compounds; Volatile Organic Compounds - analysis
• ISSN: 0308-8146; 1873-7072
• DOI: 10.1016/j.foodchem.2023.135950

•The classification of food microorganism was summarized.•The generation mechanism of mVOCs in food were reviewed.•The sampling techniques for mVOCs in food were expounded.•The analytical methods of mVOCs in food were reviewed.•The existing problems and future development trend of mVOCs detection were explored. 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.