Production process defects of MiXi beverage detected by neutral desorption extractive electrospray ionization mass spectrometry

Abstract

Process defects in the model production process of MiXi beverage, typical examples of extremely viscous food products, have been successfully detected using neutral desorption-extractive electrospray ionization mass spectrometry (ND-EESI-MS) without sample pretreatment. We employed statistical analysis to explore the correlation between process defects in production and metabolite ions in the fingerprints of MiXi samples with diverse qualities, which were acquired using ND-EESI-MS. Abnormal signals in the fingerprint profiles, such as the unexpected presence of heavy metal ions or pesticides, as well as changes in beneficial compounds like D-glucose, can indicate defects or issues encountered in the production process. Meanwhile, we quantitatively analysed the concentrations of heavy metals and pesticide residues in MiXi beverage, and the results showed a strong linear relationship (R2 > 0.99) between heavy metals and pesticide residues in the concentration range 0.50–200.00 μg L−1, with a limit of detection (LOD) of 0.04–1.44 μg L−1 and limit of quantification (LOQ) of 0.12–4.36 μg L−1, with an RSD of 0.39–3.66%. Furthermore, in contrast to previous methods, concealed defects occurring in the manufacturing process, including raw material screening, soaking, and extraction, can be directly detected by terminal product analysis, showing that ND-EESI-MS was a promising tool for quality control in viscous beverages and tracing defects in the production process.

Graphical abstract: Production process defects of MiXi beverage detected by neutral desorption extractive electrospray ionization mass spectrometry

Supplementary files

Article information

Article type
Paper
Submitted
14 mar. 2025
Accepted
06 jún. 2025
First published
12 jún. 2025

Analyst, 2025, Advance Article

Production process defects of MiXi beverage detected by neutral desorption extractive electrospray ionization mass spectrometry

L. Pan, M. Qin, L. Wang, L. Huang, H. Xing, N. Wang, T. Yang, L. Hu, R. Su and H. Chen, Analyst, 2025, Advance Article , DOI: 10.1039/D5AN00299K

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