Prediction of collision cross section values: application to non-intentionally added substance identification in food contact materials

Song, X. -C ; Dreolin, N. ; Damiani, T. ; Canellas, E. (Universidad de Zaragoza) ; Nerin, C. (Universidad de Zaragoza)

Resumen: The synthetic chemicals in food contact materials can migrate into food and endanger human health. In this study, the traveling wave collision cross section in nitrogen values of more than 400 chemicals in food contact materials were experimentally derived by traveling wave ion mobility spectrometry. A support vector machine-based collision cross section (CCS) prediction model was developed based on CCS values of food contact chemicals and a series of molecular descriptors. More than 92% of protonated and 81% of sodiated adducts showed a relative deviation below 5%. Median relative errors for protonated and sodiated molecules were 1.50 and 1.82%, respectively. The model was then applied to the structural annotation of oligomers migrating from polyamide adhesives. The identification confidence of 11 oligomers was improved by the direct comparison of the experimental data with the predicted CCS values. Finally, the challenges and opportunities of current machine-learning models on CCS prediction were also discussed. © 2022 The Authors. Published by American Chemical Society.

Idioma: Inglés

DOI: 10.1021/acs.jafc.1c06989

Año: 2022

Publicado en: JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 70, 4 (2022), 1272-1281
ISSN: 0021-8561

Factor impacto JCR: 6.1 (2022)

Categ. JCR: CHEMISTRY, APPLIED rank: 10 / 72 = 0.139 (2022) - Q1 - T1
Categ. JCR: AGRICULTURE, MULTIDISCIPLINARY rank: 6 / 58 = 0.103 (2022) - Q1 - T1
Categ. JCR: FOOD SCIENCE & TECHNOLOGY rank: 22 / 142 = 0.155 (2022) - Q1 - T1

Factor impacto CITESCORE: 9.7 - Chemistry (Q1) - Agricultural and Biological Sciences (Q1)

Factor impacto SCIMAGO: 1.099 - Chemistry (miscellaneous) (Q1) - Agricultural and Biological Sciences (miscellaneous) (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA-FEDER/T53-20R
Financiación: info:eu-repo/grantAgreement/ES/MICINN/RTI2018-097805-B-I00

Tipo y forma: Article (Published version)

Área (Departamento): Área Química Analítica (Dpto. Química Analítica)