2026-05-11T20:25:42Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/52582022-05-30T22:42:07Zcom_10259_4249com_10259_5086com_10259_2604col_10259_4250

Ortiz Fernández, Mª Cruz 406 500 Sanllorente Méndez, Silvia 522 500 Herrero Gutiérrez, Ana 282 500 Reguera Alonso, Celia 469 500 Rubio Martínez, Laura 492 500 Oca Casado, Mª Leticia f48d1f74-11ad-4f46-81b4-0a577c496594 500 Valverde Som, Lucía 583 500 Arce, M. M. c25cc62c-0b06-4277-8924-d95dc29a4d8a 500 Sánchez Pastor, Mª Sagrario 518 500 Sarabia Peinador, Luis Antonio 534 500 2020-04-03T21:25:18Z 2020-04-03T21:25:18Z 2020-05 0169-7439 http://hdl.handle.net/10259/5258 10.1016/j.chemolab.2020.104003 The growing demand for controls of foodstuffs, personal care products, medicines and the environment is unquestionable, as well as a better understanding of the toxicity of chemical products. This causes a growing need to propose methods of analysis for the unequivocal identification and quantification of analytes in complex samples. Several official organizations that regulate these aspects in pesticides, migrants or additives, have increased the requirements regarding the figures of merit, among others, for the unequivocal identification of the target analytes. The general recommendation is the use of the information provided by chromatographic techniques on the test sample, for example, the use of HPLC-DAD or GC-MS data. Therefore, for each sample, a data matrix formed by the response vector (absorbances or abundances) recorded at each retention time is available. A data array is obtained when the matrices corresponding to the calibration standards and the test samples are concatenated. There are several chemometric techniques with the second-order advantage that can handle data arrays, so target analytes can be identified and quantified using them even in the presence of interferents. In this work, PARAFAC has been considered as a good option. If the data array is trilinear, its analysis using PARAFAC/PARAFAC2 enables the unequivocal identification and quantification of the target analyte so that the result is valid according to the criteria imposed by the authorities. In this work, the chemometric methodology is explained through four different case studies related to the determination of analytes in complex matrices (bisphenol A migrated from polycarbonate, dichlobenil in onion, oxybenzone in sunscreen cosmetic creams and melamine migrated from melaware). This multi-way methodology solves the problems of the coelution of interferents that have a similar absorbance spectrum in HPLC-DAD (or share m/z ratios in GC-MS) with the target analyte or with the internal standard causing false-negative results with conventional identification methods. In addition, the PARAFAC decomposition of trilinear arrays enables the joint optimization of several analytical parameters (extraction, clean up, etc.) that control different sample pretreatments prior to the chromatographic determination of complex samples. Spanish MINECO (AEI/FEDER, UE) through project CTQ2017‐88894‐R and by Junta de Castilla y León through project BU012P17 (all co‐financed with European FEDER funds). application/pdf eng Elsevier Chemometrics and Intelligent Laboratory Systems. 2020, V. 200, 104003 https://doi.org/10.1016/j.chemolab.2020.104003 info:eu-repo/grantAgreement/MINECO/CTQ2017‐88894‐R info:eu-repo/grantAgreement/JCyL/BU012P17 Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess PARAFAC PARAFAC2 GC-MS HPLC-DAD Unequivocal identification Química analítica Chemistry, Analytic Three-way PARAFAC decomposition of chromatographic data for the unequivocal identification and quantification of compounds in a regulatory framework info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Chemometrics and Intelligent Laboratory Systems 200 104003 TEXT Ortiz-ci1s_2020.pdf.txt Ortiz-ci1s_2020.pdf.txt Extracted text text/plain 74231 https://riubu.ubu.es/bitstream/10259/5258/5/Ortiz-ci1s_2020.pdf.txt f635641cf9185d9582d7e01756f19a6a MD5 5 THUMBNAIL Ortiz-ci1s_2020.pdf.jpg Ortiz-ci1s_2020.pdf.jpg IM Thumbnail image/jpeg 4505 https://riubu.ubu.es/bitstream/10259/5258/4/Ortiz-ci1s_2020.pdf.jpg aabb321c68468f1463bbf65220eebfef MD5 4 LICENSE license.txt license.txt text/plain; charset=utf-8 998 https://riubu.ubu.es/bitstream/10259/5258/3/license.txt aa90105e1c90a1b4fe810649aa967b7d MD5 3 CC-LICENSE license_rdf license_rdf application/rdf+xml; charset=utf-8 805 https://riubu.ubu.es/bitstream/10259/5258/2/license_rdf 4460e5956bc1d1639be9ae6146a50347 MD5 2 ORIGINAL Ortiz-ci1s_2020.pdf Ortiz-ci1s_2020.pdf application/pdf 1419554 https://riubu.ubu.es/bitstream/10259/5258/1/Ortiz-ci1s_2020.pdf a695455b70445bcbe2b4ba289a453bc3 MD5 1 10259/5258 oai:riubu.ubu.es:10259/5258 2022-05-31 00:42:07.616 Repositorio Institucional de la Universidad de Burgos bubrep@ubu.es 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