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.
