Application of the area correlation constraint in the MCR-ALS quantitative analysis of complex mixture samples
The application of the recently developed area correlation constraint in Multivariate CurveResolution–Alternating Least Squares (MCR-ALS) for the quantitative determination of analyte mixtures is shown. The feasibility of the proposed constraint is tested firstly for the calibration and quantitation of PAHs mixtures in their synthetic mixtures (validation samples) and in river water samples dissolved organic matter (DOM) using EEM fluorescent three-way data. In this case, MCR-ALS results obtained with the proposed area correlation constraint are comparable with the results obtained with methods based on the fulfillment of the trilinear model, like PARAFAC and MCR-ALS with the trilinearity constraint. Secondly, the possibility of applying this new area correlation constraint is extended to the analytical determination of lipid mixtures in synthetic and cell culture samples by LC-MS, where the trilinear model does not hold. The applicability of the proposed area correlation constraint is assessed, and it is proposed as a general tool for the quantitative determination of unknown mixtures of analytes in complex natural samples with severe profile overlapping and unknown composition, whatever the data structure is.
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| Format: | artículo biblioteca |
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Elsevier
2020
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| Subjects: | MCR-ALSArea correlation constraintExcitation-emission dataLC-MS data, |
| Online Access: | http://hdl.handle.net/10261/228512 |
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