Multiway Partial Least-Squares Coupled to Residual Trilinearization: A Genuine Multidimensional Tool for the Study of Third-Order Data. Simultaneous Analysis of Procaine and Its Metabolite p-Am

详细信息    查看全文

• 作者：Patricia C. Damiani ; Isabel Dur&aacute ; n-Mer&aacute ; s ; Alejandro Garcí ; a-Reiriz ; Ana Jimé ; nez-Giró ; n ; Arsenio Mu&ntilde ; oz de la Pe&ntilde ; a ; Alejandro C. Olivieri
• 刊名：Analytical Chemistry
• 出版年：2007
• 出版时间：September 15, 2007
• 年：2007
• 卷：79
• 期：18
• 页码：6949 - 6958
• 全文大小：369K
• 年卷期：v.79,no.18(September 15, 2007)
• ISSN：1520-6882

文摘

A new third-order multivariate calibration approach,based on the combination of multiway-partial least-squares with a separate procedure called residual trilinearization (N-PLS/RTL), is presented and applied tomulticomponent analysis using third-order data. Theproposed chemometric algorithm is able to predict analyteconcentrations in the presence of unexpected samplecomponents, which require strict adherence to the second-order advantage. Results for the determination of procaineand its metabolite p-aminobenzoic acid in equine serumare discussed, based on kinetic fluorescence excitation-emission four-way measurements and application of thenewly developed multiway methodology. Since the analytes are also the reagent and product of the hydrolysisreaction followed by fast-scanning fluorescence spectroscopy, the classical approach based on parallel factoranalysis is challenged by strong linear dependencies andmultilinearity losses. In comparison, N-PLS/RTL appearsan appealing genuine multiway alternative that avoids thelatter complications, yielding analytical results that arestatistically comparable to those rendered by relatedunfolded algorithms, which are also able to process four-way data. Prediction was made on validation samples witha qualitative composition similar to the calibration set andalso on test samples containing unexpected equine serumcomponents.