Use of the Cross-Section Technique Linked with Multivariate Calibration Methods To Resolve Complex Pesticide Mixtures
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- 作者：A. Garrido Frenich ; J. L. Martí ; nez Vidal ; and M. Martí ; nez Galera
- 刊名：Analytical Chemistry
- 出版年：1999
- 出版时间：November 1, 1999
- 年：1999
- 卷：71
- 期：21
- 页码：4844 - 4850
- 全文大小：302K
- 年卷期：v.71,no.21(November 1, 1999)
- ISSN：1520-6882
文摘
The potential of the cross-section (CS) approach incombination with the partial least squares (PLS) andprincipal component regression (PCR) was assessed inthe resolution of a complex pesticide mixture showingtwelve overlapped components in High PerformanceLiquid Chromatography with Diode Array Detection (HPLC-DAD). Careful selection of the CS through the three-dimensional (3D) (A, 
, t) data matrix gave two-dimensional (2D) signals with the best sensitivity for thedetermination of each pesticide. In all cases, the application of the PLS method demonstrated a better quantitativeprediction ability than that of the PCR method. The CS-PLS approach is a powerful analytical tool. Ten pesticideswere well-resolved, while for the other two pesticides ofthe mixture prediction ability was poor, and they couldnot be determined, probably due to their low net analyticalsignal. The CS-PLS model was evaluated by predicting theconcentrations of independent test set samples. Finally,the proposed model was successfully applied for thedetermination of these pesticides in groundwater.
, t) data matrix gave two-dimensional (2D) signals with the best sensitivity for thedetermination of each pesticide. In all cases, the application of the PLS method demonstrated a better quantitativeprediction ability than that of the PCR method. The CS-PLS approach is a powerful analytical tool. Ten pesticideswere well-resolved, while for the other two pesticides ofthe mixture prediction ability was poor, and they couldnot be determined, probably due to their low net analyticalsignal. The CS-PLS model was evaluated by predicting theconcentrations of independent test set samples. Finally,the proposed model was successfully applied for thedetermination of these pesticides in groundwater.