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R. Rosipal, “Kernel Partial Least Squares for Nonlinear Regression and Discrimination,” Neural Network World, Vol. 13, No. 3, 2003, pp. 291-300.

has been cited by the following article:

• TITLE: Near-Infrared Spectroscopy Coupled with Kernel Partial Least Squares-Discriminant Analysis for Rapid Screening Water Containing Malathion

  AUTHORS: Congying Gu, Bingren Xiang, Yilong Su, Jianping Xu

  KEYWORDS: Kernel Partial Least Squares-Discriminant Analysis; Near-Infrared Spectroscopy; Malathion; Water

  JOURNAL NAME: American Journal of Analytical Chemistry, Vol.4 No.3, March 27, 2013

  ABSTRACT: Near-infrared spectroscopy coupled with kernel partial least squares-discriminant analysis was used to rapidly screen water containing malathion. In the wavenumber of 4348 cm-1 to 9091 cm-1, the overall correct classification rate of kernel partial least squares-discriminant analysis was 100% for training set, and 100% for test set, with the lowest concentration detected malathion residues in water being 1 μg·ml-1. Kernel partial least squares-discriminant analysis was able to have a good performance in classifying data in nonlinear systems. It was inferred that Near-infrared spectroscopy coupled with the kernel partial least squares-discriminant analysis had a potential in rapid screening other pesticide residues in water.