Sequential application of backward interval partial least squares and genetic algorithms for the selection of relevant spectral regions

Journal of Chemometrics - Tập 18 Số 11 - Trang 486-497 - 2004
Riccardo Leardi1, Lars Nørgaard2
1Department of Pharmaceutical and Food Chemistry and Technology, University of Genoa, Genoa, Italy
2Chemometrics Group, Department of Food Science, The Royal Veterinary and Agricultural University, Rolighedsvej 30, DK-1958 Frederiksberg, Denmark

Tóm tắt

AbstractIt is nowadays widely accepted that genetic algorithms (GAs) are powerful tools in variable selection and that after suitable modifications they can also be powerful in detecting the most relevant spectral regions for multivariate calibration. One of the main limitations of GAs is related to the fact that when spectral intensities are measured at a very large number of wavelengths the search domain increases correspondingly and therefore the detection of the relevant regions is much more difficult. A modification of interval partial least squares (iPLS), designated backward interval PLS (biPLS), is developed and studied such that it can detect and remove the least relevant regions, thereby reducing the search domain to a size that GAs can handle easily. In this paper the application to two different spectroscopic data sets will be shown: infrared spectroscopic analysis of polymer film additives and determination of the contents of erucic acid and total fatty acids in brassica seeds by near‐infrared spectroscopy. The developed method is compared with model performances based on expert selection of variables as well as with results from application of the previously developed GA‐PLS method. The sequential application of biPLS and GA‐PLS has proven successful, and comparable or better results have been obtained, introducing a more automatic region selection procedure and a substantial decrease in computation time. Copyright © 2005 John Wiley & Sons, Ltd.

Từ khóa


Tài liệu tham khảo

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Leardi R, 2002, Selection of the NIRS regions predictive of oil and erucic acid contents in samples of Brassica juncea by genetic algorithm‐PLS, XVII Congr. Naz. di Chimica Analitica, 294

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Thông tin xuất bản

Journal of Chemometrics

Tập 18 Số 11

486-497

Thông tin tác giả