Partial Least Squares Discriminant Analysis Model Based on Variable Selection Applied to Identify the Adulterated Olive Oil-Reference-Cited by-同舟云学术

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Partial Least Squares Discriminant Analysis Model Based on Variable Selection Applied to Identify the Adulterated Olive Oil

Published:2015-11-13 Issue:6 Volume:9 Page:1713-1718
ISSN:1936-9751
Container-title:Food Analytical Methods
language:en
Short-container-title:Food Anal. Methods

Author:

Li Xinhui,Wang Sulan,Shi Weimin,Shen Qi

Funder

the National natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Safety Research,Safety, Risk, Reliability and Quality,Applied Microbiology and Biotechnology,Food Science,Analytical Chemistry

Link

http://link.springer.com/content/pdf/10.1007/s12161-015-0355-8.pdf

Reference31 articles.

1. Araújo MCU, Saldanha TCB, Galvão RKH, Yoneyama T, Chame HC, Visani V (2001) The successive projections algorithm for variable selection in spectroscopic multicomponent analysis. Chemometr Intell Lab 57:65–73

2. Ballabio D, Consonni V, Mauri A, Todeschini R (2010) Canonical Measure of Correlation (CMC) and Canonical Measure of Distance (CMD) between sets of data. Part 3. Variable selection in classification. Anal Chim Acta 657:116–22

3. Boschetti CE, Olivieri AC (2004) A new genetic algorithm applied to the near infrared analysis of gasolines. J Near Infrared Spec 12:85–91

4. Cai W, Li Y, Shao X (2008) A variable selection method based on uninformative variable elimination for multivariate calibration of near-infrared spectra. Chemometr Intell Lab 90:188–94

5. Centner V, Massart DL (1996) Elimination of uninformative variables for multivariate calibration. Anal Chem 68:3851–8

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