Issue 45, 2017

Application of the Kohonen map analysis (KMA) on chromatographic datasets to achieve unsupervised classification of olive and non-olive oil samples: a novel approach

Abstract

In the present work, a novel procedure that involves application of the Kohonen map analysis (KMA) algorithm on the chromatographic datasets is introduced for quality monitoring of olive oil samples. The proposed procedure is tested using the chromatographic datasets acquired for 118 oil samples belonging to the class of olive, non-olive and blended oil samples. The obtained results clearly indicate that the KMA algorithm is highly sensitive, specific and precise in classifying the samples. In summary, the proposed KMA-chromatographic combination provides a simple, unbiased and sensitive procedure to perform quality monitoring of the olive oils.

Graphical abstract: Application of the Kohonen map analysis (KMA) on chromatographic datasets to achieve unsupervised classification of olive and non-olive oil samples: a novel approach

Article information

Article type
Paper
Submitted
14 Aug 2017
Accepted
18 Oct 2017
First published
19 Oct 2017

Anal. Methods, 2017,9, 6386-6393

Application of the Kohonen map analysis (KMA) on chromatographic datasets to achieve unsupervised classification of olive and non-olive oil samples: a novel approach

K. Kumar, Anal. Methods, 2017, 9, 6386 DOI: 10.1039/C7AY01963G

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