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Issue 45, 2017
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Application of the Kohonen map analysis (KMA) on chromatographic datasets to achieve unsupervised classification of olive and non-olive oil samples: a novel approach

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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

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Publication details

The article was received on 14 Aug 2017, accepted on 18 Oct 2017 and first published on 19 Oct 2017


Article type: Paper
DOI: 10.1039/C7AY01963G
Citation: Anal. Methods, 2017,9, 6386-6393
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    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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