Application of the Kohonen map analysis (KMA) on chromatographic datasets to achieve unsupervised classification of olive and non-olive oil samples: a novel approach. Issue 45 (8th November 2017)

• Record Type: Journal Article
• Authors: Kumar, Keshav
• Is Part Of: Analytical methods. Volume 9:Issue 45(2017)
• Page Start: 6386
• Page End: 6393
• Publication Date: 2017-11-08
• Subjects: Chemistry, Analytic -- Periodicals; Analytical biochemistry -- Periodicals; Chemical laboratories -- Standards -- Periodicals; 543.1905
• DOI: 10.1039/c7ay01963g
• Languages: English
• ISSNs: 1759-9660

Abstract

Abstract : 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. 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.