Comprehensive two-dimensional gas chromatography for fingerprint pattern recognition in olive oils produced by two different techniques in Portuguese olive varieties Galega Vulgar, Cobrançosa e Carrasquenha

• Published in: Analytica chimica acta 2009-02, Vol.633 (2), p.263-270
• Main Authors: Vaz-Freire, L. Torres, da Silva, M.D.R. Gomes, Freitas, A.M. Costa
• Format: Article
• Language: English
• Subjects: Analysis of Variance; Analytical chemistry; Chemistry; Chromatographic methods and physical methods associated with chromatography; Chromatography, Gas - methods; Comprehensive two-dimensional gas chromatography; Exact sciences and technology; Fingerprinting; Fruit - chemistry; Galega; Gas chromatographic methods; Image Processing, Computer-Assisted; Image treatment; Olea; Olea - chemistry; Olive Oil; Plant Extracts - analysis; Plant Oils - analysis; Principal Component Analysis; Reproducibility of Results; Solid phase micro extraction; Spectrometric and optical methods; Volatile organic compounds; Volatilization
• ISSN: 0003-2670; 1873-4324
• DOI: 10.1016/j.aca.2008.11.057

For olive oil production a metal hammer-decanter olive processing line was compared to a traditional metal hammer-press line, a discontinuous method which, if properly used, yields high-quality virgin olive oils. Galega, Carrasquenha and Cobrançosa olives (traditional Portuguese varieties) were studied. The analysis of the aroma compounds was performed after headspace-solid phase micro extraction. The analytical results obtained after comprehensive gas chromatography in tandem with time of flight mass spectrometry (GC × GC/ToFMS) for these three different olive oil varieties, from a single year harvest and processed with two different extraction technologies, were compared using statistical image treatment, by means of ImageJ software, for fingerprint recognitions and compared with principal component analysis when the area data of each chromatographic spot of the contour plots were considered. The differences used to classify the olive oils studied under different groups after principal component analysis were observed independently of the treatment used (peak areas or the sum of the pixels counts). When the individual peak areas were considered, more then 75.7% of the total variance is explained by the first two principal components while in the case where the data were subjected to image treatment 84.0% of the total variance is explained by the first two principal components. In both cases the first and second principal components present eigenvalues higher then 1.0. Fingerprint image monitoring of the aroma compounds of the olive oil allowed a rapid differentiation of the three varieties studied as well as the extraction methods used. The volatile compounds responsible for their characterization were tentatively identified in a bi-dimensional polar/non-polar column set in the GC × GC/Tof-MS apparatus. This methodology allowed the reduction of the number of compounds needed for matrices characterization, preserving the efficiency of the discrimination, when compared with the traditional methods where the identification of all peaks is needed.