218 Eur. J. Lipid Sci. Technol. 2010, 112, 218–226 Research Paper Comparison of fatty acid profiles and mid-infrared spectral data for classification of olive oils Gozde Gurdeniz, Banu Ozen and Figen Tokatli Izmir Institute of Technology, Department of Food Engineering, Urla-Izmir, Turkey The composition of olive oils may vary depending on environmental and technological factors. Fatty acid profiles and Fourier-transform infrared (FT-IR) spectroscopy data in combination with chemometric methods were used to classify extra-virgin olive oils according to geographical origin and harvest year. Oils were obtained from 30 different areas of northern and southern parts of the Aegean Region of Turkey for two consecutive harvest years. Fatty acid composition data analyzed with principal component analysis was more successful in distinguishing northern olive oil samples from southern samples compared to spectral data. Both methods have the ability to differentiate olive oil samples with respect to harvest year. Partial least squares (PLS) analysis was also applied to detect a correlation between fatty acid profile and spectral data. Correlation coefficients (R2) of a calibration set for stearic, oleic, linoleic, arachidic and linolenic acids were determined as 0.83, 0.97, 0.97, 0.83 and 0.69, respectively. Fatty acid profiles were very effective in classification of oils with respect to geographic origin and harvest year. On the other hand, FT-IRspectra in combination with PLS could be a useful and rapid tool for the determination of some of the fatty acids of olive oils. Keywords: Classification / Fatty acid profile / Infrared spectroscopy / Olive oil Received: October 10, 2008; accepted: March 19, 2009 DOI 10.1002/ejlt.200800229 1 Introduction acids, waxes, sterols, hydrocarbons) as well as subtle differ- ences in the concentration of major components [2, 3]. The recent popularity of olive oil could be attributed to not The fatty acid profile determined by gas chromatography only its sensorial characteristics but also its potential health supplies extremely useful information for the classification benefits. These benefits have been related to its well-balanced studies. There are several studies involving the use of the fatty fatty acid composition, where oleic acid is the main compo- acid composition in the classification of olive oils. Differ- nent, and to the presence of minor biomolecules, such as entiation of monovarietal olive oils by their basic classes of vitamins and natural antioxidants [1]. compounds including fatty acids was achieved using principal The composition of olive oils varies with geographic origin component analysis (PCA) and linear discriminant analysis due to a number of different factors: regional differences in [4]. It was stated that the genotype has a higher influence on climate, soil, and agricultural practice. In Europe, certification the fatty acid composition than the microclimate [5]. Also, a of extra-virgin olive oils according to the geographical origin is study on Sicilian olive oils indicated that the effect of the cul- assured by the Designation of Origin regulations [Protected tivar is predominant in the olive oil classification based on fatty Designation of Origin (PDO) and Protected Geographical acid composition, but a minor but well-defined geographic Indication (PGI)]. Classification according to the area of effect is also present [6]. production of high-commercial-value oils exploits the infor- Although chromatographic methods supply a high degree mation about the content of minor constituents (phenolic of classification, there is an increasing demand for rapid, inexpensive and effective techniques for the determination of the authenticity of olive oils, and infrared (IR) spectroscopy combined with chemometric techniques is one of the promis- Correspondence: Banu Ozen, Izmir Institute of Technology, Department of Food Engineering, 35430 Urla-Izmir, Turkey. ing rapid methods. IR spectroscopy, a vibrational spectro- E-mail: [email protected] scopic technique, has advantages such as high speed of meas- Fax: 190 232 7506196 urement, moderate instrument cost and relative ease of sample © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.ejlst.com Eur. J. Lipid Sci. Technol. 2010, 112, 218–226 Classification of olive oils 219 preparation, especially for liquid and paste materials [7]. north (N) or south (S) according to the region where the Changes in dipole moment of molecules due to absorbance of olives were obtained from (Tables 1 and 2). Also, numbers energy from a light source in the IR region produce the IR beside N or S represent the first or second harvest year. While spectrum. Peaks observed in the IR profile of a fat or oil sam- mainly the Ayvalik variety is cultivated in the North Aegean, ple correspond to structural or functional groups. When ana- Memecik is the dominant variety in the southern part of the lyzed with multivariate statistical techniques, even subtle dif- Aegean region. As soon as the olive oil samples were received ferences in the IR spectra of fats and oils would become useful from the processing plant, they were transferred into dark for characterization and classification studies. IR spectroscopy glass bottles and kept at 8 7C in a refrigerator. All analyses could also provide quantitative information such as trans con- were completed within 2 months after receipt of the samples tent, iodine value, peroxide value and free fatty acid content in each harvest year. about fats and oils [8]. Pure extra-virgin olive oil samples were differentiated from other oils using Fourier-transform (FT)- 2.2 Gas chromatographic analysis IR and FT-Raman spectroscopy with multivariate statistical methods [9, 10]. Tapp et al. [11] were able to discriminate Fatty acid methyl esters (FAME) containing C8–C24 (2–11% extra-virgin olive oils from different producing countries with relative concentration) were used as reference standard FT-IR in combination with multivariate analysis. 93.9% cor- (Supelco No. 18918). The olive oil samples were dissolved in rect classification of olive oil samples with respect to geo- hexane and saponified to their methyl esters with the addition graphical origin was achieved using near-IR (NIR) spectros- of methanolic KOH solution as described in the official jour- copy in combination with factorial discriminant analysis [12]. nal of the EU [16]. Gas chromatographic analyses were per- FT-IR spectra, which contain information about the com- formed on an Agilent 6890 gas chromatograph with a flame plete chemical composition of the analyzed material, have the ionization detector (FID) and a split/splittless (1 : 50) injector, advantage of rapid analysis time. So, there exist studies in- equipped with a HP 88 capillary column (100 m60.25 mm volving the use of FT-IR with chemometrics for the determi- ID60.2 mm). The carrier gas was helium with 2 mL/min nation of analytical parameters such as peroxide value and free constant flow. Injection and detector temperatures were 250 fatty acidity value [13, 14]. Another analytically determined and 280 7C, respectively. The oven temperature program was parameter, fatty acids are one of the major ingredients that run at 120 7C for 1 min, varied at 3 7C/min to 220 7C and held olive oil contains in its chemical structure. Classification at this temperature for 5 min. Peak quantification is expressed studies could also provide the opportunity to check whether as percentage of FAME using FAME standards and sample there is a correlation between the IR spectra and the fatty acid chromatograms. Measurements were conducted in duplicate profile of an olive oil obtained from GC analysis using multi- or triplicate for each olive oil sample. variate statistical analysis. In this respect, Galtier and Dupuy Fatty acids used in the analysis were myristic acid (14:0), [15] verified the availability of NIR spectroscopy with chem- palmitic acid (16:0), palmitoleic acid (16:1), stearic acid ometrics instead of chromatographic determinations such as (18:0), oleic acid (18:1), linoleic acid (18:2), arachidic acid fatty acids and triacylglycerols for the determination of origin. (20:0), linolenic acid (18:3) and behenic acid (22:0). In this study, chemometric techniques were applied to the classification of extra-virgin olive oil samples according to 2.3 FT-mid-IR analysis geographical origin and harvest year, using two different data sets: (1) fatty acid profiles obtained from GC analysis and All IR spectra were acquired in the 4000–650 cm–1 range with (2) spectral data obtained from FT-IR. The discrimination a Perkin Elmer Spectrum 100 FT-IR spectrometer (Perkin ability of these two methods was compared and discussed. Elmer, Wellesley, MA, USA). This instrument was equipped Furthermore, the relation between FT-IR spectra and fatty with a horizontal attenuated total reflectance (HATR) sam- acid profiles to predict the fatty acid composition of olive oils pling accessory (ZnSe crystal) and a deuterated triglycine was studied with multivariate statistical analysis. sulfate (DTGS) detector. The HATR accessory was used to collect the spectral data of the oils. The resolution was set at 2cm–1 and the number of scans collected for each spectrum 2 Materials and methods was 128. The ZnSe crystal was cleaned with hexane in be- tween sample runs. Measurements were conducted in dupli- 2.1 Samples cate or triplicate for each olive oil sample and harvest year. Extra-virgin olive oil samples belonging to 30 different loca- 2.4 Statistical analysis tions of the Aegean region of Turkey were obtained from the same olive oil producer for two consecutive harvest years Data analysis was performed using multivariate statistical (2005/06 and 2006/07). There were 25 and 22 olive oil sam- methods with SIMCA software (Umetrics, Sweden). The ples belonging to the 2005/06 and 2006/07 harvest years, 3620–2520 and 1875.5–675 cm–1 regions of the FT-IR spec- respectively. The olive oil samples were coded either as tra were used in the statistical analysis.