Authentication of Turkish olive oils by using detailed pigment profile and spectroscopic techniques

Abstract

BACKGROUND Minor compounds of olive oil could have discriminatory characteristics in the authentication of this product. It was aimed to determine the detailed pigment profiles of Turkish olive oils and use them in differentiation of the samples in comparison to fast, reliable, and environmentally friendly Fourier‐transform infrared (FTIR) and ultraviolet (UV)–visible spectroscopic techniques. Pigment contents of 91 olive oils obtained from different locations for two consecutive harvesting years were determined with chromatographic analysis and FTIR and UV–visible spectra of these samples were also obtained. All data were analyzed with orthogonal partial least‐squares discriminant analysis to investigate the differentiation ability of these methods with regard to their detailed pigment and spectroscopic profiles. RESULTS Pheophytin a (2.78–8.98 mg kg−1) and lutein (1.19–4.07 mg kg−1) were the major pigments in all samples. Pigment profiles provided successful classification of olive oils with respect to their designated origins and harvesting year with average correct classification rates of 97%. UV–visible spectroscopy has quite similar results with pigment profiles in terms of its discriminatory power. In addition, FTIR and fused data were slightly better in discrimination of the samples, and the fused dataset has the highest correct classification rate of 100%. CONCLUSION Use of detailed pigment profiles is quite promising in authentication of olive oils. However, UV–visible and FTIR spectroscopic techniques could be reliable alternatives for the same purposes. All of the techniques studied have great potential in ‘protected designation of origin’ certification studies. © 2020 Society of Chemical Industry

Fourier transform infrared spectroscopy-chemometric approach as a non-destructive olive cultivar tool for discriminating Portuguese monovarietal olive oils

“…2) recorded for the cvs. Cobrançosa, Madural, Santulhana, and Verdeal Transmontana monovarietal EVOO were in line with those reported in the literature for olive oils from different cultivars, geographical origins, quality grades, analyzed in fresh or after storage [27,28,37,38], in particular with those described by Machado et al [36] for cv. Cobrançosa oils produced in the South region of Portugal (Alentejo region).…”

“…FTIR-chemometric tools allowed the quantification of several characteristics of olive oils (e.g., fatty acids, wax, diacylglycerol, squalene, iodine values, free acidity, peroxide value, color pigment contents, sensory intensities and rancid markers, phenol content and antioxidant activity, among others) [12][13][14][15][16][17][18][19], the identification of olive oil adulteration/mixing with different vegetable oils as well as to discriminate olive oils from other vegetable oils [14,[20][21][22][23][24][25][26], to discriminate the geographical origin of olive oils [12,27,28], to evaluate the thermo/auto oxidation of olive oils [29,30], and to differentiate/classify olive oils according to their commercial grade [31]. Besides these applications, olive oils were also successfully classified according to the olive cultivar/botanical variety, which constitute a major commercial interest due to the high value of monovarietal oils.…”

Fatty acid alkyl ester and wax compositions of olive oils as varietal authentication indicators

“…Orthogonal partial least squares discriminant analysis (OPLS-DA) was the preferred multivariate statistical analysis tool throughout the study to visualize discrimination among the groups of interest. OPLS-DA is a supervised data classification technique, in which the relationship between two data matrices as measured X giving information about the wet chemical data and as dummy Y relying on user-defined class information, was investigated [27]. For chemometric analysis, fatty acid profile matrix included 91 rows (samples) and 11 columns (individual fatty acids).…”

“…Another parameter was variable importance for the projection (VIP) values which were obtained with SIMCA software and used to determine the most effective variables in differentiation. If the VIP values of variables are greater or close to 1, they are considered as significant variables for the OPLS-DA model [27].…”

“…However, differences in oleic and linoleic acid contents were observed between varieties in this study (Table 1) which is consistent with a previous report in the literature [28]. Oleic acid contents of the olive oils from S region were higher (71.21 ± 2.19%) than Table 1 Averages of chemical parameters of olive oils obtained from different varietal origin 1 Free fatty acid, 2,3 specific extinction coefficient at 232 nm and 270 nm, respectively, 4 palmitic acid, 5 palmitoleic acid, 6 heptadecanoic acid, 7 cis-10-heptadecanoic acid, 8 stearic acid, 9 oleic acid, 10 linoleic acid, 11 arachidic acid, 12 linolenic acid, 13 cis-11-eicosenoic acid, 14 cis-11,14-eicosadienoic acid, 15−22 methyl and ethyl forms of the mentioned fatty acids, 23−25 individual waxes according to carbon number, 26 total fatty acid ethyl esters, 27 total fatty acid methyl esters, 28 total fatty acid ethyl and methyl esters as alkyl esters, 29 ratio between total ethyl and methyl esters, 30 1).…”