INSTRUMENTS & APPLICATIONS IR Investigates: Edible Oils Vibrational spectroscopy offers an alternative for detecting adulteration of these dietary supplements. David Filmore FTIR spectra (left) of flaxseed oil (red line) and sunflower oil (black line) are highly similar, but PCA (right) readily differentiates samples of pure and adulterated flaxseed oils. (Adapted with permission from Ozen, B.; Weiss, I.; Mauer, L. J. J. Agric. Food Chem. 2003, 51, 5871–5876.) dible oils from sources as various as consumer confidence in the industry and troscopy have recently surfaced as poten- olives, evening primrose flower, can have a considerable economic impact. tial alternatives. They can be carried out Eflaxseed, and cod liver have grown According to the European Union (EU) by simply directing light at a sample into a substantial component of the multi- website, adulteration of olive oil with with little to no preparation. In addi- billion dollar dietary supplement industry, hazelnut oil is causing an annual loss of 4 tion, data can be collected in a matter of based on myriad reports of lower choles- million euros for EU countries (1). Addi- minutes. Rather than separating particu- terol, better immune health, anti-inflam- tionally, there is potential for serious health lar constituents, they provide an overall matory properties, increased energy, and consequences, as was experienced in the early fingerprint, based on bond vibrations, that overall well-being. 1980s in Spain with the outbreak of severe can be distinguished from other finger- Assuming one trusts the health asser- lung disease—“toxic oil syndrome”—that prints with sophisticated chemometric tions (or allusions) on the label of a partic- was linked to the ingestion of a fraudulent- techniques, such as principal-compo- ular specialty oil product, product authen- ly marketed “olive oil” (2). nent analysis (PCA) and partial least ticity is at a high premium. If one is willing squares (PLS). Theoretically, one need not to pay an elevated price for the specialty Good Vibrations? have a detailed understanding of the chem- label, then inside the container there better Chromatographic techniques, such as GC ical nature of the samples for this approach, be that specific substance recently high- and HPLC, are the standard methods for making it ideal for routine use. lighted in the journal X and obtained from analyzing the fatty acid or sterol compo- Virgin, or unrefined, olive oil is one of said exotic locale. The market for such nents of edible oils. But they involve time- the most established “specialty” oils on products depends on these assurances. consuming sample preparation steps that store shelves that is at least partly market- But the financial incentive for incorpo- destroy the sample, precluding it from ed for its healthful properties. The high rating cheaper oil ingredients, which might further analysis. Nuclear magnetic reso- price of virgin olive oil has made it a target have very similar physical and chemical prop- nance has been shown to be an effective for adulteration. erties to those of the authentic substance, technique, but it is hampered by long and Several European researchers, led by into high-priced, “value-added” products is complex analysis. These approaches do not Gerard Downey from the Irish Agricultural significant. Consequently, oil adulteration is fulfill the need for rapid and nondestruc- not a trivial issue. And the inability to detect tive measurements for routine detection. KEY TERMS: environmental, spectroscopy it in a quick and inexpensive manner degrades Techniques like IR and Raman spec- ©2004 AMERICAN CHEMICAL SOCIETY FEBRUARY 2004 TODAY’S CHEMIST AT WORK 29 INSTRUMENTS & APPLICATIONS and Food Development Authority, recent- extent of sunflower oil adulteration. Using sample, and the researchers did not have ly demonstrated the use of IR for the detec- the first derivatives of the spectra as the to contend with natural chemical varia- tion and quantification of relatively inex- source of variation, the scientists were tions that result from different harvests, pensive sunflower oil in samples of extra able to correctly classify 100% of the 115 geographical locations, and so on. The virgin olive oil (3). Simple observation of samples as pure or adulterated. And using group is looking to extend the technique the IR spectra of pure and adulterated olive PLS regression, which compresses complex to a wider range of samples to be more oil, as well as pure sunflower oil, shows data into a small number of predictive applicable to commercial product testing. no significant differences. But a straight- “scores”, they could quantify sunflower forward hierarchical cluster analysis tech- oil contamination down to 1% concen- Hazelnut Threat nique based on spectral variation clearly trations. They caution, however, that these An even greater challenge, however, is and accurately groups olive oil samples by results are based on a single sunflower oil presented to olive oil suppliers and regu- lators by hazelnut oil. The triacylglycerol, sterol, and fatty acid compositions of olive and hazelnut oil are much more similar than those of olive and sunflower oil. The fraud that is having such a notable economic effect in Europe has involved contamination levels of 5–20% hazelnut oil—concentrations that have not been detectable by conventional methods (4). Lisa Mauer and colleagues at Purdue University attempted to detect extra virgin olive oil adulteration with hazelnut oil using Fourier transform (FT) IR (5). The only difference between the FTIR spectra of the two oils was the intensity of the bands in the 1300–1000 cm–1 region, which is asso- ciated with C–O stretching and OH defor- mation in alcohols. PCA was used to assess the variability of each sample spectrum in this region and reduce the multivariate data to a two-dimensional plot in which the distance between each point is a useful description of the similarity of the samples. PCA plots derived from the spectra of pure olive oil and pure hazelnut oil were clearly distinguishable, but plots of pure and adulterated olive oil were less so. The lowest concentration at which all samples were correctly classified was 25% hazel- nut oil. At the sub-20% levels that the researchers were interested in, the sample points were insufficient for reliable analy- sis. Using the same method, however, the scientists were able to detect and quantify down to 2% sunflower oil adulteration of hazelnut oil, which they say is important because hazelnut oil is gaining recogni- tion as a specialty food product high in vitamin E and monounsaturated fatty acids. Meanwhile, E. Consuelo López-Díez and colleagues at the University of Manches- ter Institute of Science and Technology (U.K.) and the Istituto Sperimentale per la Elaiotecnica in Italy took a slightly differ- ent approach to the problem (6 ). They used Raman spectroscopy, which also meas- ures IR vibrational transitions, but does 30 TODAY’S CHEMIST AT WORK FEBRUARY 2004 www.tcawonline.org so based on the inelastic scattering of longer- than others. “It’s interesting to see that some oil-en.html. wavelength incident light. Specifically, they of the oils, such as canola oil and pumpkin (2) Gelpí, E.; et al. Environ. Health Perspect. 2002, took Raman spectra, via a fiber-optic seed oil or hazelnut oil and olive oil, are 110, 457–464. (3) Downey, G.; McIntyre, P.; Davies, A. N. J. Agric. sampling station that would allow remote structurally so similar,” Mauer says. “But Food Chem. 2002, 50, 5520–5525. sampling for on-the-spot product analysis, while you see dietary claims related to pump- (4) Blanch, G. P.; et al. J. Agric. Food Chem. 1998, of 21 olive–hazelnut oil mixtures ranging kin seed oil, I don’t know of any canola oil 46, 3153–3157. from 0 to 100% hazelnut oil in 5% incre- being sold in capsules for health purposes.” (5) Ozen, B.; Mauer, L. J. J. Agric. Food Chem. 2002, ments (4 replicates of each). A PCA plot 50, 3898–3901. (6) López-Díez, E. C.; Bianchi, G.; Goodacre, R. E. from the spectra showed notable separa- References J. Agric. Food Chem. 2003, 51, 6145–6150. tion between the samples. By using PLS, (1) European Union press release, 2001; http://europa. (7) Ozen, B.;Weiss, I.; Mauer,L. J. J. Agric. Food Chem. the scientists accurately predicted the hazel- eu.int/comm/research/press/2001/pr1110-olive 2003, 51, 5871–5876. ◆ nut concentration in all of the samples, including the 0 and 5% ones. They also applied a sophisticated genetic program- ming (GP) method, which works in an evolutionary manner by progressively select- ing particular spectral features for improved prediction of results. The GP technique was as effective as PLS, but interestingly, the researchers could not pick out any specific input variables that had dispro- portionate influence on the predictions. It was clear that the whole Raman spec- trum (in this case, 3000–1000 cm–1) was necessary for this analysis, highlighting both the difficulty of the problem and the power of the method. Across the Spectrum There are, of course, other important specialty oils that are acquiring substan- tial markets. In another study, Lisa Mauer’s group at Purdue performed FTIR analy- sis and compared 14 so-called dietary supplement oils (DSOs) and 5 common food oils (7 ). “This is the first time this method has been used to differentiate a whole spectrum of food samples, such as the 19 oils used in this study, instead of only comparing two sample types,” Mauer says. They constructed a PCS-type plot for replicate samples of all 19 oils that provid- ed a general picture of which oils were the most chemically similar. Five of the DSOs—borage, evening primrose, flaxseed, grape seed, and pumpkin seed oils—were then chosen for adulteration experiments with either sunflower or canola oil that they closely neighbored or overlapped on the plot.