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Get the 411 on Edible Oils
A new spectroscopic tool can be used to ID edible oils
by Bertrand Lahner, Phd
Edible oils are used in a wide variety of food products such as margarines, salad, cooking oils, mayonnaise, salad dressings, and confectioners’ coatings. They play a major role in determining the taste, texture, nutrient profile, and shelf life of food products.
Characterizing an unknown sample of edible oil and checking for its purity or for its possible blending with other edible oils are common problems facing oil chemists, because the respective chemical compositions of different edible oils are extremely similar. This article will examine the capability of encoded photometric near infrared (EP-NIR) spectroscopy to collect sufficient NIR information to differentiate samples of three edible oils—canola, corn, and olive.
Three Edible Oils
Canola oil derives from rapeseeds. Compared with other edible oils, canola oil has the lowest level of saturated fat and one of the highest levels of heart-healthy monounsaturated fat. It also contains high levels of omega-3 fatty acids, which can help decrease the risk of heart disease and lower blood pressure. Research has demonstrated that 19 grams of canola oil—about 1 1/2 tablespoons per day—may reduce the risk of coronary heart disease due to its unsaturated fat content if it replaces a similar amount of saturated fat in the diet without increasing calories. Canola oil is thin compared with corn oil and, unlike olive oil, it is flavorless.
Corn oil, which is extracted from the germ of corn, is high in polyunsaturated fat. Corn oil is perfect for frying because it has a high smoke point. It is almost tasteless and odorless. Studies using typical American foods have found that no vegetable oil is more effective than corn oil in lowering blood cholesterol levels.
Olive oil is considered healthier than many others because it has high levels of monounsaturated fat and polyphenols. Evidence from epidemiological studies suggests that a higher proportion of monounsaturated fats in the diet is linked to a reduction in the risk of coronary heart disease.
EP-NIR spectroscopy technology (Aspectrics; Pleasanton, Calif.) covers a wide spectral range of 1,375-2,750 nanometers, whereas traditional NIR systems typically stop at 2,100 nanometers. EP-NIR facilitates fast scanning operation and is capable of simultaneously measuring multiple components in the parts per million range at a rate of 100 scans per second. This rate results in high sample throughput, real-time quality control monitoring, and a high degree of sensitivity through spectral averaging.
Furthermore, EP-NIR units do not utilize hygroscopic optical components or internal lasers. The EP-NIR spectrometers have been designed to encode analytical information in the same way as Fourier transform NIR interferometers, without the environmentally sensitive components of such instruments.
EP-NIR technology is military certified for vibration insensitive operation under Military 202G Method 204D. A high frequency vibration resistance test was performed to determine the effect of vibration on component parts of the analyzer in sweeping frequency ranges of 0.5 to 30 hertz. The units demonstrated no degradation in electrical or photometric performance either during or after the test. Moreover, the photometric performance was further tested by collecting spectra as these vibrations were applied to the analyzer. Even under the stress of such vibrations, the EP-NIR analyzer retained photometric performance and met root mean square signal-to-noise specifications greater than 50,000:1.
EP-NIR spectroscopy relies upon a simple, flexible, and efficient photometric design in which the incoming near infrared beam from a sample is imaged onto a diffraction grating-based spectrograph. The dispersed radiation from the grating is then imaged across an aperture onto the surface of an encoder disk, which is spinning at 6,000 revolutions per minute (100 hertz), providing fast real-time detection. The encoder disk has a series of reflective tracks spatially located within the dispersed grating image to correspond to the wavelengths and wavelength regions used for the analysis.
Each track has a pattern that produces a reflected beam with a unique sinusoidal modulation for each individual wavelength. The reflected beams are brought to an image on a single detector, which generates an interferogram type of signal. The intensity contribution for each wavelength component is obtained by applying a Fourier transform to the interferogram.
Identifying Oil Samples
An EP-NIR spectrometer covering the 1,375-2,750 nanometer spectral range was coupled to an external halogen NIR source and a 2-millimeter path-length process transmission multimode fiber probe to positively identify samples of canola, corn, and olive oils without false positive responses.
Commercially available samples of canola, corn, and olive oils were analyzed in four replicates, re-collecting a new background between each assay. All spectra were collected using a chemometrics software package (Aspectrics). Data collection parameters were 30-second time integration. Data treatment was performed in three steps:
- Calculating absorbance spectra (from single beam intensity spectra) using open beam configuration as a background;
- Calculating the second order derivative for each absorbance spectrum; and
- Developing principal component analysis (PCA)-based methods for the identification of each type of oil.
Initial chemometrics testing was conducted on the absorbance spectra themselves (Figure 1, p. 36). This approach yielded no significant result; the NIR spectroscopic differences among the three types of oils were too small to be identified and modeled using a PCA approach. When these small variations were enhanced by calculating the second order derivative spectrum of each of the sample absorbance spectrum, however, spectral ranges of 1,600-1,950 nanometers and 2,000-2,600 nanometers (Figure 2, p. 36) were clearly identified as relevant for the identification of material.
Results demonstrated that when projecting the EP-NIR spectrometer response in a space designed to identify a type of oil, all oil spectra are plotted within 99% probability of being the specific type of oil. In addition, the remaining oil samples are plotted within 99% probability of not being the specific type of oil (Figure 3, p. 36). It should be noted that it was the access to spectral information in the 2,000-2,600 nanometer (5,000-3,850 cm-1) range that enabled this application.
The results from this experiment confirm that EP-NIR spectroscopy, together with an NIR source and a 2-millimeter path-length process transmission multimode fiber probe, can identify each type of oil. The results also confirm that the model is solid enough to prevent even partial false positive responses. A significant source of spectral information is obtained in the range between 2,000-2,600 nano-meters (5,000-3,850 cm-1).
Lanher is director of applied sciences and technology at Aspectrics. For more information, call (925) 931-9270 or visit www.aspectrics.com.