The Use of FTIR Spectroscopy and Chemometrics for Rapid Authentication of Extra Virgin Olive Oil

The authenticity of high value edible fats and oils including extra virgin olive oil (EVOO) is an emerging issue, currently. The potential employment of Fourier transform infrared (FTIR) spectroscopy in combination with chemometrics of multivariate calibration and discriminant analysis has been exploited for rapid authentication of EVOO from canola oil (Ca‐O). The optimization of two calibration models of partial least square (PLS) and principle component regression was performed in order to quantify the level of Ca‐O in EVOO. The chemometrics of discriminant analysis (DA) was used for making the classification between pure EVOO and EVOO adulterated with Ca‐O. The individual oils and their blends were scanned on good contact with ZnSe crystals in horizontal attenuated total reflectance, as a sampling technique. The wavenumbers of 3,028–2,985 and 1,200–987 cm^?1 were used for quantification and classification of EVOO adulterated with Ca‐O. The results showed that PLS with normal FTIR spectra was well suited for quantitative analysis of Ca‐O with a value of the coefficient of determination (R²) > 0.99. The error, expressed as root mean square error of calibration obtained was relatively low, i.e. 0.108 % (v/v). DA can make the classification between pure EVOO and that adulterated with Ca‐O with one misclassified reported.     

Developing FT-NIR and PLS1 Methodology for Predicting Adulteration in Representative Varieties/Blends of Extra Virgin Olive Oils

It was previously demonstrated that Fourier transform near infrared (FT‐NIR) spectroscopy and partial least squares (PLS1) were successfully used to assess whether an olive oil was extra virgin, and if adulterated, with which type of vegetable oil and by how much using previously developed PLS1 calibration models. This last prediction required an initial set of four PLS1 calibration models that were based on gravimetrically prepared mixtures of a specific variety of extra virgin olive oil (EVOO) spiked with adulterants. The current study was undertaken after obtaining a range of EVOO varieties grown in different countries. It was found that all the different types of EVOO varieties investigated belonged to four distinct groups, and each required the development of additional sets of specific PLS1 calibration models to ensure that they can be used to predict low concentrations of vegetable oils high in linoleic, oleic, or palmitic acid, and/or refined olive oil. These four distinct sets of PLS1 calibration models were required to cover the range of EVOO varieties with a linoleic acid content from 1.3 to 15.5 % of total fatty acids. An FT‐NIR library was established with 66 EVOO products obtained from California and Europe. The quality and/or purity of EVOO were assessed by determining the FT‐NIR Index, a measure of the volatile content of EVOO. The use of these PLS1 calibration models made it possible to predict the authenticity of EVOO and the identity and quantity of potential adulterant oils in minutes.     

Evaluation of MALDI-TOF/MS Technology in Olive Oil Adulteration

Adulteration of extra virgin olive oil (EVOO) by addition of other vegetable oils or lower-grade olive oils is a common problem of the oil market worldwide. Therefore, we developed a fast protocol for detection of EVOO adulteration by mass spectrometry fingerprinting of triacylglycerol (TAG) profiles based on MALDI-TOF/MS. For that purpose, EVOO TAG profiles were compared with those of edible sunflower oil and olive oil composed of refined olive oil and virgin olive oils. Adulteration of EVOO was simulated by addition of sunflower and mixture of refined olive oil and virgin olive oils at 1, 10 and 20% w/w. Results of mass spectrometry TAG profiling were compared with routinely assessed K values for identification of adulteration. MALDI-TOF/MS technology coupled with statistical analysis was proven as useful for detection of adulteration in EVOO at a rate down to 1%. In contrast, standard spectrophotometric methods failed to identify minor adulterations. In addition, the ability of MALDI-TOF/MS in detection of adulteration was tested on EVOO samples from different geographical regions. Results demonstrated that MALDI-TOF/MS technology coupled with statistical analysis is able to distinguish adulterated oils from other EVOO.     

Determination of the Si?H content of hydrogen silicone oil by a combination of the fourier transform near infrared,attenuated total reflectance–fourier transform infrared,and partial least squares regression models

To verify the feasibility of the determination of the Si? H content (HC) of hydrogen silicone oil (HS‐oil) with Fourier transform near infrared (FT‐NIR) spectroscopy and attenuated total reflectance (ATR)–Fourier transform infrared (FTIR) spectroscopy combined with the partial least squares regression (PLS‐R) model, HS‐oil samples were synthesized from concentrated hydrosilicone oil (HC = 1.4 wt %), octamethylcyclotetrasiloxane, and hexamethyldisiloxane or prepared by the dilution of concentrated hydrosilicone oil with octamethylcyclotetrasiloxane. The FT‐NIR PLS‐R model (8695–4000 cm^?1, two principal components) was developed from the FT‐NIR spectral data, and the coefficient of determination for cross‐validation (R²) and the coefficient of determination for external validation (r²) were 0.992 and 0.995, respectively. The ATR–FTIR PLS‐R model (2302–2040 cm^?1, one principal component) was developed from the ATR–FTIR spectral data; it produced an R² of 0.995 and an r² of 0.996. This study demonstrated that the combination of FT‐NIR and ATR–FTIR spectroscopy with the PLS‐R model were successfully used to determine the HC of the HS‐oil. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40694.     

Determination of the SiH content of hydrogen silicone oil by a combination of the fourier transform near infrared,attenuated total reflectance–fourier transform infrared,and partial least squares regression models

To verify the feasibility of the determination of the Si?H content (HC) of hydrogen silicone oil (HS‐oil) with Fourier transform near infrared (FT‐NIR) spectroscopy and attenuated total reflectance (ATR)–Fourier transform infrared (FTIR) spectroscopy combined with the partial least squares regression (PLS‐R) model, HS‐oil samples were synthesized from concentrated hydrosilicone oil (HC = 1.4 wt %), octamethylcyclotetrasiloxane, and hexamethyldisiloxane or prepared by the dilution of concentrated hydrosilicone oil with octamethylcyclotetrasiloxane. The FT‐NIR PLS‐R model (8695–4000 cm^?1, two principal components) was developed from the FT‐NIR spectral data, and the coefficient of determination for cross‐validation (R²) and the coefficient of determination for external validation (r²) were 0.992 and 0.995, respectively. The ATR–FTIR PLS‐R model (2302–2040 cm^?1, one principal component) was developed from the ATR–FTIR spectral data; it produced an R² of 0.995 and an r² of 0.996. This study demonstrated that the combination of FT‐NIR and ATR–FTIR spectroscopy with the PLS‐R model were successfully used to determine the HC of the HS‐oil. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40694.     

Investigating Chemical Properties and Oxidative Stability of Kernel Oil from Pistacia khinjuk Growing Wild in Iran

In this study in order to introduce a new vegetable oil, oxidative stability and chemical characteristics of Pistacia khinjuk kernel oil (PKKO) as compared with P. atlantica kernel oil (PAKO) and extra virgin olive oil (EVOO) were investigated. Oxidative stability of studied oils was considered based on the conjugated diene value (CDV), carbonyl value (CV) and oil/oxidative stability index (OSI) through an 8‐h thermal process at 170 °C. Also, chemical characteristics [fatty acid composition, unsaponifiable matter (USM), total tocopherols (TT), total phenolics (TP) and total sterols (TS), iodine value, saponification number and waxes] of these oils were analyzed. The ratio of polyunsaturated fatty acids to saturated fatty acids and the oxidizability (Cox) value of PKKO (1.14 and 2.78; respectively) were between those of PAKO (2.37 and 4.23; respectively) and EVOO (1.14 and 2.78; respectively). USM content of the three studied oils was between 1.1 and 1.51 %. TT and TP contents of PKKO (619.4 and 26.6 ppm) were lower than those of PAKO (845.33 and 75.22 ppm) and higher than those of EVOO (365.23 and 19.78 ppm). TS contents of PKKO, PAKO and EVOO were 2,500, 2,150 and 3,800 ppm, respectively. Oxidative stability data indicated that PKKO is the most resilient oil against lipid oxidation, followed by PAKO and EVOO. CDV significantly increased by the lowest speed for PKKO, followed by PAKO and EVOO. Increase of CV and reduction of OSI for PKKO, PAKO and EVOO were 29.2, 128 and 338.7 and 32.8, 67.9 and 79.3 %; respectively.     

Oxidative Stability and Changes in Chemical Composition of Extra Virgin Olive Oils After Short‐Term Deep‐Frying of French Fries

We aimed at investigating oxidative stability and changes in fatty acid and tocopherol composition of extra virgin olive oil (EVOO) in comparison with refined seed oils during short‐term deep‐frying of French fries, and changes in the composition of the French fries deep‐fried in EVOO. EVOO samples from Spain, Brazil, and Portugal, and refined seed oils of soybean and sunflower were studied. Oil samples were used for deep‐frying of French fries at 180 °C, for up to 75 min of successive frying. Tocopherol and fatty acid composition were determined in fresh and spent vegetable oils. Tocopherol, fatty acid, and volatile composition (by SPME–GC–MS) were also determined in French fries deep‐fried in EVOO. Oil oxidation was monitored by peroxide, acid, and p‐anisidine values, and by Rancimat after deep‐frying. Differential scanning calorimetry (DSC) analysis was used as a proxy of the quality of the spent oils. EVOOs presented the lowest degree of oleic and linoleic acids losses, low formation of free fatty acids and carbonyl compounds, and were highly stable after deep‐frying. In addition, oleic acid, tocopherols, and flavor compounds were transferred from EVOO into the French fries. In conclusion, EVOOs were more stable than refined seed oils during short‐term deep‐frying of French fries and also contributed to enhance the nutritional value, and possibly improve the flavor, of the fries prepared in EVOO.     

Novel,Rapid Identification,and Quantification of Adulterants in Extra Virgin Olive Oil Using Near‐Infrared Spectroscopy and Chemometrics

A new, rapid Fourier transform near infrared (FT‐NIR) spectroscopic procedure is described to screen for the authenticity of extra virgin olive oils (EVOO) and to determine the kind and amount of an adulterant in EVOO. To screen EVOO, a partial least squares (PLS1) calibration model was developed to estimate a newly created FT‐NIR index based mainly on the relative intensities of two unique carbonyl overtone absorptions in the FT‐NIR spectra of EVOO and other mixtures attributed to volatile (5280 cm^?1) and non‐volatile (5180 cm^?1) components. Spectra were also used to predict the fatty acid (FA) composition of EVOO or samples spiked with an adulterant using previously developed PLS1 calibration models. Some adulterated mixtures could be identified provided the FA profile was sufficiently different from those of EVOO. To identify the type and determine the quantity of an adulterant, gravimetric mixtures were prepared by spiking EVOO with different concentrations of each adulterant. Based on FT‐NIR spectra, four PLS1 calibration models were developed for four specific groups of adulterants, each with a characteristic FA composition. Using these different PLS1 calibration models for prediction, plots of predicted vs. gravimetric concentrations of an adulterant in EVOO yielded linear regression functions with four unique sets of slopes, one for each group of adulterants. Four corresponding slope rules were defined that allowed for the determination of the nature and concentration of an adulterant in EVOO products by applying these four calibration models. The standard addition technique was used for confirmation.     

Detection of Olive Oil Adulteration Using FT-IR Spectroscopy and PLS with Variable Importance of Projection (VIP) Scores

Determination of adulteration and authenticity of extra virgin olive oil (EVOO) was investigated by means of infrared spectroscopy and chemometric methods. The study was focused on the detection and quantification of extra virgin olive oil adulteration by soybean (SB) and sunflower (SF) oils using FT-IR spectroscopy based on the use of PLS modeling and variable importance of projection (VIP) scores. A PLS model, using orthogonal signal correction and mean centering data pretreatments, and VIP scores variable preselection, was able to predict the concentration of sunflower and soybean oil adulterants in the 1–24 % weight ratio range with relative prediction errors lower than 3 % (w/w), for external validation samples. Moreover, the PLS-DA (discriminant analysis) model using the same preselected wavelengths was able to explain 99.9 % of variance and to predict with 100 % accuracy both classes of adulteration (EVOO–SB and EVOO–SF) in the external validation.     

Photoinduced and thermal oxidation of rapeseed and sunflower oils

The aim of the present study was to compare oxidative stability of different sunflower and rapeseed oils. Ultra violet (UV) irradiation was used as an accelerator of the oil oxidation process. After UV irradiation, the formed volatile compounds were extracted by headspace solid‐phase microextraction HS‐SPME (DVB/CAR/PDMS fibre) and analysed by gas chromatography coupled with a flame ionization detector (GC/FID). At the same time, the same oil samples were thermally oxidized. The induction periods were determined on the basis of hexanal to 2‐trans‐nonenal ratio in the analysed samples. Finally, the obtained results were compared with induction period values obtained through the determination of peroxide and anisidine values, and from the Rancimat method, manostatic test and differential scanning calorimetry (DSC) method. The results obtained using the new method were well correlated with those achieved with the well‐established analytical techniques. The values of the induction period obtained after UV/HS‐SPME/GC/FID were up to three times higher than those from Rancimat, but the correlation between these two methods was on a very good level (correlation coefficient R>0.98). Similar correlation was also observed between these new methods and the DSC or manostatic test. In all cases, better results were obtained for rapeseed oils than sunflower oils.     

Detection of Soft‐Deodorized Olive Oil and Refined Vegetable Oils in Virgin Olive Oil Using Near Infrared Spectroscopy and Traditional Analytical Parameters

The European Parliament identifies virgin olive oil (VOO) as one of the foods which are often subject to fraudulent activities. Possibilities of adulteration are the application of illegal soft deodorization of extra virgin olive oil (EVOO) or the commercialization of blends of EVOO with soft‐deodorized EVOO or refined vegetable oils. Despite the search for possibilities to prove the illegal soft deodorization of EVOO or the addition of cheaper vegetable oils to EVOO, suitable methods are still missing. Therefore, the aim of the study is to develop a new analytical and statistical approach addressing detection of mild deodorization or addition of refined foreign oils. For this purpose, VOOs are treated in lab‐scale for 1 h up to 28 days at different temperatures (20, 50, 60, 80,100, 110, and 170 °C) in order to simulate and study the effect of heat treatment on known analytical parameters by near infrared spectroscopy (NIR). A logit regression model enabling the calculation of the probability for a heat treatment is developed. This new methodology allows detecting both soft deodorized olive oils and blends of EVOO with cheaper full refined vegetable oils. Adding only 10% of full refined oil could be detected in extra VOO. Practical Applications: NIR methods combined with chemometrics have become one of the most attractive analytical tools to control quality of food. It is a simple, precise, and rapid method. All relevant analytical parameters of oxidative and thermal fat degradation can be determined in a single run and be used to detect adulterated virgin olive oils (VOOs). The use of a simple equation developed from the logistic regression using peroxide value, K‐values, p‐anisidine value, pyropheophytine, 1,2‐diacylglycerols, total polar compounds and monomeric oxidized triacylglycerols, and other well‐known parameters allows to detect mild deodorized olive oils or also blends of VOO with soft‐deodorized ones or the addition of low amounts of foreign vegetable oils. This technique has potential to be used as a screening method for the detection of adulterated olive oils using both the traditional laboratory methods and the corresponding NIR‐methods.     

Palm oil analysis in adulterated sesame oil using chromatography and FTIR spectroscopy

This study highlights the application of two analytical techniques, namely GC‐FID and FTIR spectroscopy, for analysis of refined‐bleached‐deodorized palm oil (RBD‐PO) in adulterated sesame oil (SeO). Using GC‐FID, the profiles of fatty acids were used for the evaluation of SeO adulteration. The increased concentrations of palmitic and oleic acids together with the decreased levels of stearic, linoleic, and linolenic acids with the increasing contents of RBD‐PO in SeO can be used for monitoring the presence of RBD‐PO in SeO. Meanwhile, FTIR spectroscopy combined with multivariate calibration of partial least square (PLS) has been successfully developed for the detection and quantification of RBD‐PO in SeO using the combined frequencies of 3040–2995, 1660–1654, and 1150–1050 cm^?1. The values of coefficient of determination (R²) for the relationship between actual versus FTIR‐calculated values of RBD‐PO in SeO and root mean square error of calibration (RMSEC) obtained are 0.997 and 1.32% v/v, respectively. In addition, using three factors, the root mean square error of prediction (RMSEP) value obtained using the developed PLS calibration model is relatively low, i.e., 1.83% v/v. Practical Application: The adulteration practice is commonly encountered in fats and oils industry. It involves the replacement of high value edible oils such as sesame oil with the lower ones like palm oil. Gas chromatography and FTIR spectroscopy can be used as reliable and accurate analytical techniques for detection and quantification of palm oil in sesame oil.     

Chemometric Studies on zNose™ and Machine Vision Technologies for Discrimination of Commercial Extra Virgin Olive Oils

The aim of this study was to classify Turkish commercial extra virgin olive oil (EVOO) samples according to geographical origins by using surface acoustic wave sensing electronic nose (zNose?) and machine vision system (MVS) analyses in combination with chemometric approaches. EVOO samples obtained from north and south Aegean region were used in the study. The data analyses were performed with principal component analysis class models, partial least squares‐discriminant analysis (PLS‐DA) and hierarchical cluster analysis (HCA). Based on the zNose? analysis, it was found that EVOO aroma profiles could be discriminated successfully according to geographical origin of the samples with the aid of the PLS‐DA method. Color analysis was conducted as an additional sensory quality parameter that is preferred by the consumers. The results of HCA and PLS‐DA methods demonstrated that color measurement alone was not an effective discriminative factor for classification of EVOO. However, PLS‐DA and HCA methods provided clear differentiation among the EVOO samples in terms of electronic nose and color measurements. This study is significant from the point of evaluating the potential of zNose? in combination with MVS as a rapid method for the classification of geographically different EVOO produced in industry.     

Detection of Extra Virgin Olive Oil Adulteration With Edible Oils Using Front‐Face Fluorescence and Visible Spectroscopies

Synchronous front‐face fluorescence and visible spectroscopies are utilized for the simple, rapid, and nondestructive quantification of extra virgin olive oil (EVOO) adulteration with corn, soybean, and sunflower oils. For each adulterant, 42 adulterated EVOO samples in the adulterant amount in the range 1.0–50 g/100 g were prepared. The partial‐least‐squares regression was executed for quantification. Both full (leave‐one‐out) cross‐validation and external validation were performed to evaluate the predictive ability. The plots of observed vs. predicted values exhibit high linearity. The coefficient of determination (R²) values are larger than 0.99. The root mean square errors of both cross‐validation and prediction are no more than 2%. The detection limits for the three seed oils using fluorescence and visible spectroscopies are in the range of 1.5–2.2% and 1.8–2.4%, respectively. The merit of this method is that both the front‐face fluorescence and visible spectroscopies are recorded toward neat oils, avoiding any sample pretreatment including dilution.     

Handheld Near‐Infrared Spectroscopy for Distinction of Extra Virgin Olive Oil from Other Olive Oil Grades Substantiated by Compositional Data

Miniaturization of analytical technology has paved the way for in‐situ screening of foods. In the current study, the spectral features of olive oils are examined by handheld near‐infrared spectroscopy to explore the technology's capabilities to distinguish extra virgin olive oil (EVOO) from lower grade oils. Eighty EVOO, forty refined olive oil (ROO), and ten pomace olive oil (POO) samples are analysed for their spectral and compositional features. The latter included analysis of the fatty acids (FAs), the chlorophylls and carotenoids, chromatic coordinates and moisture contents. The 1350–1570 nm wavelength range appeared most suitable for distinction of the oils. One‐class classification models with three different classifiers are subsequently estimated using this range, and their quantitative performance is assessed from probabilistic data. Soft independent modeling of class analogies models appears to predict the identity of the oils with a high success rate. Compared to the other oils, POO comprises a significantly higher and lower proportion of polyunsaturated and monounsaturated FAs, respectively. Higher contents of chlorophylls, carotenoids, and moisture are noted for EVOO. The relevant spectral information for distinction of the oils correlates strongly with the degree of unsaturation of the oils as well as their levels of chlorophylls, carotenoids, and moisture. Practical Applications: The findings of this study demonstrate that the handheld NIRS technique is promising for future rapid screening of olive oil grades. The statistical methods used and the robust validation procedure will help potential users to select the optimal strategy for multivariate data analysis. In addition, the exploration of correlations with compositional characteristics provides insight into the handheld NIRS working mechanism in regard to EVOO authentication.     

Method for determining oxidation of vegetable oils by near-infrared spectroscopy

Use of near-infrared (NIR) transmittance spectroscopy for rapid determination of the oxidation level in soybean oils (SBO) was investigated, and calibrations were developed for quantitative determination of peroxide value (PV), conjugated diene value (CD), and anisidine value (AV) of SBO. Partial least squares (PLS) regression and forward stepwise multiple linear regression were used to develop calibration models from spectral data in log 1/T, first derivative and second derivative of log 1/T formats for both 1- and 2-mm path lengths. The models were validated by comparing NIR results from independent sample sets to the values obtained by official methods. The spectral region from 1100 to 2200 nm was best for measuring oxidation when using a 2-mm path length. PLS regression using first-derivative spectra gave the best results for PV. For the validation sets, linear relationships were obtained for PV (r=0.99), and CD (r=0.95), compared with accepted reference procedures. However, measurement of AV by NIR was less successful than measurement of the other two indices of oxidation, especially for an external validation sample set. Results obtained in this study indicate that NIR spectroscopy is a useful technique for measuring oxidation in soybean oil.     

Olive Oil Quality and Sensory Changes During House‐Use Simulation and Temporal Assessment Using an Electronic Tongue

During domestic usage, olive oil bottle manipulation may lead to a quality decrease due to agitation and oxygenation. Therefore, assessing the domestic consumption time period during which the initial quality grade is retained may allow including this information as a recommendation, ensuring olive oil consumers’ satisfaction. Temporal changes of physicochemical, chemical, and sensory parameters of extra‐virgin olive oils (EVOO) were monitored during 1‐month simulated house‐use conditions. It was observed that K₂₃₂ (R‐Pearson ≥+0.81) and ΔK increased resulting in a significant olive oil quality decrease from EVOO (during the initial 21 days of simulated usage) to lampante olive oil (after 28 days of simulated usage) as well as the appearance of rancid sensation. As lampante olive oils cannot be commercialized, it is pertinent to establish olive oil shelf life under usual home‐use conditions. Principal component analysis allowed grouping the olive oils according to home‐use time period and how bottles are stored after their first opening, showing that the overall olive oil physicochemical and sensory characteristics changed with the domestic‐use time period. Finally, a potentiometric electronic tongue coupled with linear discriminant analysis was used to discriminate olive oils according to the domestic‐use time period (leave‐one‐out cross‐validation sensitivities ≥95%). Thus, this device could be used to indirectly assess the quality of the remaining bottled olive oil by establishing for how long an olive oil bottle has been used under domestic conditions.     

Quantitative Fourier transform infrared analysis for anisidine value and aldehydes in thermally stressed oils

A Fourier transform infrared (FTIR) transmission-based spectroscopic method was investigated for the simultaneous monitoring of aldehyde formation and the determination of anisidine value (AV) in thermally stressed oils. Synthetic calibration standards were prepared by adding known amounts of hexanal,t-2-hexenal andt,t-2,4-decadienal to canola oil (these compounds considered representative of aldehydic compounds formed during oxidation) plus random amounts of other compounds representative of oxidation by-products. The standards were analyzed for their chemical AV. With the partial least squares (PLS) technique, an FTIR spectrometer was calibrated to predict both the concentrations of individual aldehyde types and AV, with the individual aldehyde contributions being related to the chemical AV by multiple linear regression to derive “apparent” AV values. The predictive capability of the PLS calibrations was assessed by analyzing canola oils that were thermally stressed at 120, 155, and 200°C. The apparent AV, predicted for these samples, matched the chemical AV values within ±1.65 AV units. A PLS calibration also was derived by using thermally stressed samples as calibration standards. This approach provided similar predictive accuracy as the use of synthetic calibration standards. As such, quantitative determination of AV by FTIR spectroscopy was shown to be feasible, and the synthetic calibration approach provided additional information on the aldehyde types present in a sample and allowed the use of a simple gravimetric approach for calibrating an FTIR spectrometer. This study provides the basis for the development of a rapid, automated FTIR method for the direct analysis for AV of thermally stressed fats and oils in their neat form without the use of chemical reagents. The implementation of such a method as a quality control tool would eliminate the use and disposal of hazardous solvents and reagents, required by the conventional chemical method, and drastically reduce analysis time (∼2 min/sample). Possible applications include monitoring of the oxidative state of frying oils or evaluation of oxidative stability of biodegradable lubricants.     

Simultaneous determination of lodine value and trans content of fats and oils by single-bounce horizontal attenuated total reflectance fourier transform infrared spectroscopy

A method for the simultaneous determination of iodine value (IV) and trans content from the Fourier transform infrared (FTIR) spectra of neat fats and oils recorded with the use of a heated single-bounce horizontal attenuated total reflectance (SB-HATR) sampling accessory was developed. Partial least squares (PLS) regression was employed for the development of the calibration models, and a set of nine pure triacylglycerols served as the calibration standards. Regression of the FTIR/PLS-predicted IV and trans contents for ten partially hydrogenated oil samples against reference values obtained by gas chromatography yielded slopes close to unity and SD of <1. Good agreement (SD<0.35) also was obtained between the trans predictions from the PLS calibration model and trans determinations performed by the recently adopted AOCS FTIR/SBHART method for the determination of isolated trans isomers in fats and oils.     

Monitoring PV in corn and soybean oils by NIR spectroscopy

NIR spectroscopy was used successfully in our laboratory to monitor oxidation levels in vegetable oils. Calibration models were developed to measure PV in both soy and corn oils, using partial least squares (PLS) regression and forward stepwise multiple linear regression, from NIR transmission spectra. PV can be measured successfully in both corn and soy oils using a single calibration. The most successful calibration was based on PLS regression of first derivative spectra. When this calibration was applied to validation sample sets containing equal numbers of corn and soy oil samples, with PV ranging from 0 to 20 meq/kg, a correlation coefficient of 0.99 between titration and NIR values was obtained, with a standard error of prediction equal to 0.72 meq/kg. For both types of oil, changes occurred in the 2068 nm region of the NIR spectra as oxidation levels increased. These changes appear to be associated with the formation of hydroperoxides during oxidation of the oils.