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.     

Near‐infrared spectroscopy for the determination of lipid oxidation in cereal food products

The present study was aimed at determining the ability of near‐infrared (NIR) spectroscopy to in situ describe fat oxidation kinetics in three different cereal‐based products: salted crackers (20% saturated palm oil and lauric oil, sprayed on surface); healthy crackers (10% unsaturated rapeseed oil, homogeneously distributed inside the product matrix); and moist pasteurised Asian noodles (1.5% unsaturated rapeseed oil, sprayed on surface). Products were stored under accelerated oxidation conditions at 40 °C. Lipid oxidation rates were determined from peroxide value (PV) measurements. We observed no significant changes in PV for the dry crackers (3 meq/kg after 60 days), a slight linear increase in PV for the healthy crackers (40 meq/kg after 60 days), and a rapid increase for the Asian noodles (80 meq/kg after 20 days). The NIR spectra were recorded between 1000 and 2500 nm by using a Fourier Transform NIR spectrometer, using an external probe. Measurements were done directly in situ on the product, on the ground samples, and on the extracted fat phase. The analysis of NIR spectral data by PLS statistical methods demonstrated some correlation trends (R² = 0.575–0.897; RMSEC = 17–55%) for the products having a significant increase in PV. It was not possible to propose predictive models to calculate the oxidation rate.     

Assessment of Interval PLS (iPLS) Calibration for the Determination of Peroxide Value in Edible Oils

Partial least squares (PLS) is a commonly used (and sometimes misused) chemometric technique for calibrating Fourier transform infrared spectroscopy, and allows the analysis of a variety of quality parameters associated with edible oils. Peroxide value (PV) is a typical parameter of interest; however, developing a robust, optimal, and reliable calibration method can be a daunting task. This paper examines and compares the use of interval PLS as a tool to develop a PLS PV calibration method for a single‐bounce attenuated total reflectance accessory relative to full spectrum PLS and experienced PLS, making use of correlation, variance, and pure component spectra. Using mixtures of fresh and oxidized oil covering a PV range of 1–20 meq/kg, backward interval PLS could systematically produce quality calibrations without the need to resort to experienced PLS. The experienced PLS requires a degree of spectral knowledge as well as diligent and tedious spectral examination, including largely unstructured iterative calibrations and cross‐validations to improve calibration performance. The backward interval PLS is also better than the full spectrum PLS in terms of model performance. In addition, the general model developed could account for the errors caused by oil types.     

Comparison of four analytical methods for the determination of peroxide value in oxidized soybean oils

Previous work in our laboratory demonstrated that soybean oil oxidation, expressed as PV, can be determined using NIR transmission spectroscopy as an alternative to the official AOCS iodometric titration method. In the present study, a comparison of four peroxide analytical methods was conducted using oxidized soybean oil. The methods included the official AOCS iodometric titration, the newly developed NIR method, the PeroxySafe^™ kit, and a ferrous xylenol orange (FOX) method, the latter two being colorimetric methods based on oxidation of iron. Five different commercially available soybean oils were exposed to fluorescent light to obtain PV levels of 0–20 meq/kg; periodic sampling was done to ensure having representative samples throughout the designated range. A total of 46 oil samples were analyzed. Statistical analysis of the data showed that the correlation coefficient (r) and standard deviation of differences (SDD) between the standard titration and NIR methods were r=0.991, SDD=0.72 meq/kg; between titration and the PeroxySafe^™ kit were r=0.993, SDD=0.56 meq/kg; and between the standard titration and FOX method were r=0.975, SDD=2.3 meq/kg. The high correlations between the titration, NIR, and PeroxySafe^™ kit data indicated that these methods were equivalent.     

Quantitative determination of total lipid hydroperoxides by a flow injection analysis system

A flow injection analysis (FIA) system coupled with a fluorescence detection system using diphenyl-1-pyrenylphosphine (DPPP) was developed as a highly sensitive and reproducible quantitative method of total lipid hydroperoxide analysis. Fluorescence analysis of DPPP oxide generated by the reaction of lipid hydroperoxides with DPPP enabled a quantitative determination of the total amount of lipid hydroperoxides. Use of 1-myristoyl-2-(12-((7-nitro-2-1,3-benzoxadiazol-4-yl)amino) dodecanoyl)-sn-glycero-3-phosphocholine as the internal standard improved the sensitivity and reproducibility of the analysis. Several commercially available edible oils, including soybean oil, rapeseed oil, olive oil, corn oil, canola oil, safflower oil, mixed vegetable oils, cod liver oil, and sardine oil were analyzed by the FIA system for the quantitative determination of total lipid hydroperoxides. The minimal amounts of sample oils required were 50 μg of soybean oil (PV=2.71 meq/kg) and 3 mg of sardine oil (PV=0.38 meq/kg) for a single injection. Thus, sensitivity was sufficient for the detection of a small amount and/or low concentration of hydroperoxides in common edible oils. The recovery of sample oils for the FIA system ranged between 87.2±2.6% and 102±5.1% when PV ranged between 0.38 and 58.8 meq/kg. The CV in the analyses of soybean oil (PV=3.25 meq/kg), cod liver oil (PV=6.71 meq/kg), rapeseed oil (PV=12.3 meq/kg), and sardine oil (PV=63.8 meq/kg) were 4.31, 5.66, 8.27, and 11.2%, respectively, demonstrating sufficient reproducibility of the FIA system for the determination of lipid hydroperoxides. The squared correlation (r ²) between the FIA system and the official AOCS iodometric titration method in a linear regression analysis was estimated at 0.9976 within the range of 0.35−77.8 meq/kg of PV (n=42). Thus, the FIA system provided satisfactory detection limits, recovery, and reproducibility. The FIA system was further applied to evaluate changes in the total amounts of lipid hydroperoxides in fish muscle stored on ice.     

In‐process monitoring in industrial olive mill by means of FT‐NIR

A total of 287 olive lots and 161 olive oil samples were analyzed for fat content, moisture and free acidity, using a Fourier transform near‐infrared (FT‐NIR) instrument located in an industrial mill. Samples having a wide range of both reference values and olive lot sizes (from <0.5 to >4 t) were collected at three industrial mill plants, located in the same Italian region, which utilize different technological equipment for virgin olive oil production. Olive paste spectra were acquired in diffuse reflectance, while oil samples were measured in transmission. Calibration models for oil content and moisture of olives as well as free acidity of virgin olive oils were developed using partial least squares (PLS) regression, first derivative and straight line subtraction. Results of calibration and validation of the PLS models selected were good. The PLS results indicate good similarity between data obtained from FT‐NIR and reference laboratory methods, allowing a rapid and less expensive screening analysis. Unfortunately, the correlation between the oil yield values recorded for all olive lots at the industrial mills and the oil content predicted by FT‐NIR was not satisfactory (R² = 0.605).     

Chemiluminescence detection of mono-, bis-, and tris-hydroperoxy triacylglycerols present in vegetable oils

A reliable method was needed to analyze molecular species of oxidized vegetable oils. In order to accomplish this goal, mono-, bis-, and tris-hydroperoxides (Mono-OOH, Bis-OOH, and Tris-OOH, respectively) of triacylglycerols formed during autoxidation and photosensitized oxidation of oils were determined by reversed-phase high-performance liquid chromatography in combination with chemiluminescence detection (CL-HPLC). Mono-OOH was the major species (96% of total hydroperoxides) in trioleoylglycerol [peroxide value (PV) 0.16 meq/kg], and Bis-OOH and Tris-OOH showed prolonged accumulation with photooxidation. This profile was confirmed in photooxidation of trilinoleoylglycerol and trilinolenoylglycerol. Soybean oil (PV 6 meq/kg) contained Mono-OOH oleoyl-linoleoyl-linoleoylglycerol as the main peroxidic molecular species (50% of total hydroperoxides). Mono-OOH trilinoleoylglycerol was the principal species (61% of total hydroperoxides) in safflower oil (PV 5 meq/kg), and Mono-OOH oleoyl-oleoyl-linoleoylglycerol was the representative species (66% of total hydroperoxides) in olive oil (PV 3 meq/kg). The CL-HPLC method, which is specific for the detection of hydroperoxides, should prove useful in studies of triacylglycerol oxidation in foods and vegetable oils.     

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.     

Monitoring peroxide value in fatliquor manufacture by Fourier transform infrared spectroscopy

A Fourier transform infrared (FTIR) spectrometer equipped with an attenuated total reflectance (ATR) sample handling accessory was used to rapidly monitor the peroxide value (PV) of oils undergoing catalytic oxidation to produce sulfonated fatliquors used in the leather industry. PV quantitation was based on the stoichiometric reaction of triphenylphosphosphine (TPP) with hydroperoxides to produce triphenylphosphine oxide (TPPO). By using a germanium ATR accessory that has a very short effective pathlength, the spectral contributions of the base oil could be subtracted out, eliminating any oil-dependent intereferences as well as providing a facile means of observing the spectral changes associated with the TPP/TPPO reaction. A calibration was devised by adding a constant amount of TPP-saturated chloroform to oils containing varying amounts of tert-butyl hydroperoxide (TBHP) to produce TPPO that had a measurable band at 1118 cm⁻¹. this band was linearly related to TBHP concentration and the calibration devised had an SD of ∼3.4 PV over the range of 0–250 PV. The ATR-PV method was standardized and the spectrometer programmed using Visual Basic to automate the analysis. the automated FTIR-ATR method was found to be a convenient means of tracking PV of oils undergoing oxidation, and the results correlated well with the PV values obtained using the AOAC iodometric method (r=0.94). The FTIR-ATR PV methodology provides a simple means of monitoring the PV of oils undergoing rapid oxidation and could serve as a quality-control tool in the production of sulfonated oils for the leather industry.     

Determining Frying Oil Degradation by Near Infrared Spectroscopy Using Chemometric Techniques

A rapid method for the determination of some important physicochemical properties in frying oils has been developed. Partial least square regression (PLS) calibration models were applied to the physicochemical parameters and near infrared spectroscopy (NIR) spectral data. PLS regression was used to find the NIR region and the data pre-processing method that give the best prediction of the chemical parameters. Calibration and validation were appropriated by leave one out cross validation and test set validation techniques for predicting free fatty acids (FFA), total polar materials (cTPM; measured by chromatographic method and iTPM measured by an instrumental method), viscosity and smoke point of the frying oil samples. For PLS models using the cross validation techniques, the best correlations (r) between NIR predicted data and the standard method data for iTPM in oils were 93.79 and root mean square error of prediction (RMSEP) values were 5.53. For PLS models using the test set validation techniques, the best correlations (r) between NIR predicted data and standard method data for FFA, cTPM, viscosity and smoke point in oils were 92.58, 94.61, 81.95 and 84.07 and RMSEP values were 0.121, 3.96, 22.30 and 8.74, respectively. In conclusion, NIR technique with chemometric analysis was found very effective in predicting frying oil quality changes.     

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.     

Discrimination of various poly(propylene) copolymers and prediction of their ethylene content by near‐infrared and Raman spectroscopy in combination with chemometric methods

Near‐infrared (NIR) diffuse reflectance (DR) spectra and Fourier‐transform (FT) Raman spectra were measured for 12 kinds of block and random poly(propylene) (PP) copolymers with different ethylene content in pellets and powder states to propose calibration models that predict the ethylene content in PP and to deepen the understanding of the NIR and Raman spectra of PP. Band assignments were proposed based calculation of the second derivatives of the original spectra, analysis of loadings and regression coefficient plots of principal component analysis (PCA) and principal component regression (PCR) (predicting the ethylene content) models, and comparison of the NIR and Raman spectra of PP with those of linear low‐density polyethylene (LLDPE) with short branches. PCR and partial least squares (PLS) regression were applied to the second derivatives of the NIR spectra and the NIR spectra after multiplicative scatter correction (MSC) to develop the calibration models. After MSC treatment, the original spectra yield slightly better results for the standard error of prediction (SEP) than the second derivatives. A plot of regression coefficients for the PCR model shows peaks due to the CH₂ groups pointing upwards and those arising from the CH₃ groups pointing downwards, clearly separating the bands due to CH₃ and CH₂ groups. For the Raman data, MSC and normalization were applied to the original spectra, and then PCR and PLS regression were carried out to build the models. The PLS regression for the normalized spectra yields the best results for the correlation coefficient and the SEP. Raman bands at 1438, 1296, and 1164 cm^?1 play key roles in the prediction of the ethylene content in PP. The NIR chemometric evaluation of the data gave better results than those derived from the Raman spectra and chemometric analysis. Possible reasons for this observation are discussed. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 87: 616–625, 2003     

Application of principal-component analysis on near-infrared spectroscopic data of vegetable oils for their classification

In the near-infrared (NIR) spectra of oil, information about fatty acid composition is concentrated in the range of 1600–2200 nm. Principal-component analysis (PCA) was applied on the standardized full NIR spectral data of this region for vegetable oils to totally capture the NIR spectral pattern. Nine varieties of vegetable oils (soybean, corn, cottonseed, olive, rice bran, peanut, rapeseed, sesame and coconut oil) could be successfully classified from their PCA scores. Examining the contribution of wavelengths to PCA scores showed that wavelengths with a high loading weight were assigned to characteristic absorption regions that correspond to specific fatty acid moieties. This classification is related to the fatty acid composition of an oil, and it can be carried out rapidly and easily after eigenvectors were obtained.     

A New Strategy for Quantitative Proportions in Complex Systems of Blended Oils by Triacyglycerols and Chemometrics Tools

Many oils sold in China and India are a blend of various oils to improve performance, stability, and nutritional characteristics, which are required in their respective markets. Quantitative analysis of the proportions of constitutive components is fundamental to the conformity and adulteration checking of edible blended oil products. A multi linear regression model with constrained linear least squares and exhaustion calculation was applied in this study. The source of the varieties in the model is a database (614 pure oils) of triacylglycerols (TAGs) collected by GC–FID and HPLC–RID. There were 20 groups of binary and ternary blended oils consisting of two or three oils out of five kinds, namely soybean, corn, peanut, rapeseed, and sunflower, which were analyzed and processed separately. Results showed that the method was able to predict the proportions of constitutive components in the edible blended oils, given that relative errors required less than 20%, the accuracy was 98.2% for the binary system if the proportion of each oil in blended oils was more than 20%, while the accuracy was 84.7% for the ternary system if the proportion of each oil in blended oils was more than 10%. The quantitative method is based on a simple analysis to determine the TAGs composition and thus it is useful for quick segregation and quality control of blended oils in routine analysis.     

润滑油基础油粘度性能的近红外光谱研究

本文采用傅立叶（FT）近红外光谱仪,在近红外长波光谱范围内,测定了不同润滑油基础油的近红外光谱,分别建立润滑油基础油40℃粘度、100℃粘度和粘度指数3项指标的偏最小二乘和BP神经网络近红外光谱分析的校正模型。研究数据表明,近红外光谱能够获得与润滑油基础油粘度相关的光谱信息。人工神经网络方法作为一种处理非线性问题的数据分析手段,能较好的定量研究近红外光谱信息与润滑油基础油之间的关系。     

Encapsulation of sea buckthorn kernel oil in modified starches

Encapsulation of CO₂-extracted sea buckthorn kernel oil and the stability of the products were investigated. Maltodextrin and an emulsifying starch derivative were used for encapsulation by spray drying. Both shell materials significantly increased the storage stability of sea buckthorn kernel oil, even though in maltodextrin capsules 10% of the total oil was extractable from the surface of the capsule. The cornstarch sodiium octenyl succinate derivative capsules contained essentially no surface oil. After 9 wk storage at controlled conditions (20°C, RH 50%), PV of the unencapsulated oil was above 90 meq/kg, whereas in the encapsulated oils, the PV was still around 20 meq/kg. The PV of the encapsulated oil was dependent on the storage conditions. A small increase in temperature (from 20 to 25–30°C) and a significant increase in humidity (from RH 50 to RH 50–70%) decreased the stability of capsules. This was associated with the physical state of the microcapsule matrix and may be linked with glass transition of the wall polymers.     

Determination of peroxide value in thermally oxidized crude palm oil by near infrared spectroscopy

A near infrared (NIR) spectroscopic method was developed to measure peroxide value (PV) in crude palm oil (CPO). Calibration standards were prepared by oxidizing CPO in a fermentor at 90°C. A partial least squares (PLS) calibration model for predicting PV was developed based on the NIR spectral region from 1350 to 1480 nm with reference to single-point baseline at 1514 nm. The optimization of calibration factors was guided by the predicted residual error sum of squares test. The standard error of calibration obtained was 0.156 over the analytical range of 2.17–10.28 PV and the correlation coefficient (R ²) was 0.994. The method was validated with an independent set of samples which was prepared in the same manner on a different day. A linear relationship between the American Oil Chemists’ Society and the NIR methods was obtained with R ² of 0.996 and standard error of performance of 0.17. This study has demonstrated that the prediction of PV in the NIR region is possible. The method developed is rapid, with total analysis time less than 2 min, is environmentally friendly, and its accuracy is generally good for quality control of CPO.     

Storage stability evaluation of some packed vegetable oil blends

The physicochemical characteristics and minor component contents of blended oils packed in pouches in relation to starting oils used for blending were studied over a period of 6 mon at two storage temperatures and humidity conditions: 27°C/65% RH and 40°C/30–40% RH. Color, PV, FFA value, β-carotene content, tocopherol content, and oryzanol content of the oils were monitored at regular intervals. The color, PV (0.6–20.7 meq O₂/kg, FFA value (0.08–2.1%), tocopherol content (360–1700 ppm%), oryzanol content (460–2,000 mg%), and sesame oil antioxidants (400–2,000 mg%) were not changed in either the starting oils or their blends. Oils and oil blends containing a higher initial PV (18.9–20.7 meq O₂/kg) showed a slight reduction in value at 40°C, whereas oils having lesser PV of 5–10 showed a slight increase during the storage period. Among the minor components studied, only β-carotene showed a reduction, 8.9–60.2% at 27°C and 48–71% at 40°C, for the different oil blends studied. The observed results indicated that the packed oil blends studied were stable under the conditions of the study, and the minor components, other than β-carotene, remained unaltered in the package even at the end of 6 mon of storage.     

Rapid determination of oxidative stability of edible oils by FTIR spectroscopy using disposable IR cards

Disposable polytetrafluoroethylene (PTFE) polymer IR (PIR) cards were used as substrates to rapidly oxidize edible oils and simultaneously monitor the extent of oxidation by FTIR spectroscopy. Four edible oils were oxidized on PIR cards and in bulk at moderate temperature (58°C), and real-time oxidation plots were obtained by measuring changes in the IR hydroperoxide (ROOH) absorbance as a function of time. The relationship between the ROOH absorbance and PV was developed using a reference method to define absorbances corresponding to PV end points of 100 and 200 meq ROOH/kg for the oils oxidized in bulk and on cards, respectively. The real-time oxidation plots obtained for the oils oxidized in bulk and on cards were similar in appearance, but the oils on the cards reached the PV end point 20 times faster than the oils oxidized in bulk. The results indicate that the use of disposable PIR cards coupled with moderate heating and aeration provides a simple, practical, and rapid means for monitoring oxidation and determining the oxidative stability of edible oils at a normal storage temperature.     

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.