Flow-injection methylene blue-based spectrophotometric method for the determination of peroxide values in edible oils

A flow-injection method for measuring the peroxide value (PV, mequiv. O₂ kg⁻¹) in edible oils is described. The technique is based on spectrophotometric monitoring at 660 nm of methylene blue (MB), generated from leucomethylene blue (LMB) oxidation with peroxides present in oil samples. After being optimized, the method was validated in terms of linearity, precision sensitivity and recovery.Linear calibration graph was obtained in the range 0.1-5 mequiv. O₂ kg⁻¹, with a detection limit (S/N  =  3) of 0.014 mequiv. O₂ kg⁻¹. The precision of the method (R.S.D., n = 9) for within and between-days is better than 1.5% and 2.2%, respectively at 0.4 mequiv. O₂ kg⁻¹. The method was applied successfully to the determination of PV in six edible oil samples, and compared to the classical official method. Using the linear regression test, Student's t-test and variance ratio F-test, there was no significant difference between the compared methods. The proposed method is accurate, simple, cheap and could be used to control edible oil rancidity with a high sample throughputs (30 samples h⁻¹).     

Flow injection determination of peroxide value in edible oils using triiodide detector

A flow injection analysis (FIA) method for the determination of peroxide value (PV) in edible oils is described. Oil sample (undiluted) and KI reagent were aspirated into a homemade reaction chamber where the redox reaction between iodide in the aqueous phase and hydroperoxides in the oil was effected by applying a short (typically 30 s) vortex action. After allowing for the emulsified oil phase to be separated from the aqueous phase (bottom layer), an aliquot of the aqueous phase containing triiodide was next aspirated to the surface of a triiodide-selective membrane for detection. The optimized FIA procedure is linear over 0.35-28.0 PV (mequiv. O₂/kg) with a detection limit of 0.32 PV. Exhibiting good reproducibility (R.S.D. of 2.7% (n = 8) for the determination of 1.1 PV) and sampling rate of 80 samples h⁻¹, the proposed method, unlike previous FIA procedures, completely eliminated the use of organic solvents (except the use of 2-propanol for cleaning of reaction chamber). Excellent correlation (R² = 0.9949) between the proposed method and the manual official AOCS method was found when applied to the determination of PV in diverse type of edible oils (n = 20).     

Evaluation of peroxide value of olive oil and antioxidant activity by luminol chemiluminescence

Three procedures are developed and investigated for the simple and fast determination of peroxide value of olive oil by luminol chemiluminescence. The procedure using hemin as catalyst in carbonate alkaline solution allows the determination of hydrogen peroxide within the range 0.014-50 μM. The method can be used for the determination of peroxide value within the range 2.00-30.0 mequiv. O₂/kg oil and results correlate very well (r² = 0.99) with those of the official method. All reagents are aqueous solutions and olive oil is dissolved in acetone:ethanol mixed solution and, hence, the method is using minimal amounts of organic solvents and can be successfully applied to field analysis. Antioxidant activity of five common compounds found in natural products was determined by using luminol CL with Co(II) as EDTA complex as catalyst at pH 9.00.     

Investigations of the adulteration of extra virgin olive oils with seed oils using their weak chemiluminescence

A weak chemiluminescence (CL) emission was observed in commercial Greek extra virgin olive oils (Knossos, Spitiko, Ananias, Altis, Minerva, Xenia) and in refined seed oils such as sunflower oils (Marata, Sanola, Sun, Mana, Sol, Minerva) as well as in corn oils (Flora, Minerva, Marata Sun and Sol) with potassium superoxide in the aprotic solvent dimethoxyethylene.On measuring the CL of mixtures of extra virgin olive oils with the cheaper refined seed oils, calibrations were produced which can be used for the determination of the adulteration of olive oils with seed oils down to 3%. Furthermore, depending on the kind of oils, “low” authenticity-CL-factors for olive oils (0.8-2.15 μmol l⁻¹ gallic acid) and “high” for seed oils (4.5-11.2 μmol l⁻¹ gallic acid) were calculated.     

Classification of edible and lampante virgin olive oil based on synchronous fluorescence and total luminescence spectroscopy

Total luminescence and synchronous fluorescence spectroscopies were tested as regards their ability to differentiate edible from lampante virgin olive oils. Total luminescence spectra were recorded by measuring the emission spectra in the range 350-720 nm at excitation wavelengths from 320 to 535 nm. The synchronous fluorescence spectra of 41 edible and 32 lampante virgin olive oils were acquired by synchronous scanning the excitation and emission monochromator maintained at an offset value of 80 nm. Classification of virgin olive oils based on their synchronous fluorescence spectra was performed by hierarchical cluster analysis and principal component analysis using the spectral range of 429-545 nm. Principal component analysis provided better discrimination between the two classes, without any classification error, while hierarchical cluster analysis allowed 97.3% correct classification. These results indicate the capability of fluorescence techniques to differentiate virgin olive oils according to their quality.     

Chemiluminescent evaluation of peroxide value in olive oil

A method is described for the evaluation of the peroxide value (PV, meq. O₂ kg⁻¹) in olive oil. The method is based on the chemiluminogenic energy-transfer reaction of bis(2,4,6-(trichlorophenyl)oxalate (TCPO) with hydrogen peroxide or total peroxides in the presence of Mn(II) as catalyst and 9,10-dimethylanthracene as fluorophore. The procedure developed allows the evaluation of PV within the range of 0.6-100 meq. O₂ kg⁻¹ (CL intensity = 1.76 × PV (meq. O₂ kg⁻¹) + 23.2, r² = 0.994, n = 9) and relative standard deviation within the range 1-5% by using a simple manual measurement.     

常压火焰离子化质谱技术对食用植物油快速分析的初探

建立了常压火焰离子化质谱(Ambient flame ionization mass spectrometry,AFI-MS)快速分析食用植物油(橄榄油、芝麻油、花生油和葵花籽油)的方法。AFI-MS检出食用植物油(橄榄油、芝麻油、花生油和葵花籽油)中的26种甘油三酯和11种甘油二脂。AFI-MS分析显示,不同的食用植物油(橄榄油、芝麻油、花生油和葵花籽油)得到的质谱图轮廓信息不同。通过对不同食用植物油的甘油三酯相对峰强度进行分析,可初步归纳出食用植物油的类型。AFI-MS分析食用植物油的操作简单,普通的打火机就可以作为离子源用于食用植物油的分析。这种便捷的离子化技术可以用于食用植物油的快速分析。     

Rapid determination of BTEXS in olives and olive oil by headspace-gas chromatography/mass spectrometry (HS-GC-MS)

In this work, a straightforward, reliable and effective automated method has been developed for the direct determination of monoaromatic volatile BTEXS group (namely benzene, toluene, ethylbenzene, o-, m- and p-xylenes, and styrene) in olives and olive oil, based on headspace technique. Separation, identification and quantitation were carried out by headspace-gas chromatography-mass spectrometry (HS-GC-MS) in selected ion monitoring (SIM) mode. Sample pretreatment or clean-up were not necessary (besides olives milling) because the olives and olive oil samples are put directly into an HS vial, automatically processed by HS and then injected in the GC-MS for chromatographic analysis. The chemical and instrumental variables were optimized using spiked olives and olive oil samples at 50 μg kg⁻¹ of each targeted species. The method was validated to ensure the quality of the results. The precision was satisfactory with relative standard deviations (RSD (%)) in the range 1.6-5.2% and 10.3-14.2% for olive oil and olives, respectively. Limits of detection were in the range 0.1-7.4 and 0.4-4.4 μg kg⁻¹ for olive oil and olives, respectively. Finally, the proposed method was applied to the analysis of real olives and olive oil samples, finding positives of the studied compounds, with overall BTEXS concentration levels in the range 23-332 μg kg⁻¹ and 4.2-87 μg kg⁻¹ for olive oil and olives, respectively.     

Determination of α-linolenic acid and linoleic acid in edible oils using near-infrared spectroscopy improved by wavelet transform and uninformative variable elimination

This paper proposes an analytical method for simultaneous near-infrared (NIR) spectrometric determination of α-linolenic and linoleic acid in eight types of edible vegetable oils and their blending. For this purpose, a combination of spectral wavelength selection by wavelet transform (WT) and elimination of uninformative variables (UVE) was proposed to obtain simple partial least square (PLS) models based on a small subset of wavelengths. WT was firstly utilized to compress full NIR spectra which contain 1413 redundant variables, and 42 wavelet approximate coefficients were obtained. UVE was then carried out to further select the informative variables. Finally, 27 and 19 wavelet approximate coefficients were selected by UVE for α-linolenic and linoleic acid, respectively. The selected variables were used as inputs of PLS model. Due to original spectra were compressed, and irrelevant variables were eliminated, more parsimonious and efficient model based on WT-UVE was obtained compared with the conventional PLS model with full spectra data. The coefficient of determination (r²) and root mean square error prediction set (RMSEP) for prediction set were 0.9345 and 0.0123 for α-linolenic acid prediction by WT-UVE-PLS model. The r² and RMSEP were 0.9054, 0.0437 for linoleic acid prediction. The good performance showed a potential application using WT-UVE to select NIR effective variables. WT-UVE can both speed up the calculation and improve the predicted results. The results indicated that it was feasible to fast determine α-linolenic acid and linoleic acid content in edible oils using NIR spectroscopy.     

Optimization and application of methods of triacylglycerol evaluation for characterization of olive oil adulteration by soybean oil with HPLC-APCI-MS-MS

Triacylglycerols (TAGs) are the main constituents of vegetable oils where they occur in complex mixtures with characteristic distributions. Mass spectrometry using an atmospheric pressure chemical ionization interface (APCI-MS) run in positive mode and an Ion Trap mass analyser were applied in the study of olive and soybean oils and their mixtures. Direct injections of soybean and olive oil solutions allowed the identification of ions derived from the main TAGs of both oils. This procedure showed to be a simple and powerful tool to evaluate mixtures or addition of soybean to olive oil. TAG separation was optimized by high performance liquid chromatography (HPLC) using an octadecylsilica LiChrospher column (250 mm × 3 mm; 5 μm) and a gradient composed of acetonitrile and 2-propanol allowed the separation of the main TAGs of the studied oils. APCI vaporization temperature was optimized and best signals were obtained at 370 °C. Multiple reaction monitoring (MRM) employing the transition of the protonated TAG molecules ([M+H]⁺) to the protonated diacylglycerol fragments ([M+H−R]⁺) improved the selectivity of TAG detection and was used in quantitative studies. Different strategies were developed to evaluate oil composition following TAG analysis by MRM. The external standard calibration and standard additions methods were compared for triolein quantification but the former showed to be biased. Further quantitative studies were based on the estimates of soybean and olive oil proportions in mixtures by comparison of TAG areas found in mixtures of known and unknown composition of both oils. Good agreement with expected or labeled values was found for a commercial blend containing 15% (w/w) of olive oil in soybean oil and to a 1:1 mixture of both oils, showing the potential of this method in characterizing oil mixtures and estimating oil proportions. Olive oils of different origins were also evaluated by mass spectra data obtained after direct injections of oil solutions and principal component analysis (PCA). Argentinean olive oils were clustered in a different area of the principal components plot (PC2 × PC1) in comparison with European olive oils. The commercial blend containing 15% (w/w) of olive oil in soybean oil appeared in a completely different area of the graphic, showing the potential of this method to screen out for olive oil adulterations.     

基于近红外光谱的食用植物油中反式脂肪酸含量快速定量检测及模型优化研究

利用近红外光谱技术对食用植物油中反式脂肪酸(Trans fatty acids,TFA)含量进行快速定量检测,并通过波段选择、预处理方法、变量筛选及建模方法对TFA含量预测模型进行优化.采用AntarisⅡ傅里叶变换近红外光谱仪在4000~10000 cm-1光谱范围采集98个食用植物油样本的近红外透射光谱,然后采用气相色谱法测定TFA的真实含量.首先,对样本原始光谱进行波段、预处理方法优选;在此基础上,采用竞争自适应重加权法(Competitive adaptive reweighted sampling,CARS)筛选TFA相关的重要变量,最后应用主成分回归、偏最小二乘和最小二乘支持向量机方法分别建立食用植物油中TFA含量的预测模型.研究结果表明,近红外光谱技术检测食用植物油中的TFA含量是可行的,优化后的最佳预测模型的校正集和预测集R2分别为0.992和0.989,RMSEC和RMSEP分别为0.071%和0.075%.最佳预测模型所用的变量仅26个,占全波段变量的0.854%.此外,与全波段偏最小二乘预测模型相比,其预测集R2由0.904上升为0.989,RMSEP由0.230%下降为0.075%.由此表明,模型优化非常必要,CARS能有效筛选TFA相关的重要变量,极大减少建模变量数,从而简化预测模型,并较大提高预测模型的精度和稳定性.     

Humic acid-bonded silica as a novel sorbent for solid-phase extraction of benzo[a]pyrene in edible oils

A novel solid-phase extraction (SPE) sorbent, humic acid-bonded silica (HAS), was prepared. Humic acids (HAs) were grafted onto silica matrices via an amide linkage between humyl chloride and the amido terminus of 3-aminopropyltrimethoxysilane (APTS)-silica gel. The resulting material was characterized by Fourier transform infrared spectrometer, elemental analysis, and nitrogen adsorption analysis. This sorbent exhibits an excellent adsorption capacity for some electron-abundant analytes owing to its peculiar structure. In this paper, we choose benzo[a]pyrene (BaP) in oil as a probe to validate the adsorption capacity of the material. Thus a fast, cheap and simple SPE method with humic acid-bonded silica cartridge for edible oil clean-up, followed by high-performance liquid chromatography (HPLC) with fluorescence detection was established. The effects of experimental variables, such as washing and elution solvents, and the amount of sorbents have been studied. The recoveries of BaP in edible oils spiked at 0.2-100 μg kg⁻¹ were in the range of 78.8-102.7% with relative standard deviations ranging between 1.3 and 9.3%; the limit of detection was -0.06 μg kg⁻¹.     

A rapid method for peroxide value determination in edible oils based on flow analysis with Fourier transform infrared spectroscopic detection

The development of an automated, rapid and highly precise method for determination of the peroxide value in edible oils based on a continuous flow system and Fourier transform infrared (FTIR) spectroscopic detection is described. The sample stream was mixed with a solvent mixture consisting of 25% (v/v) toluene in hexanol which contained triphenylphosphine (TPP). The hydroperoxides present in the sample reacted stoichiometrically with TPP to give triphenylphosphine oxide (TPPO) which has a characteristic and intense absorption band at 542 cm-1. A 10% (m/v) TPP solution in the solvent mixture and a 100 cm reaction coil were necessary for complete reaction. FTIR transmission spectra were recorded using a flow cell equipped with CsI windows having an optical pathlength of 100 microns. By using tert-butyl hydroperoxide spiked oil standards and evaluation of the band formed at 542 cm-1 a linear calibration graph covering the range 1-100 PV (peroxide value; mequiv O2 kg-1 oil) was obtained. The relative standard deviation was 0.23% (n = 11) and the throughput 24 samples h-1. The developed system was also applied to the determination of PV in olive, sunflower and corn oils, showing good agreement with the official reference method of the European Community which is based on titration using organic solvents. The results obtained clearly show that the developed method is superior to the standard wet chemical method, hence suggesting its application in routine analysis and quality control.     

Determination of methylmercury and estimation of total mercury in seafood using high performance liquid chromatography (HPLC) and inductively coupled plasma-mass spectrometry (ICP-MS): Method development and validation

A method was developed for determination of methylmercury and estimation of total mercury in seafood. Mercury (Hg) compounds were extracted from 0.5 g edible seafood or 0.2 g lyophilized reference material by adding 50 ml aqueous 1% w/v l-cysteine·HCl·H₂O and heating 120 min at 60 °C in glass vials. Hg compounds in 50 μl of filtered extract were separated by reversed-phase high performance liquid chromatography using a C-18 column and aqueous 0.1% w/v l-cysteine·HCl·H₂O + 0.1% w/v l-cysteine mobile phase at room temperature and were detected by inductively coupled plasma-mass spectrometry at mass-to-charge ratio 202. Total Hg was calculated as the mathematical sum of methyl and inorganic Hg determined in extracts. For seafoods containing 0.055-2.78 mg kg⁻¹ methylmercury and 0.014-0.137 mg kg⁻¹ inorganic Hg, precision of analyses was ≤5% relative standard deviation (R.S.D.) for methylmercury and ≤9% R.S.D. for inorganic Hg. Recovery of added analyte was 94% for methylmercury and 98% for inorganic Hg. Methyl and total Hg results for reference materials agreed with certified values. Limits of quantitation were 0.007 mg kg⁻¹ methylmercury and 0.005 mg kg⁻¹ inorganic Hg in edible seafood and 0.017 mg kg⁻¹ methylmercury and 0.012 mg kg⁻¹ inorganic Hg in lyophilized reference materials. Evaluation of analyte stability demonstrated that l-cysteine both stabilized and de-alkylated methylmercury, depending on holding time and cysteine concentration. Polypropylene adversely affected methylmercury stability. Total Hg results determined by this method were equivalent to results determined independently by cold vapour-atomic absorption spectrometry. Methylmercury was the predominant form of Hg in finfish. Ratios of methylmercury/total Hg determined by this method were 93-98% for finfish and 38-48% for mollusks.     

Comparative study of electrospray and photospray ionization sources coupled to quadrupole time-of-flight mass spectrometer for olive oil authentication

The use of fast and reliable analytical procedures for olive oil authentication is a priority demand due to its wide consumption and healthy benefits. Olive oil adulteration with other cheaper vegetable oils is a common practice that has to be detected and controlled. Rapid screening methods based on high resolution tandem mass spectrometry constitute today the option of choice due to sample handling simplicity and the elimination of the chromatographic step. The selection of the ionization source is critical and the comparison of their reliability necessary. The possibilities of the direct infusion electrospray ionization (ESI) and the recently introduced atmospheric pressure photospray ionization source (APPI), coupled to quadrupole time-of-flight (QqTOF), have been critically studied and compared to control olive oil adulteration. These techniques are very rapid (approximately 1 min per sample) and have high discrimination power to elucidate key components in the edible oils studied (olive, hazelnut, sunflower and corn). Nevertheless, both sources are complementary, being APPI more sensitive for monoacyl- and diacylglycerol fragment ions and ESI for triacylglycerols. In addition, methods reproducibility's are very high, especially for APPI source. Mixtures of olive oil with the others vegetable oils can be easily discriminated which has been tested by using principal components analysis (PCA) with both ESI-MS and APPI-MS spectra. Analogously, linear discriminant analysis (LDA) confirms methods reproducibility and detection of other oils used as adulterants, in particular hazelnut oil, which is especially difficult given its chemical similarity with olive oil.     

Development of a 2D laser ablation inductively coupled plasma mass spectrometry mapping procedure for mercury in maize (Zea mays L.) root cross-sections

A LA-ICP-MS method based on a 213 nm Nd:YAG laser and a quadrupole ICP-MS has been developed for mapping of mercury in root cross-sections of maize (Zea mays L.) to investigate the mechanism of mercury uptake from soil and its potential translocation to the edible parts. Conventional rastering was found to be unusable due to sorption of mercury onto the internal parts of the LA device, giving rising to memory effects resulting in serious loss of resolution and inaccurate quantification. Spot analysis on a virtual grid on the surface of the root sections using washout times of 10 s in between spots greatly alleviated problems related to these memory effects. By ablating straight through the root sections on a poly(methyl methacrylate) support the calibration process was simplified as internal standardization and matrix-matching could be circumvented. Mercury-spiked freeze-drying embedding medium, sectioned similarly to the root sections, was used for the preparation of the standards. Standards and root sections were subjected to spot analysis using the following operational parameters: beam diameter, 15 μm; laser fluence, 2.5 J cm⁻²; repetition rate, 20 Hz; dwell time, 1 s; acquisition time, 0.1 s. The mercury peaks for standards and roots sections could be consistently integrated for quantification and construction of the 2D mercury maps for the root sections. This approach was successfully used to investigate the mercury distribution in root sections of maize grown in soil spiked to a level of 50 mg kg⁻¹ DW HgCl₂. It was found that at given Hg concentrations in the substrate Hg ions practically do not cross root plasma membranes of the endodermal barrier, but are entirely retained in the root apoplastic space. This suggests that maize plants grown in Hg-contaminated areas translocate Hg to the upper edible parts of the plant only to a small extent.     

DSC方法在特级初榨橄榄油掺假鉴别中的应用

采用差示扫描量热法(DSC)对进口特级初榨橄榄油中葵花籽油的掺假鉴别进行了系统研究。由橄榄油入手考察了升降温循环实验条件下油品的重复性及数据可靠性,以此为基础提出采用程序降温的方法研究油品的结晶特性。统计了研究体系内的8种特级初榨橄榄油、6种其他食用油以及5种比例的模拟掺假油的结晶峰温度值,建立了回归方程。结果表明:进口特级初榨橄榄油在-60~-46℃区间内具有尖锐的结晶峰;随着掺入葵花籽油比例的升高,模拟掺假油的结晶温度逐渐向低温区移动,结晶峰形由尖锐逐渐变平坦;由结晶起始温度和结晶峰值温度分别相对于掺假油体积分数建立的回归方程具有很好的相关性,可以快速准确地鉴别特级初榨橄榄油。     

Improving Prediction of Peroxide Value of Edible Oils Using Regularized Regression Models

We present four unique prediction techniques, combined with multiple data pre-processing methods, utilizing a wide range of both oil types and oil peroxide values (PV) as well as incorporating natural aging for peroxide creation. Samples were PV assayed using a standard starch titration method, AOCS Method Cd 8-53, and used as a verified reference method for PV determination. Near-infrared (NIR) spectra were collected from each sample in two unique optical pathlengths (OPLs), 2 and 24 mm, then fused into a third distinct set. All three sets were used in partial least squares (PLS) regression, ridge regression, LASSO regression, and elastic net regression model calculation. While no individual regression model was established as the best, global models for each regression type and pre-processing method show good agreement between all regression types when performed in their optimal scenarios. Furthermore, small spectral window size boxcar averaging shows prediction accuracy improvements for edible oil PVs. Best-performing models for each regression type are: PLS regression, 25 point boxcar window fused OPL spectral information RMSEP = 2.50; ridge regression, 5 point boxcar window, 24 mm OPL, RMSEP = 2.20; LASSO raw spectral information, 24 mm OPL, RMSEP = 1.80; and elastic net, 10 point boxcar window, 24 mm OPL, RMSEP = 1.91. The results show promising advancements in the development of a full global model for PV determination of edible oils.     

Maize kernel hardness classification by near infrared (NIR) hyperspectral imaging and multivariate data analysis

The use of near infrared (NIR) hyperspectral imaging and hyperspectral image analysis for distinguishing between hard, intermediate and soft maize kernels from inbred lines was evaluated. NIR hyperspectral images of two sets (12 and 24 kernels) of whole maize kernels were acquired using a Spectral Dimensions MatrixNIR camera with a spectral range of 960-1662 nm and a sisuChema SWIR (short wave infrared) hyperspectral pushbroom imaging system with a spectral range of 1000-2498 nm. Exploratory principal component analysis (PCA) was used on absorbance images to remove background, bad pixels and shading. On the cleaned images, PCA could be used effectively to find histological classes including glassy (hard) and floury (soft) endosperm. PCA illustrated a distinct difference between glassy and floury endosperm along principal component (PC) three on the MatrixNIR and PC two on the sisuChema with two distinguishable clusters. Subsequently partial least squares discriminant analysis (PLS-DA) was applied to build a classification model. The PLS-DA model from the MatrixNIR image (12 kernels) resulted in root mean square error of prediction (RMSEP) value of 0.18. This was repeated on the MatrixNIR image of the 24 kernels which resulted in RMSEP of 0.18. The sisuChema image yielded RMSEP value of 0.29. The reproducible results obtained with the different data sets indicate that the method proposed in this paper has a real potential for future classification uses.     

Application of unfold principal component analysis and parallel factor analysis to the exploratory analysis of olive oils by means of excitation-emission matrix fluorescence spectroscopy

Discrimination between virgin olive oils and pure olive oils is of primary importance for controlling adulterations. Here, we show the potential usefulness of two multiway methods, unfold principal component analysis (U-PCA) and parallel factor analysis (PARAFAC), for the exploratory analysis of the two types of oils. We applied both methods to the excitation-emission fluorescence matrices (EEM) of olive oils and then compared the results with the ones obtained by multivariate principal component analysis (PCA) based on a fluorescence spectrum recorded at only one excitation wavelength. For U-PCA and PARAFAC, the ranges studied were λ_ex=300-400 nm, λ_em=400-695 nm and λ_ex=300-400 nm, λ_em=400-600 nm. The first range contained chlorophylls, whose peak was much more intense than those of the rest of species. The second range did not contain the chlorophylls peak but only the fluorescence spectra of the remaining compounds (oxidation products and Vitamin E). The three-component PARAFAC model on the second range was found to be the most interpretable. With this model, we could distinguish well between the two groups of oils and we could find the underlying fluorescent spectra of three families of compounds.