Prediction of the acid value,peroxide value and the percentage of some fatty acids in edible oils during long heating time by chemometrics analysis of FTIR-ATR spectra

Edible oils are used in the preparation of foods as a part of their recipe or for frying. So to ensure of food safety, checking the quality of the oils before and after usage is an important subject in food control laboratories. In this study, edible oils from four different sources (canola, corn, sunflower and frying) were heated for 36 h at 170 °C and sampling was done every 6 h. The free fatty acid, peroxide value and the content of some fatty acids (C16:0, C18:0, C18:1, C18:2, C18:3) of the oil samples were determined by standard methods. Then, the ATR-FTIR spectra of the samples were collected. The partial least squares (PLS) regression combined with genetic algorithm was performed on the spectroscopic data to obtain the appropriate predictive models for the simultaneous estimation of acid value, peroxide value and the percentage of five kinds of fatty acids. The effect of some preprocessing methods on these models was also investigated. Preprocessing of data by orthogonal signal correction (OSC) resulted in the best predictive models for all oil properties. The correlation coefficients of calibration set (>0.99) and validation set (>0.86 and in most case >0.94) of the OSC–PLS model suggested suitable predictive modeling for all studied parameters in the oil samples. This method could be suggested as a rapid, economical and environmental friendly technique for simultaneous determination of seven noted parameters in the edible oils.     

在线热辅助甲基化-气相色谱法分析棉籽仁中的脂肪酸组成

建立了分析棉籽仁中脂肪酸组成的在线热辅助甲基化-气相色谱法。将0.3 mg棉籽仁样品与2 μ L三甲基氢氧化硫（0.2 mol/L）加入裂解器,在350℃下进行甲基化反应,通过气相色谱仪进行分离分析,共检测到8种脂肪酸甲酯成分,分别为亚油酸（C18：2）、油酸（C18：1）、棕榈酸（C16：0）、硬脂酸（C18：0）、肉豆蔻酸（C14：0）、棕榈油酸（C16：1）、花生酸（C20：0）和二十二酸（C22：0）,不饱和脂肪酸的相对含量为66.30%~72.54%,其中亚油酸的相对含量为43.20%~53.61%,相对峰面积的相对标准偏差（RSD）小于10%（n=5）。通过分析5组棉籽仁样品与3种食用油中的脂肪酸组成,结果表明不同产地的棉籽仁中的脂肪酸组成差异不明显,且棉籽仁中的脂肪酸组成与玉米油最为接近,相似度为0.960~0.992。该方法简单、快速、准确,适合分析棉籽仁中的脂肪酸组成。     

Study of the GC-MS determination of the palmitic-stearic acid ratio for the characterisation of drying oil in painting: La Encarnación by Alonso Cano as a case study

The correct identification of drying oils plays an essential role in providing an understanding of the conservation and deterioration of artistic materials in works of art. To this end, this work proposes the use of peak area ratios from fatty acids after ensuring that the linear responses of the detector are tested. A GC-MS method, previously reported in the literature, was revisited to its developed and validated in order to identify and quantify of eight fatty acids that are widely used as markers for drying oils in paintings, namely myristic acid (C(14:0)), palmitic acid (C(16:0)), stearic acid (C(18:0)), oleic acid (C(18:1)), linoleic acid (C(18:2)), suberic acid (2C(8)), azelaic acid, (2C(9)) and sebacic acid (2C(10)). The quaternary ammonium reagent m-(trifluoromethyl)phenyltrimethylammonium hydroxide (TMTFAH) was used for derivatization prior to GC-MS analysis of the oils. MS spectra were obtained for each methyl ester derivative of the fatty acids and the characteristic fragments were identified. The method was validated in terms of calibration functions, detection and quantification limits and reproducibility using the signal recorded in SIR mode, since two of the methyl derivatives were not totally separated in the chromatographic run. The proposed method was successfully applied to identify and characterise the most widely used drying oils (linseed oil, poppy seed oil and walnut oil) in the painting La Encarnación. This 17th century easel painting is located in the main chapel of the cathedral in Granada (Spain) and was painted by the well-known artist of the Spanish Golden Age, Alonso Cano (1601-1667).     

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.     

Olive oil or lard?: Distinguishing plant oils from animal fats in the archeological record of the eastern Mediterranean using gas chromatography/combustion/isotope ratio mass spectrometry

Distinguishing animal fats from plant oils in archaeological residues is not straightforward. Characteristic plant sterols, such as β-sitosterol, are often missing in archaeological samples and specific biomarkers do not exist for most plant fats. Identification is usually based on a range of characteristics such as fatty acid ratios, all of which indicate that a plant oil may be present, none of which uniquely distinguish plant oils from other fats. Degradation and dissolution during burial alter fatty acid ratios and remove short-chain fatty acids, resulting in degraded plant oils with similar fatty acid profiles to other degraded fats. Compound-specific stable isotope analysis of δ(13)C(18:0) and δ(13)C(16:0), carried out by gas chromatography/combustion/isotope ratio mass spectrometry (GC/C/IRMS), has provided a means of distinguishing fish oils, dairy fats, ruminant and non-ruminant adipose fats, but plant oils are rarely included in these analyses. For modern plant oils where C(18:1) is abundant, δ(13)C(18:1) and δ(13)C(16:0) are usually measured. These results cannot be compared with archaeological data or data from other modern reference fats where δ(13)C(18:0) and δ(13)C(16:0) are measured, as C(18:0) and C(18:1) are formed by different processes resulting in different isotopic values. Eight samples of six modern plant oils were saponified, releasing sufficient C(18:0) to measure the isotopic values, which were plotted against δ(13)C(16:0). The isotopic values for these oils, with one exception, formed a tight cluster between ruminant and non-ruminant animal fats. This result complicates the interpretation of mixed fatty residues in geographical areas where both animal fats and plant oils were in use.     

Glycidyl fatty acid esters in food by LC-MS/MS: method development

An improved method based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) for the analysis of glycidyl fatty acid esters in oils was developed. The method incorporates stable isotope dilution analysis (SIDA) for quantifying the five target analytes: glycidyl esters of palmitic (C16:0), stearic (C18:0), oleic (C18:1), linoleic (C18:2) and linolenic acid (C18:3). For the analysis, 10 mg sample of edible oil or fat is dissolved in acetone, spiked with deuterium labelled analogs of glycidyl esters and purified by a two-step chromatography on C18 and normal silica solid phase extraction (SPE) cartridges using methanol and 5% ethyl acetate in hexane, respectively. If the concentration of analytes is expected to be below 0.5 mg/kg, 0.5 g sample of oil is pre-concentrated first using a silica column. The dried final extract is re-dissolved in 250 μL of a mixture of methanol/isopropanol (1:1, v/v), 15 μL is injected on the analytical C18 LC column and analytes are eluted with 100% methanol. Detection of target glycidyl fatty acid esters is accomplished by LC-MS/MS using positive ion atmospheric pressure chemical ionization operating in Multiple Reaction Monitoring mode monitoring 2 ion transitions for each analyte. The method was tested on replicates of a virgin olive oil which was free of glycidyl esters. The method detection limit was calculated to be in the range of 70-150 μg/kg for each analyte using 10 mg sample and 1-3 μg/kg using 0.5 g sample of oil. Average recoveries of 5 glycidyl esters spiked at 10, 1 and 0.1 mg/kg were in the range 84% to 108%. The major advantage of our method is use of SIDA for all analytes using commercially available internal standards and detection limits that are lower by a factor of 5-10 from published methods when 0.5 g sample of oil is used. Additionally, MS/MS mass chromatograms offer greater specificity than liquid chromatography-mass spectrometry operated in selected ion monitoring mode. The method will be applied to the survey of glycidyl fatty acid esters in food products on the Canadian market.     

Study of the GC–MS determination of the palmitic–stearic acid ratio for the characterisation of drying oil in painting: La Encarnación by Alonso Cano as a case study

The correct identification of drying oils plays an essential role in providing an understanding of the conservation and deterioration of artistic materials in works of art. To this end, this work proposes the use of peak area ratios from fatty acids after ensuring that the linear responses of the detector are tested. A GC-MS method, previously reported in the literature, was revisited to its developed and validated in order to identify and quantify of eight fatty acids that are widely used as markers for drying oils in paintings, namely myristic acid (C_14:0), palmitic acid (C_16:0), stearic acid (C_18:0), oleic acid (C_18:1), linoleic acid (C_18:2), suberic acid (2C₈), azelaic acid, (2C₉) and sebacic acid (2C₁₀). The quaternary ammonium reagent m-(trifluoromethyl)phenyltrimethylammonium hydroxide (TMTFAH) was used for derivatization prior to GC-MS analysis of the oils. MS spectra were obtained for each methyl ester derivative of the fatty acids and the characteristic fragments were identified. The method was validated in terms of calibration functions, detection and quantification limits and reproducibility using the signal recorded in SIR mode, since two of the methyl derivatives were not totally separated in the chromatographic run. The proposed method was successfully applied to identify and characterise the most widely used drying oils (linseed oil, poppy seed oil and walnut oil) in the painting La Encarnación. This 17th century easel painting is located in the main chapel of the cathedral in Granada (Spain) and was painted by the well-known artist of the Spanish Golden Age, Alonso Cano (1601-1667).     

SPME/GC-MS鉴别地沟油新方法

采用固相微萃取(SPME)气相色谱-质谱联用(GC-MS)技术,研究了油脂内源及外源物质的微量化学成分。结果发现:纯正花生油和大豆油不含反式脂肪酸,地沟油含有反式脂肪酸trans-C18∶1、trans-C18∶2;纯正花生油和大豆油中含有正己醛、正壬醛和正癸醛等杂质,而地沟油中除了这几种醛类外还含有乙酸、3-丁烯腈、2,5-二甲基吡嗪等特征杂质成分。通过测定内源性物质和外源性物质的存在,两种检测结果互相印证,综合判断,最终可确定是否为地沟油,据此首次建立了SPME/GC-MS鉴别地沟油的新方法。该方法不但可用于地沟油的鉴别,还可用于掺假食用油的检测。     

碱催化法衍生化气相色谱/质谱法分析青海湖裸鲤鱼油中的脂肪酸

用碱催化法将青海湖裸鲤鱼油甲酯化,以气相色谱/质谱法分析鱼油中的脂肪酸。青海湖裸鲤可食用部分中鱼油含量为25.13%。从鱼油中共鉴定出47种脂肪酸,包括直链、单支链、多支链饱和脂肪酸,单不饱和、多不饱和脂肪酸,环丙烷基、呋喃基脂肪酸等。不饱和脂肪酸含量为73.6%,其中多不饱和脂肪酸含量为25.4%,以C18∶2(4.9%),C18∶3(3.1%),C20∶4(1.3%),C20∶5(二十碳五烯酸（EPA）, 9.4%)和C22∶6(二十二碳六烯酸（DHA）, 6.7%)为主。单不饱和脂肪酸含量为48.2%,主要由C16∶1(20.3%),C18∶1(25.9%)构成。饱和脂肪酸含量为25.7%,主要有C14∶0(3.4%),C16∶0 (19.4%)和C18∶0(1.1%)。青海湖裸鲤鱼油中还存在不常见的环丙烷基和呋喃基脂肪酸及多种奇数碳链和支链脂肪酸。因此,青海湖裸鲤是功能性脂肪酸的重要膳食来源。     

Comparative study on fatty acid composition of olive (Olea europaea L.), with emphasis on phytosterol contents

The present study was designed to determine the fatty acid composition and phytosterol contents of Turkish native olive cultivars, namely Kilis Yağlık and Nizip Yağlık cv. In this context, olive fruits from 34 locations were sampled and then screened for their components in comparison. Fifteen different fatty acids were found in both olive oils. In the order of abundance, the most important ones were oleic acid (18:1) > palmitic acid (16:0) > linoleic acid (18:2) > stearic acid (18:0). Significant differences were observed in the contents of oleic acid (18:1), palmitic acid (16:0), linoleic acid (18:2) but not for stearic acid content in comparison both oils (p < 0.01). There were significant differences in terms of unsaturated fatty acids, saturated fatty acids and polyunsaturated fatty acids (p < 0.01). The seven phytosterols – cholesterol, campesterol, stigmasterol, β ‐sitosterol, Δ‐5‐avenasterol, Δ‐7‐stigmastenol and Δ‐7‐avenasterol – were studied in both oil sources. The predominant sterols were β ‐sitosterol, Δ5‐avenasterol and campesterol in the samples analysed. However, no significant differences were found in the levels of the phytosterols between the two olive cultivars.     

Dynamic and isothermal DSC investigation of the kinetics of thermooxidative decomposition of some edible oils

The kinetics of thermooxidation of edible oils: soybean oil, rapeseed oil, corn and peanut oil was investigated in two ways. The DSC and its pressure version (PDSC) were used for measurements under the isothermal and non-isothermal conditions in atmosphere of oxygen. Comparing these two methods for each oil the differences between the values of activation energies were observed. However, mechanism of oxidation in both method was different.     

LF-NMR结合化学模式识别鉴别油脂种类及餐饮废弃油脂

应用主成分分析(Principal component analysis,PCA)和聚类分析法(Cluster analysis,CA)对9种(27个)常见食用植物油及100个餐饮废油的低场核磁共振(Low-field nuclear magnetic resonance,LF-NMR)(T2)弛豫特性数据进行分析。结果表明:在正常食用油种类区分方面,主成分分析的效果较优,9种食用油在主成分分布图上按种类正确分组,边界清晰。而在正常食用油与餐饮废油的区分方面,聚类分析效果较优,引入30个待测样本后,聚类分析(127个样品,欧式距离=5)的正确率为94.49%,分析误判率为5.51%,分组效果良好。LF-NMR结合化学模式识别可实现对油脂种类及餐饮废弃油脂的鉴别。     

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。     

Electrospray ionization mass spectrometry and partial least squares discriminant analysis applied to the quality control of olive oil

Direct infusion electrospray ionization mass spectrometry in the positive ion mode [ESI(+)‐MS] is used to obtain fingerprints of aqueous–methanolic extracts of two types of olive oils, extra virgin (EV) and ordinary (OR), as well as of samples of EV olive oil adulterated by the addition of OR olive oil and other edible oils: corn (CO), sunflower (SF), soybean (SO) and canola (CA). The MS data is treated by the partial least squares discriminant analysis (PLS‐DA) protocol aiming at discriminating the above‐mentioned classes formed by the genuine olive oils, EV (1) and OR (2), as well as the EV adulterated samples, i.e. EV/SO (3), EV/CO (4), EV/SF (5), EV/CA (6) and EV/OR (7). The PLS‐DA model employed is built with 190 and 70 samples for the training and test sets, respectively. For all classes (1–7), EV and OR olive oils as well as the adulterated samples (in a proportion varying from 0.5 to 20.0% w/w) are properly classified. The developed methodology required no ions identification and demonstrated to be fast, as each measurement lasted about 3 min including the extraction step and MS analysis, and reliable, because high sensitivities (rate of true positives) and specificities (rate of true negatives) were achieved. Finally, it can be envisaged that this approach has potential to be applied in quality control of EV olive oils. Copyright © 2013 John Wiley & Sons, Ltd.     

Sequential (step-by-step) detection,identification and quantitation of extra virgin olive oil adulteration by chemometric treatment of chromatographic profiles

An analytical method for the sequential detection, identification and quantitation of extra virgin olive oil adulteration with four edible vegetable oils--sunflower, corn, peanut and coconut oils--is proposed. The only data required for this method are the results obtained from an analysis of the lipid fraction by gas chromatography-mass spectrometry. A total number of 566 samples (pure oils and samples of adulterated olive oil) were used to develop the chemometric models, which were designed to accomplish, step-by-step, the three aims of the method: to detect whether an olive oil sample is adulterated, to identify the type of adulterant used in the fraud, and to determine how much aldulterant is in the sample. Qualitative analysis was carried out via two chemometric approaches--soft independent modelling of class analogy (SIMCA) and K nearest neighbours (KNN)--both approaches exhibited prediction abilities that were always higher than 91% for adulterant detection and 88% for type of adulterant identification. Quantitative analysis was based on partial least squares regression (PLSR), which yielded R2 values of >0.90 for calibration and validation sets and thus made it possible to determine adulteration with excellent precision according to the Shenk criteria.     

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.     

GC-MS法鉴别食用油和餐饮业中废弃油脂的研究

用气相色谱 质谱联用(GC MS)方法对7种餐饮业中废弃油脂(简称废油脂)和5种合格成品食用油(简称食用油)中所有脂肪酸进行分析。研究发现,废油脂中部分不饱和脂肪酸受到氧化,使脂肪酸相对不饱和度(U R)值明显小于同种类食用油中的脂肪酸相对不饱和度(U R)值,其脂肪酸的质量分数分布与同种类的食用油中脂肪酸的质量分数分布有很大的区别,以及绝大部分废油脂中存在较大量矿物油。研究表明,脂肪酸相对不饱和度(U R)值和脂肪酸的质量分数分布可以鉴别废油脂。     

High-resolution detection of adulteration of maize oil using multi-component compound-specific delta13C values of major and minor components and discriminant analysis

Maize oil commands a premium price and is thus a target for adulteration with cheaper vegetable oils. Detection of this activity presents a particular challenge to the analyst because of the natural variability in the fatty acid composition of maize oils and because of their high sterol and tocopherol contents. This paper describes a method that allows detection of adulteration at concentrations of just 5% (m/m), based on the Mahalanobis distances of the principal component scores of the delta(13)C values of major and minor vegetable oil components. The method makes use of a database consisting of delta(13)C values and relative abundances of the major fatty acyl components of over 150 vegetable oils. The sterols and tocopherols of 16 maize oils and 6 potential adulterant oils were found to be depleted in (13)C by a constant amount relative to the bulk oil. Moreover, since maize oil contains particularly high levels of sterols and tocopherols, their delta(13)C values were not significantly altered when groundnut oil was added up to 20% (m/m) and it is possible to use the values for the minor components to predict the values that would be expected in a pure oil; therefore, comparison of the predicted values with those obtained experimentally allows adulteration to be detected. A refinement involved performing a discriminant analysis on the delta(13)C values of the bulk oil and the major fatty acids (16:0, 18:1 and 18:2) and using the Mahalanobis distances to determine the percentage of adulterant oil present. This approach may be refined further by including the delta(13)C values of the minor components in the discriminant analysis thereby increasing the sensitivity of the approach to concentrations at which adulteration would not be attractive economically.     

羟肟酸法快速测定食用油主要营养必需脂肪酸

建立了用ＨＰＬＣ简便快速测定食用油主要营养必需脂肪酸的羟肟酸法。样品一步衍生成羟肟酸上机分析,不需分离纯化。线性范围为０．０５～０．６０ｇ／Ｌ,回收率９６．９３％,ＲＳＤ＝１．８０％（ｎ＝４）,日内和日间ＲＳＤ分别为１．２４％和１．６２％（ｎ＝６）。比较１８∶３,１８∶２和１８∶１的甲酯与相应的三脂肪酸甘油酯标准品衍生的标准曲线,发现二者转化率均相差近一倍,回收率实验和样品实测结果亦证实,选取甲酯标准品衍生作标准曲线用于油脂定量是不合理的。     

Rapid and sensitive determination of fatty acids in edible oil by liquid chromatography-electrospray ionization tandem mass spectrometry

A sensitive and robust on-line LC/MS method was developed for quantitative determination of linoleic acid,docosahexaenoic acid and docosanoic acid from edible oil samples.The oil samples were dissolved in chloroform-isopropyl alcohol(20:80,v:v)solution and the three fatty acids were separated by HPLC with a C4 column using 10 mmol/L ammonium acetate-isopropyl alcohol-acetonitrile(20:40:40,v:v:v)mobile phase in isocratic elution.Electrospray ionization mass spectrometry with the selected ion recording monitoring was used to detect and quantify the fatty acid.The calibration curves were linear in the range of 10.00–5000 pg/mL for linoleic acid and docosanoic acid,and 1.000–500.0 pg/mL for docosahexaenoic acid.The limit of detection was 2.0 pg/mL for linoleic acid,3.0 pg/mL for docosanoic acid,and 0.20 pg/mL for docosahexaenoic acid.The results showed that the method described in this paper could be utilized for rapid determination of three fatty acids at picogram levels in edible oils.