基质辅助激光解吸电离-傅里叶变换离子回旋共振质谱技术用于食用油中甘油三酯的快速分析

食用油中甘油三酯(Triacylglycerols,TAGs)的含量及种类快速高效的检测方法对保障人体健康具有重要意义。本研究基于基质辅助激光解吸电离-傅里叶变换离子回旋共振质谱(MALDI-FTICR-MS)技术建立了一种用于食用油中TAG的直接快速定性分析方法。采用2,5-二羟基苯甲酸(DHB)的丙酮溶液作为基质,二氯甲烷作为食用油的溶剂,在激光能量为15%、频率为100 Hz、辐照次数为100 Shots条件下可以获得重复稳定的信号(RSD9%)。利用一级质谱和二级质谱对食用油中TAG进行了初步的分类分析。在置信度为95%的条件下,采用主成分分析(PCA)方法可对34种食用油进行很好的分类。利用本方法可以直接识别出橄榄油中掺杂5%的菜籽油,表明本方法可以用于食用油样品的快速筛查分析。     

基于多孔石墨碳柱和正辛烷-异丙醇流动相的高效液相色谱法分离分析食用油中的甘油三酯

建立了分离食用油中甘油三酯(TAG)的高效液相色谱分析方法。使用多孔石墨碳柱(Hypercarb柱, 100 mm×2.1 mm, 5μm),以正辛烷-异丙醇(70∶30,V/V)为流动相,流速0.25 mL/min,在60℃柱温下分离,检测波长215 nm。考察了实验条件对分离和检测的影响。在优化条件下,分离了7种植物油和5种动物油中的TAG,借助质谱联用技术,识别了玉米油中14种TAG、橄榄油中9种TAG、葵花籽油中14种TAG、大豆油中14种TAG、芝麻油中15种TAG、花生油中18种TAG、菜籽油中17种TAG、鸡油中16种TAG、猪油中17种TAG、羊油中12种TAG、牛油中14种TAG和鹅油中16种TAG。在分析鸡油和牛油时,实现了SLP和SOP与其各自异构体的分离,表明本方法具有分离TAG位置异构体的能力。采样本方法分离并分析了玉米油、菜籽油、葵花籽油、大豆油、花生油、芝麻油、橄榄油中的三亚油酰基甘油三酯(LLL)的含量。本方法使用的流动相污染小、实用性较好,为食用油中的TAG及其异构体的分析提供了有价值的参考。     

实时直接分析-四极杆飞行时间质谱法快速鉴别油茶籽油真伪

建立了实时直接分析-四极杆飞行时间质谱(DART-QTOF-MS)技术结合化学计量学分析快速鉴别油茶籽油的方法。4种食用油(油茶籽油、菜籽油、花生油和大豆油)用甲醇-异丙醇(50∶50,含5 mmol/L乙酸铵)稀释后经实时直接分析离子源解吸电离,在正离子模式下以TOF MS和信息依赖采集模式获得质谱数据,对4种食用油的质谱图进行了初步鉴定,并采用化学计量学建立主成分分析(PCA)和正交偏最小二乘法-判别分析(OPLS-DA)模型,以实现数据可视化和油茶籽油的快速鉴别。结果表明,4种食用油的质谱图存在明显差异,主要为甘油三酯(TAG)氨加合离子［TAG+NH4］+(m/z 850~1 100)、甘油二酯(DAG)氨加合离子［DAG+NH4］+(m/z 600~700)和DART源内碎片离子,共检出20种甘油三酯和6种甘油二酯。进一步采用化学计量学对4种植物油指纹图谱进行分析,发现该方法可准确鉴别和预测油茶籽油、菜籽油、花生油和大豆油,具有前处理简单、分析速度快、操作方便和准确可靠等优点,可用于油茶籽油的鉴别研究。     

大气压化学电离-高分辨质谱直接分析食用油中的甘油三酯

建立了食用油中甘油三酯的大气压化学电离-质谱直接分析检测方法.在考察实验条件影响的基础上,选择乙腈作为溶剂,正离子检测模式,进样流速为800 μL/h,喷雾器温度250℃,电晕针电流为5000 nA.用本方法对10种食用油进行分析,结果表明,植物油与动物油之间差异较大.经主成分分析,选择m/z 857.76与m/z 881.76峰强度比作为指标,重复性RSD＜5％,可直接识别出玉米油中掺杂5％的猪油.用碰撞诱导解离(CID)实验初步鉴别了食用油的3个特征峰.利用本方法对泔水油样品和煎炸油样品进行分析,结果泔水油样品中含有植物油和动物油,而煎炸油样品也与商品食用油存在差异.本方法可用于食用油样品的快速筛查.     

人工神经网络用于直接化学电离质谱分析食用油品质的研究

无需任何样品预处理,采用表面解吸常压化学电离质谱(DAPCI-MS)技术直接对涂覆在载玻片表面的食用油样品和地沟油样品进行检测,快速获得了不同油类样品的质谱信号;并运用改进的反向传输(BP)人工神经网络对DAPCI-MS所得到的油类样品质谱数据进行有监督的分类识别,建立多分组预测模型。结果表明:DAPCI-MS能够承受食用油中复杂基体的影响,可对油类样品进行直接快速质谱分析;误差反转(BP)神经网络具有良好的分类判别能力,对食用油样品质谱数据识别效果比较理想,能够在对地沟油和非地沟油样品进行有效区分的同时,实现对不同品种的食用油的分离及分类判别。本方法分析速度快,信息提取准确,识别精度高,对快速质谱技术结合神经网络在该领域的应用以及食用油品质的快速鉴定具有重要的借鉴意义。     

液相色谱-大气压化学电离质谱分析鉴别地沟油中的氧化成分

采用液相色谱-大气压化学电离质谱(HPLC-APCI-MS)方法,分析了食用油脂和地沟油的甘油三酯(TAG)组成。采用C18色谱柱,乙腈-丙酮为流动相,梯度洗脱,APCI正离子模式检测。应用本方法检测了15个地沟油和11个食用油样品,结果表明,地沟油中存在三亚油酸甘油酯(LLL)、二亚油酸单油酸甘油酯(LOL)、二亚油酸单亚麻酸甘油酯(LLnL),二油酸单亚油酸甘油酯(OOL)等甘油三酯的5种亚油酰基氧化产物。采用偏最小二乘法判别分析(PLS-DA)化学计量学方法,分析建立了地沟油和正常食用油的判别模型,实现了正常食用油和地沟油区分,模型正确判别率96.2%。在判别模型中,含有亚油酸环氧化物的TAG分子对判别贡献率较大,该类化合物可作为地沟油区别于正常油脂的标志成分。     

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。     

高温气相色谱-质谱联用法分析玉米油、掺杂油和煎煮油

用MXT-65TG金属毛细管柱研究了食用油中甘油三酯的高温气相色谱-质谱分析方法。考察了实验条件对分离检测的影响。根据质谱图中甘油三酯裂解的碎片离子[RCO]~+,[RCO+74]~+,[RCO+128]~+和[M-RCOO]~+,结合谱库检索,对食用油中甘油三酯组成进行定性分析。利用该方法,研究了掺杂不同比例的猪油时,玉米油甘油三酯谱图的差异,显示该方法可检测到玉米油中掺杂含量低至10%的猪油。对自制煎炸油和水煮油样品的分析显示,其中甘油二酯的相对含量逐渐升高。     

气相色谱-负化学源质谱联用法测定水产品及食用油中氟乐灵的残留量

建立了一种可用于水产品及食用油中氟乐灵残留量分析的分散型固相萃取-气相色谱-负化学离子源质谱方法。水产品及食用油经乙腈提取,4 ℃冷藏后,采用分散型固相萃取法净化,由气相色谱-负化学离子源质谱选择离子监测技术进行测定与确证,同位素内标法定量。在1~40 μg/L范围内氟乐灵农药的线性关系良好;方法定量限（LOQ）为0.02 μg/kg;对鳗鱼、烤鳗、梭子蟹、小龙虾、猪油和橄榄油等6种复杂基质进行1.0、2.0和3.0 μg/kg等3个水平的添加回收试验,平均回收率均处于80%~100%之间,RSD≤10.3%;无干扰现象出现。该方法可作为水产品及食用油中氟乐灵残留检测的确证方法。     

基于微波等离子体炬串联质谱鉴别蜂蜜和糖浆

采用微波等离子体炬串联质谱(Microwave plasma torch mass spectrometry,MPT-MS)技术,在无需样品预处理的条件下,建立了快速鉴别3种蜂蜜和4种糖浆的方法。在正离子模式下,蜂蜜和糖浆直接由MPT产生的火焰离子化,生成的离子采用四极杆质谱仪(QM)检测,得到蜂蜜和糖浆的质谱信息,采用化学计量学方法进一步对质谱数据进行分析。结果表明,MPT-MS结合化学计量学的方法,可以快速鉴别蜂蜜和糖浆,主成分分析(PCA)显示PC1、PC2和PC3的总贡献率达91.2%;聚类分析(CA)显示当临界值为7时,除紫云英蜜和菊粉糖浆外,可以有效的区分蜂蜜和糖浆;偏最小二乘判别分析(PLS-DA)显示蜂蜜和糖浆可以被有效区分;判别分析(DA)显示蜂蜜和糖浆的判别准确率为100%。本方法无需样品预处理,具有分析速度快、信息提取准确和识别精度高等优点,可用于蜂蜜与主要掺假糖浆的鉴别。     

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。     

Development of a voltammetric electronic tongue for discrimination of edible oils

In this paper, we propose a novel strategy to perform cyclic voltammetric measurements with a platinum microelectrode directly in edible oil samples. The microelectrode was employed as an electronic tongue that, along with the application of chemometrics to the current–potential responses, proved useful for discriminating oils on the basis of their quality and geographical origin. The method proposed here is based on the use of suitable room temperature ionic liquids, added to oils as supporting electrolytes to provide conductivity to the low-polarity samples. The entire voltammograms, recorded directly on the oil/RTIL mixtures, were processed via principal component analysis and a classification technique (K nearest neighbors), to extract information on samples characteristics. Data processing showed that oils having different nature (i.e. maize and olive) or geographical origin (i.e. olive oils coming from different regions) can be distinguished.     

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。     

Rapid screening of mixed edible oils and gutter oils by matrix-assisted laser desorption/ionization mass spectrometry

Authentication of edible oils is a long-term issue in food safety, and becomes particularly important with the emergence and wide spread of gutter oils in recent years. Due to the very high analytical demand and diversity of gutter oils, a high throughput analytical method and a versatile strategy for authentication of mixed edible oils and gutter oils are highly desirable. In this study, an improved matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) method has been developed for direct analysis of edible oils. This method involved on-target sample loading, automatic data acquisition and simple data processing. MALDI-MS spectra with high quality and high reproducibility have been obtained using this method, and a preliminary spectral database of edible oils has been set up. The authenticity of an edible oil sample can be determined by comparing its MALDI-MS spectrum and principal component analysis (PCA) results with those of its labeled oil in the database. This method is simple and the whole process only takes several minutes for analysis of one oil sample. We demonstrated that the method was sensitive to change in oil compositions and can be used for measuring compositions of mixed oils. The capability of the method for determining mislabeling enables it for rapid screening of gutter oils since fraudulent mislabeling is a common feature of gutter oils.     

Determination of polycyclic aromatic hydrocarbons in vegetable oils using solid-phase microextraction-comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry

A simple and fast solid-phase microextraction method coupled with comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry was developed for analysis of polycyclic aromatic hydrocarbons in edible oil, performed directly in a hexane solution of the oil. Sampling conditions (solvent used, extraction time, extraction temperature and fiber rinsing time) were optimized by using a sample of oil fortified with a standard solution of polycyclic aromatic hydrocarbons. The method was validated by calculating linear range, correlation coefficient, accuracy, repeatability, detection limit and quantification limit. The method was applied to several oils collected from the market and directly from an olive pomace extraction plant.     

Differentiation of vegetable oils by mass spectrometry combined with statistical analysis

The main triacylglycerol (TAG) composition of different plant oils (almond, avocado, corn germ, grape seed, linseed, mustard seed, olive, peanut, pumpkin seed, sesame seed, soybean, sunflower, walnut and wheat germ) were analyzed using two different mass spectrometric techniques: HPLC/APCI-MS (high-performance liquid chromatography/atmospheric pressure chemical ionization mass spectrometry) and MALDI-TOFMS (matrix-assisted laser desorption/ionization time-of-flight mass spectrometry).Linear discriminant analysis (LDA) as a multivariate mathematical statistical method was successfully used to distinguish different plant oils based on their relative TAG composition. With LDA analysis of either APCI-MS or MALDI-MS data, the classification among the almond, avocado, grape seed, linseed, mustard seed, olive, sesame seed and soybean oil samples was 100% correct. In both cases only 6 different oil samples from a total of 73 were not classified correctly.     

Discriminating olive and non-olive oils using HPLC-CAD and chemometrics

This work presents a method for an efficient differentiation of olive oil and several types of vegetable oils using chemometric tools. Triacylglycerides (TAGs) profiles of 126 samples of different categories and varieties of olive oils, and types of edible oils, including corn, sunflower, peanut, soybean, rapeseed, canola, seed, sesame, grape seed, and some mixed oils, have been analyzed. High-performance liquid chromatography coupled to a charged aerosol detector was used to characterize TAGs. The complete chromatograms were evaluated by PCA, PLS-DA, and MCR in combination with suitable preprocessing. The chromatographic data show two clusters; one for olive oil samples and another for the non-olive oils. Commercial oil blends are located between the groups, depending on the concentration of olive oil in the sample. As a result, a good classification among olive oils and non-olive oils and a chemical justification of such classification was achieved.