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。     

应用化学计量学和顶空-气相色谱质谱联用技术对7种植物油进行类别分析

采用静态顶空-气相色谱质谱联用技术对7种食用植物油(菜籽油、大豆油、花生油、棉籽油、玉米油、芝麻油、棕榈油)中易挥发成分进行了采集,应用化学计量学分析方法对各油种间易挥发成分的差异进行了评价。通过主成份分析、偏最小二乘判别分析等方法,建立了分类预测模型,分类模型训练和模型验证准确率均为100%,鉴定出了每种植物油的主要标志化合物,为建立植物油类别分析提供了强有力的手段。实验证明,根据植物油挥发性物质对不同种类的植物油进行分类和判别是可行的。     

二维近红外-中红外相关谱在掺假芝麻油判别中的应用

提出了基于二维近红外-中红外相关谱判别掺假芝麻油的方法。分别配制了40个纯芝麻油样品和40个掺假芝麻油(掺入的玉米油的体积分数在3%~60%之间)样品,并采集了所有样品的近红外光谱和中红外光谱。在4 540~6 000cm~(-1)对650~1 800cm~(-1)内进行同步二维近红外-中红外相关谱计算,建立了掺假芝麻油的多维偏最小二乘判别模型,并将其预测性能与二维近红外相关谱和二维中红外相关谱判别模型的预测性能进行了比较。结果表明:上述3个模型对预测集未知样品的判别正确率分别为96.3%,92.6%,96.3%。     

三维荧光等高线特征谱及其应用研究

用图像信息统计法,得到了三维荧光等高线指纹图谱在发射波长方向和激发波长方向的1对特征谱以及1个沿发射波长方向并带有激发波长信息的特征谱.基于3种特征谱,对花生油、调和油和芝麻油的29个食用植物油样本进行了模式识别,结果表明:3种特征谱均能以数值集的形式描述物质的荧光性质,具有特征性和可计算性;数据客观,识别结果准确.将现代的数值分析技术与3种特征谱结合,不仅可实现物质的分类与鉴别,还可揭示化学变化过程中物质结构变化的客观规律.     

微波辅助衍生GC-MS测定脂肪酸及校正变换矩阵法用于食用植物油鉴别的研究

建立了微波衍生化GC—MS测定食用植物油中的脂肪酸含量．并采用校正变换矩阵法对食用植物油的成分进行测定的方法。对微波衍生化的实验条件进行了优化．利用建立的校正模型对40个花生油、菜籽油、芝麻油、棉籽油、棕榈油的二元、三元、四元、五元人工合成样品进行了计算预测，所有样品的平均预测误差部小于5％。对8个实际样品进行了测定．其中有3个掺伪样品．所测调和食用油的结果与标签标示结果相符性较好。本方法可用于快速、准确地测定食用油中各成分含量或定性、定量鉴别掺伪成分。     

二维相关红外光谱与奶粉的品质分析

采用红外光谱法(FT-IR)并结合二阶导数谱对几种奶粉产品进行了无损快速鉴别。结果表明：不同脂肪含量的奶粉其最主要的差别直观地表现在1747cm^-1对应的脂肪C=O吸收峰强度的不同;同理,不同糖含量的奶粉红外谱图上的主要差别就体现在糖的特征峰带(1150—900cm^-1)的强度上。最后,采用二维相关红外光谱法(2D-IR)对全脂奶粉和全脂甜奶粉进行了热扰动过程研究,发现由于糖类物质的加入,奶粉蛋白成分在常温下变得相对稳定。该法为研究奶粉的稳定性提供了一条新的途径。     

聚丙烯光照老化下挥发性有机物的热解析-气相色谱谱质联用分析

改造了大体积顶空采样器,在其样品室上方加入氙灯用以模拟阳光照射,以采集聚合物样品在光照条件下逸出的挥发性有机物。使用Tenax吸附管收集某聚丙烯材料光照老化过程中产生的挥发性有机物,通过热解析-气相色谱/质谱联用仪分析挥发性有机物的种类和相对含量。随着光照时间的增加,挥发性有机物的强度有所变化,但物质种类并未改变。聚丙烯样品中的挥发性有机物主要是烷烃、烯烃、酮、醛等物质。     

GC-MS双内标法测定植物油中脂肪酸组成

建立了植物油中脂肪酸组成及含量的气相色谱-质谱联用双内标定量的检测方法。样品经甲脂化衍生后,通过HP-88毛细管柱(100 m×0.25 mm×0.20μm)分离,在选择离子监测(SIM)模式的条件下,植物油中46种脂肪酸成分在39 min以内得到了较好的分离。利用保留时间和特征离子定性,根据定量离子的峰面积,采用内标法定量。该方法简便、快速、准确、可靠。同时对亚麻籽油中棕榈酸、硬脂酸、油酸、亚油酸和α-亚麻酸进行6次测量,结果的回收率为99.1%~101.6%,变异系数均小于4.00%。将本方法应用于市售样品分析,结果证明这些食用植物油完全符合相关的国家标准。     

光电直读光谱法测定低合金钢中碳、硅、锰、磷、硫的干扰校正

光电直读光谱仪作为一种快速分析仪器,在金属材料的质量控制中发挥着很重要的作用。它的工作原理是应用标准物质制作工作曲线,使各分析元素的谱线强度与其含量呈线性关系,通过将样品中分析元素的谱线强度代入到建立的工作曲线,计算出对应含量。     

气相色谱-质谱技术结合化学计量学对6种植物油进行判别分析

测定了6种不同种类植物油(茶籽油、大豆油、花生油、葵花籽油、玉米油和芝麻油)的脂肪酸组成及含量,旨在探讨利用植物油脂肪酸的指标对不同种类的植物油进行分类和判别的可能性。采用气相色谱-质谱联用技术,对6种不同植物油中脂肪酸的组成和含量进行测定,用SPSS.19.0统计软件进行主成分分析、聚类分析和判别分析。对6种不同植物油脂肪酸进行分析、对比,得出植物油脂的主要成分为C16∶0,C18∶0,C18∶1 cis-9,C18∶2 cis-9,12和C18∶3 cis-9,12,15。这5种主要脂肪酸的总含量在茶籽油、大豆油、花生油、葵花籽油、玉米油和芝麻油中分别为98.455%,97.586%,89.019%,97.378%,98.294%和98.021%。6种植物油的不饱和度(U/S)均大于2.000,其中最小为花生油2.055,最大为茶籽油3.976。进行主成分分析降维得到前3个主成分,因为前3个主成分的特征//值均大于1且累计贡献率达到80.060%,第1主成分的贡献率为35.853%,第2主成分的贡献率为23.847%,第3主成分的贡献率为20.360%。建立了3个典则判别函数,典则判别函数的相关系数均大于0.990,且对于茶籽油、大豆油、花生油、葵花籽油、玉米油和芝麻油的初始分类正确率为100.0%,交叉验证正确率为100.0%。     

傅里叶变换红外光谱结合模式识别法快速鉴别食用油的真伪

采用傅里叶变换红外光谱(FTIR)结合簇类独立软模式识别技术(SIMCA)建立了真伪食用油的快速鉴别方法. 该方法依据FTIR 的指纹特性, 收集并分析了53 个合格食用油和13 个伪造食用油的FTIR 谱图; 通过对谱图取二阶导数和标准化处理, 主成分分析(PCA)提取特征变量; 采用SIMCA 方法分别随机选取43 个合格食用油和9 个伪食用油样品的FTIR 谱图组成训练集, 构建得到真伪食用油的SIMCA 分类模型. 该模型经过剩余10 个合格食用油和4 个伪食用油的验证, 正确识别率达到了100%. 说明FTIR 结合SIMCA 可能成为快速鉴别食用油真伪的一种新方法.     

我国油料产品品质的近红外光谱快速检测技术研究进展

近红外光谱技术是一种快速无损检测技术,具有操作简单、检测成本低、无需化学试剂、绿色环保,以及可实现多品质参数同步检测等优点。该文综述了我国油料和食用植物油品质的近红外光谱速测技术研究进展,包括油料含油量、粗蛋白含量、脂肪酸含量等品质指标,食用油的理化指标,以及脂肪酸和食用油的真实性鉴别,并对油料产品品质的近红外光谱速测技术的发展前景进行了展望。     

Effort to improve the quantitative determination of oxidation and hydrolysis compound classes in edible vegetable oils.

This paper proposes an analytical method to evaluate the classes of products of polymerization, oxidation and hydrolysis as well as the polar compounds present in refined edible oils in a more reliable fashion. The polar compounds of a marketed refined peanut oil were analyzed by preparative gel permeation chromatography and the classes of substances corresponding to single chromatogram peaks were collected by means of a fraction collector, purified and used as standards for high-performance size-exclusion chromatographic analysis. The linearity of detector response, the precision and accuracy of the method for each class of compounds and for polar compounds were assessed. Another aim was to verify whether this method may be applied to other refined peanut oils and to edible vegetable oils in general, even of different botanical origin, using the standards that had already been prepared for that particular peanut oil. The results obtained showed that this was possible and the analytical method developed can be extended to the most common edible vegetable oils.     

傅里叶变换红外吸收光谱识别五种植物油的研究

以花生油、大豆油、芝麻油、棉籽油和米糠油为样品,采用傅里叶变换红外光谱仪,采集傅里叶变换红外吸收光谱,对光谱预处理后,提取红外特征信息,以1746cm-1和2855cm-1处的吸收峰面积比值为横坐标,1099cm-1处与1119cm-1处的吸收峰面积比为纵坐标,在Origin6.0上做出二维分布图,对各种油脂进行识别分析。结果显示,大豆油与其它4种油脂之间有明显区分;大豆油、花生油和芝麻油分布效果好,但棉籽油各样品点之间比较分散;能与其它油脂区分开的有以下几种分布花生油明显区别于芝麻油、棉籽油和大豆油;米糠油明显区别于棉籽油和大豆油。分布有交叉的油脂有米糠油与花生油或芝麻油有交叉,棉籽油与芝麻油有交叉。     

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。     

Rapid characterization of edible oils by direct matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis using triacylglycerols

Direct matrix-assisted laser desorption/ionization time-of-flight mass spectrometric (MALDI-TOFMS) analysis of solutions of edible fats/oils yielded spectra useful for their rapid differentiation and classification. Results also reflected the individual fatty acid components and their degree of unsaturation. After dissolution in hexane, MALDI-MS analysis revealed spectra showing characteristic triacylglycerols (TAGs), the main fat/oil components, as sodium adduct ions. The Euclidean distances calculated using the mass and intensity values for 20 TAGs were used to evaluate and compare spectra. With cluster analysis, animal fats grouped together differently than vegetable oils and the individual oils grouped together by type. The ion abundances for the individual TAGs and their presumed compositions were used to approximate the overall fatty acid composition of canola, soybean, corn, olive and peanut oil, as well as lard. Using this approach the calculated fatty acid compositions and degree of unsaturation generally fell within about 4% of literature values. When the degree of saturation was compared with values calculated from the package labeling the differences were about 7%.     

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.     

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.     

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.