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%。     

应用Milkoscan FT120对牛奶掺假的研究

采用红外扫描乳品测定仪对原料乳中脂肪、蛋白、干物质、乳糖、柠檬酸密度、冰点、碳水化合物、全糖、游离脂肪酸等成分参数的检测建立原料乳光谱数据库,在具有代表性原料乳中加入植脂末模拟牛奶掺假,通过应用掺假模块鉴别生鲜牛奶是否掺假.     

低场核磁共振结合化学计量学方法快速检测掺假核桃油

以掺假核桃油样品为低场核磁共振检测对象,利用主成分分析法(PCA)和偏最小二乘回归法(PLSR)分析处理Carr-Purcell-Meiboom-Gill(CPMG)序列的核磁共振弛豫数据,旨在探求一种能快速检测核桃油品质的新方法。对几种常见掺假形式(掺入大豆油、玉米油、葵花油)的核桃油样品和纯核桃油样品进行检测和评价。实验结果表明:纯核桃油和掺入不同种类食用油的掺假核桃油在主成分得分图上可以得到很好的区分,且掺假样品随掺假比例在图中呈规律性分布;采用PLSR法对CPMG数据和实际掺假率进行回归,可实现对核桃油掺假水平的准确定量测定。方法快速、无损、准确,在食用油制品的品质控制及评价方面具有很大的应用潜力。     

粒子群最小二乘支持向量机结合偏最小二乘法用于芝麻油质量的鉴别

结合粒子群最小二乘支持向量机(PSO-LSSVM)与偏最小二乘法(PLS)提出一种基于气相色谱技术的新方法,对芝麻油进行真伪鉴别,并对掺伪品中掺假比例进行定量分析。采用主成分分析法(PCA)对857个样本的脂肪酸色谱数据进行分析,优选主成分作为最小二乘支持向量机(LSSVM)的输入向量。利用粒子群算法(PSO)优化LSSVM,构建芝麻油掺伪鉴别的两级分类模型,同时运用PLS建立掺伪芝麻油中掺伪油脂的定量校正模型,两级分类模型的准确率分别达到了100%和98.7%,定量分析模型的平均预测标准偏差(RMSEP)为3.91%。结果表明,本方法的鉴别准确性和模型泛化能力均优于经典的BP神经网络和支持向量机(SVM),可用于食用油脂加工和流通环节的质量控制,为食用油质量的准确鉴定提供了一条有效途径。     

用纸上扩散法快速检测辣椒油中的苏丹红

应用毛细现象知识以及物质的溶解、吸附原理,研究了一种仅用一小块打印纸、一支钢笔和少量酒精就能无环境毒害、简便、快速地检测辣椒油中是否含有苏丹红Ⅰ、Ⅱ、Ⅲ、Ⅳ的检测方法。该方法最低检出浓度为0.8g/L,与实验所测的辣椒油中需要加入苏丹红的最低以假乱真浓度基本一致。虽然少量染料对该检测可以产生误判,但在辣椒油中添加掺假染料必须考虑价格、颜色、油溶性、怪味、剧毒等性质,目前仅发现苏丹红能同时满足上述制假条件,因此它们并不妨碍该方法用于辣椒油是否含有苏丹红的自我保护性检测,其也非常适合执法人员的现场快速检验。该方法构思巧妙,具有非常强的实用性。     

电喷雾萃取电离质谱法用于掺假白酒的快速分析

采用自行研制的电喷雾萃取电离源(EESI)与LTQ-XL质谱仪耦合,并结合主成分分析(PCA)和聚类分析(CA),建立了一种能在无需样品预处理的条件下直接、快速、准确鉴别茅台等八种掺假白酒(混掺水和工业酒精,且通过酒精计调控掺假酒的酒精度与真酒保持一致)的新方法. 同时,利用串联质谱能够对目标组分进行准确鉴定. 研究结果表明,EESI-LTQ-MS检测单个样品的时间小于1 min,且重现性好,PCA区分正确率高达96.5%. 通过设置未知样分析进一步验证了该方法的可行性. 此外,还结合单光子电离飞行时间质谱法(SPI-TOF-MS)对检测谱图进行对比分析. 阐述了EESI和SPI两种电离技术在挥发性有机物分析上具有各自的优势,且两种检测手段具有互补的特点. 为市场上酒类饮品真假的快速鉴别及品质鉴定建立了一个综合的分析方法,对于快速筛选伪劣酒类产品具有非常重要的应用价值.     

用气相色谱仪检测食用植物油中掺杂的棕榈油

某种油脂混杂少量其它油脂的检验方法(即掺伪试验),有些已被公认,如棉籽油的哈尔芬(Halphen)试验,芝麻油的修正威氏(Modified     

光谱法鉴别油茶籽油的真伪1

采用紫外光谱法、荧光光谱法、表面增强拉曼光谱对油茶籽油、掺玉米油油茶籽油等进行分析测试.结果表明,紫外光谱法对油茶籽油的掺假比较难以鉴别,荧光光谱法能够一定程度上对掺假油茶籽油进行鉴别;不同掺假比例的油茶籽油与纯油茶籽油的表面增强拉曼光谱可明显区分,且掺假比例越大,掺假样品与纯油茶籽油的鉴别效果越好,因此表面增强拉曼光谱可作为一种简单、可靠的方法用于鉴别油茶籽油.     

基于核酸等温扩增与侧向层析试纸联用鉴定黑胡椒调味品的真实性

本研究以黑胡椒中木瓜籽掺假为代表性研究对象,开发了一种分子扩增与侧向流动层析（LFA）联用方法,通过整合重组酶聚合酶链式扩增反应（RPA）和LFA技术,实现了对黑胡椒样品中木瓜籽掺假的敏感快速检测。该方法的检出限（LOD）为0.1%,整个检测过程可以在40 min内完成,适用于现场测试,并成功用于鉴定香料黑胡椒的真实性。     

中国有望推行牛乳掺假快速检测方法

中国科协在不久前召开的新闻发布会上宣布,一种快速检测牛乳掺假的方法已经研发出来,广泛推行后将对保障我国乳品安全发挥重要作用。为了寻找一种适合企业和牧场用于监控牛乳品质的快速、价廉、简便、无损的方法,浙江工商大学研究小组利用低场核磁共振仪研究了纯牛乳和各种形式（掺水、掺食盐、掺尿素、掺豆浆、掺复原乳）的掺假乳的弛豫特性（差别）,并用主成分分析法处理样品的检测数据。     

气相色谱法与麻油纯度试验法在芝麻油掺伪鉴定中的应用

用气相色谱法和麻油纯度试验法对芝麻油掺伪情况进行分析。用气相色谱法分析脂肪酸组成,测定植物油中的主要脂肪酸,来确定是何种油或掺入其它何种植物油;麻油纯度试验法用于定量。两者可结合起来使用。     

气相色谱-质谱法测定植物油中8种维生素E及其在芝麻油真伪鉴别方面的应用

建立了气相色谱-质谱（GC-MS）同时测定植物油中α-、β-、γ-、δ-生育酚和α-、β-、γ-、δ-生育三烯酚等8种维生素E的分析方法。植物油样品经甲醇超声提取、浓缩、定容,在分时段选择离子监测（SIM）模式下分离分析,采用外标法进行定量。结果表明,8种维生素E可实现基线分离;在0.01~1 mg/L范围内,所有目标物均呈良好线性关系,相关系数均大于0.99;检出限和定量限分别为0.03~0.25 mg/kg和0.10~0.83 mg/kg;在芝麻油中分别添加10、50和250 mg/kg 3个水平的8种维生素E进行加标试验,平均回收率为87.5%~107.4%,相对标准偏差（RSD）≤ 7.5%。所建立的方法简单、准确、可靠,且灵敏度高,可用于测定植物油中8种维生素E的含量。采用上述方法对芝麻油、大豆油、菜籽油、葵花籽油、花生油、玉米油和棕榈油等7种共75个植物油样品中维生素E的含量进行测定。结果显示,芝麻油与其他6种植物油中的8种维生素E的组成和含量均有显著差异性,因此该方法可作为芝麻油掺入其他植物油的特征鉴定指标。     

Comparative Study using Raman and Visible Spectroscopy of Cretan Extra Virgin Olive Oil Adulteration with Sunflower Oil

The adulteration of extra virgin olive oil with low-quality and inexpensive seed oil is a serious problem in the industry. In recent years, the characterization of extra virgin olive oil adulteration with various techniques has been successfully implemented. In this work, a comparative study of Raman and visible spectroscopy is presented. These methods are rapid, noninvasive, and no sample pretreatment is required. We used both methods to study Cretan extra virgin olive oil adulterated with sunflower oil. Statistical analysis based on partial least square regression was used to determine the detection limits of the methods. Raman spectroscopy was superior in comparison to visible spectroscopy with adulteration detection limits of 3.5 and 5.5%, respectively, for the same samples. These results indicate that both techniques are suitable for olive oil quality control.     

Analysis of olive oil and seed oil triglycerides by capillary gas chromatography as a tool for the detection of the adulteration of olive oil

Individual triglyceride (TG) species of olive oil and several seed oils (corn, cottonseed, palm, peanut, soybean, and sunflower) are baseline separated on a WCOT TAP CB fused-silica capillary column by capillary gas chromatography (CGC) with a flame-ionization detector (FID) and either cold on-column or split injection. An adulteration of olive oil with a low content (< 5%) of these seed oils (except peanut oil) can be verified by the detection of the increasing levels of trilinolein or tripalmitin in olive oil in which these TG species are normally absent or present at very low levels (< 0.5%). An adulteration with over 20% peanut oil can be detected by the increasing levels of palmitodilinolein. TG species that can be coeluted with trilinolein in the reversed-phase high-performance liquid chromatographic (RP-HPLC) mode are baseline separated by the CGC technique, and their structures are identified by selective ion monitoring mass spectrometry. The following comparisons--the CGC-FID and RP-HPLC methods for detection of adulteration, cold on-column and split-injection modes for CGC-FID, and silylation or thin-layer chromatography pretreatment and simple dilution of one or more of the oil samples--are also presented. The normalized percentage area of the TG species is sufficient for the method limits used in this study. Mixtures of virgin olive oil with refined or residue olive oil could not be distinguished from the virgin type by the method used in this study.     

Direct olive oil authentication: detection of adulteration of olive oil with hazelnut oil by direct coupling of headspace and mass spectrometry, and multivariate regression techniques

Control of adulteration of olive oil, together with authentication and contamination, is one of the main aspects in the quality control of olive oil. Adulteration with hazelnut oil is one of the most difficult to detect due to the similar composition of hazelnut and olive oils; both virgin olive oil and olive oil are subjected to that kind of adulteration. The main objective of this work was to develop an analytical method able to detect adulteration of virgin olive oils and olive oils with hazelnut oil by means of its analysis by a headspace autosampler directly coupled to a mass spectrometer used as detector (ChemSensor). As no chromatographic separation of the individual components of the samples exists, a global signal of the sample is obtained and employed for its characterization by means of chemometric techniques. Four different crude hazelnut oils from Turkey were employed for the development of the method. Multivariate regression techniques (partial least squares and principal components analysis) were applied to generate adequate regression models. Good values were obtained in both techniques for the parameters employed (standard errors of prediction (SEP) and prediction residual error sum of squares (PRESS)) to evaluate its goodness. With the proposed method, minimum adulteration levels of 7 and 15% can be detected in refined and virgin olive oils, respectively. Once validated, the method was applied to the detection of such adulteration in commercial olive oil and virgin olive oil samples.     

应用校正变换矩阵法识别掺伪食用油

根据食用油中脂肪酸、甾醇以及生育酚含量,应用校正转换矩阵法对花生油掺伪进行了定量检测。用所建立的校正模型对棕榈油、菜籽油和棉籽油掺入到花生油所得到的２７个二元和６个四元人工合成样品进行了验证,结果令人满意。对从市场上购得的５种花生油进行了测定,其中一种是由菜籽油假冒的花生油,另一种为掺入花生精油的棕榈油。     

Detection of refined olive oil adulteration with refined hazelnut oil by employing NMR spectroscopy and multivariate statistical analysis

NMR spectroscopy was employed for the detection of adulteration of refined olive oil with refined hazelnut oil. Fatty acids and iodine number were determined by ¹H NMR, whereas ³¹P NMR was used for the quantification of minor compounds including phenolic compounds, diacylglycerols, sterols, and free fatty acids (free acidity). Classification of the refined oils based on their fatty acids content and the concentration of their minor compounds was achieved by using the forward stepwise canonical discriminant analysis (CDA) and the classification binary trees (CBTs). Both methods provided good discrimination between the refined hazelnut and olive oils. Different admixtures of refined olive oils with refined hazelnut oils were prepared and analyzed by ¹H NMR and ³¹P NMR spectroscopy. Subsequent application of CDA to the NMR data allowed the detection of the presence of refined hazelnut oils in refined olive oils at percentages higher than 5%. Application of the non-linear classification method of the binary trees offered better possibilities of measuring adulteration of the refined olive oils at a lower limit of detection than that obtained by the CDA method.     

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.     

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.