模式识别法分析5种植物油脂

通过模式识别方法区分花生油、大豆油、米糠油、棕榈油和菜籽油。采用气相色谱法分析5种植物油脂的脂肪酸,用面积归一化法计算每个植物油脂样品的各脂肪酸相对含量。以每个植物油脂中9个脂肪酸的相对含量为变量,采用SPSS13.0软件的模式识别技术对119个植物油脂样品进行区分。由主成分分析图可知,花生油、大豆油、米糠油、棕榈油和菜籽油被清晰地分为5组。判别分析建立的判别方程能较好地实现样品的判别,自身验证和交互验证的准确率均为100%。另取每种植物油脂各5个样品(共25个)进行验证,识别准确率为100%。对调和有棕榈油的花生油进行主成分分析,在主成分分析图上,调和油的分布点在花生油分布区域与棕榈油分布区域之间。     

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。     

应用激光拉曼光谱法检查核桃油的掺假

应用激光拉曼光谱法对掺入其它植物油(如大豆油、花生油、玉米油、棕榈油或棉籽油)的核桃油进行检测。从上述6种纯植物油的拉曼光谱图中取6个主峰的相对拉曼光谱强度为变量进行主成分分析,从所得的二维散点图可知核桃油与其它5种油均分处于图的不同区域;对掺杂不同比例(质量分数)其它油品的核桃油,在其散点图中也可见两者分处不同区域,据此可对掺杂其它油品的核桃油作出定性鉴别。利用波数为1 256cm-1处拉曼光谱相对强度与掺杂油品的含量(w%)之间的线性关系及其所建立的线性回归方程,对掺杂的样品进行了定量分析。在纯核桃油中分别掺入质量分数从8%~95%的棕榈油制备了10份试样,按上述方法进行定量分析,结果表明预测值与已知值的相对误差在1.01%~2.35%之间。     

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。     

近红外光谱技术用于花生油中棕榈油含量的测定

本文采用近红外光谱技术采集样品的近红外光谱数据,光谱经一阶求导后,采用偏最小二乘法(PLS)建立花生油中棕榈油含量的定标模型,并用交互验证法对模型进行了验证。模型相关系数为0.9963,校正均方根(RMSEC)为0.937。该模型应用于实际样品的检测,结果令人满意。     

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。     

近红外光谱法定性检测菜籽油中多效唑残留

采用近红外光谱技术结合化学计量学方法对菜籽油中多效唑残留进行定性检测。在4000~10000 cm-1光谱范围内采集126个菜籽油样本的近红外透射光谱。对原始光谱进行初步分析后,分别采用线性判别分析(LDA)、簇类独立软模式法(SIMCA)和最小二乘支持向量机(LSSVM)三种不同方法建立菜籽油中多效唑残留的定性检测模型,并对不同多效唑残留的菜籽油样本的分类正确率进行分析。研究结果表明,LDA,SIMCA及LSSVM 3种方法建立的检测模型均具有较高的判别能力,其校正集和预测集的正确率分别为93.33%,91.11%,95.56%和86.11%,88.89%,83.33%。此外,高多效唑残留样本的分类正确率大致趋于100%,而低多效唑残留样本的分类正确率则有一定波动。由此可知,利用近红外光谱技术可对菜籽油中多效唑残留进行快速、无损的定性检测。     

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。     

油脚料的深加工利用

油脚料的深加工利用杨冰（四川大学化学系，成都６１００６４）我国传统上的食用油脂多为植物油。诸如菜籽油，大豆油，花生油等的产量和耗量一直很大。单以菜籽油而言，每年的产量泄５００～６００万吨，其次是大豆油。无论过去还是现在，植物油厂都有数量可观的副产物出...     

一种有机硅改性植物油的制备及其性能表征

甲醇与菜籽油进行酯交换反应,其产物先通过过氧乙酸环氧化,再用乙酸开环制备出一种菜籽油醇,该醇与有机硅进行反应,从而制备出一种润滑性能优异的润滑油基础油。红外光谱对该化合物进行了表征。四球磨机对其润滑性能进行考察发现,该化合物的摩擦系数为0.063,磨斑直径为0.493mm,而菜籽油的摩擦系数为0.132,磨斑直径为1.763mm。此结果表明,该化合物的润滑性能较菜籽油有很大改进。     

Analysis of Peanut Oil Adulterated with Other Edible Oils by Spectrophotometry

Since peanut oil(PO) is more expensive than other seed oils, some PO is adulterated with other cheap seed oils, such as soybean oil, palm olein, cottonseed oil, corn oil and rapeseed oil. The conventional method for determining whether PO was adulterated is to detect the freezing point of oils. The proposed method for the determination of adulterants in PO was based on monitoring the change of absorbance when the sample was refrigerated. A special spectrophotometer was developed. A total of 10 kinds of POs from different suppliers were chosen and adulterated with other seed oils at the volume fraction levels ranging from 5% to 30%. A total of 150 samples were analyzed by the proposed method and the results were satisfactory.     

Simultaneous extraction of tocotrienols and tocopherols from cereals using pressurized liquid extraction prior to LC determination

Tocopherols and tocotrienols have been simultaneously determined in food samples using a rapid and simple analytical method including pressurized liquid extraction (PLE) and LC with electrochemical detection. Separation was carried out on a Phenomenex Synergi 4 μm Hydro‐RP 80A column, using a solution of 2.5 mM acetic acid/sodium acetate in methanol/water (99:1, v/v) as mobile phase at a flow rate of 1.0 mL/min. Column temperature was maintained at 30°C. Detection was performed by coulometric detection at 500 mV except for (β+γ)‐tocotrienol, in wheat and rye samples, which was at +350 mV. A palm oil containing a relatively large amount of γ‐tocotrienol and lower concentrations of α‐ and δ‐tocotrienols and α‐ and γ‐tocopherols was used to provide reference retention times for the tocotrienols. Analyte quantification was performed using the external standard method. The calibration equations of tocopherols were used to quantify both tocopherols and their corresponding tocotrienols. The extraction recoveries obtained using the optimized PLE conditions were in the 80–114% range, with RSDs lower than 15%. The method was successfully applied to the determination of tocotrienols and tocopherols in cereal (wheat, rye, barley, maize and oat) and palm oil samples.     

Characterization of Peanut Oil by Infrared Spectroscopy with an Improved Gaussian Mixture Model

The Gaussian mixture model (GMM) and regression (GMR) are widely used statistical tools in pattern classification and nonlinear regression. In this paper, the suitability score was used for variable selection to improve GMM and GMR. The improved GMM was used to characterize peanut oil adulterated with palm oil using Fourier transform infrared spectroscopy. The improved GMR was applied to determine the concentration of palm oil contaminant present. As comparison, GMM and GMR with principal component analysis for feature extraction, support vector machine, back-propagation artificial neural network, nearest centroid classification, and partial least-squares analysis were also used to classify and quantify peanut oil. It was demonstrated that the method is a new classification and regression strategy for the detection of adulterated edible oil.     

共轴双脉冲激光诱导击穿光谱和最小二乘支持向量机法定量分析植物油中铬

利用共轴双脉冲激光诱导击穿光谱( DP-LIBS)技术对植物油(大豆油、花生油和玉米油)中的重金属铬( Cr)含量进行定量分析。采用Ava-Spec双通道高精度光谱仪采集样品的LIBS光谱,然后通过其LIBS谱线图确定了CN分子谱线(421.49 nm)、Ca原子谱线(422.64 nm)及Cr的3条原子谱线(425.39、427.43和428.87 nm),根据上述谱线建立了Cr元素的单变量定标模型和最小二乘支持向量机(LS-SVM)校正模型,并用验证样品对它们进行检验。研究结果表明,对于单变量定标法,大豆油、花生油及玉米油验证样品的平均预测相对误差(PRE)分别为12.57%,12.11%和13.72%;对于三变量LS-SVM法,其定标样品真实值与预测值之间的拟合度 R2分别为0.9785,0.9792和0.9654,验证样品的平均 PRE 分别为8.92%,8.33%和10.98%;对于五变量LS-SVM法(增加两基体元素谱线变量),其定标样品真实值与预测值之间的拟合度R2分别为0.9895,0.9901和0.9855,验证样品的平均PRE分别为7.46%,8.96%和8.95%。由此可知,LS-SVM校正模型性能优于单变量定标法,且五变量LS-SVM校正模型性能优于三变量LS-SVM校正模型;采用LS-SVM法及引入合适的基体元素谱线( CN、Ca)能有效减小定量分析误差,提高LIBS技术对植物油中Cr含量预测的精度。     

Determination of Organophosphorus Pesticides in Soybean Oil, Peanut Oil and Sesame Oil by Low-Temperature Extraction and GC-FPD

A low-temperature clean-up method for residue determination was developed and validated for 14 organophosphorus pesticides in soybean oil, peanut oil and sesame oil by gas chromatography with flame photometric detector (GC-FPD). A different matrix influenced the response and retention time of pesticides. Hence matrix-matched calibration standards were used to counteract the matrix effect. The pesticide responses in blank samples of soybean oil, peanut oil and sesame oil were within the linear range of 0.02–1 mg kg⁻¹ and the correlation coefficients were higher than 0.9989. Average recoveries obtained from different oil samples at three fortified levels were higher than 50% with relative standard deviations (RSDs) of less than 15%. The limit of detections (LODs) of studied pesticides ranged from 2 to 5 μg kg⁻¹. Thirty-nine commercial samples were analyzed, and the results were confirmed by gas chromatography–mass spectrometry (GC–MS) in selective ion monitoring (SIM) mode.     

Analysis of free fatty acids by a micro-liquid chromatograph directly coupled with a mass spectrometer through a vacuum nebulizing interface

A liquid chromatograph directly coupled with a quadrupole mass spectrometer through a vacuum nebulizing interface was applied to the analysis of various free fatty acids. Chemical ionization mass spectra of the C₇? C₂₂ free fatty acids were first examined using either methanol or benzene as the reagents. Then the practical compositional analysis of the fatty acids were performed with various biological samples such as bean oil, rape oil, palm oil and milk fat where most of the fatty acids are included as their triglycerides.     

Effect of ingredients on the mass loss,pasting properties and thermal profile of semi-sweet biscuit dough

The drive to utilise different lipids, both for health benefits and for commercial reasons, in bakery goods has been extensive. However, the roles of the lipid plays in many products, let alone the influence of the level of saturation, are uncertain. The objective of work carried out is to understand how the typical ingredients in biscuit would impact on the thermal profile of semi-sweet biscuit dough. Three different techniques have been used namely gravimetric analysis (TGA), rapid visco analyser and differential scanning calorimetry (DSC). Wheat flour, sugar and fat/oil were the main ingredients used to produce basic dough of semi-sweet biscuit for this study. Semi-sweet biscuit dough formulations with varying types of oils namely palm oil, palm olein, palm stearine, sunflower oil and butterfat were developed. The final mass (i.e. the total amount of moisture lost) for the samples showed significant differences between the doughs; with the control dough, dough contained palm stearine and butter falling into one group and the butter, palm oil, palm olein and sunflower oil forming the second group that showed less mass loss. Doughs containing low levels of saturated fatty acids (palm olein, palm oil and sunflower oil) showed significant difference on the drying properties of samples compared to doughs containing high saturated fatty acids (palm stearine and butter) as revealed by TGA. Pasting properties result showed that oil with different saturation influenced peak viscosity obtained. The DSC results showed that sugar and oil increased the gelatinisation peak temperature up to 2 and 6 °C, respectively. Oils with low saturated fatty acids have more capability to make contact with starch granules during the mixing processing as compared to oil with a high level of saturated fat. It is suggested that the oil presence in the system was delaying the drying process by coating the wheat flour particles hence slowing the drying process as compared to a sample without oil.     

Ultrasound-assisted treatment of palm oil samples for the determination of copper and lead by stripping chronopotentiometry

The concentration of trace metals in vegetable oils is an important criterion for the assessment of oil qualities with regard to freshness, keeping properties, storage and their influence on human nutrition and health. In this work, an effective and simple method for the determination of copper and lead in palm oil by stripping chronopotentiometry (SCP) is proposed. The metal ions were concentrated as their amalgams on the glassy carbon surface of a working electrode that was coated with a thin mercury film. An ultrasonic bath was used for the extraction of copper and lead from eleven oil samples using a 1:1 (v/v) mixture of concentrated hydrochloric acid and hydrogen peroxide. Efficient extraction of copper and lead (∼ 100%) was attained after 60 min of ultrasonic pre-treatment. A good correlation between the amount of sample and the time necessary for complete liberation of the metals was observed. The accuracy of the method was evaluated by means of a reference sample of skim milk powder containing trace elements (BCR 151). Quantitative analysis was carried out by the method of standard additions. Good linearity was obtained in the range of the concentrations examined. Detection limits of 13 and 50 ng g^− 1 were found for Cu and Pb, respectively, in the palm oil samples. The average values found for the palm oil samples analyzed were in the range of < 0.013-2.67 µg g^− 1 for copper and < 0.050-1.82 µg g^− 1 for lead. The palm oil samples were also analyzed by graphite furnace atomic absorption spectrometry (GFAAS), demonstrating a very good correlation between the results.