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.     

Use of diffusion‐ordered NMR spectroscopy and HPLC–UV–SPE–NMR to identify undeclared synthetic drugs in medicines illegally sold as phytotherapies

The informal (and/or illegal) e‐commerce of pharmaceutical formulations causes problems that governmental health agencies find hard to control, one of which concerns formulas sold as natural products. The purpose of this work was to explore the advantages and limitations of DOSY and HPLC–UV–SPE–NMR. These techniques were used to identify the components of a formula illegally marketed in Brazil as an herbal medicine possessing anti‐inflammatory and analgesic properties. DOSY was able to detect the major components present at higher concentrations. Complete characterization was achieved using HPLC–UV–SPE–NMR, and 1D and 2D NMR analyses enabled the identification of known synthetic drugs. These were ranitidine and a mixture of orphenadrine citrate, piroxicam, and dexamethasone, which are co‐formulated in a remedy called Rheumazim that is used to relieve severe pain, but it is prohibited in Brazil because of a lack of sufficient pharmacokinetic and pharmacodynamic information. Copyright © 2013 John Wiley & Sons, Ltd.     

Characterization of Gasoline by 1H Nuclear Magnetic Resonance and Chemometrics

Automotive fuel adulteration is an old and significant problem. One common type of fuel adulteration is the addition of diesel to gasoline. Unsupervised models were developed through hierarchical cluster and principal component analysis models. Supervised models through partial least square discriminant analysis using ¹H nuclear magnetic resonance spectra as the input were used to classify samples as adulterated or unadulterated. Quantitative models were developed using partial least squares to determine the gasoline and diesel concentrations in the samples. This set contained samples composed of pure gasoline and anhydrous ethanol reproducing commercial gasoline and other samples treated with diesel. Hierarchical cluster and principal component analysis did not distinguish between adulterated and unadulterated samples except for the most adulterated materials. However, partial least square discriminant analysis classified 100% of the samples correctly. The partial least square algorithm provided excellent regression models for the gasoline and diesel content. The determination coefficient was 0.9920 for both models, whereas the root mean square error of cross-validation and root mean square error of prediction for the diesel model were 2.32 and 1.42%, respectively, and 2.40 and 1.38% for the gasoline model.     

Detection and analysis of paraffin oil adulteration in coconut oil using fiber optic long period grating sensor

A fiber optic sensing system for the detection of adulteration of coconut oil by paraffin oil is experimentally demonstrated. The sensing mechanism is based on the sensitive dependence of the resonance peaks of a long period grating (LPG) on the changes of the refractive index of the environmental medium surrounding the cladding surface of the grating. The wavelength shift of the attenuation bands of the LPG was measured with the sensor immersed in a mixture of paraffin oil and pure coconut oil in different proportions. Detection limit of adulteration was found to be 3% for coconut oil-paraffin oil binary mixture.     

超高效液相色谱-三重四极杆质谱法测定食品中34种非法添加减肥类化合物

建立了超高效液相色谱-三重四极杆质谱测定食品(含保健食品)中34种减肥类非法添加化合物的方法。采用Waters CORTECS T3色谱柱(100 mm×2.1 mm,2.7μm),以0.1%(v/v)甲酸水溶液-含0.1%(v/v)甲酸的乙腈溶液为流动相,梯度洗脱,在电喷雾离子源、正离子或负离子模式下以多反应监测(MRM)方式检测。西布曲明等29种化合物在0.5~10μg/L范围内、氯噻嗪等5种化合物在2.5~50μg/L范围内均呈良好的线性关系,相关系数(r)均大于0.99;西布曲明等29种化合物在5、10和20μg/kg添加水平下的平均加标回收率为49.2%~136.2%,相对标准偏差(RSD)为0.7%~15.0%(n=6),氯噻嗪等5种化合物在25、50和100μg/kg添加水平下的平均加标回收率为51.5%~130.9%,RSD为0.8%~14.0%(n=6);西布曲明等29种化合物的检出限为5μg/kg,定量限为10μg/kg,氯噻嗪等5种化合物的检出限为25μg/kg,定量限为50μg/kg。本方法已应用于实际样品的测定,共检出了12种化合物,有效打击了非法添加行为。     

1H NMR and UV-visible data fusion for determining Sudan dyes in culinary spices

Two data fusion strategies (variable and decision level) combined with a multivariate classification approach (Partial Least Squares-Discriminant Analysis, PLS-DA) have been applied to get benefits from the synergistic effect of the information obtained from two spectroscopic techniques: UV-visible and ¹H NMR. Variable level data fusion consists of merging the spectra obtained from each spectroscopic technique in what is called “meta-spectrum” and then applying the classification technique. Decision level data fusion combines the results of individually applying the classification technique in each spectroscopic technique. Among the possible ways of combinations, we have used the fuzzy aggregation connective operators. This procedure has been applied to determine banned dyes (Sudan III and IV) in culinary spices. The results show that data fusion is an effective strategy since the classification results are better than the individual ones: between 80 and 100% for the individual techniques and between 97 and 100% with the two fusion strategies.     

Orbitrap高分辨质谱法高通量筛查生化药品、中成药与保健品中非法添加的13种消化类化学药物

建立了生化药品、中成药和保健品中非法添加的13种消化类化学药的超高效液相色谱-Orbitrap高分辨质谱(UHPLC-HRMS)高通量筛查方法。供试品以甲醇-水(50∶50)为提取溶剂,经Hypersil Gold C18(2.1 mm×100 mm,3μm)色谱柱分离,以乙腈-0.1%甲酸水为流动相进行梯度洗脱,单次分析仅需10min。采用正离子检测,Full MS/dd-MS2扫描模式。通过比较供试品与对照品的色谱保留时间、高分辨一级和二级质谱,判断供试品中是否非法添加消化类药物,并对阳性样品进行定量分析。13种化合物的线性范围均为8.0~800μg/L,相关系数(r)均不低于0.998 5,回收率为94.6%~106.2%,相对标准偏差为1.2%~2.9%。该法快速简便、通量高、选择性好、灵敏度高,并已用于生化药品、中成药及保健品非法添加消化类化学药的高通量筛查和测定,在38批中成药中发现5批阳性样品,在43批保健品中发现3批阳性样品。     

基于多特征算法选择的太赫兹时域光谱用于水稻种子掺假研究

该文提出了一种基于太赫兹时域光谱的水稻种子模式识别方法。实验以10种不同品牌混合掺假的水稻种子为样本,基于采集的样本太赫兹时域光谱数据,通过建立Relief、随机森林（RF）、支持向量机递归特征消除（SVM-RFE）和最大相关最小冗余（mRMR）模型分别对样本光谱波长进行特征选择,最后设计分类器对4种特征选择方法处理后的样本进行分类识别。结果表明,基于布谷鸟算法（CS）优化的极限学习机模型对经RF特征选择算法提取后的样本光谱数据具有最佳识别效果,其准确率可达100%,实验对于法庭科学领域内种子的掺假鉴定具有一定的借鉴意义。     

基于液相色谱-串联质谱法的肉类特征肽段鉴别及掺假测定

建立了液相色谱-串联质谱技术鉴别肉类特征肽段及定量检测羊肉中常见外源肉掺假的方法。样品经蛋白质提取、胰蛋白酶水解和固相萃取小柱净化后,利用超高效液相色谱-四极杆/静电场轨道阱高分辨质谱（UPLC-Q/Exactive-HRMS）和Proteinpilot软件,实现蛋白质和多肽的鉴定;再通过基本局部比对搜索工具（BLAST）与Uniprot数据库对比分析,筛选出羊肉、鸭肉、猪肉和鸡肉的20个物种特征性多肽标志物;最后利用高效液相色谱-三重四极杆质谱（UPLC-QqQ-MS）系统对羊肉、鸭肉、猪肉和鸡肉的特征性多肽进行了验证和多反应监测（MRM）定量研究。将鸭肉、猪肉和鸡肉分别按照质量分数为1%、5%、10%、20%、50%的比例掺加到羊肉中,得到鸭肉最低掺假检出限为0.25%、猪肉最低掺假检出限为0.17%、鸡肉最低掺假检出限为0.10%。     

超高效液相色谱-四极杆-飞行时间质谱法定性筛查保健食品中西地那非及其相关功效类非法添加化合物

建立了超高效液相色谱-四极杆-飞行时间质谱（UPLC-Q-TOF-MS）定性筛查102种西地那非及其相关功效化合物的方法。甲醇超声提取样品;采用Agilent Poroshell 120 SB-C18色谱柱（75 mm×3.0 mm,2.7 μm）,以0.1%（v/v）甲酸水溶液-乙腈为流动相梯度洗脱,流速0.4 mL/min;采用电喷雾离子（ESI）源,Q-TOF-MS作检测器,正离子模式检测;与对照品保留时间、母离子及碎片离子精确相对分子质量、元素组成比对,准确定性。西地那非等100种化合物在10种基质中的检出限为0.1~50 mg/kg或0.1~50 mg/L。并分类归纳了文中涉及的98种磷酸二酯酶5抑制剂质谱碎片裂解规律,为可疑物的识别和鉴定提供参考。该方法已应用于实际样品的测定,检出19种化合物,有效打击了非法添加行为。