Comparison of mass spectrometry-based electronic nose and solid phase microextraction gas chromatography-mass spectrometry technique to assess infant formula oxidation

Two headspace techniques based on mass spectrometry detection (MS), electronic nose, and solid phase microextraction coupled to gas chromatography-mass spectrometry (SPME-GC/MS) were evaluated for their ability to differentiate various infant formula powders based on changes of their volatiles upon storage. The electronic nose gave unresolved MS fingerprints of the samples gas phases that were further submitted to principal component analysis (PCA). Such direct MS recording combined to multivariate treatment enabled a rapid differentiation of the infant formulas over a 4 week storage test. Although MS-based electronic nose advantages are its easy-to-use aspect and its meaningful data interpretation obtained with a high throughput (100 samples per 24 h), its greatest disadvantage is that the present compounds could not be identified and quantified. For these reasons, a SPME-GC/MS measurement was also investigated. This technique allowed the identification of saturated aldehydes as the main volatiles present in the headspace of infant milk powders. An isotope dilution assay was further developed to quantitate hexanal as a potential indicator of infant milk powder oxidation. Thus, hexanal content was found to vary from roughly 500 and 3500 microg/kg for relatively non-oxidized and oxidized infant formulas, respectively.     

Prediction of Penicillium expansum spoilage and patulin concentration in apples used for apple juice production by electronic nose analysis

Classification models for Penicillium expansum spoilage of apples and prediction models for patulin concentration in apples usable for apple juice production were made on the basis of electronic nose (e-nose) analysis correlated to HPLC quantification of patulin. A total of 15 Golden Delicious and 4 Jonagold apples were surface sterilized and divided into three groups per variety. The Golden Delicious group consisted of five apples each. Group 1 was untreated control, group 2 was surface inoculated with P. expansum, and group 3 was inoculated in the core with P. expansum. The apples were incubated at 25 degrees C for 10 days. E-nose analysis was performed daily. At day 10 the Golden Delicious apples were individually processed for apple juice production. During apple juice production the mash and juice were analyzed by e-nose, and samples were taken for patulin analysis by HPLC. The volatile metabolite profile was obtained by collection of volatile metabolites, on tubes containing Tenax TA, overnight between the 9th and 10th days of incubation and subsequent analysis of the collected compounds by GC-MS. Prediction models using partial least-squares, with high correlation, for prediction of patulin concentration in shredded apples as well as apple juice were successfully created. It was also shown that it is possible to classify P. expansum spoilage in apples correctly on the basis of soft independent modeling of class analogy classification of e-nose analysis data. To the authors' knowledge this is the first report of a regression model between e-nose data and mycotoxin content in which actual concentrations are reported. This implies that it is possible to predict mycotoxin production and concentration by e-nose analysis.     

基于DFI-RSE电子鼻传感器阵列优化的葡萄酒SO2检测

酿造过程中SO2的监控是葡萄酒产业信息化和葡萄酒品质保障的关键。针对传统SO2测定方法操作复杂、耗费时间长等问题,该研究提出基于电子鼻技术建立葡萄酒中SO2检测方法。为提高电子鼻检测性能,提出一种基于动态特征重要度-递归传感器消除（Dynamic Feature Importance-Recursive Sensor Elimination,DFI-RSE）的气体传感器阵列优化算法。将最大信息系数（Maximum Information Coefficient,MIC）作为度量变量间关系的标准,定义DFI选择兼顾高有效性与低冗余性的特征构成特征子集。进一步计算特征子集中的传感器重要度,结合RSE移除重要度较低的传感器,获得最优阵列组合。采用偏最小二乘回归（Partial Least Squares Regression,PLSR）、多层感知器（Multi-Layer Perceptron,MLP）、支持向量回归（Support Vector Regression,SVR）和贝叶斯岭回归（Bayesian Ridge Regression,BRR）对DFI-RSE优化前后阵列的检测能力进行比较。结果表明,针对间隔40 mg/L、0～200 mg/L范围内不同SO2添加量的葡萄酒样品,优化后阵列的传感器数量由原来的16个降低为8个,特征数量减少了59%,4种回归模型的决定系数均高于0.98,其中MLP模型检测效果最佳,均方根误差为7.73 mg/L,优于原始阵列且节省了运行时间。所建立的基于电子鼻的葡萄酒SO2添加量检测和相应的阵列构建与优化方法为葡萄酒酿造过程中SO2的有效监控技术研究提供参考。     

Immunochemical and mass spectrometry detection of residual proteins in gluten fined red wine

Recently, wheat gluten has been proposed as technological adjuvant in order to clarify wines. However, the possibility that residual gluten proteins remain in treated wines cannot be excluded, representing a hazard for wheat allergic or celiac disease patients. In this work, commercial wheat glutens, in both partially hydrolyzed (GBS-P51) and nonhydrolyzed (Gluvital 21000) forms, were used as fining agents in red wine at different concentrations. Beside immunoenzymatic analyses using anti-gliadin, anti-prolamin antibodies and pooled sera of wheat allergic patients, a method based on liquid chromatography coupled to mass spectrometry has been proposed to detect residues of gluten proteins. Residual gluten proteins were detected by anti-prolamin antibodies, anti-gliadin antibodies and sera-IgE only in the wine treated with GBS-P51 at concentration 50, 150, and 300 g/hL, respectively, whereas no residual proteins were detected by these systems in the wine treated with Gluvital 21000. In contrast liquid chromatography-mass spectrometry analyses allowed the detection of proteins in red wines fined down to 1 g/hL of Gluvital 21000 and GBS-P51. Our results indicate that MS methods are superior to immunochemical methods in detecting gluten proteins in wines and that adverse reactions against gluten treated wines cannot be excluded.     

Screening for potential pigments derived from anthocyanins in red wine using nanoelectrospray tandem mass spectrometry

Red wine extracts were screened for potential wine pigments derived from anthocyanins, using a combination of nanoelectrospray tandem mass spectrometry techniques. Fourteen aglycons were considered to be of anthocyanidin origin on the basis of their MS/MS spectra. The proposed structures of the aglycons were anthocyanidin C-4 substituted with vinyl linkage between C-4 and the hydroxy group at C-5. The anthocyanidin derivatives identified in the wine extracts were vinyl, vinylmethyl, vinylformic acid, 4-vinylphenol, 4-vinylguaiacol, and vinylcatechin adducts of malvidin as well as vinylformic acid and 4-vinylphenol adducts of peonidin and petunidin. The presence of vinyl alcohol, 4-vinylcatechol, and 4-vinylsyringol adducts of malvidin was also proposed.     

Ground red peppers: capsaicinoids content,Scoville scores,and discrimination by an electronic nose

High-pressure liquid chromatography (HPLC) was used to determine the capsaicin, dihydrocapsaicin, and total capsaicinoids levels of different ground red pepper samples obtained from local retail markets in Izmir, Turkey. Scoville scores were determined using sensory tests. An electronic nose (EN) was used to discriminate ground red pepper samples by headspace volatiles. EN data were analyzed using discriminant function analysis (DFA). An overall correct classification rate of pepper varieties by EN of 91% was obtained. A linear correlation between capsaicin, dihydrocapsaicin, and total capsaicinoids and Scoville scores was also observed, and R (2) values of 0.89, 0.85, and 0.91 were obtained, respectively.     

电子鼻与电子舌在食品检测中的应用研究进展

随着嗅觉与味觉传感器技术的发展，电子鼻与电子舌技术在食品检测中得到了不断研究与应用。电子鼻由气敏传感器、信号处理和模式识别系统等功能器件组成。电子舌是用类脂膜作为味觉传感器，以类似人的味觉感受方式检测味觉物质。着重阐述了电子鼻与电子舌技术的结构组成，重点介绍了其在食品新鲜度检测、果蔬成熟度评价及饮料、酒类识别等轻工业中的应用现状与发展趋势，并指出了这些信息新技术实现过程中所需要解决的问题。     

基于电子鼻的鱼粉中挥发性盐基氮检测模型比较

挥发性盐基氮（TVB-N）是表征鱼粉新鲜度的主要指标之一,为了探讨基于电子鼻系统检测鱼粉新鲜度的可行性,研制了检测鱼粉中TVB-N质量分数的电子鼻测量系统。该系统主要由氧化锡气敏传感器阵列、便携式数据采集设备和基于LabVIEW的采集程序组成。利用该系统对不同TVB-N质量分数的鱼粉样本进行气味信号采集,同时对鱼粉样本中的TVB-N的质量分数采用半微量凯式定氮法进行检测,利用2σ准则对传感器响应值进行数据剔除处理,建立了鱼粉中TVB-N质量分数的主成分分析（PCA）、多元线性回归（MLR）、BP神经网络模型,并用预测样本对模型进行验证。试验结果为：3种模型TVB-N质量分数预测值与实测值之间的决定系数R2、预测标准误差SEP、最大相对误差RE-max及平均相对误差RE-mean分别为0.48、10.25、13.62%、6.06%;0.59、9.14、13.91%、5.57%;0.94、3.64、6.30%、1.88%。BP神经网络效果最好,多元线性回归次之,主成分分析最差。研究结果表明,利用电子鼻技术可以有效对鱼粉中TVB-N质量分数进行检测。     

SPME-MS-MVA as an electronic nose for the study of off-flavors in milk

A new technique using solid-phase microextraction, mass spectrometry, and multivariate analysis (SPME-MS-MVA) was developed for the study of off-flavors in milk. The analytical column of a GC/MS system was replaced with a 1-m deactivated fused-silica column, which served as a transfer line to deliver volatiles extracted from milk samples with a Carboxen-SPME fiber to the mass spectrometer. Mass fragmentation data resulting from the unresolved milk volatile components were subjected to MVA. Principal component analysis based on SPME-MS-MVA provided rapid differentiation of control reduced-fat milk (2% butterfat content) samples from reduced-fat milk samples abused by light, heat, copper, and microbial contamination. The three psychrotrophic bacteria studied included Pseudomonas fluorescens, Pseudomonas aureofaciens, and Pseudomonas putrefaciens. SPME-MS-MVA is rapid and offers significant advantages over commercial electronic nose instruments currently being used as quality assurance tools to differentiate normal-tasting food and beverage samples from those containing off-flavors and malodors.     

Rapid method for the discrimination of red wine cultivars based on mid-infrared spectroscopy of phenolic wine extracts

Mid-infrared spectroscopy and UV-vis spectroscopy combined with multivariate data analysis have been applied for the discrimination of Austrian red wines, including the cultivars Cabernet Sauvignon, Merlot, Pinot Noir, Blaufr?nkisch (Lemberger), St. Laurent, and Zweigelt. Both authentic wines and their phenolic extracts were investigated by attenuated total reflectance (ATR)-mid-infrared spectroscopy. Phenolic extracts were also investigated by UV-vis spectroscopy. The wine extracts were obtained by solid-phase extraction with C-18 columns and elution by methanol containing 0.01% hydrochloric acid. Hierarchical cluster analysis was performed with mid-infrared spectra of both wines and extracts, as well as with UV-vis spectra of the phenolic extracts. Data processing involved vector normalization and derivation of the spectra. Due to varying concentrations of main components including sugar and organic acids, satisfactory classification of untreated wines was not achieved. However, when using mid-infrared spectra of the phenolic extracts, almost complete discrimination of all cultivars investigated was achieved. The use of UV-vis spectroscopy for cultivar discrimination was found to be limited to the authentication of the Burgundy species Pinot Noir. In addition, soft independent modeling of class analogy was applied to the mid-infrared spectra of the extracts. It was possible to establish class models for five different wine cultivars and to classify test samples correctly.     

Early detection of fungal growth in bakery products by use of an electronic nose based on mass spectrometry

This paper presents the design, optimization, and evaluation of a mass spectrometry-based electronic nose (MS e-nose) for early detection of unwanted fungal growth in bakery products. Seven fungal species (Aspergillus flavus, Aspergillus niger, Eurotium amstelodami, Eurotium herbariorum, Eurotium rubrum, Eurotium repens, and Penicillium corylophillum) were isolated from bakery products and used for the study. Two sampling headspace techniques were tested: static headspace (SH) and solid-phase microextraction (SPME). Cross-validated models based on principal component analysis (PCA), coupled to discriminant function analysis (DFA) and fuzzy ARTMAP, were used as data treatment. When attempting to discriminate between inoculated and blank control vials or between genera or species of in vitro growing cultures, sampling based on SPME showed better results than those based on static headspace. The SPME-MS-based e-nose was able to predict fungal growth with 88% success after 24 h of inoculation and 98% success after 48 h when changes were monitored in the headspace of fungal cultures growing on bakery product analogues. Prediction of the right fungal genus reached 78% and 88% after 24 and 96 h, respectively.     

Effect of caffeic acid on the color of red wine

The copigmentation effect of prefermentation additions of different doses of caffeic acid was investigated during the 1997 harvest. Microfermentation with the major red grape cultivars Listán negro and Negramoll, grown in the Canary Islands, was carried out with the same protocol. Visible and UV spectra were registered periodically. HPLC chromatograms were carried out. The color enhancement of cv. Negramoll wine varied between 13 and 75% (AU at 520 nm), and that of cv. Listán negro wine between 25 and 45% at the end of fermentation. During aging these values were enhanced to reach even >100% in some cases. An initial complex of the 1:1 type, where one molecule of caffeic acid associates with one molecule of anthocyanin, has been identified using the mathematical procedure of Brouillard et al. (J. Am. Chem. Soc. 1989, 111, 2604-2610). Caffeic acid seems to contribute to color stability and protection against oxidation. The importance of nonpigment composition in pigment extraction and color retention during and after fermentation is demonstrated.     

Quantitative reconstruction of the nonvolatile sensometabolome of a red wine

The first comprehensive quantitative determination of 82 putative taste-active metabolites and mineral salts, the ranking of these compounds in their sensory impact based on dose-over-threshold (DoT) factors, followed by the confirmation of their sensory relevance by taste reconstruction and omission experiments enabled the decoding of the nonvolatile sensometabolome of a red wine. For the first time, the bitterness of the red wine could be demonstrated to be induced by subthreshold concentrations of phenolic acid ethyl esters and flavan-3-ols. Whereas the velvety astringent onset was imparted by three flavon-3-ol glucosides and dihydroflavon-3-ol rhamnosides, the puckering astringent offset was caused by a polymeric fraction exhibiting molecular masses above >5 kDa and was found to be amplified by the organic acids. The perceived sourness was imparted by l-tartaric acid, d-galacturonic acid, acetic acid, succinic acid, l-malic acid, and l-lactic acid and was slightly suppressed by the chlorides of potassium, magnesium, and ammonium, respectively. In addition, d-fructose and glycerol as well as subthreshold concentrations of glucose, 1,2-propandiol, and myo-inositol were found to be responsible for the sweetness, whereas the mouthfulness and body of the red wine were induced only by glycerol, 1,2-propandiol, and myo-inositol.     

典型掺假蜂蜜的电子鼻信息变化特征及判别能力

为建立蜂蜜掺假快速检测方法,该文利用电子鼻并结合主成分分析（principal component analysis,PCA）数据处理方法研究了掺入10%、20%、30%、40%、50%、60%、70%油菜蜜和大米糖浆的掺假蜂蜜的电子鼻信息变化特征,并以掺假蜂蜜的电子鼻信息变化特征为指导,结合判别因子分析（linear discriminant analysis,LDA）模式识别算法研究了电子鼻对掺假蜂蜜的定性识别分析能力。结果表明,掺假蜂蜜的电子鼻信息呈现线性变化,并且电子鼻对掺假蜂蜜有较强的敏感力。LDA模式识别算法可以将纯蜂蜜样品与掺假蜂蜜样品很好的区分开,LDA掺假判别模型正确识别率为94.7%,该技术可以为蜂蜜掺假鉴别提供技术支撑。     

用于山核桃陈化时间检测的电子鼻传感器阵列优化

为更好地进行山核桃陈化时间检测,论文拟通过传感器阵列优化来有效提高电子鼻对其区分预测能力。该文依据响应曲线保留响应明显的传感器,并在提取传感器特征值构成初始特征矩阵的基础上,结合均值分析、变异系数分析、聚类分析、相关性分析和多重共线性分析进行逐步优化以获取最终优化传感器阵列。对优化前后的数据采用主成分分析法(principal component analysis,PCA)和偏最小二乘回归(partial least squares regression,PLSR)进行样品区分和预测能力的对比。结果表明:通过优化,经不同人工陈化时间(0、5、10、15d)处理的山核桃能有效区分开,且在PCA得分图中更为聚集;优化后的陈化时间回归模型(R2=0.933 4)较优化前(R2=0.888 7)具有更好的预测能力。说明所给出的阵列优化方法有效可行,为电子鼻针对性检测提供了一种思路。     

Direct method for determining seed and skin proanthocyanidin extraction into red wine

A method was developed for determining the amount of seed and skin proanthocyanidin extraction into wines by direct measurement. This method was based upon the analysis of proanthocyanidin cleavage products after acid catalysis in the presence of excess phloroglucinol. On the basis of the analysis of proanthocyanidin extracts from grape tissues, two observations were made as follows: (i) the seed and skin proanthocyanidin extension subunit compositions were considerably different from each other, and (ii) their composition did not vary with extraction time. Thus, by comparing the proportional extension subunit composition of proanthocyanidins in wine relative to their proportional composition in corresponding grape seed and skin, it was possible to determine the contribution of each to wine. To provide additional information, the procedure was used to investigate seed and skin proanthocyanidin extraction during commercial-scale fermentations that had undergone 4 or 10 day low temperature prefermentation skin contact prior to the onset of fermentation. The results for both fermentations indicated that the proportion of skin tannin declined during fermentation and also showed that at the end of fermentation the amount and proportion of skin tannin were the same.     

Identification and characterization of complex bioactive oligosaccharides in white and red wine by a combination of mass spectrometry and gas chromatography

Over forty-five complex free oligosaccharides (of which several are novel) have been isolated and chemically characterized by gas chromatography and high resolution and high mass accuracy matrix-assisted laser desorption/ionization mass spectrometry (MALDI-FTICR MS) in red and white wines, Grignolino and Chardonnay, respectively. Oligosaccharides with a degree of polymerization between 3 and 14 were separated from simple monosaccharides and disaccharides by solid-phase extraction. The concentrations of free oligosaccharides were over 100 mg/L in both red and white wines. The free oligosaccharides-characterized for the first time in the present study-include hexose-oligosaccharides, xyloglucans, and arabinogalactans and may be the natural byproduct of the degradation of cell wall polysaccharides. The coupled gas chromatography and accurate mass spectrometry approach revealed an effective method to characterize and quantify complex functional oligosaccharides in both red and white wine.     

电子鼻在牦牛肉和牛肉猪肉识别中的应用

为了探索电子鼻对肉类掺假识别的可行性,利用电子鼻对牦牛肉、牛肉和猪肉样品进行了分析。通过对所获得的数据进行主成分分析（principal component analysis,PCA）、判别因子分析（discriminant factor analysis,DFA）和偏最小二乘回归分析（partial least-squares analysis,PLS）。结果表明：几种肉类在电子鼻传感器上有不同的特征性响应图谱,电子鼻能够有效识别猪、牛肉;同时电子鼻能够识别不同部位的牦牛肉和普通牛肉;但不能识别不同部位的猪肉。在牛肉馅中掺入不同比例的猪肉馅时,电子鼻也能进行识别。采用偏最小二乘回归分析对数据进行处理,电子鼻响应信号和猪肉馅掺入比例之间有很好的相关性（决定系数R2为0.9762）,PLS模型预测误差在1.27%～7.00%之间。试验证明电子鼻可用于肉类的识别。     

Quantitative colorimetric assay for total protein applied to the red wine Pinot noir

A standard method for assaying protein in red wine is currently lacking. The method described here is based on protein precipitation followed by dye binding quantification. Improvements over existing approaches include minimal sample processing prior to protein precipitation with cold trichloroacetic acid/acetone and quantification based on absorbance relative to a commercially available standard representative of proteins likely to be found in wine, the yeast mannoprotein invertase. The precipitation method shortened preparation time relative to currently published methods and the mannoprotein standard yielded values comparable to those obtained by micro-Kjeldahl analysis. The assay was used to measure protein in 48 Pinot noir wines from 6 to 32 years old. The protein content of these wines was found to range from 50 to 102 mg/L with a mean value of 70 mg/L. The availability of a simple and relatively rapid procedure for assaying protein provides a practical tool to quantify a wine component that has been overlooked in routine analyses of red wines.     

基于多种变量分析方法鉴别食醋种类电子鼻信号特征筛选

为了提高6种食醋的电子鼻鉴别能力,该文提出了一种基于多变量分析的食醋电子鼻信号多特征表征策略。初选不同的特征表征电子鼻信号,构建电子鼻信号的初始特征矩阵。采取载荷分析进行电子鼻传感器阵列优化,优选了12个气敏传感器的响应数据进行后续分析。为消除各传感器响应信号之间的相关性,对优选阵列的特征矩阵进行主成分分析(principal component analysis,PCA),并利用WilksΛ统计量选择鉴别能力最优的主成分子阵。在选择最优主成分子阵的基础上,以生成主成分的每一个原始特征变量为对象,计算每一个原始特征变量在主成分子阵中的贡献系数绝对值之和,且根据系数绝对值之和从大到小排序;同时,根据不同和值的指定,形成了不同容量的原始特征变量集。最后,借助于Fisher判别分析(Fisher discriminant analysis,FDA)探索了不同容量原始特征变量集的鉴别结果,确定了最佳的原始特征变量集。结果表明,特征选择前后传感器信号的表征特征发生了明显变化,最终采用48个特征参量实现了对食醋电子鼻信号的有效表征。在48个特征参量表征条件下,同时运用FDA和BP神经网络(back propagation neural network,BPNN)对6种食醋进行了鉴别分析,训练集的鉴别正确率分别在93%和98%以上,测试集的鉴别正确率也分别达到了90%和93%以上。另外,利用巴氏距离进一步揭示了样品间的可分离程度及FDA与BPNN结果的可信性。研究结果可为电子鼻信号多特征表征提供了一种新思路。