应用电子鼻和GC-MS比较牛肉不同部位的挥发性物质组成

实验的目的是探讨不同部位牛肉对不同加热温度的气味影响。实验运用电子鼻对60、120℃加热后不同部位的牛肉（牛腱子肉、牛后腿肉、牛前腿肉、牛肩肉和上脑牛肉）进行电子鼻检测,所得数据采用线性判别式分析法（LDA）分析,获得不同部位和不同温度下牛肉气味的指纹图谱;并进一步运用GC-MS分析导致气味差异的挥发性物质组成,结果表明:通过GC-MS分析,在60℃下,牛后腿肉,牛前腿肉,牛腱子肉,牛肩肉,上脑牛肉中分别鉴定出28、27、24、24、17种挥发性物质,120℃下,牛后腿肉,牛前腿肉,牛腱子肉,牛肩肉,上脑牛肉中分别鉴定出20、33、16、20、21种挥发性物质,而气味的差异主要由醛类和醇类物质的含量和组成所造成。      

基于电子鼻和GC-MS对优质稻谷挥发性成分差异性分析

采用电子鼻和GC-MS对两种优质稻谷苏香粳3号和南粳46挥发性物质进行鉴定并结合主成分分析法分析它们储藏期间挥发性组分的变化和差异。结果表明：电子鼻可以有效区分不同储藏时间的稻谷样品,使用GC-MS测定稻谷的挥发性成分主要有烷烃类、苯烯烃类、醛类、酮类、醇醚类、酸酯类和杂环类 7 大类。温度条件对不同挥发性物质的含量占比有很大影响,两种稻谷低温时烷烃类和酮类含量占比较高,高温时酸酯类含量占比更高。对两种稻谷的挥发性成分进行主成分分析可知,两种稻谷的特征性挥发物质有所不同,苏香粳3号拥有更多种酸酯类和杂环类特征性物质,而南粳46在烯烃类和醛酮类有更多种独特的物质。可以根据特征性挥发物质来区分苏香粳3号和南粳46,为通过寻找特征性挥发物质来区分不同稻谷提供参考依据。     

电子鼻和气质联用技术分析不同酒龄酱香型白酒挥发性成分

以5种不同酒龄的酱香型白酒为研究对象,研究了不同酒龄的酱香型白酒品质以及风味变化规律,通过电子鼻和气相色谱-质谱联用（GC-MS）技术对酱香型年份酒的香气化合物进行整体区分及定性定量分析。结果表明,电子鼻检测到不同酒龄的酱香型白酒香气成分差异明显;在5种不同酒龄的酒样中共定性出52种物质。随着酒龄的增加,酯类物质含量呈先减少后增加趋势,醇类物质呈现波浪形变化趋势;酸类物质呈上升趋势;呋喃类物质上升趋势明显;其中有8种物质（丁酸乙酯、己酸乙酯、庚酸乙酯、戊酸乙酯、丁酸、戊酸、己酸、乙偶姻）的含量上升趋势明显,5种物质（苯乙酸乙酯、2-甲基丙醇、2-甲基丁醇、呋喃、四甲基吡嗪）的含量下降趋势明显。聚类分析（CA）、主成分分析（PCA）与线性判别分析（LDA）的结果也表明,5个不同酒龄的酒样在挥发性成分上具有较为明显的差异,初步证实了通过电子鼻和气质联用技术区分酱香型白酒酒龄的可行性。     

电子鼻结合气质联用法分析大菱鲆冷藏过程中挥发性成分变化

通过测定大菱鲆在4℃冷藏过程中的感官品质、菌落总数和TVB-N值等指标的变化,确定贮藏20d时已达腐败阶段。利用电子鼻检测新鲜及腐败鱼肉的气味差异,并对所获数据进行主成分分析,同时结合顶空固相微萃取(HS-SPME)和气质联用技术(GC-MS)对新鲜及腐败鱼肉的挥发性成分进行分析鉴定。结果表明:电子鼻对新鲜及腐败鱼肉整体风味的区分快速、灵敏,其分析结果与常规新鲜度评价指标的变化致;采用GC-MS法在新鲜及腐败鱼肉中分别检测出27及28种挥发性物质,主要为醛类、酮类、醇类、酯类、烃类和胺类化合物等,其中醛类、酮类和醇类物质在新鲜鱼肉中的含量较高,而胺类物质在腐败鱼肉中含量较高。     

电子鼻和气质联用法分析普洱茶香气成分

为了解不同品牌普洱茶香气成分的特点和差异性,本研究采用电子鼻(electronic nose,E-nose)和顶空固相微萃取(headspace solid phase microextraction,HS-SPME)结合气相色谱-质谱联用(gas chromatography-mass spectrometry,GC-MS)对3个品牌普洱茶香气成分进行分析和鉴定。结果表明,E-nose能够较好区分3个品牌的普洱茶,主成分分析显示不同品牌样品间差异明显,区分度良好。进一步采用HS-SPME-GC-MS对普洱茶香气构成进行分析,结果共检测出74种化合物,共有成分38种,其中大益普洱茶、老同志普洱茶和澜沧古茶分别检测出66、53和48种,主要包括:醛类、醇类、酮类、甲氧基苯类化合物等物质,且物质组成和含量差异显著,主要差异性物质包括2-羟基-6-甲基苯甲醛、藏红花醛、芳樟醇氧化物、4-萜烯醇、甲基庚烯酮、(E,E)-3,5-辛二烯-2-酮、1,4-二甲氧基苯、1-甲氧基-4-(1-丙烯基)-苯、邻异丙基甲苯、α-松油烯、邻苯二甲酸二甲酯、咖啡因。香气活性值(odour active values,OAV)分析表明造成香气差异的物质主要是(E)-2-辛烯醛、(E,E)-2,4-壬二烯醛、壬醛、α-紫罗兰酮、香叶基丙酮。     

利用电子鼻和气质联用研究腊肉挥发性风味物质的形成规律

为研究腊肉加工过程中整体风味的变化,用固相微萃取（SPME）结合气相色谱-质谱联用（GC-MS）对川味传统烟熏腊肉不同加工阶段样品中的挥发性风味物质进行了鉴定,并应用电子鼻和偏最小二乘回归（PLS）分析比较各加工阶段样品的整体风味。结果表明,在川味腊肉加工的6个阶段,共鉴定出挥发性风味成分183种,包括醛、酮、酯、醇、酸、酚、醚和杂环类等;随着加工的不断进行,挥发性风味物质的种类不断增加,从原料中的75种增加到成品中的116种,其峰面积也增加了近4倍;PLS分析和电子鼻可以很好地区分6个不同加工阶段的样品。因此川味腊肉加工过程中,无论是整体风味还是挥发性物质的种类和含量都会发生显著变化,其风味是在加工中逐渐形成的。      

应用顶空固相微萃取-气相色谱质谱技术解析酿造用高粱蒸煮挥发性香气成分

通过比较不同样品前处理方法提取分析蒸熟高粱中香气组分的效果,开发出基于瓶内蒸煮结合顶空固相微萃取-气相色谱质谱联用(headspace solid phase microextraction and gas chromatography mass spectrometry,HSSPME-GC-MS)分析酿造用高粱蒸煮香气组分的方法。采用该方法研究了白酒酿造主要原料高粱蒸煮后挥发性香气特征。在蒸熟的高粱中共鉴定出46种挥发性香气成分,包括醛类化合物16种,有机酸类化合物7种,醇类化合物6种、酯类化合物6种,酚类化合物4种、酮类化合物2种、呋喃类化合物2种、其他类化合物3种。其中峰面积相对含量较高的化合物有苯甲醛(20.21%),己酸(9.00%),壬醛(8.66%),糠醛(8.90%),2-戊基呋喃(6.48%)和萘(5.49%)。同时还检测到一批香气阈值较低的化合物,如壬醛、(E,E)-2,4-癸二烯醛、(E)-2-辛烯醛、(E)-2-癸烯醛、1-辛烯-3-醇、香兰素、4-乙基愈创木酚、4-乙烯基愈创木酚、γ-辛内酯、γ-壬内酯等。这些香气物质可能是构成酿造用高粱蒸煮香气特征的主要香气组分。     

基于电子鼻技术监测羊奶发酵前后不同阶段风味的变化

本文利用电子鼻PEN3分析了羊奶发酵前后不同阶段的风味变化。结果表明,新鲜羊奶经过发酵后,特征挥发性成分在电子鼻传感器上的响应由原来的传感器6(甲烷)为主转变成以传感器7(充化氢)、传感器9(有机芳香硫化物)和传感器2(氮氧化合物)为主的挥发性物质,改变了羊奶的气味。采用PCA及LDA分析发现:PCA分析法能准确区分羊奶发酵前后的不同阶段,LDA体现出了发酵前后的不同阶段挥发性成分明显的变化趋势,且变化趋势与理论分析相符。      

Analytical methods for the determination of the geographic origin of Emmental cheese: volatile compounds by GC/MS-FID and electronic nose

The volatile compounds of Emmental cheese of different origins were investigated to check their suitability as markers of geographic origin. A total of 20 Emmental cheese samples from Switzerland, Allgäu (D), Bretagne (F), Savoie (F), Vorarlberg (A) and Finland (produced in winter with a ripening time according to that sold in the corresponding regions) were analysed using dynamic headspace gas chromatography followed by flame ionisation and mass spectrometry. All regions were easily differentiated by using compounds occurring only in the corresponding region or by combining a few compounds by principal component analysis (PCA). Further analyses were carried out using a mass spectrometry-based electronic nose. PCA achieved 90 and 91% of correct classifications for the Emmental from Switzerland and other regions, respectively.     

A comparison of warmed-over flavour in pork by sensory analysis, GC/MS and the electronic nose

Pork muscle samples (M. longissimus dorsi and M. psoas major) were obtained from pigs given one of 4 dietary treatments, (i) control diet, (ii) supplemental iron (300 mg iron (II) sulphate/kg feed), (iii) supplemental vitamin E (200 mg dl-α-tocopheryl acetate/kg of feed) and (iv) supplemental vitamin E+supplemental iron. Warmed-over flavour (WOF) was evaluated by a trained sensory panel (n=8) for the four treatments cooked and refrigerated at 4?°C for up to 5 days. Gas chromatography mass spectrometry (GC/MS) and Electronic nose analysis was performed on a subset of the full design which included samples of M. longissimus dorsi, treatments (ii) and (iii) and M. psoas major with treatment (i) for 0 days of WOF development. Day 5 of WOF development was included in the subset and represented by samples of M. longissimus dorsi, treatment (iv) and M. psoas major, treatments (ii) and (iii). Bi-linear modeling was used to determine the correlation of GC/MS and electronic nose data to sensory data. Also, the reproducibility and reliability of electronic nose data was evaluated by repeating the analysis of samples in a different laboratory and with a time difference of approximately 11 months. Mean-centring was used to normalise the data from these two different electronic noise data sets. GC/MS data correlated to sensory data with specific compounds (e.g., pentanal, 2-pentylfuran, octanal, nonanal, 1-octen-3-ol and hexanal), proving to be good indices of oxidation in cooked samples of M. longissimus dorsi and M. psoas major. Electronic nose data correlated to sensory data and separated the sensory variation. The reproducibility of this data was high with the second set of samples being predictive of the first set.     

Characterization of flavour and volatile compounds of fermented squid using electronic nose and HPMS in combination with GC-MS

The present study investigated the flavour characteristics and key volatile components of fermented squid (Dosidicus gigas) as well as their formation mechanism by three different starter cultures of lactic acid bacteria (LAB) and natural squid. The sensory assessment, volatile compounds, as well as the amino acids of the mixed fermented squid were detected using pickled brine as samples of fermented squid. A total 88 types of volatile compounds were found in four samples by 0–72 h of fermentation. After fermentation by LAB, the volatile compounds of squid showed that the fermented squid with different started cultures differed mainly in terms of numbers of alcohols, ketones, and esters. Furthermore, the amounts of volatile compounds among three starter cultures were also obviously different. Gas Chromatography-Mass Spectrometer (GC-MS) analysis indicated that the mixed fermentation process contained relatively higher (+)-limonene (11.71%) (lemon scent) and 3-hydroxy-2-butanone (5.72%) (creamy taste). These compounds were not detected in the control group. The main flavour compounds of nonanal and 2, 4-decadienal were gradually reduced. Meanwhile, 2, 3-butanedione, 2-heptanone, 2-pentylfuran, and nonanoic acid are the key flavour components. The total principal component is 94.01%, which were clarified by electronic nose in combination with principal components analysis. After mixed fermentation by LAB, the total amino acid (TAA) content reached 85.36 g/100 g, which was almost twice the amount of the control, especially in aspartate, glutamate, and threonine. Our results indicated that LAB has obvious effects on deodorization and flavour promotion during the fermentation of squid. This study provided an important basis for the further development and utilization of squid.     

采用电子鼻和GC-MS技术研究慕萨莱思中挥发性成分

以阿瓦提慕萨莱思为研究对象,采用电子鼻技术(E-nose)和固相微萃取-气相色谱质谱联用(SPME-GC-MS)技术对不同酒精度原酒(G1、G2、G3)及慕萨莱思成品酒(G4、G5、G6、G7)中的挥发性成分进行检测,研究分析其挥发性成分的变化,结果表明:PCA模型的区分指数DI值在80以上,说明样品能够很好的被区分;监督型DFA模型主要用来预测未知样品,结合使用PCA模型和DFA模型可以有效建立区分辨别不同种类的慕萨莱思;利用GC-MS共检测出挥发性物质164种,其中G1为67种、G2为47种、G3为55种、G4为45种、G5为54种、G6为57种、G7为51种。通过主成分分析(PCA)可知,慕萨莱思中醇类、酯类以及酸类物质是最主要的挥发性组成成分。其中贡献较大的为苯乙醇、1-戊醇、己酸、辛酸、月桂酸、癸酸、乙酸乙酯、苯乙酸乙酯、辛酸乙酯、棕榈酸乙酯等。GC-MS与电子鼻数据结果建立的PLS模型决定系数均大于90.0%,具有很好的相关性。     

基于电子鼻和HS-SPME-GC-MS检测并分析籼稻谷储藏期间挥发性物质的研究

利用电子鼻对不同储藏时间(0、30、60、90、120、150、180 d)、储藏温度35℃、储藏水分15.5%的籼稻进行检测,并对籼稻的整体挥发性物质进行主成分分析,在此基础上利用顶空固相微萃取结合气质联用法(HS-SPME-GC-MS)对籼稻储藏期间挥发性物质的相对含量进行测定,最后采用主成分分析法对挥发性物质进行分析。结果表明:电子鼻检测第一、二主成分的累计贡献率达到99%,区分指数为81,主成分图显示初始和储藏6个月的数据无重叠,区分效果较好;GC-MS结果显示,样品中的挥发性物质共102种,烃类、醇类、醛类、酮类、杂环类挥发性物质的相对含量随储藏时间延长而呈现增大的趋势,主成分分析结果显示,醇、醛、酮对样品整体挥发性物质的贡献最大,然后依次为杂环类、烃类、酸酯类,通过计算主成分得分和观察挥发性物质相对含量的变化,推断出籼稻谷储藏期间导致其品质劣变的特征性物质为2-己基-1-癸醇、苯甲醇、己醛、癸醛、顺-2-癸烯醛、2-十二烯醛、2-十一酮、5-十三酮,电子鼻和GC-MS联用能较好地从宏观和微观2个方面对样品挥发性物质进行检测和分析,同时主成分分析能有效地推断出籼稻谷品质劣变的特征性挥发物。     

电子鼻、气相色谱-嗅辨仪和气相色谱-质谱联用技术结合识别豉香白酒中异嗅物质

目的采用电子鼻、气相色谱-嗅辨仪和气相色谱-质谱联用技术等多手段结合研究豉香白酒中异嗅物质的组成。方法采用电子鼻、气相色谱-嗅辨仪和气相色谱-质谱联用技术相结合的方法分析了某豉香型白酒的嗅味物质。通过谱图比对及统计学分析,找出2款酒样中具有显著性差异的物质,并最终确定了2款白酒中嗅味差异物质的主要组成。结果共定性了53种酒体成分,其中有8种差异化合物有白酒风味贡献,通过验证确定丁酸、异戊醇是2款白酒中主要的异嗅味物质。结论相较于利用感官员进行呈味物质辨识的酒体异嗅分析方法,该方法具有更客观、更准确、可重复高的优势,期望为白酒智能化感官研究和酒体品质控制提供参考。     

基于电子舌、电子鼻和GC-MS分析襄阳大头菜新、老卤水滋味和挥发性物质

通过电子舌、电子鼻、气相色谱-质谱联用（GC-MS）技术对襄阳大头菜新、老卤水中的理化性质、滋味品质和挥发性物质进行分析。电子舌数据分析结果显示,襄阳大头菜新卤水的酸味、丰度和咸味均显著低于老卤水（P＜0.05）。电子鼻的数据分析结果显示,与新卤水相比,老卤水刺激性气味减少,芳香性气味更浓郁。GC-MS分析结果显示,新卤水中最主要的挥发性物质为异硫氰酸烯丙酯。对电子舌、电子鼻和GC-MS数据的主成分分析（PCA）结果显示,大头菜新卤水中W1S（甲烷）、W2S（乙醇）、W3S（烷烃）、W1W（有机硫化物、萜类）、W2W（有机硫化物）、W6S（氢气）和酯类含量较高,反映出了襄阳大头菜新卤水中异硫氰酸烯丙酯含量高;而大头菜老卤水中WIC（芳香类物质）、W3C（氨气、芳香类物质）、W5C（烷烃,芳香类物质）、醛类、酸味、丰度、后味A占据优势,说明襄阳大头菜老卤水中硫醚类物质含量丰富,醛类物质较多,酸味、丰度和后味A突出。     

Lethality of Salmonella and Listeria innocua in fully cooked chicken breast meat products during postcook in-package pasteurization

The process lethality model was used to predict the thermal kill of Salmonella and Listeria innocua in fully cooked and vacuum-packaged chicken breast meat during hot-water postprocess pasteurization. Time-temperature profiles of the meat samples during treatment and D-values (decimal reduction times) and z-values (change in temperature required to change the D-value) for Salmonella and L. innocua in the same meat product were used in the prediction of lethality. The results of the model prediction were compared with those of the inoculation study for the same meat product at a 95% confidence level of up to 10(7) CFU/g for Salmonella and L. innocua. The thermal lethality predictions obtained with the process lethality model for Salmonella and L. innocua were within the 95% confidence level for the experimental data from the inoculation study, suggesting that the process lethality model was a useful tool for the determination of the kill of Salmonella or L. innocua at up to 10(7) CFU/g in fully cooked chicken breast meat products during postprocess pasteurization with hot water.     

电子鼻技术对猪肉挥发性盐基氮的预测研究

为预测不同肥瘦配比猪肉的新鲜度,对4℃恒温贮藏条件下的新鲜猪肉进行挥发性盐基总氮(Total Volatile Basic Nitrogen,TVB-N)检测和营养成分检测,同时利用电子鼻技术检测挥发性气味的信息。以传感器阵列特征值为自变量建立蛋白质、脂肪的回归预测模型,分别对不同肥瘦配比的猪肉样本建立不分类和分类2种TVB-N神经网络预测模型。结果表明:先分类再建立神经网络模型预测的效果更优,将样本进行二分类建立2个模型后,模型训练组的相关系数达0.994、0.985(p<0.01),预测组的相关系数达到0.984、0.979(p<0.01);模型的绝对误差小而且分布区间集中,训练组和预测组各有86%、62.6%的样本的绝对误差在0~1之间;训练组中没有绝对误差大于2.5的样本,预测组中仅有8.5%的样本绝对误差大于2.5。电子鼻传感器特征信号与TVB-N数据具有很强的相关性,电子鼻可以快速预测出不同肥瘦配比猪肉在贮藏期间TVB-N含量的变化,进而无损的评价猪肉的新鲜度。     

Detection and quantification of ochratoxin A and deoxynivalenol in barley grains by GC-MS and electronic nose

Mycotoxin contamination of cereal grains can be detected and quantified using complex extraction procedures and analytical techniques. Normally, the grain odour, i.e. the presence of non-grain volatile metabolites, is used for quality classification of grain. We have investigated the possibility of using fungal volatile metabolites as indicators of mycotoxins in grain. Ten barley samples with normal odour, and 30 with some kind of off-odour were selected from Swedish granaries. The samples were evaluated with regard to moisture content, fungal contamination, ergosterol content, and levels of ochratoxin A (OA) and deoxynivalenol (DON). Volatile compounds were also analysed using both an electronic nose and gas chromatography combined with mass spectrometry (GC-MS). Samples with normal odour had no detectable ochratoxin A and average DON contents of 16 microg kg(-1) (range 0-80), while samples with off-odour had average OA contents of 76 microg kg(-1) (range 0-934) and DON contents of 69 microg kg(-1) (range 0-857). Data were evaluated by multivariate data analysis using projection methods such as principal component analysis (PCA) and partial least squares (PLS). The results show that it was possible to classify the OA level as below or above the maximum limit of 5 microg kg(-1) cereal grain established by the Swedish National Food Administration, and that the DON level could be estimated using PLS. Samples with OA levels below 5 microg kg(-1) had higher concentration of aldehydes (nonanal, 2-hexenal) and alcohols (1-penten-3-ol, 1-octanol). Samples with OA levels above 5 microg kg(-1) had higher concentrations of ketones (2-hexanone, 3-octanone). The GC-MS system predicted OA concentrations with a higher accuracy than the electronic nose, since the GC-MS misclassified only 3 of 37 samples and the electronic nose 7 of 37 samples. No correlation was found between odour and OA level, as samples with pronounced or strong off-odours had OA levels both below and above 5 microg kg(-1). We were able to predict DON levels in the naturally contaminated barley samples using the volatile compounds detected and quantified by either GC-MS or the electronic nose. Pentane, methylpyrazine, 3-pentanone, 3-octene-2-ol and isooctylacetate showed a positive correlation with DON, while ethylhexanol, pentadecane, toluene, 1-octanol, 1-nonanol, and 1-heptanol showed a negative correlation with DON. The root mean square error of estimation values for prediction of DON based on GC-MS and electronic nose data were 16 and 25 microg kg(-1), respectively.     

基于气相离子迁移谱和电子鼻技术分析 核桃挥发性风味物质

为研究不同品种核桃挥发性风味物质的差异和核桃品种的区分方法,以5种核桃为研究对象,采用气相离子迁移谱（GC-IMS）和电子鼻（E-nose）技术结合主成分分析(PCA）、线性判别分析（LDA）和聚类分析,对核桃挥发性风味物质的组成及品种差异进行了研究。结果表明：GC-IMS技术结合聚类分析和E-nose技术结合LDA分析均能有效区分核桃品种;采用GC-IMS技术从5种核桃中分离出73种挥发性成分,鉴定出其中19种物质,主要有醇类、酮类、醛类和酯类,其中乙醇、2-甲基丙醇、1-戊醇、3-甲基-3-丁烯-1-醇、正己醇、2-庚酮、戊醛、己醛、庚醛、壬醛、苯甲醛和乙酸乙酯是区分核桃品种的关键物质; E-nose分析结果表明,W3C、W5C、W1C和W6S传感器在区分核桃品种上有较大贡献,LDA由于考虑了组间差距,对于核桃品种的区分相较PCA更为明显;两种风味分析技术相比较,GC-IMS可对挥发性物质进行定性和定量检测,E-nose虽不能鉴定挥发性物质的具体种类,但样品处理简单,可实现品种的快速区分。