PVC薄膜味觉传感器阵列对调味品和软饮料的识别

以铂工作电极(PtE)为基底聚合吡咯(PPy),并在聚吡咯表面被覆不同味敏剂修饰的PVC薄膜,得到八支味觉传感器,并进而与217型双盐桥饱和甘汞电极构成味觉传感器阵列-8-PPP-TSA。采用开路电位法获取调味品和软饮料不同样品在各传感器界面的数据响应矩阵,数据矩阵使用主成分分析方法可将各样品属性的相似相异程度在二维得分图上得以直观表达,调味品被分为鲜、咸-鲜、咸、酸四个区,软饮料被大致分为甜、高酸低甜、高甜低酸三个区;根据各样本之间的欧氏距离大小,使用聚类分析方法作亲疏关系树形谱系图,在不同的相似度下可将众多样品依据亲疏关系远近进行有层次的味觉聚类区分,错判较少。此外,模式识别分析结果表明,8-PPP-TSA的仿生味觉识别具有与生物味觉识别相似的特点。     

人工甜味味觉传感器的研究进展

人工味觉传感器按味觉响应原理不同可分为电位型传感器和伏安型传感器,是近年来兴起的一种用来检测味觉的电化学生物传感器形式。本文从味觉的仿生学角度介绍了人工味觉传感器的原理,通过味觉检测研究方法阐述了其构建方法及研究现状。主要概括了电位型味觉传感器在甜味检测方面的应用,包括PVC薄膜传感器对蔗糖的高敏感度选择性检测以及各类传感器对软饮料等甜味物质的检测。目前的实验研究表明,利用电化学生物传感器对甜味物质具有一定的选择性识别,且操作简单快速,但在准确度上还有待提高,同时人工味觉的仿生表达还需要更深入的研究。     

薄膜荧光传感器对冷藏鸭肉新鲜度的无损检测

目的:探究薄膜荧光传感器在肉品新鲜度检测中的可应用性,实现鸭肉新鲜度的无损、快速检测。方法:采用薄膜荧光传感器技术检测冷藏7 d内的鸭肉新鲜度,并测定其pH值、挥发性盐基氮(TVB-N)和生物胺含量,对传感器响应值与鸭肉新鲜度指标进行相关性分析。结果:pH值随贮藏时间的延长呈上升趋势,在贮藏第7天达到最大值;TVB-N含量随贮藏时间的延长而显著增加(P<0.05),在贮藏第7天达到17.51 mg/100 g,已超过限量值;生物胺中的色胺、腐胺、尸胺、章鱼胺和酪胺随贮藏时间的延长呈上升趋势,其中尸胺上升幅度最为明显,贮藏第7天时其含量是初始值的56.79倍。相关性分析结果表明,传感器响应值与生物胺总量的相关系数为-0.935(P<0.01),与TVB-N值和pH值的相关系数分别为0.841,0.857(P<0.05)。回归分析表明,响应值与TVB-N值、苯乙胺之间呈指数相关,拟合的回归方程为y = 0.154e-0.021x和y = 0.0664e-0.015x,决定系数分别为0.971和0.936,通过响应值能够较准确的预测TVB-N值和苯乙胺含量。结论:薄膜荧光传感器可用于鸭肉新鲜度的无损、快速和实时监测,为薄膜荧光传感器的应用提供理论参考,同时为肉类新鲜度检测提供新思路和技术支撑。     

电子舌技术背景与研究进展

介绍了电子舌的概念、基本结构及其发展历史,重点讨论了电子舌系统的技术背景。电子舌通常由三大部分组成,一是传感器阵列,包括PVC薄膜传感器阵列、Langmuir-Blodgett修饰膜传感器阵列、硫属玻璃传感器阵列等;二是模式识别方法,如主成分分析法、人工神经网络法、偏最小二乘法、简单优劣判别分析法等;三是相关的专家自学习系统。还介绍了作者近年来研究实现的新型多频脉冲电子舌——智舌（Smartongue）系统,并对电子舌发展的整体方向和趋势作了展望,强调电子舌等智能感觉系统将成为分析科学及其它学科领域中一类具有广阔发展前景的思路与技术。     

固体支撑双层脂质膜（S—BLM）味觉传感器的初步研究

介绍一种固体支撑双层脂质膜（Ｓ－ＢＬＭ）味觉传感器的制作方法，通过对膜的形成过程和寿命的观察，验证了Ｓ－ＢＬＭ具备制作简单，成形快，稳定性，寿命长等优点。Ｓ－ＢＭＬ味觉传感器对不同浓度的蔗糖、柠檬酸进行测定，发现在一定范围内，味物质浓度与膜电容之间较好地符合Ｇ．Ｈ．Ｔｅｃｈｎｅｒ感觉对数定律。     

固体支撑双层脂质膜（S—BLM）味觉传感器的初步研究

本文介绍了一种固体支撑双层脂质膜（Ｓ－ＢＬＭ）味觉传感器的制作方法。通过对膜的形成过程和寿命的观察测定。验证了Ｓ－ＢＬＭ所具备的制作简单，形成快，稳定好，寿命长等优点。我们以Ｓ－ＢＬＭ为味觉传感器，对不同浓度的蔗糖，柠檬酸进行测定，发现在了定范围内，味物质浓度与膜电容之间较好地符合了Ｇ．Ｈ．Ｔｅｃｈｎｅｒ感觉对数定律。     

基于离子选择性电极传感器阵列的白酒香型快速鉴别

白酒是中国传统且独有的产品,酿造原料和酿造工艺的不同产生了不同风味及口感的白酒,现阶段白酒的香型主要分为8种。为了实现对不同香型白酒的快速鉴别,本试验组建了由12个不同的离子选择性电极组成的味觉传感器阵列,对8种不同香型的白酒进行检测。在数据分析过程中,利用主成分分析法、聚类分析法和线性判别法对实验数据进行分析与识别。在主成分分析三维图中,8种不同香型的白酒能被很明显得区分开来,前3个主成分的累计贡献率为75.01%;利用聚类分析进一步对数据进行分析,其对8种不同香型白酒的识别率达到了93.75%;最后通过线性判别法对测试样本进行识别,校正集和预测集的识别率均达到了100%。研究表明:此味觉传感器阵列对不同香型的白酒具有较好的鉴别能力。     

用味觉传感器进行食品检查

人类的感觉一类是对物理量(即光、音、压力等)的感觉;另一类是综合多种化学物质的味觉和嗅觉。故有必要研究后者多种要素的测定方法,并对所得数据进行剖析。迄今为止,尚未确定出味觉的客观判断标准,常用模糊量的变化来表示。本文主要讨论采用模拟生物感受体结构的多种人工膜制成传感器,对食品进行味觉检查,并对味觉传感器客观的味觉测定方法作了阐释和展望。     

基于纳米技术的血红蛋白生物传感器快速测定油炸食品的丙烯酰胺

丙烯酰胺是一种神经毒素,具有潜在致癌性。丙烯酰胺分子可以和血红蛋白结构中N-末端缬氨酸的α-NH2形成共价化合物引起电极钝化,其含量不同,钝化程度也不同。基于此原理,本研究将多壁碳纳米管/血红蛋白/壳聚糖修饰的生物传感器用于油炸食品中丙烯酰胺的检测。利用差分伏安脉冲法对油炸食品中丙烯酰胺进行定量分析并对条件优化,多壁碳纳米管修饰量为10μg/cm2、支持电解质溶液为0.1 mol/L的PBS溶液(p H=7.4,含5×10-3 mol/L K4[Fe(CN)6],0.1 mol/L Na Cl),其中K4[Fe(CN)6]作为氧化还原探针,电位增量0.008 V、脉冲幅度0.05 V、脉冲宽度0.1 V、脉冲间隔0.1 s,丙烯酰胺线性检测范围3.0×10-8 mol/L~3.0×10-7 mol/L,最低检测限(S/N=3)为1.2×10-8 mol/L。与高效液相色谱法相比,该法具有简便、快速、准确、样品预处理简单、无需衍生化等优点。     

河鲀毒素生物传感器的研究

基于河鲀毒素(TTX)对细胞膜Na+通道的阻断作用,建立一种检测TTX的简易组织生物传感器。组织生物传感器由pNa电极、青蛙膀胱膜、电位计等构成。在pNa电极顶端用两层醋酸纤维薄膜包裹,中间夹入青蛙膀胱膜,构成感受器。将电极插入pNa=4的NaCl溶液中,使电极输出信号趋于稳定。将TTX被测液注入感受器系统,测定感受器输出量的抑制值。每次测定只需5min。最低检出限为0.002MU/ml(3.56×10-3μg/ml)。用0.003%Na3N保存,可连续使用250h。以生物传感器和小鼠生物试验法比较,建立了工作曲线,便于在餐饮企业对原料鱼进行检测和应用。     

Migration of 4-nonylphenol from polyvinyl chloride food packaging films into food simulants and foods.

Migration of 4-nonylphenol (NP) from polyvinyl chloride (PVC) films for food packaging into food simulants and foods has been studied in domestic applications such as wrapping of food and reheating in a microwave oven. The migration of NP from the PVC films was determined by high-performance liquid chromatography with electrochemical coulometric-array detection (LC/ED). Twelve PVC films intended for commercial use and ten for domestic applications (total: 22 samples) were analysed. Some of the PVC films (two home-use and ten retail-use) contained NP at concentrations of between 500 and 3300 microg/g. Migration of NP from the films was influenced by the test conditions (n-heptane at 25 degrees C for 60 min, distilled water at 60 degrees C for 30 min and 4% acetic acid at 60 degrees C for 30 min). The amount of NP migrating from the PVC films into n-heptane (0.33-1.6 microg/cm2) was higher than the amount migrating into distilled water or 4% acetic acid (up to 9.7 ng/cm2) for the 11 films in which NP was detected. Up to 0.23% of the NP migrated into distilled water and 4% acetic acid and up to 62.5% into n-heptane. In addition, we investigated NP migration into cooked rice samples wrapped in PVC film. Using spiked samples the method gave an average recovery of 83.7% (n = 5) with a standard deviation of 2.5%. Migration of NP ranged from not detectable (< 1.0 ng/g) to 410.0 ng/g by reheating samples in a microwave oven for 1 min and from not detectable to 76.5 ng/g by keeping samples at room temperature for 30 min.     

Head space sensor array for the detection of aflatoxin M1 in raw ewe's milk

A novel screening method was developed for simple and rapid detection of aflatoxin M1 contamination in raw ewe's milk samples without the need for sample pretreatment. The method was based on the use of a commercial head space sensor array system constituted by 12 metal oxide semiconductor sensors, 10 metal oxide semiconductor field-effect transistor sensors, and a pattern recognition software. Twenty-four raw milk samples collected from two different groups of ewes fed with a formulated feed that contained increasing amounts of aflatoxin B1 and six noncontaminated ewe's milk samples were analyzed. The results obtained by using the head space sensor array, processed by statistical methods, made it possible to group the samples according to the presence or the absence of aflatoxin M1. Sample classification was in complete agreement with the aflatoxin M1 content measured by an enzyme-linked immunosorbent assay procedure. This is the first report, to our knowledge, of detection of aflatoxin M1 in ewe's milk by a multisensor array.     

Colorimetric sensor arrays based on chemo-responsive dyes for food odor visualization

BackgroundThe colorimetric sensor array technology simulates human olfaction to analyze, identify and examine complex gas and volatility based on chem-responsive dyes. Unlike human olfaction and electronic noses, colorimetric sensor array is more objective and not susceptible to interference. In additional, with the visualization, rapidity and non-destruction of analysis, colorimetric sensor array has been increasingly applied in food science and industry.Scope and approachThis review focuses on the colorimetric sensor array technology and its major applications in food industry. Technical considerations associated with the chemo-responsive dyes, substrate materials, and data processing methods are discussed. In application, any type of food samples including solid, liquid food samples could be directly analyzed using colorimetric sensor array. Additionally, the recent development, and future research trends are also involved.Key findings and conclusionsThe colorimetric sensor array technology offers an exciting method to establish the correlation between the output of a colorimetric sensor array and the odor components, thereby enabling visual quantification of odors. It provides a potential odor-image-based monitoring tool for the rapid, reliable and in-line assessment of food safety and quality.     

Monitoring oxidative quality of pork scratchings,peanuts, oatmeal and muesli by sensor array

A sensor array (electronic nose) was successfully applied for predicting the content of hexanal and other volatiles in different dry fat‐containing products, showing the potential of replacing time‐consuming traditional laboratory analysis by faster in‐process monitoring methods. Unfortunately, prediction of free radical content was not successful, making early prediction of oxidation by sensor array infeasible. Owing to the non‐specificity of the sensors, a generic model could not be generated even though a series of standards was shown to have a high correlation between hexanal concentration and individual or multiple sensor responses. PCA models of sensor array responses of eg pork scratchings revealed a clear separation of samples stored in the experimental factor light versus darkness. Copyright © 2004 Society of Chemical Industry     

霉变玉米气体传感器阵列快速检测

玉米易受霉菌感染发生霉变,影响食用安全。快速测定玉米霉变程度是控制其危害的前提。本研究拟利用基于气体传感器阵列的电子鼻技术,获取不同霉变程度玉米的特征气味信息,建立玉米霉变程度快速检测方法。辐照灭菌玉米分别接种5种谷物中常见有害霉菌,并于28 ℃和85%相对湿度环境中储藏15 d直至严重霉变。在第0、6、9、12和15 d,采集样品的气味信息的电子鼻特征响应信号,建立了玉米霉变程度的定性定量模型。结果表明,主成分分析(PCA)法可成功区分不同霉变程度的玉米样品。线性判别分析(LDA)对受单一霉菌侵染的不同霉变程度玉米样品的平均识别率达93.3%以上,全部样品达76.7%。样品中菌落总数的偏最小二乘回归分析(PLSR)模型的预测决定系数(R_p2)达0.777,预测均方根误差和相对分析偏差(RPD)分别为0.981 log CFU/g和2.12。结果表明,应用电子鼻技术快速检测玉米霉变具有一定可行性,下一步需要不断扩大样本量以提高方法的精度和可靠性。     

Spinyhead croaker (<Emphasis Type="Italic">Collichthys lucidus</Emphasis>) quality determination using multi-walled carbon nanotubes gas-ionization sensor array

In this paper, a novel spinyhead croaker (Collichthys lucidus) quality analysis method using multi-walled carbon nanotubes (MWCNT) gas-ionization sensor array and stochastic resonance (SR) was proposed. The sensor array consisted of two MWCNT gas sensors. One was used as anodic sensor, and the other as cathodal sensor. Sensor array response to croakers under different storage time was measured. Responses of two MWCNT sensors were processed by SR. Signal-to-noise ratio (SNR) was utilized to characterize croaker quality. Meanwhile, total volatile basic nitrogen index was examined to provide quality reference to cold stored croaker samples in each day. Croaker quality was determined by SNR maximal values and its located noise intensities.     

PVDF/PVC膜化学稳定性研究

采用干湿法纺制PVDF/PVC中空纤维膜,并进行化学稳定性测试。试验表明:PVDF/PVC中空纤维膜经过次氯酸钠溶液清洗之后,膜通量有所回升,且回升程度与溶液的浓度和作用时间有关系;PVDF/PVC中空纤维膜耐酸性和抗氧化性较好,耐碱性较差。同时分析污染后膜的情况,结果表明,化学清洗比水清洗更为有效,膜的抗污染性能有待进一步提高,为PVDF/PVC纤维膜的应用提供理论基础。     

Rapid method for prediction of Escherichia coli numbers using an electronic sensor array and an artificial neural network

An electronic sensor array with 12 nonspecific metal oxide sensors was evaluated for its ability to monitor volatile compounds in super broth alone and in super broth inoculated with Escherichia coli (ATCC 25922) at 37 degrees C for 2 to 12 h. Using discriminant function analysis, it was possible to differentiate super broth alone from that containing E. coli when cell numbers were 10(5) CFU or more. There was a good agreement between the volatile profiles from the electronic sensor array and a gas chromatography-mass spectrometer method. The potential to predict the number of E. coli and the concentration of specific metabolic compounds was investigated using an artificial neural network (ANN). The artificial neural network was composed of an input layer, one hidden layer, and an output layer, with a hyperbolic tangent sigmoidal transfer function in the hidden layer and a linear transfer function in the output layer. Good prediction was found as measured by a regression coefficient (R2 = 0.999) between actual and predicted data.     

热缩膜成型皱缩面料的感性形象分析

采用感性工学的研究方法,论证热缩膜皱缩产品的市场价值。通过因子分析的方法提取代表消费者对服装面料外观形象感觉的主要因子,采用生产中常用的10种面料进行不同的热缩膜成型皱缩工艺进行处理,得到10组共20块面料。利用感性工学的方法以及SPSS软件分析了感性评价结果,探讨了面料的感性形象因子构成及热缩膜成型皱缩面料肌理图案的感性形象评价尺度。研究结果表明:得到的感性形象评价尺度适用于单件热缩膜成型的服装设计,服装面料感性形象在皱缩以后得到了很大程度的改观,从而论证了这种工艺所具有的市场价值。