电子鼻和电子舌在乳制品品质及货架期监控中的应用研究

基于仿生技术和传感器技术的电子鼻和电子舌技术的应用研究发展迅速.本文介绍了电子鼻和电子舌系统的构成和工作原理以及其在分析乳制品的风味、监控其储藏阶段的成熟或变质过程、控制原料乳的质量及掺假(杂)等方面的应用现状.     

Influence of storage temperature on microbial spoilage characteristics of haddock fillets (Melanogrammus aeglefinus) evaluated by multivariate quality prediction

The proliferation of specific spoilage organisms (SSO) and quality changes were evaluated in haddock fillets stored in styrofoam boxes at 0, 7 and 15 degrees C and under temperature fluctuations. A rapid electronic nose technique was used to monitor different classes of compounds, representing microbial metabolites that were characteristic for the onset of spoilage odors. Photobacterium phosphoreum predominated among the spoilage bacteria and high levels of TVB-N were observed at sensory rejection. Pseudomonas spp. appeared to be responsible for the development of sweet, fruity spoilage odors in haddock fillets coinciding with increasing response of the electronic nose CO sensor. H(2)S-producing bacteria, most likely Shewanella putrefaciens, were associated with the H(2)S sensor's response at abusive temperature conditions. Partial Least Squares Regression (PLSR) was used as an explorative tool to provide a better understanding of the spoilage potential of SSOs, by evaluating models based on electronic nose responses and counts of specific spoilage organisms to predict sensory quality (Torry scores). The best prediction of the sensory quality was obtained by PLSR models based on five variables: the electronic nose sensors (CO, NH(3) and H(2)S), pseudomonads counts and a time-temperature variable. Good agreement between the predicted and experimental data indicates that these variables characterize the sensory quality of haddock fillets stored under different temperatures.     

粮食真菌毒素污染的无损检测方法研究进展

粮食种植、加工和储运过程易受真菌毒素污染,严重威胁人畜健康。然而,目前传统的真菌毒素检测方法存在过程繁琐、时效性差或灵敏度低等缺点,难以满足现场快速准确检测的需要,日益成为制约粮食质量安全的瓶颈。现代无损检测技术作为一种新兴的检测技术,可以在不破坏样品的情况下对其进行质量评价,是粮食品质在线、实时检测的一个重要发展方向,在粮食真菌毒素污染的快速分析方面具有巨大的应用潜力。本文重点综述了近红外光谱、高光谱图像、电子鼻等典型无损检测技术在粮食真菌毒素污染检测分析中的最新研究进展,讨论了各种技术的优点及限制因素,并对其应用前景进行了展望。     

Identification of the aroma compounds in stinky mandarin fish (Siniperca chuatsi) and comparison of volatiles during fermentation and storage

Identification of aroma compounds in Stinky Mandarin fish (Siniperca chuatsi) and comparison of volatiles during fermentation (with spices and salt) and storage were analysed by electronic nose (e‐nose) combining with gas chromatography–mass spectrometry (GC‐MS). Among the sixty‐one detected volatiles, thirteen aroma‐active compounds, especially linalool, were identified in stinky mandarin fish according to thresholds and concentrations. Totally, twenty‐four aroma compounds correlated well with the periods of fermentation and storage. Trimethylamine, indole, sulphur‐containing compounds, acetic acid, esters and phenols increased continually, while aldehydes decreased. According to these quality indicators, e‐nose data using principal component analysis showed a clear discrimination of the fermented fish and were in good agreement with the results of GC‐MS. In conclusion, fermentation favoured to retard spoilage and provided new aroma compounds. The technique employing an e‐nose in combination with GC‐MS could compare and identify the aroma and quality of stinky mandarin fish.     

谷物霉菌挥发性物质的电子鼻与GC-MS检测研究

为建立粮食受霉菌污染的快速检测方法,本研究利用电子鼻与气相色谱质谱联用(GC-MS)技术对6种谷物中常见霉菌在不同生长阶段(1、2、5、13 d)的特征挥发性气味物质进行了检测分析。GC-MS结果显示不同霉菌的挥发性物质成分存在差异,且在生长后期差异更加显著。基于电子鼻信号的主成分分析(PCA)法能够有效区分生长中后期(5、13 d)不同菌属的霉菌样品。线性判别分析(LDA)和偏最小二乘判别分析(PLS-DA)模型对黄曲霉类、寄生曲霉类和青霉类样品的整体判别正确率分别达到100%和97.4%。结果表明,运用电子鼻与GC-MS技术对粮食霉菌污染情况进行快速鉴定具有一定可行性。     

Application of solid phase-microextraction (SPME) and electronic nose techniques to differentiate volatiles of sesame oils prepared with diverse roasting conditions

Headspace volatiles of sesame oil (SO) from sesame seeds roasted at 9 different conditions were analyzed by a combination of solid phase microextraction (SPME)-gas chromatography/mass spectrometry (GC/MS), electronic nose/metal oxide sensors (MOS), and electronic nose/MS. As roasting temperature increased from 213 to 247 °C, total headspace volatiles and pyrazines increased significantly (P < 0.05). Pyrazines were major volatiles in SO and furans, thiazoles, aldehydes, and alcohols were also detected. Roasting temperature was more discrimination factor than roasting time for the volatiles in SO through the principal component analysis (PCA) of SPME-GC/MS, electronic nose/MOS, and electronic nose/MS. Electronic nose/MS showed that ion fragment 52, 76, 53, and 51 amu played important roles in discriminating volatiles in SO from roasted sesame seeds, which are the major ion fragments from pyrazines, furans, and furfurals. SO roasted at 213, 230, and 247 °C were clearly differentiated from each other on the base of volatile distribution by SPME-GC/MS, electronic nose/MOS, and electronic nose/MS analyses. Practical Application: The results of this study are ready to apply for the discriminating samples using a combinational analysis of volatiles. Not only vegetable oils prepared from roasting process but also any food sample possessing volatiles could be targets for the SPME-GC/MS and electronic nose assays. Contents and types of pyrazines in sesame seed oil could be used as markers to track down the degree of roasting and oxidation during oil preparation.     

电子鼻在水果品质评价体系中应用的研究进展

人工智能技术电子鼻具有客观、准确、快捷、全面地评价气味并且具有不破坏样品和重复性好的特点,可运用于对水果品质评价体系中。本文介绍了电子鼻技术工作原理和常用的模式识别技术,并综述了电子鼻在水果成熟度监控、货架期预测、区分不同品种以及危害分析中的应用,剖析总结了电子鼻技术存在的问题,并提出了电子鼻技术的发展趋势和方向。     

无损检测技术在稻米品质检测中的应用及展望

稻米作为世界上主要的粮食作物,在生活水平不断提高的今天,稻米的品质成为民众关心的重点。为了保证稻米品质,有必要寻找或开发更为快速和无损的检测方法。稻米无损检测技术是建立稻米质量和稻米安全有效监控体系的关键技术。综述了我国近年来稻米品质无损检测技术的研究现状与应用。从近红外光谱技术、电子鼻技术及计算机视觉检测技术在稻米的碾米品质、外观品质、营养品质、蒸煮品质、食味品质5个方面的应用阐述了稻米品质无损检测技术的研究进展及存在问题,并对稻米品质检测技术的发展作出了展望。     

Volatiles for mycological quality grading of barley grains: determinations using gas chromatography-mass spectrometry and electronic nose

The possibility of using an electronic nose or gas chromatography combined with mass spectrometry (GC-MS) to quantify ergosterol and colony forming units (CFU) of naturally contaminated barley samples was investigated. Each sample was split into three parts for (i) ergosterol and CFU analysis, (ii) measurements with the electronic nose and (iii) identification of volatiles collected on an adsorbent with a GC-MS system. Forty samples were selected after sensory analysis to obtain 10 samples with normal odour and 30 with some degree of off-odour. The data set of volatile compounds and the data collected from the electronic nose were evaluated by multivariate analyse techniques. SIMCA classification (soft independent modelling of class analogy) was used for objective evaluation of the usefulness of the data from the GC-MS or electronic nose measurements for classification of grain samples as normal or with off-odour. The main volatile compounds of grain with normal odour were 2-hexenal, benzaldehyde and nonanal, while 3-octanone, methylheptanone and trimethylbenzene were the main volatile compounds of grain with off-odours. Using data from the electronic nose three samples of 40 were misclassified, while data analysis of the volatile compounds detected with the GC-MS, led to six misclassified samples. Regression models (partial least-squares, PLS) were built to predict ergosterol- and CFU-levels with data from the GC-MS or electronic nose measurements. PLS models based on both GC-MS and electronic nose data could be used to predict the ergosterol levels with high accuracy and with low root mean square error of prediction (RMSEP). CFU values from naturally infected grain could not be predicted with the same degree of confidence.     

电子鼻在乳品工业中的应用

介绍了电子鼻的工作原理,基本组成和发展历程。综述了电子鼻在乳品工业中的应用进展,特别是在乳制品成熟时间和货架期的预测、挥发性物质的分析、微生物的分类,干酪种类的分类和乳制品产地的区分等方面。展望了电子鼻在乳品工业中的应用前景。     

电子鼻在食品感官检测中的应用进展

近年来 ,随着电子鼻技术越来越多地受到各国学者的关注 ,其研究和应用领域 ,特别是在食品检测研究和应用领域也不断得到扩大。文中主要介绍了近几年电子鼻在国内外食品品质检测、食品的新鲜度和成熟度评价、食品的掺杂区分和食品败坏早期检测领域研究的进展 ,并提出今后该注意和研究的问题。     

电子鼻气敏传感器的工作原理及其在肉品掺假中的应用研究进展

电子鼻作为一种新型仿生嗅觉检测技术,具有检测时间短、样品预处理简单、检测结果可靠等优点,受到国内外学者的广泛关注。目前,市场上存在许多基于不同检测原理和机制的新型电子鼻传感器,其类型和阵列的差异与电子鼻的应用扩展密切相关。本文重点阐述电子鼻中金属氧化物型、导电聚合型、质量敏感型、场效应管型、光纤型等气敏传感器的工作原理,分析影响电子鼻检测结果的主要因素,并概述电子鼻在生鲜肉与肉制品掺假中的应用研究进展,以期为电子鼻的工业化推广和肉品掺假检测技术革新提供参考。     

自制电子鼻检测霉变大米

为对不同霉变程度的大米实现快速鉴别,研制了一套以LabVIEW为平台用于检测大米霉变的电子鼻系统。通过霉菌孢子液侵染正常大米,使用该电子鼻系统对不同天数掺入不同比例霉米的大米样品挥发物进行检测,对采集数据进行主成分分析（PCA）、线性判别分析（LDA）,最后使用反向传播（back propagation,BP）神经网络建立预测模型。结果表明,得分图显示正常大米和霉变大米挥发物差异性显著,LDA分类效果优于PCA;所建立的模型预测值和实际值相关性达0.953以上,训练集和测试集平均相对误差分别为3.56%、4.18%,训练集和测试集对于正常大米样本识别率为100%。综上,电子鼻系统可以作为霉变大米无损检测的有效手段,在大米品质鉴别方面具有实际应用意义。     

电子鼻技术在果蔬检测中的应用

电子鼻技术作为一种新兴的智能仿生技术,在工业和农业方面都得到了广泛的研究与应用,具有样品处理简单、检测速度快、识别效果好、实时、无损的优点。由于电子鼻具有满足农产品品质无损检测要求等优点,电子鼻系统正在被越来越多地运用到农业研究之中。本文介绍了电子鼻的发展史和一些常见的电子鼻型号,其中典型的有PEN3型和FOX4000等。分析了电子鼻系统的组成构造,介绍了电子鼻系统的工作原理。其中重点阐述了电子鼻技术在水果与蔬菜中的研究与应用。在农业生产过程中,电子鼻在对区分果蔬的不同类型与品种、合理地制定与调整果蔬的贮藏时间和条件以及鉴别与评价果蔬品质等方面有着很大的帮助。最后,主要针对电子鼻技术在农业中的应用,从多个方面对电子鼻技术存在的问题及其发展趋势进行了探讨。     

Using an electronic nose for determining the spoilage of vacuum-packaged beef

The use of an electronic nose in the quantitative determination of the degree of spoilage of vacuum-packaged beef was evaluated. Beef from four different slaughterhouses was sliced, vacuum-packaged and stored at 4 degrees C for 8 weeks. Samples were withdrawn for bacterial (aerobic bacteria, lactic acid bacteria, Brochothrix thermosphacta, Pseudomonas and Enterobacteriaceae) and sensorial analyses and analysis of the volatile compounds during the storage period. A trained panel was used for the sensorial evaluations. The volatile compounds were analysed using an electronic nose containing a sensory array composed of 10 metal oxide semiconductor field-effect transistors, four Tagushi type sensors and one CO2-sensitive sensor. Four of the 15 sensors were excluded due to lack of response or overloading. Partial least-squares regression was used to define the mathematical relationships between the degree of spoilage of vacuum-packaged beef, as determined by the sensory panel, and the signal magnitudes of the sensors of the electronic nose. The mathematical models were validated after 6 months using a new set of samples. The stability of the sensors during this period was examined and it was shown that the sensitivity of five of the 11 sensors used had changed. Using the six remaining sensors, the signal patterns obtained from the meat from the different slaughterhouses did not change over a period of 6 months. It was shown that the degree of spoilage, as calculated using a model based on two Tagushi sensors, correlated well with the degree of spoilage determined by the sensory panel (r2 = 0.94).     

基于电子鼻技术的猪肉脯品质判别分析

为实现猪肉脯品质的快速判别,采用电子鼻技术对12 个品牌3 个批次共108 个猪肉脯样品进行分析检测,同时依据GB/T 31406—2015《肉脯》对样品的蛋白质、水分、氯化物、脂肪及总糖含量进行品质评判,选取电子鼻响应曲线中120～150 s稳定数据段的平均值作为表征变量,结合主成分分析和k最近邻法（k=3）建立猪肉脯品质等级的判别模型。结果表明,所建模型的理论判别准确率可达89.81%,基于电子鼻技术的猪肉脯品质判别具有一定的可行性。     

基于电子鼻与气相色谱-质谱法探究小麦与碎麦挥发性香气成分差异

目的 解析小麦与碎麦挥发性香气成分差异。方法 采用顶空固相微萃取(headspace solid-phase microextraction, HS-SPME)技术联用电子鼻(electronic nose, E-Nose)与气相色谱-质谱法(gas chromatography-mass spectrometry, GC-MS)分析小麦与碎麦香气成分, 通过多元统计分析正交偏最小二乘法(orthogonal partial least squares-discriminant analysis, OPLS-DA)挖掘小麦与碎麦差异挥发物。结果 小麦与碎麦的香气成分存在显著差异, 整体上小麦挥发物响应强度高于碎麦, 小麦变成碎麦后部分香气值损失, 氧化分子和芳香化合物显著降低, 脂肪酸类化合物变化不明显, 酮类和胺类化合响应值较为接近。通过GC-MS共鉴定出42种化合物, 10种挥发物组分在小麦和碎麦共同检出, 小麦和碎麦中烷烃类化合物较多, 小麦主要挥发物为柠檬烯、十五烯和壬醛; 碎麦的主要挥发物是苯乙烯, 柠檬烯和间乙基甲苯。基于小麦和碎麦挥发组分建立了OPLS-DA评估模型, 共筛选出7种差异挥发物判别小麦品质。结论 本研究成功建立了区别小麦和碎麦的方法, 分析了小麦与碎麦香气成分差异, 为小麦品质判别提供了科学依据。     

口罩中有毒有害物质的思考

在疫情防控常态化的形势下,PP材质口罩是日常与口、鼻长时间接触的特殊消费日用品.简述PP材质口罩现有检测技术的不足,对可分解致癌芳香胺染料、甲醛、邻苯二甲酸酯、铅镉重金属、有机挥发物等有毒有害物质测定方法提出建议,需要设定限量要求,为建立较完善的PP材质口罩质量监控体系提供可靠依据.     

Sensory based quality control utilising an electronic nose and GC-MS analyses to predict end-product quality from raw materials

The objective of the present study was to investigate if an electronic nose, comprising six metal oxide sensors (MOS) could predict the sensory quality of porcine meat loaf, based on measuring the volatiles in either the raw materials or the meat loaf produced from those raw materials. A multivariate data analysis strategy involving analysis of variance partial least squares regression (APLSR) and principal component analysis (PCA) was used to determine causal and predictive relationships between the raw material and meat loaf samples, sensory analysis, electronic nose, and GC-MS measurements. The results showed that the six MOS sensors in the Danish odour sensor system (DOSS) could detect the raw materials that led to unacceptable products, as determined by sensory profiling and in-house sensory quality control (QC), and separate those raw materials from each other, based on the volatile composition, as determined by GC-MS. However, the electronic nose was unable to detect all the sensory unacceptable meat loaf samples themselves due to changes in the volatile composition after cooking. Analysis of the GC-MS compounds identified from raw materials and meat loaf samples indicate that two MOS sensors mainly responded to alcohols and to a lesser degree to aldehydes and alkanes, whereas two other sensors most likely responded to low molecular weight sulphur compounds. Thus, the results indicate that measuring volatiles with the MOS sensors in the DOSS system, on raw materials for processed meat products, may be a feasible strategy in sensory based quality control, and may also have potential in predicting the sensory quality of the end product.     

基于电子鼻气味指纹图谱快速鉴别茶籽油

以不同产地、不同类型、不同工艺和不同质量的茶籽油为研究对象，通过电子鼻技术获取茶籽油的风味信息，结合Loading负载分析、主成分分析（?principal component analysis，PCA）、线性判别分析（linear discriminant analysis，LDA）等对电子鼻传感器数据进行解读。通过欧氏距离（?euclidean distance，ED）、马氏距离（?markov distance，MD）和判别函数法(discriminant function method，DFA)对未知样品进行鉴别，以期建立不同茶籽油的快速、准确鉴别方法。结果表明：加工工艺极大地影响了茶籽油的气味差异，电子鼻响应值雷达图及Loading负载分析均表明W1S、W1W、W2S、W2W传感器对茶籽油样品具有较好的响应值，通过ED、MD、DFA可以识别不同类型和不同质量的茶籽油。基于PCA的LDA可以有效的鉴别不同类型的茶籽油，模型准确性高，其确定性大于99%。电子鼻技术结合化学计量学可以快速、有效鉴别不同的茶籽油并为茶籽油掺伪的快速鉴别提供了借鉴。