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Applications of electronic nose (e-nose) and electronic tongue (e-tongue) in food quality-related properties determination: A review

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Artificial Intelligence in Agriculture 2020年第1期4卷 104-115页

作者： Juzhong Tan Jie Xu Department of Food Science Rutgers UniversityNew BrunswickNJ 08901USA Department of Food Science and Technology The Ohio State UniversityColumbusOH 43210USA

Background:An e-nose or an e-tongue is a group of gas sensors or chemical sensors that simulate human nose or human *** e-nose and e-tongue have showngreat promise and utility in improving assessments of food quality characteristics compared with traditional detection *** and approach:This review summarizes the application of e-nose and e-tongue in determining the quality-related properties of *** working principles,applications,and limitations of the sensors employed by electronic noses and electronic tongueswere introduced and *** pattern recognition algorithms,including artificial neural network(ANN),convolutional neural network(CNN),principal component analysis(PCA),partial least square regression(PLS),and support vector machine(SVM),were introduced and compared in this *** findings and conclusions:Overall,e-nose or e-tongue combining pattern recognition algorithms are very powerful analytical tools,which are relatively low-cost,rapid,and accurate.e-nose and e-tongue are also suitable for both in-line and off-line measurements,which are very useful in monitoring food processing and detecting the end product *** user of e-nose and e-tongue need to strictly control sample preparation,sampling,and data processing.

关键词： e-nose e-tongue Food quality assessments

Odor evaluation of Vehicle Interior Materials Based on Portable e-nose

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Odor Evaluation of Vehicle Interior Materials Based on Porta...

Identification of the flavor profiles of Chinese pancakes from various areas using smart instruments combined with e-noses and e-tongues

第三十九届中国控制会议

作者： Zhe-Hua Sun Ke-Xian Liu Xue-Han Xu Qing-Hao Meng Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information Engineering Tianjin University

The evaluation of the odor emitted by the interior materials is of great significance to the air quality control in the vehicle. This paper focuses on the multi-label classification problem of the odor type（i.e. the type of material from which the odor is released） and the grade evaluation in the vehicle. Two multi-label classifiers based on binary relevance（BR） and classification chain（CC） were designed to distinguish odor types and grades simultaneously and to distinguish odor types first and then grades, respectively. Based on the self-designed portable e-nose, six grades of odors released from six types of common interior materials were detected and classified. experimental results showed that both the multi-label classifiers achieved better recognition accuracy, but the CC had an average recognition rate of 88.17% slightly better than the BR. It is preliminarily verified that the portable e-nose based multi-label classifiers could be used to evaluate the odor of automotive interior materials.

关键词： e-nose vehicle interior materials multi-label classifier Odor evaluation

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International Journal of Agricultural and Biological engineering 2023年第1期16卷 283-290页

作者： Wei Liu Yue Fan Qiannan Liu Fen Xu Liang Zhang Honghai Hu Institute of Food Science and Technology Chinese Academy of Agricultural Sciences/Key Laboratory of Agro-Products ProcessingMinistry of Agriculture and Rural AffairsBeijing 100193China

In order to reveal the flavor characteristics of Chinese pancakes,the aroma and taste compounds of seven traditional Chinese pancakes were *** results showed that electronic nose(e-nose)analysis with PCA could successfully distinguish the aroma profiles of seven Chinese pancakes;the principal components PC1 and PC2 represented 75.74%and 23.2%of the total variance(98.94%)***,the discrimination index of taste profiles of seven Chinese pancakes based on electronic tongue(e-tongue)analysis with LDA was 99.32%;the discriminant factors DF1 and DF2 represented 94.99%and 4.33%of the total variance ***,GC-MS results demonstrated that thirty-threeﬂavor compounds were identiﬁed in seven Chinese pancakes,including aldehydes,alcohols,alkanes,acids,and *** the flavor components,aldehydes with ROAVs higher than 1 contributed most significantly to the overall aroma,such as(e,e)-2,4-nonadienal present the largest contribution in Qingzhou pancake,Jinan and Yishui pancake;hexanal present the largest contribution in Shenxian and Gaomi pancake;nonanal and benzeneacetaldehyde present the largest contribution in Linqu and Tai’an pancake,*** umami and sweet taste amino acids were the most abundant in all the Chinese pancake samples,and Qingzhou pancake had relatively high amino acid *** content of glucose was higher than maltose in Gaomi,Shenxian,and Tai’an pancakes,whereas the content of maltose was higher than glucose in Linqu,Qingzhou,Jinan,and Yishui *** results indicated that the aroma and taste proﬁles of Chinese pancakes differed significantly in terms of their flavor compound *** presented results could be beneficial for providing a comprehensive method for flavor profile identification of traditional whole-grain-based staples such as Chinese pancakes.

关键词： Chinese pancake flavor profile e-nose e-tongue smart instrument identification

electronic noses Using Quantitative Artificial Neural Network

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Chemical Research in Chinese Universities 2001年第4期17卷 380-386页

作者： WeN Li-jing BIAN Li-ping LU Yu ZHANG Mei-zhuo YU Li-ping YANG Peng-yuan Department of Chemistry Fudan UniversityShanghai 200433P.R.China

The present paper covers a new type of electronic nose (e-nose) with a four-sensor array, which has been applied to detecting gases quantitatively in the presence of interference. This e-nose has adapted fundamental aspects of relative error (Re) in changing quantitative analysis into the artificial neural network (ANN). Thus, both the quantitative and the qualitative requirements for ANN in implementing e-nose can be satisfied. In addition, the e-nose uses only 4 sensors in the sensor array, and can be designed for different usages simply by changing one or two sensor(s). Various gases were tested by this kind of e-nose, including alcohol vapor, CO, iiquefied-petrol-gas and CO2. Satisfactory quantitative results were obtained and no qualitative mistake in prediction was observed for the samples being mixed with interference gases.

关键词： e-nose ANN Relative error Quantitative analysis

High Pressure Treatment Changes Spoilage Characteristics and Shelf Life of Pacific Oysters(Crassostrea gigas)During Refrigerated Storage

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Journal of Ocean University of China 2017年第2期16卷 351-355页

作者： CAO Rong ZHAO Ling LIU Qi Department of Food engineering and Nutrition Yellow Sea Fisheries Research InstituteChinese Academy of Fishery SciencesQingdao 266071P.R.China

The effects of high pressure(HP) treatment on spoilage characteristic and shelf life extension of Pacific oysters(Crassostrea gigas) during refrigerated storage were *** showed that HP treatment of 275 MPa for 3 min or 300 MPa for 2 min could achieve 100% full release of oyster adductor muscle,pressures higher than 350 MPa caused excessive release as the shells of oysters were broken,thus use of higher pressures should be cautious in oyster processing industry because of its adverse impact on the appearance of *** treatment(300 MPa,2 min) was proper for the shucking of Pacific oyster(Crassostrea gigas) in *** treatment caused no organoleptic ***,HP treatment resulted in obvious differences in biochemical spoilage indicators(p H,TVB-N and TBARS) changes and volatile compounds profile determined by electronic nose during *** treatment(300 MPa,2 min) also led to a reduction of aerobic bacterial count(APC) by 1.27 log ***,the APC values of oysters treated by HP were always lower than those of the control samples during *** on the organoleptic,biochemical and microbiological indicators,shelf life of 6-8 d for control and 12 d for HP-treated oysters could be *** treatment showed great potential in oyster processing and preservation.

关键词： high pressure processing oyster spoilage e-nose shelf life

Projective Mapping and Product Positioning of Deep Fat Fried Snack

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Food and Nutrition Sciences 2011年第6期2卷 674-683页

作者： Ramasamy Ravi Vivek Kumar Singh Maya Prakash 不详

A study was carried out to examine the quality parameters of commercially available popular deep-fried snack-Mu- rukku. eight samples (four spicy and four salty) of most commonly consumed deep-fried snacks in India, viz., murukku (an extruded strands-like product made from the mixture of rice flour and black gram dhal flour) were analyzed for moisture, oil content, CIe instrumental color (L*a*b*), instrumental texture measurement (breaking strength of murukku strands), aroma finger printing by electronic nose and sensory quality. Quantitative descriptive analysis (QDA) and results showed that sample ‘A’ had highest acceptance and sample D lowest acceptance scores. The results indicated that significant variations were observed in moisture content (2.21 - 3.35%), oil content (30.10 - 34.61%) and textural parameters. electronic nose technique was found useful in fingerprinting the aroma pattern of market samples in a short time. Descriptive sensory profiling coupled with principal component analysis showed the interrelationship among and between sensory, instrumental, chemical parameters.

关键词： Deep-Fried Snacks Texture e-nose Sensory Profiling Product Positioning PCA QDA CIe

Breath Analysis for Detecting Diseases on Respiratory, Metabolic and Digestive System

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Journal of Biomedical Science and engineering 2019年第1期12卷 40-52页

作者： Lu Kou David Zhang Jane You Yingbin Jiang Biometrics Research Center Department of Computing The Hong Kong Polytechnic University Hong Kong China Department of Computer Science Harbin Institute of Technology Shenzhen Graduate School Shenzhen China

Recently, biological technology and computer science are of great importance in medical applications. Since one’s breath biomarkers have been proved to be related with diseases, it is possible to detect diseases by analysis of breath samples captured by e-noses. In this paper, a novel medical e-nose system specific to disease diagnosis was used to collect a large-scale breath dataset. Methods for signal processing, feature extracting as well as feature & sensor selection were discussed for detecting diseases on respiratory, metabolic and digestive system. Sequential forward selection is used to select the best combination of sensors and features. The experimental results showed that the proposed system was able to well distinguish healthy samples and samples with different diseases. The results also showed the most significant sensors and features for different tasks, which meets the relationship between diseases and breath biomarkers. By selecting best combination of different sensors and features for different tasks, the e-nose system is shown to be helpful and effective for diseases diagnosis on respiratory, metabolic and digestive system.

关键词： e-nose Chemical Sensors Breath Analysis

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闽北水仙茶香气特征及其指纹图谱研究

闽北水仙茶香气特征及其指纹图谱研究

作者：张丹丹福建农林大学

学位级别：硕士

闽北水仙茶是以福建水仙品种为原料,依照闽北乌龙茶采制工艺加工制成的一种条形乌龙茶,是闽北乌龙茶产品最大的品类,占闽北乌龙茶中的60%-70%的比重。闽北水仙茶有三个最著名的产品品类,即武夷水仙、建阳水仙和建瓯水仙,分别产自福建省... 详细信息

闽北水仙茶是以福建水仙品种为原料,依照闽北乌龙茶采制工艺加工制成的一种条形乌龙茶,是闽北乌龙茶产品最大的品类,占闽北乌龙茶中的60%-70%的比重。闽北水仙茶有三个最著名的产品品类,即武夷水仙、建阳水仙和建瓯水仙,分别产自福建省南平地区的武夷山市、建阳区和建瓯市。本研究以上述三个水仙茶产品为研究对象,使用质子传递-反应飞行时间质谱、气相色谱-质谱联用仪和电子鼻三种分析测试手段,并结合数据挖掘技术,研究了闽北水仙茶香气特征,并实现了产地溯源的高准确率判别。主要研究结果如下:1、探究了 PTR-TOF-MS在检测茶叶香气中的分析方法,通过对PTR-TOF-MS分析方法的研究优化,为之后的相关研究提供理论支持。对仪器扫描范围、e/N值、检测样品质量、样品预热温度、时间等参数进行筛选,根据仪器的特性及性能选择最佳扫描范围为:m/z13-500;最佳e/N值为:140Td;最佳样品检测质量为3g;样品最佳预热温度、预热时间分别为:70℃、10min;对比3种不同香气采集方法（干茶法、茶粉法、茶汤法）的PTR-TOF-MS检测结果表明:选择干茶法进行样品检测实验效果最佳,相对标准偏差最小。2、应用优化的PTR-TOF-MS在茶叶中的检测方法,成功将PTR-TOF-MS技术应用于茶叶产地溯源,在无需样品预处理的前提下,采集了3个产地的闽北水仙茶的香气指纹图谱,并初步鉴定了其质量峰,其中3个不同产地的闽北水仙茶的香气以萜烯类含量最高,是构成闽北水仙茶香气特征的主要物质;3个产地水仙茶香气组分相差较小,而大部分香气成分含量的差异达到极显著水平（p＜0.01）,3个产地闽北水仙茶香气总浓度值的排序依次为:武夷山＞建瓯＞建阳;采用SIMCA法、KNN法、PLS-DA法对3个不同产地闽北水仙茶进行模式识别,3种识别模型训练集的识别正确率分别为:86.0%、98.92%、97.84%,测试集的识别正确率均达到76.67%、93.33%、87.67%,其中KNN模法的识别准确率较最高,其次为PLS-DA法,识别效果最差的为SIMCA法,以上PLS-DA模型、KNN模型两个识别模型均有着较好的实际预测效果和应用价值,为建立快速、无损、准确的茶叶产地溯源提供了新方法。3、采用HS-SPMe/GC-MS技术对闽北水仙茶香气进行分析,闽北水仙茶共鉴定出70种香气成分,其中武夷水仙68种、建阳水仙61种、建瓯水仙63种,而武夷水仙茶香气成分数量较多、含量最高,建阳水仙与建瓯水仙的香气成分及含量较为相近。橙花叔醇、芳樟醇、β-紫罗酮、3,5-辛二烯-2-酮是武夷水仙的主要香气成分;橙花叔醇、α-法尼烯、糠醛、（e,e）-2,4-庚二烯醛是建阳水仙的主要香气成分;橙花叔醇、α-法尼烯、芳樟醇、3,5-辛二烯-2-酮是建瓯水仙的主要香气物质。3个产地的闽北水仙茶在香气成分上有较高的相似度,其中橙花叔醇含量是闽北水仙茶最主要的香气成分,占闽北水仙茶香气总含量的9.16～9.81%。将3个产地的闽北水仙茶共有的28种香气成分进行主成分分析,共提取出3个主成分,累计贡献率达到97.93%,聚类分析结果表明建阳水仙与建瓯水仙相似度较高;采用PLS-DA对3个产地的闽北水仙茶进行模式识别,其训练集的正确识别率93.54%,其测试集的正确识别率为76.67%。基本能够实现武夷水仙、建瓯水仙、建阳水仙的有效区分。4、采用e-nose技术对不同产地的闽北水仙茶进行产地识别分析,3个产地的闽北水仙茶香气的电子鼻响应值具有一定的相似性,均在S2、S4、S6、S7、S10等5个传感器中响应值较高,且在这5传感器中的响应值从高到底的排序为:武夷山＞建瓯＞建阳。根据电子鼻数据特征采用Fisher判别模式对不同产地的闽北水仙茶进行识别,结果表明,回代总正判率为93.51%,交叉验证总正判率为91.39%。判别结果表明,通过步进式引入变量建立的Fisher判别函数,具有较高的回代正判率和交叉验证正判率,能够实现武夷水仙、建瓯水仙、建阳水仙的有效区分。5、结合供试茶样的感官品质审评,对PTR-TOF-MS、GC-MS、e-nose三种检测技术在闽北水仙茶中香气检测中的应用进行比较,结果表明:3种检测技术均能对不同产地的闽北水仙茶实现产地溯源,其中PTR-TOF-MS技术效果较好。3种检测技术在茶叶香气检测方面、茶叶产地溯源方面各有其优缺点,三者相互补充、相互应证,为深入研究茶叶香气成分特征以及揭示茶叶香气品质提供了先进的技术支撑。

关键词：乌龙茶闽北水仙茶 PTR-TOF-MS GC-MS e-nose 品质香气成分产地溯源

模拟不同运输条件下大豆的霉变规律及霉变程度的识别

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模拟不同运输条件下大豆的霉变规律及霉变程度的识别

作者：符丽雪黑龙江八一农垦大学

学位级别：硕士

受种植地域以及产量等因素的影响,我国南北地区的大豆供需量差异较大,为维持大豆市场的供应稳定,需要将北方主产区的大豆跨区域运输至南方销售区—“北粮南运”。集装箱运输作为一种经济高效的多模式联运方式被广泛应用。但由于南北气... 详细信息

受种植地域以及产量等因素的影响,我国南北地区的大豆供需量差异较大,为维持大豆市场的供应稳定,需要将北方主产区的大豆跨区域运输至南方销售区—“北粮南运”。集装箱运输作为一种经济高效的多模式联运方式被广泛应用。但由于南北气候差异明显,运输过程中的环境条件复杂难控,因此集装箱内的大豆存在霉变的风险,易导致大豆质量损失,引起经济纠纷。因此,探究大豆在不同运输条件下的霉变规律及大豆霉变的主要影响因素,对大豆的霉变情况进行快速检测和早期预警具有重要意义。本研究以东北大豆为研究对象,探究模拟不同运输条件下集装箱内大豆的霉变规律及影响大豆霉变的主要因素,分离纯化出引起大豆霉变的优势霉菌菌株。利用e-nose和GC-IMS技术分析大豆霉变过程中挥发性有机化合物的组成和含量变化,筛选出用于霉变识别的特征挥发性有机化合物,对大豆的霉变程度进行区分识别。其具体研究结论如下:1.模拟不同运输条件下影响大豆霉变的主要因素为大豆的水分含量、环境温湿度、运输时间以及结露情况。未结露情况下,当大豆的水分含量在安全值以下时,大豆中的霉菌总数受环境温湿度和运输时间的影响较小,不易发生霉变;当大豆的水分含量高于安全值时,大豆中的霉菌总数受环境温湿度和运输时间的影响较大,可能发生霉变。结露情况下,大豆中的霉菌总数与大豆的水分含量显著相关,易发生霉变;水分含量为12%、13%、14%的大豆分别于4、12、24 d发生霉变。运输过程中引起集装箱内大豆霉变的菌群以曲霉属、青霉属和根霉属为主。筛选出的优势霉菌菌株分别为Aspergillus niger（黑曲霉）、Penicillium rubens（产红青霉）、Rhizopus microsporus（小孢根霉）、Penicillium oxalicum（草酸青霉）和Aspergillus versicolor（杂色曲霉）。2.利用电子鼻（e-nose）技术,对不同霉变程度的大豆进行定性和定量分析。以每种优势霉菌接种大豆后放入人工气候箱中培养（30℃、RH=90%）,分别于0、8、16、24 d取样进行e-nose检测,结合主成分分析（PCA）和线性判别分析（LDA）对霉变大豆的气味特征进行分类判别。结果显示,不同霉变程度大豆中的挥发性有机化合物含量不同,主要体现在硫类、氮氧类、甲烷等短链烷烃类以及醇醚醛酮类物质上;PCA和LDA可以区分不同霉菌污染的大豆,起主要贡献作用的传感器为W2W（对有机硫类物质敏感）,其次为W1W（对无机硫类物质响应敏感）、W5S（对小分子氮氧化合物类物质敏感）、W1S（对甲烷等短链烷烃类物质敏感）和W2S（对醇醚醛酮类物质灵敏）;PCA和LDA对不同霉变程度大豆的分类效果较好,LDA建模组和预测组判别准确率分别为97.88%和90.28%。研究结果表明,e-nose技术在不同霉菌污染的不同霉变程度大豆的区分识别上具有可行性。3.用GC-IMS技术对5种优势霉菌的m VOCs和霉变大豆中的挥发性有机化合物进行分析鉴定。从优势霉菌中筛选出了16个特征m VOCs;在霉变大豆中,共检测出54种挥发性有机化合物,包括24种醛类、15种酮类、10种醇类、2种酯类、1种吡嗪和1种芳香类化合物,其中醛类、酮类和醇类物质物质占比较大。随着霉变程度的加深,壬醛、辛醛、癸醛、庚醛、戊醛、甲基-5-庚烯-2-酮、（e）-2-己烯醛、（e）-2-戊烯醛的含量逐渐降低,而苯乙醛、3-甲基-2-丁烯醛、3-甲基丁醛、3-甲硫基丙醛、3-辛酮、1-辛烯-3-醇、2-甲基-1-丙醇、2-甲基-1-丁醇、2-乙基-3,5-二甲基吡嗪的含量逐渐升高,结合优势霉菌特征m VOCs分析,可以此作为大豆霉变程度识别的特征挥发性有机化合物。PCA和聚类结果显示,不同霉变程度的大豆样本挥发性有机化合物容易被区分,霉变程度对挥发性有机化合物的含量变化有明显的影响,此结果与e-nose检测结果一致。实验结果表明,GC-IMS结合化学计量学方法可以有效区分不同霉变程度的大豆样品,在大豆霉变程度的识别上具有可行性。

关键词：大豆霉变规律优势霉菌 e-nose GC-IMS