电子鼻判别不同储藏条件下糙米品质的研究

采用德国Airsense 公司生产的PEN3 型电子鼻系统对不同储藏条件下的糙米进行分析检测。通过对传感器响应值进行PCA、LDA 方法的分析,发现PCA 和LDA 均能准确判别出不同水分含量的糙米;PCA、LDA 方法均可判别不同温度储藏的糙米样品,LDA 方法呈现出良好的集中性和单向趋势;LDA 可以很好的区分不同氧气体积分数储藏的糙米样品,并根据氧气体积分数的不同呈现出明显的规律,但总贡献率要低于PCA 方法。另外,通过方差分析发现不同储藏条件对电子鼻响应值的影响大小有所差异,顺序为水分条件＞温度＞氧气体积分数,水分和温度存在交互作用。另外,采用Loadings 分析方法可以得知传感器W5C、W1S 在检测中起到的作用最大,可以对电子鼻的传感器进行优化与选择,根据不同的具体条件选择适当的传感器阵列组合。     

Assessment of cooked alpaca and llama meats from the statistical analysis of data collected using an 'electronic nose'

As part of an EU-funded project to assist in developing the production chain of meat from camelids in South America we have investigated the possibility of using an electronic nose to distinguish between the different types of meat of commercial interest. On-site monitoring of freshly cooked camelid meat using a Bloodhound electronic nose has been carried out in Peru and Bolivia. Sampling was carried out using inert, collapsible plastic bags. Linear discriminant analysis of data generated by the electronic nose classified the samples of meat. Some problems experienced in analysing the data relating to sample size are discussed.     

电子鼻技术在乳品生产与质量控制中的应用

电子鼻能够分析识别和检测复杂风味及成分,检测具有快速、客观、准确等特点。本文介绍电子鼻的基本构成和工作原理,综述其在乳品货架期测定、不同工艺乳品分类、原料乳掺假检验、乳制品中特定成分的测定、乳中微生物分析、不同产地牛乳的区分等乳品生产过程与质量控制中的应用。     

基于电子鼻的红肠风味评价

为应用电子鼻快速、客观地评价红肠风味,使用电子鼻以及顶空固相微萃取和气相色谱-质谱联用对3 个不同生产批次的各批次3 种不同红肠中挥发性物质进行检测分析,并对其进行感官指标评定。采用支持向量机方法对不同红肠样品的电子鼻数据进行识别分类;利用相对气味活度值确定不同红肠中的关键风味物质;用主成分分析方法对红肠挥发性物质整体分析;利用正交偏最小二乘判别分析方法对电子鼻传感器和红肠关键风味的相关性进行分析,并使用逐步回归建立电子鼻与关键风味物质和感官评价指标数据的回归模型。通过支持向量机分析结果可知,电子鼻对不同种类红肠以及不同生产批次同种类红肠均具有良好的区别能力;气相色谱-质谱联用检测出不同种类化合物共117 种;通过相对气味活度值可知不同红肠中的关键风味物质种类差异较大,仅烯丙硫醇是各红肠的共有关键风味物质;主成分分析表明不同种类红肠在总体风味成分上明显不同;感官分析表明不同红肠在不同口感风味评价上存在差异,烟熏味和咸味为红肠最主要的风味;正交偏最小二乘判别分析显示电子鼻传感器数据与关键风味物质具有良好的相关性;建立电子鼻与关键风味物质和感官评价指标回归模型（R2＞0.8,P＜0.01）表明应用电子鼻可以对红肠风味进行评价预测分析。     

电子舌对食醋品质鉴定及区分的研究

醋是我国传统的调味品,醋中的风味是反映其质量的重要部分。为区分不同等级及不同品牌的食醋,测试了市售的同一品牌不同等级的保宁醋,及不同品牌的白醋、老陈醋和香醋对电子舌传感器的响应信号,并采用主成成分分析法(PCA)对响应信号进行分析。结果表明,电子舌传感器能明显的区别出同一品牌不同档次的保宁醋及不同类别的食醋。     

Monitoring sausage fermentation using an electronic nose

In this study a sensor array and pattern recognition routines (an electronic nose) were used to monitor a sausage fermentation in order to follow the changes in emitted volatile compounds during the fermentation process and to compare the electronic nose results with a sensory analysis. From the sensor array responses the fermentation time could be predicted using different methods, where principal component regression and an artificial neural network based on all sensors in the electronic nose performed best. A sensory panel evaluated the final product and these results were compared with the electronic nose measurements in the early stage of the process and on the final sausages. A principal component analysis showed that one of the sausage batches clearly deviated from the other using both the sensory panel data and the electronic nose responses. The deviating batch was different already after 4 h and the difference was consistent during the process. © 1998 SCI.     

电子鼻对奶油酸值的快速测定

介绍了一种快速可行的奶油酸值的测定方法,该方法基于FOX3000型电子鼻对不同酶解程度的奶油做酸值线性模型分析,建立最小回归定量分析模式(PLS)酸值标准曲线,对未知酸值的奶油快速检测,准确性为93.85%,此方法便于实验室和工业化生产使用。     

8种植物油气味指纹模型的建立

运用电子鼻对8种不同加热温度下的植物油进行检测,建立了8种植物油的气味指纹模型,采用线性判别式(LDA)进行分析,通过判别函数法(DFA)对其进行验证。结果表明:电子鼻能够很好地对不同种类以及不同温度的植物油进行区分;在DFA分析中模型对未知样品的识别值大于96%,能对所测的8种植物油样品进行有效地识别,正确率达到100%。电子鼻建立的植物油的气味指纹模型是可靠的。     

不同水解度鸡肉香精的风味研究

以5种不同水解度的鸡骨架水解液为基料,通过美拉德反应制备鸡肉香精。利用感官评价以及电子鼻技术对不同水解度鸡肉香精的风味属性进行评价,并用气相色谱质谱仪(GC-MS)技术分析检测其风味物质。采用主成分分析(PCA)区分不同水解度鸡肉香精,通过偏最小二乘法(PLSR)将感官属性与GC-MS检测得到的风味物质进行相关性分析。感官评定结果表明5种不同水解度鸡肉香精的鸡肉味、脂肪香、大蒜味、辛辣味、酱香味、协调性,整体风味具有显著差异;电子鼻结合PCA分析不同水解度鸡肉香精达到99%的区分度,可以很好的区分辨别不同水解度鸡肉香精;GC-MS分析检测不同水解度鸡肉香精得到82种风味物质,主要包括醛类(17),酮类(7),含氮含硫化合物(12),烯类(15),醇类(19),酯类(2)以及酸类(10)。PLSR分析得到36种风味物质与感官属性相关性较好。实验说明电子鼻,GC-MS结合多元统计分析方法是一项有效的识别不同水解度鸡肉香精的工具。     

A Study on Soluble Solids Content Assessment Using Electronic Nose: Persimmon Fruit Picked on Different Dates

Soluble solids content is an important internal quality attribute in determining fruit maturity and harvesting time. In this study, an electronic nose was used to monitor the soluble solids content based on the change of volatile compounds of persimmon fruit during different picking-dates. Principal component analysis was applied to investigate whether the sensors’ response of the electronic nose was able to distinguish persimmons among different picking dates corresponding to different maturity levels. The loading analysis was used to identify those sensors that contribute most for flavor modeling. The results indicated that the electronic nose could distinguish the different picking dates using principal component analysis. The model testing showed that a support vector machine could achieve better prediction accuracy and generalization than multiple linear regression and back-propagation neural network and the average prediction accuracy, root mean square error, and mean relative error of the soluble solids content. By using support vector machine models were 91.36, 0.71, and 0.58%, respectively, which implied that the electronic nose was effective for soluble solids content prediction of persimmons on the basis of the support vector machine model.     

Use of electronic nose and trained sensory panel in the evaluation of tomato quality

In this paper the performances of an electronic nose based on metalloporphyrin‐coated quartz microbalance sensors and of an experienced panel of seven human assessors in the evaluation of gases derived from degradation reactions in tomatoes are presented and discussed. The performances are measured in terms of the capability of both systems to distinguish between samples of different quality coming from conventional and organic production systems. The study deals with the application of pattern recognition techniques based on either multivariate statistical methods (PCA, GPA) or artificial neural networks using a self‐organising map (SOM). The response pattern of the sensor array and the sensory data are analysed and compared using these methods. Similarities in the classification of the data by electronic nose and human sensory profiling are found. © 2000 Society of Chemical Industry     

电子舌技术在普洱散茶等级评价中的应用

为了探讨茶叶的感官审评结果与电子舌测定结果的相关性,3个等级的云南普洱散茶分别被用于感官审评以及电位型电子舌的检测.电子舌测定结合主成分分析法(PCA)的结果显示,在第一和第二主成分的得分图上,电子舌可以区分特征十分相近的不同等级的普洱茶.同时对感官与仪器分析数据进行PCA分析后,找到了与不同等级茶叶感官品质相关性较高的传感器.因此,电子舌有望应用于茶叶生产的在线检测,以保证质量的一致性与分等分级的客观性.     

基于电子鼻对酥油贮藏期间质量变化规律的研究

利用电子鼻技术,以产自内蒙古的酥油为原料,对4、25、32℃贮藏期间的酥油质量变化进行研究,并配合感官评价、酸值、过氧化物值指标进行检测,探讨电子鼻用于酥油贮藏期间质量变化的可行性。结果表明：32℃酥油在4个月左右的贮藏期内,酸值上升最明显,过氧化物值先上升后下降,在贮藏后期发生酸败,产生哈败味道无法食用。而在4℃贮藏时,酥油各项化学指标变化不明显。同时,使用电子鼻对不同温度相同贮藏期的样品的顶空气味进行指纹分析。采用电子鼻分析系统中的线性判别法聚类模型分析相关数据,结果与理化指标的检测存在很高的相似性,证明电子鼻可用于酥油的质量监控。     

不同工艺热反应风味香料的电子鼻检测

为评价不同反应工艺对天然香料风味的影响,首先通过正交试验,研究以香菇提取液为基料,结合其它前体物质进行Maillard反应制备新型风味调料,再通过电子鼻PEN3系统动态采集9组不同香料芳香成分,得到电子鼻的响应值,采用PCA、LDA模式识别方法进行数据分析。结果表明,在基本配方条件下,添加赖氨酸、木糖和甘油,在110℃条件下热反应120min,可制得风味浓郁的新型风味调料,利用电子鼻能够无损检测并区分不同处理工艺的热反应香料。     

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).     

基于电子舌和电子眼结合改进MobileNetv3的黄芪快速溯源检测

目的:实现对不同产地黄芪的快速溯源检测。方法:提出了一种基于电子舌和电子眼结合改进MobileNetv3网络的黄芪产地快速检测方法。采用电子舌和电子眼分别采集不同黄芪样本的一维指纹图谱信息和二维外观图像信息。利用格拉姆角场(Gramian angular field, GAF)将一维电子舌信号转换为二维图像信息，保留电子舌信号中时间序列相关特征，再将其与电子眼采集的图像信息进行数据融合，采用基于金字塔切分注意力机制(Pyramid split attention, PSA)改进的MobileNetv3模型实现对不同产地黄芪样本的分类识别。结果:相较于单独使用电子舌或者电子眼，该方法具有更高的识别准确率，其测试集准确率、精确率、召回率和F₁-Score分别达到98.8%,98.8%,98.8%和0.99。改进的MobileNetv3网络分类准确率较原始模型提高了8%,参数量仅为原参数量的20%左右。结论:改进的MobileNetv3网络可以有效减少参数的计算量，提高不同产地黄芪识别的准确率。     

利用电子鼻区分不同产地、不同品种的烤烟

为了探索区分不同产地、不同品种烤烟的有效方法,利用电子鼻检测了3个地区（贵州、云南、辽宁）共70种烤烟样品的挥发性成分,并对电子鼻采集数据分别进行主成分分析、聚类分析和判别函数分析。通过判别函数分析方法所建立模型对测试集样品的正确判别率达到91.7%,结果表明电子鼻方法可以有效地区分不同产地、不同品种的烤烟,该方法可为人工鉴定烤烟提供参考。      

Application of the electronic nose to the identification of different milk flavorings

In this paper, studies were conducted to determine the odor profile feature of five commercial milk flavorings (three natural milk flavorings and two synthetic flavorings) and one self-made enzyme induced milk flavoring prepared by lipolyzed milk fat. The discrimination of different flavor analysis methods was also evaluated. The ability of an electronic nose consisting of 18 metal oxide semiconductor (MOS) sensors to correlate with the solid phase micro extraction gas chromatography mass spectrometry (SPME-GC–MS) analysis and the sensory test of different milk flavorings was determined. The principal component analysis (PCA) of electronic nose sensor data has been compared with the data provided by GC–MS and sensory analysis. The results indicate that the electronic nose sensors can clearly and rapidly distinguish the difference among the synthetic milk flavorings, the natural milk flavorings and the enzyme induced milk flavoring. And the discrimination among different natural milk flavorings, which were easily confused by sensory tests, was also well performed by the electronic nose.     

基于味觉特征的黄酒酒龄鉴别方法研究

为对黄酒酒龄进行鉴别,采用电子舌结合化学计量学方法建立了酒龄鉴别方法。采用电子舌采集了不同酒龄黄酒样品的味觉指纹信息,对比分析了不同清洗溶液对电子舌响应信号的影响,采用主成分分析和判别因子分析法建立了酒龄鉴别模型。分析结果表明：采用10％的酒精做清洗溶液时,数据点较集中,重复性较好;判别因子法所建酒龄鉴别模型中1年陈、3年陈和5年陈样品集的鉴别正确率均为100％。研究表明：电子舌结合化学计量学方法可较好地用于黄酒酒龄鉴别。