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.     

电子舌对掺入果葡糖浆掺假蜂蜜的识别

采用电子舌对不同蜂蜜以及掺入果葡糖浆的蜂蜜样品进行测定,对所获得的数据进行主成分分析、判别因子分析和偏最小二乘回归分析。结果表明:电子舌能够区分不同蜂蜜样品和掺假蜂蜜样品(果葡糖浆掺入比例≥5%);对掺假蜂蜜样品建立了偏最小二乘回归分析预测模型,电子舌响应信号和果葡糖浆掺入比例之间有很好的相关性(决定系数R2为0.992 0),偏最小二乘回归分析模型预测误差均≤5%(掺入比例为10%~70%)。试验证明电子舌可用于掺入果葡糖浆的掺假蜂蜜的识别。     

Monitoring of physical–chemical and microbiological changes in fresh pork meat under cold storage by means of a potentiometric electronic tongue

This work describes the correlation found along 10 days between potentiometric measurements obtained by using an electronic tongue and the variation in certain physicochemical, microbial and biochemical parameters measured on a whole piece of pork loin stored under refrigeration. The electronic tongue consists of a set of six electrodes made of Au, Ag, Cu, Pb, Zn and C, and a reference electrode. Through the use of various multivariate analysis techniques, such as: PCA and two types of artificial neural networks (i.e. multilayer perceptron (MLP) and fuzzy ARTMAP) it was found that it is possible to determine the time elapsed in relation to the degradation of the loin by using simple potentiometric measurements. Additionally, in the same pork sample used to measure redox potentials with the electronic tongue, the following parameters were also determined; pH, microbial count, concentrations of inosine 5′-monophosphate (IMP), inosine (Ino) and hypoxanthine (Hx). Through the use of PLS analysis, it was found a rather good correlation between pH and the potentiometric data. Also a remarkable correlation was observed between the measures carried out with the electronic tongue and the so-called K-index that simultaneously measures the variation in the adenosine triphosphate (ATP) degradation products. These results suggest that this simple, or a similar electronic tongue, could be useful for the undemanding qualitative or semi-quantitative evaluation of freshness in meat samples in a wide range of situations.     

Use of an electronic tongue and HPLC with electrochemical detection to differentiate molds in culture media

A study was conducted to further evaluate an electronic tongue, using high-performance liquid chromatography (HPLC) with electrochemical (EC) and UV detection as a reference method. The electronic tongue consisted of four working electrodes made of different metals and arranged in a standard three-electrode configuration. Pulses of voltage were applied to the metals, and the current responses were sampled and collected in a data matrix. The objectives of the present investigation were to examine the ability of the electronic tongue to distinguish between two mold species growing in three different media, and to obtain support for the hypothesis that the device actually discriminates between different redox-active metabolites produced by the molds. Peak areas in EC and UV HPLC chromatograms were collected in a data matrix. The electronic tongue data and the EC and UV data were then subjected to principal component analysis (PCA). A number of peaks in the HPLC-EC chromatograms indicated that the growth media contained redox-active metabolites. Moreover, PCA of peak areas in EC chromatograms revealed differences between the distribution of redox-active metabolites produced by the two species and between the three culture media. The same pattern was apparent in a PCA score plot of electronic tongue data. The peaks in the UV and EC chromatograms differed, and these were also shown by the PCA score plots.     

Discrimination of edible fungi varieties and evaluation of their umami intensities by using an electronic tongue method

The flavour and taste of edible fungi are highly associated with the presence of several umami substances. In this study, the different edible fungi are discriminated by an electronic tongue method. The response data are analysed by the PCA (principal component analysis), DFA (discriminant factor analysis) and PLS (partial least square) method. The results show that the two data analysis methods (PCA and DFA) could successfully distinguish the variety of edible fungi. Moreover, the umami intensities of the edible fungi solutions are evaluated and compared by an electronic tongue analysis with calibration by the responses of different monosodium glutamate (MSG) concentrations. The signals are also used to build up PLS models to estimate and predict the umami intensities of the edible fungi. The results of this study indicate that the electronic tongue has a great potential in qualitative and quantitative analysis of the sensory quality of edible fungi.     

电子舌识别技术对腌制黄瓜调料的定量化分析

采用一种基于电子舌识别技术的方法对腌制黄瓜中盐、总酸、还原糖和乳酸钙进行定量分析。采用PLS分析和BP-ANN分析对数据进行处理,建立并对比了两种预测模型。结果表明,PLS模型和BP-ANN模型均具有较好的预测能力,相关系数(R2)均在0.9以上。对于盐和乳酸钙,两种模型适用性相似;对于总酸,BP-ANN模型优于PLS模型;对于还原糖,PLS模型优于BP-ANN模型。该研究为电子舌识别技术在腌制黄瓜调料定量化分析中应用的可行性提供了理论依据。     

基于电子舌技术对信阳毛尖茶品质的评价

采用电子舌技术对磨盘山和狮河口两种信阳毛尖茶(各五个等级)进行了检测。采用主成分分析法(PCA)并结合区别指数考察了电子舌对两种毛尖茶的等级区分效果,建立了茶叶等级识别的偏最小二乘(PLS)判别模型。各四个等级的磨盘山茶样与狮河口茶样在PCA得分图上得到了良好区分,区别指数分别为78.94和84.22;对两种茶进行等级判定的PLS模型相关系数均大于0.9,且模型对\     

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。     

电子舌对鸡汤和人工勾兑高汤及其混合样品的识别

运用电子舌对鸡汤与人工勾兑高汤及其混合样品进行识别,对所获得的数据进行主成分分析、判别因子分析和偏最小二乘回归分析。结果表明:电子舌能够有效识别鸡汤与各种人工勾兑的汤,以及其混合样品;对不同混合比例的鸡汤建立了偏最小二乘回归分析预测模型,电子舌响应信号和鸡汤混合比例之间有很好的相关性(相关系数为0.958 71),偏最小二乘回归分析模型预测误差在15%以内。证明电子舌可用于鸡汤与人工勾兑汤的识别。     

采用电子舌法检测橙汁及白酒的品牌及纯度

模仿人类味觉感知机理,研制了一套基于虚拟仪器和物联网的饮料质量电子舌检测系统。系统检测时,首先利用传感器阵列对样本进行大幅脉冲扫描,以获取对各类橙汁及白酒的味觉\     

电子舌对啤酒的区分识别研究

采用电子舌对不同品牌的啤酒及其混合样品进行识别,对所获得的数据进行主成分分析、判别因子分析和偏最小二乘回归分析。结果表明：电子舌能够有效识别不同品牌的啤酒及不同品牌啤酒的混合样品;对不同品牌啤酒的混合样品建立了偏最小二乘回归分析预测模型,电子舌响应信号和啤酒混合比例之间有很好的相关性(相关系数为0.9436),偏最小二乘回归分析模型预测误差在1.43%～3.00%之间。证明电子舌可用于啤酒的识别。     

基于电子鼻和电子舌的白酒检测

研究利用电子鼻和电子舌技术快速检测白酒品质。以不同品牌、不同香型和不同比例掺假白酒为检测对象,采用主成分分析、线性判别分析和偏最小二乘法对电子鼻整体气味响应图谱和电子舌在1、10、100和1000Hz四个不同频段脉冲激发下的金、银、钨、钛四个工作电极组成的传感电极阵列响应信号进行分析。结果显示:电子舌对不同品牌和不同香型白酒的区分能力要优于电子鼻,且LDA的识别效果较PCA更好;利用偏最小二乘法建立的定量预测模型,在主成分数取5时,电子舌所建模型最优。用独立样品检验模型精度,模型预测值和参考值的相关系数为0.881。研究结果可为白酒生产和销售过程中的质量监控提供支持。     

电子舌与真实味觉评价的差异性研究进展

电子舌作为研究液体样品味觉信息的新型分析检测设备,近年来已经在食品领域得到了较为广泛的应用。文章介绍电子舌技术的基本原理,与真实味觉评价方法的异同点,相关设备研究应用现状,以期为开发商业化应用的电子舌设备提供新的思路。     

电子舌技术在饮料识别中的应用

电子舌技术是一种分析、识别液体味道的新型检测手段,在饮料识别中的应用日益广泛。介绍了电子舌技术的基本原理,综述了电子舌在饮料识别中的应用,展望了电子舌技术在饮料识别中的发展趋势和应用前景,并指出了电子舌技术在实现过程中所需要解决的问题。     

Is ergosterol a new microbiological quality parameter in foods or not?

One of the most important spoilage factors of foods is molds. Therefore, it is important to determine the presence of mold in foods quickly because of the deterioration of aroma, flavor, appearance, and textural structure as well as the mycotoxins, which are toxic secondary metabolites of molds. Twenty-five percent of agricultural products worldwide are infected with mycotoxins directly or indirectly. With the global population increasingly rising, the need for access of safe and adequate food in the future has great importance. Quantification of ergosterol, a constituent of the membrane of molds and a precursor of vitamin D₂, is a feasible method for determination of fungal contamination in foods. The aim of this review is to discuss the possibility of using ergosterol as an indicator of mold growth in foods.     

Evaluation of an artificial olfactory system for grain quality discrimination

A commercially available Cyranose-320™ conducting polymer-based electronic nose system was used to analyze the headspace from stored barley samples. Three types of barley samples were analyzed, namely, clean barley, naturally Fusarium infected barley and Fusarium inoculated clean barley. The barley samples were stored at moisture contents of 13, 18, 20 and 25 g of water/100 g sample. The raw signals obtained from the electronic nose system were pre-processed by various signal-processing techniques to extract area-based features. Principal component analysis was subsequently performed on the processed signals to further reduce the dimensionalities. Classification models using linear (LDA) and quadratic discriminant analyses (QDA) were developed using the extracted features. The performance of the developed models was validated using leave-1-out cross validation and bootstrapping method. The models classified the barley samples stored into two groups based on the ergosterol content, i.e., “acceptable” (ergosterol content <3.0 μg/g) and “unacceptable” (ergosterol content ?3.0 μg/g). Overall, the total maximum classification accuracy obtained was 86.8% by both LDA and QDA when leave-1-out cross-validation was used. By bootstrapping validation the maximum total classification accuracy obtained was 86.4% and 86.1% respectively, by QDA and LDA. The study proves that there is potential in using an electronic nose system for indicating mold spoilage in stored grains, and necessitates future studies in this direction.     

基于电子舌与电子鼻评价烘培时间对黄秋葵籽风味品质的影响

分析不同烘焙时间对黄秋葵籽滋味、气味的影响,采用电子舌法、电子鼻法结合感官评定比较分析黄秋葵籽风味品质的变化。结果表明:电子舌与电子鼻对不同烘焙时间下的黄秋葵籽风味特征呈现不同的响应值,电子舌中涩味的特征向量值最高为0.88,电子鼻对硫化物响应最强;黄秋葵籽烘焙25 min的感官评定总体风味较佳。电子舌PCA分析能较好地区分不同烘焙时间下的黄秋葵籽测试液,而电子鼻的PCA和LDA分析对测试液的区分均存在重叠区,区分性不好。感官评定与电子舌检测的结果对于烘焙时间引起黄秋葵籽的滋味的变化均得到了较好的区分。感官评定与电子鼻检测的结果对于烘焙时间引起黄秋葵籽的气味的变化区分效果均不好。不同烘焙时间下黄秋葵籽感官评定的结果具有差异性,电子舌和电子鼻分析结果与感官评定结果相比较风味品质的检测结果相近。     

麦角甾醇的研究进展

麦角甾醇主要存在于酵母菌、霉菌等真菌和某些植物中,是一种重要的植物甾醇,具有重要的生理作用,是食品、饲料及医药等工业中常用的一种原料。文章总结近十年来国内外对麦角甾醇的研究状况,分别对麦角甾醇的生物合成途径、高产麦角甾醇菌株的选育和麦角甾醇的萃取方法予以综述,为进一步研究麦角甾醇提供参考。     

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。      

响应面法优化根霉菌产麦角固醇的液体发酵工艺

以米根霉(Rhizopus oryzae ZW017)发酵产麦角固醇的产量为响应值,对其液体发酵工艺进行优化。采用HPLC法检测菌株产麦角固醇含量,在单因素筛选试验基础上,以PDB液体发酵培养为基础条件,应用响应面分析法(RSM)对碳源、氮源及发酵时间进行优化。结果表明:以葡萄糖、酵母膏分别为最佳碳、氮源;最佳工艺条件为:PDB基础培养基中添加葡萄糖3g/L、酵母膏5g/L、发酵培养9.64d,麦角固醇平均产量达5761.83μg/100mL,较优化前提高了247.86%,与构建模型理论预测值(5818.39μg/100mL)相吻合,且100mL液体培养基中麦角固醇产量占菌体细胞干质量(0.36g)的1.60%。