Background:An e-nose or an e-tongue is a group of gas sensors or chemical sensors that simulate human nose or human tongue.Both e-nose and e-tongue have showngreat promise and utility in improving assessments of food ...Background:An e-nose or an e-tongue is a group of gas sensors or chemical sensors that simulate human nose or human tongue.Both e-nose and e-tongue have showngreat promise and utility in improving assessments of food quality characteristics compared with traditional detection methods.Scope and approach:This review summarizes the application of e-nose and e-tongue in determining the quality-related properties of foods.The working principles,applications,and limitations of the sensors employed by electronic noses and electronic tongueswere introduced and compared.Widelyemployed 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 review.Key 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 quality.The user of e-nose and e-tongue need to strictly control sample preparation,sampling,and data processing.展开更多
文摘Background:An e-nose or an e-tongue is a group of gas sensors or chemical sensors that simulate human nose or human tongue.Both e-nose and e-tongue have showngreat promise and utility in improving assessments of food quality characteristics compared with traditional detection methods.Scope and approach:This review summarizes the application of e-nose and e-tongue in determining the quality-related properties of foods.The working principles,applications,and limitations of the sensors employed by electronic noses and electronic tongueswere introduced and compared.Widelyemployed 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 review.Key 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 quality.The user of e-nose and e-tongue need to strictly control sample preparation,sampling,and data processing.
文摘目的研究浓香、酱香、清香型白酒挥发性风味的特征与差异的物质基础。方法利用气相色谱-离子迁移谱法(gas chromatography-ion mobility spectrometry,GC-IMS)、气相色谱-氢火焰离子检测器(gas chromatography-flame ionization detector,GC-FID)、电子鼻(E-nose)结合感官评定手段研究浓、酱、清香型白酒的挥发性风味成分。结果GC-IMS和GC-FID在3种香型白酒样品中共鉴定出73种挥发性化合物,主要为酯类、醇类、酮类和醛类物质;浓香型白酒中的己酸乙酯、己酸含量较高;酱香型白酒物质种类最为丰富,含有多种长链脂肪酸与脂肪酸酯;清香型白酒中物质种类相对较少,乳酸乙酯、乙酸乙酯在其中含量较高;借助偏最小二乘法-判别分析从39种骨架物质中筛选出16种变量投影重要性(variable important in projection,VIP)值大于1的差异标记物用以区分浓香、酱香、清香型3种香型白酒,分别为甲醇、正己醇、辛酸乙酯、戊酸、乳酸乙酯、丁酸、庚酸乙酯、异戊醇、壬酸乙酯、乙酸、己酸乙酯、辛酸、庚酸、戊酸乙酯、甲酸乙酯和乙醛。结论本研究建立了3种香型白酒的可视化指纹图谱,阐明浓香、酱香、清香型白酒中特征挥发性风味物质与其含量差异。
