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When partaking of any food or beverage, we actually perceive its flavour, which is the combined effect of aroma and taste. This parallel processing of signals from our nose and tongue is possible due to the presence of large and complex biological neural networks in our brain. Artificial perception of odor and taste is attempted by the scientists using similar techniques, and is implemented with an array of sensors and an array of electrodes known as electronic nose and tongue, respectively. Fusion of electronic nose and tongue at various levels provides improved results for various applications This review article discusses different techniques of fusing electronic nose and tongue information as well as applications of the combined system in different fields. [ABSTRACT FROM AUTHOR]

The feasibility of sensors (Electronic Nose, EN; Electronic Tongue, ET) and spectra (Near Infrared spectrum, NIR; Mid Infrared spectrum, MIR) to evaluate raw honey samples (Vitex, Jujube and Acacia) was explored. Partial least squares discriminant analysis (PLSDA) model, support vector machine (SVM) algorithms model and Interval partial least squares (iPLS) model were used to classify the botanical origin. The results indicate that spectra and sensors could classify the botanical origin of honey rapidly and accurately, since total accuracy for calibration and prediction sets was all almost 100% in EN and ET analysis by SVM model and in NIR and MIR analysis by iPLS model. Then principal components analysis (PCA) and PLSDA model were used to determine the adulterants. Total accuracy for calibration and prediction sets was all above 96% in NIR, MIR and ET by PLSDA model. The results indicate that ET is more suitable for detecting honey adulteration. [ABSTRACT FROM AUTHOR]

Electronic nose (E-nose), Electronic tongue (E-tongue) and Computer Vision System (CVS) are three analytical systems which have been used separately in the food and pharmaceutical industries as quality evaluation methods. The E-nose and E-tongue are designed to mimic the mammalian olfactory and taste systems, both containing sensors that non-selectively interact with flavor molecules to produce some sort of electronic signals. The produced signals are related to the material quality or its main chemical components. The major aim in the use of CVS is to realize the mode of operation of human vision and is based on image analysis to extract some specific attributes as quality features. The extracted color and flavor features are analyzed in a computer using multivariate data analysis to recognize patterns in the data. Since these three systems are non-destructive, rapid, economic and consistent, their fusion can form a powerful and objective inspection tool able to out-perform the individual constituting techniques. The combined evaluation technique has a variety of applications replacing the systems that may not have sufficient performance individually for specific uses. Application of these three techniques are individually reviewed with emphasis on the fusion of the artificial senses. Spectroscopy methods which are also covered can be coupled with these artificial senses to enrich the extracted information from the food industry. [ABSTRACT FROM AUTHOR]

Highlights: [•] Seven techniques were applied for evaluation adulteration of tomato juices. [•] Sensor drift and humidity problems were considered. [•] Different feature selection and data fusion methods were discussed. [ABSTRACT FROM AUTHOR]