## 4 Electronic Nose, Electronic Tongue, and Electronic Eye in Sensory Food Sciences
### Electronic Tongue  
The human sense of taste recognizes five basic tastes: sweetness, acidity, bitterness, saltiness, and umami. Sensory panels are commonly used to evaluate food taste, but they can be costly, time-consuming, and subject to bias. To address these challenges, researchers have developed the E-tongue as a fast and objective alternative [79]. An E-tongue is a multi-sensor system consisting of an array of sensors or biosensors combined with multivariate statistical analysis techniques such as principal component analysis (PCA), linear discriminant analysis (LDA), soft independent modeling of class analogy (SIMCA), and partial least squares (PLS) regression. It is widely used for fast, reproducible, quantitative, and qualitative measurements [80]. The E-tongue mimics the human taste system and consists of three main components: a sample preprocessor, similar to the taste receptors in the oral cavity, which converts the characteristics of the liquid sample into electronic signals [81]; a sensor/biosensor array which functions like the neural sensory system, which detects the signals from the preprocessor and transmits them to the data processing unit; and a data processing and pattern recognition system, which analyzes and interprets the collected information. This system includes three key elements: non-specific chemical sensors with partial selectivity, a pattern recognition method for data interpretation, and multivariate calibration for advanced processing [82]. Pattern recognition and classification are performed using measurable electrical signals [83]. The sensor array determines system performance by converting chemical interactions into signal outputs. E-tongues operate in liquid phases using electrochemical techniques like voltammetry, potentiometry, and conductority [84], with potentiometric and voltammetric sensors being the most widely used [85]. While both methods are based on electrochemical principles, voltammetry differs from potentiometry because it involves current flow between electrodes and often produces more complex data. Voltammetry provides higher-orderinformation, including reaction kinetics, but is limited to redox-active species. In contrast, potentiometric sensors are sensitive to charged molecules. Due to their complementary characteristics, hybrid E-tongues have been developed by combining these techniques. A hybrid E-tongue can integrate potentiometric, voltammetric, and/or conductivity sensors and optical, amperometric, mass sensors, and enzymatic biosensors [86]. After collecting signals from all sensor types, chemometric methods are applied to process the data, as the response of each sensor depends on the concentration of multiple components. Combining different sensor types, the hybrid E-tongue provides more comprehensive information about a sample, enhancing reliability, accuracy, and classification precision [86]. Biosensors are also being integrated into hybrid systems. For example, a combination of potentiometric and voltammetric sensors with a multi-enzymatic biosensor has been used to analyze wine samples for the determination of sugars (glucose, fructose, maltose) and fermentation products (ethanol, glycerol) [87]. These hybrid systems have been applied in various fields, including the classification of fermented milk [86], the measurement of NaCl, NaNO\({}_{3}\), and KNO\({}_{3}\) concentrations [88], the monitoring of beer fermentation [89], the quality control of wine [90], the tracking of wine fermentation and storage [91], and the detection of trinitrotoluene (TNT) [92]. For example, ion-selective electrodes have been used to measure pH, carbon dioxide, and chloride ion concentrations in the classification of fermented milk. The voltammetric E-tongue had six working electrodes (gold, iridium, palladium, platinum, rhenium, and rhodium) and an Ag/AgCl reference electrode. Pulse voltammetry was used to record current transients in response to voltage pulses at decreasing potentials [86].