# Electronic Sensing Technologies in Food Quality Assessment: A Comprehensive Literature Review
## 4 e-Nose  
In the 1980s, research on machine olfaction led to the accepted definition of e-nose as a device with a variety of electrochemical gas sensors with partial specificity and a pattern recognition system [7]. In order to meet practical needs, an e-nose using nanomaterials was developed, which was inspired by the mammalian sense of smell [72], standing out as a promising biomimetic device [73; 74; 75]. Its original design goal was to capture specific odor molecules in the air to enable the recognition of various gases. Importantly, e-nose technology has developed very rapidly over the last thirty years [76; 77; 78; 79; 80]. The e-nose concept has gone from its original form to the development of materials and identification methods. Activities related to the commercialization of e-noses have forced efforts to reduce their costs and to give the expanded stationary devices smaller dimensions, which would allow for their mobile use, e.g., in plantations or processing plant conditions. These devices are cost-effective, portable, easy to operate, and above all, allow for rapid analysis [7; 81]. The stages of e-nose evolution are presented in Figure 1. Examples of e-nose use in food quality assessment and the obtained results are presented in Table 1. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Device Type/Sensors Used** & **Application** & **Quantitative Metrics** & **References** \\ \hline BME680 from Bosch, SGP30 from Sensirion, & & & \\ and CCS811 and iAQ-Core from ScioSense/4 & Abnormal fermentations & Consistency with the results & \\ digital gas sensors with integrated & occurring in table dives & obtained by the tasting panel & [82] \\ MOX sensors & & & \\ \hline MOS & Moldy bread detection & 100\% accuracy & [83] \\ \hline E-nose equipped with a space automation & & & \\ system above the surface and & & & \\ 18 MOS sensors & & & \\ \hline
8 MOS gas sensors: & & & \\ (1) two types of Taguchi (Figaro Engineering & & \\ Inc., Osaka, Japan) sensors (TGS813 and & & & \\ TGS822); (2) five types of MQ sensors (MQ3, MQ4, MQ8, MQ135, and MQ136) (Hanwei & Olive oil classification and & 97.75\% accuracy in the test result & [85] \\ Electronics Group Corporation, China); and & & & \\ (3) one FIS sensor (NISSHA FIS, Inc., Tagawa, Yodogawa-ku, Osaka, Japan) & & & \\ \hline
10 MOS sensors with different sensitivities & Identification of instant & Explained 86.96\%, 98.09\%, and & \\  & starch noodle spices based & 94.38\% of the total variance, and & \\  & on different flavor profiles & the CA results were consistent & \\  & & & with the PCA results \\ \hline MOS sensors: MQ4, MQ5, MQ9, and MQ135 & Evaluation of the shelf life & Exceeding the threshold value on & [87] \\  & of various edible seeds & the 120 th day of storage & \\ \hline  & & Rapid detection, low sample & \\  & & requirement, and no & \\  & & pre-treatment required; & \\ Heracles Analyzer Neo (Alpha Mos, & Characteristics of vinegar & disadvantages include difficulty & \\ Toulouse, France) & quality and volatility & in absolute quantification of & \\  & & components and inability to & \\  & & determine inorganic & \\  & & flavor components & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Applications and obtained effects of the e-nose system. Figure 1: The development of e-nose technology. Developed on the basis of [81].