# Electronic Sensing Technologies in Food Quality Assessment: A Comprehensive Literature Review
## 6 e-Eye  
The appearance of food refers to how it is visually perceived, including its color, structure, surface texture, and morphological features. These aspects are influenced by physical, chemical, microbiological, and sensory changes, which indicate product quality [6]. e-Eye systems can analyze surface texture in ways that exceed the human eye's capabilities, examining characteristics such as graininess, smoothness, and roughness. Furthermore, appearance is crucial for describing fresh food products in terms of their structure. While it is not always feasible to cover all measurable features since they vary depending on the specific product and the purpose of the analysis, understanding these attributes is essential [158]. e-Eye is a modern technology that offers several advantages, including sample preservation, user-friendliness, non-invasiveness, minimal or no sample preparation, and the capability to generate and permanently store high-quality images. However, there are some disadvantages to consider. This tool must be operated in a controlled environment devoid of light to prevent interference. Additionally, it can only assess one side of the samples at a time and requires careful attention to separate the background to obtain accurate data. Regular calibration is also necessary to ensure optimal performance [159; 160]. Images captured by e-eye typically result from colorimetric, spectrophotometric, or computer vision measurements. The most commonly used color space in the food industry is L*a*b*. Spectrophotometers measure the entire spectrum of a sample within the visible range, and using mathematical conversions, the results are expressed as color coordinates in the L*a*b* format. The computer vision system comprises a lighting setup, a digital RGB camera, a sample holder, and the necessary hardware and software for image acquisition and processing. The camera sensors convert the intensity of the incident light into an electrical signal [161]. Examples of the use of e-eye to assess food quality, along with the results obtained, are presented in Table 5. \begin{table}
\begin{tabular}{c c c} \hline
**Device Type/Sensors Used** & **Application** & **Quantitative Metrics** & **References** \\ \hline IRIS VA400 E-eye (Alpha MOS, & Characterization of the & A total of 40 characteristic colors were & \\ Toulouse, France) & different quality levels of & distinguished, mainly reddish-brown, & [98] \\ \hline A system consisting of an electronic & A method for detecting the & & \\ eyepiece (aperture: f/2.5) equipped & geographical origin of black & & \\ with a 5 million-element CMOS & pepper, which involves the & & Relationships between sensory \\ (complementary metal oxide & synergistic use of ET, EN, and & characteristics of black pepper and & [162] \\ semiconductor) sensor, a holder, a light-emitting diode (LED) lamp, an LED lamp switch, and image & EE together with CNN and & & \\ processing software & CAM incorporated into deep & & \\ \hline Combination of 3 intelligent & Understanding the impact of & Fast, non-destructive, and intelligent \\ sensory techniques (e-eye, e-nose, and e-tongue) with multivariate & different processing methods & sensory technology introduced in the & \\ statistical methods & on the sensory quality & & \\ of chestnuts & of N\({}_{2}\) packaging on the browning of & \\ chestnuts after cooking & & \\ \hline \end{tabular}
\end{table} 
Table 5: Application and obtained effects of the e-eye system. The quality of the e-eye system relies on several components, including the electronics, camera, frame grabber, and lighting system. Depending on their application, CCDs can vary in construction types (such as linear, interline, and frame transfer) and resolutions (which refers to the number and size of pixels). A properly designed lighting system is crucial as it enhances the analysis's precision and minimizes artifact occurrence.