Electronic Sensing Technologies in Food Quality Assessment: A Comprehensive Literature Review
Source abstract
Abstract
This manuscript was prepared for the purpose of an in-depth analysis of the development of electronic sensors in food quality assessment. In this study, the following research question was asked: What are the arguments for the development of electronic sensors for food assessment? The aim of this work was to comprehensively review the current scientific literature presenting the discussed issues and their systematization, as well as to present the prospects, threats, and applications of electronic sensors in food quality testing. The greatest interest of researchers lies in the use of e-nose. In contrast, fewer publications concerned e-tongue applications, and the smallest number of works concerned e-eye application. The initial application of electronic sensors in the food industry progressed from research on the identification of single ingredients or properties to the creation of increasingly complex research instruments that comprehensively analyze areas of food characteristics. Specifically, e-sensor research has focused on individual e-nose, e-tongue, and e-eye devices and has not provided complete information about food. This is confirmed by the high accuracy of research results regarding the combined use of sensors in food quality assessment.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Chemical Sensor Technologies · Spectroscopy and Chemometric Analyses · Identification and Quantification in Food
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Agricultural Processing and Commodity Science, Institute of Food Technology and Nutrition, Faculty of Technology and Life Sciences, University of Rzeszów, Zelwerowicza 4, 35-601 Rzeszow, Poland
References (100+)
Show source-provided references
1. Latest Advances in Imaging Techniques for Characterizing Soft, Multiphasic Food Materials10.1016/j.cis.2020.102154 ↗
2. Electronic Nose and Its Application in the Food Industry: A Review10.1007/s00217-023-04381-z ↗
3. Electronic Tongue and Electronic Nose for Food Quality and Safety10.1016/j.foodres.2022.112214 ↗
4. Class, L.-C., Kuhnen, G., Rohn, S., and Kuballa, J. (2021). Diving Deep into the Data: A Review of Deep Learning Approaches and Potential Applications in Foodomics. Foods, 10.10.3390/foods10081803 ↗
5. Advancement of Metal Oxide Nanomaterials on Agri-Food Fronts10.1016/j.scitotenv.2024.172048 ↗
6. E-Sensing Systems for Shelf Life Evaluation: A Review on Applications to Fresh Food of Animal Origin10.1016/j.fpsl.2023.101221 ↗
7. Electronic Noses for Food Quality: A Review10.1016/j.jfoodeng.2014.07.019 ↗
8. Li, Y., Ye, Z., and Li, Q. (2023). Precise Identification of Food Smells to Enable Human–Computer Interface for Digital Smells. Electronics, 12.10.3390/electronics12020418 ↗
9. Lab-on-a-Chip Technologies for Food Safety, Processing, and Packaging Applications: A Review10.1007/s10311-021-01342-4 ↗
10. Applications of Artificial Intelligence and Machine Learning in Food Quality Control and Safety Assessment10.1007/s12393-023-09363-1 ↗
11. Sensors, Society, and Sustainability
12. Huang, W., Yin, M., Xia, J., and Zhang, X. (2024). A Review of Cross-Scale and Cross-Modal Intelligent Sensing and Detection Technology for Food Quality: Mechanism Analysis, Decoupling Strategy and Integrated Applications. Trends Food Sci. Technol., 151.10.1016/j.tifs.2024.104646 ↗
13. Method of Reaching Consensus on Probability of Food Safety Based on the Integration of Finite Credible Data on Block Chain10.1109/ACCESS.2021.3108178 ↗
14. Humans Can Discriminate More than 1 Trillion Olfactory Stimuli10.1126/science.1249168 ↗
15. Applications of Electronic Nose (e-Nose) and Electronic Tongue (e-Tongue) in Food Quality-Related Properties Determination: A Review
16. A Review of Environmental Occurrence, Toxicity, Biotransformation and Biomonitoring of Volatile Organic Compounds10.1016/j.enceco.2021.01.001 ↗
17. A Mechanistic Review on Machine Learning-Supported Detection and Analysis of Volatile Organic Compounds for Food Quality and Safety10.1016/j.tifs.2023.104297 ↗
18. Novel Techniques for Evaluating Freshness Quality Attributes of Fish: A Review of Recent Developments10.1016/j.tifs.2018.12.002 ↗
19. Molecular Characterisation of Interactions between β-Lactoglobulin and Hexanal—An off Flavour Compound10.1016/j.foodhyd.2023.109260 ↗
20. Flavor Formation and Regulation of Peas (Pisum sativum L.) Seed Milk via Enzyme Activity Inhibition and off-Flavor Compounds Control Release10.1016/j.foodchem.2022.132203 ↗
21. Liu, J., Nam, Y., Choi, D., Choi, Y., Lee, S.-E., Oh, H., Wang, G., Lee, S.H., Liu, Y., and Hong, S. (2024). MXene/Hydrogel-Based Bioelectronic Nose for the Direct Evaluation of Food Spoilage in Both Liquid and Gas-Phase Environments. Biosens. Bioelectron., 256.10.1016/j.bios.2024.116260 ↗
22. Neural-Network-Integrated Electronic Nose System for Identification of Spoiled Beef10.1016/j.lwt.2005.01.002 ↗
23. Tibaduiza, D., Anaya, M., Gómez, J., Sarmiento, J., Perez, M., Lara, C., Ruiz, J., Osorio, N., Rodriguez, K., and Hernandez, I. (2024). Electronic Tongues and Noses: A General Overview. Biosensors, 14.10.3390/bios14040190 ↗
24. Wei, M., Liu, X., Xie, P., Lei, Y., Yu, H., Han, A., Xie, L., Jia, H., Lin, S., and Bai, Y. (2022). Characterization of Volatile Profiles and Correlated Contributing Compounds in Pan-Fried Steaks from Different Chinese Yellow Cattle Breeds through GC-Q-Orbitrap, E-Nose, and Sensory Evaluation. Molecules, 27.10.3390/molecules27113593 ↗
25. Gonzalez Viejo, C., and Fuentes, S. (2022). Digital Detection of Olive Oil Rancidity Levels and Aroma Profiles Using Near-Infrared Spectroscopy, a Low-Cost Electronic Nose and Machine Learning Modelling. Chemosensors, 10.10.3390/chemosensors10050159 ↗
26. Effects of Zanthoxylum Bungeanum M. and Capsicum Annuum L. Oil on the Formation of Aroma Characteristics of Jiao-Ma Chicken as Evaluated by GC-MS and E-Nose10.1590/fst.56022 ↗
27. Analysis of Volatile Organic Compounds and Metabolites of Three Cultivars of Asparagus (Asparagus officinalis L.) Using E-Nose, GC-IMS, and LC-MS/MS10.1080/21655979.2022.2056318 ↗
28. High Performance Liquid Chromatography Coupled with Post—Column Derivatization Methods in Food Analysis: Chemistries and Applications in the Last Two Decades10.1016/j.foodchem.2024.138577 ↗
29. Analysis of Veterinary Drugs and Pesticides in Food Using Liquid Chromatography-Mass Spectrometry10.1016/j.trac.2024.117888 ↗
30. Pan, W., Benjakul, S., Sanmartin, C., Guidi, A., Ying, X., Ma, L., Weng, X., Yu, J., and Deng, S. (2022). Characterization of the Flavor Profile of Bigeye Tuna Slices Treated by Cold Plasma Using E-Nose and GC-IMS. Fishes, 7.10.3390/fishes7010013 ↗
31. Wu, H., Viejo, C.G., Fuentes, S., Dunshea, F.R., and Suleria, H.A.R. (2023). The Impact of Wet Fermentation on Coffee Quality Traits and Volatile Compounds Using Digital Technologies. Fermentation, 9.10.3390/fermentation9010068 ↗
32. Utilisation of a Portable Electronic Nose, NeOse Pro, to Follow the Microbial Fermentation of a Yoghurt
33. Characterization of the Volatile Profile from Six Different Varieties of Chinese Chives by HS-SPME/GC–MS Coupled with E. NOSE10.1016/j.jksus.2022.101971 ↗
34. Ninh, D.K., Phan, K.D., Nguyen, T.T.A., Dang, M.N., Le Thanh, N., and Ferrero, F. (2024). Classification of Urea Content in Fish Using Absorbance Near-Infrared Spectroscopy and Machine Learning. Appl. Sci., 14.10.3390/app14198586 ↗
35. Cappelli, A., Cividino, S., Redaelli, V., Tripodi, G., Aiello, G., Velotto, S., and Zaninelli, M. (2024). Applying Spectroscopies, Imaging Analyses, and Other Non-Destructive Techniques to Olives and Extra Virgin Olive Oil: A Systematic Review of Current Knowledge and Future Applications. Agriculture, 14.10.3390/agriculture14071160 ↗
36. She, X., Huang, J., Cao, X., Wu, M., and Yang, Y. (2024). Rapid Measurement of Total Saponins, Mannitol, and Naringenin in Dendrobium Officinale by Near-Infrared Spectroscopy and Chemometrics. Foods, 13.10.3390/foods13081199 ↗
37. Application of Nuclear Magnetic Resonance in Food Analysis10.1590/fst.43622 ↗
38. Nuclear Magnetic Resonance Spectroscopy Applications in the Food Industry
39. Sacchi, R., and Paolillo, L. (2007). NMR for Food Quality and Traceability. Advances in Food Diagnostics, John Wiley & Sons, Ltd.10.1002/9780470277805.ch5 ↗
40. DNA-Based Techniques to Check Quality and Authenticity of Food, Feed and Medicinal Products of Plant Origin: A Review10.1016/j.tifs.2024.104568 ↗
41. Nasiru, M.M., Umair, M., Boateng, E.F., Alnadari, F., Khan, K.R., Wang, Z., Luo, J., Yan, W., Zhuang, H., and Majrashi, A. (2022). Characterisation of Flavour Attributes in Egg White Protein Using HS-GC-IMS Combined with E-Nose and E-Tongue: Effect of High-Voltage Cold Plasma Treatment Time. Molecules, 27.10.3390/molecules27030601 ↗
42. Trends in Artificial Aroma Sensing by Means of Electronic Nose Technologies to Advance Dairy Production—A Review10.1080/10408398.2021.1945533 ↗
43. Application of Electronic Nose and Eye Systems for Detection of Adulteration in Olive Oil Based on Chemometrics and Optimization Approaches10.3897/jucs.90346 ↗
44. Development of Food Electronic Nose for Prawn (Macrobrachium Rosenbergii) Quality Rapid Assessment and Their Relationship with the Physicochemical Index10.1080/10942912.2021.1879135 ↗
45. Minami, K., Kobayashi, H., Matoba, M., Kamiya, Y., Maji, S., Nemoto, T., Tohno, M., Nakakubo, R., and Yoshikawa, G. (2023). Measurement of Volatile Fatty Acids in Silage through Odors with Nanomechanical Sensors. Biosensors, 13.10.3390/bios13020152 ↗
46. Application of Electronic Nose to Predict the Optimum Fermentation Time for Low-Country Sri Lankan Tea10.1155/2022/7703352 ↗
47. Gonzalez Viejo, C., and Fuentes, S. (2022). Digital Assessment and Classification of Wine Faults Using a Low-Cost Electronic Nose, Near-Infrared Spectroscopy and Machine Learning Modelling. Sensors, 22.10.3390/s22062303 ↗
48. Gonzalez Viejo, C., Harris, N.M., and Fuentes, S. (2022). Quality Traits of Sourdough Bread Obtained by Novel Digital Technologies and Machine Learning Modelling. Fermentation, 8.10.3390/fermentation8100516 ↗
49. Tatli, S., Mirzaee-Ghaleh, E., Rabbani, H., Karami, H., and Wilson, A.D. (2022). Prediction of Residual NPK Levels in Crop Fruits by Electronic-Nose VOC Analysis Following Application of Multiple Fertilizer Rates. Appl. Sci., 12.10.3390/app122111263 ↗
50. Electronic Noses: Powerful Tools in Meat Quality Assessment10.1016/j.meatsci.2017.04.240 ↗
51. Application of Electronic Tongue for Fresh Foods Quality Evaluation: A Review10.1080/87559129.2018.1424184 ↗
52. Palumbo, M., Attolico, G., Capozzi, V., Cozzolino, R., Corvino, A., de Chiara, M.L.V., Pace, B., Pelosi, S., Ricci, I., and Romaniello, R. (2022). Emerging Postharvest Technologies to Enhance the Shelf-Life of Fruit and Vegetables: An Overview. Foods, 11.10.3390/foods11233925 ↗
53. Life Cycle Assessment in Green Chemistry: Overview of Key Parameters and Methodological Concerns10.1007/s11367-012-0500-1 ↗
54. Mediated Biosensors10.1016/S0956-5663(01)00313-X ↗
55. Electrochemical Sensors and Biosensors: Effective Tools for Detecting Heavy Metals in Water and Food with Possible Implications for Children’s Health10.1016/j.ijoes.2024.100643 ↗
56. Modesti, M., Tonacci, A., Sansone, F., Billeci, L., Bellincontro, A., Cacopardo, G., Sanmartin, C., Taglieri, I., and Venturi, F. (2022). E-Senses, Panel Tests and Wearable Sensors: A Teamwork for Food Quality Assessment and Prediction of Consumer’s Choices. Chemosensors, 10.10.3390/chemosensors10070244 ↗
57. Recent Applications of Potentiometric Electronic Tongue and Electronic Nose in Sensory Evaluation10.3746/pnf.2022.27.4.354 ↗
58. Wang, D., Zhang, M., Jiang, Q., and Mujumdar, A.S. (2024). Intelligent System/Equipment for Quality Deterioration Detection of Fresh Food: Recent Advances and Application. Foods, 13.10.3390/foods13111662 ↗
59. Fusion of Electronic Nose, Electronic Tongue and Computer Vision for Animal Source Food Authentication and Quality Assessment—A Review10.1016/j.jfoodeng.2017.04.024 ↗
60. New Data Preprocessing Trends Based on Ensemble of Multiple Preprocessing Techniques10.1016/j.trac.2020.116045 ↗
61. Application of Electronic Nose as a Non-Invasive Technique for Odor Fingerprinting and Detection of Bacterial Foodborne Pathogens: A Review10.1007/s13197-019-04143-4 ↗
62. Piezoelectric Materials: Advanced Applications in Electro-Chemical Processes10.1016/j.egyr.2023.03.077 ↗
63. “Electronic Tongue” in the Food Industry10.30721/fsab2020.v3.i1.74 ↗
64. Evaluation of Umami Taste in Hanwoo with Different Feed Sources by Chemical Analysis, Electronic Tongue Analysis, and Sensory Evaluation10.1016/j.fochx.2023.100889 ↗
65. Comparison of Taste Characteristics between Koji Mold–Ripened Cheese and Camembert Cheese Using an Electronic Tongue System10.3168/jds.2023-23277 ↗
66. A Potentiometric Electronic Tongue for the Discrimination of Honey According to the Botanical Origin. Comparison with Traditional Methodologies: Physicochemical Parameters and Volatile Profile10.1016/j.jfoodeng.2011.10.036 ↗
67. Beer Discrimination Using a Portable Electronic Tongue Based on Screen-Printed Electrodes10.1016/j.jfoodeng.2015.02.018 ↗
68. Braunger, M.L., Shimizu, F.M., Jimenez, M.J., Amaral, L.R., Piazzetta, M.H.d.O., Gobbi, Â.L., Magalhães, P.S., Rodrigues, V., Oliveira, O.N., and Riul, A. (2017). Microfluidic Electronic Tongue Applied to Soil Analysis. Chemosensors, 5.10.3390/chemosensors5020014 ↗
69. Liang, Z., Tian, F., Yang, S.X., Zhang, C., Sun, H., and Liu, T. (2018). Study on Interference Suppression Algorithms for Electronic Noses: A Review. Sensors, 18.10.3390/s18041179 ↗
70. Al-Attabi, Z., Al-Habsi, N., and Rahman, M.S. (2022). Use of Electronic Tongue to Determine Quality and Safety of Fresh Produce. Nondestructive Quality Assessment Techniques for Fresh Fruits and Vegetables, Springer.10.1007/978-981-19-5422-1_16 ↗
71. Construction, Working, and Applications of E-Tongue: A Versatile Tool for All Tastes?10.1149/10701.20193ecst ↗
72. Surfactant-like Peptide Self-Assembled into Hybrid Nanostructures for Electronic Nose Applications10.1021/acsnano.1c10734 ↗
73. Electronic Nose: Current Status and Future Trends10.1021/cr068121q ↗
74. Electronic Noses: From Advanced Materials to Sensors Aided with Data Processing10.1002/admt.201800488 ↗
75. Application of Electronic Nose for Industrial Odors and Gaseous Emissions Measurement and Monitoring—An Overview10.1016/j.talanta.2015.06.050 ↗
76. Munekata, P.E.S., Finardi, S., de Souza, C.K., Meinert, C., Pateiro, M., Hoffmann, T.G., Domínguez, R., Bertoli, S.L., Kumar, M., and Lorenzo, J.M. (2023). Applications of Electronic Nose, Electronic Eye and Electronic Tongue in Quality, Safety and Shelf Life of Meat and Meat Products: A Review. Sensors, 23.10.3390/s23020672 ↗
77. Abu-Khalaf, N., and Masoud, W. (2022). [Retracted] Electronic Nose for Differentiation and Quantification of Yeast Species in White Fresh Soft Cheese. Appl. Bionics Biomech., 2022.10.1155/2022/8472661 ↗
78. Carrillo-Gómez, J.K., Acevedo, C.M.D., and García-Rico, R.O. (2021). Detection of the Bacteria Concentration Level in Pasteurized Milk by Using Two Different Artificial Multisensory Methods. Sens. Bio-Sens. Res., 33.10.1016/j.sbsr.2021.100428 ↗
79. Cui, S., Cao, L., Acosta, N., Zhu, H., and Ling, P.P. (2021). Development of Portable E-Nose System for Fast Diagnosis of Whitefly Infestation in Tomato Plant in Greenhouse. Chemosensors, 9.10.3390/chemosensors9110297 ↗
80. Khorramifar, A., Rasekh, M., Karami, H., Covington, J.A., Derakhshani, S.M., Ramos, J., and Gancarz, M. (2022). Application of MOS Gas Sensors Coupled with Chemometrics Methods to Predict the Amount of Sugar and Carbohydrates in Potatoes. Molecules, 27.10.3390/molecules27113508 ↗
81. Aouadi, B., Zaukuu, J.-L.Z., Vitális, F., Bodor, Z., Fehér, O., Gillay, Z., Bazar, G., and Kovacs, Z. (2020). Historical Evolution and Food Control Achievements of Near Infrared Spectroscopy, Electronic Nose, and Electronic Tongue—Critical Overview. Sensors, 20.10.3390/s20195479 ↗
82. Sánchez, R., Martín-Tornero, E., Lozano, J., Boselli, E., Arroyo, P., Meléndez, F., and Martín-Vertedor, D. (2021). E-Nose Discrimination of Abnormal Fermentations in Spanish-Style Green Olives. Molecules, 26.10.3390/molecules26175353 ↗
83. Estakhroueiyeh, H.R., and Rashedi, E. (2015, January 29–30). Detecting Moldy Bread Using an E-Nose and the KNN Classifier. Proceedings of the 2015 5th International Conference on Computer and Knowledge Engineering (ICCKE), Mashhad, Iran.10.1109/ICCKE.2015.7365836 ↗
84. Longjing Tea Quality Classification by Fusion of Features Collected from E-Nose10.1016/j.chemolab.2015.03.010 ↗
85. Olive Oil Classification and Fraud Detection Using E-Nose and Ultrasonic System10.1007/s12161-021-02035-y ↗
86. Ma, R., Shen, H., Cheng, H., Zhang, G., and Zheng, J. (2023). Combining E-Nose and e-Tongue for Improved Recognition of Instant Starch Noodles Seasonings. Front. Nutr., 9.10.3389/fnut.2022.1074958 ↗
87. Development of Rapid and Non-Destructive Electric Nose (E-Nose) System for Shelf Life Evaluation of Different Edible Seeds10.1016/j.foodchem.2023.136562 ↗
88. Physicochemical Parameters Combined Flash GC E-Nose and Artificial Neural Network for Quality and Volatile Characterization of Vinegar with Different Brewing Techniques10.1016/j.foodchem.2021.131658 ↗
89. Analysis of the Volatile Profiles of Kiwifruits Experiencing Soft Rot Using E-Nose and HS-SPME/GC–MS10.1016/j.lwt.2022.114405 ↗
90. The Potential of E-Nose Aroma Profiling for Identifying the Geographical Origin of Licorice (Glycyrrhiza glabra L.) Roots10.1016/j.foodchem.2014.05.142 ↗
91. Storage Time of Nut Spreads Using Flash Gas Chromatography E-Nose Combined with Multivariate Data Analysis10.1016/j.lwt.2022.113217 ↗
92. Zhou, Q., Dai, Z., Song, F., Li, Z., Song, C., and Ling, C. (2023). Monitoring Black Tea Fermentation Quality by Intelligent Sensors: Comparison of Image, e-Nose and Data Fusion. Food Biosci., 52.10.1016/j.fbio.2023.102454 ↗
93. Using a Low-Cost Components e-Nose for Basic Detection of Different Foodstuffs10.1109/JSEN.2022.3181513 ↗
94. Optimizing the Winemaking Process: NIR Spectroscopy and e-Nose Analysis for the Online Monitoring of Fermentation10.1002/jsfa.13336 ↗
95. A Framework for Analysing E-Nose Data Based on Fuzzy Set Multiple Linear Regression: Paddy Quality Assessment10.1016/j.sna.2017.10.020 ↗
96. Portable FBAR Based E-Nose for Cold Chain Real-Time Bananas Shelf Time Detection10.1063/10.0016870 ↗
97. Insights into the Volatile Flavor and Quality Profiles of Loquat (Eriobotrya japonica Lindl.) during Shelf-Life via HS-GC-IMS, E-Nose, and E-Tongue10.1016/j.fochx.2023.100886 ↗
98. Evaluation of the Quality Grade of Congou Black Tea by the Fusion of GC-E-Nose, E-Tongue, and E-Eye10.1016/j.fochx.2024.101519 ↗
99. Fujioka, K. (2021). Comparison of Cheese Aroma Intensity Measured Using an Electronic Nose (E-Nose) Non-Destructively with the Aroma Intensity Scores of a Sensory Evaluation: A Pilot Study. Sensors, 21.10.3390/s21248368 ↗
100. Bu, N., Yang, Q., Chen, J., Li, Y., and Liu, D. (2023). Characterization and Discrimination of Volatile Compounds in Chilled Tan Mutton Meat during Storage Using HiSorb-TD-GC-MS and E-Nose. Molecules, 28.10.3390/molecules28134993 ↗