1,033
Views
7
CrossRef citations to date
0
Altmetric
Reviews

Toward in-process technology-aided automation for enhanced microbial food safety and quality assurance in milk and beverages processing

, , , ORCID Icon & ORCID Icon

References

  • Abdullah, S. A., S. H. Lee, I. K. Cho, Q. X. Li, S. Jun, and W. Choi. 2013. Pasteurization of kava juice using novel continuous flow microwave heating technique. Food Science and Biotechnology 22 (4):961–6. doi: 10.1007/s10068-013-0170-1.
  • Adley, C. C. 2014. Past, present and future of sensors in food production. Foods (Basel, Switzerland) 3 (3):491–510. doi: 10.3390/foods3030491.
  • Akdeniz, V., and A. S. Akalın. 2020. Recent advances in dual effect of power ultrasound to microorganisms in dairy industry: Activation or inactivation. Critical Reviews in Food Science and Nutrition 64 (4):1–16.
  • Alagumeenaakshi, M., S. Ajitha, J. Sathika, and R. Navaneethakrishnan. 2021. Milk adulteration monitoring. Paper presented at the 2021 International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA). IEEE Xplore. doi: 10.1109/ICAECA52838.2021.9675630.
  • Alenyorege, E. A., H. Ma, and I. Ayim. 2019. Inactivation kinetics of inoculated Escherichia coli and Listeria innocua in fresh‐cut Chinese cabbage using sweeping frequency ultrasound. Journal of Food Safety 39 (6):e12696. doi: 10.1111/jfs.12696.
  • Ali, H., H. Nawaz, M. Saleem, F. Nurjis, and M. Ahmed. 2016. Qualitative analysis of desi ghee, edible oils, and spreads using Raman spectroscopy. Journal of Raman Spectroscopy 47 (6):706–11. doi: 10.1002/jrs.4891.
  • Altan, A., M. H. Oztop, K. L. McCarthy, and M. J. McCarthy. 2011. Monitoring changes in feta cheese during brining by magnetic ­resonance imaging and NMR relaxometry. Journal of Food Engineering 107 (2):200–7. doi: 10.1016/j.jfoodeng.2011.06.023.
  • Avhale, G., A. Shaligram, and D. Gharpure. 2021. IoT based intelligent tracking, early-warning & management (ITEM) tool for efficient milk transportation in dairy industry. Paper presented at the AIP Conference Proceedings, 1:2335. doi: 10.1063/5.0043687.
  • Ayyannawar, V. V., and S. R. Metri. 2021. Detection of fat in milk using photoconductivity and color detection tecnique with smart billing. In ICT analysis and applications, 399–410. Springer. ISBN 978-981-15-8354-4 (eBook). doi: 10.1007/978-981-15-8354-4.
  • Babu, G. S., V. R. Krishna, V. Dharma Teja, and S. BALRAJ YADAV. 2018. Milk quality testing using intelligent inference perfomance evaluation system integrated with IoT. International Journal of Engineering & Technology 7 (2.20):74–7. doi: 10.14419/ijet.v7i2.20.11757.
  • Badia-Melis, R., and L. Ruiz-Garcia. 2016. Real-time tracking and remote monitoring in food traceability. In Advances in food traceability techniques and technologies, 209–24. UK: Elsevier.
  • Baek, S. H., J. H. Kang, Y. H. Hwang, K. M. Ok, K. Kwak, and H. S. Chun. 2016. Detection of methomyl, a carbamate insecticide, in food matrices using terahertz time-domain spectroscopy. Journal of Infrared, Millimeter, and Terahertz Waves 37 (5):486–97. doi: 10.1007/s10762-015-0234-9.
  • Baek, S. H., H. B. Lim, and H. S. Chun. 2014. Detection of melamine in foods using terahertz time-domain spectroscopy. Journal of Agricultural and Food Chemistry 62 (24):5403–7. doi: 10.1021/jf501170z.
  • Bakalets, I. A., and M. S. Chvanova. 2020. Using neural network to ensure the packing quality of pasteurized milk. Paper presented at the 2020 4th Scientific School on Dynamics of Complex Networks and their Application in Intellectual Robotics (DCNAIR). IEEE. doi: 10.1109/DCNAIR50402.2020.9216924.
  • Barboza da Silva, C., A. A. N. Silva, G. Barroso, P. T. Yamamoto, V. Arthur, C. F. M. Toledo, and T. d A. Mastrangelo. 2021. Convolutional neural networks using enhanced radiographs for real-time detection of Sitophilus zeamais in maize grain. Foods 10 (4):879. doi: 10.3390/foods10040879.
  • Bauriegel, E., A. Giebel, M. Geyer, U. Schmidt, and W. Herppich. 2011. Early detection of Fusarium infection in wheat using hyper-spectral imaging. Computers and Electronics in Agriculture 75 (2):304–12. doi: 10.1016/j.compag.2010.12.006.
  • Beattie, R. J., S. J. Bell, L. J. Farmer, B. W. Moss, and D. Patterson. 2004. Preliminary investigation of the application of Raman spectroscopy to the prediction of the sensory quality of beef silverside. Meat Science 66 (4):903–13. doi: 10.1016/j.meatsci.2003.08.012.
  • Benlloch-Tinoco, M., M. Igual, A. Salvador, D. Rodrigo, and N. Martínez-Navarrete. 2014. Quality and acceptability of microwave and conventionally pasteurised kiwifruit puree. Food and Bioprocess Technology 7 (11):3282–92. doi: 10.1007/s11947-014-1315-9.
  • Besghini, D., M. Mauri, and R. Simonutti. 2019. Time domain NMR in polymer science: From the laboratory to the industry. Applied Sciences 9 (9):1801. doi: 10.3390/app9091801.
  • Bhagya Raj, G., and K. K. Dash. 2020. Comprehensive study on applications of artificial neural network in food process modeling. Critical Reviews in Food Science and Nutrition 62 (10):1–28.
  • Bhattacharjee, C., V. Saxena, and S. Dutta. 2019. Novel thermal and non-thermal processing of watermelon juice. Trends in Food Science & Technology 93:234–43. doi: 10.1016/j.tifs.2019.09.015.
  • Bischof, J., B. Mahr, J. Choi, M. Behling, and D. Mewes. 2007. Use of X-ray tomography to map crystalline and amorphous phases in frozen biomaterials. Annals of Biomedical Engineering 35 (2):292–304.
  • Bogue, R. 2018. Sensing with terahertz radiation: A review of recent progress. Sensor Review 38 (2):216–22. doi: 10.1108/SR-10-2017-0221.
  • Bougdira, A., I. Akharraz, and A. Ahaitouf. 2019. Fuzzy approach to enhance quality control within intelligent traceability systems. Paper presented at the 2019 International Conference on Wireless Technologies, Embedded and Intelligent Systems (WITS). IEEE. doi: 10.1109/WITS.2019.8723764.
  • Bouteille, R., M. Gaudet, B. Lecanu, and H. This. 2013. Monitoring lactic acid production during milk fermentation by in situ quantitative proton nuclear magnetic resonance spectroscopy. Journal of Dairy Science 96 (4):2071–80.
  • Bouzembrak, Y., M. Klüche, A. Gavai, and H. J. Marvin. 2019. Internet of Things in food safety: Literature review and a bibliometric analysis. Trends in Food Science & Technology 94:54–64. doi: 10.1016/j.tifs.2019.11.002.
  • Boyacı, I. H., H. T. Temiz, R. S. Uysal, H. M. Velioğlu, R. J. Yadegari, and M. M. Rishkan. 2014. A novel method for discrimination of beef and horsemeat using Raman spectroscopy. Food Chemistry 148:37–41.
  • Brosnan, T. M., W. D. Daley, and M. J. Smith. 1996. Comparison of image analysis techniques for defect detection in food-processing applications. Paper presented at the Optics in Agriculture, Forestry, and Biological Processing II. Boston, MA, USA: Photonics East ‘96, 1996. doi: 10.1117/12.262869.
  • Buckley, M., and A. Reid. 2010. Global food safety: Keeping food safe from farm to table, 41. USA: American Society for Microbiology.
  • Calderon-Cordova, C., M. Gonzaga, J. Morales, M. Morocho, B. Torres, and C. Ramirez. 2018. Prototype industrial IoT applied to temperature monitoring in storage silos of dairy products. Paper presented at the 2018 13th Iberian Conference on Information Systems and Technologies (CISTI). IEEE. doi: 10.23919/CISTI.2018.8399299.
  • Caldwell, D. G. 2012. Robotics and automation in the food industry: Current and future technologies. UK: Elsevier.
  • Cao, Z., X. Cai, H. Li, W. Huang, X. Yang, L. Tao, … H. Wang. 2019. A network anomaly monitoring method based on edge computing for CPS/IOT. Paper presented at the 2019 IEEE International Conference on Industrial Internet (ICII). 11-12 November 2019, Orlando, FL, USA. doi: 10.1109/ICII.2019.00018.
  • Capello, F., M. Toja, and N. Trapani. 2016. A real-time monitoring service based on industrial internet of things to manage agrifood logistics. Paper presented at the 6th International Conference on Information Systems, Logistics and Supply Chain. June 1 – 4, Bordeaux, France.
  • Casco, M., R. Jagus, M. Agüero, and M. Fernandez. 2022. Ultrasound and its combination with natural antimicrobials: Effects on shelf life and quality stability of a fruit and vegetable smoothie. Food and Bioprocess Technology 15:1–16.
  • Chen, R.-Y. 2015. Autonomous tracing system for backward design in food supply chain. Food Control 51:70–84. doi: 10.1016/j.foodcont.2014.11.004.
  • Cheng, S., T. Zhang, L. Yao, X. Wang, Y. Song, H. Wang, H. Wang, and M. Tan. 2018. Use of low-field-NMR and MRI to characterize water mobility and distribution in pacific oyster (Crassostrea gigas) during drying process. Drying Technology 36 (5):630–6. doi: 10.1080/07373937.2017.1359839.
  • Chen, Q., C. Zhang, J. Zhao, and Q. Ouyang. 2013. Recent advances in emerging imaging techniques for non-destructive detection of food quality and safety. TrAC Trends in Analytical Chemistry 52:261–74. doi: 10.1016/j.trac.2013.09.007.
  • Cho, G.-L., and J.-W. Ha. 2019. Application of X-ray for inactivation of foodborne pathogens in ready-to-eat sliced ham and mechanism of the bactericidal action. Food Control 96:343–50. doi: 10.1016/j.foodcont.2018.09.034.
  • Chudasama, R., S. Dobariya, K. Patel, and H. Lopes. 2017. DAPS: Dairy analysis and prediction system using technical indicators. Paper presented at the 2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS). Chennai, India: IEEE. doi: 10.1109/SSPS.2017.8071587.
  • Coutinho, N. M., M. R. Silveira, L. M. Fernandes, J. Moraes, T. C. Pimentel, M. Q. Freitas, M. C. Silva, R. S. L. Raices, C. S. Ranadheera, F. O. Borges, et al. 2019. Processing chocolate milk drink by low-pressure cold plasma technology. Food Chemistry 278:276–83. doi: 10.1016/j.foodchem.2018.11.061.
  • Coutinho, N. M., M. R. Silveira, T. C. Pimentel, M. Q. Freitas, J. Moraes, L. M. Fernandes, M. C. Silva, R. S. Raices, C. S. Ranadheera, F. O. Borges, et al. 2019. Chocolate milk drink processed by cold plasma technology: Physical characteristics, thermal behavior and microstructure. LWT 102:324–9. doi: 10.1016/j.lwt.2018.12.055.
  • Cui, L., Y. Chen, M. Li, T. Liu, P. Yang, L. Guo, and X. Wang. 2020. Detection of water variation in rosebuds during hot-air drying by LF-NMR and MRI. Drying Technology 38 (3):304–12. doi: 10.1080/07373937.2019.1565577.
  • da Silva, R. G., T. E. Fischer, D. M. Zardo, P. R. Los, I. M. Demiate, A. Nogueira, and A. Alberti. 2021. Technological potential of the use of ultrasound and freeze concentration in Fuyu persimmon juice. Journal of Food Processing and Preservation 45 (12):e15989. doi: 10.1111/jfpp.15989.
  • Dale, L. M., A. Thewis, C. Boudry, I. Rotar, P. Dardenne, V. Baeten, and J. A. F. Pierna. 2013. Hyperspectral imaging applications in agriculture and agro-food product quality and safety control: A review. Applied Spectroscopy Reviews 48 (2):142–59. doi: 10.1080/05704928.2012.705800.
  • Dalitz, F., M. Cudaj, M. Maiwald, and G. Guthausen. 2012. Process and reaction monitoring by low-field NMR spectroscopy. Progress in Nuclear Magnetic Resonance Spectroscopy 60 (2012):52–70. doi: 10.1016/j.pnmrs.2011.11.003.
  • Deng, X., S. Cao, and A. L. Horn. 2021. Emerging applications of machine learning in food safety. Annual Review of Food Science and Technology 12:513–38.
  • DePree, N., A. Prince-Pike, B. Young, and D. Wilson. 2019. Predictive modelling of instant whole milk powder functional performance across three industrial plants. Journal of Food Engineering 252:1–9. doi: 10.1016/j.jfoodeng.2019.01.011.
  • Eazhumalai, G., T. Ranjitha Gracy, A. Mishra, and U. S. Annapure. 2021. Atmospheric pressure nonthermal pin to plate plasma system for the microbial decontamination of oat milk. Journal of Food Processing and Preservation:e16181. doi: 10.1111/jfpp.16181
  • Einarsdóttir, H., M. J. Emerson, L. H. Clemmensen, K. Scherer, K. Willer, M. Bech, R. Larsen, B. K. Ersbøll, and F. Pfeiffer. 2016. Novelty detection of foreign objects in food using multi-modal X-ray imaging. Food Control 67:39–47. doi: 10.1016/j.foodcont.2016.02.023.
  • Eom, K.-H., K.-H. Hyun, S. Lin, and J.-W. Kim. 2014. The meat freshness monitoring system using the smart RFID tag. International Journal of Distributed Sensor Networks 10 (7):591812. doi: 10.1155/2014/591812.
  • Fan, C., Z. Hu, A. Mustapha, and M. Lin. 2011. Rapid detection of food-and waterborne bacteria using surface-enhanced Raman spectroscopy coupled with silver nanosubstrates. Applied Microbiology and Biotechnology 92 (5):1053–61.
  • Fang, Z., M. Wang, W. Hu, and S. Chen. 2021. Potassium di-hydrogen phosphate identification based on wide energy X-ray absorption spectrum and an artificial neural network. Computers and Electronics in Agriculture 183:106062. doi: 10.1016/j.compag.2021.106062.
  • FAO. 2017. The future of food and agriculture–Trends and challenges. Annual Report 296:17–31.
  • Feizollahi, E., N. Misra, and M. Roopesh. 2021. Factors influencing the antimicrobial efficacy of Dielectric Barrier Discharge (DBD) Atmospheric Cold Plasma (ACP) in food processing applications. Critical Reviews in Food Science and Nutrition 61 (4):666–89.
  • Feng, J., Z. Fu, Z. Wang, M. Xu, and X. Zhang. 2013. Development and evaluation on a RFID-based traceability system for cattle/beef quality safety in China. Food Control 31 (2):314–25. doi: 10.1016/j.foodcont.2012.10.016.
  • Fourie, C. J., P. Van Der Westhuyzen, and P. Van Niekerk. 2007. An automated system for impedance measurements in milk. Paper presented at the AFRICON 2007. Windhoek, South Africa: IEEE. doi: 10.1109/AFRCON.2007.4401535.
  • Fusco, V., D. Chieffi, F. Fanelli, A. F. Logrieco, G.-S. Cho, J. Kabisch, C. Böhnlein, and C. M. A. P. Franz. 2020. Microbial quality and safety of milk and milk products in the 21st century. Comprehensive Reviews in Food Science and Food Safety 19 (4):2013–49. doi: 10.1111/1541-4337.12568.
  • Gabrić, D., F. Barba, S. Roohinejad, S. M. T. Gharibzahedi, M. Radojčin, P. Putnik, and D. Bursać Kovačević. 2018. Pulsed electric fields as an alternative to thermal processing for preservation of nutritive and physicochemical properties of beverages: A review. Journal of Food Process Engineering 41 (1):e12638. doi: 10.1111/jfpe.12638.
  • Gao, Y., K. Xu, H. Peng, J. Jiang, R. Zhao, and J. Lu. 2018. Effect of heat treatment on water absorption of Chinese fir using TD-NMR. Applied Sciences 9 (1):78. doi: 10.3390/app9010078.
  • Gonzalez Viejo, C., D. D. Torrico, F. R. Dunshea, and S. Fuentes. 2019. Development of artificial neural network models to assess beer acceptability based on sensory properties using a robotic pourer: A comparative model approach to achieve an artificial intelligence system. Beverages 5 (2):33. doi: 10.3390/beverages5020033.
  • Guimarães, J. T., P. P. Almeida, M. L. Brito, B. O. Cruz, N. S. Costa, R. V. Almeida Ito, J. C. Mota, M. R. Bertolo, S. T. Morais, R. P. Neto, et al. 2022. In vivo functional and health benefits of a prebiotic soursop whey beverage processed by high-intensity ultrasound: Study with healthy Wistar rats. Food Chemistry 380:132193. doi: 10.1016/j.foodchem.2022.132193.
  • Gupta, K., and N. Rakesh. 2018. IoT-based solution for food adulteration. Paper Presented at the Proceedings of First International Conference on Smart System, Innovations and Computing. Jaipur, India: Springer.
  • Haff, R. P, and N. Toyofuku. 2008. X-ray detection of defects and contaminants in the food industry. Sensing and Instrumentation for Food Quality and Safety 2 (4):262–73. doi: 10.1007/s11694-008-9059-8.
  • Hameed, S., L. Xie, and Y. Ying. 2018. Conventional and emerging detection techniques for pathogenic bacteria in food science: A review. Trends in Food Science & Technology 81:61–73. doi: 10.1016/j.tifs.2018.05.020.
  • Han, W., Y. Gu, W. Wang, Y. Zhang, Y. Yin, J. Wang, and L.-R. Zheng. 2015. The design of an electronic pedigree system for food safety. Information Systems Frontiers 17 (2):275–87. doi: 10.1007/s10796-012-9372-y.
  • Hand, A. 2015. Process automation: Making the case for integrated safety. https://www.automationworld.com/products/control/blog/13313299/process-automation-making-the-case-for-integrated-safety
  • Hatzakis, E. 2019. Nuclear magnetic resonance (NMR) spectroscopy in food science: A comprehensive review. Comprehensive Reviews in Food Science and Food Safety 18 (1):189–220. doi: 10.1111/1541-4337.12408.
  • Hemme, T., and J. Otte. 2010. Status and prospects for smallholder milk production: A global perspective. Italy: Food and Agriculture Organization of the United Nations (FAO).
  • Hendriksen, R. S., V. Bortolaia, H. Tate, G. H. Tyson, F. M. Aarestrup, and P. F. McDermott. 2019. Using genomics to track global antimicrobial resistance. Frontiers in Public Health 7:242.
  • Horputra, P., R. Phrajonthong, and P. Kaewprapha. 2021. Deep learning-based bottle caps inspection in beverage manufacturing and packaging process. Paper presented at the 2021 9th International Electrical Engineering Congress (iEECON). doi: 10.1109/iEECON51072.2021.9440326.
  • Hu, Y., S. Wang, S. Wang, and X. Lu. 2017. Application of nuclear magnetic resonance spectroscopy in food adulteration determination: The example of Sudan dye I in paprika powder. Scientific Reports 7 (1):1–9. doi: 10.1038/s41598-017-02921-8.
  • Hussain, S. A., C. S. Ramaiah, M. G. Prasad, and S. M. Hussain. 2016. Milk products monitoring system with arm processor for early detection of microbial activity. Paper presented at the 2016 3rd MEC International Conference on Big Data and Smart City (ICBDSC). doi: 10.1109/ICBDSC.2016.7460385.
  • Iorio, M. C., A. Bevilacqua, M. R. Corbo, D. Campaniello, M. Sinigaglia, and C. Altieri. 2019. A case study on the use of ultrasound for the inhibition of Escherichia coli O157: H7 and Listeria monocytogenes in almond milk. Ultrasonics Sonochemistry 52:477–83.
  • Jadhav, S., S. V. Patil, T. Thanuja, M. Shivu, and G. Shankar. 2018. Monitoring of industrial water usage by using Internet of Things. Paper presented at the 2018 International Conference on Information, Communication, Engineering and Technology (ICICET). doi: 10.1109/ICICET.2018.8533822.
  • Jesus, A. 2021. AI in the food and beverage industry – 3 current use-cases. https://emerj.com/ai-sector-overviews/artificial-intelligence-food-beverage/
  • Jiangping, M., C. Jiaxin, Z. Xin, and H. Lihong. 2014. Design method of high-speed robot fruit-milk packaging line based on petri net. Journal of Tianjin University (Science and Technology) 31 (8):120–31.
  • Jin, C., Y. Bouzembrak, J. Zhou, Q. Liang, L. M. van den Bulk, A. Gavai, N. Liu, L. J. van den Heuvel, W. Hoenderdaal, and H. J. Marvin. 2020. Big Data in food safety-A review. Current Opinion in Food Science 36:24–32. doi: 10.1016/j.cofs.2020.11.006.
  • Jin, H., H. Li, Z. Yin, Y. Zhu, A. Lu, D. Zhao, and C. Li. 2021. Application of Raman spectroscopy in the rapid detection of waste cooking oil. Food Chemistry 362:130191.
  • Juraga, E., V. Stulić, T. Vukušić Pavičić, J. Gajdoš Kljusurić, M. Brnčić, and Z. Herceg. 2021. The influence of high-power ultrasound and bactofugation on microbiological quality of milk. Food Technology and Biotechnology 59 (4):454–62.
  • Juric, P., M. B. Bakaric, X. Wang, X. Zhang, and M. Matetic. 2016. Mining data streams for the analysis of parameter fluctuations in iot-aided fruit cold-chain. Annals of DAAAM & Proceedings 27:756–61.
  • Kaavya, R., R. Pandiselvam, M. Mohammed, R. Dakshayani, A. Kothakota, S. V. Ramesh, D. Cozzolino, and C. Ashokkumar. 2020. Application of infrared spectroscopy techniques for the assessment of quality and safety in spices: A review. Applied Spectroscopy Reviews 55 (7):593–611. doi: 10.1080/05704928.2020.1713801.
  • Kakani, V., V. H. Nguyen, B. P. Kumar, H. Kim, and V. R. Pasupuleti. 2020. A critical review on computer vision and artificial intelligence in food industry. Journal of Agriculture and Food Research 2:100033. doi: 10.1016/j.jafr.2020.100033.
  • Kaushal, P., and R. P. Mudhalwadkar. 2021. Internet of things enabled electronic tongue for remote monitoring of water quality. In Smart sensors measurements and instrumentation, 71–9. Springer. ISBN 978-981-16-0336-5 (eBook). doi: 10.1007/978-981-16-0336-5.
  • Kaya, A., A. S. Keçeli, C. Catal, and B. Tekinerdogan. 2020. Sensor failure tolerable machine learning-based food quality prediction model. Sensors 20 (11):3173. doi: 10.3390/s20113173.
  • Kim, M., A. Lefcourt, K. Chao, Y. Chen, I. Kim, and D. Chan. 2002. Multispectral detection of fecal contamination on apples based on hyperspectral imagery: Part I. Application of visible and near–infrared reflectance imaging. Transactions of the ASAE 45 (6):2027.
  • Kimbahune, S., S. M. Ghouse, B. Mithun, S. Shinde, and A. K. Jha. 2016. Hyperspectral sensing based analysis for determining milk adulteration. Paper presented at the Hyperspectral Imaging Sensors: Innovative Applications and Sensor Standards 2016.
  • Kozub, Y. A., V. Komlatsky, and T. Khoroshailo. 2020. About some automated processes in the production of dairy products. Paper presented at the IOP Conference Series: Materials Science and Engineering. doi: 10.1088/1757-899X/862/3/032021.
  • Kraggerud, H., J. Wold, M. Høy, and R. Abrahamsen. 2009. X‐ray images for the control of eye formation in cheese. International Journal of Dairy Technology 62 (2):147–53. doi: 10.1111/j.1471-0307.2009.00478.x.
  • Kuo, M.-I., M. Anderson, and S. Gunasekaran. 2003. Determining effects of freezing on pasta filata and non-pasta filata Mozzarella cheeses by nuclear magnetic resonance imaging. Journal of Dairy Science 86 (8):2525–36.
  • Lan, Y., D. Han, F. Bai, Z. Zhong, and Z. Weng. 2020. Review of research and application of fluid flow detection based on computer vision. Paper presented at the Proceedings of the 4th International Conference on Computer Science and Application Engineering. doi: 10.1145/3424978.3425112.
  • Latha, R., G. Sreekanth, R. Suganthe, R. Rajadevi, S. Karthikeyan, S. Kanivel, and B. Inbaraj. 2021. Automatic detection of tea leaf diseases using deep convolution neural network. Paper presented at the 2021 International Conference on Computer Communication and Informatics (ICCCI). doi: 10.1109/ICCCI50826.2021.9402225.
  • Lewis, R. A. 2014. A review of terahertz sources. Journal of Physics D: Applied Physics 47 (37):374001. doi: 10.1088/0022-3727/47/37/374001.
  • Ley, D., and I. Braune. 1994. Vision-based level control for beverage-filling processes. Paper presented at the Sensors and Control for Automation.
  • Liao, X., J. Li, A. I. Muhammad, Y. Suo, S. Chen, X. Ye, D. Liu, and T. Ding. 2018. Application of a dielectric barrier discharge atmospheric cold plasma (Dbd‐Acp) for Eshcerichia coli inactivation in apple juice. Journal of Food Science 83 (2):401–8. doi: 10.1111/1750-3841.14045.
  • Li, Y.-S, and J. S. Church. 2014. Raman spectroscopy in the analysis of food and pharmaceutical nanomaterials. Journal of Food and Drug Analysis 22 (1):29–48.
  • Lin, X., W.-L.-J. Hasi, X.-T. Lou, S.-q.-g.-w. Han, D.-Y. Lin, and Z.-W. Lu. 2015. Direct and quantitative detection of dicyandiamide (DCD) in milk using surface-enhanced Raman spectroscopy. Analytical Methods 7 (9):3869–75. doi: 10.1039/C5AY00313J.
  • Li, F., E. Santillan-Urquiza, U. Cronin, E. O'Meara, W. McCarthy, S. A. Hogan, M. G. Wilkinson, and J. T. Tobin. 2021. Assessment of the response of indigenous microflora and inoculated Bacillus licheniformis endospores in reconstituted skim milk to microwave and conventional heating systems by flow cytometry. Journal of Dairy Science 104 (9):9627–44. doi: 10.3168/jds.2020-19875.
  • Liu, Y., H. Pu, and D.-W. Sun. 2017. Hyperspectral imaging technique for evaluating food quality and safety during various processes: A review of recent applications. Trends in Food Science & Technology 69:25–35. doi: 10.1016/j.tifs.2017.08.013.
  • Liu, Q., K. Sun, J. Peng, M. Xing, L. Pan, and K. Tu. 2018. Identification of bruise and fungi contamination in strawberries using hyperspectral imaging technology and multivariate analysis. Food Analytical Methods 11 (5):1518–27. doi: 10.1007/s12161-017-1136-3.
  • Liu, B., P. Zhou, X. Liu, X. Sun, H. Li, and M. Lin. 2013. Detection of pesticides in fruits by surface-enhanced Raman spectroscopy coupled with gold nanostructures. Food and Bioprocess Technology 6 (3):710–8. doi: 10.1007/s11947-011-0774-5.
  • Li, C., X. Zang, B.-W. Zhu, and M. Tan. 2017. A method to analyze the protein denaturation of whole quail egg based on in situ NMR and MRI. International Journal of Food Engineering 13 (5). doi: 10.1515/ijfe-2016-0379.
  • Li, L., M. Zhang, B. Bhandari, and L. Zhou. 2018. LF-NMR online detection of water dynamics in apple cubes during microwave vacuum drying. Drying Technology 36 (16):2006–15. doi: 10.1080/07373937.2018.1432643.
  • Liu, G., G. Li, R. Yang, and L. Guo. 2018. Improving food safety in supply chain based on big data. Paper presented at the E3S Web of Conferences. doi: 10.1051/e3sconf/20185303084.
  • Lu, Y., H. Ishikawa, Y. Kwon, F. Hu, T. Miyakawa, and M. Tanokura. 2018. Real-time monitoring of chemical changes in three kinds of fermented milk products during fermentation using quantitative difference nuclear magnetic resonance spectroscopy. Journal of Agricultural and Food Chemistry 66 (6):1479–87.
  • Luis, R. d., O. Arias, E. Puertolas, S. Benede, L. Sanchez, M. Calvo, and M. D. Perez. 2009. Effect of high-intensity pulse electric fields on denaturation of bovine whey proteins. Milchwissenschaft 64 (4):422–6.
  • Ma, J., D.-W. Sun, H. Pu, J.-H. Cheng, and Q. Wei. 2019. Advanced techniques for hyperspectral imaging in the food industry: Principles and recent applications. Annual Review of Food Science and Technology 10:197–220.
  • Mahnot, N. K., C. L. Mahanta, K. M. Keener, and N. Misra. 2019. Strategy to achieve a 5-log Salmonella inactivation in tender coconut water using high voltage atmospheric cold plasma (HVACP). Food Chemistry 284:303–11.
  • Majdinasab, M., A. Hayat, and J. L. Marty. 2018. Aptamer-based assays and aptasensors for detection of pathogenic bacteria in food samples. TrAC Trends in Analytical Chemistry 107:60–77. doi: 10.1016/j.trac.2018.07.016.
  • Manzoor, M. F., N. Ahmad, R. M. Aadil, A. Rahaman, Z. Ahmed, A. Rehman, A. Siddeeg, X. ‐A. Zeng, and A. Manzoor. 2019. Impact of pulsed electric field on rheological, structural, and physicochemical properties of almond milk. Journal of Food Process Engineering 42 (8):e13299. doi: 10.1111/jfpe.13299.
  • Martins, C. P. C., R. N. Cavalcanti, T. S. F. Cardozo, S. M. Couto, J. T. Guimarães, C. F. Balthazar, R. S. Rocha, T. C. Pimentel, M. Q. Freitas, R. S. L. Raices, et al. 2021. Effects of microwave heating on the chemical composition and bioactivity of orange juice-milk beverages. Food Chemistry 345:128746. doi: 10.1016/j.foodchem.2020.128746.
  • Martysiak-Żurowska, D., E. Malinowska-Pańczyk, M. Orzołek, B. Kiełbratowska, and E. Sinkiewicz–Darol. 2022. Effect of convection and microwave heating on the retention of bioactive components in human milk. Food Chemistry 374:131772.
  • Martysiak-Żurowska, D., E. Malinowska-Pańczyk, M. Orzołek, B. Kusznierewicz, and B. Kiełbratowska. 2022. Effect of microwave and convection heating on selected nutrients of human milk. Food Chemistry 369:130958.
  • Marušić, A. 2011. Food safety and security: What were favourite topics for research in the last decade? Journal of Global Health 1 (1):72–8.
  • Mavani, N. R., J. M. Ali, S. Othman, M. Hussain, H. Hashim, and N. A. Rahman. 2021. Application of artificial intelligence in food industry—A guideline. Food Engineering Reviews 14:1–42.
  • Mendes-Oliveira, G., A. J. Deering, M. F. San MartinGonzalez, and O. H. Campanella. 2020. Microwave pasteurization of apple juice: Modeling the inactivation of Escherichia coli O157: H7 and Salmonella Typhimurium at 80–90° C. Food Microbiology 87:103382.
  • Mezgec, S, and B. Koroušić Seljak. 2017. NutriNet: A deep learning food and drink image recognition system for dietary assessment. Nutrients 9 (7):657. doi: 10.3390/nu9070657.
  • Mishra, G., B. K. Panda, W. A. Ramirez, H. Jung, C. B. Singh, S. H. Lee, and I. Lee. 2021. Research advancements in optical imaging and spectroscopic techniques for nondestructive detection of mold infection and mycotoxins in cereal grains and nuts. Comprehensive Reviews in Food Science and Food Safety 20:4612–51. doi: 10.1111/1541-4337.12801.
  • Mohamad, A., N. N. Abdul Karim Shah, A. Sulaiman, N. Mohd Adzahan, and R. M. Aadil. 2021. Pulsed electric field of goat milk: Impact on Escherichia coli ATCC 8739 and vitamin constituents. Journal of Food Process Engineering 44 (9):e13779. doi: 10.1111/jfpe.13779.
  • Momivama, H., Y. Sasaki, I. Yosbimine, S. Nagano, T. Yuasa, and C. Otani. 2018. Study of 3D imaging using a CW diode terahertz source for practical applications. Paper presented at the 2018 43rd International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz).
  • Morales‐De La Peña, M., L. Salvia‐Trujillo, A. Rojas‐Graü, and O. Martín‐Belloso. 2017. Effects of high intensity pulsed electric fields or thermal treatments and refrigerated storage on antioxidant compounds of fruit juice‐milk beverages. Part II: Carotenoids. Journal of Food Processing and Preservation 41 (5):e13143.
  • Morita, K., Y. Ogawa, C. N. Thai, and F. Tanaka. 2003. Soft X-ray image analysis to detect foreign materials in foods. Food Science and Technology Research 9 (2):137–41. doi: 10.3136/fstr.9.137.
  • Mortazavi, N., and J. Aliakbarlu. 2019. Antibacterial effects of ultrasound, cinnamon essential oil, and their combination against Listeria monocytogenes and Salmonella Typhimurium in milk. Journal of Food Science 84 (12):3700–6.
  • Müller, C., L. David, V. Chiş, and S. C. Pînzaru. 2014. Detection of thiabendazole applied on citrus fruits and bananas using surface enhanced Raman scattering. Food Chemistry 145:814–20.
  • Murphy, S. I., S. J. Reichler, N. H. Martin, K. J. Boor, and M. Wiedmann. 2021. Machine learning and advanced statistical modeling can identify key quality management practices that affect postpasteurization contamination of fluid milk. Journal of Food Protection 84 (9):1496–511.
  • Narvankar, D., C. Singh, D. Jayas, and N. White. 2009. Assessment of soft X-ray imaging for detection of fungal infection in wheat. Biosystems Engineering 103 (1):49–56. doi: 10.1016/j.biosystemseng.2009.01.016.
  • Niemira, B. A. 2012. Cold plasma decontamination of foods. Annual Review of Food Science and Technology 3:125–42. doi: 10.1146/annurev-food-022811-101132.
  • Nieuwoudt, M., S. Holroyd, C. McGoverin, M. Simpson, and D. Williams. 2016. Raman spectroscopy as an effective screening method for detecting adulteration of milk with small nitrogen-rich molecules and sucrose. Journal of Dairy Science 99 (4):2520–36. doi: 10.3168/jds.2015-10342.
  • Nirenjena, S., D. L. BalaSubramanian, and M. Monisha. 2018. Advancement in monitoring the food supply chain management using IOT. International Journal of Pure and Applied Mathematics 119 (15):3123–31.
  • Ok, G., H. J. Shin, M.-C. Lim, and S.-W. Choi. 2019. Large-scan-area sub-terahertz imaging system for nondestructive food quality inspection. Food Control. 96:383–9. doi: 10.1016/j.foodcont.2018.09.035.
  • Olatunde, O. O., K. Chantakun, and S. Benjakul. 2021. Microbial, chemical qualities and shelf-life of blue swimming crab (Portunus armatus) lump meat as influenced by in-package high voltage cold plasma treatment. Food Bioscience 43:101274. doi: 10.1016/j.fbio.2021.101274.
  • Orina, I., M. Manley, and P. J. Williams. 2017. Use of high-resolution X-ray micro-computed tomography for the analysis of internal structural changes in maize infected with Fusarium verticillioides. Food Analytical Methods 10 (9):2919–33. doi: 10.1007/s12161-017-0831-4.
  • Ouyang, N., H. Ma, Y. Ding, F. Lu, L. Guo, X. Zhang, and C. Gu. 2022. Effect of slit dual-frequency ultrasonic emulsification technology on the stability of walnut emulsions. Ultrasonics Sonochemistry 82:105876.
  • Patel, P., and C. Beveridge. 2003. In-line sensors for food process monitoring and control. In Rapid and on-line instrumentation for food quality assurance, 215–39. Cambridge, UK: Woodhead Publishing Ltd.
  • Patel, P., and A. Doddamani. 2019. Role of sensor in the food processing industries. International Archives in Applied Science and Technology 10:10–8.
  • Patil, A., E. Jakatdar, S. Bhadreshwarmath, V. Kumbhar, P. Mitragotri, B. Deshmukh, and R. Mistry. 2021. Design of a low cost system for determination of fat using IOT and ML. Paper presented at the Journal of Physics: Conference Series. doi: 10.1088/1742-6596/1969/1/012034.
  • Qin, J., K. Chao, and M. S. Kim. 2012. Nondestructive evaluation of internal maturity of tomatoes using spatially offset Raman spectroscopy. Postharvest Biology and Technology 71:21–31. doi: 10.1016/j.postharvbio.2012.04.008.
  • Rajakumar, G., T. A. Kumar, T. Samuel, and E. M. Kumaran. 2018. IoT based milk monitoring system for detection of milk adulteration. International Journal of Pure and Applied Mathematics 118 (9):21–32.
  • Ramirez-Asis, E., J. Vilchez-Carcamo, C. M. Thakar, K. Phasinam, T. Kassanuk, and M. Naved. 2022. A review on role of artificial intelligence in food processing and manufacturing industry. Materials Today: Proceedings 51:2462–5. doi: 10.1016/j.matpr.2021.11.616.
  • Ravikanth, L., D. S. Jayas, N. D. G. White, P. G. Fields, and D.-W. Sun. 2017. Extraction of spectral information from hyperspectral data and application of hyperspectral imaging for food and agricultural products. Food and Bioprocess Technology 10 (1):1–33. doi: 10.1007/s11947-016-1817-8.
  • Ren, A., A. Zahid, D. Fan, X. Yang, M. A. Imran, A. Alomainy, and Q. H. Abbasi. 2019. State-of-the-art in terahertz sensing for food and water security – A comprehensive review. Trends in Food Science & Technology 85:241–51. doi: 10.1016/j.tifs.2019.01.019.
  • Riverol, C., G. Ricart, C. Carosi, and C. Di Santis. 2008. Application of advanced soft control strategies into the dairy industry. Innovative Food Science & Emerging Technologies 9 (3):298–305. doi: 10.1016/j.ifset.2007.07.002.
  • Roh, S. H., Y. J. Oh, S. Y. Lee, J. H. Kang, and S. C. Min. 2020. Inactivation of Escherichia coli O157: H7, Salmonella, Listeria monocytogenes, and Tulane virus in processed chicken breast via atmospheric in-package cold plasma treatment. LWT 127:109429. doi: 10.1016/j.lwt.2020.109429.
  • Sainz-García, E., I. López-Alfaro, R. Múgica-Vidal, R. López, R. Escribano-Viana, J. Portu, F. Alba-Elías, and L. González-Arenzana. 2019. Effect of the atmospheric pressure cold plasma treatment on Tempranillo red wine quality in batch and flow systems. Beverages 5 (3):50. doi: 10.3390/beverages5030050.
  • Samak, D., S. Jad, N. Nabil, A. Wassal, and M. Torki. 2019. Spectrometer as an ubiquitous sensor for IoT applications targeting food quality. Paper presented at the 2019 IEEE/ACS 16th International Conference on Computer Systems and Applications (AICCSA). doi: 10.1109/AICCSA47632.2019.9035230.
  • Scallan, E., R. M. Hoekstra, F. J. Angulo, R. V. Tauxe, M.-A. Widdowson, S. L. Roy, J. L. Jones, and P. M. Griffin. 2011. Foodborne illness acquired in the United States—major pathogens. Emerging Infectious Diseases 17 (1):7–15. doi: 10.3201/eid1701.P11101.
  • Seo, S.-M., S.-W. Kim, J.-W. Jeon, J.-H. Kim, H.-S. Kim, J.-H. Cho, W.-H. Lee, and S.-H. Paek. 2016. Food contamination monitoring via internet of things, exemplified by using pocket-sized immunosensor as terminal unit. Sensors and Actuators B: Chemical 233:148–56. doi: 10.1016/j.snb.2016.04.061.
  • Shaw, P., N. Kumar, S. Mumtaz, J. S. Lim, J. H. Jang, D. Kim, B. D. Sahu, A. Bogaerts, and E. H. Choi. 2021. Evaluation of non-thermal effect of microwave radiation and its mode of action in bacterial cell inactivation. Scientific Reports 11 (1):1–12. doi: 10.1038/s41598-021-93274-w.
  • Shih, C.-W., and C.-H. Wang. 2016. Integrating wireless sensor networks with statistical quality control to develop a cold chain system in food industries. Computer Standards & Interfaces 45:62–78. doi: 10.1016/j.csi.2015.12.004.
  • Siddeeg, A., X. A. Zeng, A. Rahaman, M. F. Manzoor, Z. Ahmed, and A. F. Ammar. 2019. Effect of pulsed electric field pretreatment of date palm fruits on free amino acids, bioactive components, and physicochemical characteristics of the alcoholic beverage. Journal of Food Science 84 (11):3156–62. doi: 10.1111/1750-3841.14825.
  • Silveira, M. R., N. M. Coutinho, E. A. Esmerino, J. Moraes, L. M. Fernandes, T. C. Pimentel, M. Q. Freitas, M. C. Silva, R. S. L. Raices, C. Senaka Ranadheera, et al. 2019. Guava-flavored whey beverage processed by cold plasma technology: Bioactive compounds, fatty acid profile and volatile compounds. Food Chemistry 279:120–7. doi: 10.1016/j.foodchem.2018.11.128.
  • Silveira, M. R., N. M. Coutinho, R. S. Rocha, J. Moraes, E. A. Esmerino, T. C. Pimentel, M. Q. Freitas, M. C. Silva, R. S. L. Raices, C. Senaka Ranadheera, et al. 2019. Guava flavored whey-beverage processed by cold plasma: Physical characteristics, thermal behavior and microstructure. Food Research International (Ottawa, ON) 119:564–70. doi: 10.1016/j.foodres.2018.10.033.
  • Simonis, P., S. Kersulis, V. Stankevich, K. Sinkevic, K. Striguniene, G. Ragoza, and A. Stirke. 2019. Pulsed electric field effects on inactivation of microorganisms in acid whey. International Journal of Food Microbiology 291:128–34.
  • Singh, C., and D. Jayas. 2013. Optical sensors and online spectroscopy for automated quality and safety inspection of food products. In Robotics and automation in the food industry, 111–29. UK: Elsevier, Woodhead Publishing Limited.
  • Smiljkovikj, K., and L. Gavrilovska. 2014. SmartWine: Intelligent end-to-end cloud-based monitoring system. Wireless Personal Communications 78 (3):1777–88. doi: 10.1007/s11277-014-1905-x.
  • Song, W., Z. Niu, and P. Zheng. 2021. Design concept evaluation of smart product-service systems considering sustainability: An integrated method. Computers & Industrial Engineering 159:107485. doi: 10.1016/j.cie.2021.107485.
  • Strieder, M. M., M. I. L. Neves, J. R. Belinato, E. K. Silva, and M. A. A. Meireles. 2022. Impact of thermosonication processing on the phytochemicals, fatty acid composition and volatile organic compounds of almond-based beverage. LWT 154:112579. doi: 10.1016/j.lwt.2021.112579.
  • Sudhakaran, V. A., and J. Minj. 2020. Basic facts about dairy processing and technologies. In Dairy processing: Advanced research to applications, 1–24. Singapore: Springer Nature. ISBN 978-981-15-2608-4 (eBook). doi: 10.1007/978-981-15-2608-4.
  • Sullivan, F. 2018. Applications of the safety systems in the food and beverage industry. https://ww2.frost.com/frost-perspectives/applications-safety-systems-food-and-beverage-industry/
  • Sun, H., G. Jiang, Q. Kong, Z. Chen, and X. Li. 2016. Design of real-time monitoring system on raw milk transport process. International Journal of Multimedia and Ubiquitous Engineering 11 (4):335–42. doi: 10.14257/ijmue.2016.11.4.33.
  • Sun, X., W. Pan, L. Wang, X. Wang, and B. Yang. 2017. Inspecting contraband hidden in milk powder using deep convolutional neural networks. Paper presented at the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC). doi: 10.1109/ITNEC.2017.8285105.
  • Syarif, I., A. S. Ahsan, M. U. H. Al Rasyid, and Y. P. Pratama. 2019. Health monitoring and early diseases detection on dairy cow based on internet of things and intelligent system. Paper presented at the 2019 International Electronics Symposium (IES), 27–28. Surabaya, Indonesia: IEEE. doi: 10.1109/ELECSYM.2019.8901527
  • Tekinerdogan, B., and C. Verdouw. 2020. Systems architecture design pattern catalog for developing digital twins. Sensors 20 (18):5103. doi: 10.3390/s20185103.
  • Thum, C., G. Ozturk, W. C. McNabb, N. C. Roy, and J. M. Leite Nobrega de Moura Bell. 2020. Effects of microwave processing conditions on microbial safety and antimicrobial proteins in bovine milk. Journal of Food Processing and Preservation 44 (3):e14348. doi: 10.1111/jfpp.14348.
  • Tyson, G. H., P. F. McDermott, C. Li, Y. Chen, D. A. Tadesse, S. Mukherjee, S. Bodeis-Jones, C. Kabera, S. A. Gaines, G. H. Loneragan, et al. 2015. WGS accurately predicts antimicrobial resistance in Escherichia coli. The Journal of Antimicrobial Chemotherapy 70 (10):2763–9. doi: 10.1093/jac/dkv186.
  • Ugarte‐Romero, E., H. Feng, and S. E. Martin. 2007. Inactivation of Shigella boydii 18 IDPH and Listeria monocytogenes Scott A with power ultrasound at different acoustic energy densities and temperatures. Journal of Food Science 72 (4):M103–M107. doi: 10.1111/j.1750-3841.2007.00340.x.
  • Verdouw, C. N., J. Wolfert, A. Beulens, and A. Rialland. 2016. Virtualization of food supply chains with the internet of things. Journal of Food Engineering 176:128–36. doi: 10.1016/j.jfoodeng.2015.11.009.
  • Violino, S., L. Ortenzi, F. Antonucci, F. Pallottino, C. Benincasa, S. Figorilli, and C. Costa. 2020. An artificial intelligence approach for Italian EVOO origin traceability through an open source IoT spectrometer. Foods 9 (6):834. doi: 10.3390/foods9060834.
  • Visconti, P., R. de Fazio, R. Velázquez, C. Del-Valle-Soto, and N. I. Giannoccaro. 2020. Development of sensors-based agri-food traceability system remotely managed by a software platform for optimized farm management. Sensors 20 (13):3632. doi: 10.3390/s20133632.
  • Wahia, H., C. Zhou, O. A. Fakayode, R. Amanor-Atiemoh, L. Zhang, A. Taiye Mustapha, J. Zhang, B. Xu, R. Zhang, and H. Ma. 2021. Quality attributes optimization of orange juice subjected to multi-frequency thermosonication: Alicyclobacillus acidoterrestris spore inactivation and applied spectroscopy ROS characterization. Food Chemistry 361:130108. doi: 10.1016/j.foodchem.2021.130108.
  • Walkling-Ribeiro, M., O. Rodríguez-González, S. Jayaram, and M. Griffiths. 2011. Microbial inactivation and shelf life comparison of ‘cold’hurdle processing with pulsed electric fields and microfiltration, and conventional thermal pasteurisation in skim milk. International Journal of Food Microbiology 144 (3):379–86. doi: 10.1016/j.ijfoodmicro.2010.10.023.
  • Wang, C., D. L. Gallagher, A. M. Dietrich, M. Su, Q. Wang, Q. Guo, J. Zhang, W. An, J. Yu, and M. Yang. 2021. Data analytics determines co-occurrence of odorants in raw water and evaluates drinking water treatment removal strategies. Environmental Science & Technology 55 (24):16770–82.
  • Wang, S., Y. Liu, Y. Zhang, X. Lü, L. Zhao, Y. Song, L. Zhang, H. Jiang, J. Zhang, and W. Ge. 2022. Processing sheep milk by cold plasma technology: Impacts on the microbial inactivation, physicochemical characteristics, and protein structure. LWT 153:112573. doi: 10.1016/j.lwt.2021.112573.
  • WHO. 2022. Food safety fact sheet. https://www.who.int/news-room/fact-sheets/detail/food-safety
  • Wu, D., and D.-W. Sun. 2013. Advanced applications of hyperspectral imaging technology for food quality and safety analysis and assessment: A review — Part I: Fundamentals. Innovative Food Science & Emerging Technologies 19:1–14. doi: 10.1016/j.ifset.2013.04.014.
  • Xiang, B. Y., M. O. Ngadi, T. Gachovska, and B. K. Simpson. 2007. Pulse electric field treatment effects on rheological properties and color of soy milk. Paper presented at the 2007 ASAE Annual Meeting.
  • Xiaowei, H., Z. Xiaobo, Z. Jiewen, S. Jiyong, Z. Xiaolei, and M. Holmes. 2014. Measurement of total anthocyanins content in flowering tea using near infrared spectroscopy combined with ant colony optimization models. Food Chemistry 164:536–43.
  • Xu, L., A. L. Garner, B. Tao, and K. M. Keener. 2017. Microbial inactivation and quality changes in orange juice treated by high voltage atmospheric cold plasma. Food and Bioprocess Technology 10 (10):1778–91. doi: 10.1007/s11947-017-1947-7.
  • Xu, J., K. W. Plaxco, and S. J. Allen. 2006. Collective dynamics of lysozyme in water: Terahertz absorption spectroscopy and comparison with theory. The Journal of Physical Chemistry. B 110 (47):24255–9.
  • Xu, L., X. Yepez, B. Applegate, K. M. Keener, B. Tao, and A. L. Garner. 2020. Penetration and microbial inactivation by high voltage atmospheric cold plasma in semi-solid material. Food and Bioprocess Technology 13 (10):1688–702. doi: 10.1007/s11947-020-02506-w.
  • Yadav, B., and M. Roopesh. 2020. In-package atmospheric cold plasma inactivation of Salmonella in freeze-dried pet foods: Effect of inoculum population, water activity, and storage. Innovative Food Science & Emerging Technologies 66:102543. doi: 10.1016/j.ifset.2020.102543.
  • Yadav, B., A. C. Spinelli, N. Misra, Y. Y. Tsui, L. M. McMullen, and M. Roopesh. 2020. Effect of in‐package atmospheric cold plasma discharge on microbial safety and quality of ready‐to‐eat ham in modified atmospheric packaging during storage. Journal of Food Science 85 (4):1203–12. doi: 10.1111/1750-3841.15072.
  • Yan, B., D. Hu, and P. Shi. 2012. A traceable platform of aquatic foods supply chain based on RFID and EPC Internet of Things. International Journal of RF Technologies 4 (1):55–70. doi: 10.3233/RFT-2012-0035.
  • Yan, T., Q. Zhang, D. Wang, P. Li, X. Tang, and W. Zhang. 2019. Determination of deoxynivalenol by ELISA and immunochromatographic strip assay based on monoclonal antibodies. Toxin Reviews 40 (3):1–7.
  • Yavari, A., D. Georgakopoulos, H. Agrawal, H. Korala, P. P. Jayaraman, and J. K. Milovac. 2020. Internet of Things milk spectrum profiling for industry 4.0 dairy and milk manufacturing. Paper presented at the 2020 International Conference on Information Networking (ICOIN). doi: 10.1109/ICOIN48656.2020.9016608.
  • Zhang, W., Y. Liu, Z. Li, S. Xu, J. Zhang, K. Hettinga, and P. Zhou. 2021. Effects of microfiltration combined with ultrasonication on shelf life and bioactive protein of skim milk. Ultrasonics Sonochemistry 77:105668.
  • Zhao, G., Y. Guo, X. Sun, and X. Wang. 2015. A system for pesticide residues detection and agricultural products traceability based on acetylcholinesterase biosensor and internet of things. International Journal of Electrochemical Science 10 (4):3387–99.
  • Zheng, J., and L. He. 2014. Surface‐enhanced Raman spectroscopy for the chemical analysis of food. Comprehensive Reviews in Food Science and Food Safety 13 (3):317–28.
  • Zhou, J., L. Sheng, R. Lv, L. Donghong, T. Ding, and X. Liao. 2021. Application of a 360-degree radiation thermosonication technology for the inactivation of Staphylococcus aureus in milk. Frontiers in Microbiology:3217. doi: 10.3389/fmicb.2021.771770
  • Zia, S., M. R. Khan, X.‐A. Zeng, M. A. Shabbir, and R. M. Aadil. 2019. Combined effect of microwave and ultrasonication treatments on the quality and stability of sugarcane juice during cold storage. International Journal of Food Science & Technology 54 (8):2563–9. doi: 10.1111/ijfs.14167.
  • Zou, B., X. Shi, L. Wang, L. Zheng, G. Zhao, and X. Wang. 2020. Information milk powder traceability and rationalization sales system based on internet of things. In Innovative computing. Lecture Notes in Electrical Engineering, eds. C. T. Yang, Y. Pei, J. W. Chang, vol. 675:1881–7. Singapore: Springer. doi: 10.1007/978-981-15-5959-4_229.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.