Application of AI Technology in Food Processing and Detection
DOI:
https://doi.org/10.53469/ijomsr.2025.08(04).04Keywords:
AI Technology, Food Processing, Food TestingAbstract
the food to Ann first, food security problem is the common people's attention, so our country has strict management system for food processing and testing, in the process of food processing and detection, use safety, advanced technology, common technologies such as microbial enzyme technology, the advantages of this technology is in the process of food testing, Do not cause any damage to the nutrition of food, to ensure the safety and health of food. This paper mainly expounds the application of microbial enzyme technology in food processing and detection, popularizing relevant food safety knowledge and improving people's food safety awareness.
References
Lyu, T., Gu, D., Chen, P., Jiang, Y., Zhang, Z., & Pang, H. & Dong, Y.(2024). Optimized CNNs for Rapid 3D Point Cloud Object Recognition. arXiv preprint arXiv:2412.02855.
Chen, J., Zhang, X., Wu, Y., Ghosh, S., Natarajan, P., Chang, S. F., & Allebach, J. (2022). One-stage object referring with gaze estimation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 5021-5030).
Tang, Y., & Zhao, S. (2025). Research on Relationship Between Aging Population Distribution and Real Estate Market Dynamics based on Neural Networks.
Xu, G., Xie, Y., Luo, Y., Yin, Y., Li, Z., & Wei, Z. (2024). Advancing Automated Surveillance: Real-Time Detection of Crown-of-Thorns Starfish via YOLOv5 Deep Learning. Journal of Theory and Practice of Engineering Science, 4(06), 1–10. https://doi.org/10.53469/jtpes.2024.04(06).01
Zheng, S., Liu, S., Zhang, Z., Gu, D., Xia, C., Pang, H., & Ampaw, E. M. (2024). Triz method for urban building energy optimization: Gwo-sarima-lstm forecasting model. arXiv preprint arXiv:2410.15283.
Pang, H., Zhou, L., Dong, Y., Chen, P., Gu, D., Lyu, T., & Zhang, H. (2024). Electronic Health Records-Based Data-Driven Diabetes Knowledge Unveiling and Risk Prognosis. arXiv preprint arXiv:2412.03961.
Liu, S., Zhao, Z., He, W., Wang, J., Peng, J., & Ma, H. (2025). Privacy-Preserving Hybrid Ensemble Model for Network Anomaly Detection: Balancing Security and Data Protection. arXiv preprint arXiv:2502.09001.
Jin, T. (2024, October). Integrated machine learning for enhanced supply chain risk prediction. In Proceedings of the 2024 8th International Conference on Electronic Information Technology and Computer Engineering (pp. 1254-1259).
Wu, Y. (2024). Improving CTR Prediction in Advertising with XGBoost. Journal of Theory and Practice of Engineering Science, 4(05), 51-55.
Dai, Y., Wang, Y., Xu, B., Wu, Y., & Xian, J. (2020). Research on image of enterprise after-sales service based on text sentiment analysis. International Journal of Computational Science and Engineering, 22(2-3), 346-354.
Xie, Y., Li, Z., Yin, Y., Wei, Z., Xu, G., & Luo, Y. (2024). Advancing Legal Citation Text Classification A Conv1D-Based Approach for Multi-Class Classification. Journal of Theory and Practice of Engineering Science, 4(02), 15–22. https://doi.org/10.53469/jtpes.2024.04(02).03
Yin, Y., Xu, G., Xie, Y., Luo, Y., Wei, Z., & Li, Z. (2024). Utilizing Deep Learning for Crystal System Classification in Lithium - Ion Batteries. Journal of Theory and Practice of Engineering Science, 4(03), 199–206. https://doi.org/10.53469/jtpes.2024.04(03).19
Luo, Y., Wei, Z., Xu, G., Li, Z., Xie, Y., & Yin, Y. (2024). Enhancing E-commerce Chatbots with Falcon-7B and 16-bit Full Quantization. Journal of Theory and Practice of Engineering Science, 4(02), 52–57. https://doi.org/10.53469/jtpes.2024.04(02).08
Zhao, S., Lu, Y., Gong, C., & Xu, Q. (2025). Research on Labour Market Efficiency Evaluation Under Impact of Media News Based on Machine Learning and DMP Model.
Yan, H., Wang, Z., Xu, Z., Wang, Z., Wu, Z., & Lyu, R. (2024, July). Research on image super-resolution reconstruction mechanism based on convolutional neural network. In Proceedings of the 2024 4th International Conference on Artificial Intelligence, Automation and High Performance Computing (pp. 142-146).
Wu, W. (2025). Fault Detection and Prediction in Models: Optimizing Resource Usage in Cloud Infrastructure.
Yao, T. (2024, August). Research on the Local Head Loss Coefficient in Short-Tube Hydraulic Testing. In 2024 3rd International Conference on Applied Mechanics and Engineering Structures (AMES 2024) (pp. 89-97). Atlantis Press.
Long, Y., Gu, D., Li, X., Lu, P., & Cao, J. (2024, September). Enhancing Educational Content Matching Using Transformer Models and InfoNCE Loss. In 2024 IEEE 7th International Conference on Information Systems and Computer Aided Education (ICISCAE) (pp. 11-15). IEEE.