Development and design of an intelligent monitoring system for cold chain meat freshness

Abstract

Cold chain meat has become the main force of meat consumption in China due to its unique taste and rich nutrition. However, there are serious regulatory blind spots throughout the cold chain process, making it difficult to monitor the freshness quality and shelf life of cold chain meat in real time. Therefore, in this study, the dominant spoilage microorganism prediction model for cold chain meat was parsed to predict the logarithmic value of the dominant spoilage microorganism in real time based on temperature information, which was compared with the freshness quality threshold to derive real-time quality information. This paper proposes to develop the system with ASP.NET three-tier architecture as the development framework and .NET Framework 4.6.2 as the development environment. Combining MySQL 5.7.31 application database, Vue 2.6 and Apache ECharts front-end technology development a intelligent monitoring system for cold chain meat freshness. The system has five core application modules: multi-role login module, big data visualization and analysis module, product information management module, product freshness quality and shelf life real-time monitoring and warning module, and system setting module, to monitor the freshness quality and shelf life of cold chain meat products at all stages, real time. The development of this system can realize the real-time supervision of the quality of cold chain meat products in the whole industrial chain of processing, storage, transportation and sales, timely detect product abnormalities, provide technical support for food enterprises, and provide food safety assurance for consumers.

Keywords

• cold chain meat
• quality prediction
• freshness
• intelligent supervision
• system development