Abstract

The sterilization of raw ready-to-eat aquatic products is a crucial method for ensuring their safety for consumption after production. However, achieving intelligent decision-making and higher sterilization efficiency remains a technical challenge. In this paper, an intelligent ultraviolet c radiation (UVC) pulse sterilization system for raw ready-to-eat aquatic products processing lines is presented. The objective of intelligently classifying and grading aquatic products in an automated production line and then sterilizing them is attained. On the basis of the thermal radiation perspective factor method, an irradiation prediction model for the columnar pulsed UVC field is developed, and an automated decision model for the UVC sterilization level is developed in conjunction with the hierarchical analysis method. Automatic control of the UVC lamp is achieved with precision. Using a combination of direct measurements and simulation calculations, the accuracy of the prediction structure is verified. In addition, the system's key model, the UVC intensity decision model, was evaluated, and the results indicated that the decision model had an error rate of 13.3% in the sterilization of raw ready-to-eat aquatic products and that the system's sterilization rate could reach approximately 95%. Additionally, the economics of implementation and overall performance of the sterilization system were evaluated and determined to be effective in reducing spoilage rates and human resource losses, thereby promoting sustainable and clean production in the raw food fish processing industry.

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