College of Engineering, China Agricultural University, Beijing 100083, China; Sanya Institute of China Agricultural University, Sanya 572025, China.
College of Engineering, China Agricultural University, Beijing 100083, China.
Food Res Int. 2024 Sep;191:114702. doi: 10.1016/j.foodres.2024.114702. Epub 2024 Jul 2.
Sterilization of Northern shrimp (Pandalus borealis) is a key tool to ensure their freshness for post-production transportation. However, in the face of the specific problem of quality deterioration caused by the increase of storage environment temperature due to unexpected circumstances or the prolongation of temporary storage time, it is still a technical challenge to realize intelligent decision-making and higher sterilization efficiency. In this paper, we propose an intelligent UV-Ozone sterilization system suitable for cold chain transportation of Northern shrimp (Pandalus borealis). Using hierarchical analysis, equipartition method and the prediction method of generalized linear model, combined with the technology of intelligent control and remote control, we realized the automatic control of the system's UV irradiance from 324 ∼ 1620 J/m, and ozone concentration from21.4 ∼ 107 mg/cm in a graded manner. The accuracy of the predicted structure was verified using a combination of direct measurement and simulation. In addition, the key model of the system, the intensity level decision model, was tested, and the test results showed that the decision model was able to accurately make decisions during the sterilization of Northern shrimp (Pandalus borealis), and the system was able to achieve a sterilization effect of 1-3 orders of magnitude. This reduces quality loss due to unexpected conditions, facilitates real-time monitoring of transported samples by staff, extends the shelf life of the samples, and improves the accuracy of sterilization, increasing the economic value of Northern shrimp (Pandalus borealis).
北方长额虾（Pandalus borealis）的杀菌是确保其在产后运输中保持新鲜度的关键工具。然而，面对由于意外情况或临时储存时间延长导致储存环境温度升高而引起的特定质量恶化问题，实现智能决策和更高的杀菌效率仍然是一个技术挑战。在本文中，我们提出了一种适用于北方长额虾（Pandalus borealis）冷链运输的智能 UV-Ozone 杀菌系统。使用层次分析法、等分法和广义线性模型的预测方法，结合智能控制和远程控制技术，我们实现了系统 UV 辐照度从 324∼1620 J/m，以及臭氧浓度从 21.4∼107 mg/cm 的自动分级控制。通过直接测量和模拟相结合的方法验证了预测结构的准确性。此外，对系统的关键模型，即强度水平决策模型进行了测试，测试结果表明，该决策模型能够在北方长额虾（Pandalus borealis）的杀菌过程中做出准确的决策，并且该系统能够实现 1-3 个数量级的杀菌效果。这减少了由于意外情况而导致的质量损失，便于工作人员实时监测运输样本，延长了样本的保质期，并提高了杀菌的准确性，增加了北方长额虾（Pandalus borealis）的经济价值。
