文献类型： 外文期刊

作者： Wang, Jingjie ¹ ; Zhang, Xiaoshuan ² ; Wang, Xiang ² ; Huang, Hongxing ¹ ; Hu, Jinyou ² ; Lin, Weijun ¹ ;

作者机构： 1.Guangdong Acad Agr Sci, Inst Agr Econ & Informat, Guangzhou 510640, Peoples R China

2.China Agr Univ, Coll Engn, Beijing 100083, Peoples R China

3.Beijing Lab Food Qual & Safety, Beijing 100083, Peoples R China

4.Minist Agr & Rural Affairs, Key Lab Urban Agr South China, Guangzhou 510640, Peoples R China

关键词： data-driven; fresh produce cold chain; efficient packages; sustainability; dynamic packaging efficiency evaluation

期刊名称：SUSTAINABILITY （ 影响因子：3.889； 五年影响因子：4.089 ）

ISSN：

年卷期： 2022 年 14 卷 2 期

页码：

收录情况： SCI

摘要： The of monitoring the Internet of Things (IoT) in the cold chain allows process data, including packaging data, to be more easily accessible. Proper optimization modelling is the core driving force towards the green and low-carbon operation of cold chain logistics, laying the necessary foundation for the development of a data-driven modelling system. Since efficient packaging is necessary for loss control in the cold chain, its final efficiency during circulation is important for realizing continuous loss prevention and efficient supply. Thus, it is urgent to determine how to utilize these continuously acquired data and how to formulate a more accurate packaging efficiency control methodology in the agri-products cold chain. Through continuous monitoring, we examined the feasibility of this topic by focusing on the concept of data-driven evaluation modelling and the dynamic formation mechanism of comprehensive packaging efficiency in cold chain logistics. The packaging efficiency in the table grape cold chain was used as an example to evaluate the comprehensive efficiency evaluation index system and data-driven evaluation framework proposed in this paper. Our results indicate that the established methodology can adapt to the continuity of comprehensive packaging efficiency, also reflecting the comprehensive efficiency evaluation of the packaging for different times and distances. Through the evaluation of our results, the differences and the dynamic processes between different final packaging efficiencies at different moments are effectively displayed. Thus, the continuous improvement of a low-carbon system in cold chain logistics could be realized.