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A Data-Driven Packaging Efficiency Optimization Method for a Low Carbon System in Agri-Products Cold Chain

Author

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  • Jingjie Wang

    (Institute of Agricultural Economics and Information, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China)

  • Xiaoshuan Zhang

    (College of Engineering, China Agricultural University, Beijing 100083, China
    Beijing Laboratory of Food Quality and Safety, Beijing 100083, China)

  • Xiang Wang

    (College of Engineering, China Agricultural University, Beijing 100083, China
    Beijing Laboratory of Food Quality and Safety, Beijing 100083, China)

  • Hongxing Huang

    (Institute of Agricultural Economics and Information, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China)

  • Jinyou Hu

    (College of Engineering, China Agricultural University, Beijing 100083, China
    Beijing Laboratory of Food Quality and Safety, Beijing 100083, China)

  • Weijun Lin

    (Institute of Agricultural Economics and Information, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China
    Key Laboratory of Urban Agriculture in South China, Ministry of Agriculture and Rural Affairs, Guangzhou 510640, China)

Abstract

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.

Suggested Citation

  • Jingjie Wang & Xiaoshuan Zhang & Xiang Wang & Hongxing Huang & Jinyou Hu & Weijun Lin, 2022. "A Data-Driven Packaging Efficiency Optimization Method for a Low Carbon System in Agri-Products Cold Chain," Sustainability, MDPI, vol. 14(2), pages 1-17, January.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:2:p:858-:d:723308
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    References listed on IDEAS

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    1. Sundarakani, Balan & Ajaykumar, Aneesh & Gunasekaran, Angappa, 2021. "Big data driven supply chain design and applications for blockchain: An action research using case study approach," Omega, Elsevier, vol. 102(C).
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    1. Liu, Zheng & Huang, Yu-Qing & Shang, Wen-Long & Zhao, Yuan-Jun & Yang, Zao-Li & Zhao, Zhao, 2022. "Precooling energy and carbon emission reduction technology investment model in a fresh food cold chain based on a differential game," Applied Energy, Elsevier, vol. 326(C).

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