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<p>Agri-food systems globally experience growing difficulties associated with losses after harvesting, irregular quality, and inefficient utilization of resources, particularly within fruit supply chain (FSC). Given the complicated structure in FSCs, it is critical to guarantee quality at all levels to sustain customer satisfaction and optimize the utilization of resources. Conventional inspections and grading techniques are frequently challenging, unreliable, and ineffective, necessitating the urgent implementation of advanced automation. Artificial Intelligence (AI) is now recognized as a revolutionary factor in redefining quality control methodologies within the agri-food sector. Therefore, considering these as research gaps, the research aims to thoroughly analyze evolution in advancements of AI applications in FSCs, concentrating on quality assurance, traceability, and sustainability outcomes, acknowledging the constraints of traditional postharvest methods. The research utilizes a systematic theme synthesizing and conceptual framework methodology to analyze the AI related technological advancements. AI applications are classified into five strategic themes along with potential enablers, challenges, and transformative potential applications. The findings indicates that AI improves decision-making, precision, minimizes operational inefficiencies, and promotes compliance with net-zero and circular economy objectives. Thus, the research proposes a conceptual framework integrating all essential components of FSC, intervention of AI, existing challenges, potential outcomes and future research agenda towards possible development in AI. The research’s contribution includes development of integrated framework bridging all related components with sustainable development. It provides a strategic roadmap for researchers, industry stakeholders, regulators and tech developers, enhancing the discussion on sustainable digital transformation FSC.</p>

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An integrated conceptual framework for AI-driven fruit supply chain quality management: pathways toward circularity and sustainability

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月9日

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  • H. M. Shrestha,
  • Mohit Malik,
  • Vijay Kumar Gahlawat,
  • Rahul S. Mor,
  • Ashish Mor,
  • Mona Sharma

摘要

Agri-food systems globally experience growing difficulties associated with losses after harvesting, irregular quality, and inefficient utilization of resources, particularly within fruit supply chain (FSC). Given the complicated structure in FSCs, it is critical to guarantee quality at all levels to sustain customer satisfaction and optimize the utilization of resources. Conventional inspections and grading techniques are frequently challenging, unreliable, and ineffective, necessitating the urgent implementation of advanced automation. Artificial Intelligence (AI) is now recognized as a revolutionary factor in redefining quality control methodologies within the agri-food sector. Therefore, considering these as research gaps, the research aims to thoroughly analyze evolution in advancements of AI applications in FSCs, concentrating on quality assurance, traceability, and sustainability outcomes, acknowledging the constraints of traditional postharvest methods. The research utilizes a systematic theme synthesizing and conceptual framework methodology to analyze the AI related technological advancements. AI applications are classified into five strategic themes along with potential enablers, challenges, and transformative potential applications. The findings indicates that AI improves decision-making, precision, minimizes operational inefficiencies, and promotes compliance with net-zero and circular economy objectives. Thus, the research proposes a conceptual framework integrating all essential components of FSC, intervention of AI, existing challenges, potential outcomes and future research agenda towards possible development in AI. The research’s contribution includes development of integrated framework bridging all related components with sustainable development. It provides a strategic roadmap for researchers, industry stakeholders, regulators and tech developers, enhancing the discussion on sustainable digital transformation FSC.