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Globalization and population explosion have worsened postharvest losses (PHL) in developing countries. This study looks to identify numerous controllable variables to reduce these losses and make the fresh produce supply chain more efficient.

The study employs the interpretive structural modelling (ISM) technique to develop a hierarchical model to comprehend the intricate relationships between the variables influencing PHL. These variables are further classified based on the relative levels of importance in terms of their driving and dependence powers.

The findings of this research provide variables for enterprises operating in fresh food supply chains to understand the specific risks that that supply chain faces and how these risks interact within the system. The fuzzy MICMAC analysis also classifies and highlights critical risk factors in the supply chain to aid implementation of PHL mitigation measures. The study highlights the importance of devising policies, legislation and efforts to regulate and curtail PHL across the global food supply chain.

The efficiency of the food supply chain contributes not only to economic sustainability but also to broader goals such as food security, better utilisation of global resources and sustainability in the supply chain.

It also highlights the significance of well-informed government policies, laws and regulations in successfully controlling and reducing PHL.

This study compares factors contributing to PHL in the fresh produce supply chain and emphasises the stakeholders’ critical role in alleviating these losses. It also highlights the significance of well-informed government policies, laws and regulations in successfully controlling and reducing PHL.