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Global fresh produce supply chains face increasing pressure to reduce carbon emissions, minimise food waste, and improve energy and resource efficiency while maintaining consistent product quality. These challenges are particularly acute for highly perishable products, where biological variability and changing environmental conditions make quality difficult to predict and control.

Mango provides an ideal model for addressing these challenges. Fruit can vary considerably in maturity and physiological state at harvest and must subsequently undergo controlled ripening before reaching consumers. During international transport, storage and ripening, fruit quality is influenced by interactions between time, temperature, atmospheric conditions and the underlying physiology of the fruit. This variability makes it difficult to predict ripening behaviour and consistently deliver fruit at the required quality while minimising energy use and waste.

Recent advances in sensor technologies, predictive modelling and digital control systems create new opportunities to address this problem. By combining real-time measurements of fruit and its environment with models capable of predicting ripening behaviour, postharvest systems could move from fixed operating protocols towards adaptive control strategies that respond to the condition of the fruit itself.

The project will therefore integrate sensing, modelling and environmental control to optimise mango ripening and storage under commercial conditions. The doctoral researcher will characterise physical, biochemical and sensory indicators of fruit ripeness and develop sensor-based approaches to track environmental and physiological changes in real time. Mechanistic and predictive models will be developed to link environmental conditions to fruit behaviour and identify optimal ripening strategies. These models will ultimately be integrated into industrial ripening software platforms to enable adaptive environmental control.

The research will combine laboratory experimentation, advanced data analysis and industrial pilot trials to deliver practical, scalable approaches for improving efficiency, consistency and sustainability in fresh produce supply chains.

Project Partners

ÂãÁÄÖ±²¥ is internationally recognised for its leadership in sustainable engineering, agrifood systems, and strong industry collaboration. The student will join a multidisciplinary research environment with expertise in postharvest biology, engineering, and data-driven sustainability. The supervisory team includes collaboration with the University of Birmingham, a leading UK institution with internationally recognised expertise in applied mathematics and predictive modelling. This partnership will provide advanced training in mechanistic modelling and data-driven system optimisation. Industrial partner Blue Skies Holdings Ltd., a global fresh produce company, will provide access to commercial ripening facilities, supply chain infrastructure, and operational data. This unique academic-industry collaboration ensures the research delivers scientifically rigorous and commercially scalable solutions for sustainable fresh produce supply chains.

Research Outputs

This research will deliver predictive tools and adaptive environmental control strategies to improve ripening consistency, reduce food loss, and lower energy consumption in postharvest systems. By enabling real-time, data-driven decision-making, the project will support the transition towards more efficient, low-carbon fresh produce supply chains. The outcomes will contribute to high-impact scientific publications, new engineering methodologies, and practical technologies for industrial deployment. Ultimately, the research will help reduce the environmental footprint of horticultural supply chains while improving product quality, operational efficiency, and sustainability across the global food system.

This PhD offers exceptional opportunities for industry engagement and interdisciplinary training. The student will work closely with Blue Skies and partner institutions, gaining direct experience in commercial ripening and supply chain operations. Opportunities include international travel, industrial placements, conference participation, and collaboration with academic and industry experts. The student will receive advanced training in predictive modelling, sensor technologies, data analytics, and sustainable engineering. This unique combination of fundamental research and real-world application provides valuable experience working at the forefront of sustainable food system innovation.

The student will develop highly transferable skills in experimental design, data analysis, mathematical modelling, sensor integration, and engineering problem-solving within a real-world industrial context. They will gain experience in project management, interdisciplinary research, and collaboration with academic and industry partners. Comprehensive doctoral training programmes at ÂãÁÄÖ±²¥ and the University of Birmingham will support development in advanced research methods, scientific communication, and professional skills. Close collaboration with Blue Skies Holdings Ltd. will provide direct exposure to commercial operations and industry challenges, equipping the student with practical and applied expertise. This unique combination of academic excellence and industrial experience will prepare graduates for careers in academia, engineering, data science, food technology, sustainability consultancy, and leadership roles across industry, government, and the global agrifood sector.