Designing Food Supply Chain for Nutritional Delivery and Traceability

Motivation: It is estimated that the number of undernourished people will exceed 840 million by 2030 with the Covid pandemic alone adding an additional 132 million. More than 2 billion people do not have regular access to nutritious and sufficient food with this trend increasing. In 2019 nearly 22% of children worldwide were estimated to suffer from some type of child malnutrition with over 340 million suffering form of micronutrient deficiencies. Traditionally our food supply chains have been designed to satisfy human hunger and taste. However, there is increasing demand coupled with sustainable development goals to design food supply chains that deliver the right nutritional content to the end consumer.

Background: Although over the last four decades the quantity and quality of food supply has increased for millions of people, this nutritional challenge still stands. Availability and affordability play a large role in how people modify their diets as well as stability of food supply, what domestic foods are available and access to trade. These are further impacted by supply chains that focus on delivering produce without the direct ability to identify, track or trace its nutritional content.
The transformation of supply chain from product volume to product functionality offers one way to tackle this challenge. This will involve changes to farming practices, storing, transportation and secondary processing, along with trace and track technologies. Therefore, this PhD topic focuses on nutritional delivery, traceability and security, and losses across the supply chain. It aims to explore the application of robotics, sensors, distributed systems, and supply chain digitisation to identify linkages between supply chain design (product, process and location) and nutrition losses (micro). Using nutrition as a data point the optimisation of supply chains to take into account product functionality as part of its digital journey opens up new ways of visualising all supply chains from food to screw threads to turbine engines. Recognising product life cycle management as well as improved circular economy benefits become increasingly possible.

Research Methods: Research methods is expected to consist of desktop design and study as well as infield analysis. Development of frameworks and associated supply chain models along with pilot test simulations will be created. Cross disciplinary work with roboticists, botanist, biochemists, food physicists and farmers, as well as cross industry supply chain specialists will be required. These skills are all available and accessible within the host institution and proposed industry sponsor.

Outputs of Research: The outcome of this research includes the food supply chain -nutrition management tool for companies and end consumer. Academically, this research contributes to supply chain design theory, where there is limited research on the impact of product functionality on the food supply chain." The scoping of this research will be conducted in collaboration with Dyson Farms through an industrial project linked with EPSRC CDT in Agri-Food Robotics.

The proposed CDT provides a unique vision of advanced RAS technologies embedded throughout the food supply chain, training the next generation of specialists and leaders in agri-food robotics and providing the underpinning research for the next generation of food production systems. These systems in turn will support the sustainable intensification of food production, the national agri-food industry, the environment, food quality and health.

RAS technologies are transforming global industries, creating new business opportunities and driving productivity across multiple sectors. The Agri-Food sector is the largest manufacturing sector of the UK and global economy. The UK food chain has a GVA of £108bn and employs 3.6m people. It is fundamentally challenged by global population growth, demographic changes, political pressures affecting migration and environmental impacts. In addition, agriculture has the lowest productivity of all industrial sectors (ONS, 2017). However, many RAS technologies are in their infancy - developing them within the agri-food sector will deliver impact but also provide a challenging environment that will significantly push the state of art in the underpinning RAS science. Although the opportunity for RAS is widely acknowledged, a shortage of trained engineers and specialists has limited the delivery of impact. This directly addresses this need and will produce the largest global cohort of RAS specialists in Agri-Food.

The impacts are multiple and include;

1) Impact on RAS technology. The Agri-Food sector provides an ideal test bed to develop multiple technologies that will have application in many industrial sectors and research domains. These include new approaches to autonomy and navigation in field environments; complex picking, grasping and manipulation; and novel applications of machine learning and AI in critical and essential sectors of the world economy.

2) Economic Impact. In the UK alone the Made Smarter Review (2017) estimates that automation and RAS will create £183bn of GVA over the next decade, £58bn of which from increased technology exports and reshoring of manufacturing. Expected impacts within Agri-Food are demonstrated by the £3.0M of industry support including the world largest agricultural engineering company (John Deere), the multinational Syngenta, one of the world's largest robotics manufacturers (ABB), the UK's largest farming company owned by James Dyson (one of the largest private investors in robotics), the UK's largest salads and fruit producer plus multiple SME RAS companies. These partners recognise the potential and need for RAS (see NFU and IAgrE Letters of Support).

3) Societal impact. Following the EU referendum, there is significant uncertainty that seasonal labour employed in the sector will be available going forwards, while the demographics of an aging population further limits the supply of manual labour. We see robotic automation as a means of performing onerous and difficult jobs in adverse environments, while advancing the UK skills base, enabling human jobs to move up the value chain and attracting skilled workers and graduates to Agri-Food.

4) Diversity impact. Gender under-representation is also a concern across the computer science, engineering and technology sectors, with only 15% of undergraduates being female. Through engagement with the EPSRC ASPIRE (Advanced Strategic Platform for Inclusive Research Environments) programme, AgriFoRwArdS will become an exemplar CDT with an EDI impact framework that is transferable to other CDTs.

5) Environmental Impact. The Agri-food sector uses 13% of UK carbon emissions and 70% of fresh water, while diffuse pollution from fertilisers and pesticides creates environmental damage. RAS technology, such as robotic weeders and field robots with advanced sensors, will enable a paradigm shift in precision agriculture that will sustainably intensify production while minimising environmental impacts.