Mathematical and Computer Science Methods for Food Science and Industry

Food processing and agricultural products catering companies are one of the major employers and economic forces in the EU, representing both a central component of the agro-food system, and a crucial provider of biomaterials and biofuels. In recent years, this strategic industry has been facing unprecedented challenges, mainly concerning food security and the threat of climate change. Additionally, the production of processed agricultural products needs to adopt and comply with several new regulations, aiming at reducing waste, improving re-utilization of by-products, limiting energy consumption and lowering the overall environmental impact. These demanding objectives can only be achieved through appropriate adaptation and innovation in the food processing activity. Disruptive innovations, however, require considerable economic efforts and the development of new skills not readily available in the agro-food domain, especially in small and medium enterprises (SMEs). A considerable number of unsustainable practices are still in place, due to the high cost of experimenting with new techniques on existing production/supply chains and validating scale-up. Developing Mathematical and Computer Science (MCS) models for the target processes can undoubtedly contribute to solving the issue, allowing even SMEs to optimize resource management and economic outputs, while guaranteeing the current levels of quality and availability of products.
The agro-food industry, however, is not a traditional application domain for MCS: at the moment, there is no structured community around this issue, nor a coordinated effort to advance the state of the art; and building adequate mathematical models for specific applications is extremely knowledge and labour intensive. It is the role of academic research to initiate the development of methods, functional models, software or technologies, which will be critical to guide the evolution of the food processing industry with regards to the grand challenges of the future. MCS researchers and practitioners can also benefit from working on agro-products industry applications, since the field provides considerable challenges to existing methodologies in MCS: uncertainty of the data, multi-scale description of the systems, coupling of models, representation of expert knowledge, etc. As the upcoming challenges for the industry grow more pressing, promoting cooperation between agro-food and applied mathematics becomes more and more urgent. The aim of this COST Action is thus to create a community of scientists and practitioners from the two different domains, stimulating the emergence of new research and ideas tackling these ambitious topics. The development of novel mathematical and computer models, following the complex systems and knowledge engineering paradigms, has been slowly gaining support in the agro-food community over the last two decades. Existing projects, however, are scattered and uncoordinated, focusing more on the solutions to specific issues than on an organized collection of demands and techniques in the field: for these reasons, major methodological breakthroughs, even stemming from applications, are still extremely rare.
Although food production is a major industry in most countries, the number of publications dedicated to the treatment of food industry problems by means of innovative MCS modelling is well below that of other types of industries. Coordinating the currently divided research efforts is crucial to avoid re-discoveries and dispersion of useful data, and at the same time promoting the sharing of theoretical and experimental results. Moreover, the application domain of agro-food products is rich and multi-faceted, and research efforts so far have not been balanced over all aspects. As a result, several features of the considered challenges are not well understood, while the expertise around others should be further developed. Significant progress in the domain can be obtained by providing a roadmap with well-defined MCS problems addressing critical issues in food processing, in particular food security and sustainability. This issue calls for the close collaboration of domain specialists with mathematicians and computer scientists.