Understanding, defining and assessing food systems’ social and economic sustainability indicators: implementation of mixed methodologies for policy insights

Sustainability encompasses the presence of three dimensions that must coexist simultaneously, namely the environmental, social, and economic ones. The economic and social dimensions are gaining the spotlight in recent years, especially within food systems. To assess social and economic impacts, indicators and tools play a fundamental role in contributing to the achievements of sustainability targets, although few of them have deepen the focus on social and economic impacts. Moreover, in a framework of citizen science and bottom-up approach for improving food systems, citizen play a key role in defying their priorities in terms of social and economic interventions. This research expands the knowledge of social and economic sustainability indicators within the food systems for robust policy insights and interventions. This work accomplishes the following objectives: 1) to define social and economic indicators within the supply chain with a stakeholder perspective, 2) to test social and economic sustainability indicators for future food systems engaging young generations. The first objective was accomplished through the development of a systematic literature review of 34 social sustainability tools, based on five food supply chain stages, namely production, processing, wholesale, retail, and consumer considering farmers, workers, consumers, and society as stakeholders. The second objective was achieved by defining and testing new food systems social and economic sustainability indicators through youth engagement for informed and robust policy insights, to provide policymakers suggestions that would incorporate young generations ones. Future food systems scenarios were evaluated by youth through focus groups, whose results were analyzed through NVivo and then through a survey with a wider platform. Conclusion addressed the main areas of policy interventions in terms of social and economic aspects of sustainable food systems youth pointed out as in need of interventions, spanning from food labelling reporting sustainable origins to better access to online food services.

Ethical Perspectives on Big Data in Agri-food: Ownership and Governance for Safety

Big data are reshaping the way we interact with technology, thus fostering new applications to increase the safety-assessment of foods. An extraordinary amount of information is analysed using machine learning approaches aimed at detecting the existence or predicting the likelihood of future risks. Food business operators have to share the results of these analyses when applying to place on the market regulated products, whereas agri-food safety agencies (including the European Food Safety Authority) are exploring new avenues to increase the accuracy of their evaluations by processing Big data. Such an informational endowment brings with it opportunities and risks correlated to the extraction of meaningful inferences from data. However, conflicting interests and tensions among the involved entities - the industry, food safety agencies, and consumers - hinder the finding of shared methods to steer the processing of Big data in a sound, transparent and trustworthy way. A recent reform in the EU sectoral legislation, the lack of trust and the presence of a considerable number of stakeholders highlight the need of ethical contributions aimed at steering the development and the deployment of Big data applications. Moreover, Artificial Intelligence guidelines and charters published by European Union institutions and Member States have to be discussed in light of applied contexts, including the one at stake. This thesis aims to contribute to these goals by discussing what principles should be put forward when processing Big data in the context of agri-food safety-risk assessment. The research focuses on two interviewed topics - data ownership and data governance - by evaluating how the regulatory framework addresses the challenges raised by Big data analysis in these domains. The outcome of the project is a tentative Roadmap aimed to identify the principles to be observed when processing Big data in this domain and their possible implementations.

Instrumental and sensory analyses for the characterization of food, phytotherapeutic or pharmaceutical hemp products

To address the request to develop rapid and easy methods for determining the cannabinoids, an HPLC-UV method (8 min) to separate and quantify the 10 main cannabinoids in hemp inflorescences was developed, and in-house validated. Moreover, the antioxidant activity of cannabidiol (CBD) in two oily matrices was investigated and compared to that of α-tocopherol, in relation to the growing market of oily solutions containing cannabidiol. Then, since no univocal legislation on the evaluation of quality and authenticity of hemp seed oil (HSO) exists, the composition and quality of cold-pressed HSOs were also explored, highlighting a great variability in terms of oxidative state minor compounds content. From the sensory point of view, a panel was trained, a specific sensory wheel and a profile sheet were developed. Due to the Covid-19 pandemic, the sensory evaluation was also performed at home. The panel showed a good performance both in the laboratory and remotely. Moreover, a focus group was used to investigate consumers’ attitudes, pointing out that a high-quality HSO has to be cold-pressed and green for them. Then, the evaluation of stability during the storage of HSOs was investigated. The results showed that photo-oxidation did not seem to significantly affect the quality of the oil during the first 3 months of storage. Finally, a study about the evolution of the volatile profile of 9 HSOs, under accelerated oxidation conditions, allowed identifying volatile markers of HSOs oxidation and freshness. This Ph.D. was developed in the context of the scholarship “Harmonized procedures of analysis of medical, herbal, food and industrial cannabis: development and validation of cannabinoids’ quality control methods, of extraction and preparation of derivatives from the plant raw material, according to the product destination” funded by Enecta S.r.l.