Food chain analysis is a highly complex procedure since it relies on numerous criteria of various types: environmental, economical, functional, sanitary, etc. Quality objectives imply different stakeholders, technicians, managers, professional organizations, end-users, public collectivities, etc. Since the goals of the implied stakeholders may be divergent, decision-making raises arbitration issues. Arbitration can be done through a compromise - a solution that satisfies, at least partially, all the actors - or favor some of the actors, depending on the decision-maker's priorities. Several questions are open to support arbitration in food chains: what kind of representation and reasoning model is suitable to allow for contradictory viewpoints ? How can stakeholders' divergent priorities be taken into account ? How can the conflicts be solved to achieve a tradeoff within a decision-support system ? This paper proposes an artificial intelligence-based approach to formalize available knowledge as elements for decision-making. It develops an argumentation-based approach to support decision in food chains and presents an analysis of a case study concerning risks/benefits within the wheat to bread chain. It concerns the controversy about the possible change in the ash content of the flour used for commonly consumed French bread, and implies several stakeholders of the chain.