Feasibility of risk‐based inspections in organic farming: results from a probabilistic model

A risk‐based inspection system might improve the efficiency of the organic farming certification system and ultimately provide a basis for increased competitiveness of this sector. This requires the definition of an effective inspection procedure that allows statistical evaluation of critical risk factors for noncompliance. In this article, we present a study based on data from selected control bodies in five European countries that is aimed at determining the feasibility of risk‐based inspections in the organic sector according to the data that are currently routinely recorded. Bayesian networks are used for identification of the factors that can affect the risk of noncompliance. The results show that previous/concurrent noncompliant behavior explains most of the risk, and that the risk increases with farm size and the complexity of their operations. The data currently recorded by control bodies appear to be insufficient to establish an effective risk‐based approach to these inspections.