Food Safety Related Data Analytics, Digital, and Artificial Intelligence Needs and Opportunities in Controlled Environment Agriculture

Controlled Environment Agriculture (CEA) is increasingly used to grow food (namely fruits and vegetables) in con-trolled indoor conditions. While often billed as “eliminating” the classical food safety concerns associated with open field cultivation of produce, traditional as well as potentially novel microbial food safety risks are a concern for CEA, as supported by a recent salmonellosis outbreak in the U.S. linked to CEA grown produce. In addition, the use of diverse technologies and practices in CEA represents a challenge in efforts to develop food safety guidance. CEA, particularly precision vertical farms, however, have the dis-tinct advantage of being “data intense” and typically have a better data collection and management structure than is found in traditional agriculture. This may position at least part of the industry to use digital tools digital tools and Artificial Intelligence (AI) to manage manage food safety. Possible AI approaches may include adaptive sampling and interventions depending on the presence of risk factors that could be predicted with the routine data generated during CEA operations. This article summarizes challenges and opportunities for using AI and digital approaches to as-sure microbial food safety and manage food safety related business risks in CEA.