The global population is increasing rapidly, together with the demand for healthy fresh food. The greenhouse industry can play an important role, but encounters difficulties finding skilled staff to manage crop production. Artificial intelligence (AI) has reached breakthroughs in several areas, however, not yet in horticulture. An international competition on “autonomous greenhouses” aimed to combine horticultural expertise with AI to make breakthroughs in fresh food production with fewer resources. Five international teams, consisting of scientists, professionals, and students with different backgrounds in horticulture and AI, participated in a greenhouse growing experiment. Each team had a 96 m2 modern greenhouse compartment to grow a cucumber crop remotely during a 4-month-period. Each compartment was equipped with standard actuators (heating, ventilation, screening, lighting, fogging, CO2 supply, water and nutrient supply). Control setpoints were remotely determined by teams using their own AI algorithms. Actuators were operated by a process computer. Different sensors continuously collected measurements. Setpoints and measurements were exchanged via a digital interface. Achievements in AI-controlled compartments were compared with a manually operated reference. Detailed results on cucumber yield, resource use, and net profit obtained by teams are explained in this paper. We can conclude that in general AI performed well in controlling a greenhouse. One team outperformed the manually-grown reference.

Greenhouses and indoor farming systems play an important role in providing fresh and nutritious food for the growing global population. Farms are becoming larger and greenhouse growers need to make complex decisions to maximize production and minimize resource use while meeting market requirements. However, highly skilled labor is increasingly lacking in the greenhouse sector. Moreover, extreme events such as the COVID-19 pandemic, can make farms temporarily less accessible. This highlights the need for more autonomous and remote-control strategies for greenhouse production. This paper describes and analyzes the results of the second “Autonomous Greenhouse Challenge”. In this challenge, an experiment was conducted in six high-tech greenhouse compartments during a period of six months of cherry tomato growing. The primary goal of the greenhouse operation was to maximize net profit, by controlling the greenhouse climate and crop with AI techniques. Five international teams with backgrounds in AI and horticulture were challenged in a competition to operate their own compartment remotely. They developed intelligent algorithms and use sensor data to determine climate setpoints and crop management strategy. All AI supported teams outperformed a human-operated greenhouse that served as reference. From the results obtained by the teams and from the analysis of the different climate-crop strategies, it was possible to detect challenges and opportunities for the future implementation of remote-control systems in greenhouse production.

The COVID-19 pandemic unveiled the fragility of food sovereignty in cities and confirmed the close connection urban dwellers have with food. Although the pandemic was not responsible for a systemic failure, it suggested how citizens would accept and indeed support a transition toward more localized food production systems. As this attitudinal shift is aligned with the sustainability literature, this work aims to explore the tools and actions needed for a policy framework transformation that recognizes the multiple benefits of food systems, while considering local needs and circumstances. This perspective paper reviews the trends in production and consumption, and systematizes several impacts emerged across European food systems in response to the first wave of pandemic emergency, with the final aim of identifying challenges and future strategies for research and innovation toward the creation of resilient and sustainable city/region food systems. The proposal does not support a return to traditional small-scale economies that might not cope with the growing global population. It instead stands to reconstruct and upscale such connections using a “think globally act locally” mind-set, engaging local communities, and making existing and future citizen-led food system initiatives more sustainable. The work outlines a set of recommended actions for policy-makers: support innovative and localized food production, training and use of information and communication technology for food production and distribution; promote cross-pollination among city/region food systems; empower schools as agents of change in food provision and education about food systems; and support the development of assessment methodologies and the application of policy tools to ensure that the different sustainability dimensions of the food chain are considered.

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Attention to urban agriculture (UA) has recently grown among practitioners, scientists, and the public, resulting in several initiatives worldwide. Despite the positive perception of modern UA and locally grown, fresh produce, the potential food safety risks connected to these practices may be underestimated, leading to regulatory gaps. Thus, there is a need for assessment tools to evaluate the food safety risks connected to specific UA initiatives, to assist practitioners in self-evaluation and control, and to provide policy makers and scholars a means to pursue and assess food safety in city regions, avoiding either a lack or an excess of regulation that could ultimately hinder the sector. To address this aim, this paper reviews the most recent and relevant literature on UA food safety assessments. Food safety indicators were identified first. Then, a food safety assessment framework for UA initiatives was developed. The framework uses business surveys and food analyses (if available) as a data source for calculating a food safety index for single UA businesses and the whole UA landscape of a given city region. The proposed framework was designed to allow its integration into the CRFS (City Region Food System) toolkit developed by FAO (Food and Agriculture Organization of the United Nations), RUAF foundation (Resource Centres on Urban Agriculture and Food Security) and Wilfrid Laurier University.