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Cherry Tomato Production in Intelligent Greenhouses—Sensors and AI for Control of Climate, Irrigation, Crop Yield, and Quality

Business Unit Greenhouse Horticulture, Wageningen University & Research (WUR), 6708PB Wageningen, The Netherlands
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Sensors 2020, 20(22), 6430; https://doi.org/10.3390/s20226430
Received: 21 October 2020 / Revised: 3 November 2020 / Accepted: 6 November 2020 / Published: 11 November 2020
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. View Full-Text
Keywords: artificial intelligence; sensors; resource use efficiency; tomato yield; indoor farming; autonomous greenhouses; climate control; irrigation control; remote control; data driven growing artificial intelligence; sensors; resource use efficiency; tomato yield; indoor farming; autonomous greenhouses; climate control; irrigation control; remote control; data driven growing
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Hemming, S.; Zwart, F.; Elings, A.; Petropoulou, A.; Righini, I. Cherry Tomato Production in Intelligent Greenhouses—Sensors and AI for Control of Climate, Irrigation, Crop Yield, and Quality. Sensors 2020, 20, 6430.

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