How Artificial Intelligence Can Predict Plant Production
November 7, 2019 
Wageningen University and Research in the Netherlands is digging even deeper into how artificial intelligence can be integrated into greenhouse production.
A new research project focuses on whether it might be possible to predict cucumber harvest, and what information artificial intelligence needs to make correct predictions. To answer this, the Business Unit Greenhouse Horticulture at Wageningen University & Research is working on the development of an AI yield prediction model and associated database.
A greenhouse is a complex system with several components such as crop, climate, and irrigation set-up. Within this system, sensors measure various plant characteristics with optical and imaging techniques. As a result, the plant itself acts as a sensor of its own biological status and its environment. Nowadays, growers monitor the crop and decide on alterations of their greenhouse management to achieve production goals.
Combining the intuition of experienced growers with sensors that continuously collect data can offer great opportunities. A database can be filled with meaningful and adequate data describing the status of climate and crop. Useful information in the datasets can be distilled and used towards data-driven decisions made with AI.
The GrowDat project aims to develop an AI framework that identifies the important climate and crop parameters for making accurate yield predictions. AI can support growers’ decisions, better understand underlying processes, and discover new patterns of the greenhouse production system.
The research aims at building expertise for the future and is funded by the Business Unit Greenhouse Horticulture of Wageningen University and Research. Relevant research to AI is performed in the Autonomous Greenhouse International Challenge. Visit the Autonomous Greenhouses website for updates on the latest implementations of AI in greenhouse horticulture.
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