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understanding water management and light distribution

Digital twin technology deployed for 3D plant growth model

Predicting crop growth is becoming increasingly sophisticated. Wageningen University & Research BU Glasshouse Horticulture uses so-called digital twins for this purpose. This technology links data from the greenhouse environment to 3D functional-structural plant models. In this way, changes in, for instance, climate regulation or cultivation strategies can be directly analyzed. Researcher Maarten van der Meer said, "Digital twin technology will soon allow growers to achieve more with their data."

Together with the companies Sobolt and LetsGrow/Hoogendoorn, WUR is developing a 3D digital plant growth model that also provides insight into water management and light distribution within the greenhouse. This model will soon be validated at Tomatoworld. Growers there will test a dashboard that aids in cultivation decisions. Van der Meer said, "Digitization means more and more data are becoming available. With a dashboard, a grower can gain more insight into this, for example, in terms of plant growth, light distribution, temperature, water consumption, and its prediction in the near future."



The future of autonomous growing
By visualizing and combining sensor data, growers can react quickly to changes and thus optimize the growth and health of their crops. "This makes the model not only practical but also valuable for the next step in autonomous growing," says Van der Meer. Digital twins are also useful for researchers and breeders. "With digital twins, you can conduct many crop trials without the need for a greenhouse," he says.

The research into digital twins is part of a broader movement towards autonomous growing, which also includes the development of robots and smart Integrated Pest Management (IPM) solutions to support the grower in daily operations. The technology offers great opportunities for the future of greenhouse farming but still requires fine-tuning and specific adaptations to crop types and greenhouse conditions.

This project receives a Growth Fund contribution from the NXTGEN HIGHTECH program.

Source: WUR

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