The Virtual Tomato Crops (VTC) model is based on the concepts of functional-structural plant modelling, which simulates individual plants and their functioning as well as their 3D architectural development. The crucial property of FSP models is that growth and development of the plants feedback on the resources driving growth, in terms of increased shading and depletion of nutrients and water. Crop behaviour is thus the result of individual plants using shared resources. The environmental variables driving plant growth and development will be simulated by a greenhouse module based on the Kaspro model.
The VTC will be continuously updated with data from the real twin; a tomato crop growing in the greenhouse. In real time, data on plant growth and growing conditions will be captured using the NPEC greenhouse facilities (www.npec.nl). Data from several sensors in the NPEC facilities, such as the multi-spectral 3D laser scanner, chlorophyll fluorescence camera, thermal camera and climate sensors, will be processed to estimate plant traits and climate conditions. The focus is therefore on estimating plant traits from sensor data. We will use and develop deep-learning methods to obtain morphological, reflectance, and physiological traits.
The output of the model will be used for automatic control of greenhouse climate settings. Research questions concern effects of model granularity on climate control advice, and the effect of daily crop status update on control performance in terms of light use efficiency. Furthermore, the digital twin can be used to virtually explore leaf pruning strategies, to test different greenhouse cover types, and to select superior crop traits.
The VTC is evaluated from an integrated and practical perspective and based on technical and economic performance. Testing will be conducted at the lab or greenhouse scale, either at WUR or at producer organisations. Results will be discussed with stakeholders.
|Effective start/end date||1/01/19 → 31/12/22|