This work demonstrates a novel methodology for creating digital twins that accurately represent plant growth dynamics in agriculture, highlighting the role of interpolation and morphing.
Digital twins can provide vital insights into agricultural products and processes. There have been a lot of documented attempts at digital twins in agriculture. However, the majority of these attempts build synthetic models and ignore the temporal dimension of the plant growth. Therefore, the existing models fail to depict actual plant details and growth. Our work replicates the actual growth of a real plant in the digital world by acquiring 3D meshes of the plant at various instants. It focuses on the transition between those acquired meshes by approximating all the consecutive pairs into approximate mesh pairs that have a common topology. The quality of these common approximate mesh pairs is quantitatively measured by an Energy term, which is minimized during the optimization process. Later, the meshes with the common topology are interpolated (morphing) to build the final digital twin of the plant. Experimental results show that the proposed methodology to attain the final morph has the potential to be a vital module, which could be responsible for the visual updates in the digital replica of the digital twin of the plant.
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Singh et al. (2025) studied this question.
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