Demin Xu, Jinyu Zhu, Yuntao Ma
Abstract
Digital twin technology integrates mathematical models, scientific laws, data from physical entities, and advanced simulations, providing a robust platform for agricultural production management. In this study, a 3D greenhouse model was built to precisely replicate its shape, size, properties, crop populations and behavior. Simulations of various production scenarios provided quantitative support for greenhouse design, shading analysis, and crop cultivation management. Moreover, light interception by a single canopy under artificial lighting was quantified, enabling feedback regulation of supplemental lighting strategies. The results indicated that the ground, canopy, wall, and roof captured 32.79 %, 29.92 %, 25.02 %, and 12.27 % of radiant energy, respectively. The average shading rates of the ground, wall, and roof within the greenhouse on the winter solstice were 39.94 %, 13.89 %, and 16.17 %. The light interception of cucumber plants in the northern and southern sections showed significant differences, with an average difference of 6.8 mol m−2 d−1 on sunny day and 1.4 mol m−2 d−1 on cloudy day. Under the sunny condition, the distributed quantitative control strategy proposed in this study met all cucumber plants’ light requirements while reducing electricity consumption by 52.6 % and improving canopy light distribution uniformity by 5.8 % compared with the conventional fixed duration lighting mode. This study introduces a novel integration of digital twin and precise canopy-scale microclimate modeling for solar greenhouses, providing actionable insights for agricultural practitioners and policymakers and supporting the digital transformation and modernization of greenhouse systems.
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