This paper clarified the mechanism of the south and north roofs' effect on the thermal environment of the Chinese solar greenhouse (CSG), using a new parameter: ridge position ratio (RPR), which can describe the dynamic dependency relationship between the south and north roofs. A mathematical model was established using a method of combining computational fluid dynamics (CFD) simulation with experiments, then the model was used to further analyse the effect of RPR on the thermal environment of the CSG. The experimental greenhouse was simulated as an empty building to obtain results independently from these factors including crop and ventilation conditions. The results showed that the occurrence time of the maximum air temperature will be delayed when RPR increases to 0.3 during the daytime. As RPR increases, the heat storage layer of the soil gradually becomes thinner, but the north wall remains unchanged. RPR has a relatively small effect on the minimum temperature of each greenhouse part during the night. Mathematical models of the relationships between RPR, the solar energy that entered the greenhouse and the released heat energy of the enclosure structures were established, respectively. This paper can provide theoretical guidance for the structural design of the CSG.

Understanding the spatial heterogeneity of light and photosynthesis distribution within a canopy is crucial for optimizing plant growth and yield, especially in the context of greenhouse structures. In previous studies, we developed a 3D functional-structural plant model (FSPM) of the Chinese solar greenhouse (CSG) and tomato plants, in which the greenhouse was reconstructed as a 3D mockup and implemented in the virtual scene. This model, which accounts for various environmental factors, allows for precise calculations of radiation, temperature, and photosynthesis at the organ level. This study focuses on elucidating optimal canopy configurations for mechanized planting in greenhouses, building upon the commonly used north–south (N–S) orientation by exploring the east–west (E–W) orientation. Investigating sixteen scenarios with varying furrow distance (1 m, 1.2 m, 1.4 m, 1.6 m) and row spacing (0.3 m, 0.4 m, 0.5 m, 0.6 m), corresponding to 16 treatments of plant spacing, four planting patterns (homogeneous row, double row, staggered row, incremental row) and two orientations were investigated. The results show that in Shenyang city, an E–W orientation with the path width = 0.5 (furrow distance + row distance) = 0.8 m (homogeneous row), and a plant distance of 0.32 m, is the optimal solution for mechanized planting at a density of 39,000 plants/ha. Our findings reveal a nuanced understanding of how altering planting configurations impacts the light environment and photosynthesis rate within solar greenhouses. Looking forward, these insights not only contribute to the field of CSG mechanized planting, but also provide a basis for enhanced CSG planting management. Future research could further explore the broader implications of these optimized configurations in diverse geographic and climatic conditions.

With the continuous use of resources, solar energy is expected to be the most used sustainable energy. To improve the solar energy efficiency in Chinese Solar Greenhouses (CSG), the effect of CSG orientation on intercepted solar radiation was systematically studied. By using a 3D CSG model and a detailed crop canopy model, the light environment within CSG was optimized. Taking the most widely used Liao-Shen type Chinese solar greenhouse (CSG-LS) as the prototype, the simulation was fully verified. The intercepted solar radiation of the maintenance structures and crops was used as the evaluation index. The results showed that the highest amount of solar radiation intercepted by the maintenance structures occurred in the CSG orientations of 4–6° south to west (S-W) in 36.8° N and 38° N areas, 8–10° S-W in 41.8° N areas, and 2–4° south to east (S-E) in 43.6° N areas. The solar radiation intercepted by the crop canopy displayed the highest value at an orientation of 2–4° S-W in 36.8° N, 38° N, 43.6° N areas, and 4–6° S-W in the 41.8° N area. Furthermore, the proposed model could provide scientific guidance for greenhouse crop modelling.