Two-span Chinese solar greenhouses (TSCSG) are commonly used in China, due to the low construction cost and high rate of land utilization. There are two sheds with one back wall in the TSCSG, compared with the traditional solar greenhouses (single-span Chinese solar greenhouses, SSCSG) with one back wall and one shed. The two sheds can be located both on the south side or separately on the north and south sides of the back wall. In terms of the addition of a north shed behind the back wall, there are different significant extreme temperature values and distribution characteristics of the walls, and soil in the TSCSG, compared with the SSCSG. In this study, the thermal environment performance of TSCSG was focused mainly on the heat transfer in the TSCSG. A three-dimensional transient state model was established for temperature environment in the TSCSG and SSCSG using computational Fluid Dynamics (CFD) on the Fluent platform. A series of experiments were carried out to collect the indoor temperature and Heat flux of the enclosure structure in the TSCSG. The ANOVA (analysis of variance) and isoscedasticity t-test method were then employed to analyze the significance of differences between simulated and test data. Consequently, the test verified that there was no significant difference between simulated and measured data. Accordingly, the CFD simulation model was employed to calculate the indoor temperature and heat flow in the TSCSG and SSCSG. Consequently, the following results were obtained after CFD simulation. Under the same external climate conditions, the nighttime indoor temperature, the soil temperature, the inner surface temperature of the wall were 1.7-3.8 ℃, 2.9-3.0 ℃, and 2.9-7.9 ℃ higher in the TSCSG than that in the SSCSG, respectively. The soil and walls of TSCSG released the heat towards the south side shed at night with a stable heat flow continuously, but nothing occurred in the SSCSG. Moreover, the heat flow rates densities of walls and soil in the TSCSG were 7.11-8.59, and 12.65-15.19 W/m², respectively, which were 0.76-2.42, and 9.71-14.36 W/m² higher than the surface heat flux densities of SSCSG, respectively. Consequently, the temperature regulation of TSCSG was stronger than the SSCSG. Additionally, the CFD model cannot consider the impact of crops in the solar greenhouses. The validation experiments were also conducted under no crop cultivation conditions. Actually, there were the crops to affect the heat storage and release of soil, walls, and other heat storage materials in the solar greenhouses, as well as indoor convective heat transfer. Therefore, it is necessary to clarify the impact of these errors for the more accurate thermal environment of TSCSG.

Nutrient Film Technique (NFT) has been one of the most important production modes of hydroponically grown lettuce in the north of China. However, the low temperature in winter and high temperature in summer can be two of the key issues to restrict the sustainable development of hydroponically grown lettuce. In this study, an acquisition monitor platform of temperature data was constructed inside and outside the greenhouse using sensors combined with the Internet of Things (IoT), in order to reduce the delayed temperature control of lettuce in the root zone in winter and summer. A specific measurement was performed on the indoor air temperature, indoor soil temperature, indoor air humidity, nutrient solution temperature, nutrient solution temperature at the return port, outdoor carbon dioxide concentration, outdoor solar radiation illumination, outdoor air pressure, outdoor air humidity, outdoor air temperature, and outdoor wind speed. The air temperature and outdoor wind speed were also collected. Pearson correlation analysis was used to determine the correlation between the ambient environmental factors and the root zone temperature after 30 min. Outdoor air pressure and outdoor air humidity shared a weak correlation with the root zone temperature after 30 min. The rest of the influencing factors were highly correlated with the root zone temperature and thus were selected as influencing features. The prediction model of root zone temperature was constructed using BP neural network and machine learning, according to the historical environmental data inside and outside the greenhouse. The optimal number of hidden layers was experimentally determined for the BP neural network, which was 15 in summer and 13 in winter. The input weights and thresholds of the BP neural network model were optimized to improve the accuracy of the BP model using dung beetle optimizer (DBO). The optimal weights and thresholds were obtained through the positional change of the dung beetles using five operations, namely, ball rolling, foraging, stealing, and reproducing. Ultimately, the DBO-BP neural network was constructed in the winter and summer seasons. The prediction model of root zone temperature in the cultivation tank was constructed to compare with GA-BP and BP neural network models. The results showed that there were more consistent trends of the predicted and real root zone temperatures. The maximum error of the temperature prediction of the DBO-BP model in winter was 2.36 °C with a coefficient of determination of 0.933, and the maximum error of the temperature prediction of this model in summer was 2.21 °C with a coefficient of determination of 0.943, while the coefficients of determination of the GA-BP and the BP models in summer were 0.928 and 0.892, respectively. The root mean square error and the average absolute error of the DBO-BP model evaluation indexes were 0.707 and 0.549, respectively, which were smaller than the rest. Thus, the DBO-BP neural network can fully meet the demand for the temperature prediction accuracy of the root zone in NFT cultivation. The finding can also provide an effective mode for rapid temperature control in the root zone of lettuce cultivation.

Urban agriculture is one of the most crucial components in modern agriculture and urban systems. The multifaceted functional values of urban agriculture are of significant importance to accelerate the agricultural transformation and urban-rural integration, thus fostering the more sustainable cities. Territorial spatial planning can serve as the spatial blueprint for sustainable development, in order to promote the functional values of urban agriculture. This study aims to realize the urban agriculture function during territorial spatial planning under supply and demand adaptation. Firstly, the systematic analysis was made on the connotations of the functional values for the urban agriculture. Then, the logical framework and practical challenges were examined to realize these functional values, from the perspective of supply and demand. Finally, the territorial spatial planning was proposed to achieve these functional values. A pathway was also recommended for “realizing the functional values of urban agriculture in territorial spatial planning”. A balanced and supply-demand aligned approach was developed to facilitate the multifaceted functions of urban agriculture within the system of territorial spatial planning. The results indicate that: 1) Urban agriculture was closely integrated with the cities. Besides the common characteristics of traditional agriculture, there were the unique features, such as symbiosis, efficiency, complexity, and personalization. The fundamental agricultural functions were also provided, such as supplying fresh agricultural products and technological innovation, as well as extended functions, like purifying the urban environment, resource recycling, urban landscapes, agrarian culture preservation, and urban experiences. Effective pathways were explored to fully realize the multifaceted functional values of urban agriculture, according to the theories of the supply-demand equilibrium, industrial multifunctionality, urban-rural integration, and agricultural location. 2) There were some mismatches between the supply of production factors and the demand for industrial upgrading, between the supply of agricultural products and the demand structure of urban residents, and between agricultural production and urban ecological resource protection in urban agriculture. Territorial spatial planning was then required to strengthen the protection and rational use of agricultural resources on the supply side. On the demand side was enhanced the planning guidance, spatial control, element assurance, and policy support. 3) Five tasks were proposed to promote and realize the agricultural values: A systematic evaluation was conducted to assess the urban agriculture; The targets were determined to clarify the direction of development; Spatial guidance was strengthened to establish the development pattern; Industrial guidance was optimized to propose the strategies for urban agriculture; The institutional mechanisms were improved to form the protective measures for urban agriculture. The “general, specialized, and detailed planning” were implemented to orderly develop the urban agriculture. The functional values were then achieved to consider the territorial spatial planning using supply-demand fit. The systematic guidance can also provide to optimize and allocate the agricultural resources in urban spaces.

In order to further understand the changing laws of environmental factors in large multi-span greenhouses under natural ventilation conditions and the internal relations between various environmental factors, and ultimately improve the precision of microclimate regulation of large multi-span greenhouses. Taking the multi-span greenhouse with a small spire structure in the Demonstration Base of Guangdong Agricultural Technology Extension Station as the research object, under the condition of natural ventilation with butterfly-shaped windows, the changes in temperature, humidity, wind speed and solar light intensity of different monitoring planes in the greenhouse were monitored. After analyzing the monitoring data, it was found that: 1) The temperature gradient in the vertical direction in the large multi-span greenhouse is more obvious than that in the small greenhouse, and the highest average temperature difference monitored can reach 7.9°C. The velocity field in the multi-span greenhouse is always maintained within the range of 0.3-0.4 m/s, and the ambient wind speed has no effect on the airflow speed in the greenhouse. The humidity and speed in the multi-span greenhouse show good uniformity. 2) In a large multi-span greenhouse, the secondary radiation generated by the internal shading has less impact on the area near the ground, which can effectively reduce the ground temperature. 3) Under the conditions studied in this research, the temperature and humidity in the greenhouse follow the external environment as well, showing that the greenhouse design is reasonable, and the air renewal and heat exchange inside and outside the greenhouse are good during natural ventilation.