A high-temperature environment is one of the most important factors limiting the growth of crops in Chinese solar greenhouses during summer. To reduce the substrate temperature of summer plant cultivation in a Chinese solar greenhouse, we proposed a water-circulating tomato-root zone-substrate-cooling system (WCTRZSCS). The system used water as the circulating medium, a chiller as the cooling source, and polyethylene raised temperature resistance (PE-RT) pipes laid in the substrate as the cooling component. The greenhouse was divided into test area TS₁ (one PE-RT pipe), TS₂ (two PE-RT pipes), and a control area CK (no PE-RT pipe) for the root-zone substrate-cooling test. The results demonstrated that (1) in the summer, WCTRZSCS can effectively reduce the substrate temperature, and (2) WCTRZSCS improves the temperature conditions for tomato vegetative growth. There were significant differences in plant height, stem diameter, dry weight, fresh weight, leaf area, net photosynthetic rate, total root length, and total root projection area between tomatoes in the test and control areas (p < 0.05). The TS₁ and TS₂ growth rates were 60.2% and 81.2% higher than CK, respectively, and the light-utilization efficiency was 56.3% and 81.3% higher than CK. (3) The system’s cooling energy consumption per unit ground area was 35.2~67.5 W·m⁻², and the coefficient of performance (COP) was 5.3~8.7. Hence, WCTRZSCS can effectively reduce the substrate temperature in the root zone, but the profit by tomato cannot offset the cost of using WCTRZSCS. Through the optimization of and improvement in the system, its economy may be further improved, and it is expected to be applied in practical production.

The internal air temperature of Chinese solar greenhouse (CSG) has the problem of uneven spatial and temporal distribution. To determine temperature distribution at different locations, we designed a greenhouse temperature real-time monitoring system based on virtual local area network (VLAN) and estimate, including interpolation estimation module, data acquisition, and transmission module. The temperature data were obtained from 24 sensors, and the Ordinary Kriging algorithm estimated the temperature distribution of the whole plane according to the data. The results showed that the real-time temperature distribution monitoring method established was fast and robust. In addition, data validity rate for VLAN technology deployed for data transmission was 2.64% higher than that of cellular network technology. The following results are obtained by interpolation estimation of temperature data using gaussian model. The average relative error (ARE) of estimate, mean absolute error (MAE), root mean square error (RMSE), and determination coefficient (R²) were −0.12 °C, 0.42 °C, 0.56 °C, and 0.9964, respectively. After simple optimization of the number of sensors, the following conclusions are drawn. When the number of sensors were decreased to 12~16, MAE, RMSE, and R² were 0.40~0.60 °C, 0.60~0.80 °C, and >0.99, respectively. Furthermore, temperature distribution in the greenhouse varied in the east–west and north–south directions and had strong regularity. The calculation speed of estimate interpolation algorithm was 50~150 ms, and greenhouse Temperature Distribution Real-time Monitoring System (TDRMS) realized simultaneous acquisition, processing, and fast estimate.