Simple model for predicting hourly air temperatures inside Chinese solar greenhouses

For an efficient energy greenhouse, temperature is the most important climate parameter, which not only affects crop growth and health but also determines the management of energy consumption. So reliable monitoring of temperature is of great significance, and often hourly values are required. However, due to the low level of automation for Chinese solar greenhouse, the loss or poor quality of climate data often occurs. In order to accurately supplement the missing data, as well as for the generation of future temperature, a 24-hour indoor temperature prediction model was established. It uses a piecewise Bezier curve equation that takes the characteristic temperature as the control point which was determined by the outside weather recording. The 130 d of observed hourly temperature data were used to build and validate the model, and the results showed that the temperature model proposed was accurate and sufficient for the simulation of the trend curve of hourly temperature change inside a solar greenhouse. (EF=0.98, R²=0.89). After validation, this temperature model proposed can be useful for the quantitative analysis of crop growth and optimal management.