Agriculture (Jul 2024)

The Marginal Effect and LSTM Prediction Model under the Chinese Solar Greenhouse Film

  • Weiwei Cheng,
  • Yu Wang,
  • Changchao Wang,
  • Zhonghua Liu

DOI
https://doi.org/10.3390/agriculture14071195
Journal volume & issue
Vol. 14, no. 7
p. 1195

Abstract

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The solar greenhouse is a significant agricultural facility in China. It enables the cultivation of crops during periods that do not coincide with the natural growing season, thus alleviating the pressure on the supply of fruits and vegetables during the winter months. The primary rationale behind the necessity of greenhouse cultivation lies in the fact that the temperature conditions conducive to optimal crop growth can be precisely replicated within this controlled environment. However, it is important to acknowledge that a distinct low-temperature area persists under the film during the overwintering period, with the precise delineation of its boundaries and distribution patterns remaining uncertain. In order to investigate the characteristics of the temperature distribution within the marginal region under the solar greenhouse film, experimental studies, CFD simulations, and LSTM prediction models were employed. The results of these studies indicate that, during the overwintering period, a low-temperature region was observed with approximately equal temperatures near the film membrane. The maximum horizontal distance from the south-side bottom corner was 6130 mm, while the minimum height from the ground was 600 mm. The lowest temperature in the low-temperature region was 4 °C, and the maximum observed temperature difference within the same period in different months was 1 °C. Additionally, a region of elevated temperatures was observed under the film. The lowest temperature in this region was 36.7 °C, and the highest temperature point was within the optimal range for crop growth. The CFD numerical simulation results were consistent with the actual observations, and the LSTM prediction model demonstrated high reliability. The findings of this study offer a theoretical foundation for the distribution of high and low temperatures in solar greenhouses. Furthermore, the developed prediction model provides the necessary buffer time for control, thus enhancing the efficiency of greenhouse cultivation.

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