Cheng Weiwei, Li Yu, Wang Liqiang, Zhang Zhi, Liu Zhonghua
College of Urban and Rural Construction, Shanxi Agricultural University, Jinzhong, China.
College of Agricultural Engineering, Shanxi Agricultural University, Jinzhong, China.
PLoS One. 2025 Aug 7;20(8):e0328302. doi: 10.1371/journal.pone.0328302. eCollection 2025.
Solar greenhouse is a primary agricultural facility in northern China during winter, providing a certain level of security for the demand for vegetables and melons in the northern regions. However, there remains a lack of uniformity between crop requirements and the light and thermal environment within the planting area of the greenhouse, resulting in non-uniform growth and development of crops. The present study set out with the objective of investigating the impact of the light environment on the internal conditions of a solar greenhouse. To this end, experimental measurements were employed in conjunction with deep learning models. The results showed that rates of change in air temperature and light intensity were significantly higher in the vertical than the horizontal direction, especially below 1,800 metres, where significant differenced in temperature and light distribution existIn the horizontal direction, the impact of light distribution on soil temperature was significant within a range of less than 4,500 mm from the southern base of the greenhouse. By contrast, the impact was less pronounced within a range of 4,500 to 9,000 mm, In the temporal dimension, light variation significantly affected soil temperatures within 150 mm of the surface, but had no significant effect on temperatures within the 300-600 mm range. Similarly, light variation significantly affected temperatures within 200 mm of the inner wall surface, but had no significant effect on temperatures within the 400-800 mm range.Furthermore, vertical differences in light intensity significantly affected temperatures within the 800 mm height range from the indoor ground level, whereas the impact at other heights was less pronounced. The LSTM prediction model was highly accurate, and this study provided the necessary data and theoretical basis for regulating the light and temperature environments in solar greenhouse.
日光温室是中国北方冬季主要的农业设施,为北方地区蔬菜和瓜果的需求提供了一定程度的保障。然而,温室种植区内作物需求与光热环境之间仍存在缺乏一致性的问题,导致作物生长发育不均。本研究旨在调查光照环境对日光温室内环境条件的影响。为此,结合深度学习模型进行了实验测量。结果表明,气温和光照强度的变化率在垂直方向上显著高于水平方向,尤其是在1800米以下,温度和光照分布存在显著差异。在水平方向上,光照分布对土壤温度的影响在距离温室南侧底部小于4500毫米的范围内显著。相比之下,在4500至9000毫米的范围内影响较小。在时间维度上,光照变化对地表以下150毫米范围内的土壤温度有显著影响,但对300 - 600毫米范围内的温度没有显著影响。同样,光照变化对内壁表面200毫米范围内的温度有显著影响,但对400 - 800毫米范围内的温度没有显著影响。此外,光照强度的垂直差异对室内地面以上800毫米高度范围内的温度有显著影响,而在其他高度的影响较小。长短期记忆(LSTM)预测模型具有很高的准确性,本研究为调节日光温室的光照和温度环境提供了必要的数据和理论依据。