Abstract: In order to study the opening and closing time of the vent in the tomato greenhouse, and to further realize the intelligent control of the greenhouse, this experiment combined the different growth periods of tomato, used the method of multiple regression to analyze the greenhouse temperature, and finally obtained the regression model of the opening or closing of the vent in the greenhouse at the different growth periods of tomato. At the same time, this experiment was compared with manual control, and the experimental data of this experiment included the basic temperature when the greenhouse vent was opened or closed, the temperature inside and outside the greenhouse, and the temperature difference between day and night. Through the research and analysis, we obtained three results as follows. The first result was that the prediction effect of the multiple regression model was effective. The R2 of the prediction model of the opening or closing time of the greenhouse vent during the flowering and fruit setting period of tomatoes was 0836 6 and 0.981 4 respectively, and the R2 of the prediction model of the opening or closing time of the greenhouse vent during the fruiting period of tomatoes was 0.911 3 and 0.951 3 respectively, and the RMSE value of each period was less than 0.95. The second result was that the indoor temperature under the model control was optimized by 42.86% during the flowering and fruit setting period of tomatoes, compared with the manual control. The diurnal temperature difference under the control of the model was more in line with the accumulation requirements of related substances in tomato roots, stems and leaves. The last conclusion was that the model control effectively adjusted the indoor temperature variation range, improved the rationality of the temperature difference between day and night, and provided conditions for the accumulation of nutrients in tomato fruits in the fruit bearing period of tomato. In conclusion, the regression model under different growth periods of tomato can better control the opening or closing time of greenhouse vents, and also well liberate labor productivity, improve the economic benefits of tomatoes, also provide research ideas for the comprehensive regulation of tomato greenhouse.

Key words: facility tomato, vent opening and closing time, the internet of things, solar greenhouse

摘要： 为研究番茄温室风口开关时间，进一步实现温室智能控制，以人工控制为对照结合番茄不同生长时期，利用多元回归方法对温室风口打开/关闭时的基础温度与室内外温度、昼夜温差进行分析，得到不同时期下温室风口打开/关闭的回归模型。研究结果表明：多元回归模型预测效果较为理想，番茄开花坐果期风口打开/关闭时间预测模型的R2分别为0836 6和0.981 4，结果期风口打开/关闭时间预测模型的R2分别为0.911 3和0.951 3，各RMSE值均小于0.95。番茄开花坐果期，与人工控制相对比模型控制下室内温度优化42.86%，同时保证了昼夜温差更加符合番茄根茎叶中相关物质的积累要求。番茄结果期，与人工控制相对比模型控制有效调整了室内温度变化范围、提升昼夜温差的合理性，为番茄果实中营养物质的积累提供条件。综上所述，番茄不同生长时期下回归模型能较好地解决温室风口开关时间的控制问题，解放劳动生产力，提升番茄经济效益，也为番茄温室的综合调控分析提供研究思路。

关键词: 设施番茄, 风口开关时间, 物联网, 日光温室