Abstract: Establishing an early warning model for the maximum or minimum temperature and humidity could provide timely forecast information for vegetable farmers to prevent heat injury, chilling damage, and high humidity diseases in extreme weather, when the greenhouse film is being uncovered or covered. In this study, environmental data for the year 2020 was collected using temperature and humidity sensors, and the daily regression analysis method was used along with statistical methods such as the Fvalue test to explore the characteristics and variation of temperature and humidity in unequal height greenhouse in Dongting Lake area. A quadratic equation was used to fit temperature and humidity data. Using the outside temperature and relative humidity values, the temperature and humidity at any given time inside the greenhouse could be estimated, and maximum or minimum warning could be provided accordingly. The results showed that there were significant differences in temperature and humidity changes in different months in unequal height greenhouses in Dongting Lake area, with stable temperature and humidity changes throughout the year. The higher temperature in the greenhouse appeared from 12:00 to 14:00 between June to September. The lower temperature in the greenhouse appeared from 4:00 to 6:00 in December and January. The higher humidity in the greenhouse appeared from 4:00 to 6:00 between March and April and between November to December. The Fvalue of the early warning models of the highest and lowest temperature and humidity in the greenhouse passed the 0.01 extremely significant level with a high fitting degree of R2>0.8, reflecting the diurnal variation of temperature and humidity in the greenhouse.

Key words: Dongting Lake area, unequal height greenhouse, early warning model, temperature and humidity, daily variation

摘要： 建立棚内最高温湿度和最低温湿度预警模型可为菜农在大棚棚膜揭盖及在极端天气下预防高温热害或低温冷害或高湿病害上及时提供预报信息。利用温湿度传感器采集2020年的环境数据，采用逐日回归分析方法，结合F值检验等统计方法，探究洞庭湖区不等高大棚的温湿度特征和变化规律；通过一元二次方程拟合棚内温湿度可对棚内逐月平均温湿度日变化进行分析和趋势模拟，根据棚外气温和相对湿度值进行棚内任一时刻的温湿度估测，并提供最高或最低预警。结果表明：在洞庭湖区不等高大棚内不同月份的温湿度变化差异显著，全年夜间的温湿度变化稳定；棚内温度较高出现在6—9月的12：00—14：00，棚内温度较低出现在12月和1月的4：00—6：00，棚内湿度较高出现在3—4月和11—12月的4：00—6：00。通过一元二次方程对棚内温湿度日变化进行模拟，建立的棚内最高温湿度、最低温湿度预警模型的F值检验均通过0.01极显著水平，拟合度高，R2＞0.8，能较好地反映棚内温湿度日变化规律。

关键词: 洞庭湖区, 不等高大棚, 预警模型, 温湿度, 日变化