Abstract:Canopy-air temperature difference can indirectly monitor the variation of crop moisture, and the time lag effect between canopy temperature and atmospheric temperature will affect the monitoring effect. In order to explore the characteristics and influencing factors of the time lag effect between canopy temperature and atmospheric temperature, winter wheat from jointing stage to ripening stage was used as the research object. The infrared temperature sensor was used to continuously monitor the canopy temperature of four different irrigation treatments with irrigation upper limits of 95% (T1), 80% (T2), 65% (T3) and 50% (T4) of field water capacity, and simultaneously obtained meteorological data such as short-wave net radiation (RS), atmospheric temperature (TA) and relative humidity (RH). The time lag between canopy temperature and atmospheric temperature was calculated by dislocation correlation method, and its variation characteristics under different growth stages and different irrigation conditions were analyzed. The correlation analysis method was used to explore the correlation between the change rate and daily mean value of meteorological factors (RS, TA, RH) and time lag. Finally, the common influence of meteorological factors (RS, TA, RH), soil moisture content (SMC) and leaf area index (LAI) on time lag was discussed by path analysis. The results showed that the change of winter wheat canopy temperature was ahead of the atmospheric temperature under different growth stages and different irrigation conditions;under different irrigation treatments, the lag time of T1, T2 and T3 treatments was higher than that of T4 treatment, and the lag time was decreased firstly and then increased at different growth stages. The correlation between the change rate of shortwave net radiation (RSCR), the change rate of atmospheric temperature (TACR) and the change rate of relative humidity (RHCR) and the time lag was higher than that between the corresponding daily mean and the time lag. At the same time, the correlation between RSCR and lag time was the highest (R=0.718~0.806), followed by TACR (R=0.582~0.661) and RHCR (R=-0.534~-0.570). Path analysis showed that the lag time was mainly affected by RSCR, SMC and LAI, but the main factors affecting the lag time were different under different irrigation conditions. T1, T2 and T3 treatments were mainly affected by RSCR and LAI, while T4 was mainly affected by RSCR and SMC. The research result can provide a theoretical basis for monitoring crop water changes by using canopy temperature difference information.
