Chinese Journal of Agrometeorology ›› 2018, Vol. 39 ›› Issue (12): 786-795.doi: 10.3969/j.issn.1000-6362.2018.12.003

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Estimation and Distribution of Minimum Air Temperature within Winter Wheat Canopy in Prone Period of Late Frost

LIU Hong-jie, NI Yong-jing, REN De-chao, DU Ke-ming, GE Jun, ZHU Pei-pei, ZHAO Jing-ling, WU Yong-feng, HU Xin   

  1. 1.Wheat Research Laboratory, Shangqiu Academy of Agriculture and Forestry Sciences, Shangqiu 47600, China; 2. Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences/Key Laboratory of Agricultural Environment, Ministry of Agriculture, Beijing 100081
  • Online:2018-12-20 Published:2018-12-11

Abstract: Using the hourly meteorological observation data at different heights within winter wheat canopy in 2016 and 2017, the height and variation of minimum air temperature within winter wheat canopy during the prone period of late frost were analyzed. An estimation model for canopy minimum air temperature was established based on the meteorological factors at the 150cm height and soil temperature at 0cm depth. The results indicated that: (1) the air temperature below 0℃ appeared earlier and lasted longer near the canopy. (2) The minimum air temperature appeared mostly at about 4/5 of the highest canopy and between AM 2:00 and AM 6:00, especially at AM 5:00. (3) Correlation of the canopy minimum air temperature with relative humidity and wind speed at 150cm height reaches P<0.01 significant level, and correlation with air temperature at different heights and soil temperature at different depths reaches P<0.001 significance level, and correlation with soil temperature decreases as the soil depth increases. (4) The value of partial correlation coefficient of the canopy minimum air temperature with air temperature, wind speed, relative humidity at 150cm height, and soil temperature at 0cm depth, were listed as temperature>wind speed>soil temperature>relative humidity. An estimation model for canopy minimum air temperature was established by multiple linear regression function. The coefficient of determination (Adj.R2) reached 0.967 and the root mean square error (RMSE) was 0.915. It was feasible to establish the estimation model for canopy minimum air temperature based on the conventional observation data of meteorological stations. The model could provide valuable information on monitoring and predicting for late frost in winter wheat.

Key words: Huanghuai winter wheat region, Winter wheat, Late frost damage, Canopy minimum air temperature