Liu Zhe, Guo Jing, Li Shaoming, Yang Yang, Zhang Xiaodong, Chen Bin, Zhao Zhuang, Yang Jianyu, Zhu Dehai. Verification and quantitative expression on southern corn leaf blight[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2011, 27(11): 160-163.
    Citation: Liu Zhe, Guo Jing, Li Shaoming, Yang Yang, Zhang Xiaodong, Chen Bin, Zhao Zhuang, Yang Jianyu, Zhu Dehai. Verification and quantitative expression on southern corn leaf blight[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2011, 27(11): 160-163.

    Verification and quantitative expression on southern corn leaf blight

    • Southern leaf blight is a major stress of maize, happening in most regions of China, especially in summer corn region. In this study, the Huang-Huai-Hai and Northeast and North China plain were chosen as the study area. Firstly, the meteorological factors resulting in Bipolaris maydis were selected through the correlation analysis between the sample meteorological data and maize regional trial data in the same county. Those were the number of the days (DT) with daily average temperature from 25 to 27℃ and the number of the days (DR) with daily rainfall between 1 and 25 mm during June, July and August. Secondly, a quantitative expression on southern corn leaf blight (Y), Y=0.05103DT+0.04333DR, was created by multivariable regression method. Using the equation, the stress of each meteorological station was calculated, and then, the stress of each county was estimated using geostatistics analysis tool of interpolation in ArcGIS. At last, the stress was compared by the equation with statistical findings and survey results, the results showed that the stress was more serious in the Huang-Huai-Hai plain, which coincides with the actual situation. In this study, the quantitative expression of southern corn leaf blight could provide simulation data of environment stresses at the county level, which could be a data source for precise extension of variety, test environment selection of field trial and environment evaluation.
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