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Chinese Journal of Applied Ecology ›› 2017, Vol. 28 ›› Issue (12): 3994-4000.doi: 10.13287/j.1001-9332.201712.018

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Prediction model of meteorological grade of wheat stripe rust in winter-reproductive area, Sichuan Basin, China

GUO Xiang1,2, WANG Ming-tian3,4*, ZHANG Guo-zhi5   

  1. 1Institute of Plateau Meteorology, China Meteorological Administration/Sichuan Province Key Laboratory of Heavy Rain and Drought-Flood Disasters in Plateau and Basin, Chengdu 610072, China
    2Sichuan Pro-vince Agro-meteorological Center, Chengdu 610072, China
    3Sichuan Meteorological Observatory, Chengdu 610071, China
    4Sichuan Province Key Laboratory of Water-Saving Agriculture in Southern Hill Area, Chengdu 6l0066, China
    5Sichuan Agriculture Department Plant Protection Station, Chengdu 610041, China
  • Received:2017-05-25 Online:2017-12-18 Published:2017-12-18
  • Contact: * E-mail:wangmt0514@163.com
  • Supported by:

    This work was supported by the Public Welfare Industry (Meteorology) Special Research (GYHY201406036), and the Key Project of Sichuan Meteorological Administration (2009-05-01)

Abstract: The winter reproductive areas of Puccinia striiformis var. striiformis in Sichuan Basin are often the places mostly affected by wheat stripe rust. With data on the meteorological condition and stripe rust situation at typical stations in the winter reproductive area in Sichuan Basin from 1999 to 2016, this paper classified the meteorological conditions inducing wheat stripe rust into 5 grades, based on the incidence area ratio of the disease. The meteorological factors which were biologically related to wheat stripe rust were determined through multiple analytical methods, and a meteorological grade model for forecasting wheat stripe rust was created. The result showed that wheat stripe rust in Sichuan Basin was significantly correlated with many meteorological factors, such as the ave-rage (maximum and minimum) temperature, precipitation and its anomaly percentage, relative humidity and its anomaly percentage, average wind speed and sunshine duration. Among these, the average temperature and the anomaly percentage of relative humidity were the determining factors. According to a historical retrospective test, the accuracy of the forecast based on the model was 64% for samples in the county-level test, and 89% for samples in the municipal-level test. In a meteorological grade forecast of wheat stripe rust in the winter reproductive areas in Sichuan Basin in 2017, the prediction was accurate for 62.8% of the samples, with 27.9% error by one grade and only 9.3% error by two or more grades. As a result, the model could deliver satisfactory forecast results, and predicate future wheat stripe rust from a meteorological point of view.