基于农业气象的稻瘟病发生程度预警数学模型

An Early Warning Mathematical Model of Rice Blast Degree Based on Agrometeorology

摘要: 目的：这里研究通过气象因素数据对稻瘟病的发生程度进行预警。方法：本文选择旬平均气温，旬平均降水量，旬平均水汽压作为预警气象因子，建立稻瘟病发生程度的数学模型，对稻瘟病发生程度进行预警。结果：实证结果表明，利用该模型对稻瘟病最高发生程度进行预警时，准确率达到98.6%；而利用该模型对稻瘟病实际发生程度进行预警时，完全准确的比例为24.70%，偏差1个等级的比例为70.73%。结论：这说明，所建立的预警模型具有较好的预警准确性。

Abstract: Objective: This study aims at prediction of the occurrence degree of rice blast by meteorological factor data. Method: In this paper, ten-day average temperature, ten-day average precipitation and ten-day average water vapor pressure are selected as early warning meteorological factors to establish a mathematical model for the occurrence degree of rice blast. Result: The empirical results show that when the model is used to predict the highest degree of rice blast, the accuracy is 98.6%. When the model is used to predict the actual degree of rice blast, the completely accurate proportion was 24.70%, and the deviation within one grade was 70.73%. Conclusion: This shows that the model has good warning accuracy.