首页 | 本学科首页   官方微博 | 高级检索  
     检索      

许昌市小麦蚜虫种群变化规律及气象预测模型
引用本文:李文峰,尹彬,曹志伟,杨晓莉,曹永周.许昌市小麦蚜虫种群变化规律及气象预测模型[J].河南农业科学,2011,40(3):81-84.
作者姓名:李文峰  尹彬  曹志伟  杨晓莉  曹永周
作者单位:1. 许昌市气象局,河南,许昌,461000
2. 鄢陵县气象局,河南,鄢陵,461200
3. 禹州市气象局,河南,禹州,461670
4. 许昌市植保站,河南,许昌,461000
摘    要:小麦蚜虫是危害许昌小麦生产的主要虫害之一,其发生面积广、危害重.为此,对许昌市小麦蚜虫的种群变化规律进行研究,并建立其发生危害的预测模型.根据许昌植保站2007年、2008年监测资料进行分析,蚜虫在小麦上迁移危害其种群数量变化遵从logistic增长曲线,可以划分为开始增长期(3月下旬-4月上旬)、加速增长期(4月中旬...

关 键 词:逐步回归  小麦蚜虫  种群变化规律  预测  气象因子

Variation of Wheat Aphid Population in Xuchang and Prediction Models With Meteorological Data
LI Wen-feng,YIN Bin,CAO Zhi-wei,YANG Xiao-li,CAO Yong-zhou.Variation of Wheat Aphid Population in Xuchang and Prediction Models With Meteorological Data[J].Journal of Henan Agricultural Sciences,2011,40(3):81-84.
Authors:LI Wen-feng  YIN Bin  CAO Zhi-wei  YANG Xiao-li  CAO Yong-zhou
Institution:1.Xuchang Meteorological Bureau,Xuchang 461000,China;2.Yanling Meteorological Bureau,Yanling 461200,China;3.Yuzhou Meteorological Bureau,Yuzhou 461670,China;4.Xuchang Plant Protection Station,Xuchang 461000,China)
Abstract:According to the monitoring data of 2007 and 2008 from Xuchang Plant Protection Station,aphid population changes in wheat complied with logistic growth curve.The population dynamics could be divided into growth beginning period(late March to early April),accelerated growth period(mid-April to early May) and slow growth period(mid-May to early June).The stage of late April to early May was the key period for aphid population growth.According to the monitoring data of 1999-2008 from Xuchang Plant Protection Station and Xuchang Weather Station,relationships of the periods of appearance and peak and the peak quantity of aphids with meteorological factors were analyzed.The results showed that heat and moisture conditions were the key meteorological factors affecting aphid population dynamics,which could promote and inhibit development of aphids,respectively.The periods of appearance and peak and the peak quantity of aphids were most ctosely related to 0cm ground temperature in March,precipitation in May,relative humidity in March and April.The correlation coefficients were-0.728,0.615 and-0.597,respectively,all reaching significant level.Using SPSS software,prediction models of the periods of appearance and peak and the peak quantity of aphids were separately constructed by stepwise regression method.The prediction models could be used in actual business due to their high prediction accuracy rate of 73% to 80%.
Keywords:Stepwise regression  Wheat aphid  Population variation  Prediction  Meteorological factors
本文献已被 CNKI 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号