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湖南烟区斜纹夜蛾(Spodoptera litura)的发生规律及预测方法
引用本文:曾爱平,陈永年,周志成,胡日生,龙建中,李小一,吴春娥.湖南烟区斜纹夜蛾(Spodoptera litura)的发生规律及预测方法[J].中国烟草科学,2010,31(6).
作者姓名:曾爱平  陈永年  周志成  胡日生  龙建中  李小一  吴春娥
作者单位:湖南农业大学生物安全科学技术学院;中国烟草中南烟草农业试验站;宁远县烟草公司;郴州市烟草公司;江华县烟草公司;
基金项目:国家烟草专卖局项目,湖南省烟草专卖局项目,湖南省教育厅项目,湖南省科技厅项目
摘    要:以郴州、宁远等县连续多年田间调查资料为基础,结合当地气象数据,分析了湖南省斜纹夜蛾的发生规律。结果表明,根据有效积温斜纹夜蛾在湖南每年发生4.0~4.5代,理论代数与实际代数相符;湖南斜纹夜蛾每年初始虫源全部为外地虫源;按虫源性质,全年可分为4个不同的发生时段;3月的诱蛾量与4—6月诱蛾量有显著的相关性,预测模型为y=233.54+112.44x4(r=0.815*,n=8);1月平均温度与4—6月诱蛾量也有明显的相关性(达90%可信度),预测模型为y1410350X3(r=0.595,n=9);同步迁飞昆虫小地老虎主迁入期(2—4月)的性诱蛾量与斜纹夜蛾主迁入期(4—6月)也具相关性,均可供发生趋势预测参考。斜纹夜蛾的百株虫量与为害率呈显著相关性。

关 键 词:斜纹夜蛾  有效积温  小地老虎  同步迁飞  预测

Occurrence Pattern of Spodoptera litura in Hunan and its Prediction Methods
ZENG Aiping,CHEN Yongnian,ZHOU Zhicheng,HU Risheng,LONG Jianzhong,LI Xiaoyi,WU Chun'e.Occurrence Pattern of Spodoptera litura in Hunan and its Prediction Methods[J].Chinese Tobacco Science,2010,31(6).
Authors:ZENG Aiping  CHEN Yongnian  ZHOU Zhicheng  HU Risheng  LONG Jianzhong  LI Xiaoyi  WU Chun'e
Affiliation:ZENG Aiping1,2,CHEN Yongnian1,ZHOU Zhicheng2,HU Risheng2,LONG Jianzhong3,LI Xiaoyi4,WU Chun'e5(1.College of Bio-safety Science and Technology,Hunan Agricultural University,Changsha 410128,China,2.China Tobacco South Experimental Station,3.Ningyuan Tobacco Company,Ningyuan,Hunan 425600,4.Chenzhou Tobacco Company,Chenzhou,Hunan 423000,5.Jianghua Tobacco Company,Jianghua,Hunan 425500,China)
Abstract:The occurrence pattern of Spodoptera litura was studied according to the continuous year data investigated in tobacco fields and weather data of Chenzhou and Ningyuan in Hunan.The results showed that,based on effective accumulated temperature,it was predicted that Spodoptera litura occurred 4-4.5 generations each year,which was in agreement with the observed value in field in Hunan Province.The initial resources of Spodoptera litura in early stage of the year were migration pest,there were four occurrence s...
Keywords:Spodoptera litura  effective accumulated temperature  Agrotis ypsilon  synchronous migration  forecasting  
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