| 稻纵卷叶螟发生期及发生程度预测模型的建立与应用 |
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| 引用本文： | 金曙光,杨茂发,金道超,杨洪,温冬梅,朱涛.稻纵卷叶螟发生期及发生程度预测模型的建立与应用[J].贵州农业科学,2012(3):115-118. |
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| 作者姓名： | 金曙光 杨茂发 金道超 杨洪 温冬梅 朱涛 |
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| 作者单位： | 贵州大学昆虫研究所;贵州省惠水县植保植检站 |
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| 基金项目： | “973”计划前期研究专项“喀斯特区域水稻‘两迁’害虫成灾机理及可持续控制的相关基础研究”(2009CB125908);贵州省农业科技攻关项目“贵州水稻‘两迁’害虫成灾机理及可持续控制研究”[黔科合NY字(2010)3064];贵州省教育厅自然科学研究项目“贵州水稻‘两迁’害虫成灾机理及可持续控制研究”(黔教2010011) |
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| 摘 要： | 为提高稻纵卷叶螟发生期和发生量预测的准确率,减少稻纵卷叶螟发生对水稻生产造成的损失,应用回归分析方法,对贵州省惠水县1993～2006年稻纵卷叶螟第三代及第四代发生期和发生程度进行分析,建立预测模型。结果表明,第三、四代稻纵卷叶螟2～3龄幼虫盛发期预测模型分别为y=30.76-5.185x和y=10.128+0.837x,发生程度模型分别为y=0.02x-0.169和y=0.000 175x1+0.004 393x2+1.494 365。
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| 关 键 词： | 稻纵卷叶螟 发生期 发生程度 预测模型 |
Establishment and Application of Prediction Model for Outbreak Period and Occurrence Degree of Cnaphalocrocis medinalis |
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| JIN Shu-guang,YANG Mao-fa,JIN Dao-chao,YANG Hong,WEN Dong-mei,ZHU Tao.Establishment and Application of Prediction Model for Outbreak Period and Occurrence Degree of Cnaphalocrocis medinalis[J].Guizhou Agricultural Sciences,2012(3):115-118. |
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| Authors: | JIN Shu-guang YANG Mao-fa JIN Dao-chao YANG Hong WEN Dong-mei ZHU Tao |
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| Institution: | 1.Institute of Entomology,Guizhou University,Guiyang,Guizhou 550025;2.Huishui Plant Protection and Quarantine Station,Huishui,Guizhou 550600,China) |
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| Abstract: | In order to enhance the prediction accuracy of outbreak period and occurrence degree of C.medinalis,reduce the loss of rice production caused by C.medinalis,regressive analysis models were used to predict the outbreak period and the occurrence degree of the third larva and fourth larva of C.medinalis in Huishui Country during 1993-2006,and the prediction model was established at the same time.The expected regressive models for the outbreak period of the third stage larva and forth stage larva are:y=130.76-5.185 x and y=10.128+0.837x separately.The expected regression models for the occurrence degree of the third larva and forth larva are:y=0.02x-0.169 and y=0.000175x1+0.004 393 x2+1.494 365 respectively. |
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| Keywords: | Cnaphalocrocis medinalis outbreak period occurrence degree prediction model |
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