基于主成分分析的玉米棉铃虫预测模型  

Forecast Model of Helicoverpa armigera Based on Principal Component Analysis

作　　者：郭小芹[1,2] 刘明春 魏育国 

机构地区：[1]中国气象局兰州干旱气象研究所,甘肃省干旱气候变化与减灾重点实验室,中国气象局干旱气候变化与减灾重点开放实验室,兰州730020 [2]甘肃省武威市气象局,甘肃武威733000

出　　处：《西北农业学报》2010年第8期69-73,共5页Acta Agriculturae Boreali-occidentalis Sinica

基　　金：公益性行业(气象)科研专项“西北地区旱作农业对气候变暖的响应特征及其预警和应对技术研究”(GYHY200806021)

摘　　要：棉铃虫是河西走廊东部玉米主要害虫之一,气象因素对其种群消长具有非常重要的影响。利用1999-2008年棉铃虫发生资料与同期气象资料,通过对棉铃虫危害程度和其种群消长动态的分析,采用主成分方法对棉铃虫发生动态进行模拟,建立了棉铃虫危害特征预测模型。检验结果表明：预测模型准确率78%~89%,订正模型准确率提高10%以上。模型预测时效超前、效果好,且具有动态特征,可用于研究区域棉铃虫发生程度的监测、预警与研究。Helicoverpa armigera is one of the main pests in spring maize grown in eastern Hexi Corridor,meteorological factors have very important implications with its population dynamics.Using observational data of Helicoverpa armigera and meteorological factors from 1999 to 2008,this paper adopted principal component analysis method to simulate population dynamics of Helicoverpa armigera and established the prediction models.The results show that model accuracy is 78%-89%,the revised prediction model increased the accuracy rate of 10%.Forecast based on the models has strong timeliness,favorable effect,and dynamic characteristics,therefore,it can be used for monitoring and early warning of occurrence degree of Helicoverpa armigera.

关 键 词：棉铃虫 预测模型 主成分分析 

分 类 号：S435.132[农业科学—农业昆虫与害虫防治]