应用马尔科夫链模型对草地螟发生程度的预测
Predicting beet webworm occurrence with the Markov chain model
康爱国1**，姜玉英2，王贺军3，张玉慧1，李强1 ，庞红岩1，沈成4，李金有1
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作者单位：1．河北省康保县植保站康保076650； 2．全国农业技术推广中心北京100125；3．河北省植保植检站石家庄050011；4．张家口市植保站张家口075000
中文关键词：草地螟，发生程度，马尔科夫链，预测
英文关键词：Loxostege stictialis，degree of occurrence，Markov chain theory，prediction
中文摘要：
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草地螟 Loxostege stictialisL．是我国北方农牧业生产上一种重要迁飞性、暴发性害虫，一旦暴发会给当地农牧生产造成严重危害。根据康保县 1977—2008年 1代草地螟幼虫发生程度的时间序列资料，应用马尔科夫链的转移概率预测法，构建了 1～3阶转移概率矩阵，组建模型对该县 2009—2011年 1代草地螟发生程度进行了预测，结果与大田实际发生情况完全一致，准确率 100%。对 1980—2011年的历史资料进行回检，历史符合率
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89. 9%，该方法可对草地螟进行长期预报，为草地螟长期预报提供了一种准确有效的方法，对草地螟发生程度的长期预报具有重要指导意义。
英文摘要：The beet webworm Loxostege stictialis (L． ) is one of the main migratory pests inNorth China． Outbreakpopulations of this pest can seriously damage host crops． On the basis of data on the first generation of beet webworm larva collected from 1977 to 2008，we constructed a matrix of migration probability by applying the Markov chain model and then used this to predict the population of the first generation in 2009－2011． By using the transition probability method of Markov chain theory，a transition probability matrix of 1 to 3 steps was constructed based on time series data on the abundance of the pests’first generation from 1979 to 1999． This was used to predict the beet webworm abundance inKangbao city from 2009 to 2011． All predictions were 100% accurate and the results show that the predictive accuracy ofthe data collected from 1980 to 2011was 89. 9%． The predicted population completely conformed to that actually observedin the field．