日光温室黄瓜霜霉病初侵染阶段关键预测因子的筛选及验证

Selecting and evaluation of key predictive factors in the primary infection stage of cucumber downy mildew in solar greenhouses

温室黄瓜霜霉病的暴发依赖于环境信息和栽培管理措施等多种因素的相互作用,生产上测报依赖各种经验模型,但输入因子种类较多,需要进行简化处理。笔者基于田间调查试验,采用主成分分析的方法,从14组日光温室黄瓜霜霉病初侵染阶段的预测因子中,筛选出了反映湿度综合信息、温度综合信息和温室管理措施的3个主成分,累计贡献率达到80.76%,并结合前人的研究成果构建经验模型。该模型对黄瓜霜霉病初侵染阶段的预测效果较好(R^2=0.94),可为日光温室黄瓜霜霉病的提早防治提供决策参考。

The outbreak of cucumber downy mildew in greenhouse depends on the combined effects of the environment conditions, the management activities and other factors. In production, plant disease prediction relies on all kinds of empirical models, but there are many kinds of input factors, which need to be simplified. The approach we adopt to solve the problem is using the principal component analysis to reduce the dimension of 14 groups of early predictors for cucumber downy mildew, based on field investigation experiment. Three principal components were selected out, which reflected the comprehensive humidity information, the temperature information and the management activities of the greenhouse,respectively. The cumulative contribution rate reached 80.76%, and an empirical model was established based on previous research results. The model had a good predictive effect（R^2 =0.94） on the occurrence date of cucumber downy mildew,and it could provide an decision reference for the early control of cucumber downy mildew in the solar greenhouses.