| 张家齐1, 张 毅2*, 石 洁1*, 张笑晴2, 郭 宁1, 张海剑1.基于判别分析的玉米茎腐病发生程度预测模型[J].植物保护,2020,46(2):85-90. |
| 基于判别分析的玉米茎腐病发生程度预测模型 |
| Prediction model of corn stalk rot based on discriminant analysis |
| 投稿时间：2019-01-17 修订日期：2019-03-08 |
| DOI：10.16688/j.zwbh.2019032 |
| 中文关键词: 玉米茎腐病 判别分析 预测模型 |
| 英文关键词:corn stalk rot discriminant analysis prediction model |
| 基金项目:国家重点研发计划（2018YFD0200602）;国家现代农业产业技术体系（CARS-02） |
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| 中文摘要: |
| 对河南省夏玉米区2003年-2018年玉米茎腐病发生、流行情况进行分析,选择制约茎腐病发生流行的主要气象因素,采用判别分析法建立茎腐病发生的两阶段预测模型。应用2003年-2014年的数据进行模型训练,利用2015年-2018年数据进行测试。结果表明,第一阶段预测模型历史回代自身验证准确率为86%,交互验证准确率为79.1%;第二阶段自身验证准确率为83.7%,交互验证准确率为76.7%。应用2015年-2018年数据进行测试,第一阶段预测准确率75%,第二阶段预测准确率85%。说明利用判别分析建立玉米茎腐病流行模型是可行的。 |
| 英文摘要: |
| We selected the main factors as restrictive elements for the studies of occurrence and epidemics of corn stalk rot in Henan province from 2003 to 2018. By using the method of discriminant analysis, we built up a two-stage prediction model. We set up the model based on the data of 2003-2014 and used the data of 2015-2018 to test the model. The results showed that the accurate rate of the first-stage prediction model was 86% in self-validation and 79.1% in cross-validation; the accurate rate of the second-stage prediction model was 83.7% in self-validation and 76.7% in cross-validation. Tested with the data of 2015-2018, the accurate rates of the first and second prediction models were 75% and 85%, respectively. The results also proved a feasible method for predicting corn stalk rot by using discriminant analysis. |
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