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早稻南方水稻黑条矮缩病发病率预测模型的建立与应用
引用本文:董城,梁少玉,陈冰,梁盛铭,陈观浩.早稻南方水稻黑条矮缩病发病率预测模型的建立与应用[J].中国稻米,2016(2):61-64.
作者姓名:董城  梁少玉  陈冰  梁盛铭  陈观浩
作者单位:1. 广东省化州市同庆农业技术推广站,广东化州,525127;2. 广东省化州市长岐农业技术推广站,广东化州,525128;3. 广东省化州市气象局,广东化州,525100;4. 广东省化州市病虫测报站,广东化州,525100
基金项目:广东省科技计划项目(2011B020416001);茂名市气象局气象科技计划项目(茂气(2012)114号)
摘    要:南方水稻黑条矮缩病是近年来在我国南方稻区重发的一种病毒性病害。为了明确生态因子与南方水稻黑条矮缩病发病率的关系,提高预测能力,避免严重损失,笔者利用化州市2007-2015年的生态因子数据与南方水稻黑条矮缩病田间实际发生数据,采用逐步回归和通径分析的方法研究了两者之间的相关性。结果表明,上年10月下旬温雨系数和上年晚稻黑条矮缩病发病率对早稻南方水稻黑条矮缩病发病率影响最大。笔者还建立了生态因子与早稻南方水稻黑条矮缩病发病率回归模型:Y=-2.7590+0.1895 X_1+0.1345 X_2+1.0495 X~3+0.0044 X_4,利用该回归方程对历史资料进行拟合,拟合程度较好,并对2015年进行预报,预报值与实际值相差较小,准确率较高。可见,该模型适宜于化州乃至粤西地区早稻南方水稻黑条矮缩病的预测预报。

关 键 词:南方水稻黑条矮缩病  生态因子  逐步回归  通径分析  预测模型

Establishment and Application of Forecasting Model on Early Southern Rice Black -streaked Dwarf Virus Disease Incidence
Abstract:The southern rice black streaked dwarf disease virus is an important viral disease that newly happen in recent years in rice area of Southern China. In order to clarify the relationship between the ecological factors and the disease incidence and improve the a-bility to predict and avoid serious losses,the author did a survey on their relationship based on the occurrence data from 2007 to 2015 by stepwise regression and path analysis. The results showed that the temperature and rain coefficient of late October last year and the late southern rice black streaked dwarf disease incidence of last year have a critical impact on the disease incidence. The author es-tablished the early southern rice black streaked dwarf virus disease incidence regression model with the ecological factors, and the model is Y^ =-2.7590+0.1895 X 1+0.1345 X 2+1.0495 X 3+0.0044 X 4 . The fitting effect of historical data is better by using the regres-sion equation. In 2015, the difference between the forecast values and actual values is small and the predictive ability is strong ,so the model is suitable for local as well as West Guangdong region.
Keywords:southern rice black-streaked dwarf virus  ecological factors  stepwise regression  path analysis  prediction model
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