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中国农学通报 ›› 2018, Vol. 34 ›› Issue (11): 92-96.doi: 10.11924/j.issn.1000-6850.casb18010100

所属专题: 水稻

• 植物保护 农药 • 上一篇    下一篇

南方水稻黑条矮缩病发生面积预测模型研究

颜松毅,陈 冰,陈观浩,宋祖钦,王春霞,梁盛铭   

  1. 广东省化州市气象局,广东省化州市气象局,广东省化州市病虫测报站,广东省化州市气象局,广东省化州市气象局,广东省化州市病虫测报站
  • 收稿日期:2018-01-18 修回日期:2018-02-24 接受日期:2018-03-02 出版日期:2018-04-16 发布日期:2018-04-16
  • 通讯作者: 陈 冰
  • 基金资助:
    广东省科技计划项目“南方水稻黑条矮缩病发生规律及防控技术研究”(2011B020416001),广东省科技计划项目“超级稻主要病虫害发生 特点及防控技术集成与推广”(2013B020416002)。

Southern Rice Black-streaked Dwarf Disease: Prediction Model of the Occurrence Area

  • Received:2018-01-18 Revised:2018-02-24 Accepted:2018-03-02 Online:2018-04-16 Published:2018-04-16

摘要: 南方水稻黑条矮缩病是近年来在中国南方稻区新发生的一种重要病毒性病害,在我国许多地区频繁流行成灾。为探索南方水稻黑条矮缩病发生流行动态规律并建立发生趋势预测模型,作者应用相关分析、逐步回归分析和通径分析方法对南方水稻黑条矮缩病发生发展的气象因子、介体虫量进行分析和模拟。结果表明:5—7月气象因子、介体虫量与发生面积均呈正相关,相关性均达显著或极显著水平;通径分析发现8月上旬稻飞虱成虫量和6月下旬—7月上旬降水量之积(X’3)对发生面积的直接作用最大(0.9318),其次为8月上旬稻飞虱成虫量和6月中旬—7月上旬降雨日数之积(X’4),而5月相对湿度(X’1)、5月上中旬相对湿度(X’2)主要通过X’3间接影响发生面积;通过逐步回归建立了预测模型y=-2.521645+0.017466 X’1+0.014457X’2+0.000050X’3-0.000296X’4。利用上述方程对2006—2016年进行回归拟合,模型预测准确、精度高,并对2017年进行预报,拟合值与实测值相差很小,准确率较高。利用该方程可对化州地区乃至粤西地区晚稻南方水稻黑条矮缩病的发生进行预测。

关键词: 红彩真猎蝽, 红彩真猎蝽, 斜纹夜蛾, 烟青虫, 烟蚜, 选择偏好

Abstract: Southern rice black-streaked dwarf disease is a kind of important viral disease, which outbroke recently in south china rice growing region, and occurred in many parts of our country. In order to research the dynamic epidemic law and establish the prediction model about occurrence trend, the author analyzed the meteorological factors and insect quantity in developing process of southern rice black-streaked dwarf disease by the methods of correlation analysis, stepwise regression analysis and path analysis. The result showed that both the meteorological factors from May to July and the insect quantity were positively correlated with the occurrence area. The correlation coefficient reached a significant level or more. Path analysis showed that the product of the imaginal rice planthoppers’ quantity in the first ten days of August and the precipitation from June 21st to July 10th, which was defined as X’3, had the most significant direct impact on occurrence area, the coefficient reached 0.9318. There were other impact factors, such as the product of the imaginal rice planthoppers’ quantity in the first ten days of August multiplied by the number of rainy days from June 21st to July 10th, which was defined as X’4, the relative humidity in May, which was defined as X’1, and the relative humidity from May 1st to May 20th , which was defined as X’2. All of them had an indirect impact on the occurrence area. The prediction model was established by stepwise regression analysis, and the prediction equation was given as Y=-2.521645+0.017466X’1+0.014457X’2+0.000050X’3-0.000296X’4, in which, y meant occurrence area, X’1 ,X’2, X’3 and X’4 were defined above. In 2017, the prediction equation was applied to predict the insect occurrence area, then there was only a very small error between prediction value and measurement value, and the high-precision prediction was obtained. The prediction equation can be applied to predict the occurrence area of southern rice black-streaked dwarf disease which outbreak in second rice growing season in Huazhou, and even in the western part of Guangdong province.