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当前位置: 首页 > 文章 > 三江平原水稻潜叶蝇发生规律及预测预报研究 中国农学通报 2017 (24) 144-147
Position: Home > Articles > Occurrence Rule and Prediction of Hydrellia griseola in Sanjiang Plain Chinese Agricultural Science Bulletin 2017 (24) 144-147

三江平原水稻潜叶蝇发生规律及预测预报研究

作  者：
顾鑫;柏晓东;丁俊杰;杨晓贺;赵海红;姚亮亮;刘伟;申宏波
单  位：
黑龙江省农业科学院佳木斯分院/农业部佳木斯作物有害生物科学观测试验站;黑龙江省伊春市林管局博士后工作站;黑龙江农业职业技术学院
关键词：
水稻潜叶蝇;通径分析;逐步回归;预测模型
摘  要：
研究旨在明确黑龙江省水稻主产区(三江平原)的水稻潜叶蝇的发生规律及影响水稻潜叶蝇发生的主要气象因子。试验从2006年开始连续10年在黑龙江省三江平原对水稻潜叶蝇的发生情况进行定点调查,收集水稻潜叶蝇发生时期的气象因子及第一代的虫口基数,采用通径分析及逐步回归的方法对6月末水稻潜叶蝇百株虫口数、气象因子及第一代虫口基数进行了研究,研究结果明确了第一代虫口基数及5月中旬的平均气温为影响水稻潜叶蝇的主要直接因子,而5月上旬的平均温度和5月下旬的平均温度是通过影响第一代虫口基数而间接影响了6月末的百株虫口数。通过逐步回归建立的短期预测模型Y=-150.012-1.432X_1+7.79X_4+0.17X_6+5.96X_7-0.121X_9-0.14X_(12)-0.09X_(15)+1.43X_(19)回归拟合效果好。可对黑龙江省三江平原水稻潜叶蝇的发生进行中短期预测。
译  名：
Occurrence Rule and Prediction of Hydrellia griseola in Sanjiang Plain
作  者：
Gu Xin;Bai Xiaodong;Ding Junjie;Yang Xiaohe;Zhao Haihong;Yao Liangliang;Liu Wei;Shen Hongbo;Ministry of Agriculture Harmful Biology of Crop Scientific Monitoring Station Jiamusi Experiment Station,Jiamusi Branch of Heilongjiang Academy of Agricultural Sciences;Heilongjiang Province Yichun Forest Authority Postdoctoral;Heilongjiang Agricultural College of Vocational Technology;
关键词：
Hydrellia griseola;;path analysis;;stepwise regression;;prediction model
摘  要：
To determine the occurrence rule of Hydrellia griseola in rice producing areas of HeilongjiangProvince(Sanjiang plain) and the main meteorological factors affecting the occurrence of Hydrellia griseola, anexperiment was conducted to investigate the occurrence of Hydrellia griseola in Sanjiang plain from 2006 for 10 consecutive years, meteorological factors and the first generation of the insect population were collectedduring Hydrellia griseola occurrence period, by means of path analysis and stepwise regression analysis, theinsect population of 100 plants, the meteorological factors and the population of the first generation of Hydrellia griseola in the end of June were studied. The results showed that the first generation of insect population andthe average air temperature in the middle of May were the direct factors that affected Hydrellia griseolas, theaverage temperature in early May and late May influenced Hydrellia griseolas population of 100 plants by itsinfluence on the first generation of insect population. The short term forecasting model based on stepwiseregression Y=-150.012-1.432X_1+7.79X_4+0.17X_6+5.96X_7-0.121X_9-0.14X_(12)-0.09X_(15)+1.43X_(19) fitting effectwas good. It could be used in the prediction of Hydrellia griseola in Sanjiang plain.

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