田间空气中小麦白粉菌分生孢子的动态监测研究
Dynamic monitoring of aerial conidia of Blumeria graminis f. sp. tritici in wheat fields
查看参考文献14篇
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文摘
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2012和2013两年度采用Burkard定容式孢子捕捉器,对田间空气中小麦白粉病菌分生孢子的监测结果表明,小麦冠层内、外白粉菌分生孢子浓度存在显著的正相关性,冠层内的白粉菌分生孢子浓度明显高于冠层外;田间空气中分生孢子的浓度逐渐升高,到小麦灌浆期达到最大值,之后逐渐降低。时间序列分析结果表明,两年度田间空气中白粉菌分生孢子浓度均符合ARIMA(1,1,0)模型,且与温度有显著的相关性,建立了基于温度的白粉菌分生孢子浓度预测模型,模型回归效果均达到了显著水平。研究结果发现,田间白粉病病情与空气中病菌分生孢子和关键气象因子具有显著相关性,并在此基础上分别建立了基于空气中分生孢子浓度,以及基于分生孢子浓度和气象因子的田间白粉病病情预测模型,其中基于分生孢子浓度的预测模型普适性要优于基于分生孢子浓度和气象因子的预测模型,可以用来预测田间小麦白粉病的发生流行程度。 |
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其他语种文摘
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Conidia of Blumeria graminis f. sp. tritici(Bgt) in the air were monitored by Burkard volumetric spore samplers in 2012 and 2013. Conidia concentration of Bgt within the canopy was positively correlated with above the canopy and was significantly higher than that above the canopy. Conidia concentration raised along with time,reached the maximum concentration at filling stage of wheat,and then declined. Time series analysis showed that conidia concentration in the fields was fitted with ARIMA(1,1,0) models. A model was constructed based on the significant correlation between conidia concentrations in the air and temperature. Two models for prediction of disease index were established by inoculum variable only,and by both inoculum and weather variables, resprctively. The model based on inoculum only has more universal applicability to predicting disease index in comparison with the model based on both inoculum and weather variables. |
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来源
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植物病理学报
,2016,46(1):112-118 【核心库】
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DOI
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10.13926/j.cnki.apps.2016.01.013
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关键词
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小麦白粉病
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孢子捕捉
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数学建模
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流行监测
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地址
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1.
安徽农业大学植物保护学院, 植物病虫害生物学国家重点实验室, 合肥, 230036
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中国农业科学院植物保护研究所, 植物病虫害生物学国家重点实验室, 北京, 100193
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安徽农业大学植物保护学院, 合肥, 230036
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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0412-0914 |
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学科
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植物保护 |
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基金
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国家973计划
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国家自然科学基金项目
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公益性行业科研专项
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新疆维吾尔自治区科技支疆项目
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文献收藏号
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CSCD:5653990
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