寒地春油菜菌核病流行分析与监测防御体系
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摘要
春油菜菌核病在黑龙江省西北部地区发病普遍,1996年该病害发病率30-60%,严重地块可高达81%,平均发病率为48.7%,2003年发病率在33%左右。油菜菌核病已经在生产上造成重大损失,成为发展油菜生产的障碍。
     寒地春油菜菌核病菌子囊盘于六月中旬在田间始见,其数量在6月下旬、7月中上旬和下旬出现三次高峰,当雨量充足时可持续保持较高水平。逐步回归分析结果表明调查日前三天的相对湿度和降水量,调查日前十天的相对湿度和降水量是影响田间子囊盘数量的最主要因素。利用8个气象因子建立了子囊盘数量的逐步回归模拟方程和BP神经网络系统模型,模型的拟合效果好,对2003年子囊盘数量的预测也较为准确。
     逐步回归分析结果表明调查日前三天内降水量、调查当天的子囊盘数量和调查日前三天的相对湿度是影响田间空中孢子量的最主要因素。建立了空中孢子量的10因子逐步回归模拟方程和21因子BP神经网络系统模型,得到拟合效果很好的数学模型。
     田间花朵发病始于6月下旬,7月上旬达到高峰期,此时也是油菜盛花期。油菜叶片于7月初开始发病,在7月中旬达到高峰期,随后逐渐下降。油菜茎秆于7月上旬开始发病,此时为土表菌核萌发直接侵染造成,发病率低,增长极为缓慢。7月下旬以后进入快速增长期,直到收获。
     利用全部环境因子进行逐步回归分析筛选得到了6个与茎秆发病率显著相关的气象因子并建立了回归方程。研究结果表明花期的气象因子对茎秆发病影响最大,利用花期各气象因子建立了茎秆发病率的回归模拟方程和神经网络模拟模型,可用于田间流行预测,上述模拟模型对2003年进行预测的预测结果均较好。
     在调查研究基础上建立了春油菜菌核病综合防治体系。实践中效果较好的措施包括:合理轮作、垄作、中耕以降低田间菌核数,选择地势较高的田块种植,合理密植和施肥,防止倒伏,适时晚播,控制杂草以改善田间环境,在关键时期进行药剂防治。药剂试验结果表明:50%农利灵可湿性粉剂防治效果最好,防效达到89%,施用剂量以1.5公斤/公顷最为经济有效,在盛花期和终花期喷施对茎秆发病均有较好的防治效果,而盛花期喷药对减轻叶部病情效果最佳。
     在收集整理大量文献资料的基础上,组建了油菜菌核病综合治理专家系统,系统提供了油菜菌核病简介、病原菌及其致病机制、寄主及抗病性、病害流行与预测预报、病害防治等方面的咨询内容。
The results of the study showed: sclerotiniose disease on the spring rape distributed in north-west area of Heilongjiang province. The occurrence rate of the disease is 30-60% generally, in serious area it can reach more than 80% in 1996. In 2003, the disease rate was 33%.
    The apothecium of the pathogen appears in the middle ten days of June. There were three peaks of the apothecium number appeared in the last ten days of June, in the middle and the last ten days of July. If the rainfall is sufficient enough, the apothecium would keep high level. The result of stepwise regression analysis showed the RH and the precipitation in the three days before investigation and in the ten days before the investigation were the key factors affecting the apothecium number. The 8 factors stepwise regression equation and BP Artificial Neural Network (ANN) model of the disease were established.
    The result of stepwise regression analysis showed the amount of rainfall and the relative humidity in the three days before investigation and the number of apothecium in the investigation day were the key factors affecting the number of the spores in the air. The 10 factors stepwise regression equation and 21 factors BP Artificial Neural Network (ANN) model of the spores were established.
    The flowers were firstly infected in the last ten days of June. The peak of the rate of disease in flowers was in the first ten days of July when it just was the peak of florescence. The leaves were firstly infected in the first ten days of July, the rate of leaves disease reached it's peak in the middle ten days of July and then reduced gradually. The stems were firstly infected in the first ten days of July, the disease was caused by the sclerotium on the earth surface, the rate of the disease was low and increased slowly. The rate of the disease on the stems increased quickly in the last ten days of July until reaping time.
    
    
    
    6 factors that affected the stem disease were selected by multifactor stepwise regression analysis and were used in establishment of the stepwise regression equation. Research results showed that the florescence meteorological factors was the key factors affecting the stems disease and were used in the establishment of the stepwise regression equation and BP-ANN model. The models can predict the stems disease in 2003 very well.
    The integrated control system of the sclerotiniose of spring rape was established. The main methods including the following factors: Reasonable rotation, ridge culture and cultivation to reduce the number of the sclerotia, planting on the higher fields, reasonable close planting and using of fertilizer to prevent lodge; controlling weeds and planting latterly to improve the condition; Carrying through the chemical control at suitable period. The 50% Ronilan (WP) was the best germicide for chemical control, the rate of control could reach 89%, the best dose of the Ronilan was 1.5kg/hm, the best time to control was the peak of florescence and the end of florescence.
    The Integrated Pest Management (IPM) counseling system was established by collecting and collating a lot of documents, the system included 5 modules: the introduction of the disease, the pathogenic fungi and it's pathogenic mechanism, the hosts and it's resistance, the epidemic and the prediction of the disease, the control of the disease.
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