关中地区小麦赤霉病预测系统
发布时间：2019-04-18 23:32
【摘要】：20世纪70年代以来,随着水肥条件的改善和栽培模式的改变,小麦赤霉病在关中地区发生逐渐加重。前人对该病的流行因素、病原菌的空间分布以及有性态发育动态、病害流行动态和药剂决策防治技术等做了大量的研究。但因受条件所限,子囊壳产生密度和空中孢子密度等方面的研究尚属空白。前人建立的病害流行动态模拟模型使用地面以上10 cm处孢子密度实测值作为菌源量,这不仅将预测的时间限制在小麦开花期,不能提前做出预警指导小麦赤霉病的药剂防治,同时降低了预测结果的准确度,增加了预测的工作量。针对这个问题,本研究以国内外最新的研究成果为基础,开展子囊壳密度与穗表孢子数的关系研究,构建了小麦赤霉病预测模型,研制小麦赤霉病预报器和远程预警系统。取得了以下主要研究结果:1、采用田间模拟试验法,建立了产壳秸秆密度与穗表孢子数的关系模型,y1=1.115+2.506 x,R2=0.972。2、以产壳秸秆密度与穗表孢子数的关系为基础,结合前人病害流行动态模拟模型,构建了新的小麦赤霉病预测模型。对2014年关中地区15个代表性的县(市)及杨凌区1986~1992年的预测准确度分别为92%和75%。3、研制出了小麦赤霉病预报器。利用单片机和雨量计、温湿度等传感器自动采集降雨量、小麦穗部温度、相对湿度,结合实地调查的产壳秸秆密度、小麦品种类型和抽穗日期等情况,预测小麦赤霉病病穗率,利用GPRS技术实现信息的存储和远程传输。4、采用ASP.NET技术,以Visual Studio.NET 2010及其携带的NET Framework 4.0为平台,结合SQL数据库技术,开发了基于小麦赤霉病预测模型的远程预警系统。
[Abstract]:Since the 1970s, with the improvement of water and fertilizer conditions and the change of cultivation pattern, the occurrence of wheat scab in Guanzhong area has become more and more serious. A great deal of research has been done on the epidemic factors, the spatial distribution of pathogenic bacteria, the dynamics of their sexual development, the epidemic dynamics of the disease, and the techniques of decision-making and control of pesticides, and so on. However, due to the limitation of conditions, the studies on the density of ascomyst production and the density of aerial spores are still blank. The disease epidemic dynamic simulation model established by predecessors used the spores density measured at 10 cm above the ground as the fungus source, which not only limited the predicted time to the flowering stage of wheat, but also could not give early warning to guide the control of wheat scab. At the same time, the accuracy of prediction results is reduced and the workload of prediction is increased. In order to solve this problem, based on the latest research results at home and abroad, the relationship between the density of ascomyst shell and the number of spores on the ear surface was studied, the prediction model of wheat scab was constructed, and the forecasting device and remote early warning system of wheat scab were developed. The main results are as follows: 1. The relationship model between the density of shell straw and the number of sporophytes per ear was established by field simulation experiment, y1, 1.115 2.506 x, R2, 0.972 2, respectively, and the relationship between the density of straw yield and the number of spores on the ear surface was established. Based on the relationship between the density of husk straw and the number of spores on the ear surface, a new prediction model of wheat scab was constructed based on the dynamic simulation model of disease prevalence. The prediction accuracy of 15 representative counties (cities) in Guanzhong region and Yangling district from 1986 to 1992 were 92% and 75% respectively. A wheat scab predictor was developed. Single chip microcomputer, rainfall gauge, temperature and humidity sensors are used to automatically collect rainfall, wheat spike temperature, relative humidity, field investigation of straw density, wheat variety type and heading date, etc., to predict the wheat scab disease spike rate. Using GPRS technology to realize the storage and remote transmission of information. 4, adopting ASP.NET technology, taking Visual Studio.NET 2010 and its carrying NET Framework 4.0as a platform, combining with SQL database technology, A remote early warning system based on wheat scab prediction model was developed.
【学位授予单位】：西北农林科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：S435.121.45;S126
本文编号：2460387
[Abstract]:Since the 1970s, with the improvement of water and fertilizer conditions and the change of cultivation pattern, the occurrence of wheat scab in Guanzhong area has become more and more serious. A great deal of research has been done on the epidemic factors, the spatial distribution of pathogenic bacteria, the dynamics of their sexual development, the epidemic dynamics of the disease, and the techniques of decision-making and control of pesticides, and so on. However, due to the limitation of conditions, the studies on the density of ascomyst production and the density of aerial spores are still blank. The disease epidemic dynamic simulation model established by predecessors used the spores density measured at 10 cm above the ground as the fungus source, which not only limited the predicted time to the flowering stage of wheat, but also could not give early warning to guide the control of wheat scab. At the same time, the accuracy of prediction results is reduced and the workload of prediction is increased. In order to solve this problem, based on the latest research results at home and abroad, the relationship between the density of ascomyst shell and the number of spores on the ear surface was studied, the prediction model of wheat scab was constructed, and the forecasting device and remote early warning system of wheat scab were developed. The main results are as follows: 1. The relationship model between the density of shell straw and the number of sporophytes per ear was established by field simulation experiment, y1, 1.115 2.506 x, R2, 0.972 2, respectively, and the relationship between the density of straw yield and the number of spores on the ear surface was established. Based on the relationship between the density of husk straw and the number of spores on the ear surface, a new prediction model of wheat scab was constructed based on the dynamic simulation model of disease prevalence. The prediction accuracy of 15 representative counties (cities) in Guanzhong region and Yangling district from 1986 to 1992 were 92% and 75% respectively. A wheat scab predictor was developed. Single chip microcomputer, rainfall gauge, temperature and humidity sensors are used to automatically collect rainfall, wheat spike temperature, relative humidity, field investigation of straw density, wheat variety type and heading date, etc., to predict the wheat scab disease spike rate. Using GPRS technology to realize the storage and remote transmission of information. 4, adopting ASP.NET technology, taking Visual Studio.NET 2010 and its carrying NET Framework 4.0as a platform, combining with SQL database technology, A remote early warning system based on wheat scab prediction model was developed.
【学位授予单位】：西北农林科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：S435.121.45;S126
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相关期刊论文 前4条
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