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将黄河中下游地区小麦条锈病周年活动期划分为秋苗侵染期、越冬休止期、复苏扩展期和春季流行期四个阶段,分阶段选取有植物病害流行学和统计学意义的气象因子,通过归一化处理和加权组合,组成小麦条锈病气象指数,用回归方法建立多时效、归一化小麦条锈病气象预报模式。检验结果显示:气象指数与小麦条锈病发生程度密切相关,其相关系数在0.4257~0.7713;各时段预报模式的回代拟合率达88.9%~100%,2006年度和2007年度的试报结果均正确。证明此气象预报模式的预报时效超前、效果好,且具有动态特点,可用于黄河中下游地区小麦条锈病发生程度的预报。
The annual activity of wheat stripe rust in the middle and lower reaches of the Yellow River was divided into four phases: autumn and seedling infestation, overwintering dormancy, recovery and expansion, and spring epidemiology. The meteorological factors of plant disease epidemiology and statistical significance were selected in stages, Through the normalization and weighted combination, the meteorological index of wheat stripe rust is formed, and the regression method is used to establish the multi-aging and normalized wheat stripe rust weather forecasting model. The test results showed that the meteorological index was closely related to the occurrence of stripe rust in wheat with a correlation coefficient of 0.4257-0.7713; the fitting-back rate of prediction model in each period was 88.9% -100%, and the test results in 2006 and 2007 correct. It proves that forecasting weather forecasting mode of this weather forecasting ahead of schedule, good effect, and has dynamic characteristics, which can be used to predict the extent of wheat stripe rust in the middle and lower reaches of the Yellow River.