小麦条锈菌生理小种动态预测

Forecast of race dynamic of wheat stripe rust

为定量预测小麦条锈病菌小种变化,通过田间小种圃人工接种试验、品种抗病性鉴定历史数据分析和专家评估等三种方法,获得了在中国多年栽种的192个小麦品种与24个小麦条锈病菌生理小种或菌系的接近实际的相对寄生适合度数据。以其为主要参数,结合历年不同小麦品种种植面积构建了多品种-多小种互作模型Cultivar-Race Dynamics Mode(CRDM)。该模型用VB6.0语言可视化编程,输入某年小麦条锈病菌各小种频率就能输出未来若干年各小种的频率。初步检验结果表明,此模型结构虽简单,但可以大体预测小种变化趋势。同时就模型的改进和条锈菌小种预测问题也进行了讨论。

Practical relative parasitic fitness data of 24 physiological races or pathotypes of Puccinia striiformis on 192 long-term planting wheat cultivars in China were determined by using artificial inoculation plot trials, historical data analysis of cultivar resistance to different physiological races of P. striiformis, and expert assessment. Based on theses data as key parameters, a model of interactions between multi-cultivars and multi-races, flamed CRDM was established, which also combined with planting area of different wheat cultivars in past years. This model was programmed with Visual Basic 6.0 and could output frequency of every race in the future by year-to-year if frequency of every race was inputted in a certain year. The preliminary tested results showed that the model could predict the general trend of race occurring frequency, however the model structure was simple. The model improvement and race forecast of P. striiformis was also discussed in this paper.