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Validation of risk models for control of leaf blotch diseases in wheat in the Nordic and Baltic countries
European Journal of Plant Pathology ( IF 1.7 ) Pub Date : 2020-05-30 , DOI: 10.1007/s10658-020-02025-6
Lise Nistrup Jørgensen , Niels Matzen , Andrea Ficke , Ghita C. Nielsen , Marja Jalli , Antanas Ronis , Björn Andersson , Annika Djurle

Risk models for decisions on fungicide use based on weather data, disease monitoring, and control thresholds are used as important elements in a sustainable cropping system. The need for control of leaf blotch diseases in wheat (caused by Zymoseptoria tritici, Parastagonospora nodorum and Pyrenophora tritici-repentis) vary significantly across years and locations. Disease development is mainly driven by humidity events during stem elongation and heading. Two risk models were tested in field trials in order to identify situations favourable for the development of leaf blotch diseases in Lithuania, Norway, Sweden, Finland and Denmark. The Crop Protection Online (CPO) model uses days with precipitation (>1 mm), while the humidity model (HM) uses 20 continuous hours with relative humidity (RH) ≥ 85% as criteria for the need of a fungicide application. Forty-seven field trials were carried out during two seasons to validate these two risk-models against reference fungicide treatments. The season 2018 was dry and 2019 had an average precipitation profile. The two risk models with few exceptions provided acceptable disease control. In 2018, very few treatments were recommended by the models, saving 85–98% of treatments compared to the reference treatments, while in the wetter season 2019, 31% fewer applications were recommended. Based on specific criteria including fungicide input and net yield responses the models gave correct recommendations in 95% of the trials in 2018 and in 54–58% of the trials in 2019 compared with reference treatments dominated by 2–3 sprays. In comparison with single spray references, the models gave correct recommendations in 54–69% of the situations.



中文翻译:

北欧和波罗的海国家控制小麦叶斑病风险模型的验证

根据天气数据,疾病监测和控制阈值决定使用杀真菌剂的风险模型被用作可持续种植系统中的重要元素。防治小麦叶片斑点病的需要(由小麦枯萎病菌Zymoseptoria tritici),诺氏副寄生虫(Parastagonospora nodorum)小麦致病疫霉(Pyrenophora tritici-repentis)引起)年份和位置的差异很大。病害发展主要受茎伸长和抽穗期间的湿度事件驱动。为了确定有利于立陶宛,挪威,瑞典,芬兰和丹麦的叶片斑点病发展的情况,在现场试验中测试了两种风险模型。在线农作物保护(CPO)模型使用的天数是降水量(> 1 mm),而湿度模型(HM)则连续使用20个小时,相对湿度(RH)≥85%作为需要杀菌剂的标准。在两个季节内进行了47次现场试验,以验证这两种相对于参考杀菌剂治疗的风险模型。2018年的季节干燥,而2019年的平均降雨情况。这两个风险模型几乎没有例外,可以提供可接受的疾病控制。在2018年,该模型建议的治疗方法很少,与参考治疗方法相比,节省了85–98%的治疗方法,而在2019年较湿润的季节,推荐的治疗方法减少了31%。根据包括杀菌剂输入和净产量响应在内的特定标准,与以2-3次喷雾剂为主的参考疗法相比,该模型在2018年的95%试验和2019年的54-58%试验中给出了正确的建议。与单一喷雾参考相比,这些模型在54–69%的情况下给出了正确的建议。根据包括杀菌剂输入和净产量响应在内的特定标准,与以2-3次喷雾剂为主的参考治疗相比,该模型在2018年的95%试验和2019年的54-58%试验中给出了正确的建议。与单一喷雾参考相比,这些模型在54–69%的情况下给出了正确的建议。根据包括杀菌剂输入和净产量响应在内的特定标准,与以2-3次喷雾剂为主的参考治疗相比,该模型在2018年的95%试验和2019年的54-58%试验中给出了正确的建议。与单一喷雾参考相比,这些模型在54–69%的情况下给出了正确的建议。

更新日期:2020-05-30
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