提前预测德国冬季大麻风险:将作物表现学和疾病发展纳入决策支持系统
Vera Krause1, Nazanin Zamani-Noor2, Lena Müller3
1Julius Kühn-Institute (JKI), Institute for Strategies and Technology Assessment, Kleinmachnow, Germany.
Pest management science
|August 23, 2025
概括
这项研究增强了SkleroPro模型,用于预测冬季大麻中的Sclerotinia茎腐烂. 改进的模型提高了疾病风险预测的准确性,有助于可持续的作物管理和减少杀菌剂的使用.
科学领域:
- 农业科学
- 植物病理学
- 农作物保护
背景情况:
- 这种由*Sclerotinia sclerotiorum*引起的菌干腐蚀对德国冬季大麻种 (*Brassica napus*) 产量构成重大威胁,可能导致高达30%的产量损失.
- 现有的SkleroPro模型对区域性硬化风险评估的预测准确性已经下降.
研究的目的:
- 改进冬季大麻的SkleroPro疾病风险预测模型
- 通过整合新的现象学模型和芽模块来提高预测准确度.
主要方法:
- 开发了一种使用温度和光周期预测开花阶段的现象模型 (BBCH 58-70).
- 使用平均最大温度和相对湿度创建了硬质细胞发芽模型.
- 将这些模块整合到 SkleroPro 模型中以改善疾病风险评估.
主要成果:
- 现象学模型实现了预测开花阶段的3.83天的平均平方误差 (RMSE).
- 结核菌的发芽模型显示出79%的准确性.
- 整合增加了SkleroPro的疾病风险预测准确度,从39%提高到66%,灵敏度提高到90%.
结论:
- 改进的SkleroPro模型可以更好地预测冬季大麻的疾病风险.
- 它确定了最佳的真菌杀菌剂应用窗口,支持可持续的做法,减少不必要的处理.
- 该工具正在进行验证,以便未来农民可以使用.
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