Machine-Cast: A scalable machine learning framework for forecasting risk of crop pests and pathogens

Machine-Cast：用于预测农作物病虫害和病原体风险的可扩展机器学习框架

• 批准号: 10005703
• 金额: $ 23.36万
• 依托单位: CLIMATE EDGE LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10005703
• 关键词: Machine; Cast; scalable; machine; learning

In this project we are building a novel pest/disease forecasting service that uses machine learning 'ensemble' techniques to imbue highly localised predictive power and wide pest-crop-geography application potential. This broad-spectrum approach to forecasting is highly innovative and has the potential to drive synergistic improvements in the usage of inputs across all of the UK's most important crops. This innovation will drive a reduction in agro-chem usage, increase in crop yields and reduce the carbon footprint of UK agriculture.

在这个项目中，我们正在建立一个新的病虫害预测服务，该服务使用机器学习“集成”技术，赋予高度本地化的预测能力和广泛的病虫害作物地理应用潜力。这种广谱预测方法具有高度创新性，并有潜力推动英国所有最重要作物投入使用的协同改进。这一创新将减少农用化学品的使用，提高作物产量，减少英国农业的碳足迹。