Smart Sprayer for Black-Grass Mapping and Resistance Monitoring

用于黑草绘图和阻力监测的智能喷雾器

• 批准号: 10028112
• 金额: $ 185.09万
• 依托单位: ROBERT BOSCH LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10028112
• 关键词: Smart; Sprayer; Black; Grass; Mapping

Black-grass (_Alopecurus myosuroides_) is the UK's most pernicious weed, causing considerable yield losses each year and threatening the sustainability of UK cereal production. Herbicides remain a key component of tactics to control this species, yet evolution of resistance due to overuse threatens their efficacy. Environmental considerations also raise concerns about such widespread herbicide use, including the potential for damaging off-target effects on potentially beneficial species. Finally, the cost to growers of existing herbicidal strategies are becoming prohibitively expensive.Precision spraying of herbicides specifically to weed patches, rather than the whole field, offers the potential to help mitigate these issues, considerably reducing herbicide use whilst maintaining effective control of the weed. To facilitate this, there is a need to develop systems for accurately and rapidly mapping the spatial distribution of the weed within the field, at time-points early enough to enable intervention. Spot application needs to be robust enough to avoid missing weeds and provide sufficient confidence for growers to support their uptake. And finally, software and machinery need to be in place for delivering the targeted, precision herbicide application.This project will enable UK SME Chafer to use the Bosch/BASF 'smart sprayer' concept and technology to develop, build and evaluate a camera-equipped self-propelled sprayer for black-grass mapping and precision patch- or spot-spraying. The artificial intelligence to identify weeds and the ability to generate precise weed maps will allow Rothamsted and BASF to conduct further research. The outcome of the project will allow field data generation to be used for agronomic recommendations. The data will be analysed on the xarvio(tm) platform, and models developed by Rothamsted will be used to develop bespoke recommendations of herbicide choice and variable-rate application of pre- and post-emergence herbicides. These plans will be implemented using precise (individual nozzle) control of herbicide application by the sprayer system, with performance evaluated against conventional 'whole-field' management in herbicide usage, cost reductions, and control efficacy.

看麦娘（Alopecurus myosuroides）是英国最有害的杂草，每年造成相当大的产量损失，并威胁到英国谷物生产的可持续性。除草剂仍然是控制这一物种的策略的关键组成部分，但由于过度使用而产生的抗药性威胁着它们的效力。环境方面的考虑也引起了人们对这种广泛使用除草剂的担忧，包括对潜在有益物种造成破坏性脱靶效应的可能性。最后，现有除草策略的成本对种植者来说变得过于昂贵。专门针对杂草块而不是整个田地精确喷洒除草剂，可以帮助缓解这些问题，大大减少除草剂的使用，同时保持对杂草的有效控制。为了促进这一点，有必要开发系统，用于准确和快速地绘制杂草在田地内的空间分布，在足够早的时间点进行干预。现场应用需要足够强大，以避免遗漏杂草，并为种植者提供足够的信心，以支持他们的吸收。最后，软件和机械设备需要到位，以提供有针对性的、精确的除草剂施用。该项目将使英国SME Chafer能够使用博世/巴斯夫的“智能喷雾器”概念和技术，开发、建造和评估配备摄像头的自走式喷雾器，用于黑草测绘和精确的斑块或点喷。识别杂草的人工智能和生成精确杂草地图的能力将使Rothamsted和BASF能够进行进一步的研究。该项目的成果将使产生的实地数据用于提出农艺建议。这些数据将在xarvio（tm）平台上进行分析，由Rothamsted开发的模型将用于制定除草剂选择和芽前和芽后除草剂变量施用的定制建议。这些计划将通过喷雾器系统对除草剂施用进行精确（单个喷嘴）控制来实施，并在除草剂使用、成本降低和控制功效方面对传统的“全田”管理进行性能评估。