Semi-Automated Monitoring of Western Flower Thrips

西花蓟马是一种重要的农业害虫，危害设施蔬菜和软果等多种作物(1)。WFT通过取食植物以及通过传播不同的疾病而造成直接损害。WFT不仅影响作物产量，还影响作物质量，例如变形的草莓，从而降低作物的市场价值。WFT已经对大多数化学杀虫剂产生了抗药性，目前WFT的控制策略依赖于有效的WFT监测及其天敌如捕食性螨类的使用。这些天敌的成功依赖于它们的使用与WFT敏感生活期的存在相吻合。在WFT出现之前使用天敌会导致这些天敌的死亡，而较晚的应用可能不足以抑制WFT种群。目前，农户采用人工监测的方式来确定害虫种群数量，不仅费力，而且容易造成误报或数据采集不准确。机器学习和人工智能的应用为开发半自动化的WFT监测系统提供了机会本项目结合了基于人工智能的监测模型来监测WFT人口。监测工具将使用信息素将WFT吸引到装有摄像头和传感器的陷阱。将使用不同的陷阱设计和成像技术来优化WFT捕获和图像质量，以实现WFT自动监控。来自这些陷阱的数据将有助于识别和量化高频交易热点，使农民能够及时准确地应用控制措施。该项目是及时的，因为与新冠肺炎相关的限制和英国退欧限制了用于手动高频交易监测的熟练劳动力的可获得性。我们的创新将填补这一空白，并帮助英国种植者生产高质量的草莓。该项目将有助于显著减少作物损失，从而提高单位面积的粮食产量。生命周期分析将被用来证明所提出的技术在减少草莓生产的碳足迹方面的效果。这项研究提供了附加值，因为这里优化的技术将为开发针对一系列病虫害的类似作物保护提供潜力。1.van Lenteren J.C.和Loomans A.J.M.(1998)病虫害，第2卷，国际会议，英国，第401-408页

Western Flower thrips (WFT) are an important agricultural pest of several crops including protected vegetables and soft fruit crops (1). WFT cause direct damage by feeding on the plant as well as through transmission of different diseases. WFT affected crops not only reduce the crop yield but also affect the crop quality e.g. deformed strawberries thereby reducing the market value of the crops. WFT have developed resistance to the most chemical insecticides and currently WFT control strategies are dependent on effective WFT monitoring and the use of its natural enemies e.g. predatory mites.Success of these natural enemies relies on their application at a time to coincide with the presence of susceptible life stages of WFT. Application of natural enemies in advance of the emergence of WFT leads to death of these enemies whilst a late application might not be enough to suppress the WFT population. Currently, farmers use manual monitoring of WFT to determine the pest population which is not only laborious but also result in false alarms or inaccurate data collection. Application of machine learning and artificial intelligence offers an opportunity to develop a semi-automated WFT monitoring systemThis project brings together artificial intelligence -based monitoring model to monitor WFT population. The monitoring tools will use pheromones to attract WFT to traps fitted with cameras and sensors. Different trap design and imaging techniques will be used to optimise the WFT capture and image quality for automated WFT monitoring. Data from these traps will help in identification and quantification of WFT hotspots enabling farmers to apply control measures timely and precisely.The project is timely as Covid-19 related restrictions and Brexit have limited the availability of skilled labour for manual WFT monitoring. Our innovation will fill this gap and help UK growers to produce quality strawberries.The project will help contribute significantly to reduce crop losses thus improving food production per unit area. The life cycle analysis will be used to demonstrate the effect of proposed technology in reducing carbon footprint of strawberry production. This study offers added value as technologies optimized here would offer potential to develop similar crop protection against a range of pest and diseases.1.van Lenteren J.C. & Loomans A.J.M. (1998) pests & diseases, vol 2, International conference, UK, pp 401--408