STTR Phase I: Automated Continuous Varroa Mite Monitor for Honeybee Hive Health

STTR 第一阶段：用于蜜蜂蜂巢健康的自动连续瓦螨监测仪

• 批准号: 2127468
• 负责人: Steve Cantley
• 金额: $ 25.53万
• 依托单位: IF, LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-15 至 2023-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2127468&HistoricalAwards=false
• 关键词: STTR; Phase; Automated; Continuous; Varroa

This Small Business Technology Transfer Phase I project addresses the health of honeybee hives and the associated $15 billion in annual agricultural services. Honeybee hives are susceptible to the parasitic Varroa destructor mite; unless the hive is treated, the presence of the Varroa mite eventually proves fatal to any bee colony it infests. Monitoring mite levels in beehives requires partial disassembly of the hive and the best counting method sacrifices some bees. Most of the nation’s 120,000+ beekeepers do not adequately test for mites. The expected output of this project is a low-cost, battery-operated “Internet-of-Things” device that can be placed inside hives, passively counting the Varroa mite population, and reporting the results to the beekeeper. The count can be used to indicate when mite treatment is needed and whether the treatment was effective. It prevents costly and unneeded prophylactic treatments that can lead to resistance in mite populations. This project fosters bee colonies that are healthy and productive, while reducing beekeeper workload and reducing unnecessary chemical treatments for beehives. The intellectual merit of this project is in the novel investigation of the use of near-infrared light wavelengths to determine where acceptable contrast exists between the exoskeletons of honeybees and Varroa mites, and the recognition of parasitic Varroa mites using modern artificial intelligence techniques that can be scaled to down for use in an edge computing environment that has significant limitations in terms of power availability and processing speed. The Phase I effort will integrate an infrared camera with variable wavelength narrowband infrared LED illumination, and photograph unparasitized and mite-infested honeybees. Human researchers will identify mites and use scored images to train an artificial intelligence engine to detect and count the mites.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个小型企业转移阶段I阶段项目解决了Honeybee Hives的健康和相关的150亿美元学术服务。蜜蜂蜂箱易受寄生的瓦罗杀伤膜螨虫的影响；除非处理蜂巢，否则瓦罗螨的存在最终证明对其感染的任何蜜蜂菌落都致命。监测蜂箱中的螨虫水平需要部分拆卸蜂巢，而最佳计数方法则牺牲了一些蜜蜂。全美的120,000多名养蜂人中的大多数都无法充分测试螨虫。该项目的预期输出是一种低成本，电池供电的“物联网”设备，可以放置在蜂箱内，被动地计算瓦罗阿螨的人群，并将结果报告给养蜂人。该计数可用于指示何时需要螨虫治疗以及治疗是否有效。它可以防止昂贵且不需要的预防治疗，从而导致缓解措施的抵抗力。该项目促进了健康且富有成效的蜜蜂殖民地，同时减少养蜂人的工作量并减少不必要的化学治疗方法。该项目的智力优点在于对使用近红外光波长的使用新颖的研究，以确定蜜蜂外骨骼和瓦罗阿螨的外骨骼之间的可接受对比，以及使用现代人工智能技术对寄生虫的识别，可以在边缘限制的环境中使用现代人工智能技术，以限制速度的限制，并在范围内限制范围。第一阶段的努力将将感染的摄像机与可变的波长窄带红外LED照明集成在一起，并照相无寄存和螨虫感染的蜜蜂。人类研究人员将识别螨虫，并使用评分的图像来训练人工智能引擎以检测和计算螨虫。该奖项反映了NSF的法定使命，并通过使用基金会的知识分子优点和更广泛的审查标准评估来诚实地获得支持。