STTR Phase I: Automated Continuous Varroa Mite Monitor for Honeybee Hive Health
STTR Phase I: Automated Continuous Varroa Mite Monitor for Honeybee Hive Health
批准号:
2127468
负责人:
Steve Cantley
金额:
$25.53万
依托单位:
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
项目状态:
已结题
起止时间:
2022-01-15 至 2023-06-30
中文摘要
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英文摘要
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.
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