Precision Beekeeping and Selective Breeding of the Honey Bee Using Multimodal Signal Processing and Machine Learning
Precision Beekeeping and Selective Breeding of the Honey Bee Using Multimodal Signal Processing and Machine Learning
批准号:
548872-2019
负责人:
Falk, Tiago
金额:
$15.3万
依托单位国家:
加拿大
项目类别:
Alliance Grants
财政年份:
2020
资助国家:
加拿大
项目状态:
已结题
起止时间:
2020-01-01 至 2021-12-31
中文摘要
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英文摘要
While mostly associated with honey production, honeybees play a more crucial role in agriculture as pollinators. In fact, nearly one third of the world's food is directly dependent on bee pollination. In Canada, beekeeping is an important agricultural industry, with bees being produced for sale, honey and other hive products, as well as delivering valuable pollination services. Over the last decade, however, bee colonies have been dying off at alarming rates. Two major factors that have been identified include the proliferation of the varroa destructor parasite, which spreads deadly viruses, and failing queen bees. Visual inspection of hives is the current existing practice of bee health monitoring. Opening a beehive, however, aggravates the colony, disrupts honeybee behavior, and limits the scope of what can be done. To overcome this limitation, Nectar Technologies Inc. has developed sensor-based technologies that are placed within hives and allow for remote assessment of the health of several hives simultaneously. To date, their solutions have relied on temperature and humidity sensors to monitor queen bee presence and on external scales to monitor hive weight, a correlate of hive health and honey production. This project aims to take this "Internet of Hives" platform to the next level. By partnering with the Centre de recherche en sciences animales de Deschambault (CRSAD, a commercial queen bee breeder) and integrating additional vibration, acoustic, and CO2 sensors within the hives, we propose to develop five key innovations: 1) build multimodal correlates of phenotypic colony performance traits to allow for remote queen performance monitoring and 2) genetic parameters to be used to select best performing colonies, 3) develop automated methods to measure colony activity and strength, 4) honey production and flow, and 5) hive health. The proposed system has the potential to be low-cost, durable, and reliable, thus will be accessible to all Canadian beekeepers, large or small. The proposed project will also allow for the discovery of new science behind honey bee dynamics and health monitoring. As such, significant societal, scientific, and economic benefits to Canada are expected.
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Precision Beekeeping and Selective Breeding of the Honey Bee Using Multimodal Signal Processing and Machine Learning
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批准号:548872-2019
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项目类别:Alliance Grants
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