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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
利用多模态信号处理和机器学习进行精准养蜂和蜜蜂选择性育种
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:
2021
资助国家:
加拿大
项目状态:
已结题
起止时间:
2021-01-01 至 2022-12-31

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中文摘要
翻译
虽然蜜蜂主要与蜂蜜生产有关,但作为传粉者,蜜蜂在农业中扮演着更关键的角色。事实上,世界上近三分之一的食物直接依赖于蜜蜂授粉。在加拿大,养蜂是一项重要的农业产业,生产用于销售的蜜蜂、蜂蜜和其他蜂箱产品,以及提供有价值的授粉服务。然而,在过去的十年里,蜂群一直在以惊人的速度消亡。已经确定的两个主要因素包括传播致命病毒的瓦罗亚破坏性寄生虫的繁殖,以及失败的蜂王。目视检查蜂箱是目前蜜蜂健康监测的现有做法。然而,打开蜂箱会加剧蜂群,扰乱蜜蜂的行为,并限制可以做的事情的范围。为了克服这一限制,Nectar Technologies Inc.开发了基于传感器的技术,这些技术可以放置在蜂箱内,并允许同时远程评估几个蜂箱的健康状况。到目前为止,他们的解决方案一直依赖温度和湿度传感器来监测蜂王的存在,并使用外部秤来监测蜂箱重量,这是蜂箱健康和蜂蜜产量的相关性。该项目旨在将这一“蜂巢互联”平台更上一层楼。通过与商业蜂王养蜂人动物科学研究中心(CRSAD)合作,并在蜂箱中集成更多的振动、声学和二氧化碳传感器,我们建议开发五项关键创新:1)建立表型蜂群性能性状的多模式关联式,以便远程监控蜂王性能,2)使用遗传参数选择表现最佳的蜂群,3)开发自动化方法来测量蜂群活动和强度,4)蜂蜜生产和流动,以及5)蜂箱健康。建议的系统具有低成本、耐用和可靠的潜力,因此加拿大所有的养蜂人,无论大小,都可以使用。拟议的项目还将允许发现蜜蜂动态和健康监测背后的新科学。因此,加拿大有望获得显著的社会、科学和经济利益。
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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Immersive Multisensory Media: from Quality of Experience to Quality of Life
Immersive Multisensory Media: from Quality of Experience to Quality of Life
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Immersive Multisensory Media: from Quality of Experience to Quality of Life
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