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学术动态

世界顶尖涉农大学交流合作提升项目“农业机器人作物多模态智能感知技术”在线系列课程

发布日期:2022-11-08    浏览次数:

报告题目:

Building Grape Disease Resistance via Systems Engineering-based Digital Agriculture(通过基于系统工程的数字农业建立葡萄抗病性)

报告人:

Dr. Yu Jiang, Assistant Professor of Systems Engineering and Data Analytics for Specialty Crops in the Horticulture Section, School of Integrative Plant Science, at Cornell AgriTech, Cornell University. (康奈尔大学,助理教授)

 

报告时间:

北京时间2022年11月11日(星期五) 9:30-11:30

 

线上报告接入方式:

腾讯会议 (VooV Meeting), 会议 ID:520 827 247

 

联系人:

苏道毕力格 sudao@cau.edu.cn

欢迎各位老师同学线上参加。

 

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Seminar Topics:

Building Grape Disease Resistance via Systems Engineering-based Digital Agriculture

 

International Experts:

Dr. Yu Jiang, Assistant Professor of Systems Engineering and Data Analytics for Specialty Crops in the Horticulture Section, School of Integrative Plant Science, at Cornell AgriTech, Cornell University.

Time:

Beijing Time (UTC +8:00) November 11th, 2022 (Friday) 9:30 AM - 11:30 AM

 

Online Meeting:

VooV Meeting, Meeting ID:520 827 247

 

Contact:

Daobilige Su sudao@cau.edu.cn

 

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摘要(Abstracts):

 

Building Grape Disease Resistance via Systems Engineering-based Digital Agriculture

Disease is one of the greatest threats to the environmental, financial, and societal sustainability of crop production in the US and worldwide, and is expected to continuously increase as the negative effects of climate change intensify. Digital agriculture enables the development of systems engineering approaches to revolutionizing plant disease research and management. This talk will focus on a set of robots and artificial intelligence (AI)-based data analysis methods for the detection and quantification of grape downy and powdery mildews. The robot and analysis method designs are particularly motivated for the adoption by researchers for genetic studies, breeding programs, and management practice improvements and by growers for production systems. Several case studies will be given to demonstrate the effectiveness and value of a systems engineering approach by integrating these robots and analysis methods to improve the overall disease resistance and management for grapes in the finger lakes region in the state of New York and beyond.

 

摘要:疾病是对美国和世界范围内作物生产的环境、金融和社会可持续性的最大威胁之一,并且随着气候变化的负面影响加剧,疾病预计将持续增加。数字农业能够开发系统工程方法来彻底改变植物病害研究和管理。本次报告将重点介绍一套基于机器人和人工智能 (AI) 的数据分析方法,用于检测和量化葡萄霜霉病和白粉病。机器人和分析方法的设计特别受到研究人员用于遗传研究、育种计划和管理实践改进以及种植者用于生产系统的推动。报告将给出几个案例研究,通过整合这些机器人和分析方法来证明系统工程方法的有效性和价值,以提高纽约州及其他地区芬格湖地区葡萄的整体抗病性和管理。

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简介(Bios):

 

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Bio: Dr. Yu Jiang is an Assistant Professor of Systems Engineering and Data Analytics for Specialty Crops in the Horticulture Section, School of Integrative Plant Science, at Cornell AgriTech, Cornell University. Prior to joining Cornell, he obtained his Ph.D. degree in Agricultural and Biological Engineering from the University of Georgia. At Cornell, he founded and leads the Cyber-Agricultural Intelligence and Robotics (CAIR) Laboratory that dedicates to the development of systems engineering solutions for challenges in specialty crop industries. He holds interdisciplinary field memberships in Horticulture, Biological and Environmental Engineering, Electrical and Computer Engineering, and Mechanical and Aerospace Engineering. He is an executive committee member of Cornell Institute for Digital Agriculture (CIDA) and devoted to the collaborative efforts on DA innovation, translation, and adoption. He and his lab has published over 30 peer-reviewed articles and received $3M funds from USDA, NASA, and private sectors to his research program. He also serves the community leadership of the Information Technology, Sensors, and Control Systems (ITSC) of ASABE as well as committee leaderships within the ITSC division.

 

个人简介:姜宇博士是康奈尔大学康奈尔农业技术中心综合植物科学学院园艺学系特种作物系统工程和数据分析助理教授。在加入康奈尔之前,他在乔治亚大学获得了农业与生物工程博士学位。在康奈尔大学,他创立并领导了网络农业智能和机器人 (CAIR) 实验室,该实验室致力于开发系统工程解决方案以应对特种作物行业的挑战。他在园艺、生物和环境工程、电气和计算机工程以及机械和航空航天工程等领域拥有跨学科领域的会员资格。他是康奈尔数字农业研究所 (CIDA) 的执行委员会成员,致力于 DA 创新、转化和应用方面的合作。他和他的实验室发表了 30 多篇经过同行评审的文章,并从美国农业部、美国宇航局和私营部门获得了300万美元的资金用于他的研究计划。他还担任 ASABE 信息技术、传感器和控制系统 (ITSC) 的社区领导以及ITSC部门内的委员会领导。




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