一．时间：2017年7月28日（周五）上午9:00
二．地点：理科楼A201
三．日程安排
时 间 |
内 容 |
主持人 |
科学研究院常务副院长 姜 东 |
9:00-9:25 |
The Challenges Before and After Building Our Automated Crop Phenotyping Platforms 报告人：周济，英国厄勒姆研究院、约翰英纳斯研究中心 |
9:25-9:50 |
High-throughput phenotyping with Phenomobile 报告人：Frédéric BARET，法国农业科学院 |
9:50-10:15 |
Prototyping of an Integrated Field Phenotyping Platform – The University of Tokyo Field Plant Phenotyping Research Laboratory 报告人：Seishi Ninomiya ，日本东京大学 |
10:15-10:25 |
中场休息 |
10:25-10:50 |
Image sensing techniques for High throughput field phenotyping 报告人：郭威，日本东京大学 |
10:50-11:15 |
How to improve data interpretation from UAV for plant monitoring 报告人：Alexis Comar，法国农业科学院 |
11:15-11:40 |
Using 3D crop model high-throughput phenotyping data interpretation 报告人：刘守阳，法国农业科学院 |
11:40-12:00 |
Releasing the Crop Phenotyping Bottleneck with Remote Sensing and Internet of Things 报告人：Daniel REYNOLDS，英国厄勒姆研究院 |
（每个报告25分钟，其中20分钟报告、5分钟交流）
四．报告人简介（按姓氏字母排序）
Frédéric Baret，法国农科院教授，UMT-Capte实验室首席科学家，农业科学、植被生理生态与植被遥感领域国际知名专家，担任PHENOME（表型）项目执行委员和Remote Sensing of Environment, IEEE Transactions on Geosciences and Remote Sensing, International Journal of Remote Sensing, Agricultural and Forest Meteorology（环境遥感，地球科学与遥感学报，国际遥感，农林气象）等期刊审稿人。近年来率领UMT-Capte科研团队致力于高通量表型技术研究，并取得卓越成果。目前在国际一流期刊发表SCI论文220多篇，总引用超过1万次，H-index高达47。
Alexis Comar，Alexis Comar is an agronomist and a specialist in high thoughput field plant phenotyping. He is now the director of HIPHEN, a INRA start-up with 9 employees specialized in plant phenotyping.
郭 威，Dr. Wei Guo received his PhD from Graduate School of Agricultural and Life Sciences, the University of Tokyo in 2014. He is now the Assistant professor at International Field Phenomics Research Laboratory, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Japan. His academic activities include work as Councilor of Japanese Society of Agricultural Informatics. His research interest includes agro-informatics, plant phenotyping, image sensing and analyzing, machine learning and AI.
刘守阳，目前在法国开展田间作物表型博士后研究。开发了基于RGB图像的小麦萌芽期田间密度和分布方式的自动估算方法。开发了小麦三维结构功能模型表型监测模块，可以实现对无人机或田间机器人搭载的RGB，LiDARP或者多光谱监测的模拟。进而构建了基于小麦结构功能模型监督的表型数据分析框架。并提出了高通量的小麦叶面积指数，冠层结构动态和叶绿素等估算方法。
Seishi Ninomiya (二宫正士)，Prof. Seishi Ninomiya received his PhD from the University of Tokyo in 1982. Now he is the professor of International Field Phenomics Research Laboratory, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Japan. His academic activities include work as Chairman of CIGR International Commission of Agricultural and Biosystems Engineering, President of Japanese Society of Agricultural Informatics, etc. His research interest includes Biometrics, applied statistics, applied genetics, agro-informatics.
Daniel REYNOLDS，Daniel Reynolds is a Crop Phenomics Research Scientist. Working on the CropQuant in-field phenotyping platform, he is focusing on remote sensing research and control systems development. Specialising in hardware and infrastructure design, he has developed modular systems to integrate remote sensor apparatus for in-field crop monitoring. Presently, he is designing bespoke remote sensors, electronic circuits and physical housings suitable for the farming and breeding versions of CropQuant. Concentrating on cost-effective, robust and scalable design of remote sensing apparatus, he has expanded the scope of the original platform design to provide a scalable and capable solution to breeding and agricultural practices.
周 济，英国厄勒姆研究院、约翰英纳斯研究中心博士，主要研究方向是克服农业和作物研究中的表型瓶颈问题。目前，团队专注于开发和使用计算机视觉，深度学习和田间遥感技术等新的方法，以此来改进田间作物研究。包括，田间三维成像系统（PhenospexTM），基于高性能计算机的高通量表型分析平台（CropMonitor，The Zhou Lab），基于物联网的遥感表型系统（CropQuant，The Zhou Lab），使用机器学习来量化种子萌发和幼苗活力的自动筛选平台（SeedGerm，The Zhou Lab），使用无人机和轻型飞机的图像数据来进行大规模作物研究和数字农业的软件系统（AirSurf，The Zhou Lab）。
联系人：
科学研究院 卢玲 陈欢 电话：84399576
