PhenomUK - Crop Phenotyping: from Sensors to Knowledge
PhenomUK - Crop Phenotyping: from Sensors to Knowledge
批准号:
MR/R025746/1
负责人:
Tony Pridmore
金额:
$67.35万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2018
资助国家:
英国
项目状态:
已结题
起止时间:
2018 至 --
中文摘要
为了跟上人口增长和气候变化的步伐,需要大幅改善作物表现,人口增长推高了全球粮食需求,气候变化增加了种植系统在英国和国际上对极端天气事件的脆弱性。虽然植物育种工作大大受益于基因组学的进步,但分析与其遗传结构和环境相关的作物表型(即植物的结构和功能)仍然是一个主要的瓶颈。解决方案将是多学科的,需要工程和计算机科学以及植物生物学。传感器需要能够测量复杂的、可变形的、活的和生长的物体--植物--的各种特性,通常是在非常恶劣的环境中。捕捉根、枝、花、种子等关键特性的结构和功能植物性状必须从这些措施中有效和高效地恢复。大多数数据采集是基于图像的,需要先进的计算机视觉技术。然后,使用先进的数据分析和机器学习方法,利用特征数据来提供对植物生长速度、开花时间、种子生产和产量的了解。PhenomUK的愿景是建立一个由计算机科学家、工程师和生物学家组成的相互了解的综合社区,跨越学科界限共同努力,塑造应对21世纪全球挑战之一所需的技术-在资源枯竭和气候变化的背景下,为不断增长的人口提供安全的食物供应。通过一系列年度会议、研讨会、网络访问、在线培训活动和泵启动研究项目,这个多学科网络项目将:1.确保英国科学家能够获得推动世界领先的植物、作物和农业科学基础发现研究所需的创新技术能力2。提供对国家植物表型能力、需求和机会的更深入的了解,使英国能够充分参与国际倡议并从这些国际倡议中获得最大利益,例如由ESFRI重点项目(https://emphasis.plant-phenotyping.eu).)创建的泛欧洲基础设施
英文摘要
Major improvements in crop performance are needed to keep pace with population growth, which is driving up global food demand, and climate change, which is increasing the vulnerability of cropping systems to extreme weather events in the UK and internationally. Whilst plant breeding efforts have greatly benefited from advances in genomics, profiling the crop phenome (i.e. the structure and function of plants) associated with their genetic structure and environment remains a major bottleneck. Solutions will be multidisciplinary, requiring engineering and computer science as well as plant biology. Sensors are required that can measure of a diverse range of properties of complex, deformable, living and growing objects - plants - often in quite hostile environments. Structural and functional plant traits capturing key properties of roots, shoots, flowers, seeds, etc. must be recovered from those measures effectively and efficiently. Most data capture is image-based, requiring advanced computer vision techniques. Trait data are then used to provide understanding of e.g. plants' growth rates, flowering times, seed production and yield, using advanced data analysis and machine learning methods.PhenomUK's vision is of an integrated, mutually-informed community of computer scientists, engineers and biologists, working together across discipline boundaries to shape the technologies needed to address one of the global challenges of the 21st century - the provision of a secure food supply to a growing population against a background of resource depletion and climate change. Through series of Annual Conferences, workshops, networking visits, online training events and pump-priming research projects, this multidisciplinary network project will:1. ensure that UK scientists have access to the innovative technological capabilities needed to drive world-leading basic discovery research in the plant, crop and agricultural sciences2. provide the deeper understanding of national plant phenotyping capabilities, needs and opportunities required to allow the UK to participate fully in and gain maximum benefit from international initiatives such as the pan-European infrastructure being created by the ESFRI EMPHASIS project (https://emphasis.plant-phenotyping.eu).
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DOI:
10.12688/f1000research.52204.2
发表时间:
2021
期刊:
F1000Research
影响因子:
--
作者:
[]
通讯作者:
How can computers help grow crops better
计算机如何帮助农作物更好地生长
DOI:
--
发表时间:
2021
期刊:
影响因子:
--
作者:
[Futurum]
通讯作者:
Futurum
DOI:
10.1038/s41467-022-31150-5
发表时间:
2022-06-21
期刊:
NATURE COMMUNICATIONS
影响因子:
16.6
作者:
[Guenat, Solene, Purnell, Phil, Davies, Zoe G., Nawrath, Maximilian, Stringer, Lindsay C., Babu, Giridhara Rathnaiah, Balasubramanian, Muniyandi, Ballantyne, Erica E. F., Bylappa, Bhuvana Kolar, Chen, Bei, De Jager, Peta, Del Prete, Andrea, Di Nuovo, Alessandro, Ehi-Eromosele, Cyril O., Eskandari Torbaghan, Mehran, Evans, Karl L., Fraundorfer, Markus, Haouas, Wissem, Izunobi, Josephat U., Jauregui-Correa, Juan Carlos, Kaddouh, Bilal Y., Lewycka, Sonia, MacIntosh, Ana C., Mady, Christine, Maple, Carsten, Mhiret, Worku N., Mohammed-Amin, Rozhen Kamal, Olawole, Olukunle Charles, Oluseyi, Temilola, Orfila, Caroline, Ossola, Alessandro, Pfeifer, Marion, Pridmore, Tony, Rijal, Moti L., Rega-Brodsky, Christine C., Robertson, Ian D., Rogers, Christopher D. F., Rouge, Charles, Rumaney, Maryam B., Seeletso, Mmabaledi K., Shaqura, Mohammed Z., Suresh, L. M., Sweeting, Martin N., Taylor Buck, Nick, Ukwuru, M. U., Verbeek, Thomas, Voss, Hinrich, Wadud, Zia, Wang, Xinjun, Winn, Neil, Dallimer, Martin]
通讯作者:
Dallimer, Martin
TTL Networks e-Event 2021 Report
TTL Networks 2021 年电子活动报告
DOI:
--
发表时间:
2021
期刊:
影响因子:
--
作者:
[Hayes, C]
通讯作者:
Hayes, C
PhenomUKRI The UK Plant and Crop Phenotyping Infrastructure
-
批准号:BB/Y512333/1
-
项目类别:Research Grant
-
资助金额:$303.26万
-
财政年份:2023
-
负责人:Tony Pridmore
-
依托单位:
High throughput phenotyping of novel root traits for early stage root bulking in cassava using an Aeroponic imaging platform
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批准号:BB/P022790/1
-
项目类别:Research Grant
-
资助金额:$40.72万
-
财政年份:2017
-
负责人:Tony Pridmore
-
依托单位:
International Workshop on Image Analysis Methods for Plant Sciences
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批准号:BB/J020451/1
-
项目类别:Research Grant
-
资助金额:$1.13万
-
财政年份:2012
-
负责人:Tony Pridmore
-
依托单位:
国内基金
海外基金
基于ANDSystem与多组学的水稻和小麦胁迫响应分子调控网络及智能作物平台(Smart Crop)的构建
-
批准号:--
-
项目类别:--
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资助金额:105万元
-
批准年份:2022
-
负责人:陈铭
-
依托单位: