| 项目编号: | BB/M018407/1
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| 项目名称: | FACCE ERA-NET+MODCARBOSTRESS |
| 作者: | John Hugh Doonan
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| 承担单位: | Aberystwyth University
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| 批准年: | 2014
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| 开始日期: | 2015-31-03
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| 结束日期: | 2018-30-03
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| 资助金额: | GBP191145
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| 资助来源: | UK-BBSRC
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| 项目类别: | Research Grant
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| 国家: | UK
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| 语种: | 英语
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| 特色学科分类: | Agri-environmental science
; Plant & crop science
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| 英文摘要: | Climate change accelerates the need for a smarter, more efficient, more secure agriculture. Because climate change is predicted to increase spatial and temporal variability, crop models able to predict the best local allele/phene combinations within a species, in addition to the best management systems (such as, for instance, species choice, rotations, sowing dates...) will be of great value for farmers and breeders worldwide. Aware of these issues and avenues, breeding companies now massively invest in crop and climate modelling.However, current crop models have large uncertainties, in particular under drought and high temperatures that often occur in combination and while their occurrences are likely to increase in several regions of the world. Whereas major environmental drivers of growth such as temperature, light and evaporative demand are now well captured in experiments, in particular following a concerted effort of the community, the availability of these information under various [CO2] is the exception. Our project will aim at delivering to simple, low cost, principles and solutions for manipulating combined stresses, including elevated CO2, in experimental set-ups. We will start to apply these principles to the different platforms that are part of the current project. |
| 资源类型: | 项目
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/101045
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| Appears in Collections: | 科学计划与规划
气候变化与战略
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作者单位: | Aberystwyth University
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| Recommended Citation: | |
John Hugh Doonan. FACCE ERA-NET+MODCARBOSTRESS. 2014-01-01.
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