LegumeLegacy - Optimising multiple benefits of grass, legume and herb mixtures in crop rotations: modelling mechanisms and legacy effects
LegumeLegacy - Optimising multiple benefits of grass, legume and herb mixtures in crop rotations: modelling mechanisms and legacy effects
批准号:
EP/X028003/1
负责人:
Christopher Reynolds
金额:
$33.8万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
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英文摘要
With the European Green Deal, the EU has committed to transition to carbon-neutral and sustainable systems of agriculture. LegumeLegacy aims to adapt existing mixed or ruminant based production systems, using state of the art knowledge from ecology, agronomy, statistics and other fields to minimize greenhouse gas emissions, nutrient inputs and leaching (and costs), while increasing carbon stocks, biodiversity and yield stability. To achieve this, an exceptional and distinctive strategy of LegumeLegacy includes a common experiment across multiple LegumeLegacy sites; 10 Doctoral Researchers (DRs; two funded by the Swiss Government) will collaborate on the common experiment and have their own distinctive and complementary research objectives. To develop a model system of crop rotation, in the common experiment grassland plots of varying diversity of six species (two grasses, two legumes, two herbs, selected for complementary functional traits) will be established as a grassland ley, grown, and terminated; the grassland leys will be followed by a wheat crop. The effect of the diversity of the grassland ley on the performance of the crop rotation will be evaluated by measurement of yield, quality and environmental performance. LegumeLegacy will recommend the design of grassland leys within crop rotations that optimise agronomic and environmental performance; the multi-site experiment will generalise the conclusion and its implementation potential across Europe.LegumeLegacy will train a cohort of 10 DRs into a new generation of future leaders who will have the capacity to develop and deploy interdisciplinary and data-driven sustainable practices in the agricultural sector. With a training programme that includes statistics, specialised research skills, targeted transferable skills and scientific co-operation within a global network, this cohort of future leaders will be equipped with professional skills for a range of associated disciplines in industry or academia.
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