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A changing climate for grassland research

A changing climate for grassland research Here, we review the current genetic approaches for grass improvement and their potential for the enhanced breeding of new varieties appropriate for a sustainable agriculture in a changing global climate. These generally out‐breeding, perennial, self‐incompatible species present unique challenges and opportunities for genetic analysis. We emphasise their distinctiveness from model species and from the in‐breeding, annual cereals. We describe the modern genetic approaches appropriate for their analysis, including association mapping. Sustainability traits discussed here include stress resistance (drought, cold and pathogeneses) and favourable agronomic characters (nutrient use efficiency, carbohydrate content, fatty acid content, winter survival, flowering time and biomass yield). Global warming will predictably affect temperature‐sensitive traits such as vernalisation, and these traits are under investigation. Grass biomass utilisation for carbon‐neutral energy generation may contribute to reduced atmospheric carbon emissions. Because the wider potential outcomes of climate change are unpredictable, breeders must be reactive to events and have a range of well‐characterised germplasm available for new applications. Contents Summary 9 I. Background 10 II. Objectives, breeding methodologies and progress in grass breeding 12 III. Markers and their suitability for genetic analysis in grasses 13 IV. Associating markers to genes for ‘sustainability’ in the grasses 13 V. The genetic control of flowering time 16 VI. Target traits: resilience against climate change and resistance to abiotic stresses 17 VII. Target traits: carbohydrates and sustainable ruminant animal production 19 VIII. Target traits: grass biomass, climate change and energy sustainability 21 IX. Conclusions 21 References 22 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png New Phytologist Wiley

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References (152)

Publisher
Wiley
Copyright
Copyright © 2006 Wiley Subscription Services, Inc., A Wiley Company
ISSN
0028-646X
eISSN
1469-8137
DOI
10.1111/j.1469-8137.2005.01549.x
pmid
16390415
Publisher site
See Article on Publisher Site

Abstract

Here, we review the current genetic approaches for grass improvement and their potential for the enhanced breeding of new varieties appropriate for a sustainable agriculture in a changing global climate. These generally out‐breeding, perennial, self‐incompatible species present unique challenges and opportunities for genetic analysis. We emphasise their distinctiveness from model species and from the in‐breeding, annual cereals. We describe the modern genetic approaches appropriate for their analysis, including association mapping. Sustainability traits discussed here include stress resistance (drought, cold and pathogeneses) and favourable agronomic characters (nutrient use efficiency, carbohydrate content, fatty acid content, winter survival, flowering time and biomass yield). Global warming will predictably affect temperature‐sensitive traits such as vernalisation, and these traits are under investigation. Grass biomass utilisation for carbon‐neutral energy generation may contribute to reduced atmospheric carbon emissions. Because the wider potential outcomes of climate change are unpredictable, breeders must be reactive to events and have a range of well‐characterised germplasm available for new applications. Contents Summary 9 I. Background 10 II. Objectives, breeding methodologies and progress in grass breeding 12 III. Markers and their suitability for genetic analysis in grasses 13 IV. Associating markers to genes for ‘sustainability’ in the grasses 13 V. The genetic control of flowering time 16 VI. Target traits: resilience against climate change and resistance to abiotic stresses 17 VII. Target traits: carbohydrates and sustainable ruminant animal production 19 VIII. Target traits: grass biomass, climate change and energy sustainability 21 IX. Conclusions 21 References 22

Journal

New PhytologistWiley

Published: Jan 1, 2006

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