Scale and Complexity in Plant Systems Research

1. Front Matter

   Pages I-X

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2. Genetics of plant performance: from molecular analysis to modelling

   1. Front Matter

      Pages 1-1

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   2. Genetic and Molecular Analysis of Growth Responses to Environmental Factors Using Arabidopsis Thaliana Natural Variation

      • M. Reymond, B. Pieper, H. Barbier, A. Ihnatowicz, M. El-lithy, D. Vreugdenhil et al.

      Pages 1-13

   3. From QTLS to Genes Controlling Root Traits in Maize

      • R. Tuberosa, S. Salvi

      Pages 15-24

   4. Multi-Trait Multi-Environment QTL Modelling for Drought-Stress Adaptation in Maize

      • M. Malosetti, J.M. Ribaut, M. Vargas, J. Crossa, M.P. Boer, F.A. Van Eeuwijk

      Pages 25-36

   5. Accounting for Variability in the Detection and Use of Markers for Simple and Complex Traits

      • S.C. Chapman, J. Wang, G.J. Rebetzke, D.G. Bonnett

      Pages 37-44

   6. An Integrated Systems Approach to Crop Improvement

      • G.L. Hammer, D.R. Jordan

      Pages 45-61

   7. Crop Systems Biology

      • X. Yin, P.C. Struik

      Pages 63-73

3. Modelling genotype × environment interactions

   1. Front Matter

      Pages 75-75

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   2. A Modelling Approach To Genotype × Environment Interaction

      • W. Sadok, B. Boussuge, C. Welcker, F. Tardieu

      Pages 77-91

   3. Modelling Genotype × Environment × Management Interactions to Improve Yield, Water Use Efficiency and Grain Protein in Wheat

      • S. Asseng, N.C. Turner

      Pages 93-103

   4. Physiological Processes to Understand Genotype × Environment Interactions in Maize Silking Dynamics

      • L. BorrÁS, M.E. Westgate, J.P. Astini

      Pages 105-113

   5. Modelling the Genetic Basis of Response Curves Underlying Genotype × Environment Interaction

      • F.A. Van Eeuwijk, M. Malosetti, M.P. Boer

      Pages 115-126

4. Physiology and genetics of crop adaptation

   1. Front Matter

      Pages 127-127

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   2. Physiological Interventions in Breeding for Adaptation to Abiotic Stress

      • M.P. Reynolds, R.M. Trethowan

      Pages 129-146

   3. Physiological Traits for Improving Wheat Yield Under a Wide Range of Conditions

      • G.A. Slafer, J.L. Araus

      Pages 147-156

   4. Is Plant Growth Driven by Sink Regulation?

      • M. Dingkuhn, D. Luquet, A. Clément-Vidal, L. Tambour, H.K. Kim, Y.H. Song

      Pages 157-170

   5. Yield Improvement Associated with Lr19 Translocation in Wheat

      • D.J. Miralles, E. Resnicoff, R. Carretero

      Pages 171-178

5. Physiology and modelling of crop adaptation

   1. Front Matter

      Pages 179-179

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   2. Simulation Analysis of Physiological Traits to Improve Yield, Nitrogen Use Efficiency and Grain Protein Concentration in Wheat

      • P. Martre, M.A. Semenov, P.D. Jamieson

      Pages 181-201

The growing demand for food and increasing scarcity of fertile land and other resources (water, energy, etc. ) present multiple challenges to plant and crop scientists to meet the demands of future generations while protecting the environment and conserve biological diversity. Novel directions in linking basic plant sciences to crop and systems research are needed to meet the growing demand for food in a sustainable way. Crop performance can be changed by modifying genetic traits of the plant through plant breeding or changing the crop environment through agronomic management practices. To achieve that, systems analysis and modelling play an important role by integrating and evaluating new findings at the gene and plant level at higher scales of aggregation. Robust crop-physiological modelling can become an essential tool to use insights from functional genomics in explaining crop behaviour. Current crop models can predict crop performance over a range of environmental conditions. Recently QTL information has been incorporated into crop models, and this has proved the potential of narrowing genotype– phenotype gaps and of applying QTL-based models for the analysis of genotype-- environment interactions. To make further progress, model structure must be upgraded to allow for more physiological feedback features. Model input parameters should be designed to be potentially grounded in gene-level understanding. Integration of crop modelling into genetic and genomic researches can enhance the future position of crop physiology in ‘plant breeding by design’ (Yin, X.

• Ecology
• arabidopsis thaliana
• breeding
• ecosystem
• ecosystems
• environment
• genes
• genetic improvement
• genetics
• nitrogen
• physiology
• regulation
• wheat

• Crop and Weed Ecology Group, Wageningen University and Research Centre, The Netherlands

  J.H.J. Spiertz, P.C. Struik, H.H. Van Laar

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