P.C. Struik – författare

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.

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.