Agronomy and Horticulture Department

 

Date of this Version

January 2007

Comments

Published in J. H. J. Spiertz, P. C. Struik, and H. H. van Laar (eds.), Scale and Complexity in Plant Systems Research: Gene-Plant-Crop Relations, Dordrecht, Netherlands: Springer, 2007; pp. 319–328. Copyright © 2007 Springer. Used by permission. http://library.wur.nl/frontis/gene-plant-crop/24_struik.pdf

Abstract

In the future, more food needs to be produced with increasingly scarce natural resources. Genomics can play a key role in accelerating yield gains because it helps to improve our understanding of genetic traits and assists in breeding for better crop performance. The scientific muscle of genomics attracted tremendous research investments, but the efficiency with which these investments are paying off is still low. How can we accelerate the application of molecular genetics to our understanding of crop physiology and subsequently to crop improvement? The missing link is a more detailed understanding of the effects of gene function on crop performance at field level under agronomically relevant conditions captured in robust, physiology-based mechanistic models. With such models the most sensitive processes and mechanisms at whole-crop level that contribute to improved crop performance can be identified. To achieve the detailed understanding necessary to build and feed these models, more research on whole-plant physiology and crop ecology is required, with a focus on the complexity of scaling up knowledge from the molecular level to the farmers’ fields and production systems. Such studies assess how the plant is able to integrate the information at different levels of organization into the functioning of the whole plant and predicting the phenotype of transgenic plants engineered for improvement of a complex trait. More investment is needed in linking whole-plant physiology, crop ecology and crop simulation with molecular biology and genomics. Moreover, long-term progress can be enhanced by the formation of multidisciplinary teams that operate through networks of excellence in developing quantitative tools that integrate complex information and different levels of organization and by the exchange of young scientists between research groups working at different hierarchical levels. On the short term improvement of the characterization of experimental environments (preferably through commonly shared protocols) and of the characterization of parents for creating mapping populations is needed. In addition, joined multi-location trials and advanced physiological and statistical approaches for determining what aspects of the environment are most influential on the genotype × environment interactions are required.

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