title: Applying modelling experiences from the past to shape crop systems biology: the need to converge crop physiology and functional genomics.
abstract: Functional genomics has been driven greatly by emerging experimental technologies. Its development as a scientific discipline will be enhanced by systems biology, which generates novel, quantitative hypotheses via modelling. However, in order to better assist crop improvement, the impact of developing functional genomics needs to be assessed at the crop level, given a projected diminishing effect of genetic alteration on phenotypes from the molecule to crop levels. This review illustrates a recently proposed research field, crop systems biology, which is located at the crossroads of crop physiology and functional genomics, and intends to promote communications between the two. Past experiences with modelling whole-crop physiology indicate that the layered structure of biological systems should be taken into account. Moreover, modelling not only plays a role in data synthesis and quantitative prediction, but certainly also in heuristics and system design. These roles of modelling can be applied to crop systems biology to enhance its contribution to our understanding of complex crop phenotypes and subsequently to crop improvement. The success of crop systems biology needs commitments from scientists along the entire knowledge chain of plant biology, from molecule or gene to crop and agro-ecosystem.
authors: Crop and Weed Ecology Group, Wageningen University, PO Box 430, 6700 AK Wageningen, the Netherlands.
authors: Xinyou
authors: X
authors: Yin
authors: Crop and Weed Ecology Group, Wageningen University, PO Box 430, 6700 AK Wageningen, the Netherlands.
authors: Paul C
authors: PC
authors: Struik
mesh_terms: D000465:Algorithms; D018556:Crops, Agricultural / Q000235:genetics* / Q000254:growth & development; D004777:Environment; D017343:Genes, Plant; D023281:Genomics; D007178:Inbreeding; D008954:Models, Biological; D010641:Phenotype; D010788:Photosynthesis; D049490:Systems Biology