Staff Publications

Staff Publications

  • external user (warningwarning)
  • Log in as
  • language uk
  • About

    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Record number 536550
Title Bringing genetics and biochemistry to crop modelling, and vice versa
Author(s) Yin, Xinyou; Linden, Gerard van der; Struik, Paul C.
Source European Journal of Agronomy (2018). - ISSN 1161-0301
DOI http://dx.doi.org/10.1016/j.eja.2018.02.005
Department(s) Crop Physiology
PE&RC
WUR PB Abiotische Stress
Publication type Refereed Article in a scientific journal
Publication year 2018
Availibility Full text available from 2020-03-03
Keyword(s) Complex phenotype - Crop improvement - G×E - Interdisciplinary approach - Systems modelling
Abstract Genetics, biochemistry, and crop modelling are independently evolving disciplines; however, they complement each other in addressing some of the important challenges that crop science faces. One of these challenges is to improve our understanding of crop genotype-to-phenotype relationships in order to assist the development of high-yielding and resource-use efficient genotypes that can adapt to particular (future) target environments. Crop models are successful in predicting the impact of environmental changes on crop productivity. However, when critically tested against real experimental data, crop models have been shown to be less successful in predicting the impact of genotypic variation and genotype-by-environment interactions exhibited in genetic populations. In order to better model gene-trait-crop performance relationships in support of breeding and genetic engineering programmes, crop models need to be improved in terms of both model parameters and model structure. We argue that integration of quantitative genetics and photosynthesis biochemistry with modelling is a first step towards a new generation of improved crop models. With genetic information and biochemical understanding incorporated, crop modelling also generates new insights and concepts that can in turn be used to improve genetic analysis and biochemical modelling of complex traits. This modelling-genetics-biochemistry framework (the MGB triangle framework) stresses the synergy among the three disciplines, and may best serve as a step to achieve the ultimate goal of the more broadly framed "Crop Systems Biology" approach to improve efficiency of both classical breeding and genetic engineering programmes.
Comments
There are no comments yet. You can post the first one!
Post a comment
 
Please log in to use this service. Login as Wageningen University & Research user or guest user in upper right hand corner of this page.