Science China Information Sciences

, Volume 54, Issue 3, pp 589–597

The next generation models for crops and agro-ecosystems

  • XinGuang Zhu
  • GuiLian Zhang
  • Danny Tholen
  • Yu Wang
  • ChangPeng Xin
  • QingFeng Song
Research Papers Special Focus

DOI: 10.1007/s11432-011-4197-8

Cite this article as:
Zhu, X., Zhang, G., Tholen, D. et al. Sci. China Inf. Sci. (2011) 54: 589. doi:10.1007/s11432-011-4197-8

Abstract

Growth in population, decrease in arable land area, and change in climate are endangering our food security. Precision agriculture has the potential to increase crop productivity thorough tailored agricultural practices for different growing areas. Many models of crops and agro-ecosystems capable of predicting interaction between plants and environments have been developed for precision agriculture. Currently, there are several representative categories of crop and agro-ecosystem models, including the de Wit school models, the DSSAT series models and the APSIM series models, which have contributed substantially to improvement of agricultural practices. However, these models are weak in predicting performances of crops under environmental and genetic perturbations are generally weak, which severely limits the application of these models in guiding precision agriculture. We need to develop the next generation crop and agro-ecosystems models with a high level of mechanistic basis, which can be integrated with high throughput data and can predict the heterogeneity of environmental factors inside canopy and dynamic canopy photosynthesis. In developing such a model close collaboration is inevitably required among scientists from different disciplines. The successful development and application of such models will undoubtedly advance precision agriculture through providing better agronomical practices tailored for different growing environments. These models will also form a basis to identify breeding targets for increased productivity at given location with given soil and climatic conditions.

Keywords

crop modelsecosystem modelscrop yieldsnonlinear analysisphotosynthesis

Copyright information

© Science China Press and Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • XinGuang Zhu
    • 1
    • 2
  • GuiLian Zhang
    • 1
  • Danny Tholen
    • 1
  • Yu Wang
    • 1
  • ChangPeng Xin
    • 1
  • QingFeng Song
    • 1
  1. 1.Plant Systems Biology Group, CAS-MPG Partner Institute and Key Laboratory for Computational Biology, Shanghai Institutes for Biological SciencesChinese Academy of SciencesShanghaiChina
  2. 2.Institute of Plant Physiology and Ecology, Shanghai Institute for Biological SciencesChinese Academy of SciencesShanghaiChina