Crop models are used in a wide range of research. Below we provide provide brief descriptions by topics with links to more detailed examples or discussions.
Climate change impact assessment
DSSAT is widely used to simulate the potential impacts of climate change. Crop simulations have been a major data source for Intergovernmental Panel on Climate Change (IPCC) assessments for agriculture (Gitay et al., 2001; Easterling et al., 2007). As early as the second IPCC assessment report, extensive use was made of results from crop growth modeling (Reilly et al., 1996).
A more detailed discussion is here.
Irrigation management
The ability of DSSAT to simulate crop production under different levels of irrigation or other management conditions and for long-term (30-years or more) weather conditions, makes the model highly suitable for studying the impacts of irrigation management strategies. Of particular note are simulation options allowing for automatic irrigation applications (i.e., varying dates or amounts) when the available soil moisture is depleted to a user-specified threshold.
A more extensive treatment of these topics is given here.
Fertilizer management
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Crop improvement
The ability of crop models to integrate effects of genetics (G), environment (E) and management (M) makes them attractive tools to support crop improvement.
A more detailed discussion is here.
Gene-based modeling
With the rapidly increasing availability of data on DNA sequences of individual cultivars or breeding lines, there is growing interest in using this incredible data resource to improve crop model development and applications. Similarly, advances in understanding of the control of plant processes at the molecular level suggests opportunities to strengthen how mechanisms are represented in crop models. These interests have given rise to a broad area of activities termed “gene-based modeling.” Topics of interest to DSSAT users and system modelers can pertain to four activities:
- Estimation of genotype-specific model parameters (GSPs)
- Improved representation of crop processes
- Guiding genetic dissection of crop processes through analysis of GSPs as phenotypes
- Use of genetic data for genetically realistic sensitivity analyses
A more extensive treatment of these topics is given here.
Pest and disease management
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Spatial analysis
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Tillage simulation
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Crop rotations
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