Applications of crop models: what a load of crop!

So if you haven’t gathered by now, crop models will continue to be the focus of my blogs. After doing a fair bit of reading around the topic now, I have started to wonder if crop models can be implemented in real agricultural situations, successfully. If yes, where is this evidence for this? Within academic research crop models have many applications, Decision Support System for Agrothechnology transfer being one (Jones et al., 2003). However outside this there is little evidence of the application of crop models to actual agricultural systems. Crop models, in general, are covered extensively yet the focus of these papers tend to explore model development (ie. validation). The lack of academic literature, surrounding the application of crop models, is either because crop models are not used in decision making or their use is not recorded (as others who use crop models, for example NGOs and governmental bodies, do not publish their work) (Stephens and Middleton 2000).

There is no shortage of literature discussing the suitability of crop models outside the academic bubble (Basso et al., 2005; Mathews, 2002).  The paper ‘The school of de WIT crop growth simulation models: a pedigree and historical overview’ (Bouman et al., 1996) is just one which paints a gloomy picture of the application of crop models. The study argues there have been very few cases where models have been successfully applied (exceptions including models analyzing irrigation schemes or disease management).

Stephens and Middleton (2000) suggests many of these studies fail (failure referring to the little potential for real life application) due to an inappropriate focus on scientific interests, ignoring the factual issues at hand. This is a widely accepted reason for the failure of crop model application to the real world. Many models (used for academic research purposes) tend to focus on gaining accurate representation of the system, which varies from the interests of farmers, highlighting a gap between the academic questions and practical needs (of farmers). Routine planning is a factor which is often ignored in crop modelling. Many agricultural decisions are focused around timing of the wet season (this is one of the areas which produces the most risk in farming). Seasonal timing of irrigation of sugar cane, in South Africa, can determine the total crop yield. The issue of routine is less prominent for other stake holders such as local governments who are making strategic agricultural decisions (for example in the face of climate change).

The needs and expertise of local farmers needs to be incorporated into crop modeling studies in order to make them more applicable past the academic scene. The benefits of which will help in reducing agricultural risks and maintaining sustained crop yields.