The ‘School of de Wit’ crop growth simulation models: A pedigree and historical overview

Sensitivity of crop model predictions to entire meteorological and soil input datasets highlights vulnerability to drought

“…Crop growth models have been used in agricultural research for several decades to help understand and predict the behaviour of crops under different conditions (Bouman et al, 1996). Recent interest in areas such as the effects of climate change on food supply (Lobell et al, 2008), potential carbon mitigation by agriculture (Smith et al, 2000) and the use of biomass as an energy source (Bringezu et al, 2009) has increased the importance of accurate crop growth modelling.…”

A Quantitative Knowledge-based Model for Designing Suitable Growth Dynamics in Rice

“…The knowledgebased model can be considered as a set of algorithms with temporal and spatial characters for designing of proper dynamic growth indices for time-course regulation criteria during rice growing period. In nature, it's a modeled or digitalized expert system for optimum decision-making on rice management (Cao and Luo, 2003), rather than a simulation model for real-time prediction of rice growth status on the whatif cycle from a given set of conditions (Bouman et al, 1996;Cao and Moss, 1997). In principle, the dynamic rice growth indices from the knowledge-based model can be used as ideal growth curves or indicators for guiding cultural management and regulation of crop growth system to obtain target grain yield (Cao and Luo, 2003;Zhu et al, 2002).…”

“…With the principle of system analysis, the simulation model can quantitatively describe and predict the dynamic processes of crop growth, development and yield formation in relation to environmental, genetic and technical factors (Bouman et al, 1996;Sinclair and Seligman, 1996;Priya and Shibasaki, 2001;Andales et al, 2003;Cao and Luo, 2003). Since the simulation models have the functions of system integration and dynamic prediction, the growth model-based decision support systems can recommend management options for user's choice through a what-if approach (Jones et al, 2003), although the models themselves cannot directly generate optimum decisions on crop production management (Plant and Stone, 1991;Cao and Luo, 2003).…”

Regional Concentration and Specialisation in Agricultural Activities in EU-9 Regions (1950-2000)

“…The contributions of the 'production ecological school' are more recent. According to this school, soil suitability, fertility and availability of water are seen as key factors behind land use, and hence behind the distribution of agricultural production (Bouman et al, 1996;Rabbinge and van Latesteijn, 1992;WRR, 1992, where again an overview of the suitability of the soil for specific agricultural crops is given).…”