Crop models are powerful tools to test hypotheses, synthesize and convey knowledge, describe and understand complex systems and compare different scenarios. Models may be used for prediction and planning of production, in decision support systems and control of the greenhouse climate, water supply and nutrient supply. The mechanistic simulation of tomato crop growth and development is described...

A robust crop model can assist in genetic improvement and cultural management of the crop. The objectives of this study were to describe a wheat (Triticum aestivum L.) model and to report results of its evaluation. The model simulates phenological development, leaf development and senescence, crop mass production and partitioning, plant nitrogen balance, yield formation and soil water and ...

We present a study on the impact of soil and climatic variability on the yield of winter wheat in the Hérault-Libron-Orb Valley in southern France. The study was based on the use of a crop simulation model (Euro-ACCESS), run at 63 individual sites throughout the study area, for the current climate (1976 to 1984) and for potential future changes in temperature and precipitation (2047 to 2054). T...

Traditional decision support systems based on crop simulation models are normally site-specific. In policy formulation, however, spatial variability of crop production often need to be evaluated due to different soil conditions, weather conditions and agricultural practices within a target-region. To address the spatial variability, a spatial model “Spatial EPIC” was developed based on a crop s...

Respiration has a profound influence on crop yield because dry matter accumulation by a crop is closely related to assimilation of CO and respiratory activity. This paper describes the development of a 2 simulation model for respiration in wheat. While the growth respiration can be assumed to be proportional to the assimilation of CO , the model concentrated on the effects of biotic and environ...

an analysis of the stages of crop growth presents an important step in the improvement of production management. through growth analysis, planning for planting systems, fertilization, pruning operations, harvest time as well as obtaining economical yield can be more accessible. therefore, a development of mathematical models simulating plant growth would be helpful in improving crop management,...