Credit hours
In-class work per week |
Practice per week |
Credits |
Duration |
Total |
3 |
3 |
8 |
15 weeks |
120 hours |
Instructor
Fábio Ricardo Marin
Quirijn de Jong van Lier
Objective
Enable the student to use computational resources for the processing, analysis, quantification and simulation of physical and biological processes in agricultural systems. To present the principles and main techniques of process-based modeling of the growth and development of agricultural crops and to enable them to understand and develop numerical computational models. Basic concepts of dynamic simulation of agricultural systems and modeling methods including sensitivity analysis, parameter estimation, stochastic analysis and model evaluation. Application of models in the analysis of agricultural systems.
Content
1) Types of models: Statistical, empirical, deterministic, mechanistic models. Dynamic and static models. Macroscopic and microscopic models. Flow-charts used in the analysis of agricultural systems.
2) Modeling tools: conservation laws and principles; differential and integral equations, numerical simulation. Discrete and continuous modeling.
3) Stochastic process modeling concepts: distribution, covariance, random variables, correlated random variables. Uncertainty.
4) Evaluation and benchmarking of models. Model sensitivity to parameters. Comparison between simulations and real data. Comparison between models. Cross-validation.
5) Development of a model based on a process of interest related to an agricultural system and presentation of modeling results in the form of a seminar at the end of the semester.
Bibliography
Wallach, D., D. Makowski, and J. W. Jones (Eds.). Working with Dynamic Crop Models: Evaluation, Analysis, Parameterization, and Applications. Elsevier. New York. ISBN 0-444-52135-6. 2006.
Chapman, S. Fortran 95/2003 for Scientists & Engineers. McGraw-Hill; 3 edition, 2007.
Goudriaan, J, & Van Laar, H.H. Modelling Potential Crop Growth Processes. Kluwer Academic Publishers, London. 1994.
Harte, J. Consider a Spherical Cow: A Course in Environmental Problem Solving. University Science Books. Sausalito, CA. 1988.
Teh, C. Introduction to Mathematical Modeling of Crop Growth: How the Equations are Derived and Assembled into a Computer Program. BrownWalker Press. Boca Raton. 2006.
Thornley, John H.M. and Ian R. Johnson. Plant and Crop Modeling: A Mathematical Approach to Plant and Crop Physiology. Oxford University Press. New York. Blackburn Press. 2000.
Wit, C.T. de & Goudriaan, J. Simulation of Ecological Processes. Pudoc, Wageningen. 1978
Overman, Allen R., e Richard V. Scholtz III. Mathematical Models of Crop Growth and Yield. CRC Press, 2002.
Soltani, Afshin, e Thomas R. Sinclair. Modeling physiology of crop development, growth and yield. CABI, 2012.