Credit hours
In-class work per week |
Practice per week |
Credits |
Duration |
Total |
3 |
2 |
6 |
15 weeks |
90 hours |
Instructor
Fábio Ricardo Marin
Quirijn de Jong van Lier
Objective
To enable the student to analyze, quantify and simulate computational processes related to the
development and growth of agricultural crops using numerical and analytical methods and computational
resources.
Content
Principles of process-based modeling. Modeling as a way of analyzing experimental data in agronomic
and environmental sciences.
- The effect of temperature on biological systems: chemical reactions, biological activity, plant
development, thermal time (degree-days), respiration.
- Interaction between canopy and radiation: absorption of radiation, photosynthesis, radiation use efficiency.
- soil water dynamics, drought stress and transpiration reduction, root water absorption and soil water balance.
- carbohydrate partitioning rules, structural efficiency.
- calibration and evaluation of models. Local and global sensitivity analysis.
- conceptualization and structuring of a process-based Python crop model to simulate crop growth or a process involved in crop growth.
Bibliography
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.
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.
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.
Mueller, J.P. Começando a programar em Python para leigos.Rio de Janeiro. Alta Books. 2016.
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.
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