
Working with Dynamic Crop Models
Methods, Tools and Examples for Agriculture and Environment
Academic Press
3rd Edition
Published on 28. September 2018
Book
Hardback
613 pages
978-0-12-811756-9 (ISBN)
Description
Working with Dynamic Crop Models: Methods, Tools and Examples for Agriculture and Environment, 3e, is a complete guide to working with dynamic system models, with emphasis on models in agronomy and environmental science. The introductory section presents the foundational information for the book including the basics of system models, simulation, the R programming language, and the statistical notions necessary for working with system models. The most important methods of working with dynamic system models, namely uncertainty and sensitivity analysis, model calibration (frequentist and Bayesian), model evaluation, and data assimilation are all treated in detail, in individual chapters.
New chapters cover the use of multi-model ensembles, the creation of metamodels that emulate the more complex dynamic system models, the combination of genetic and environmental information in gene-based crop models, and the use of dynamic system models to aid in sampling.
The book emphasizes both understanding and practical implementation of the methods that are covered. Each chapter simply and clearly explains the underlying principles and assumptions of each method that is presented, with numerous examples and illustrations. R code for applying the methods is given throughout. This code is designed so that it can be adapted relatively easily to new problems.
New chapters cover the use of multi-model ensembles, the creation of metamodels that emulate the more complex dynamic system models, the combination of genetic and environmental information in gene-based crop models, and the use of dynamic system models to aid in sampling.
The book emphasizes both understanding and practical implementation of the methods that are covered. Each chapter simply and clearly explains the underlying principles and assumptions of each method that is presented, with numerous examples and illustrations. R code for applying the methods is given throughout. This code is designed so that it can be adapted relatively easily to new problems.
More details
Edition
3rd edition
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
College/higher education
Researchers and advanced students in agronomy, agricultural and biological engineering, agricultural economics and agricultural statistics.
Dimensions
Height: 229 mm
Width: 152 mm
Weight
1260 gr
ISBN-13
978-0-12-811756-9 (9780128117569)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Daniel Wallach | David Makowski | James W. Jones
Working with Dynamic Crop Models
Methods, Tools and Examples for Agriculture and Environment
E-Book
09/2018
3rd Edition
Academic Press
€131.00
Available for download
Previous edition

Daniel Wallach | David Makowski | James W. Jones
Working with Dynamic Crop Models
Methods, Tools and Examples for Agriculture and Environment
Book
10/2018
2nd Edition
Academic Press
€94.09
The article will not be published
Persons
Daniel Wallach focuses on the application of statistical methods of dynamic systems, specifically on agronomy models. He has published in Agriculture, Ecosystems and Environment; Journal of Agricultural, Biological and Environmental Statistics and European Journal of Agronomy. David Makowski is an expert with the European Food Safety authority and the French Agency for Food, Environmental and Occupational Health and Safety and has authored 50 refereed articles and 10 book chapters on statistics, agricultural modeling and risk analysis. James Jones has authored more than 250 refereed scientific journal articles, developed and teached a graduate course based mostly on this book. He is a Fellow of the American Society of Agricultural and Biological Engineers, Fellow of the American Society of Agronomy, Fellow of the Soil Science Society of America and serves on several international science advisory committees related to agriculture and climate. Francois Brun specializes in agricultural modeling systems using the R language, and has published in Journal of Experimental Botany.
Author
Institut National de la Recherche Agronomique INRA, UMR INRA/INP, Toulouse, France
Institut National de la Recherche Agronomique INRA, UMR INRA/INA, Thiverval-Grignon, France
Agricultural and Biological Engineering Department, University of Florida, Gainesville, FL, USA
ACTA-INRA Toulouse, Castanet Tolosan, France
Content
Section A Background
1. Basics of Agricultural System Models
2. The R Programming Language and Software
3. Simulation with Dynamic System Models
4. Statistical Notions Useful for Modeling
5. Regression Analysis, Frequentist
Section B Basic methods
6. Uncertainty and Sensitivity Analysis
7. Calibration of System Models
8. Parameter Estimation With Bayesian Methods
9. Model Evaluation
10. Putting It All Together in a Case Study
Section C Advanced Methods
11. Metamodeling
12. Multimodel Ensembles
13. Gene-Based Crop Models
14. Data Assimilation for Dynamic Models
15. Models as an Aid to Sampling
Appendix 1: The Models Included in the ZeBook R Package: Description, R Code, and Examples of Results
Appendix 2: An Overview of the R Package ZeBook
1. Basics of Agricultural System Models
2. The R Programming Language and Software
3. Simulation with Dynamic System Models
4. Statistical Notions Useful for Modeling
5. Regression Analysis, Frequentist
Section B Basic methods
6. Uncertainty and Sensitivity Analysis
7. Calibration of System Models
8. Parameter Estimation With Bayesian Methods
9. Model Evaluation
10. Putting It All Together in a Case Study
Section C Advanced Methods
11. Metamodeling
12. Multimodel Ensembles
13. Gene-Based Crop Models
14. Data Assimilation for Dynamic Models
15. Models as an Aid to Sampling
Appendix 1: The Models Included in the ZeBook R Package: Description, R Code, and Examples of Results
Appendix 2: An Overview of the R Package ZeBook