Working with Dynamic Crop Models
Methods, Tools and Examples for Agriculture and Environment
2nd Edition
Published on 9. December 2013
Book
Hardback
504 pages
978-0-12-397008-4 (ISBN)
Description
This second edition of Working with Dynamic Crop Models is meant for self-learning by researchers or for use in graduate level courses devoted to methods for working with dynamic models in crop, agricultural, and related sciences.
Each chapter focuses on a particular topic and includes an introduction, a detailed explanation of the available methods, applications of the methods to one or two simple models that are followed throughout the book, real-life examples of the methods from literature, and finally a section detailing implementation of the methods using the R programming language.
The consistent use of R makes this book immediately and directly applicable to scientists seeking to develop models quickly and effectively, and the selected examples ensure broad appeal to scientists in various disciplines.
Each chapter focuses on a particular topic and includes an introduction, a detailed explanation of the available methods, applications of the methods to one or two simple models that are followed throughout the book, real-life examples of the methods from literature, and finally a section detailing implementation of the methods using the R programming language.
The consistent use of R makes this book immediately and directly applicable to scientists seeking to develop models quickly and effectively, and the selected examples ensure broad appeal to scientists in various disciplines.
Reviews / Votes
"This edition adds chapters on the basics of dynamic system models, statistics, and simulation; examples of how the methods can be applied to real-world problems; advanced methods for parameter estimation, model evaluation, and data assimilation; a new chapter on how the topics fit together in a complete modeling project; and information on how to use the R language and platform." --ProtoView.com, April 2014More details
Edition
2nd edition
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
Professional and scholarly
Researchers and graduate students in agronomy, agricultural and biological engineering, agricultural economics and agricultural statistics. Teachers of advanced courses in modeling of biological systems.
Dimensions
Height: 229 mm
Width: 152 mm
Weight
740 gr
ISBN-13
978-0-12-397008-4 (9780123970084)
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
New editions
Daniel Wallach | David Makowski | James W. Jones
Working with Dynamic Crop Models
Methods, Tools and Examples for Agriculture and Environment
Book
09/2018
3rd Edition
Academic Press
€142.37
Shipment within 15-20 days
Additional editions
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
Daniel Wallach | David Makowski | James W. Jones
Working with Dynamic Crop Models
Methods, Tools and Examples for Agriculture and Environment
E-Book
11/2013
2nd Edition
Academic Press
€74.95
Available for download
Previous edition
Daniel Wallach | David Makowski | James W. Jones
Working with Dynamic Crop Models
Evaluation, Analysis, Parameterization, and Applications
Book
05/2006
Elsevier
€86.65
Article exhausted; check for reprint
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 I Basics1. Basics of Agricultural System Models2. Statistical notions useful for modeling3. The R programming language and software4. Simulation with dynamic system models
Section II Methods5. Uncertainty and sensitivity analysis6. Parameter estimation with classical methods7. Bayesian methods for parameter estimation8. Data assimilation for dynamic models9. Model evaluation10. Putting it all together in a case study
Appendices1. Model descriptions2. An overview of the R package ZeBook
Section II Methods5. Uncertainty and sensitivity analysis6. Parameter estimation with classical methods7. Bayesian methods for parameter estimation8. Data assimilation for dynamic models9. Model evaluation10. Putting it all together in a case study
Appendices1. Model descriptions2. An overview of the R package ZeBook