Working with Dynamic Crop Models - 3rd Edition - ISBN: 9780128117569, 9780128117576

Working with Dynamic Crop Models

3rd Edition

Methods, Tools and Examples for Agriculture and Environment

Authors: Daniel Wallach David Makowski James Jones Francois Brun
Hardcover ISBN: 9780128117569
eBook ISBN: 9780128117576
Imprint: Academic Press
Published Date: 1st September 2018
Page Count: 528
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Description

Working with Dynamic Crop Models: Methods, Tools and Examples for Agriculture and Environment, Third Edition, presents a completely revised and updated edition ensuring that those seeking to understand and apply methods for working with dynamic models have applicable insight into current modeling. Structured by topic, each chapter includes an introduction, a detailed explanation of available methods, illustrations showing how the methods can be applied, and a detailed description of their implementation. The examples guide readers to direct, effective and efficient application of the methods that are accompanied by the core concepts they need to be successful.

Known for not simply being a numerical recipes book, the book is designed for relative ease in adapting the provided code to new problems and challenges.

Key Features

  • Includes new chapters on ensemble modeling, meta-models, gene-based modeling and improved strategies for using models
  • Presents insights on modeling, from the basics, to the most recent advances in techniques and software
  • Provides examples for applicable learning
  • Features an integrative chapter illustrating how different topics fit together in a complete modeling project

Readership

Researchers and advanced students in agronomy, agricultural and biological engineering, agricultural economics and agricultural statistics

Table of Contents

Section I 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

Section II Basic methods
6. Uncertainty and sensitivity analysis
7. Parameter estimation, classical (frequentist) approach
8. Parameter estimation, Bayesian approach
9. Model evaluation
10. Putting it all together in a case study

Section III Advanced methods
11. Meta-models
12. Working with ensembles of models
13. Gene based modeling
14. Data assimilation for dynamic models
15. Models as an aid to sampling

Appendices
1. Model descriptions
2. An overview of the R package ZeBook

Details

No. of pages:
528
Language:
English
Copyright:
© Academic Press 2019
Published:
Imprint:
Academic Press
Hardcover ISBN:
9780128117569
eBook ISBN:
9780128117576

About the Author

Daniel Wallach

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.

Affiliations and Expertise

Institut National de la Recherche Agronomique INRA, UMR INRA/INP, Toulouse, France

David Makowski

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.

Affiliations and Expertise

Institut National de la Recherche Agronomique INRA, UMR INRA/INA, Thiverval-Grignon, France

James Jones

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.

Affiliations and Expertise

Agricultural and Biological Engineering Department, University of Florida, Gainesville, FL, USA

Francois Brun

Francois Brun specializes in agricultural modeling systems using the R language, and has published in Journal of Experimental Botany.

Affiliations and Expertise

ACTA-INRA Toulouse, Castanet Tolosan, France

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