Working with Dynamic Crop Models
Evaluation, Analysis, Parameterization, and Applications
Published on 9. May 2006
Book
Paperback/Softback
462 pages
978-1-4933-0234-5 (ISBN)
Description
Mathematical models are being used more and more widely to study complex dynamic systems (global weather, ecological systems, hydrological systems, nuclear reactors etc. including the specific subject of this book, crop-soil systems). The models are important aids in understanding, predicting and managing these systems.
Such models are complex and imperfect. One fundamental research direction is to seek a better understanding of how these systems function, and to propose mathematical expressions embodying that understanding. However, this is not sufficient. It is also essential to have tools (often mathematical and statistical methods) to aid in developing, improving and using the models built from those equations.
The book is specifically concerned with the application of methods to crop models, but much of the material is also applicable to dynamic system models in other fields. The goal of this book is to fill that gap.
Such models are complex and imperfect. One fundamental research direction is to seek a better understanding of how these systems function, and to propose mathematical expressions embodying that understanding. However, this is not sufficient. It is also essential to have tools (often mathematical and statistical methods) to aid in developing, improving and using the models built from those equations.
The book is specifically concerned with the application of methods to crop models, but much of the material is also applicable to dynamic system models in other fields. The goal of this book is to fill that gap.
More details
Language
English
Place of publication
United States
Publishing group
Elsevier Health Sciences
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.
ISBN-13
978-1-4933-0234-5 (9781493302345)
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
10/2018
2nd Edition
Academic Press
€94.09
The article will not be published
Additional editions
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
1 The two forms of crop models
2 Evaluating crop models
3 Uncertainty and sensitivity analysis for crop models
4 Parameter estimation for crop models
5 Data assimilation with crop models
6 Representing and optimizing management decisions with crop models
7 Using crop models for multiple fields
SECTION II APPLICATIONS
8 Introduction to section II
9 Fundamental concepts of crop models illustrated by a comparative approach
10 Crop models with genotype parameters
11 Model assisted genetic improvement of crops
12 Parameterization and evaluation of a corn crop model
13 Evaluation of a model for kiwifruit
14 Sensitivity and uncertainty analysis of a static denitrification model
15 Sensitivity analysis of PASTIS, a model of nitrogen transport and transformation in the soil
16 Sensitivity analysis of GENESYS, a model for studying the effects of cropping system on gene flow
17 Data assimilation and parameter estimation for precision agriculture with the crop model STICS
18 Application of extended and ensemble Kalman filters to soil carbon estimation
19 Analyzing and improving corn irrigation strategies with MODERATO, a combination of a corn crop model and a decision model
20 Managing wheat for ethanol production. A multiple criteria approach
2 Evaluating crop models
3 Uncertainty and sensitivity analysis for crop models
4 Parameter estimation for crop models
5 Data assimilation with crop models
6 Representing and optimizing management decisions with crop models
7 Using crop models for multiple fields
SECTION II APPLICATIONS
8 Introduction to section II
9 Fundamental concepts of crop models illustrated by a comparative approach
10 Crop models with genotype parameters
11 Model assisted genetic improvement of crops
12 Parameterization and evaluation of a corn crop model
13 Evaluation of a model for kiwifruit
14 Sensitivity and uncertainty analysis of a static denitrification model
15 Sensitivity analysis of PASTIS, a model of nitrogen transport and transformation in the soil
16 Sensitivity analysis of GENESYS, a model for studying the effects of cropping system on gene flow
17 Data assimilation and parameter estimation for precision agriculture with the crop model STICS
18 Application of extended and ensemble Kalman filters to soil carbon estimation
19 Analyzing and improving corn irrigation strategies with MODERATO, a combination of a corn crop model and a decision model
20 Managing wheat for ethanol production. A multiple criteria approach