Limited Offer
Save 50% on book bundles
Immediately download your ebook while waiting for your print delivery. No promo code needed.
Working with Dynamic Crop Models
Evaluation, Analysis, Parameterization, and Applications
- 1st Edition - May 10, 2006
- Authors: Daniel Wallach, David Makowski, James W. Jones, Francois Brun
- Editors: Daniel Wallach, David Makowski, James W. Jones
- Language: English
- eBook ISBN:9 7 8 - 0 - 0 8 - 0 4 6 1 9 3 - 9
Mathematical models are being used more and more widely to study complex dynamic systems (global weather, ecological systems, hydrological systems, nuclear reactors etc. including… Read more
Purchase options
Institutional subscription on ScienceDirect
Request a sales quoteMathematical 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.
* State-of-the-art methods explained simply and illustrated specifically for crop models
* Parameter estimation – applying statistical methods to the complex case of crop models, including Bayesian methods
* Includes model evaluation, understanding and estimating prediction error
* Offers a unique data assimilation by using the Kalman filter and beyond
* Parameter estimation – applying statistical methods to the complex case of crop models, including Bayesian methods
* Includes model evaluation, understanding and estimating prediction error
* Offers a unique data assimilation by using the Kalman filter and beyond
Researchers and graduate students in agronomy, agricultural and biological engineering, agricultural economics and agricultural statistics. Teachers of advanced courses in modeling of biological systems.
1 The two forms of crop models
D. Wallach
2 Evaluating crop models
D. Wallach
3 Uncertainty and sensitivity analysis for crop models
H. Monod, C. Naud, D. Makowski
4 Parameter estimation for crop models
D. Makowski, J. Hillier, D. Wallach, B. Andrieu, M.-H. Jeuffroy
5 Data assimilation with crop models
D. Makowski, M. Guérif, J. W. Jones, W. Graham
6 Representing and optimizing management decisions with crop models
J. E. Bergez, F. Garcia, D. Wallach
7 Using crop models for multiple fields
D. Leenhardt, D. Wallach, P. Le Moigne, M. Guérif, A. Bruand, M. A. Casterad
SECTION II APPLICATIONS
8 Introduction to section II
9 Fundamental concepts of crop models illustrated by a comparative approach
N. Brisson, J. Wery, K. Boote
10 Crop models with genotype parameters
M-H Jeuffroy, A. Barbottin, J. W. Jones, J. Lecoeur
11 Model assisted genetic improvement of crops
C.D. Messina, K.J. Boote, C. Löffler, J.W. Jones, and C.E. Vallejos
12 Parameterization and evaluation of a corn crop model
D. Wallach.
13 Evaluation of a model for kiwifruit
F. Lescourret and D. Wallach
14 Sensitivity and uncertainty analysis of a static denitrification model
B. Gabrielle
15 Sensitivity analysis of PASTIS, a model of nitrogen transport and transformation in the soil
P. Garnier
16 Sensitivity analysis of GENESYS, a model for studying the effects of cropping system on gene flow
N. Colbach and N. Molinari
17 Data assimilation and parameter estimation for precision agriculture with the crop model STICS
M. Guérif, V. Houlès, D. Makowski and C. Lauvernet
18 Application of extended and ensemble Kalman filters to soil carbon estimation
J. Jones and W. Graham
19 Analyzing and improving corn irrigation strategies with MODERATO, a combination of a corn crop model and a decision model
J. E. Bergez, J. M. Deumier and B. Lacroix
20 Managing wheat for ethanol production. A multiple criteria approach
C. Loyce, J. P. Rellier and J. M. Meynard
Appendix. Statistical notions
D. Wallach
2 Evaluating crop models
D. Wallach
3 Uncertainty and sensitivity analysis for crop models
H. Monod, C. Naud, D. Makowski
4 Parameter estimation for crop models
D. Makowski, J. Hillier, D. Wallach, B. Andrieu, M.-H. Jeuffroy
5 Data assimilation with crop models
D. Makowski, M. Guérif, J. W. Jones, W. Graham
6 Representing and optimizing management decisions with crop models
J. E. Bergez, F. Garcia, D. Wallach
7 Using crop models for multiple fields
D. Leenhardt, D. Wallach, P. Le Moigne, M. Guérif, A. Bruand, M. A. Casterad
SECTION II APPLICATIONS
8 Introduction to section II
9 Fundamental concepts of crop models illustrated by a comparative approach
N. Brisson, J. Wery, K. Boote
10 Crop models with genotype parameters
M-H Jeuffroy, A. Barbottin, J. W. Jones, J. Lecoeur
11 Model assisted genetic improvement of crops
C.D. Messina, K.J. Boote, C. Löffler, J.W. Jones, and C.E. Vallejos
12 Parameterization and evaluation of a corn crop model
D. Wallach.
13 Evaluation of a model for kiwifruit
F. Lescourret and D. Wallach
14 Sensitivity and uncertainty analysis of a static denitrification model
B. Gabrielle
15 Sensitivity analysis of PASTIS, a model of nitrogen transport and transformation in the soil
P. Garnier
16 Sensitivity analysis of GENESYS, a model for studying the effects of cropping system on gene flow
N. Colbach and N. Molinari
17 Data assimilation and parameter estimation for precision agriculture with the crop model STICS
M. Guérif, V. Houlès, D. Makowski and C. Lauvernet
18 Application of extended and ensemble Kalman filters to soil carbon estimation
J. Jones and W. Graham
19 Analyzing and improving corn irrigation strategies with MODERATO, a combination of a corn crop model and a decision model
J. E. Bergez, J. M. Deumier and B. Lacroix
20 Managing wheat for ethanol production. A multiple criteria approach
C. Loyce, J. P. Rellier and J. M. Meynard
Appendix. Statistical notions
- No. of pages: 462
- Language: English
- Edition: 1
- Published: May 10, 2006
- Imprint: Elsevier Science
- eBook ISBN: 9780080461939
DW
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, FranceDM
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, FranceJJ
James W. 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, USADW
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, FranceDM
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, FranceJJ
James W. 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, USAFB
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