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Life Sciences - Agriculture | Data and Models in Action - Methodological Issues in Production Ecology

Data and Models in Action

Methodological Issues in Production Ecology

Stein, A., Penning de Vries, F.W. (Eds.)

1999, VIII, 180 p.

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Under leadership of CT de Wit a large amount of modeling, building prototypes and also application, was carried out in the 1970s and 1980s. Comprehensive models were built, evaluated and carefully documented in the areas of crop growth production, plant breeding, soil water and nutrients, and in crop protection. Simulation techniques and biophysical theories developed in parallel. Simulation and experimentation always went hand in hand. Much of this work is documented in a long series of PhD theses under supervision of De Wit, in the series of Simulation Monographs (PUDOC), and in numerous other publications. This work has inspired many scientists across the global science community. The CT de Wit Graduate School of Production Ecology (PE) of the Wageningen University builds further on this platform and finds new subjects for research on and with models, and data. The PE platform provides also an excellent opportunity to develop contacts, cooperation and joint software with research groups in related fields and abroad. This book precipitates from such an exploration in new directions. We realize that modem information systems and statistics can offer a substantial contribution to the modelling framework. Good examples can be found here, and these provide a clear direction for the years to come.

Content Level » Research

Keywords » agriculture - bayesian statistics - ecology - geographical information system - modeling - statistics

Related subjects » Agriculture - Applications - Geographical Information Systems - Statistics

Table of contents 

Preface. Contributors & Editors. General Introduction. I: Practical Aspects of Modeling. 1. Development of a morphogenetic model from field and lab data: modeling the seed number per node on a pea stem; M.H. Jeuffroy. 2. Pathways in crop modeling for cultivation control; G. van Straten. 3. Finding and using data for small scale applications of agrometeorological models such as yield forecasting at a European scale; P. Vossen. II: Some Statistical Aspects of Modeling. 4. Data use and Bayesian statistics for model calibration; M.J.W. Jansen. 5.Models and Scale: Up- and Down-Scaling; J.U. Smith. III: Geographical Information Systems for Production Ecology. 6. Modern geographic information systems and model linking; P.A. Longley, M.F. Goodchild. 7. Multi-scale approaches for geodata; M. Molenaar. IV: Perspectives for Automated Modeling. 8. Examples of object-oriented design in agricultural research; P.J. Schotman. 9. Computer based trends in automated modeling; J.L. Top. References. Index.

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