| Records |
Author  |
Deligios, P.; Ledda, L.; Farci, R.; Doro, L.; Roggero, P.P. |
| Title |
Impatto dei cambiamenti climatici sulla produzione di colza da bioenergia in un ambiente mediterraneo |
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Conference Article |
| Year |
2012 |
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CropM |
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XLI Convegno annuale Società Italiana di Agronomia, Bari, Italy, 2012-09-19 to 2012-09-21 |
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MA @ admin @ |
Serial |
2387 |
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Dumont, B.; Ferrandis, V., S.; Leemans, V.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
| Title |
Vers un système de prédiction du rendement en temps réel |
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Conference Article |
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2012 |
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CropM |
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IXeme Seminaire STICS, Orléans, Sainte Montaine (France)., 2012-10-16 to 2012-10-16 |
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no |
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MA @ admin @ |
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2405 |
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Dumont, B.; Leemans, V.; Ferrandis Vallterra, S.; Vancutsem, F.; Seutin, B.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
| Title |
Assessing the potential of an algorithm based on mean climatic data to predict wheat yield |
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Conference Article |
| Year |
2012 |
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CropM |
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11th International Conference on Precision Agriculture. Indianapolis (USA)., 2012-07-15 to 2012-07-18 |
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no |
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MA @ admin @ |
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2404 |
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Dumont, B.; Leemans, V.; Ferrandis Vallterra, S.; Vancutsem, F.; Seutin, B.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
| Title |
A first step towards a real-time predictive yield support system |
Type |
Conference Article |
| Year |
2012 |
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CropM |
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CIGR-AgEng 2012, International Conference on Agricultural Engineering, Valencia (Spain)., 2012-07-07 to 2012-07-12 |
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no |
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MA @ admin @ |
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2403 |
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Dumont, B.; Vancutsem, F.; Seutin, B.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
| Title |
Simulation de la croissance du blé à l’aide de modèles écophysiologiques: Synthèse bibliographique des méthodes, potentialités et limitations |
Type |
Journal Article |
| Year |
2012 |
Publication |
Biotechnologie, Agronomie, Société et Environnement |
Abbreviated Journal |
Biotechnologie, Agronomie, Société et Environnement |
| Volume |
163 |
Issue |
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Pages |
376-386 |
| Keywords |
crops; growth; soil; Triticum; wheats; calibration; optimization methods |
| Abstract |
Crop models describe the growth and development of a crop interacting with its surrounding agro-environmental conditions (soil, climate and the close conditions of the plant). However, the implementation of such models remains difficult because of the high number of explanatory variables and parameters. It often happens that important discrepancies appear between measured and simulated values. This article aims to highlight the different sources of uncertainty related to the use of crop models, as well as the actual methods that allow a compensation for or, at least, a consideration of these sources of error during analysis of the model results. This article presents a literature review, which firstly synthesises the general mathematical structure of crop models. The main criteria for evaluating crop models are then described. Finally, several methods used for improving models are given. Parameter estimation methods, including frequentist and Bayesian approaches, are presented and data assimilation methods are reviewed. |
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French |
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CropM, ftnotmacsur |
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no |
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MA @ admin @ |
Serial |
4584 |
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