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Author Dumont, B.
Title Uncertainty linked to crop modelling in order to develop decision support tools Type Book Whole
Year 2014 Publication Abbreviated Journal
Volume Issue Pages 193 pp
Keywords
Abstract
Address
Corporate Author Thesis (down) Ph.D. thesis
Publisher Université de Liège Place of Publication Liège Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title PhD
Series Volume PhD Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes CropM Approved no
Call Number MA @ admin @ Serial 5154
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Author Mansouri, M.; Dumont, B.; Destain, M.-F.
Title Predicting Grain Protein Content of Winter Wheat Type Conference Article
Year 2014 Publication Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address
Corporate Author Thesis (down)
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference 22nd European Symposium on Artificial Networks, Computational Intelligence and Machine Learning. Bruges, Belgium, 2014-04-23 to 2014-04-25
Notes Approved no
Call Number MA @ admin @ Serial 2631
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Author Mansouri, M.; Dumont, B.; Destain, M.-F.
Title Bayesian methods for predicting and modelling winter wheat biomass Type Conference Article
Year 2014 Publication Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address
Corporate Author Thesis (down)
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference MACSUR CropM International Symposium and Workshop: Modelling climate change impacts on crop production for food security, Oslo, Norway, 2014-02-10 to 2014-02-12
Notes Approved no
Call Number MA @ admin @ Serial 2629
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Author Mansouri, M.; Dumont, B.; Destain, M.-F.
Title Bayesian methods for predicting LAI and soil moisture Type Conference Article
Year 2012 Publication Abbreviated Journal
Volume Issue Pages
Keywords CropM
Abstract
Address
Corporate Author Thesis (down)
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference 11th International Conference on Precision Agriculture. Indianapolis (USA), 2012-07-15 to 2012-07-18
Notes Approved no
Call Number MA @ admin @ Serial 2627
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Author Maiorano, A.; Martre, P.; Asseng, S.; Ewert, F.; Müller, C.; Rötter, R.P.; Ruane, A.C.; Semenov, M.A.; Wallach, D.; Wang, E.; Alderman, P.D.; Kassie, B.T.; Biernath, C.; Basso, B.; Cammarano, D.; Challinor, A.J.; Doltra, J.; Dumont, B.; Rezaei, E.E.; Gayler, S.; Kersebaum, K.C.; Kimball, B.A.; Koehler, A.-K.; Liu, B.; O’Leary, G.J.; Olesen, J.E.; Ottman, M.J.; Priesack, E.; Reynolds, M.; Stratonovitch, P.; Streck, T.; Thorburn, P.J.; Waha, K.; Wall, G.W.; White, J.W.; Zhao, Z.; Zhu, Y.
Title Crop model improvement reduces the uncertainty of the response to temperature of multi-model ensembles Type Journal Article
Year 2016 Publication Field Crops Research Abbreviated Journal Field Crops Research
Volume 202 Issue Pages 5-20
Keywords Impact uncertainty; High temperature; Model improvement; Multi-model ensemble; Wheat crop model
Abstract To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles (MMEs) have been suggested. Model improvements can improve the accuracy of simulations and reduce the uncertainty of climate change impact assessments. Furthermore, they can reduce the number of models needed in a MME. Herein, 15 wheat growth models of a larger MME were improved through re-parameterization and/or incorporating or modifying heat stress effects on phenology, leaf growth and senescence, biomass growth, and grain number and size using detailed field experimental data from the USDA Hot Serial Cereal experiment (calibration data set). Simulation results from before and after model improvement were then evaluated with independent field experiments from a CIMMYT world-wide field trial network (evaluation data set). Model improvements decreased the variation (10th to 90th model ensemble percentile range) of grain yields simulated by the MME on average by 39% in the calibration data set and by 26% in the independent evaluation data set for crops grown in mean seasonal temperatures >24 °C. MME mean squared error in simulating grain yield decreased by 37%. A reduction in MME uncertainty range by 27% increased MME prediction skills by 47%. Results suggest that the mean level of variation observed in field experiments and used as a benchmark can be reached with half the number of models in the MME. Improving crop models is therefore important to increase the certainty of model-based impact assessments and allow more practical, i.e. smaller MMEs to be used effectively.
Address 2016-09-13
Corporate Author Thesis (down)
Publisher Place of Publication Editor
Language Language Summary Language Newsletter July 2016 Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0378-4290 ISBN Medium Article
Area CropM Expedition Conference
Notes CropMwp;wos; ft=macsur; wsnot_yet; Approved no
Call Number MA @ admin @ Serial 4776
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