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Bruno Basso

Showing results (41-50 of 56) with videos related to

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Scientific Reports|July 11, 2025
A multi model ensemble reveals net climate benefits from regenerative practices in US Midwest croplandsBruno Basso, Tommaso Tadiello, Neville Millar, et al.
Global Change Biology|January 8, 2014
How do various maize crop models vary in their responses to climate change factors?Simona Bassu, Nadine Brisson, Jean-Louis Durand, et al.
Global Change Biology|October 29, 2017
Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N<sub>2</sub> O emissionsFiona Ehrhardt, Jean-François Soussana, Gianni Bellocchi, et al.
Global Change Biology|February 3, 2026
Beyond Climate Change: The Role of Integrated Soil Fertility Management for Sustaining Future Maize Yield in Sub-Saharan AfricaAntoine Couëdel, Gatien N Falconnier, Myriam Adam, et al.
Nature Food|June 6, 2025
Gaps and strategies for accurate simulation of waterlogging impacts on crop productivityMargarita Garcia-Vila, Murilo Dos Santos Vianna, Matthew Tom Harrison, et al.
Global Change Biology|October 21, 2014
Multimodel ensembles of wheat growth: many models are better than onePierre Martre, Daniel Wallach, Senthold Asseng, et al.
Global Change Biology|July 29, 2018
Multimodel ensembles improve predictions of crop-environment-management interactionsDaniel Wallach, Pierre Martre, Bing Liu, et al.
Journal of Experimental Botany|June 21, 2022
Simulation of winter wheat response to variable sowing dates and densities in a high-yielding environmentSibylle Dueri, Hamish Brown, Senthold Asseng, et al.
Global Change Biology|July 7, 2020
Modelling climate change impacts on maize yields under low nitrogen input conditions in sub-Saharan AfricaGatien N Falconnier, Marc Corbeels, Kenneth J Boote, et al.
Nature Plants|August 4, 2017
Erratum: The uncertainty of crop yield projections is reduced by improved temperature response functionsEnli Wang, Pierre Martre, Zhigan Zhao, et al.
Pageof 6

Showing results (41-50 of 56) with videos related to

Sort By:
Pageof 6
Scientific Reports|July 11, 2025
A multi model ensemble reveals net climate benefits from regenerative practices in US Midwest croplandsBruno Basso, Tommaso Tadiello, Neville Millar, et al.
Global Change Biology|January 8, 2014
How do various maize crop models vary in their responses to climate change factors?Simona Bassu, Nadine Brisson, Jean-Louis Durand, et al.
Global Change Biology|October 29, 2017
Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N<sub>2</sub> O emissionsFiona Ehrhardt, Jean-François Soussana, Gianni Bellocchi, et al.
Global Change Biology|February 3, 2026
Beyond Climate Change: The Role of Integrated Soil Fertility Management for Sustaining Future Maize Yield in Sub-Saharan AfricaAntoine Couëdel, Gatien N Falconnier, Myriam Adam, et al.
Nature Food|June 6, 2025
Gaps and strategies for accurate simulation of waterlogging impacts on crop productivityMargarita Garcia-Vila, Murilo Dos Santos Vianna, Matthew Tom Harrison, et al.
Global Change Biology|October 21, 2014
Multimodel ensembles of wheat growth: many models are better than onePierre Martre, Daniel Wallach, Senthold Asseng, et al.
Global Change Biology|July 29, 2018
Multimodel ensembles improve predictions of crop-environment-management interactionsDaniel Wallach, Pierre Martre, Bing Liu, et al.
Journal of Experimental Botany|June 21, 2022
Simulation of winter wheat response to variable sowing dates and densities in a high-yielding environmentSibylle Dueri, Hamish Brown, Senthold Asseng, et al.
Global Change Biology|July 7, 2020
Modelling climate change impacts on maize yields under low nitrogen input conditions in sub-Saharan AfricaGatien N Falconnier, Marc Corbeels, Kenneth J Boote, et al.
Nature Plants|August 4, 2017
Erratum: The uncertainty of crop yield projections is reduced by improved temperature response functionsEnli Wang, Pierre Martre, Zhigan Zhao, et al.
Pageof 6