| Climate change impact and adaptation for wheat protein S Asseng, P Martre, A Maiorano, RP Rötter, GJ O’Leary, GJ Fitzgerald, ... Global change biology 25 (1), 155-173, 2019 | 614 | 2019 |
| The uncertainty of crop yield projections is reduced by improved temperature response functions E Wang, P Martre, Z Zhao, F Ewert, A Maiorano, RP Rötter, BA Kimball, ... Nature plants 3 (8), 1-13, 2017 | 367 | 2017 |
| Environmental and economic benefits of variable rate nitrogen fertilization in a nitrate vulnerable zone B Basso, B Dumont, D Cammarano, A Pezzuolo, F Marinello, L Sartori Science of the total environment 545, 227-235, 2016 | 275 | 2016 |
| Global wheat production with 1.5 and 2.0° C above pre‐industrial warming B Liu, P Martre, F Ewert, JR Porter, AJ Challinor, C Müller, AC Ruane, ... Global Change Biology 25 (4), 1428-1444, 2019 | 197 | 2019 |
| Crop model improvement reduces the uncertainty of the response to temperature of multi-model ensembles A Maiorano, P Martre, S Asseng, F Ewert, C Müller, RP Rötter, AC Ruane, ... Field crops research 202, 5-20, 2017 | 186 | 2017 |
| Multimodel ensembles improve predictions of crop–environment–management interactions D Wallach, P Martre, B Liu, S Asseng, F Ewert, PJ Thorburn, ... Global change biology 24 (11), 5072-5083, 2018 | 180 | 2018 |
| Temperature and precipitation effects on wheat yield across a European transect: a crop model ensemble analysis using impact response surfaces N Pirttioja, TR Carter, S Fronzek, M Bindi, H Hoffmann, T Palosuo, ... Climate Research 65, 87-105, 2015 | 177 | 2015 |
| Global wheat head detection 2021: An improved dataset for benchmarking wheat head detection methods E David, M Serouart, D Smith, S Madec, K Velumani, S Liu, X Wang, ... Plant Phenomics, 2021 | 149 | 2021 |
| Adaptation response surfaces for managing wheat under perturbed climate and CO2 in a Mediterranean environment M Ruiz-Ramos, R Ferrise, A Rodríguez, IJ Lorite, M Bindi, TR Carter, ... Agricultural Systems 159, 260-274, 2018 | 129 | 2018 |
| Simulation of maize evapotranspiration: An inter-comparison among 29 maize models BA Kimball, KJ Boote, JL Hatfield, LR Ahuja, C Stockle, S Archontoulis, ... Agricultural and Forest Meteorology 271, 264-284, 2019 | 119 | 2019 |
| The chaos in calibrating crop models: Lessons learned from a multi-model calibration exercise D Wallach, T Palosuo, P Thorburn, Z Hochman, E Gourdain, ... Environmental Modelling & Software 145, 105206, 2021 | 101 | 2021 |
| Soil organic carbon and nitrogen feedbacks on crop yields under climate change B Basso, B Dumont, B Maestrini, I Shcherbak, GP Robertson, JR Porter, ... Agricultural & Environmental Letters 3 (1), 180026, 2018 | 91 | 2018 |
| Advances in crop modeling for a sustainable agriculture G Hoogenboom, CH Porter, KJ Boote, V Shelia, PW Wilkens, U Singh, ... DSSAT Crop Model Ecosyst, 173-216, 2019 | 89* | 2019 |
| Impact of crop residue management on crop production and soil chemistry after seven years of crop rotation in temperate climate, loamy soils MP Hiel, S Barbieux, J Pierreux, C Olivier, G Lobet, C Roisin, S Garré, ... PeerJ 6, e4836, 2018 | 86 | 2018 |
| Parameter identification of the STICS crop model, using an accelerated formal MCMC approach B Dumont, V Leemans, M Mansouri, B Bodson, JP Destain, MF Destain Environmental Modelling & Software 52, 121-135, 2014 | 83 | 2014 |
| Evidence for increasing global wheat yield potential JR Guarin, P Martre, F Ewert, H Webber, S Dueri, D Calderini, ... Environmental Research Letters 17 (12), 124045, 2022 | 79 | 2022 |
| Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change S Fronzek, N Pirttioja, TR Carter, M Bindi, H Hoffmann, T Palosuo, ... Agricultural systems 159, 209-224, 2018 | 78 | 2018 |
| Evaluating the impact of soil conservation measures on soil organic carbon at the farm scale A Pezzuolo, B Dumont, L Sartori, F Marinello, MDA Migliorati, B Basso Computers and Electronics in Agriculture 135, 175-182, 2017 | 66 | 2017 |
| Implications of crop model ensemble size and composition for estimates of adaptation effects and agreement of recommendations A Rodriguez, M Ruiz-Ramos, T Palosuo, TR Carter, S Fronzek, IJ Lorite, ... Agricultural and Forest Meteorology 264, 351-362, 2019 | 60 | 2019 |
| Deep learning for wheat ear segmentation and ear density measurement: From heading to maturity S Dandrifosse, E Ennadifi, A Carlier, B Gosselin, B Dumont, B Mercatoris Computers and Electronics in Agriculture 199, 107161, 2022 | 58 | 2022 |
