Author |
Title |
Year |
Publication |
Volume |
Pages |
Tao, F.; Palosuo, T.; Roetter, R.P.; Hernandez Diaz-Ambrona, C.G.; Ines Minguez, M.; Semenov, M.A.; Kersebaum, K.C.; Cammarano, D.; Specka, X.; Nendel, C.; Srivastava, A.K.; Ewert, F.; Padovan, G.; Ferrise, R.; Martre, P.; Rodriguez, L.; Ruiz-Ramos, M.; Gaiser, T.; Hohn, J.G.; Salo, T.; Dibari, C.; Schulman, A.H. |
Why do crop models diverge substantially in climate impact projections? A comprehensive analysis based on eight barley crop models |
2020 |
Agricultural and Forest Meteorology |
281 |
107851 |
Yin, X.; Olesen, J.E.; Wang, M.; Öztürk, I.; Zhang, H.; Chen, F. |
Impacts and adaptation of the cropping systems to climate change in the Northeast Farming Region of China |
2016 |
European Journal of Agronomy |
78 |
60-72 |
Sanna, M.; Bellocchi, G.; Fumagalli, M.; Acutis, M. |
A new method for analysing the interrelationship between performance indicators with an application to agrometeorological models |
2015 |
Environmental Modelling & Software |
73 |
286-304 |
Schauberger, B.; Rolinski, S.; Müller, C. |
A network-based approach for semi-quantitative knowledge mining and its application to yield variability |
2016 |
Environmental Research Letters |
11 |
123001 |
Wallach, D.; Nissanka, S.P.; Karunaratne, A.S.; Weerakoon, W.M.W.; Thorburn, P.J.; Boote, K.J.; Jones, J.W. |
Accounting for both parameter and model structure uncertainty in crop model predictions of phenology: A case study on rice |
2016 |
European Journal of Agronomy |
|
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