Simulation of spring barley yield in different climatic zones of Northern and Central Europe: A comparison of nine crop models

By R. Rötter, T. Palosuo, K. Kersebaum, Carlos Angulo, M. Bindi, Frank Ewert, R. Ferrise, P. Hlavinka, M. Moriondo, Claas Nendel and 5 more. 2012

333 citations recorded by the source corpus.

Subfields: Agronomy and Crop Science, Ecology, Evolution, Behavior and Systematics, Plant Science

View Paper: https://www.semanticscholar.org/paper/c28fa5f06c5e06784ec7a7fe131596e6354344a6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Agronomy and Crop Science

1. Pierre Martre
2. John R. Porter
3. Kenneth J. Boote
4. James W. Jones
5. Frank Ewert
6. Jerry L. Hatfield
7. Mikhail A. Semenov
8. Christoph Müller

In Ecology, Evolution, Behavior and Systematics

1. Frank Ewert
2. Kenneth J. Boote
3. James W. Jones
4. Senthold Asseng
5. John R. Porter
6. Hendrik Boogaard
7. Jerry L. Hatfield
8. Soo-Hyung Kim

In Plant Science

1. James W. Jones
2. Kenneth J. Boote
3. Pierre Martre
4. John R. Porter
5. Christoph Müller
6. Jerry L. Hatfield
7. Frank Ewert
8. Mikhail A. Semenov

Citations in the corpus

• Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change (2017, neutral): “These models can di ff er greatly in their treatment of key processes and hence in their response to environmental conditions (Asseng et al., 2013; Palosuo et al., 2011; Rötter et al., 2012).”
• How do various maize crop models vary in their responses to climate change factors? (2014, background): “…crop models for response to climatic factors have already been explored for wheat and barley (Diekkr€uger et al., 1995; Goudriaan, 1996; Palosuo et al., 2011; R€otter et al., 2012; Asseng et al., 2013), but similar studies are scarce for maize in spite of the great economic importance of that crop.”
• Crop modelling for integrated assessment of risk to food production from climate change (2015, methodology): “The use of dynamic, process-based crop and cropping system simulation models for climate change impact and risk assessment studies has become increasingly important (Tubiello and Ewert, 2002; Challinor et al., 2009a; White et al., 2011; R€otter et al., 2012a; Angulo et al., 2013b).”
• Designing future barley ideotypes using a crop model ensemble (2017, methodology): “The strengths of inter-model comparison and nsemble modelling have been demonstrated in many studies (e.g., alosuo et al., 2011; Rötter et al., 2012; Asseng et al., 2013, 2015; assu et al., 2014; Li et al., 2015; Martre et al., 2015b).”
• Testing farm management options as climate change adaptation strategies using the MONICA model (2014, background): “, 2011) and spring barley (Rötter et al., 2012).”