An overview of the crop model STICS

By Nadine Brisson, C. Gary, Eric Justes, R. Roche, B. Mary, D. Ripoche, D. Zimmer, J. Sierra, P. Bertuzzi, Philippe Burger and 9 more. 2003

1,147 citations recorded by the source corpus.

Subfields: Ecology, Evolution, Behavior and Systematics, Plant Science, Soil Science

View Paper: https://www.semanticscholar.org/paper/89868fc3deb2a8226e6d983aa1def1ba44cb87a6

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Citations in the corpus

Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science (2017, background): “A number of other cropping and grassland systemmodels have similar components and capabilities (e.g., APSIM, Keating et al., 2003a, 2003b and Holzworth et al., 2014; CROPSYST, Stöckle et al., 2003, 2014; EPIC, Williams et al., 1989; STICS, Brisson et al., 2003 and Bergez et al., 2014; SALUS, Basso a”
Some Parameter Estimation Issues in Functional-Structural Plant Modelling (2011, methodology): “To describe plant growth, crop models or process-based models were first developed [31], [5].”
Maize Radiation Use Efficiency under Optimal Growth Conditions (2005, background): “Growth can be determined ronments (Brisson et al., 2003; Jones and Kiniry, 1986; using net CO2 uptake, total aboveground dry matter, orMuchow et al., 1990).”
Global mapping of Jatropha curcas yield based on response of fitness to present and future climate (2010, methodology): “Crop productivity in response to the environment is traditionally defined from either (1) land suitability models that empirically weigh combinations of crop responses to relevant agroclimatic factors (FAO, 1983, 1985; Sys et al., 1991; Rossiter, 1996) or (2) physically based models such as STICS (B”
Modelling diverse root density dynamics and deep nitrogen uptake—A simple approach (2009, methodology): “, 1991) and a water balance module (Brisson et al., 2003).”
How do various maize crop models vary in their responses to climate change factors? (2014, positive): “(2011) and Chun et al. (2011). With the exception of a few models, this difference suggests that the studied crop model algorithms for CO2 effect on transpiration may be reducing transpiration insufficiently for C4 species (Boote et al.”
The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and Pilot Studies (2013, neutral): “…effects of climate on crop yield include statistical models (e.g., Schlenker et al., 2006; Lobell and Burke, 2010) and process-based dynamic crop growth models (e.g., Keating et al., 2003; Brisson et al., 2003; Jones et al., 2003; van Ittersum and Donatelli, 2003; Challinor et al., 2004).”
Adaptation of the crop model STICS to intercropping. Theoretical basis and parameterisation (2003, positive): “Its novelty is its capability to adapt to various crops [14] (wheat, maize, soybean, sorghum, flax, grassland, tomato, sugar beet, sunflower, pea, rapeseed, banana, sugarcane, carrot, lettuce, etc.).”