The DSSAT cropping system model

By James W. Jones, Gerrit Hoogenboom, Cheryl H. Porter, Kenneth J. Boote, W. Batchelor, L. Hunt, P. Wilkens, U. Singh, A. J. Gijsman, J. Ritchie. 2003

4,135 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/e59f56e30f1eb7578a8e2ea1140c0765ddb1e024

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In Ecology, Evolution, Behavior and Systematics

In Plant Science

Citations in the corpus

Crop yield gaps: their importance, magnitudes, and causes. (2009, neutral): “Less sophisticated models simplify simulation of net assimilation by using a standard value for radiation-use efficiency that accounts for both photosynthesis and respiration (25); more sophisticated models simulate both photosynthesis and respiration directly (26).”
nasapower: A NASA POWER Global Meteorology, Surface Solar Energy and Climatology Data Client for R (2018, methodology): “…get_power() into a function that generates and locally saves a text file in the International Consortium for Agricultural Systems Applications (ICASA) format for use in the Decision Support System for Agrotechnology Transfer (DSSAT) framework (G. Hoogenboom et al., 2017; J. W. Jones et al., 2003).”
Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison (2013, methodology): “Site-based models were developed to simulate processes at the field scale, and include dynamic interactions among crop, soil, atmosphere, and management components (2, 20, 30).”
Resilience in Agriculture through Crop Diversification: Adaptive Management for Environmental Change (2011, methodology): “At the farm field level, techniques such as crop modeling (e.g., Decision Support System for Agrotechnology Transfer [Jones et al. 2003], Agricultural Production Systems Simulator [Keating et al. 2003]) allow researchers to simulate crop mixtures within a specific regional setting in order to model…”
Physiological and management factors contributing to soybean potential yield (2015, methodology): “023 (Jones et al., 2003) was also used to simulate soybean yield for the environmental conditions in Fayetteville.”
Variability in regional wheat yields as a function of climate, soil and economic variables: Assessing the risk of confounding (2005, background): “Considerable progress has been made in the past decades to improve process-based modeling of crop productivity at the plot and field scale (Brisson et al., 2003; Jamieson et al., 1998; Jones et al., 2003; Keating et al., 2003; Stockle et al., 2003; van Ittersum et al., 2003).”
Modelling the impacts of pests and diseases on agricultural systems (2017, methodology): “They may consist of generic crop simulators such as CropSyst (Stöckle et al., 2003) or STICS (Brisson et al., 2003), or of platforms which share parts of the simulation engine (i.e., modelling approaches) and retain specific modules for crops, such as DSSAT (Jones et al., 2003) or APSIM (Brown et al”
A simulation model of cereal-legume intercropping systems for semi-arid regions I. Model development (2005, background): “Many crop models have been developed for monoculture production systems (Jones et al., 2003; Keating et al., 2003; Van Ittersum et al., 2003).”