The DOI matches its Crossref record; 210 of the 216 references it cites were found in a registry or an index.
The DSSAT cropping system model
Abstract
The decision support system for agrotechnology transfer (DSSAT) has been in use for the last 15 years by researchers worldwide. This package incorporates models of 16 different crops with software that facilitates the evaluation and application of the crop models for different purposes. Over the last few years, it has become increasingly difficult to maintain the DSSAT crop models, partly due to fact that there were different sets of computer code for different crops with little attention to software design at the level of crop models themselves. Thus, the DSSAT crop models have been re-designed and programmed to facilitate more efficient incorporation of new scientific advances, applications, documentation and maintenance. The basis for the new DSSAT cropping system model (CSM) design is a modular structure in which components separate along scientific discipline lines and are structured to allow easy replacement or addition of modules. It has one Soil module, a Crop Template module which can simulate different crops by defining species input files, an interface to add individual crop models if they have the same design and interface, a Weather module, and a module for dealing with competition for light and water among the soil, plants, and atmosphere. It is also designed for incorporation into various application packages, ranging from those that help researchers adapt and test the CSM to those that operate the DSSAT-CSM to simulate production over time and space for different purposes. In this paper, we describe this new DSSAT-CSM design as well as approaches used to model the primary scientific components (soil, crop, weather, and management). In addition, the paper describes data requirements and methods used for model evaluation. We provide an overview of the hundreds of published studies in which the DSSAT crop models have been used for various applications. The benefits of the new, re-designed DSSAT-CSM will provide considerable opportunities to its developers and others in the scientific community for greater cooperation in interdisciplinary research and in the application of knowledge to solve problems at field, farm, and higher levels.
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In the citing paper
“The Cropping System Model (CSM)-CROPGRO-Cotton model (Jones et al., 2003; Pathak et al., 2007) is implemented in the Decision Support System for Agrotechnology Transfer (DSSAT; Hoogenboom et al., 2012).”
From Development and Application of Process-based Simulation Models for Cotton Production: A Review of Past, Present, and Future Directions (2014) · cites this paper as Jones et al., 2003
In the citing paper
“Notably process-based models have previously been used to evaluate the growth, development and yield of annual and perennial crops under a wide range of conditions (Jones et al., 2003;Keating et al., 2003;Stöckle et al., 2003), including climate change projection across the globe (White et al., 2011;Asseng et al., 2013).”
From Intensify production, transform biomass to energy and novel goods and protect soils in Europe—A vision how to mobilize marginal lands (2018) · cites this paper as Jones et al., 2003
Citations
Cites
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Research works printed but not linked: 9
- Boote, K.J., Bennett, J.M., Jones, J.W., Jowers, H.E., 1989. On-farm testing of peanut and soybean models in Florida. ASAE P No. 89-4040. Am. Soc. Agr. Engr. (ASAE), St. Joseph, MI, pp. 54.
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- Zalud, 2001, Estimation of winter wheat nitrogen stress using the CERES crop model, Rostlinna Vyroba, 47, 253
Cited by
Sorted by citations
Rising temperatures reduce global wheat production
Asseng, S., Ewert, F., Martre, P., Rötter, R. P., Lobell, D. B., Cammarano, D., Kimball, B. A., Ottman, M. J., Wall, G. W., White, J. W., et al. (2015) · Nature Climate Change · doi:10.1038/nclimate2470 · Cited by 2,491
Self-citationRosenzweig, C., Elliott, J., Deryng, D., Ruane, A. C., Müller, C., Arneth, A., Boote, K. J., Folberth, C., Glotter, M., Khabarov, N., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1222463110 · Cited by 2,319
Self-citationRemote sensing for agricultural applications: A meta-review
Weiss, M., Jacob, F., & Duveiller, G. (2019) · Remote Sensing of Environment · doi:10.1016/j.rse.2019.111402 · Cited by 1,948
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APSIM – evolution towards a new generation of agricultural systems simulation
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Metadata
- Authors
- Jones, J. W., Hoogenboom, G., Porter, C. H., Boote, K. J., Batchelor, W. D., Hunt, L. A., Wilkens, P. W., Singh, U., Gijsman, A. J., & Ritchie, J. T.
- Affiliations
- University of Florida (US)
- University of Georgia (US)
- Iowa State University (US)
- University of Guelph (CA)
- International Fertilizer Development Center (US)
- Michigan State University (US)
- Corresponding author
- Jones, J.W
- Venue
- European Journal of Agronomy
- Publisher
- Elsevier BV
- Published
- 2003-01
- Volume
- 18
- Issue
- 3-4
- Pages
- 235-265
- ISSN
- 1161-0301 (ISSN-L)
- OpenAlex
- W2158883105
- Cited by
- 4,465
- References
- 216
- Citations by year
- 2026: 349 · 2025: 341 · 2024: 296 · 2023: 286 · 2022: 328 · 2021: 313 · 2020: 329 · 2019: 269 · 2018: 241 · 2017: 254 · 2016: 198 · 2015: 191 · 2014: 190 · 2013: 175 · 2012: 178
- FWCI
- 26.41
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- European Journal of Agronomy (publishedVersion)
- European Journal of Agronomy
- Topics
- Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Climate change impacts on agriculture
- Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Agricultural Productivity and Crop Improvement
- Life Sciences › Agricultural and Biological Sciences › Soil Science › Irrigation Practices and Water Management
- Keywords
- DSSAT, crop growth simulation, modular software design, soil model, model evaluation, agricultural technology transfer, crop yield simulation
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