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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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“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
Crop evapotranspiration : guidelines for computing crop water requirements
Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998) · FAO eBooks · Cited by 20,540
On the Assessment of Surface Heat Flux and Evaporation Using Large-Scale Parameters
Priestley, C. H. B., & Taylor, R. J. (1972) · Monthly Weather Review · doi:10.1175/1520-0493(1972)100 · Cited by 6,545
Model for predicting evaporation from a row crop with incomplete cover
Ritchie, J. T. (1972) · Water Resources Research · doi:10.1029/wr008i005p01204 · Cited by 2,240
Self-citationGuidelines for predicting crop water requirements
Doorenbos, J. (1977) · Medical Entomology and Zoology · Cited by 2,226
Dynamics of C, N, P and S in grassland soils: a model
Parton, W. J., Stewart, J. W., & Cole, C. V. (1988) · Biogeochemistry · doi:10.1007/bf02180320 · Cited by 1,483
Palmer, R. A. (1953) · Science · doi:10.1126/science.118.3075.3 · Cited by 1,354
Stochastic simulation of daily precipitation, temperature, and solar radiation
Richardson, C. W. (1981) · Water Resources Research · doi:10.1029/wr017i001p00182 · Cited by 1,299
A Modeling Approach to Determining the Relationship Between Erosion and Soil Productivity
Williams, J. R., Jones, C., & Dyke, P. T. (1984) · Transactions of the ASAE · doi:10.13031/2013.32748 · Cited by 1,145
CERES-Maize: a simulation model of maize growth and development
Jones, C., Kiniry, J. R., & Dyke, P. T. (1986) · Cited by 1,109
McCown, R. L., Hammer, G., Hargreaves, J. N. G., Holzworth, D. P., & Freebairn, D. M. (1996) · Agricultural Systems · doi:10.1016/0308-521x(94)00055-v · Cited by 967
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.
- Bowen, W.T., Jones, J.W., Thornton P.K., 1992. Crop simulation as a potential tool for evaluating sustainable land management. Utilization of Soil Survey Information for Sustainable Land Use Proceedings: 11–24 July.
- Giraldo, 1998, Adaptation of the DSSAT model for simulation of Brachiaria decumbens production, Pasturas Tropicales, 20, 2
- Hunkár, 1994, Validation of crop simulation model CERES-Maize, Quarterly Journal of Hungarian Meteorology Series, 98, 37
- Jones J.W. Ritchie, J.T., 1991. Crop growth models In: Hoffman, G.J, Howell, T.A., Solomon, K.H. (Eds.), Management of Farm Irrigation Systems, American Society for Agricultural Engineering, pp. 63–89.
- Jones, J.W., Boote, K.J., Hoogenboom, G., Jagtap, S.S., Wilkerson, G.G., 1989. SOYGRO V5.42, Soybean Crop Growth Simulation Model. User's Guide. Fl. Agric. Exp. Sta., Journal No. 8304. University of Florida, Gainesville. pp. 53.
- Paz, 2001, Estimating potential economic return for variable rate management in soybeans, Trans. ASAE, 44, 1335
- Singh, 1999, Soybean (Glycine max) yield prediction from current and historical weather data using CROPGRO model, Indian Journal of Agricultural Sciences, 69, 639
- Zalud, 2001, Estimation of winter wheat nitrogen stress using the CERES crop model, Rostlinna Vyroba, 47, 253
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Fang, H., Liang, S., & Hoogenboom, G. (2011) · International Journal of Remote Sensing · doi:10.1080/01431160903505310 · Cited by 201
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Is soybean yield limited by nitrogen supply?
Menza, N. C. L., Monzón, J. P., Specht, J. E., & Grassini, P. (2017) · Field Crops Research · doi:10.1016/j.fcr.2017.08.009 · Cited by 187
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Zhang, X., Wang, S., Sun, H., Chen, S., Shao, L., & Liu, X. (2013) · European Journal of Agronomy · doi:10.1016/j.eja.2013.05.005 · Cited by 148
Xu, J., Cai, H., Wang, X., Ma, C., Lu, Y., Ding, Y., Wang, X., Chen, H., Wang, Y., & Saddique, Q. (2019) · Agricultural Water Management · doi:10.1016/j.agwat.2019.105904 · Cited by 148
Luquet, D., Dingkuhn, M., Kim, H., Tambour, L., & Clément‐Vidal, A. (2006) · Functional Plant Biology · doi:10.1071/fp05266 · Cited by 148
Mishra, A. K., Ines, A. V. M., Das, N. N., Khedun, C. P., Singh, V. P., Sivakumar, B., & Hansen, J. (2014) · Journal of Hydrology · doi:10.1016/j.jhydrol.2014.10.038 · Cited by 147
From genome to crop: integration through simulation modeling
Hoogenboom, G., White, J. W., & Messina, C. D. (2004) · Field Crops Research · doi:10.1016/j.fcr.2004.07.014 · Cited by 147
Self-citationHerrero, M., Thornton, P. K., Bernués, A., Baltenweck, I., Vervoort, J., van de Steeg, J., Makokha, S., van Wijk, M. T., Ng’ang’a, S. K., Rufino, M. C., et al. (2014) · Global Environmental Change · doi:10.1016/j.gloenvcha.2013.12.008 · Cited by 146
Agricultural investments and hunger in Africa modeling potential contributions to SDG2 – Zero Hunger
Mason-D’Croz, D., Sulser, T. B., Wiebe, K., Rosegrant, M. W., Lowder, S. K., Nin‐Pratt, A., Willenbockel, D., Robinson, S., Zhu, T., Cenacchi, N., et al. (2018) · World Development · doi:10.1016/j.worlddev.2018.12.006 · Cited by 169
A gene-based model to simulate soybean development and yield responses to environment
Messina, C. D., Jones, J. W., Boote, K. J., & Vallejos, C. E. (2006) · Crop Science · doi:10.2135/cropsci2005.04-0372 · Cited by 145
Self-citationDeJonge, K. C., Ascough, J. C., Ahmadi, M., Andales, A. A., & Arabi, M. (2012) · Ecological Modelling · doi:10.1016/j.ecolmodel.2012.01.024 · Cited by 145
Varshney, R. K., Thudi, M., Pandey, M. K., Tardieu, F., Ojiewo, C. O., Vadez, V., Whitbread, A. M., Siddique, K. H. M., Nguyen, H. T., Carberry, P., et al. (2018) · Journal of Experimental Botany · doi:10.1093/jxb/ery088 · Cited by 150
Allometric approach to crop nutrition and implications for crop diagnosis and phenotyping. A review
Lemaire, G., Sinclair, T. R., Sadras, V. O., & Bélanger, G. (2019) · Agronomy for Sustainable Development · doi:10.1007/s13593-019-0570-6 · Cited by 145
Bouma, J., Montanarella, L., & Evanylo, G. K. (2019) · Soil Use and Management · doi:10.1111/sum.12518 · Cited by 152
Liu, H. L., Yang, J., Tan, C. S., Drury, C. F., Reynolds, W. D., Zhang, T. Q., Bai, Y., Jin, J., He, P., & Hoogenboom, G. (2011) · Agricultural Water Management · doi:10.1016/j.agwat.2011.01.017 · Cited by 144
Self-citationClimate change impact on China food security in 2050
Ye, L., Xiong, W., Li, Z., Yang, P., Wu, W., Yang, G., Fu, Y., Zou, J., Chen, Z., Ranst, É. V., et al. (2012) · Agronomy for Sustainable Development · doi:10.1007/s13593-012-0102-0 · Cited by 143
White, J. W., Hoogenboom, G., Stackhouse, P. W., & Hoell, J. M., Jr. (2008) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2008.05.017 · Cited by 143
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Kim, H., Ko, J., Kang, S.-C., & Tenhunen, J. (2012) · Global Change Biology · doi:10.1111/gcb.12047 · Cited by 143
Zhao, C., Liu, B., Xiao, L.-J., Hoogenboom, G., Boote, K., Kassie, B., Pavan, W., Shelia, V., Kim, K. S., Hernández-Ochoa, I., et al. (2019) · European Journal of Agronomy · doi:10.1016/j.eja.2019.01.009 · Cited by 135
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Searchinger, T. D., Estes, L. D., Thornton, P. K., Beringer, T., Notenbaert, A. M. O., Rubenstein, D. I., Heimlich, R. E., Licker, R., & Herrero, M. (2015) · Nature Climate Change · doi:10.1038/nclimate2584 · Cited by 151
Corbeels, M., Chirat, G., Messad, S., & Thierfelder, C. (2016) · European Journal of Agronomy · doi:10.1016/j.eja.2016.02.001 · Cited by 141
Understanding the weather signal in national crop‐yield variability
Frieler, K., Schauberger, B., Arneth, A., Balkovič, J., Chryssanthacopoulos, J. P., Deryng, D., Elliott, J. W., Folberth, C., Khabarov, N., Müller, C., et al. (2017) · Earth s Future · doi:10.1002/2016ef000525 · Cited by 147
Xie, Y., Wang, P., Bai, X., Khan, J., Zhang, S., Li, L., & Wang, L. (2017) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2017.06.015 · Cited by 142
Zheng, B., Biddulph, B., Li, D., Kuchel, H., & Chapman, S. C. (2013) · Journal of Experimental Botany · doi:10.1093/jxb/ert209 · Cited by 140
Hot spots of wheat yield decline with rising temperatures
Asseng, S., Cammarano, D., Basso, B., Chung, U., Alderman, P. D., Sonder, K., Reynolds, M. P., & Lobell, D. B. (2016) · Global Change Biology · doi:10.1111/gcb.13530 · Cited by 143
Noah‐MP‐Crop: Introducing dynamic crop growth in the Noah‐MP land surface model
Liu, X., Chen, F., Barlage, M. J., Zhou, G., & Niyogi, D. (2016) · Journal of Geophysical Research Atmospheres · doi:10.1002/2016jd025597 · Cited by 141
Jin, Z., Azzari, G., & Lobell, D. B. (2017) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2017.08.001 · Cited by 142
Maize systems under climate change in sub-Saharan Africa
Tesfaye, K., Gbegbelegbe, S., Cairns, J. E., Shiferaw, B. A., Prasanna, B. M., Sonder, K., Boote, K. J., Makumbi, D., & Robertson, R. (2015) · International Journal of Climate Change Strategies and Management · doi:10.1108/ijccsm-01-2014-0005 · Cited by 140
Self-citationAttia, A., Rajan, N., Xue, Q., Nair, S. S., Ibrahim, A. M. H., & Hays, D. B. (2015) · Agricultural Water Management · doi:10.1016/j.agwat.2015.11.002 · Cited by 142
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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