DSSAT (Decision Support System for Agrotechnology Transfer) model

The Decision Support System for Agrotechnology Transfer (DSSAT) is a software application program that comprises crop simulation models for over 42 crops (as of Version 4.7.5) as well as tools to facilitate effective use of the models.

AgricultureCropDecision

Contributor(s)

Initial contribute: 2019-07-16

Authorship

:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
Is authorship not correct? Feed back

Classification(s)

Method-focused categoriesProcess-perspectiveBiological process calculation

Detailed Description

English {{currentDetailLanguage}} English

Quoted from: https://dssat.net/models-overview/

Crop models calculate expected growth and development based on equations that describe how a crop, as community of plants, respond to soil and weather conditions. At their simplest level of interpretation, the equations used in a model are a set of differential equations representing rates of growth or development. Numerical integration over time, typically with daily or hourly time steps, allows estimation of growth, development, and water and nutrient levels. The equations are based on information from crop physiology, soil science, meteorology and other fields.

The models provided in DSSAT deal primarily with annual crops including wheat, rice, maize and various grain legumes but also include herbaceous perennials such as forage legumes and grasses. Besides crop growth and development, the models simulate water and nutrient dynamics in the soil and crop, so processes such as leaching, organic matter decomposition, and runoff are also considered. The level of process details varies greatly, and in many cases, users may select among model options, allowing the user to assess how different assumptions affect simulations.

Model applications range from real-time decision support for crop management to assessing the potential impact of climate change on global food security. Crop models are also invaluable as heuristic devices that help identify research problems where our current knowledge has limits and further research is needed. The ability of crop models to simulate how different weather years or soil conditions affect crop performance make models especially useful in research involving climatic uncertainty or geospatial variation. Recent advances in field phenomics and crop genomics are opening opportunities for crop models to support research in fundamental plant science.

Because the quality of simulation results depends heavily on the data inputs, DSSAT includes tools to assist modelers in organizing input data for crop management, soils and weather. An especially challenging set of inputs are the genotype-specific parameters (GSPs) used to quantify how one cultivar differs from another. GSPs are most often estimated through calibration to measurements from field trials, and DSSAT provides tools both to organize data used for calibration and to estimate required GSPs.

 

The Cropping System Model (CSM) is structured in a modular format in which components separate along scientific discipline lines and have interfaces which allow replacement or addition of modules. CSM now incorporates all crop models as modules using a single soil module and a single weather module. The new cropping system model now contains models of 40+ crops derived from the original SOYGRO, PNUTGRO, CERES-Maize, and CERES-Wheat crop growth models.

The following schematic illustrates the connection between the primary and secondary modules of the CSM. The main program controls all the timing for the model, while the Land Unit module is used to control processing and data transfer between all primary modules.

DSSAT Cropping System Model schematic

 

Primary Modules

Management module

Soil module

Weather module

Soil-Plant-Atmosphere module

Plant module

模型元数据

{{htmlJSON.HowtoCite}}

University of Florida (UF), Gainesville, Florida, USA, International Fertilizer Development Center (IFDC), Muscle Shoals, Alabama, USA, Agriculture and Agri-Food Canada (AAFC), Ottawa, Ontario, Canada, Auburn University (AU), Auburn, Alabama, USA, Brazilian Agricultural Research Corporation (EMBRAPA), Brasília, Federal District, Brazil, International Center for Tropical Agriculture (CIAT), Cali, Colombia, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India, International Food Policy Research Institute (IFPRI), Washington, District of Columbia, USA, International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico, University of Sao Paulo – ESALQ, Piracicaba, Sao Paulo, Brazil, Michigan State University (MSU), East Lansing, Michigan, USA, Oklahoma State University (OSU), Stillwater, Oklahoma, USA, Polytechnic University of Madrid (UPM), Madrid, Spain, Seoul National University (SNU), Seoul, Republic of Korea, South African Sugarcane Research Institute (SASRI), Mount Edgecombe, South Africa, Texas A&M University (TAMU), College Station, Texas, USA, University of California Davis (UC Davis), Davis, California, USA, University of Hawaii (UH), Honolulu, Hawaii, USA, University of Kentucky (UK), Lexington, Kentucky, USA, University of Passo Fundo (UPF), Passo Fundo, Rio Grande do Sul, Brazil, USDA – Agricultural Research Service, US Arid Land Agricultural Research Center, Maricopa, USA (2019). DSSAT (Decision Support System for Agrotechnology Transfer) model, Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/7115006e-9a0c-4bc5-87d7-fe780724a6d1
{{htmlJSON.Copy}}

Contributor(s)

Initial contribute : 2019-07-16

{{htmlJSON.CoContributor}}

Authorship

:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
:  
View
Is authorship not correct? Feed back

QR Code

×

{{curRelation.overview}}
{{curRelation.author.join('; ')}}
{{curRelation.journal}}









{{htmlJSON.RelatedItems}}

{{htmlJSON.LinkResourceFromRepositoryOrCreate}}{{htmlJSON.create}}.

Drop the file here, orclick to upload.
Select From My Space
+ add

{{htmlJSON.authorshipSubmitted}}

Cancel Submit
{{htmlJSON.Cancel}} {{htmlJSON.Submit}}
{{htmlJSON.Localizations}} + {{htmlJSON.Add}}
{{ item.label }} {{ item.value }}
{{htmlJSON.ModelName}}:
{{htmlJSON.Cancel}} {{htmlJSON.Submit}}
名称 别名 {{tag}} +
系列名 版本号 目的 修改内容 创建/修改日期 作者
摘要 详细描述
{{tag}} + 添加关键字
* 时间参考系
* 空间参考系类型 * 空间参考系名称

起始日期 终止日期 进展 开发者
* 是否开源 * 访问方式 * 使用方式 开源协议 * 传输方式 * 获取地址 * 发布日期 * 发布者



编号 目的 修改内容 创建/修改日期 作者





时间分辨率 时间尺度 时间步长 时间范围 空间维度 格网类型 空间分辨率 空间尺度 空间范围
{{tag}} +
* 类型
图例


* 名称 * 描述
示例描述 * 名称 * 类型 * 值/链接 上传


{{htmlJSON.Cancel}} {{htmlJSON.Submit}}
Title Author Date Journal Volume(Issue) Pages Links Doi Operation
{{htmlJSON.Cancel}} {{htmlJSON.Submit}}
{{htmlJSON.Add}} {{htmlJSON.Cancel}}

{{articleUploading.title}}

Authors:  {{articleUploading.authors[0]}}, {{articleUploading.authors[1]}}, {{articleUploading.authors[2]}}, et al.

Journal:   {{articleUploading.journal}}

Date:   {{articleUploading.date}}

Page range:   {{articleUploading.pageRange}}

Link:   {{articleUploading.link}}

DOI:   {{articleUploading.doi}}

Yes, this is it Cancel

The article {{articleUploading.title}} has been uploaded yet.

OK
{{htmlJSON.Cancel}} {{htmlJSON.Confirm}}
gtZta.NVIuqd