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13
Jun

DSSAT & MWCropDSS 2018 International Training Program

The DSSAT and MWCropDSS 2018 International Training Program entitled “Efficient and precision agricultural resource utilization under changes with simulation models and GIS” will be held from August 27 through September 1, 2018 at Chiang Mai University in Chiang Mai, Thailand. This workshop is jointly presented by Chiang Mai University, The University of Florida, the DSSAT […]

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21
May

DSSAT 2018 International Training Program at the University of Georgia

Agricultural scientists from across the world met on the University of Georgia Griffin Campus from May 14-19, 2018 to learn about the latest Version 4.7.2 of the DSSAT computer software program. The Decision Support System for Agrotechnology Transfer (DSSAT) helps researchers predict the growth and yield of various crops in response to the genetics, weather […]

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27
Apr

CRAFT: A New Spatial Yield Forecasting Tool

The CCAFS Regional Agricultural Forecasting Toolbox (CRAFT) is a software platform designed for yield forecasting at spatial resolutions of either 5 or 30 arc-minutes using an ensemble modeling approach. Currently the DSSAT, APSIM, and SARRA-H crop simulation models have been implemented for nine important food and feed crops using the AgMIP IT tools. CRAFT was […]

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13
Apr

New Perennial Forage Model in DSSAT 4.7

We are pleased to announce the release of the CSM-CROPGRO-Perennial-Forage model in DSSAT Version 4.7, complete with species adaptations and data files for three perennial forages:  Brachiaria brizantha Stapf cv. Marandu, ‘Tifton 85’ bermudagrass (Cynodon spp.), and alfalfa (Medicago sativa L.) cv. Aragón. The CROPGRO Perennial Forage Model (CROPGRO-PFM) was developed from the annual crop […]

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12
Apr

DSSAT 2018 @ Indonesia

A DSSAT training workshop was held from April 9 through April 13, 2018 at the Training Center of Pt. Great Giant Pineapple, Terbanggi Besar Km 77, Lampung Tengah, Indonesia. The workshop was attended by 21 participants who were introduced to an updated version of the ALOHA-Pineapple model of DSSAT Version 4.7, with specific applications as […]

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23
Mar

DSSAT 2018 @ Tunisia

A DSSAT International Training Program was held from March 19 through March 24, 2018 at Hôtel du Parc, Tunis, Tunisia. The workshop was financially sponsored by the Bundesanstalt für Geowissenschaften und Rohstoffe (BGR) in Hannover, Germany as part of the Coopération régionale pour une Gestion Durable des Ressources en Eau au Maghreb Project. The workshop […]

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05
Mar

Ongoing Improvements and Applications of the CERES-Rice Model

Rice is the most important cereal crop, and it is grown in a wide range of agro-environments, from temperate to tropical regions. It is also highly vulnerable to climatic variability and has a very low nutrient-use efficiency. Crop simulation models are an attractive option for understanding and predicting the effect of the multitude of factors and […]

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27
Feb

DSSAT 2018 IITA International Training Program

Decision Support for Agrotechnology Transfer (DSSAT) Team Leader and Facilitator, Gerrit Hoogenboom, led a team of DSSAT experts from the University of Florida on a 5-day international training program in IITA, Ibadan. The training titled: “Assessing crop production, nutrient management, climatic risk and environmental sustainability with simulation models,” was held from 26 February to 2 […]

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25
Jan

UF researchers are trying to grow potatoes and pineapples on a computer

UF researchers are discovering ways to efficiently use resources to provide for the world’s increasing population by growing digital crops. UF’s Institute of Food and Agricultural Sciences researchers, with the help of various fundings, have discovered new advances in precision agriculture, an interdisciplinary approach to farming that uses technology to form digital simulations of crop […]

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19
Jan

[Q] Soil layer options

There are 3 methods of dealing with soil layers in DSSAT, controlled by MESOL in simulation controls: MESOL = 1: old DSSAT method of forcing soil layer thicknesses to be 5, 10, 15, 15, 15, 30, 30, 30, 60, 60, 60 cm thick. Soil properties are blended when user input layers are forced to standard […]

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