Abstract
To ensure agricultural sustainability and desirable environmental outcomes, stakeholders need systems-based model-driven decision support tools. The objective of this study was to develop a global scale web-based geospatial crop modeling application called Food, Agriculture, and Resource Management system (FARMs), to simplify the application of the crop simulation model —Decision Support System for Agrotechnology Transfer (DSSAT) without requiring users to create input weather, climate, and soil files. FARMs was built based on open source Geographic Information System (GIS) technologies and DSSAT to allow for adaptive management through its ability to perform in-season yield predictions for alfalfa and maize, currently. Validation of FARMs against variety trial data in California was acceptable between measured and simulated yields for alfalfa. The work done in this study showed how a complex model like DSSAT can be translated into a useable web-based decision support tool for near-real-time simulation with the help of open-source GIS technologies.
Highlights
There are many crop management and related computer software developed for various purposes
Scientists have developed powerful biophysical or crop simulation model (CSM)s such as Decision Support System for Agrotechnology Transfer (DSSAT) [1,2,3], APSIM [4,5], AQUACROP [6], RZWQM [7], CropSyst [8], and SWAP [9] that are capable of predicting crop yield as affected by genetics, environment, management, and socioeconomics (G × E × M × S) [10] interactions
Running CSM itself can be complicated for some users, especially without science or engineering background
Summary
There are many crop management and related computer software developed for various purposes. CSM usually runs in a desktop environment, which requires users to pre- and postprocess input and output data. Users must prepare weather and soil input data for the field of interest before running a CSM in a desktop environment. It is hard to get the weather and soil data for the specific time and location on many occasions. Even if those data are available, it is time-consuming and labor-intensive to organize the input data into the correct format for each CSM. It is hard to find a CSM with geospatial capabilities to compare output results for multiple fields and crop management scenarios intuitively. Most CSMs are designed to be operated in a forward mode, i.e., cannot be updated or interrupted during the simulation which limits the ability to update the model with new information gathered during the season
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