Methodology for the use of DSSAT models for precision agriculture decision support

被引：103

作者：

Thorp, Kelly R. ^{[2
]}

DeJonge, Kendall C. ^{[3
]}

Kaleita, Amy L. ^{[1
]}

Batchelor, William D. ^{[4
]}

Paz, Joel O. ^{[5
]}

机构：

[1] Iowa State Univ, Dept Agr & Biosyst Engn, Ames, IA 50011 USA

[2] ARS, USDA, Maricopa, AZ USA

[3] USA, Corps Engineers, Omaha, NE USA

[4] Mississippi State Univ, Mississippi State, MS 39762 USA

[5] Univ Georgia, Griffin, GA USA

来源：

COMPUTERS AND ELECTRONICS IN AGRICULTURE | 2008年 / 64卷 / 02期

关键词：

Precision farming; Crop models; Prescriptions; DSSAT; Decision support system;

D O I：

10.1016/j.compag.2008.05.022

中图分类号：

S [农业科学];

学科分类号：

09 ;

摘要：

A prototype decision support system (DSS) called Apollo was developed to assist researchers in using the Decision Support System for Agrotechnology Transfer (DSSAT) crop growth models to analyze precision farming datasets. Because the DSSAT models are written to simulate crop growth and development within a homogenous unit of land, the Apollo DSS has specialized functions to manage running the DSSAT models to simulate and analyze spatially variable land and management. The DSS has modules that allow the user to build model input files for spatial simulations across predefined management zones, calibrate the models to simulate historic spatial yield variability, validate the models for seasons not used for calibration, and estimate the crop response and environmental impacts of nitrogen, plant population, cultivar, and irrigation prescriptions. This paper details the functionality of Apollo, and presents the results of an example application. (C) 2008 Elsevier B.V. All rights reserved.

引用

页码：276 / 285

页数：10

共 25 条

[1] The impact of climate variability and change on crop yield in Bulgaria [J].