Agriculture Reference
In-Depth Information
of uncertainty in yield simulations. A correction procedure based on the extent of
variation in plant stand uniformity or dominant plant density may be necessary.
Correction also is required to compensate for yield loss from plants missing in a
population; to some extent, neighboring plants can compensate for missing plants
because they have more space to intercept light. Pommel and Bonhomme (1998)
demonstrated the degree of compensation and losses from irregular stands in corn.
Summary
Simulation models are important for providing producers and policy makers with
better decision-making capabilities. By predicting the response of different sus-
tainability indicators to changes in crop management and climate, models can
provide much needed information for designing sustainable cropping systems and
landscapes. Functional models are particularly useful in that they integrate crop
growth and yield with environmental responses such as nitrate leaching, carbon
sequestration, erosion, and nitrous oxide emissions. It would be impossible for a
single model to address all the issues regarding sustainable crop productivity or
meet the goals of every researcher, planner, or policy maker. However, based on
the successes of models like DSSAT, CENTURY, SALUS, and EPIC—along with
continuing technological improvements—it is reasonable to expect development of
more useful Decision Support System models to meet a growing range of demands.
SALUS is promising because it has a crop model with several years of testing and
is coupled with tested conservative simulations of soil C, N, and P models, allowing
users to account for the impact of agronomic management on crop net primary pro-
ductivity and on the environment. It also has tested capability to simulate climate
change impact on production and the environment. The coupling with TERRAE
makes SALUS a unique system with the capabilities of simulating the effects of
topography and terrain attributes on water routing across the landscape.
References
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Allmaras, R.  R., E. A.  Hallauer, W. W.  Nelson, and S. D.  Evans. 1977. Surface energy
balance and soil thermal property modifications by tillage induced soil structure.
Technical Bulletin 306-1977, Minnesota Agricultural Experiment Station, University
of Minnesota, Minneapolis, Minnesota, USA.
Basso, B. 2000. Digital terrain analysis and simulation modeling to assess spatial variability
of soil water balance and crop production. Dissertation, Michigan State University, East
Lansing, Michigan, USA.
Basso, B., M. Bertocco L. Sartori, and E. C. Martin. 2007. Analyzing the effects of climate
variability on spatial pattern of yield in a maize-wheat-soybean rotation. European
Journal of Agronomy 26:82-91.
Basso, B., D. Cammarano, A. Troccoli, D. Chen, and J. T. Ritchie. 2010. Long-term wheat
response to nitrogen in a rainfed Mediterranean environment: field data and simulation
analysis. European Journal of Agronomy 33:132-138.
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