Agriculture Reference
In-Depth Information
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Daily variables computed each day.
•
Yearly or annual variables provided an annual summary of values accumulated
throughout the calendar year.
•
Harvest variables provide harvest yield and relevant crop and soil conditions at
harvest time accumulated throughout the growing season.
Output Time Step
The user may restrict the amount of information printed in the daily report by
specifying a time step interval.
Limitations/Shortcomings
No specific limitations are documented. CropSyst does not handle leap year. It is
not tested in case of vertisol.
10.3.5 Decision Support Model
In developing or developed countries, detailed and long-term field experiments are
often difficult to conduct due to financial or personnel limitations. Decision support
models can provide effective information by extrapolating field experimental results
to a range of production scenarios than is possible with field trials, reducing the
amount of repetitive, laborious and time-consuming experimentation. For example,
the effects of soil types and seasons, alternative production with direct reference to
the farmers' resource base, sustainability, and long-term suitability of production
system, can all be studied. By doing so, it can help to identify knowledge gaps, gain
insight into situations where experimental results are lacking or are incomplete. This
in turn may help to develop new or refine existing fertilizer recommendations for a
wide range of production conditions.
10.3.5.1 DSSAT
The Decision Support System for Agrotechnology Transfer (DSSAT) (Tsuji et al.,
agement options. It has been widely used in both developed and developing
countries. The model handles management strategies that involve crop rotations,
irrigation, fertilization, and organic applications. The DSSAT contains various sub-
models. The CERES-Wheat within DSSAT can simulate the main process of crop
growth and development such as timing of phenological events, the development of
canopy to intercept photosynthetically active radiation, and dry matter accumula-
tion. It allows the inclusion of cultivar-specific information that makes it possible
to predict the cultivar variations in plant ontogeny, yield component characteristics
and their interactions with weather. The biomass calculated is partitioned between
leaves, stems, roots, ears and grains. The proportion partitioned to each organ is
determined by the stage of development and growing conditions, modified when
deficiencies of water and nutrient supplies occur. Crop yields are determined as a
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