Every day we are
faced with situations that require us to make decisions for the best way
to handle and solve them. There are many factors one must take into
consideration when solving a problem. You must compile all useful
information to identify and solve problems and make decisions. In a
large corporation this could be nearly impossible for a person to do
alone and the amount of manpower spent on this process would be immense.
Today there is specific software designed to assist organizations with
the steps involved in making decisions and solving problems. “A
decision support system (DSS) is an organized collection of people,
procedures, software, databases, and devices used to help make decisions
that solve problems”. [1] DSSs are also used in many organizations
such as healthcare, law enforcement, nonprofit organizations and
government. A growing area of DSS application, concepts, principles, and
techniques is in agricultural production.
Decision Support System for Agrotechnology Transfer (DSSAT) is a software application program
“that comprises crop simulation models for over 28 crops (as of v4.5).
DSSAT uses data base management programs for soil, weather, and crop
management and experimental data, and by utilities and application
programs”. The system allows uses to create crop simulation models that
can mimic growth, development and yield as a function of the
soil-plant-atmosphere dynamics, and they have been used for many
applications ranging from on-farm and precision management to regional
assessments of the impact of climate variability and climate change.
This program has been in use for more than 20 years by researchers,
educators, consultants, extension agents, growers, and policy and
decision makers in over 100 countries worldwide. [2] This system is
important because the crop models can predict crop yield and resource
dynamics (water, nitrogen) as well as an economic component that
calculates gross margins based harvested yield and byproducts, the price
of the harvested products, and input costs. Agriculture is an important
business and farms are a huge investment in both time and money. This
program allows for the users ie farmers to predict what are the best
crops to grow and predict what their profits can be. Also on the flip
side, these models can help determine whether it is even a good idea for
the farms to plant crops in the first place.
The federal states
of Germany have installed a national DSS for agricultural production.
The program titled ZEPP (Central Institution for Decision Support
Systems and Programs in Crop Protection) guarantees a permanent
supply of meteorological data, organizes and co-ordinates trials,
incorporates scientific progress into the existing DSSs and, in close
co-operation with universities and federal research stations, develops
new systems for important pests. [3] The goal of the ZEPP is to “develop,
collect and examine existing forecasting and simulation models for
important agricultural and horticultural pests and diseases and to adapt
these models for practical use”. DSS are employed for the estimation of
disease/pest risk, the necessity for pesticide treatments, forecast of
the optimal timing for field assessments, forecast of the optimal timing
for pesticide treatments and recommendation of appropriate pesticides
[4] Disease and pest can completely wipe out a crop and destroy the
land that it invades. This DDS allows the farmers to predict which
infestation they should worry about and the proper course of action to
take to prevent serious loss to there crops.
Decision support systems
gather and present data from a wide range of sources for a wide range
of organizations. DSS applications help people make decisions based on
data that is collected. Rather than just relying on a database, which is
a single information resource, DDSs use a combination of integrated
resources that work together to solve a problem. In the
agricultural sector, the use and implementation of DDS applications has
proved to be beneficial to the users. These systems help reduce the
cloud of mystery that surrounds the future and helps prevent serious
loss by making educated and calculated decisions for how these farms
should run.
[1] Fundamentals of Information Systems, 6th Edition pg 288
[4] http://www.intechopen.com/books/efficient-decision-support-systems-practice-and-challenges-from-current-to-future/decision-support-systems-in-agriculture-administration-of-meteorological-data-use-of-geographic-info
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