What Exactly Is a Crop-Growth Model?
Crop-growth models simulate a different growing-season scenario very
quickly, often every second or faster. Reddy says that technically the
melon model is a simple one because it predicts only yields and harvest
timing. The more complex models like Gossym and Glycim also predict
timing of water, fertilizer, and chemical applications.
"All crop-growth models package scientific research and rules
of thumb, supplementing or replacing farmers' rules of thumbs, habits,
and guesswork," Reddy says. "Because these are scientific
models that have principles of plant physiology and soil physics built
into them, they can be used not only to help farmers, but also for other
applications, like studying the effects of global climate change on
crop yields or lowering nitrogen levels in bodies of water like the
Chesapeake Bay." Reddy, Dennis J. Timlin, a soil scientist at Beltsville,
and Jeff Baker work with colleagues around the world on these types
of environmental uses.
"The models 'learn' from years of computer monitoring of crops
grown in hard-wired outdoor growth chambers as well as from years of
field trials on farms around the country," Reddy says. "All
the models are programmed into software that can be downloaded from
the Internet or a CD."
The Cotton Production Model (CPM), a successor to Gossym, was released
in 2002 on the ARS Office of Technology Transfer's Internet site (http://ott.ars.usda.gov/)
for further research and commercial development. "It predicts the
timing of all cotton-farming operations," Reddy says. The CPMalong
with Glycim, the melon model, and an earlier version of the potato modelis
available on the Internet or on CD.
A new rice crop-growth model will soon be available at this site, and
a corn model will be available within the next few years. A wheat model
is in the planning stages.
Don't Forget the Soil
In 1996, Timlin and Yakov A. Pachepsky, another ARS soil scientist
at Beltsville, helped develop 2DSOIL, a soils component for the modelsalong
with soil physicists Jirka Simunek and Rien van Genuchten at ARS' Salinity
Laboratory in Riverside, California. They used parts of various models,
including Glycim. Timlin worked closely with Pachepsky and Reddyas
well as with Frank D. Whisler, a now retired professor of soil science
at Mississippi State Universityin moving Glycim into on-farm use.
Reddy says that by working with farmers, researchers gained valuable
insights on how to design models for practical use. For example, Pachepsky
and ARS computer programmer Eugene Mironenko developed GUICS (Graphical
User Interface for Crop Simulators), a generic interface that makes
all ARS crop models easier to use. They had substantial help from farmers
who were using the soybean model.
Customizing the Model
Farmers localize a crop-growth model by choosing their field soil types,
local weather, and crop variety and typing in some simple measurements
of their crops' growth.
The models are typically coupled with field weather stations that send
data to desktop computers over phone lines. The weather data is automatically
updated every 10 minutes or so.
Baker says that for the melon model, all farmers have to do is "download
the air temperature data and make simple measurements for each melon
varietysuch things as the rate at which their vines grow new leaf
When Reddy and Acock were in Mississippi, they saw firsthand that knowing
the moment to harvest is just as critical to cotton farmers as it is
to melon farmers. They saw farmers' army of harvest vehicles lined up
across the horizon, rushing to beat storm clouds that loomed in the
distance and that threatened to knock cotton bolls down into a sea of
mud. Like melon growers, if they harvest too early, they will have less
cotton; if they wait too long, the quality and price go down, sometimes
dramatically if the weather turns bad.
The threat of damage from severe rainstorms is much higher for Mississippi
cotton farmers than for melon growers in the dry Rio Grande Valley.
On the other hand, produce has a much shorter shelf lifeand higher
individual crop valuesthan field crops. In the end, the pressures
of horticultural crop and field crop farming are more similar than they
The Heart of Crop Models
Growth chambers are the heartor brainsof crop-growth models.
They are where the models gain an intimate knowledge of crop growtha
knowledge that can easily surpass a farmer's. That's partly because
the chambers monitor plant growth every 10 seconds or so, 24 hours a
day, along with hidden root growth, soil moisture, temperature, and
other conditions. From this data, crop models can "see" things
before they are visible to the human eye.
Mississippi State acquired the first such chambers in the world. Their
10 bubble-top containers have been monitoring cotton and other plants
since 1974, providing the knowledge base for Gossym and Glycim. Reddy
and Acock went to Beltsville in 1989 and set up 12 similar units there.
Kambham R. Reddy, a plant physiologist and colleague of V.R. Reddy's
while at Mississippi State, has been working with the chamber facility
since arriving at the university 14 years ago. From the growth-chamber
data, he and his associates have developed mathematical equations for
Gossym to simulate over 200 different cotton growth functions.
No Time for Models?
Don Baker has seen farming from both sides nowas a scientific
researcher and as a farm consultant. He toured farms and worked with
farmers during his 25 years of Gossym research. But it was only after
he retired from ARS and began working daily with farmers that he was
really struck by the fast pace of farmingone so hectic during
the growing season that farmers had no time to run models.
"We had Gossym on 300 farms at one point, and we couldn't give
the farmers all the assistance they needed," Baker says. "I
knew farmers were busy, but you just can't fully appreciate how busy
until you work with them daily, as I do now."
As a consultant for cotton and soybean farmers in the Mississippi Delta,
Baker sees the issues they face in the fieldpersonnel, procurement,
weather, equipment breakdowns, and fertilizer and chemical decisions.
"There are many times when farmers just can't sit at a desk computer;
they're too busy directing the battle," Baker says.
Sam Turner, an ARS computer specialist at Mississippi State, worked
with Baker, V. R. Reddy, and Acock on the Gossym and Glycim models.
He points out that "All farmers work with modelsit's just
that some are in their heads. Their experience and common sense give
them a conceptual model that frames their farming decisions. But a computer
model is a nice supplement to the model in their heads because, unlike
the human mind, it never forgets, and it contains all the knowledge
scientists have learned about crops and farming."
Despite the time limitations, Baker agrees with Turner that farmers
can't farm without a model, whether in their heads or on a computer.
"It would be like flying a plane without visual sighting or instruments,"
The Bottom Line
Crop-growth models can save farmers a lot of money and worry. The cotton
model, for example, earns farmers an average $60 to $80 an acre in additional
profits. Mitchener says that in 1984, Gossym would have saved him hundreds
of thousands of dollars of cotton had he listened to the model during
early tests. He lost about 200 pounds of cotton an acre because he didn't
harvest exactly when the cotton was ready. The cotton fell to the ground
Reddy says a survey by Mississippi State University showed that soybean
farmers credit the model with increasing yields up to 29 percent and
increasing irrigation efficiency fourfold.
"These types of numbers are the bottom line for models,"
Reddy says, "but they don't tell the full story. Perhaps equally
important to farmers is how models help them examine their crops in
a more timely manner and in ways they had not previously considered.
And they enable researchers to study the effects of environmental conditions
in ways considered impossible before. The more we learn, the more the
possibilities for model applications appear limitless."By
Agricultural Research Service Information Staff.
This research is part of Integrated Agricultural Systems, an ARS
National Program (#207) described on the World Wide Web at http://www.ars.usda.gov.
V.R. Reddy, Dennis
J. Timlin, and Jeff Baker
are at the USDA-ARS Alternate
Crops and Systems Laboratory, Bldg. 001, 10300 Baltimore Ave., Beltsville,
MD 20705-2350; phone (301) 504-5872, fax (301) 504-5823.
"Predicting the Perfect Moments in Farming From Planting
to Harvest" was published in the November
2002 issue of Agricultural Research magazine.