Decision aid helps growers make precision ag choices

Cotton farmers seem to be at the point where they know precision agriculture will work, says Jeanne Reeves, Cotton Incorporated agricultural economist.

The question remains, however, will it pay?

Cotton Incorporated has an interactive tool that could help cotton farmers put the numbers to the question. The Computerized Cotton Yield Monitor is an interactive decision aid designed to help cotton farmers evaluate the yield gains and input savings required to pay for investment in a cotton yield monitoring system.

The downloadable version of the decision aid is available on the Cotton Incorporated Website under Agricultural Research or is available through the mail.

The Agricultural Economics Production Economics Analysis Group at the University of Tennessee developed the decision aid with funding from Cotton Incorporated.

It grew out of a survey of farmers in Alabama, Florida, Georgia, Mississippi, North Carolina and Tennessee.

The survey was conducted to determine attitudes toward and current use of precision agriculture and the willingness of cotton producers to pay for a cotton yield monitoring system.

Through the decision aid, a farmer can plug in information specific to the farm. The decision aid asks for information regarding acres and equipment. “For example, if you've got this many acres and this much variability, this is how long it will take to pay for precision agriculture on your farm,” Reeves says. “The decision aid will be able to give you specific numbers about precision agriculture on your farm.”

To run the decision aid, you'll need an IBM or IBM compatible computer, with a hard disk of 1.0 MB free disk space and Windows 95 or higher.

In short, the decision aid will be able to tell the farmer how many acres he would need in order to pay for a yield monitor or a variable-rate applicator. The CYMIDA calculates ownership and information system costs based on data for your farm for the information system, farm and crop inputs.

You can enter data regarding your crop acreage, lint yields, expected lint price, picker size, equipment costs, etc.

It also includes input decisions for nitrogen, phosphorous, potassium, lime, seed, growth regulators, fungicide, herbicide, insecticide, harvest aids and drainage.

Reeves points out that the cost of adopting precision agriculture “depends” on the farm. That's where the decision aid will help the farmer determine if the technology can pay for itself. If a farmer already has a grain yield monitor, the addition of sensors could cost about $4,000. The purchase of a cotton yield monitor runs much higher.

“If you spend $15,000 to save $20 per acre, you've still got to remember that you have to spend $15,000 first in order to get the savings,” Reeves says.

Cost has been one of the primary factors affecting the adoption of precision agriculture.

In its first precision farming survey in 2001, Cotton Incorporated found that the most common technologies used in cotton production were grid and management zone soil sampling, variable-rate lime application, plant tissue testing, soil survey maps and variable-rate phosphorous and potassium application.

The survey listed average costs of the practices. Farmers listed profit and environmental benefits as the most influential factors in choosing to adopt precision agriculture. Extension and universities, crop consultants and farm dealers were the most helpful in learning about these technologies.

Eight-five percent of adopters and 63 percent of those yet to adopt precision practices thought precision farming would be profitable for them in the future. Some 86 percent of the adopters and 74 percent of non-adopters owned computers while 74 percent and 55 percent used them for farm management, respectively.

Reeves plans another survey in 2005.

e-mail: [email protected]

Hide comments


  • Allowed HTML tags: <em> <strong> <blockquote> <br> <p>

Plain text

  • No HTML tags allowed.
  • Web page addresses and e-mail addresses turn into links automatically.
  • Lines and paragraphs break automatically.