Untitled Document

Current Research
Briefs

Site Specific Production Systems:
Economics of Precision Farming Practices
in the Texas High Plains for Cotton,
Grain Sorghum, Corn, and Peanuts

Increased use of fertilizers, pesticides, and other inputs have contributed to the enhancement of agriculture's productivity in recent decades.


Today,
production agriculture is facing many challenges such as increasing cost of production, shortage of irrigation water, and increased public concern on the impacts of agricultural production on the environment.

In the future... to survive in the highly competitive world market of agricultural commodities, agricultural producers must produce high quality products at low prices while using environmentally sound practices.
One way to address these objectives is to adopt precision farming technology.

Traditionally, input use in agriculture has assumed field homogeneity with respect to soil fertility, soil moisture, pest populations, and crop characteristics. That is, optimal decision rules of input use do not account for differences of those characteristics within fields. Precision farming, precision agriculture, or site-specific management recognizes the variability of such factors within fields and seeks to optimize variable input use under these conditions.

It has been said that precision farming is an advanced information-technology-based management system designed to identify, analyze and manage site-soil spatial and temporal variability within fields for optimum profitability, sustainability, and protection of the environment.

The development of precision farming practices -- is closely related to the many new technologies that have been utilized in agricultural production in recent years. These new technologies involve microcomputers, microprocessor based control systems, satellite positioning technologies, and many kinds of sensors. With the help of these technologies, variable rate application of fertilizers and spraying of weeds, spatial soil testing, and yield mapping are becoming available.

 

 

Principal Investigator: Eduardo Segarra
Agricultural Economist, Texas Agricultural Experiment Station and Texas Tech University, Lubbock


The project's overall objective?

Derive optimal decision rules of input use (irrigation water, fertilizers, herbicides and insecticides) and evaluate the economic impacts of precision farming practices in cotton, grain sorghum, corn, and peanut production in the Texas High Plains. Precision farming optimal decision rules of input use have already been derived for cotton, grain sorghum, and corn production.

Results indicate:
· Precision farming practices are economically beneficial as compared to conventional practices in cotton, corn and grain sorghum production, but widespread use of these practices will critically depend on their adoption cost.
·
The economic benefits of precision farming practices are not evenly distributed across fields - in fact, spatial variability of both yields and profits across fields are magnified under precision farming practices as compared to conventional practices.
·
Precision farming can effectively be used to identify "management zones" within fields where the potential for significant improvements in profits are possible.

What's ahead ...

This project could have significant impacts on well over 5.0 million acres of cropland in the production of corn, grain sorghum, peanuts and cotton in the Texas High Plains. Corn, grain sorghum, and cotton results have been released to professional and agricultural producers audiences. Peanut production work is ongoing.

It is anticipated that next year, results applicable to peanut production will be available. Also, precision farming optimal decision rules of input use refinements for the other crops will be made.

For more information about this project, contact:

Eduardo Segarra, PhD, Ag Economist
Department of Agriculture and Applied Economics
Texas Tech University, MS 42132,
Luboock, TX 79409-2132
PHONE: (806)742-2821
FAX: (806) 742-1099
EMAIL: EDUARDO.SEGARRA@TTU.EDU