This ongoing project has demonstrated on-farm input costs savings and increased yields through the use of a total-farm variable rate management program in the Mid-South.

Work will continue on: 1) evaluating the variable-rate application systems in both dryland and irrigated cotton producing systems in western Oklahoma; 2) reducing cotton production cost by greater than 30 percent per acre; 3) introducing producers to the successful usage of multispectral imagery with variable rate crop input applications; 4) developing a broad based system for farm wide variable rate crop input applications in cotton production; and 5) creating one or two new variable-rate “Technology Demonstration Farms” to expand producer exposure and knowledge gained in previous studies.

The 2005 season work at Oklahoma State University under the direction of Tim Sharp will focus on refining the nitrogen, plant growth regulator and crop termination treatments. COTMAN data will be used, and the expectation is to further increase yield, reduce cost and improve harvest efficiency.

In Louisiana, multi-spectral images of agricultural fields were used to determine variable rate applications of plant growth regulator and defoliants in 2004 and for pesticide application in 2005.

Spatially variable rate (SPV) technology based on remote sensing was demonstrated on 13 farms inLouisiana. Louisiana State University researchers found that SVP application of plant growth regulators and defoliants resulted in considerable savings from reduced chemical usage.

The researchers want to: 1) demonstrate SVP treatments based on remote sensing to commercial pesticide applicators; 2) introduce spatially variable insecticide treatments based on historical yield; 3) increase industry awareness of the various technologies associated with spatially variable inputs; 4) develop a better understanding of the economics of spatially variable inputs; 5) adapt the current prototype application system and evaluate performance on a commercial aircraft; and 6) validate the use of these technologies on multiple farms using various production strategies.

Preliminary data analysis shows that both remote sensing and soil electrical conductivity have the potential to indicate soil compaction.

University of Arkansas scientists will continue to evaluate VERIS and remote sensing technology for identifying and mapping soil compaction levels in the field. They also will develop subsoiling guidelines for cotton agriculture in Arkansas based on the VERIS and/or remote sensing data.

Researchers at Texas Tech University will continue data collection during the 2005 growing season to help delineate management zones within fields for variable-rate Pix and defoliant application. Yield mapping data will be analyzed for the variable-rate and uniform treatments using GIS software to determine significant differences and to evaluate the potential benefits of variable-rate versus uniform application.

Fiber quality will be mapped for several fields from samples taken during harvest and analyzed by the International Textile Center. Prior to harvest, plant mapping will be performed at the fiber sampling locations and will be used to investigate the relationship between fiber quality and boll maturity. Differences in crop canopy growth will be monitored using remote sensing.

Results of these experiments will be used to formulate a method for site-specific management to manipulate boll maturity and improve fiber quality in parts of fields that are prone to discounts. The study information will be used to evaluate differences in net income between precision agriculture and conventional crop management.

From 2002-2004, University of Georgia researchers collected detailed information on five Variable Rate Irrigation (VRI) pivots located in different areas of Georgia. Along with millions of gallons of water savings, they noted an increase in yield due largely to not over watering the boggy field sections and being able to apply more water to the very sandy spots. In 2004, 20 fields in southwest Georgia were selected to be equipped with the VRI system to evaluate its impact on cotton yield and quality and on water use efficiency.

A key 2005 objective is to develop a second generation VRI system that is capable of using wireless Internet reception and data transmission. The VRI control system will be coupled to sensing systems to enhance field operations. A third objective is to develop a rapid, cost effective system that can give producers a reliable estimate of the impact a VRI system would have on a field.

This University of California research continues to evaluate the remote detection of crop water stress in California cotton and assess its accuracy for use in irrigation scheduling. They have found, for example, that chlorophyll content and water stress indices were shown to spatially correspond to water content – information that could be integrated into farm management practices (water content maps) if the system becomes operational.

In 2005, project scientists are refining and validating current remotely sensed spectral indices to improve the accuracy in predicting irrigation demand. Included will be measures of the plant water content before and after defoliation.