1. Development of On-the-go Nitrogen Application Algorithms for Cotton Terry Griffin, Ph.D., CCA Assistant Professor – Economics Dept. of Agricultural Economics & Agribusiness NEU Conference

2. Motivation and Issue Analyses have been conducted for single datasets Failed to model multiple climates, systems, etc. Global response estimated from pooled dataset Derive on-the-go nitrogen application algorithms Objective Objective: analyze multi-state experiment data to estimate response between active sensor reflectance and cotton yield for on-the-go nitrogen management –Develop on-the-go N application algorithm

3. Data and Methods Pooled model 13 –Multiple site-years; 13 states –All data (sites and years) in single dataset –Each sub-dataset controlled for heterogeneity –Testing for heterogeneity between sub-datasets Correlation among –yield, nitrogen rate, NDVI values and timing Regression analysis of pooled dataset

4. Challenges Cotton in a perennial N rate sufficient to cause yield penalty Identifying appropriate timing for NDVI –DAP, GDD60 Testing functional forms of relationships Testing indexes for algorithm –Variety, location, and GDD60 specific –Global algorithm with local intercept/slope shifters

5. Correlation Coefficients YLDNDVI MidNDVI Late YLD1 NDVI Mid0.211 NDVI2 Late-0.220.451

6. Cotton Yield Response to Applied N Theoretically quadratic; without plateau

7. Cotton yield by N rate: 7 site-years

8. NDVI by N rate

9. NDVI wrt N rate by Timing

10. Summary and Future Work Analysis is on-going –Have not determined optimum algorithm Use of GDD60 needs to be revisited

11. Acknowledgements Funding from Cotton Inc. Collaborators in respective states John Kelley – Graduate Student

12. Terry Griffin Assistant Professor - Economics 501.671.2182 tgriffin@uaex.edu