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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. Motivation and Issue. Analyses have been conducted for single datasets - PowerPoint PPT Presentation
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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
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
ObjectiveObjective: 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
Data and Methods
• Pooled model– Multiple site-years; 1313 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
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
Correlation Coefficients
YLD NDVI Mid NDVI Late
YLD 1
NDVI Mid 0.21 1
NDVI2 Late -0.22 0.45 1
Cotton Yield Response to Applied N
• Theoretically quadratic; without plateau
Cotton yield by N rate: 7 site-years
NDVI by N rate
NDVI wrt N rate by Timing
Summary and Future Work
• Analysis is on-going– Have not determined optimum algorithm
• Use of GDD60 needs to be revisited
Acknowledgements
• Funding from Cotton Inc.
• Collaborators in respective states
• John Kelley – Graduate Student