• Jac J. Varco - Professor of Agronomy, Mississippi State University
• Marvin L. Salin - Professor of Biochemistry and Biotechnology, Mississippi State University
• Dr. Susan M. Bridges - Associate Professor of Computer Science, Mississippi State University
• Dr. Will H. McCarty - Extension Cotton Specialist, Mississippi State University

This project involves investigating nutritional effects on crop reflectance and pigmentation and applications of remote sensing in the decision support process for variable rate nitrogen fertilization. Nitrogen fertilization represents a significant cost factor in the production of cotton. Mississippi produces a cotton crop worth around 642 million dollars using a fertilizer nitrogen rate which averages near 110 lb/acre across approximately 1,000,000 acres. Optimizing the rate applied to achieve maximum profitability is critical, since too little can limit yield and thus profits, and an excess can cause rank growth which increases the need for growth regulators and insecticides, increases the incidence of boll rot, and makes defoliation more difficult.

Nitrogen nutrition is known to influence leaf chlorophyll concentration and greenness and through the use of remote sensing we may be able to estimate the nutritional status of a crop to assist in establishing more accurate side-dress nitrogen rates. The quantity of fertilizer nitrogen required by a crop is determined by an integration of soil and climatic factors and their effects on crop growth and nitrogen losses. Due to the highly transient nature of soil available nitrogen, there is no simple or routine soil test that can be used to predict availability and fertilizer needs and crop models have been shown to be inaccurate in predicting nitrogen nutrition of cotton across soils.

Alluvial derived soils of the Mississippi Delta pose an even greater challenge due the high degree of soil heterogeneity within farmer managed fields. With the advent of technology that can be used to specifically treat differing areas, there is a need for developing decision support criteria for which to base variable rate nitrogen fertilization. Recent research has shown Delta alluvial soils to vary widely in their nitrogen supplying capacity and cotton yield potential and, thus are suitable for variable rate application of fertilizer nitrogen. Remote sensing has the potential to be used as a tool to assist in soil or field characterization and in the visualization of crop health and nutritional status.

Currently we are using residual available soil nitrogen to a depth of 3 ft., soil clay content, and elevation and relative soil moisture inferred from multi-spectral images. We believe that variable rate application of fertilizer nitrogen utilizing a multi-factor approach including features determined through remote sensing can maximize nitrogen use efficiency, increase profitability, and minimize the potential for environmental contamination.