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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #243844
Title: Calibrating canopy reflectance sensors to predict optimal mid-season nitrogen rate for cotton

Author
item OLIVEIRA, LUCIANE - University Of Missouri
item SCHARF, PETER - University Of Missouri
item Vories, Earl
item Drummond, Scott
item DUNN, DAVID - University Of Missouri
item STEVENS, WILLIAM - University Of Missouri
item Bronson, Kevin
item Benson, Nelson
item HUBBARD, VICKI - University Of Missouri
item JONES, ANDREA - University Of Missouri

Submitted to: Soil Science Society of America Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/24/2012
Publication Date: 1/1/2013
Citation: Oliveira, L.F., Scharf, P.C., Vories, E.D., Drummond, S.T., Dunn, D.J., Stevens, W.E., Bronson, K.F., Benson, N.R., Hubbard, V.C., Jones, A.S. 2013. Calibrating canopy reflectance sensors to predict optimal mid-season nitrogen rate for cotton. Soil Science Society of America Journal. 77(1):173-183. DOI: 10.2136/sssaj2012.0154.

Interpretive Summary: Nitrogen (N) is an essential nutrient for cotton production and inadequate N supply can severely reduce yield; consequently there is a tendency to over-apply nitrogen. High N application can result in increased cost in pesticides, growth regulator, and defoliant, as well as environmental problems through leaching and runoff of N-rich water. The labor-intensive and time-consuming nature of current N diagnostic tools limits their use; however, reflectance sensors offer the potential to diagnose N needs immediately and translate the diagnosis into a real-time, variable-rate application of N. Nitrogen rate experiments were conducted for two years on various soils to develop recommendations based on reflectance measurements to support variable-rate fertilization. Sensors gave good predictions of optimal N rate, suggesting that variable-rate N applications to cotton based on real-time reflectance measurements are feasible. Refinement of the procedures will result in savings for farmers from not over-applying N to insure against deficiencies. Furthermore, less excess N in the environment will benefit everyone through higher water quality.

Technical Abstract: Inadequate N supply can limit yield of cotton (Gossypium hirsutum L.), while too much N can cause excessive vegetative growth and delayed maturity. Reflectance sensors offer the potential to diagnose N need, and to translate this diagnosis into a variable-rate application of N in real time. Our objective was to calibrate canopy reflectance sensors to predict economically optimal N rate (EONR) in support of variable-rate fertilization. Nitrogen rate experiments were conducted on three soils in 2006 and 2007. Reflectance was measured with three sensors (Crop Circle, GreenSeeker, and Cropscan) at three growth stages (early square, mid-square, and early flower) and at three heights above the canopy (25, 50, and 100 cm). Economically optimal N rate ranged from 0 to 220 kg N ha-1, suggesting that the need to diagnose EONR is great. Relative reflectance for all three sensors was weakly related to EONR at the early square stage, but was related more strongly at the mid-square and early flower stages. Regression equations were not significantly different between mid-square and early flower stages, suggesting that a single equation could be used to translate reflectance measurements to N rates over this period. Relationship to EONR was best for all sensors when placed 50 cm above the canopy. For these stages and height, all three sensors were similarly related to EONR (r2 = 0.59 to 0.62). These relationships could feasibly support successful variable-rate N applications to cotton.