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Aerial Color Infrared Photography for Determining Early In‐Season Nitrogen Requirements in Corn

Agronomy Journal · 2006 · Vol. 98(4) · pp. 968–977
Ravi P. SripadaRonnie W. HeinigerJeffrey G. WhiteAlan D. Meijer

Abstract

In‐season determination of corn ( Zea mays L.) N requirements via remote sensing may help optimize N application decisions and improve profit, fertilizer use efficiency, and environmental quality. The objective of this study was to use aerial color‐infrared (CIR) photography as a remote‐sensing technique for predicting in‐season N requirements for corn at the V7 growth stage. Field studies were conducted for 2 yr at three locations, each with and without irrigation, in the North Carolina Coastal Plain. Experimental treatments were a complete factorial of four N rates at planting (N PL ) and five N rates at V7 (N V7 ). Aerial CIR photographs were taken at each of the locations at V7 before N application. Optimum N V7 ranged from 0 to 207 kg N ha −1 with a mean of 67 kg N ha −1 . Significant but weak correlations were observed between optimum N V7 rates and the band combinations relative green, Relative Green Difference Vegetation Index, and Relative Difference Vegetation Index as measured in CIR photos. High proportions of soil reflectance in the images early in the corn growing season (V7) likely confounded our attempts to relate spectral information to optimum N V7 rates. The primary obstacles to applying this technique early in the season are the use of relative digital counts or indices that require high‐N reference strips in the field and strong background reflectance from the soil. When the N PL treatments that were nonresponsive to N V7 (i.e., optimum N V7 = 0) were removed from the analysis, the normalized near infrared, the Green Difference Vegetation Index, the Green Ratio Vegetation Index, and the Green Normalized Difference Vegetation Index were the best predictors of optimum N V7 rate ( r 2 = 0.33).

Remote Sensing in AgricultureRemote Sensing and LiDAR ApplicationsSmart Agriculture and AIGrowing seasonIrrigationEnvironmental scienceSowingAerial photographyVegetation (pathology)FertilizerMathematicsRemote sensingAgronomy
Citations
419
FWCI
2.16
field-weighted impact
References
29
Percentile
87%
vs. same field & year
Citations per year
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Aerial Color Infrared Photography for Determining Early In‐Season Nitrogen Requirements in Corn · Scinovex