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Agronomy Journal 95:167-176 (2003)
© 2003 American Society of Agronomy

REMOTE SENSING

Field Validation of a Remote Sensing Technique for Early Nitrogen Application Decisions in Wheat

Michael Flowers*,a, Randall Weisza, Ronnie Heinigerb, Barry Tarletona and Alan Meijerb

a Dep. of Crop Sci., North Carolina State Univ., Box 7620, Raleigh, NC 27695-7620
b Dep. of Crop Sci., North Carolina State Univ., Vernon James Res. and Ext. Cent., 207 Research Rd., Plymouth, NC 27962

* Corresponding author (mflowers{at}cropserv1.cropsci.ncsu.edu)

Received for publication January 5, 2002. Studies have shown that winter wheat (Triticum aestivum L.) tiller density at growth stage 25 (GS 25) can be used to determine when a GS-25 N application is needed. However, determining GS-25 tiller density is difficult and time consuming. Color infrared aerial photographs have been successfully used to predict GS-25 tiller density. The objective of this study was to validate a previously reported remote sensing technique to predict GS-25 tiller density based on near-infrared (NIR) digital counts and within-field tiller density references across a wide range of environments. The NIR remote sensing technique was evaluated through linear regression and quadrant plot analysis to determine the accuracy of GS-25 tiller density predictions and GS-25 N application decisions based on a critical GS-25 tiller density threshold. The impact of different wheat varieties, soil colors, and weed populations were also evaluated through covariate analysis using 10 site-years of data. At three site-years, a randomized complete block design with three varieties and either two or three seeding rates was used. At these site-years, variety had a significant influence on spectral measurements. Seven additional site-years had a single variety and seeding rate. The NIR remote sensing technique was found to account for 76% of the variation between predicted and measured GS-25 tiller density across 10 site-years of data. Accurate GS-25 N application decisions were made 85.5% of the time by the NIR remote sensing technique across a wide range of environments including six soil types, six wheat varieties, and two systems.

Abbreviations: B, blue (band) • CIR, color infrared • DVI, difference vegetation index • G, green (band) • GS, growth stage • NDVI, normalized difference vegetation index • NIR, near infrared • OSAVI, optimized soil-adjusted vegetation index • R, red (band) • RVI, ratio vegetation index • SAVI, soil-adjusted vegetation index




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Soil Science Society of America Journal
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