Field validation of a remote sensing technique for early nitrogen application decisions in wheat

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.