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ARS Home » Plains Area » Lincoln, Nebraska » Agroecosystem Management Research » Research » Publications at this Location » Publication #220943

Title: Active sensor assessment of corn nitrogen status

item Shanahan, John
item Schepers, James

Submitted to: Agronomy Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 9/1/2007
Publication Date: 11/1/2007
Citation: Shanahan, J.F., Solari, F., Ferguson, R., Schepers, J.S. 2007. Active sensor assessment of corn nitrogen status. Agronomy Abstracts #193-4.

Interpretive Summary:

Technical Abstract: Use of active sensor measurements of in-season corn (Zea mays L.) nitrogen (N) status for directing spatially-variable N applications has been advocated to improve N use efficiency. However, first it is necessary to confirm that active sensors can reliably assess corn N status. Our research goals were to determine the most appropriate: 1) growth stage and 2) vegetation index with greatest sensitivity in assessing variation in canopy N status and grain yield, using active sensor readings. Variable crop N conditions were generated by supplying fertilize N at different amounts and times in three field studies conducted near Shelton, NE in 2005. Sensor and SPAD chlorophyll meter readings were gathered at two vegetative (V11 and V15) and two reproductive (R1 and R3) growth stages, using the Crop Circle active sensor that measures canopy reflectance in two bands (amber and NIR; centered at 590 and 880 nm). Reflectance values were converted to three vegetation indices; the amber normalized difference vegetation index (ANDVI), simple ratio index (SRI), and chlorophyll index (CHLI). Grain yields were also determined. Variation among N treatments for all vegetation indices was more highly correlated with SPAD readings for vegetative than reproductive growth stages, with the SRI and CHLI being more sensitive than ANDVI in detecting variation in canopy greenness. The SRI and CHLI values were also more sensitive in distinguishing grain yield variation than ANDVI. Our findings indicate active sensor assessments are capable of detecting variations in canopy N status and could be used to direct spatially variable N applications.