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United States Department of Agriculture

Agricultural Research Service

Title: NORMALIZING STRATEGIES TO DETECT CORN NITROGEN STRESS AND GRAIN YIELD FROM IMAGERY)

Author
item Shanahan, John
item Tringe, James
item Schepers, Aaron
item Ferguson, R
item Francis, Dennis
item Schepers, James

Submitted to: Agronomy Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 6/25/1999
Publication Date: N/A
Citation: Shanahan, J.F., Tringe, J.M., Schepers, A.R. Ferguson, R. B., Francis, D.D., Schepers. J. S. 1999. Normalizing strategies to detect corn N stress and grain yield from imagery. American Society of Agronomy Abstracts. p. 247.

Interpretive Summary:

Technical Abstract: The goal of this research is to compare different normalizing strategies for remote sensing data as a means of predicting nitrogen stress and final grain yield for corn. The work was conducted near Shelton, NE during the 1997-98 seasons. Treatments consisted of a combination of 4 corn hybrids, differing in canopy architecture, and 5 N rates. Remotely sensed data for the entire plot area were collected at different crop growth stages using four-band multi-spectral (blue, green, red, and near-infrared) system from aircraft. Images (0.5-m spatial resolution) were geo-referenced and converted into various vegetation indices, including NDVI. Grain yield for each plot was also determined at maturity. Vegetation indices collected during mid grain fill were most highly correlated with grain yield, and normalizing absolute grain yields to the treatment average further improved this relationship.

Last Modified: 8/24/2016
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