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Title: Evaluation of vegetation indices for early assessment of corn status and yield potential in Southeastern U.S.

Author
item TORINO, MIGUEL - Auburn University
item ORTIZ, BRENDA - Auburn University
item FULTON, JOHN - Auburn University
item Balkcom, Kipling
item WOOD, C - Auburn University

Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/6/2014
Publication Date: 5/30/2014
Publication URL: http://handle.nal.usda.gov/10113/62402
Citation: Torino, M., Ortiz, B., Fulton, J., Balkcom, K.S., Wood, C.W. 2014. Evaluation of vegetation indices for early assessment of corn status and yield potential in Southeastern U.S. Agronomy Journal. 106:1389–1401.

Interpretive Summary: The use of crop canopy sensors for variable rate nitrogen application in corn production requires evaluation across the southeastern U.S. Auburn University scientists in cooperation with ARS researchers at the National Soil Dynamics Laboratory in Auburn, AL conducted experiments between 2010 and 2012 at three locations in Alabama to identify vegetation indices that best: (i) correlate with plant status variables such as leaf area index and leaf chlorophyll and (ii) predict corn grain yield at early growth stages. Among eleven vegetation indices evaluated, the normalized difference red-edge, chlorophyll index red-edge, simple ratio red-edge, and inverse simple ratio red-edge had the strong correlation with plant status variables. Corn yield prediction based on vegetation index was lowest at the V6 growth stage and highest at V10 stage. These results indicate that crop canopy sensors can successfully be used for corn production in the Southeast, but the ideal time to maximize their effectiveness does not correspond to the V6 growth stage when growers typically apply N to corn in the region.

Technical Abstract: The use of crop canopy sensors for variable rate nitrogen (VRN) application in corn (Zea mays L.) production across the southeastern U.S. implies assessment of corn N status as early as the V6 growth stage. Our goals were to identify vegetation indices (VIs) that best: (i) correlate with plant status variables such as leaf area index (LAI) and leaf chlorophyll (Chl) and (ii) predict corn grain yield at early growth stages. An N fertilization study was conducted between 2010 and 2012 at three Alabama sites. Six N fertilizer rates (0 to 280 kg N ha-1on 56 kg N ha-1 increments) were applied at planting. Data collected at V6, V8, V10 vegetative growth stages were leaf Chl, LAI, and spectral reflectance. Data showed that corn N response could be influenced by the rainfall pre- and post-N application as well as the soil texture. Among eleven vegetation indices evaluated through a canonical correlation analysis, the normalized difference red-edge (NDRE), Chl index red-edge [CI (RE)], simple ratio red-edge [SR (RE)], and inverse simple ratio red-edge [ISR (RE)] had the strong correlation with plant status variables. Vegetation index based corn yield prediction was the lowest at V6 and the highest at V10 stage. At V8 and V10 stages, the yield models based on NDRE, CI (RE), or SR (RE) explained most of yield variation. These results indicated that early season estimation of crop N status and yield potential may be more accurate if red-edge vegetation indices are used.