Evaluation of vegetation indices for early assessment of corn status and yield potential in the southeastern United States

MS Torino, BV Ortiz, JP Fulton, KS Balkcom… - Agronomy …, 2014 - Wiley Online Library
Agronomy Journal, 2014Wiley Online Library
The use of crop canopy sensors for variable rate nitrogen (VRN) application in corn (Zea
mays L.) production across the southeastern United States 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 …
The use of crop canopy sensors for variable rate nitrogen (VRN) application in corn (Zea mays L.) production across the southeastern United States 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 (0–280 kg N ha−1 on 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 11 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.
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