68-3 Evaluation of Algorithm for Nitrogen Application of Corn in South Carolina.

Poster Number 174

See more from this Division: C03 Crop Ecology, Management & Quality
See more from this Session: Corn and Soybean Management
Monday, November 1, 2010
Long Beach Convention Center, Exhibit Hall BC, Lower Level
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Mioko Tamura1, Pawel Wiatrak1, David Wallace2 and Ahmad Khalilian3, (1)Entomology, Soils, and Plant Sciences, Clemson University, Blackville, SC
(2)Southern States Cooperative, Alcolu, SC
(3)Biosystems Engineering, Clemson University, Blackville, SC
Nitrogen (N) is not uniformly utilized by corn (Zea mays L.) due to considerable soil texture variations in the Southeastern U.S. Soil texture affects soil water content and plant available water; therefore, the N utilization. However, there is currently no standard procedure for soil-base variable N application on corn. The objectives of the study were to 1) evaluate plant growth and N utilization using optical sensing technology under three soil EC zones in response to N application timing and rate, and 2) test a South Carolina corn algorithm for sidedress N for each soil EC zone and across all zones. A commercially available Veris Technologies® 3100 was used to identify field soil variations and to define three zones based on soil EC levels.  Nitrogen was applied at 45 kg ha-1 increments from 0 to 180 kg N ha-1 at two timings (all at plant or sidedress). During the corn vegetation stages, normalized difference vegetation index (NDVI), leaf area index (LAI) and single photon avalanche diode (SPAD) were used to evaluate the crop growth. NDVI readings at about V6 corn stage generated different sidedress rates for each soil EC zone using a South Carolina corn algorithm and N rich strip. Plant response to N fertilization treatment will be presented by each soil EC zone separately on biomass, grain yield, and N concentrations in leaf, ear, and stalk tissues.   
See more from this Division: C03 Crop Ecology, Management & Quality
See more from this Session: Corn and Soybean Management