99576 Mid-Season Prediction of Wheat Grain Yield Potential and Nitrogen Response.

Poster Number 155-1208

See more from this Division: ASA Section: Biometry and Statistical Computing
See more from this Session: Biometry & Statistical Computing Poster

Monday, November 7, 2016
Phoenix Convention Center North, Exhibit Hall CDE

Melissa Rae Golden, Oklahoma State University, Stillwater, OK
Abstract:
Soil nutrient management has made significant advances in efficiency, especially with nitrogen (N) fertilization. Room for improvement exists concerning mid-season prediction of grain yield and ensuing fertilizer nitrogen (N) rates. Sequential normalized difference vegetation index (NDVI) measurements from two long-term nutrient management experiments (Experiment 222 and Experiment 502) were used to improve the prediction of yield potential, and situations where added N is unlikely to increase winter wheat (Triticum aestivum L.) grain yields in the southern Great Plains. These sequential readings will be used by-date, and over dates to better predict grain yield collected from the same plots at harvest. Additional climatological data will also be employed by site to improve yield prediction indices, including cumulative growing degree days from planting to sensing.

See more from this Division: ASA Section: Biometry and Statistical Computing
See more from this Session: Biometry & Statistical Computing Poster