Managing Global Resources for a Secure Future

2017 Annual Meeting | Oct. 22-25 | Tampa, FL

226-2 Predicting Potential Grain Protein Content of Spring Wheat with in-Season Hand-Held Optical Sensors.

See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: Sensor-Based Nutrient Management Oral Session (contains student competition)

Tuesday, October 24, 2017: 10:30 AM
Tampa Convention Center, Room 4

Matthew Rellaford, North Dakota State University, Fargo, ND and Joel Ransom, P.O. Box 6050, North Dakota State University, Fargo, ND
Abstract:
Spring wheat producers lack in-season tools to predict grain protein content in order to decide whether to apply mid-season top-dress nitrogen. This study was conducted to determine whether Normalized Difference Vegetation Index (NDVI) is predictive of GPC and, if so, what the earliest predictive growth-stage would be. A hand-held sensor was used to collect NDVI from three locations in the northern Great Plains with a range of fertility treatments resulting in a difference of yield and protein. NDVI was further normalized against a high N treatment (224 kg N ha-1) and analyzed through linear regression. Normalized NDVI became more predictive of GPC with plant maturity, measured at Zadoks growth stages 15, 37, and 45 (R2 = 0.35, 0.65, 0.85 respectively). Total protein (GPC x yield) was even more predictive of normalized NDVI (R2 = 0.47, 0.74, 0.89 respectively). The predictability of NDVI on GPC varied between environments with sandy soils showing a greater predictability than clayey soils. NDVI may be a useful tool for producers at predicting GPC and total protein and more research should be done on sensing methods that go beyond hand-held devices such as unmanned aerial systems.

See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: Sensor-Based Nutrient Management Oral Session (contains student competition)