Managing Global Resources for a Secure Future

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

49-8 Evaluation of Spring Wheat Senescence Using Multispectral Data.

See more from this Division: ASA Section: Climatology and Modeling
See more from this Session: Agricultural Remote Sensing General Oral (includes student competition)

Monday, October 23, 2017: 11:00 AM
Tampa Convention Center, Room 5

Breno Bicego Vieitez de Almeida1, Aaron Wipf2, Scott Powell2 and Jessica A Torrion3, (1)Plant Sciences and Plant Pathology, Montana State University, Bozeman, MT
(2)Montana State University, Bozeman, MT
(3)Northwestern Agricultural Research Center, Montana State University, Kalispell, MT
Abstract:
Senescence rating is a phenotyping approach to characterize yield and protein in crops. For wheat, rapid senescence due to genetics (G), environment (E) and management (M) can enhance grain protein content but can also have a negative impact on yield. Scoring senescence visually in the field can be subjective and time-consuming, especially with a large G x E x M study. Nitrogen and water regime studies with various cultivars of hard red and soft white spring wheat were used to: 1) develop a senescence rating methodology, and 2) understand which plant traits induce senescence. In 2016 and 2017, a fixed wing drone was flown successively starting from late milk to near-harvest maturity to gather temporal multispectral data. The sensor acquired data centered at the 550 nm (Green), 660 nm (Red) and 790 nm (Near Infra-Red) portion of the electromagnetic spectrum. Indices such as Normalized Difference Vegetation Index and Plant Senescence Rating Index were calculated. Representative pixels were sampled from each experimental unit (i.e., plots) and regressed with the visual senescence scores. In 2017, a handheld multispectral sensor was used together with the drone flight mission to expand the available multispectral data to evaluate its utility and develop an index for senescence rating. This approach will provide a non-subjective methodology for large area physiological studies or breeding programs.

See more from this Division: ASA Section: Climatology and Modeling
See more from this Session: Agricultural Remote Sensing General Oral (includes student competition)