Managing Global Resources for a Secure Future

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

49-17 Analysis of Plant Growth and Yield Using an UAS (Unmanned Aircraft System)-Based Remote Sensing Platform.

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: 3:10 PM
Tampa Convention Center, Room 5

Juan Landivar-Bowles1, Jinha Jung2, Murilo Maeda1, Anjin Chang2 and Junho Yeom2, (1)Texas A&M AgriLife Research, Corpus Christi, TX
(2)School of Engineering and Computer Sciences, Texas A&M University Corpus Christi, Corpus Christi, TX
Abstract:
Analysis of plant growth and yield using an UAS (Unmanned Aircraft System)-based remote sensing platform

An UAS-based high throughput phenotyping system for cotton was developed by Texas A&M AgriLife and Texas A&M University, Corpus Christi. The system includes an automated data processing workflow for temporal UAS data collected over the growing season to extract various phenotypic features such as plant height, canopy cover, canopy volume, bloom count, open boll count, vegetation indices, and canopy surface temperature. In addition, growth analysis is performed by fitting non-linear models to the UAS-derived phenotypic features to represent temporal responses of cotton genotypes. This growth analysis will provide the following information for each experimental unit: (1) growth rate related parameters such as maximum growth rate, timing of the maximum growth rate, duration and timing of half maximum growth rate, increasing slope of growth rate in early season, and decreasing slope of growth rate in late season, and (2) efficiency related parameters such as the maximum normalized difference vegetation index (NDVI) or Excessive Greenness Index (ExG), timing of the maximum NDVI and ExG, increasing slope of NDVI and ExG in early season, and decreasing slope of NDVI and ExG in late season. In this presentation, the correlation of these parameters with cottonseed yield will be discussed.

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