Using Unmanned Aerial Systems to Track Growth and Predict Yield in Cotton

Cotton (Gossypium hirsutum L.) growth rate as well as yield varies with different rates of management inputs. The ability to monitor and quantify these differences using remote sensing shows great potential for research as well as production. This technology can be used to help breeders select for traits of interest by collecting data such as height and yield. Producers can use this technology to help facilitate making in-season management decisions by observing plant health using normalized difference vegetation index (NDVI). Using an unmanned aerial system (UAS) greatly reduces the time and labor required to collect field scale data in comparison to traditional methods. The objective of this study was to determine if growth and yield could be accurately monitored using imagery collected from a UAS. Remote sensing data using a UAS were collected from a study testing the effects of irrigation on eight different commercial cotton cultivars grown at the Texas A&M Brazos Research Farm. The study has a split plot design with irrigation as the main plot (90% ET replacement, 45% ET replacement and dryland), and cultivars (PHY499, FM2807, DP15R551, DP1549, FM1900, ST6182, NG1511, ST4943) as the subplot treatments. Images were collected using two different fixed winged UAS platforms. Images collected contained four spectral bands, (Red, Green, Blue and Near Infrared). Results summarizing the performance of the unmanned aerial system will be presented at this conference.