Evaluation of a Novel Thermal Imaging System for the Detection of Crop Water Status in Field-Grown Cotton

The main objective of this study was to investigate the efficacy of a novel thermal imaging system for the detection of near-continuous canopy temperatures and by extension, crop water status. During the 2018 growing season, the camera was mounted on an extendable 15-meter pole at the Stripling Irrigation Research Park in Camilla, GA. In addition, a total of 27 SmartCrop infrared thermometers (IRTs) and 27 soil moisture sensors from the University of Georgia Smart Sensor Array (UGA SSA) were installed in the experimental area. Plot boundaries were defined using ImageJ and plot averages calculated for all the different sampling dates (between 1200 and 1400h). Several thermal camera-based and SmartCrop-based CWSIs, (1) empirical CWSI calculated using canopy-air T differences to VPD for dry and wet baseline definition; (2) using Jones (1992) energy balance approach for both dry and wet baselines; (3) using Jones (1992) for wet baseline calculations and air T + 5°C as dry baseline; (4) using Monteith and Unsworth (1990) energy balance for wet baseline calculations and air T + 5°C as dry baseline, were compared to the previously defined and well-established CWSI calculation method for cotton in the Southeastern US. Soil moisture data were collected hourly and displayed on a dedicated website. The study included three irrigation treatments, three different cotton cultivars (PHY 490, PHY 330, and ST 6182), and a total of 54 replicate plots. In-field crop water status (predawn and midday leaf water potential), and crop response measurements (growth and physiology) were collected weekly, beginning at cotton squaring. Established IRT and soil moisture-based methods agreed closely with the CWSI developed using the novel imaging system, respectively (r2 = 0.842) and (r2 = 0.585), indicating the system could be exploited as an irrigation scheduling tool, improving irrigation water use efficiency.