Proximal thermal imaging-based irrigation scheduling for bread wheat in Egypt

Owing to the significance of leaf and air temperature differences (ΔT) under arid conditions, this study aimed to prove the proximal thermal imaging concept for irrigation scheduling under controlled irrigation amounts for wheat in Egypt. This led to variation in leaf relative water content (RWC), soil water content (SWC) and ΔT and allowed us to obtain relationships. Two experiments were conducted in the 2022 winter season under different agroecological conditions. The average temperature of bright leaves (Tleaf) and average temperature of entire images (Timage) were estimated. Strong inverse relationships were observed between the bright leaves and air temperature difference (ΔT-L) and both RWC and SWC, with R2 values of 0.736 and 0.844, respectively. Additionally, the entire image and air temperature difference (ΔT-I) showed strong inverse relationships, with R2 values of 0.735 and 0.880, respectively. The study proved reliability for detecting water stress, instantly measuring RWC and SWC and providing thermal-based irrigation scheduling in newly reclaimed lands. This study recommends determining ΔT thresholds for various crops. The study was the first step to prove the concept under controlled conditions and provide ΔT thresholds. The next step will capitalize on findings to schedule irrigation under uncontrolled conditions in farmer fields in the 2023 winter season to test the ability to achieve an impact.