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UAV-Thermal Imaging: A Robust Technology to Evaluate in-field Crop Water Stress and Yield Variation of Wheat Genotypes

机译:无人机 - 热成像:评估现场农作物水分应激和小麦基因型的产量变异的鲁棒技术

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In recent years, unmanned aerial vehicle (UAV) - based thermal imaging techniques have become increasingly popular in precision agriculture, especially in monitoring crop biotic and abiotic stresses, and soil water, irrigation scheduling, and residue mapping. However, studies are limited on thermal imaging techniques in yield estimation and in-field variability assessment. Here we evaluate the potential of UAV thermal imaging techniques to assess crop water stress and predict grain yield of 18 contrasting wheat genotypes. We conducted an airborne campaign close to crop flowering to capture thermal imagery for a rain fed wheat experimental field in southern Queensland, Australia. Plot wise canopy temperatures (°C) (Tcanopy) were extracted from thermal imagery to determine crop water stress index (CWSI). Wheat grain yield was significantly correlated with CWSI (R2= 0.63; RMSE= 0.34 t/ha). The results suggest potential for UAV thermal imaging techniques to measure crop water status and predict yield under water-limited environments.
机译:近年来,基于无人的空中车辆(UAV)的热成像技术在精密农业中越来越受欢迎,特别是在监测作物生物和非生物应力,以及土壤水,灌溉调度和残留映射。然而,研究在产量估计和现场变异评估中的热成像技术受到限制。在这里,我们评估无人机热成像技术的潜力,以评估作物水分应激,预测18个对比小麦基因型的粮食产量。我们在澳大利亚南部昆士兰南部的雨美麦实验领域进行了近距离作物开花的机载活动。绘制明智的树冠温度(°C)(t canopy )从热图像中提取,以确定作物水分应激指数(CWSI)。小麦籽粒产量与CWSI显着相关(R. 2 = 0.63; RMSE = 0.34 T / HA)。结果表明UAV热成像技术测量作物水位和预测水有限环境下的产量。

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