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

Sumanta Das, J. Christopher, A. Apan, Malini Roy Choudhury, S. Chapman, N. Menzies, Y. Dang
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引用次数: 7

Abstract

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.
无人机热成像:一种评估小麦基因型田间作物水分胁迫和产量变化的可靠技术
近年来,基于无人机(UAV)的热成像技术在精准农业中越来越受欢迎,特别是在作物生物和非生物胁迫监测、土壤水分、灌溉调度和残留物测绘等方面。然而,热成像技术在产量估算和田间变异性评估方面的研究有限。在此,我们评估了无人机热成像技术在评估作物水分胁迫和预测18种不同小麦基因型籽粒产量方面的潜力。我们在澳大利亚昆士兰州南部的一个雨养小麦试验田进行了一次接近作物开花的空降活动,以捕捉热图像。从热图像中提取逐图冠层温度(°C) (Tcanopy)来确定作物水分胁迫指数(CWSI)。小麦籽粒产量与CWSI显著相关(R2= 0.63;RMSE= 0.34 t/ha)。研究结果表明,在缺水环境下,无人机热成像技术在测量作物水分状况和预测产量方面具有潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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