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  • UAV-thermal imaging: A robust technology to evaluate in-field crop water stress and yield variation of wheat genotypes

    Author(s)
    Das, S
    Christopher, J
    Apan, A
    Choudhury, MR
    Chapman, S
    Menzies, NW
    Dang, YP
    Griffith University Author(s)
    Menzies, Neal W.
    Year published
    2020
    Metadata
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    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 ...
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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.
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    Conference Title
    2020 IEEE India Geoscience and Remote Sensing Symposium (InGARSS)
    DOI
    https://doi.org/10.1109/InGARSS48198.2020.9358955
    Publication URI
    http://hdl.handle.net/10072/419706
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    • Conference outputs

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