Potential of the existing and novel spectral reflectance indices for estimating the leaf water status and grain yield of spring wheat exposed to different irrigation rates
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DOI: 10.1016/j.agwat.2019.03.006
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References listed on IDEAS
- Elsayed, Salah & Elhoweity, Mohamed & Ibrahim, Hazem H. & Dewir, Yaser Hassan & Migdadi, Hussein M. & Schmidhalter, Urs, 2017. "Thermal imaging and passive reflectance sensing to estimate the water status and grain yield of wheat under different irrigation regimes," Agricultural Water Management, Elsevier, vol. 189(C), pages 98-110.
- El-Hendawy, Salah E. & Hassan, Wael M. & Al-Suhaibani, Nasser A. & Schmidhalter, Urs, 2017. "Spectral assessment of drought tolerance indices and grain yield in advanced spring wheat lines grown under full and limited water irrigation," Agricultural Water Management, Elsevier, vol. 182(C), pages 1-12.
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- Adel H. Elmetwalli & Yasser S. A. Mazrou & Andrew N. Tyler & Peter D. Hunter & Osama Elsherbiny & Zaher Mundher Yaseen & Salah Elsayed, 2022. "Assessing the Efficiency of Remote Sensing and Machine Learning Algorithms to Quantify Wheat Characteristics in the Nile Delta Region of Egypt," Agriculture, MDPI, vol. 12(3), pages 1-21, February.
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Keywords
Equivalent water thickness; Estimated evapotranspiration; Hyperspectral reflectance; Leaf water potential; Phenotyping; Wavelength selection;All these keywords.
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