| dc.description.abstract | The increasing demand of wheat and the incidence of extreme weather events demand the development of high yielding wheat cultivars with resilience to extreme heat events. Photoprotective traits, as cuticular waxes, support the plant to maintain the photosynthetic activity, decrease stomatal water loss and regulate the plant’s internal temperature under extreme abiotic stress. The work described in this dissertation aims to develop new tools for phenotyping epicuticular wax and grain yields that can potentially contribute to accelerate the genetic gain of wheat to fulfill the demand of this economically important cereal by 2050. The objectives of this study were; i) to understand the role of leaf EW as a photoprotective mechanism for adaptation, ii) develop reliable and efficient indirect selection methodologies for the accurate estimation of EW content, and iii) define selection indices for indirect estimation of GG of GY under heat stress environments incorporating the spectral response of the plant.
For the first objective, a set of RIL’s was evaluated under controlled conditions. The light reflectance of wavelength at the visible region were highly associated with EW. For the estimation of EW with a leaf clip spectroradiometer, three empirical spectral indices were developed: EWI-1 Blue/Red, EWI-2 Blue/NIR, EWI-15 625 (1/736 – 1/832) and EWI-16 (625-736) / 832. Two additional linear models are also proposed, the Model-10 and Model-11. For the second objective, a set of spring wheat landraces and product of interspecific hybridization was evaluated under severe heat stress conditions. The canopy reflectance of the NIR and SWIR was highly associated with the EW load of the flag leaves. For field phenotyping, the spectral indices DIB-2, DIB-3, and the linear model MB-DI-2 provided a reliable indirect estimation of the EW content in leaves. And for the last objective, the canopy reflectance obtained in the second study was evaluated for indirect selection of the GG of the wheat genotypes. Indirect selection with the Smith/Hazel index did not provide any additional GG when the components of GY were incorporated. The best parameters for indirect selection based on indices were BIO; the broadband vegetation indices ARI, ReCl, NDII, SAVI, GRVI and TDVI; and the narrow band vegetation index NDVI. | en |
