###### Abstract
The spectral reflectance at blue, green (520-580 nm), red (640-680 nm), red-edge, and near-infrared (NIR, 350-700 nm) regions were also found to be sensitive to salt stress in different field crops [13; 33; 34; 35]. [PERSON] et al. [15] also found that the spectral reflectance of cotton at the NIR and shortwave-infrared (SWIR, 1300-2500 nm) regions showed obvious differences between five salinity levels, and these differences were most obvious in three spectrum regions: (1) 920 to 1120 nm, (2) 1650 to 1850 nm, and (3) 2000 to 2400 nm. Consequently, these close associations between plant characteristics and spectral reflectance of the canopy at these three spectrum regions indicate that the high-throughput phenotyping technique (HTPT) is a promising salt-response screening tool that can be incorporated in plant breeding. Currently, the feasibility of using HTTP to evaluate several genotypes under normal and varying abiotic stresses, particularly drought stress, was reported in different field crops [19; 36; 37; 38; 39]. However, few studies have tried to identify salt tolerance in wheat genotypes using HTTP. Additionally, almost all of these studies reported the spectral evaluation of a relatively small number of genotypes, leaving a substantial field to be explored by researchers addressing the use of HTTP to evaluate a large number of genotypes. Generally, HTTP data have often been exploited as an indirect screening tool after they are used to establish specific spectral reflectance indices (SRIs). These SRIs are usually obtained by incorporating two or three spectral bands in simple mathematical formulas. Importantly, the majority of the published SRIs are usually developed on the basis of their relationships with various plant traits. Therefore, several SRIs have been widely applied to rapidly and nondestructively assess several plant traits under either control or stress conditions [15; 19; 39; 40; 41; 42; 43; 44; 45; 46]. For example, the normalized difference vegetation index (NDVI), photochemical reflectance index, water index (WI), and normalized difference water index (NDWI) were each found to be sensitive to salinity stress. Therefore, they are widely applied to delineate the negative impacts of salinity stress on plant growth and production in different crops [15; 19; 20; 31; 35; 47; 48; 49]. [PERSON] et al. [34] reported a possibility of providing an early warning of salinity effects on the growth of eggplant and cauliflower plants through seven SRIs that are concentrated mainly in the green, red, and NIR regions. [PERSON] et al. [50] estimated the genotypic differences in shoot fresh wheat between two spring wheat genotypes under salinity stress using the NDVI and simple ratio indices: R780/R550 and R760/R670. However, the use of SRIs as simple and rapid tools for genotype evaluation in a breeding program requires identification of the plant growth stage in which the maximum genotypic differences appear. Because several factors have been found to affect canopy spectral reflectance signatures, and some SRIs may be more effective under certain conditions but are not suitable under other conditions, it is necessary to test the performance of published SRIs with different crops, abiotic stresses, and locations. The need to further validate the published SRIs for phenotyping the plant traits related to the salinity tolerance of genotypes remains. Because most SRIs include only two to three wavelengths, they tend to perform poorly at early growth stages, particularly vegetation-related-SRIs. Poor performance may also be due to the saturation problems that are observed with a high leaf area index, above-ground biomass, and chlorophyll content [39; 51]. Additionally, the performance of SRIs in the estimation of traits is influenced by their limited wavelengths when measured across various growth conditions [44; 49]. Most SRIs exhibit substantial multicollinearity among themselves because they are formulated from broad wavelengths with similar reflectance and absorption behaviors exhibited by the plant canopy.