## 4 Discussion  
Previous studies have reported that whole-plant biomass is considered one of the most useful phenotypic traits to evaluate genotypes in breeding programs under both normal and stress conditions. This is because this plant trait reflects several physiological processes, integrates plant responses to stresses at the whole-plant level and at different growth stages, and is directly related to radiation use efficiency and final crop production [19; 21; 22; 28; 66; 67]. Interestingly, this study confirmed that plant biomass measured at booting (BDW-BT) and antihesin (BDW-AN) growth stages, as well as the BY measured at maturity, are important phenotypic traits for differentiating salt tolerance among genotypes. We observed a sufficient genotypic variation for these traits (i.e., genotype had a highly significant main effect on these traits (\(p<0.0001\)) with a wide range between the minimum and maximum values for these traits across genotypes (Figure S1). This wide range of genotypic variation in plant biomass at different growth stages indicates that some tested genotypes might possess more efficient mechanisms than others to cope with the osmotic injury and specific ion toxicity effects of salinity stress. This further indicates that measurements of biomass at different growth stages can be used as potential screening criteria for differentiating salt tolerance behavior between wheat genotypes. Unfortunately, the direct assessment of plant biomass based on destructive sampling methods is generally time- and cost-inefficient, tedious, and unable to detect the dynamic changes of this trait in real time. Tools that are rapid, nondestructive, and cost-efficient are therefore urgently needed to assess plant biomass, particularly when plant breeders wish to incorporate this plant trait into breeding programs as screening criteria to evaluate the salt tolerance of a large number of genotypes across different growth stages. In general, exposing plants to high-salinity levels leads to noticeable changes and modifications in several morphological, anatomical, biochemical, and physiological plant characteristics [5; 68; 69; 70]. Fortunately, the characteristics of spectral signatures that are reflected from the plant canopy at specific full-spectrum wavelengths using hyperspectral sensors are usually closely associated with these changes [5; 42; 45; 71; 72]. This reveals that it is possible to rapidly and nondestructively assess plant biomass for large germplasm collections based on genotypic variation in the spectral reflectance behavior over the full-spectrum range. Interestingly, the results in Figure 1 revealed that there are obvious differences between the minimum and maximum values of spectral reflectance across all genotypes in the three main regions of the spectrum at three different growth stages, with a few exceptions. Additionally, the standard deviation of spectral reflectance across all genotypes is highest in the VIS and SWIR regions at the EMG stage and in the three regions of the spectrum at the AN stage (Figure 3). This genotypic variation in spectral reflectance behavior makes the hyperspectral reflectance tool a promising technique for providing crucial information for genotype selection and management of abiotic stresses and allows for the effective evaluation of a large number of genotypes without compromising the accuracy of conventional phenotyping methods through repetitive assessments of screening criteria of interest. The results in Figure 4 further confirmed this and indicated that the three traits (BDW-BT, BDW-AN, and BY) showed significant correlation with the wavelengths in the three regions of the spectrum. However, the value of correlation between traits and wavelengths depends on growth stages. The wavelengths in the VIS region exhibited a weak correlation (not significant) with the three traits at the BT stage, and they showed weak to strong correlations (r ranged from \(-0.25\) to \(-0.80\)) with the three traits at the AN and EGM stages.