## 4 Discussion
The three traits were better correlated with wavelengths in the SWIR region than with wavelengths in the NIR region at the BT stage, and the opposite was found at the AN and EMG stages, with a few exceptions (Figure 4). These findings revealed that in using hyperspectral reflectance tools, specific wheat growth stages must be taken into account when phenotyping the plant traits for a large number of genotypes. These findings also suggest that the hyperspectral reflectance tool can be applicable in salinity studies for assessing plant biomass and for effectively screening wheat genotypes at the early growth stage, obviating the need to grow genotypes to maturity, but thissuggestion is only applicable by looking at specific wavelengths in the red-edge and SWIR regions as shown in Figure 4. Generally, the spectral reflectance at wavelengths in the VIS, NIR, and SWIR regions is affected primarily by the vegetation growth status (contents of chlorophyll and other photosynthetic pigments), plant biomass status (cumulative plant biomass, canopy structure, and leaf cellular structure), and plant water status (content of canopy water and material absorbed light such as lignin, cellulose, protein, and cell walls), respectively [73; 74; 75; 76; 77; 78]. According to [PERSON] [24], plant biomass responds to salinity stress in two phases, referred to as the osmotic phase and ionic phase. In the first phase, the plant canopy begins to show symptoms of a water deficit because the high salt concentrations in the root zone restrict the capacity of roots to uptake sufficient water. In the second phase, which corresponds to the build-up of harmful ions (Na\({}^{+}\) and Cl\({}^{-}\)) in the leaves, necrosis and senescence are the main canopy symptoms. These two phases of salinity stress, in addition to the close relationship between spectral reflectance at specific wavelengths and plant canopy characteristics may explain why the relationships between SWIR wavelengths and plant biomass are stronger at the early stage (BT) than those in the VIS and NIR regions, and vice versa at the later stages (AN and EMG stages). Identification of the Best Spectral Reflectance Indices and Growth Stage for Indirect Biomass Assessment  
Previous studies have reported that SRIs can be used as indirect alternative evaluation tools for providing rapid and accurate assessment of stress-related traits [13; 17; 19; 50; 79; 80]. However, SRI type (vegetation- or water-based), sampling date (phenological growth stages), and the degree of genotypic variation for SRIs play a key role in the capability of SRIs to accurately assess and monitor plant traits of interest. In the case of the SRI type, previous studies reported that in capturing genotypic variability in grain yield and biomass under diverse environmental conditions, water-related SRIs, which are calculated from wavelengths located in the NIR and SWIR regions, always performed better than the vegetation-related SRIs, which are calculated from wavelengths located in the VIS and red-edge regions [19; 36; 63; 79; 81]. Because there is a significant interaction between growth stages and genotypes for different SRIs, the suitable growth stage for assessing the plant traits based on SRIs must be cautiously identified to accurate assessment of the most effective plant traits among genotypes. In wheat, most previous studies reported that the majority of SRIs were sensitive to variation in measured plant traits (i.e., plant biomass and grain yield) when recorded after the heading stage (AN and EMG stages). Combining SRIs across multiple stages also gave a better correlation with plant traits than any individual growth stage [17; 21; 44; 63; 79; 81; 82; 83]. This study dealt with the abovementioned three factors and found that a significant genotypic variation was observed for all SRIs (Table 2), with a wide range between the minimum and maximum values for these indices at different stages separately and across three stages (Table 3).