## 4 Discussion
### Spectral Signature of Hybrids
This spectral band, as well as blue, plays a fundamental role in the photosynthetic metabolism of plants [43]. Red light is intensely absorbed by chlorophyll in tissue that carries out photosynthesis, and compared to blue SB, there was little difference in reflectance between the hybrids, but the pattern of higher or lower reflectance remained the same, reinforcing the fact that hybrids with lower reflectance may have better photosynthetic performance. At wavelength G_550, hybrids H1 and H3 reflected more and in a similar pattern. Within the visible range, the green wavelength is the most reflective, because around 10 to 50% of the green wavelength is not absorbed by the leaf chloroplasts [43; 44]. The fraction of this band that is absorbed or transmitted by the plant is used in the essential processes of photosynthesis [45]. Among the roles played by the green wavelength is the CO2 assimilation used in the growth of plant biomass and yield. This SB is essential for the bottom leaves of the plant, where the blue and red wavelengths have a more limited incidence because they are more captured by the upper portion of the canopy [45; 46]. The hybrids with the highest absorption in the 550 nm band, which corresponds to green light, were the same ones that absorbed less in the blue and red wavelengths. Both wavelengths, RE and NIR, are sensitive to capturing plant reflectance, especially when plants are under stress [47] or when there are changes in the water status [48]. Due to this sensitivity, the sorghum hybrids reflected these wavelengths differently. This high reflectance above 700 nm is due to the spectrum's sensitivity to changes in chlorophyll content, which in the Rededge range is mainly carried out by chlorophyll a [49]. It is noteworthy that the hybrids that reflected less in the visible range wavelengths were the ones that absorbed the most electromagnetic radiation. This indicates that these hybrids had a higher amount of chlorophyll [50]. This suggests that they had greater photosynthetic activity, and thus are physiologically superior. Vis can provide information on several physiological parameters of the crop according to the reflectance values [35]. There was a great distinction between the hybrids for each VI used (Figure 4), even more so than between the wavelengths, because the indices used are sensitive to capturing the photosynthetically active activity of the plant canopy, leading to inferences about chlorophyll activity [51]. The VIs are calculated based on reflectance values at different wavelengths in the visible range, especially using distinct combinations between reflectances in the Rededge and NIR ranges. By combining these bands, the sensitivity of the indices to estimating chlorophyll is increased, which is further improved by combining NIR and Red, which are the most widely used for estimating plant biomass, as is the case with NDVI [52]. GNDVI is another index that is widely used in agriculture and, in this study, was able to differentiate sorghum hybrids in a similar way to NDVI. SAVI and MSAVI are indices that use medium and low-resolution images and can minimize soil influences [20], which were also able to differentiate between sorghum hybrids. Aiming at improving the efficiency of this data, associating this information with machine learning and looking for algorithms that provide accurate answers on the biophysical attributes of crops would improve the resources for evaluation in various fields [51]. [PERSON] et al. [53], combining multispectral UAV data and machine learning algorithms achieved good accuracy in soybean classifications regarding grain industrial variables. There is an example of this distinction, it is possible to observe in Figure 1, an example with an NDVI map showing the variability between hybrids, which was possible to be distinguished by ML techniques.