# Modeling Actual Evapotranspirationiration with MSI-Sentinel Images and Machine Learning Algorithms
## 4 Discussions  
The spectral bands of blue and red stand out in approach 1 because these wavelengths are absorbed mostly by alpha and beta-chlorophylls, resulting in the release of oxygen from photosynthesis [11; 39; 40]. It means that the magnitude of the release of this chalcogen occurs in them. Thus, the greater the absorption of blue and red wavelengths, the greater the oxygen release and, consequently, the greater the water vapor release since water vapor is released along with oxygen during photosynthesis, explaining why these spectral bands stood out. The green wavelength of the MSI sensor ranges from 0.53 to 0.59 \(\upmu\)m, and the wavelengths in this range are less absorbed by pigments [11]; thus, it impacts little on photosynthesis and water release by plants. The near-infrared is reflected and/or transmitted by the structure of the mesophyll as a form of protection of its physiological and molecular structure. Thus, this length is not related to photosynthesis but to the physiological structure that influences photosynthesis indirectly. As a result, this wavelength has less prominence than the others. The wavelengths in the short infrared are the ones that stood out in the second approach because they are spectral bands strongly absorbed by the water content present in plants [41; 42]. Therefore, when the leaves are in hydric comfort, these wavelengths tend to be more absorbed. On the other hand, when occurring hydric stress, these wavelengths tend to be less absorbed and more reflected. Several studies demonstrated the importance of shortwaves for monitoring and quantifying water stress on plants [43; 44; 45; 46]. The red edge wavelengths are also important bands in approach 2 for the same principles as the short infrared. They are absorbed by water content in plants as a \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**DAE**} & **Approach 1** & **Approach 2** & **METRIC** & \multicolumn{2}{c}{**Difference (\%)**} \\ \cline{2-6}  & **(mm)** & **(mm)** & **(mm)** & **Approach 1** & **Approach 2** \\ \hline
060 & 6.71 \(\pm\) 0.44 & 6.63 \(\pm\) 0.36 & 6.75 \(\pm\) 0.25 & 0.59 & 1.77 \\
195 & 4.52 \(\pm\) 0.22 & 4.48 \(\pm\) 0.09 & 4.78 \(\pm\) 0.06 & 5.44 & 6.28 \\
220 & 4.25 \(\pm\) 0.21 & 4.68 \(\pm\) 0.11 & 4.79 \(\pm\) 0.08 & 11.27 & 2.30 \\
275 & 3.75 \(\pm\) 0.36 & 4.32 \(\pm\) 0.20 & 4.44 \(\pm\) 0.17 & 16.54 & 2.77 \\ \hline ET-Total & 1417.77 & 1474.26 & 1544.11 & 8.18 & 4.52 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Evapotranspiration averages for coinciding dates between Sentinel-2 and Landsat-8. result of the sensitivity of red edge spectral responses to water content in plant leaves [47]. These authors mention that vegetation indices that have red edges in their equation have a higher sensitivity to water content in maize crops. [PERSON] et al. [42], studying water stress and spectral response in sugarcane crops, identified that the near-infrared wavelength was sensitive to the water content in leaves. [PERSON] et al. [43] also obtained similar results with wheat crops. Thus, it strengthens the evidence for the importance of these wavelengths in quantifying water content, even more so when they are normalized with other bands through the NRPB. This is one of the arguments stating the superior predictive capacity of approach 2 compared to approach 1. The presence of the short infrared and red edge spectral bands in approach 2 significantly improves the statistical metrics of the models. The dispersion found in ET\({}_{\mathrm{r}}F\) values lower than 0.6 in both approaches may be related to greater heterogeneity of the cultivated area. When ET\({}_{\mathrm{r}}F\) values are lower than 0.6, the crop does not completely cover the soil, and there may be patches of soil with different colors, moisture, etc., a proliferation of weeds in parts of the area, and even a greater degree of the vigor of the crop in parts of the plot. The fact that approach 1 is more dispersed than approach 2 is linked, quantitatively and qualitatively, to their predictors.