3.3.2. Estimated Stem Water Potential

The difference between the measured and estimated SWP values was calculated per MC for each canopy extraction and temperature calculation method, highlighting the differences between the datasets (Figure 9). A value of zero indicates no difference between the measured and estimated SWP. Positive values indicate that the estimated SWP is lower (more negative, the MC more stressed) than the measured SWP. Conversely, negative values indicate that the estimated SWP value is higher (less negative, the MC less stressed) than the measured SWP values. The average difference between the measured and estimated SWP (SWPe\_T100%) in the RGB-BM dataset is substantially higher in comparison to the other canopy extraction methods and indicates a shift to more positive values, in comparison to the SWPe\_T33% values. The MSE and RMSE values reinforce this point and indicate that the SWPe\_T100% values of both the RGB-BM and the VS extraction methods are higher than the measured SWP values, indicating that the extraction quality is poorer than the 2PE and ED methods. The average differences between the measured and estimated SWP (SWPe\_T33%) for each extraction method are mostly negative and close to zero. The histogram analysis, MSE, and RMSE all indicate that the 2PE, ED, and VS methods are similar to each other, while the RGB-BM is slightly different. These results suggest that theoretical irrigation decisions based on the SWPe\_T33% values of the 2PE, ED, and VS methods would yield similar results.

**Figure 9.** The histogram of the difference between the measured and estimated stem water potential (SWPe) calculated using the canopy temperature data of the average 100% (SWPe\_T100%) (pink bars) and the average of the coolest 33% (SWPe\_T33%) (blue bars) of canopy pixels for the 2-pixel erosion (2PE), edge detection (ED), vegetation segmentation (VS), and RGB binary masking (RGB-BM) canopy extraction methods. The frequency refers to the number of management cells (MC). The table insert provides the descriptive statistics of each dataset. Note: the Y-axis range of the RGB-BM method is specifically different from the other methods.

The distribution of the SWPe\_T100% and SWPe\_T33% values for each canopy extraction method were compared to the defined optimal SWP range for stage III (between −1.17 and −1.43 MPa) (Figure 10). Within the SWPe\_T100% dataset, the RGB-BM distribution is noticeably offset to more negative SWP values, and a substantially high percentage of below-range values (75%) were calculated, indicating that the orchard was estimated to be under greater stress in comparison to the 2PE and ED methods. Forty-three percent of the VS method's SWPe values are below the optimum range. The majority of the SWPe values of the 2PE and ED (63%) methods are within the optimal range of orchard water

status. The SWPe\_T33% dataset is characterized by a higher percentage of values within the optimal range of orchard water status for each canopy extraction method in comparison to the SWPe\_T100% dataset. Additionally, the variance of the SWPe\_T33% values is substantially smaller in comparison to the SWPe\_T100% dataset for each extraction method. A negligible percentage of above-range SWPe values was calculated, indicating that the orchard is theoretically not over-irrigated. The measured SWP distribution is similar to the SWPe\_T100% ED method dataset.

**Figure 10.** Histogram of percent estimated stem water potential (SWPe) (MPa) calculated using the canopy temperature data of the average 100% (SWPe\_T100%) and the average of the coolest 33% (SWPe\_T33%) of canopy pixels in comparison to the defined optimal SWP range for stage III: upper (−1.17 Mpa, blue dashed line) and lower (−1.43 Mpa, red dashed line) thresholds. Below-range SWP values indicate orchard stress, while above-range water status values indicate theoretical overirrigation. The canopy extraction methods tested were 2-pixel erosion (2PE, turquoise polygon), edge detection (ED, blue polygon), vegetation segmentation (VS, pink polygon), and RGB binary masking (RGB-BM, red polygon).
