## 5 Results and Analysis
### Evaluation of the Accuracy of Axillary Bud Removal Point Positioning  
When the robot end effector performs the pruning task, ensuring the accuracy of the pruning point is critical. In order to evaluate the accuracy of the pruning points, two evaluation criteria have been established as follows: Rule 1: The removal point is on the axillary branch; and Rule 2: The distance from the removal point to the junction of the main branch and the axillary branch is less than 1 cm, i.e., the stump length is less than 1 cm. Pruning points that meet both of these criteria are considered to be accurately identified.  
To establish a correlation between the actual length of the axillary bud stump and the pixels in the image, the concept of pixels per inch (_PPI_) must be considered. Pixel density refers to the number of pixels per inch of screen, usually expressed in pixels per inch (_PPI_), and is calculated using the following formula:  
\[PPI=\frac{\sqrt{W^{2}+H^{2}}}{S} \tag{17}\]  
where \(W\) and \(H\) are the resolution width and height of the resolution, and \(S\) is the screen size. The general formula for the actual length corresponding to the pixels in the image is as follows:  
\[\text{Actual length}(CM)=\frac{2.54}{PPI}\times\text{Pixel value} \tag{18}\]  
In order to match the image processing results with the practical requirements of agricultural operations, a statistical method based on pixel intervals was used, where every 50 pixels was treated as an interval. The number of pixels within these intervals and their corresponding actual lengths were statistically analyzed, as shown in Table 3. From Table 3, it can be seen that within the [0, 150] pixel interval, the actual length of the armpit is less than 1 cm, thus meeting the criteria for armpit removal. However, below the interval with the highest pixel value, we used a different partitioning method to simplify the analysis, as the pixel values in this interval no longer have any practical agronomic significance for locating armpit removal points. Calculation of the actual length corresponds to the pixel values according to the above formula. To ensure the results of the image processing correspondent with the practical requirements of agricultural operations, a statistical method based on pixel intervals was adopted, where every 50 pixels were treated as an interval. Statistical analysis was conducted on the number of pixels within these intervals and their corresponding actual lengths, as shown in Table 3. From Table 3, it can be observed that within the [0, 150] pixel interval, the actual length of the armpit is less than 1 cm, satisfying the criteria for armpit removal.  
Figure 11: VGG16-UNet model segmentation visualization results.  
Figure 12 uses a pie chart to statistically analyze whether all detected axillary bud removal points meet Rule 1, which refers to the number of removal points located on the axillary buds. According to the statistics in Figure 12, there are a total of 701 axillary bud objects, of which 643 removal positions are located on the axillary buds. Therefore, the recognition accuracy of Rule 1 is 91.7%.  
Figure 13 shows, by means of a pie chart, whether all the detected axillary bud removal points meet Rule 2, which states that the stubble length should be less than 1 cm. Based on the statistics from Figure 13, of the 701 axillary bud objects, 653 have a stubble length of less than 1 cm. Therefore, the detection rate of Rule 2 is 93.2%.  
Table 4 provides a comprehensive evaluation of the detection accuracy for Rule 1 and Rule 2. In practical applications, accuracy and compliance with agricultural standards for pruning operations by the robot end effector are only ensured when both rules are satisfied simultaneously. Based on the integrated assessment of Rule 1 and Rule 2, the overall accuracy rate for axillary bud removal points is 85.5%.