## 3 Results and Discussion
### Ablation Study
#### 3.6.3 Overall Strategies  
To validate the effectiveness of the proposed strategy, a series of ablation experiments were conducted on the SBDS dataset (see Table 5). By replacing the bottleneck part of C2f in the backbone network with PCIB, an improvement of 0.3% in mAP\({}_{0.5}\) was achieved compared to the baseline model, while the number of parameters only increased by 0.2 M. This indicates that the replacement with PCIB effectively enhanced the feature extraction capability of the network without a significant increase in the number of parameters. Further, when MS-FPN was employed as the neck network, although there was an increase in the parameters and FLOPs of the model, the precision and mAP\({}_{0.5}\) improved by 1.2% and 1.0%, respectively. This improvement addressed the deficiencies in fine-grained information loss during the upsampling and feature fusion processes of existing feature pyramids. Additionally, with the inclusion of Focaler-shape-IoU, the recall and mAP\({}_{0.50.95}\) increased by 0.4% and 0.3%, respectively, which resolved the imbalance between easy and difficult samples and significantly enhanced the detection accuracy in complex scenarios such as overlaps and occlusions. After integrating these strategies, our model achieved improvements of 2.0%, 1.3%, and 1.7% in precision, recall, and mAP\({}_{0.5}\), respectively, compared to the baseline model. Although the parameters and computational complexity slightly increased, the model's information extraction and feature fusion capabilities were significantly enhanced. Notably, the model maintained real-time performance with an FPS reduction from 121.6 to 87.5, meeting the requirements for real-time deployment in strawberry ripeness detection. These results underscore the significant effectiveness of our model in improving detection performance while maintaining feasibility for practical applications in agricultural automation. We further intuitively compared the differences in strawberry ripeness detection performance between our model and the baseline model. As shown in Figure 11, the test results of the baseline model are presented in Figure 11a,c, while the results of our improved model are displayed in Figure 11b,d. In Figure 11a, the strawberry labeled as \"r\" was not detected due to its overlap with another larger strawberry, reflecting the baseline model's insufficient feature extraction capability when dealing with strawberries whose colors are similar to the background. Similarly, the high degree of overlap between a half-ripe and a ripe strawberry led to the misdetection of two strawberries labeled as \"s\" as a single half-ripe strawberry, further highlighting the baseline model's limitations in handling overlapping targets. In Figure 11c, the strawberries labeled as \"t\" and \"u\" were not detected due to their small size, revealing the baseline model's limitations in detecting small targets. Meanwhile, the strawberry labeled as \"v\" greatly overlapped another larger \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**CIoU** & **Shape-IoU** & **Focaler-IoU** & **Precision** & **Recall** & **mAP\({}_{0.5}\)** & **mAP\({}_{0.75}\)** & **mAP\({}_{0.50.95}\)** \\ \hline \(\surd\) & & & 90.1 & 85.2 & 91.0 & 82.7 & 75.1 \\ \(\surd\) & & & \(\surd\) & 90.4 & 85.4 & 91.2 & 82.9 & 75.2 \\  & \(\surd\) & & 90.3 & 85.4 & 91.3 & 82.9 & 75.3 \\  & \(\surd\) & \(\surd\) & 90.4 & 85.5 & 91.4 & 83.1 & 75.3 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Ablation experiments of Focaler-shape-IoU on the SBDS dataset. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**CloU** & **Shape-IoU** & **Focaler-IoU** & **Precision** & **Recall** & **mAP\({}_{0.5}\)** & **mAP\({}_{0.75}\)** & **mAP\({}_{0.50.95}\)** \\ \hline \(\surd\) & & & 90.1 & 85.2 & 91.0 & 82.7 & 75.1 \\ \(\surd\) & & & \(\surd\) & 90.4 & 85.4 & 91.2 & 82.9 & 75.2 \\  & \(\surd\) & & 90.3 & 85.4 & 91.3 & 82.9 & 75.3 \\  & \(\surd\) & \(\surd\) & 90.4 & 85.5 & 91.4 & 83.1 & 75.3 \\ \hline \hline \end{tabular}
\end{table}