Yan, Jingyu, Duan, Huichuan, Xu, Rongfeng, Sun, Meili, Ji, Ze  ORCID: https://orcid.org/0000-0002-8968-9902, Xu, Li and Jia, Weikuan
2025.
Mrtic Det: A structure aware detection framework for thinning stage fruit in non structured orchards.
Computers and Electronics in Agriculture
239
(Part A)
, 110940.
10.1016/j.compag.2025.110940
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Abstract
The thinning period in orchards poses significant challenges, including small object detection, occlusions, dense distributions, and size variations. To address these issues, this study proposes MRtic-Det, an advanced object detection model designed to enhance accuracy and efficiency in fruit detection tasks. Built on the RT-DETR-L architecture, MRtic-Det incorporates the MODMamba backbone for superior feature extraction and the CrossSourceMerge Neck to improve multi-scale information fusion by integrating high-level spatial features with low-level visual cues. Additionally, a P2 layer detection head is introduced to strengthen small-object detection capabilities. The performance of MRtic-Det is evaluated on two self-collected datasets, including an apple thinning dataset and a golden pear thinning dataset. Experimental results demonstrate significant improvements, with MRtic-Det achieving an AP50 increase of 4.9 percentage points and an AP50-95 increase of 5.8 percentage points on the apple thinning dataset, while reducing model parameters by 45.4 %. The golden pear thinning dataset further validates the model’s generalization capability, underscoring its adaptability to various fruit types and orchard environments. MRtic-Det offers a robust and efficient solution for fruit thinning robots, advancing the field of precision agriculture.
| Item Type: | Article |
|---|---|
| Date Type: | Publication |
| Status: | Published |
| Schools: | Schools > Engineering |
| Publisher: | Elsevier |
| ISSN: | 0168-1699 |
| Date of First Compliant Deposit: | 1 October 2025 |
| Date of Acceptance: | 26 August 2025 |
| Last Modified: | 03 Sep 2026 01:45 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/181089 |
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