YOLOv8-MSP-PD: A Lightweight YOLOv8-Based Detection Method for Jinxiu Malus Fruit in Field Conditions Article Swipe
Yi Liu
,
Xiang Han
,
Hongjian Zhang
,
Shuangxi Liu
,
Wei Ma
,
Yinfa Yan
,
Linlin Sun
,
Linlong Jing
,
Yongxian Wang
,
Jinxing Wang
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/agronomy15071581
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/agronomy15071581
Accurate detection of Jinxiu Malus fruits in unstructured orchard environments is hampered by frequent overlap, occlusion, and variable illumination. To address these challenges, we propose YOLOv8-MSP-PD (YOLOv8 with Multi-Scale Pyramid Fusion and Proportional Distance IoU), a lightweight model built on an enhanced YOLOv8 architecture. We replace the backbone with MobileNetV4, incorporating unified inverted bottleneck (UIB) modules and depth-wise separable convolutions for efficient feature extraction. We introduce a spatial pyramid pooling fast cross-stage partial connections (SPPFCSPC) module for multi-scale feature fusion and a modified proportional distance IoU (MPD-IoU) loss to optimize bounding-box regression. Finally, layer-adaptive magnitude pruning (LAMP) combined with knowledge distillation compresses the model while retaining performance. On our custom Jinxiu Malus dataset, YOLOv8-MSP-PD achieves a mean average precision (mAP) of 92.2% (1.6% gain over baseline), reduces floating-point operations (FLOPs) by 59.9%, and shrinks to 2.2 MB. Five-fold cross-validation confirms stability, and comparisons with Faster R-CNN and SSD demonstrate superior accuracy and efficiency. This work offers a practical vision solution for agricultural robots and guidance for lightweight detection in precision agriculture.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/agronomy15071581
- https://www.mdpi.com/2073-4395/15/7/1581/pdf?version=1751100116
- OA Status
- gold
- Cited By
- 1
- References
- 23
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4411834591
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4411834591Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/agronomy15071581Digital Object Identifier
- Title
-
YOLOv8-MSP-PD: A Lightweight YOLOv8-Based Detection Method for Jinxiu Malus Fruit in Field ConditionsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2025Year of publication
- Publication date
-
2025-06-28Full publication date if available
- Authors
-
Yi Liu, Xiang Han, Hongjian Zhang, Shuangxi Liu, Wei Ma, Yinfa Yan, Linlin Sun, Linlong Jing, Yongxian Wang, Jinxing WangList of authors in order
- Landing page
-
https://doi.org/10.3390/agronomy15071581Publisher landing page
- PDF URL
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https://www.mdpi.com/2073-4395/15/7/1581/pdf?version=1751100116Direct link to full text PDF
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2073-4395/15/7/1581/pdf?version=1751100116Direct OA link when available
- Concepts
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Malus, Field (mathematics), Horticulture, Environmental science, Mathematics, Biology, Pure mathematicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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23Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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