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Forests
Special Issues
Harvesting, Processing and Management of Specialty Forest Products and Biomass
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Harvesting, Processing and Management of Specialty Forest Products and Biomass

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Operations and Engineering".

Deadline for manuscript submissions: 20 April 2026 | Viewed by 1820

Special Issue Editors

Dr. Xiaopeng Bai

E-Mail Website
Guest Editor
School of Technology, Beijing Forestry University, Beijing 100083, China
Interests: intelligent equipment; harvesting and processing technology; high-value utilization technology of biomass; application of AI in bioenergy systems
Prof. Dr. Wenbin Li

E-Mail Website
Guest Editor
School of Technology, Beijing Forestry University, Beijing 100083, China
Interests: automation and intelligence of forestry equipment; human engineering; forest environmental information monitoring
Dr. Ruifang Dong

E-Mail Website
Guest Editor
School of Technology, Beijing Forestry University, Beijing 100083, China
Interests: SLAM; navigation and localization for forestry robot; environment perception

Special Issue Information

Dear Colleagues,

This Special Issue welcomes contributions on technological innovations across the entire value chain of specialty forest products and forest grass resources, including, but not limited to, the following areas:

1. Harvesting and Processing of Specialty Forest Products:

  • Equipment and system development for specialty forest product harvesting and processing (e.g., Walnut, Lycium barbarum, Blueberry, Soapberry, Grape, Camellia fruit, Torreya).
  • Quality detection and production forecasting of specialty forest products, alongside quality assessment of forest biomass-derived materials.
  • Autonomous navigation, obstacle avoidance, target identification, and positioning technologies for complex orchard environments.
  • Three-dimensional reconstruction and measurement for forestry environment, intelligent pruning, and other automated management tasks.

2. High-Value Utilization of Agricultural and Forestry Biomass:

  • Efficient utilization technologies and equipment for forest and grass biomass.
  • Energy conversion through compression moulding, gasification, liquefaction, and pretreatment (e.g. torrefaction, pyrolysis, steam explosion, dry explosion, etc.).
  • Advanced processing technologies, from the fabrication of novel materials to the green extraction and value-added utilization of bioactive compounds.

3. Intelligent Forestry Operations:

  • Route planning and operation management.
  • Monitoring of operations, perception, and decision-making systems for forestry machinery.
  • Digital twin and AI applications for forestry optimization.

4. Sustainability Assessment and System Optimization:

  • Life cycle assessment of harvesting and processing technologies.
  • Techno-economic analysis of integrated production systems.
  • Ecological impact and sustainable management strategies.

Dr. Xiaopeng Bai
Prof. Dr. Wenbin Li
Dr. Ruifang Dong
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • harvesting and processing
  • specialty forest fruits
  • biomass and bioenergy
  • forestry operations
  • sustainability assessment

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

38 pages, 150385 KB  
Article
ERD-YOLO-DMS: A Multi-Domain Fusion Framework for High-Speed Real-Time Online Plywood Veneer Detection
by Hongxu Li, Zhihong Liang, Mingming Qin, Shihuan Xie, Yuxiang Huang, Xinyu Tong and Linghao Dai
Forests 2026, 17(4), 404; https://doi.org/10.3390/f17040404 - 24 Mar 2026
Viewed by 189
Abstract
Plywood has emerged as a key sustainable material in modern building. Yet, ensuring its consistent performance requires rigorous quality control of the rotary-cut veneers used in its manufacture. This task is complicated by the high-speed nature of industrial conveyors, where motion blur and [...] Read more.
Plywood has emerged as a key sustainable material in modern building. Yet, ensuring its consistent performance requires rigorous quality control of the rotary-cut veneers used in its manufacture. This task is complicated by the high-speed nature of industrial conveyors, where motion blur and the complex, varying textures of eucalyptus wood drastically reduce the effectiveness of real-time surface inspection. This study proposes an intelligent, real-time defect detection system specifically optimized for the diverse defect morphology of eucalyptus veneers. A lightweight model, YOLOv11-DMS-Veneers, was developed by integrating MobileNetV4 as the backbone, a Dynamic Head for multi-scale feature extraction, and a Shape-IoU loss function to precisely localize irregular defects like cracks and knots. Additionally, an ERD video enhancement framework (combining ESRGAN, RIFE, and DnCNN) was implemented to mitigate motion blur in dynamic environments. Experimental results demonstrate that the proposed model achieves a mean Average Precision (mAP@50) of 96.0% and a Precision of 95.7% with a low computational cost of only 4.5 GFlops, significantly outperforming traditional algorithms. Notably, the detection precision for challenging linear cracks reached 93.9%. In dynamic tests at conveyor speeds up to 24 m/min, the video enhancement strategy increased the average detection confidence by 0.288, maintaining a maximum confidence of 0.890. This technology offers a robust solution for the automated quality control of eucalyptus veneers, facilitating the production of high-performance plywood and advancing the efficient application of engineered wood in the building industry. Full article
(This article belongs to the Special Issue Harvesting, Processing and Management of Specialty Forest Products and Biomass)
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27 pages, 6957 KB  
Article
Research on AGV Path Optimization Based on an Improved A* and DWA Fusion Algorithm
by Kun Wang, Shuai Li, Mingyang Zhang and Jun Zhang
Forests 2026, 17(1), 31; https://doi.org/10.3390/f17010031 - 26 Dec 2025
Viewed by 678
Abstract
Forestry environments—such as logging sites, transport trails, and resource monitoring areas—are characterized by rugged terrain and irregularly distributed obstacles, which pose substantial challenges for AGV route planning. This poses challenges for route planning in automated guided vehicles (AGVs) and forestry machinery. To address [...] Read more.
Forestry environments—such as logging sites, transport trails, and resource monitoring areas—are characterized by rugged terrain and irregularly distributed obstacles, which pose substantial challenges for AGV route planning. This poses challenges for route planning in automated guided vehicles (AGVs) and forestry machinery. To address these challenges, this study proposes a hybrid path optimization method that integrates an improved A* algorithm with the Dynamic Window Approach (DWA). At the global planning level, the improved A* incorporates a dynamically weighted heuristic function, a steering-penalty term, and Floyd-based path smoothing to enhance path feasibility and continuity. In terms of local planning, the improved DWA algorithm employs adaptive weight adjustment, risk-perception factors, a sub-goal guidance mechanism, and a non-uniform and adaptive sampling strategy, thereby strengthening obstacle avoidance in dynamic environments. Simulation experiments on two-dimensional grid maps demonstrate that this method reduces path lengths by an average of 6.82%, 8.13%, and 21.78% for 20 × 20, 30 × 30, and 100 × 100 maps, respectively; planning time was reduced by an average of 21.02%, 16.65%, and 9.33%; total steering angle was reduced by an average of 100°, 487.5°, and 587.5°. These results indicate that the proposed hybrid algorithm offers practical technical guidance for intelligent forestry operations in complex natural environments, including timber harvesting, biomass transportation, and precision stand management. Full article
(This article belongs to the Special Issue Harvesting, Processing and Management of Specialty Forest Products and Biomass)
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21 pages, 3827 KB  
Article
Detection of Printing Defects on Wood-Derived Paper Products Using an Improved YOLOv8n
by Mingyang Zhang, Shuai Li, Jun Zhang, Xiaopeng Bai, Kun Wang and Hongxia Yuan
Forests 2025, 16(12), 1818; https://doi.org/10.3390/f16121818 - 5 Dec 2025
Viewed by 571
Abstract
Paper-based printing materials originate from the wood-based value chain–wood–pulp–paper–printing—and their yield reflects the utilization efficiency of pulp and paper resources. In roll-to-roll printing production, small printing defects (e.g., missing prints, smudges, cracks) often cause rework and scrap, thereby increasing the consumption of wood-derived [...] Read more.
Paper-based printing materials originate from the wood-based value chain–wood–pulp–paper–printing—and their yield reflects the utilization efficiency of pulp and paper resources. In roll-to-roll printing production, small printing defects (e.g., missing prints, smudges, cracks) often cause rework and scrap, thereby increasing the consumption of wood-derived materials. To improve resource efficiency, this study proposes a lightweight, improved YOLOv8n model for real-time small-defect detection. The Efficient IoU (EIoU) loss is introduced in the bounding box regression stage to improve localization accuracy, and a Squeeze-and-Excitation (SE) channel attention mechanism is embedded in the feature fusion stage to strengthen feature representation for small printing defects. Evaluations conducted on datasets collected from real production lines demonstrate that, with 3.02 M parameters and 8.1 GFLOPs, the model achieves mAP@0.5 = 94.1%, Precision = 95.1%, Recall = 94.3%, and an inference speed of 100.2 FPS, outperforming the baseline model. The proposed method contributes to reducing rework and material waste, supporting the efficient utilization of wood resources and the sustainable development of the paper-based packaging industry. Full article
(This article belongs to the Special Issue Harvesting, Processing and Management of Specialty Forest Products and Biomass)
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