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Recent Advances in Nondestructive Evaluation of Wood: In-Forest Wood Quality...
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Recent Advances in Nondestructive Evaluation of Wood: In-Forest Wood Quality Assessments—2nd Edition

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

Deadline for manuscript submissions: 30 September 2025 | Viewed by 3394

Special Issue Editors

Dr. Xiping Wang

E-Mail Website
Guest Editor
Forest Products Laboratory, USDA Forest Service, Madison, WI 53726, USA
Interests: nondestructive testing and evaluation of wood; wood quality assessment; measuring wood properties; heat treatment for invasive species; structural condition assessment
Special Issues, Collections and Topics in MDPI journals
Dr. Brunela Pollastrelli Rodrigues

E-Mail Website
Guest Editor Assistant
Wood Utilization and Biomaterials, Department of Forestry and Environmental Conservation, College of Agriculture, Forestry and Life Sciences, Clemson University, 126 Lehotsky Hall, Clemson, SC 29634, USA
Interests: wood quality; quantitative wood anatomy; nondestructive evaluation of wood; biomass utilization

Special Issue Information

Dear Colleagues,

Recent research and development of nondestructive testing technologies has brought in-forest assessments of the wood and fiber properties of standing trees into forest management, resource evaluations, harvesting operations, and efficient wood utilization. Significant values are associated with the wood and fiber quality of forests used for the production of structural lumber, engineered wood products (such as glulam, LVL, and CLT), and pulping and paper. Rapid and nondestructive measurements of trees allow for these values to be captured through more effective silvicultural practices, as well as the allocation of resources to the highest value users and the application of the best processing methods. This Special Issue calls for research papers on in-forest wood quality assessments using emerging nondestructive and precision-based technologies and wood quality modeling with a focus on forest resource evaluation and wood utilization. Examples include SilviScan™, near infrared, DiscBot, acoustic waves, resistance drilling, and other novel concepts and methods. Moreover, we invite original papers and reviews that address how these technologies and the knowledge obtained from them can support the development of the next generation of forests, e.g., through tree breeding and silviculture.

Dr. Xiping Wang
Guest Editor

Dr. Brunela Pollastrelli Rodrigues
Guest Editor Assistant

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 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • forest
  • forest management
  • genetic improvement
  • nondestructive testing and evaluation
  • silviculture
  • standing trees
  • wood and fiber properties
  • wood quality
  • wood utilization

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Published Papers (5 papers)

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15 pages, 4415 KiB  
Article
Interference of Edaphoclimatic Variations on Nondestructive Parameters Measured in Standing Trees
by Carolina Kravetz, Cinthya Bertoldo, Rafael Lorensani and Karina Ferreira
Forests 2025, 16(3), 535; https://doi.org/10.3390/f16030535 - 19 Mar 2025
Viewed by 293
Abstract
The diversity of commercial tree planting sites, with their distinct environmental conditions, directly influences tree growth and consequently impacts the wood properties in various ways. However, there is limited research evaluating the impact of these variations in nondestructive testing. Therefore, this study aimed [...] Read more.
The diversity of commercial tree planting sites, with their distinct environmental conditions, directly influences tree growth and consequently impacts the wood properties in various ways. However, there is limited research evaluating the impact of these variations in nondestructive testing. Therefore, this study aimed to investigate whether edaphoclimatic variations affect parameters obtained through nondestructive tests conducted on standing trees. To this end, 30 specimens were selected from 3 Eucalyptus sp. clones, aged 1, 3, and 4 years, grown in 2 regions, totaling 540 trees. Tree development was monitored quarterly over 12 months. The tests included ultrasound propagation, drilling resistance, and penetration resistance, and the trees were measured for diameter at breast height (DBH) and height. Among the edaphoclimatic factors evaluated, only temperature and soil water storage differed statistically between the two study regions. The higher temperature and lower soil water storage in region 2 promoted tree growth, with these trees showing greater drilling resistance and higher longitudinal wave velocities. In addition, the influence of climatic factors was evidenced by the variation of wave propagation velocity throughout the year. Periods of lower water availability resulted in higher velocities, while periods of greater precipitation were associated with lower velocities. The research results showed that temperature and soil water storage had significant effects on tree growth (DBH and height), as well as ultrasound wave propagation velocity and drilling resistance. Full article
(This article belongs to the Special Issue Recent Advances in Nondestructive Evaluation of Wood: In-Forest Wood Quality Assessments—2nd Edition)
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14 pages, 3313 KiB  
Article
Assessment of Oak Roundwood Quality Using Photogrammetry and Acoustic Surveys
by Michela Nocetti, Giovanni Aminti, Margherita Vicario and Michele Brunetti
Forests 2025, 16(3), 421; https://doi.org/10.3390/f16030421 - 25 Feb 2025
Viewed by 466
Abstract
Hardwood has a variety of applications and can be used for low-value products, such as firewood, or for high-value applications, achieving significantly higher prices. Therefore, assessing the quality of raw material is essential for allocating the wood to the most suitable end use. [...] Read more.
Hardwood has a variety of applications and can be used for low-value products, such as firewood, or for high-value applications, achieving significantly higher prices. Therefore, assessing the quality of raw material is essential for allocating the wood to the most suitable end use. The aim of this study was to explore the use of the photogrammetry technique to determine dimensional characteristics and perform remote visual grading of round oak timber stored at a log yard. The results of the visual classification were then compared with non-destructive acoustic measurements to assess their level of agreement. Based on the point cloud obtained from photogrammetry, logs were classified into three quality groups according to the European standard for round timber grading. The diameter measurements of the logs obtained through the photogrammetry survey were comparable to those taken manually, with an average difference of 0.46 cm and a mean absolute error of 2.1 cm compared to field measurements. However, the log lengths measured from the 3D survey were, on average, 5 cm shorter than those obtained using a measuring tape. The visual classification performed on the 3D reconstruction was based on the evaluation of log size, knots, buckles, and sweep, resulting in 39%, 27%, and 24% of the pieces being grouped into the high-, medium-, and low-quality classes, respectively. Acoustic measurements, performed using both resonance and time-of-flight (ToF) methods, were highly correlated with each other and successfully distinguished the three quality classes only when sweep was excluded from the classification criteria. When curvature was also considered as a parameter for log grading, acoustic velocity only differentiated the lowest quality class from the other two. Full article
(This article belongs to the Special Issue Recent Advances in Nondestructive Evaluation of Wood: In-Forest Wood Quality Assessments—2nd Edition)
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13 pages, 2311 KiB  
Article
Machine Learning Algorithms and Nondestructive Methods for Estimating Wood Density in Planted Forest Trees
by Rafael Gustavo Mansini Lorensani and Raquel Gonçalves
Forests 2025, 16(2), 376; https://doi.org/10.3390/f16020376 - 19 Feb 2025
Viewed by 594
Abstract
Inferring forest properties is crucial for the timber industry, enabling efficient monitoring, predictive analysis, and optimized management. Nondestructive testing (NDT) methods have proven to be valuable tools for achieving these goals. Recent advancements in data analysis, driven by machine learning (ML) algorithms, have [...] Read more.
Inferring forest properties is crucial for the timber industry, enabling efficient monitoring, predictive analysis, and optimized management. Nondestructive testing (NDT) methods have proven to be valuable tools for achieving these goals. Recent advancements in data analysis, driven by machine learning (ML) algorithms, have revolutionized this field. This study analyzed 492 eucalyptus trees (Eucalyptus sp.), aged 3 to 7 years, planted in São Paulo, Brazil. Data from forest inventories were combined with results from ultrasound, drilling resistance, sclerometric impact, and penetration resistance tests. Seven machine learning algorithms were evaluated to compare their generalization capabilities with conventional statistical methods for predicting basic wood density. Among the models, extreme gradient boosting (XGBoost) achieved the highest accuracy, with a coefficient of determination (R2) of 89% and a root mean square error (RMSE) of 10.6 kg·m−3. In contrast, the conventional statistical model, using the same parameters, yielded an R2 of 33% and an RMSE of 26.4 kg·m−3. These findings highlight the superior performance of machine learning in the nondestructive inference of wood properties, paving the way for its broader application in forest management and the timber industry. Full article
(This article belongs to the Special Issue Recent Advances in Nondestructive Evaluation of Wood: In-Forest Wood Quality Assessments—2nd Edition)
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21 pages, 4717 KiB  
Article
Quantity and Quality of Narrow-Leaved Ash (Fraxinus angustifolia Vahl) Wood Forest Products in Relation to Tree Crown Defoliation
by Branko Ursić, Željko Zečić and Dinko Vusić
Forests 2025, 16(1), 147; https://doi.org/10.3390/f16010147 - 14 Jan 2025
Viewed by 673
Abstract
Forest stands are developing in changeable climate conditions that influence stand health and consequently assortment quality. Narrow-leaved ash is strongly affected by dieback because of new fungal diseases. The main aim of this study was to determine the quantity and quality of produced [...] Read more.
Forest stands are developing in changeable climate conditions that influence stand health and consequently assortment quality. Narrow-leaved ash is strongly affected by dieback because of new fungal diseases. The main aim of this study was to determine the quantity and quality of produced wood assortments in dieback-affected narrow-leaved ash stands. Based on the study results, the average tree value increased with tree diameter and partially decreased with tree crown defoliation degree. The healthy (crown defoliated up to 25%) and 3A (crown defoliated from 61 to 80%) trees had significantly higher average tree values (EUR/m3) compared to the significantly defoliated 3B trees (crown defoliated from 81 to 99%) and dead trees (100% defoliated crown). The influence of stand age and share of narrow-leaved ash in stand volume were confirmed as factors influencing the average tree value. Wood chips quality remained the same regardless of tree crown defoliation degree. Based on the significance influence of the tree crown defoliation degree on the average tree value, current assortment tables should be expanded in order to achieve more accurate expected values. Full article
(This article belongs to the Special Issue Recent Advances in Nondestructive Evaluation of Wood: In-Forest Wood Quality Assessments—2nd Edition)
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18 pages, 16218 KiB  
Article
Research on Non-Destructive Testing of Log Knot Resistance Based on Improved Inverse-Distance-Weighted Interpolation Algorithm
by Fenglu Liu, Wenhao Chen, Qinhui Wang and Jiawei Xiao
Forests 2024, 15(11), 1858; https://doi.org/10.3390/f15111858 - 23 Oct 2024
Viewed by 758
Abstract
The objective of this paper is to propose a non-destructive resistance detection imaging algorithm for log knots based on improved inverse-distance-weighted interpolation algorithm, i.e., the eccentric circle-based inverse-distance-weighted (ECIDW) method, to predict the size, shape, and position of internal knots of logs; evaluate [...] Read more.
The objective of this paper is to propose a non-destructive resistance detection imaging algorithm for log knots based on improved inverse-distance-weighted interpolation algorithm, i.e., the eccentric circle-based inverse-distance-weighted (ECIDW) method, to predict the size, shape, and position of internal knots of logs; evaluate its precision and accuracy; and both lay a theoretical foundation and provide a scientific basis for predicting and assessing knots in standing trees. Six sample logs with natural knots were selected for this study. Resistance measurements were performed on the log cross-sections using a digital bridge, and resistance tomography was conducted using the improved ECIDW algorithm, which combines the azimuth search method with the eccentric circle search method. The results indicated that both the conventional inverse-distance-weighted (IDW) algorithm and the ECIDW algorithm accurately predicted the positions of the knots. However, neither algorithm was able to predict the shape of the knots with high precision, leading to some discrepancies between the predicted and actual knot shapes. The relative error (Dt1) between the knot areas measured by the IDW algorithm and the actual knot areas ranged from 18.97% to 88.34%. The relative error (Dt2) for the knot areas predicted by the ECIDW algorithm ranged from 1.82% to 74.16%. The average prediction accuracy for the knot areas using the IDW algorithm was 51.58%, compared to 72.90% using the ECIDW algorithm. This indicates that the ECIDW algorithm has higher accuracy in predicting knot areas compared to the conventional IDW algorithm. The ECIDW algorithm proposed in this paper provides a more reasonable and accurate prediction and evaluation of knots inside logs. Compared to the conventional IDW algorithm, the ECIDW algorithm demonstrates greater precision and accuracy in predicting the shape and size of knots. While the resistance method shows significant potential for predicting internal knots in logs and standing trees, further improvements to the algorithm were needed to enhance the imaging effects and the precision and accuracy of knot area and shape predictions. Full article
(This article belongs to the Special Issue Recent Advances in Nondestructive Evaluation of Wood: In-Forest Wood Quality Assessments—2nd Edition)
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