Wood Cross-sections Research Articles

Comparison Between Gans and Diffusion Models in the Generation of Synthetic Images for Enhancing Tree Species Recognition

Objective: This study investigates the application of Generative Adversarial Networks (GANs) and Diffusion Models in data augmentation to improve the classification of tree species images, which is essential for sustainable forest management. Theoretical Framework: Fundamental concepts of machine learning, generative and classifier networks, as well as data augmentation techniques through synthetic image generation, are presented, establishing a solid foundation for the research. Method: The research utilized 2,178 images of cross-sections of wood from 18 species, applying Deep Convolutional GAN (DCGAN) and U-Net with diffusion on a rare species, evaluated using FID and IS metrics. The generated images were used to train and validate classification models, assessed by F1-score. Results and Discussion: The results revealed that Diffusion Models generated more realistic images and performed better in the classification of the rare species. The discussion contextualizes these results in light of the theoretical framework, exploring their implications for environmental management. Limitations, such as the impact of indiscriminate addition of synthetic data, are also addressed. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the results can be applied or influence practices in the field of forest management and environmental management. These implications may cover areas such as sustainable innovation and biodiversity conservation. Originality/Value: This study contributes to the literature by demonstrating the potential of Diffusion Models to outperform GANs in generating synthetic images for sustainable forest management purposes. The relevance and value of this research are evidenced by its practical application in promoting innovative and sustainable practices in environmental management.

Suitability of an ornamental tree, Sorbus alnifolia, as a source of industrial wood: Properties and the juvenile to mature transition

Ornamental trees are being promoted to supplement wood for industrial applications in China. To determine the wood utilization potential of an ornamental tree species, Sorbus alnifolia, this study investigated the radial variation of anatomical characteristics of its wood cross-section. The results showed that S. alnifolia is porous with high cell wall percentage, fiber percentage, and vessel percentage, small fiber and vessel sizes, and low vessel frequency. The transition age between juvenile wood and mature wood is 7 to 11 years for vessels, 12 to 16 years for axial parenchyma, and 18 to 24 years for fibers. Mature wood exhibits a higher percentage of cell walls, thicker fiber walls, and a lower percentage of vessels than juvenile wood. This result implies that wood is easy to dry, has strong permeability, good physical and mechanical properties, and a high fiber yield.

The influence of geographical location on moisture distribution in wood cross sections: a numerical simulation study using Austria as an example

Wood constantly interacts with the surrounding, locally varying climate, leading to changes in the moisture content. Advanced simulation tools can predict the two-dimensional moisture distributions caused by these changing climate conditions within wood cross sections over time. However, there is a notable absence of systematic simulation results for diverse climatic conditions and various wood cross sections. This study seeks to bridge this gap in research. Here, we present moisture fields in three solid timber and three glued laminated timber cross sections in Austria and show the effect of the location and the altitude on the moisture content distribution. The results reveal decreasing influence of the location on the moisture content development with increasing cross section size, and primarily the altitude affecting the moisture content. In addition, the results are compared with the standard for the design of timber–concrete composite structures (ONR CEN/TS 19103), revealing appropriate values in most of the cases. Only for cross sections with a width of 14 cm and larger, assigned to a specific region, the standard value is assumed underestimated. Furthermore, the distribution of moisture gradients, which are related to the crack depth development, are analyzed for Austria, demonstrating the influence of mountain areas in the moisture gradient development.

Evaluation of Moisture-Induced Stresses in Wood Cross-Sections Determined with a Time-Dependent, Plastic Material Model during Long-Time Exposure

In recent years, the use of timber as a building material in larger construction applications such as multi-story buildings and bridges has increased. This requires a better understanding of the material to realize such constructions and design them more economically. However, accurate computational simulations of timber structures are challenging due to the complexity and inhomogeneity of this naturally grown material. It exhibits growth inhomogeneities such as knots and fiber deviations, orthotropic material behavior and moisture dependence of almost all physical parameters. Describing the creep response of wood under real climate conditions is particularly difficult. Changes in moisture content, plasticity and viscoelasticity affect moisture-induced stresses and potentially lead to cracks and structural damage. In this paper, we apply a material model that combines time and moisture-dependent behavior with multisurface plasticity to simulate cross-sections of different dimensions over a 14-month climate period. Our findings indicate that considering this long-term behavior has a minor impact on moisture-induced stresses during the drying period. However, during the wetting period, neglecting the time- and moisture-dependent material behavior of wood leads to a significant overestimation of tensile stresses within the cross-section, resulting in unrealistic predictions of wetting-induced fracture. Therefore, simulations during wetting periods require a sophisticated rheological model to properly reproduce the stress field.

New Methods in Digital Wood Anatomy: The Use of Pixel-Contrast Densitometry with Example of Angiosperm Shrubs in Southern Siberia.

This methodological study describes the adaptation of a new method in digital wood anatomy, pixel-contrast densitometry, for angiosperm species. The new method was tested on eight species of shrubs and small trees in Southern Siberia, whose wood structure varies from ring-porous to diffuse-porous, with different spatial organizations of vessels. A two-step transformation of wood cross-section photographs by smoothing and Otsu's classification algorithm was proposed to separate images into cell wall areas and empty spaces within (lumen) and between cells. Good synchronicity between measurements within the ring allowed us to create profiles of wood porosity (proportion of empty spaces) describing the growth ring structure and capturing inter-annual differences between rings. For longer-lived species, 14-32-year series from at least ten specimens were measured. Their analysis revealed that maximum (for all wood types), mean, and minimum porosity (for diffuse-porous wood) in the ring have common external signals, mostly independent of ring width, i.e., they can be used as ecological indicators. Further research directions include a comparison of this method with other approaches in densitometry, clarification of sample processing, and the extraction of ecologically meaningful data from wood structures.

Исследование структуры и механических свойств годичных колец древесины дуба черешчатого (Quercus robur) методами наноиндентирования и скретч-теста

Optical methods and optical properties are usually used to research the structure of wood and its ring structure. However, these properties are not directly related to its mechanical and other physical characteristics. To study them, methods of x-ray densitometry, synchrotron radiation, nuclear magnetic resonance, etc., which are not very common in wood science, are used. These methods are quite labor-intensive and require expensive equipment. In this regard, there is a need to develop simple and convenient means and methods for studying the micromechanical properties of wood. The main goal of the work is to develop such an approach using nanoindentation and digital scratching of a cross section of wood and to identify its potential in the further development of dendrochronology and related disciplines. Using the NI method, radial dependences of hardness H and Young's modulus E were obtained for eleven consecutive annual pedunculate oak (Quercus robur L.) wood rings for 3 different loads Pmax = 2, 100 and 500 mN. The values of H in the range from 70 to 340 MPa and Young's modulus E in the range from 2 to 10 GPa were determined for the corresponding loads and early (EW) and late wood (LW). Using the scratch test method, profiles of the normal force Fn and the corresponding hardness HS (in the range from 53 to 225 MPa) were obtained for the period 2007-2020. According to both methods, the widths of annual rings were determined; the discrepancy between the values and the optical method was < 3 %.

Anisotropic structural carbon skeleton decorated with Co nanoparticles towards oxygen evolution reaction

Hierarchical carbon skeletons derived from natural wood can be employed as the substrates to fabricate self-supported catalysts. The typically three sections (cross section, radial section, and tangential section) of wood would significantly affect the electrocatalytic performance. Therefore, the correlations between anisotropy structure of wood derived hierarchical carbon skeletons and oxygen evolution reaction (OER) performances was systematically investigated. The cross-sectional wood-derived carbon decorated with Co nanoparticles requires an overpotential of 370 mV to deliver 50 mA cm−2 superior to those of radial-sectional and tangential-sectional counterparts. The cross-section of wood derived carbon skeleton possesses higher content of Co nanoparticles, which is accounted for the enhanced OER catalytic activity. This work highlights the critical contribution of anisotropy of carbon skeletons in promoting the OER properties and provides a new paradigm for designing advanced electrocatalysts.

Kriterij za objektivno određivanje vrijednosti praga osjetljivosti pri filtriranju signala hrapavosti strojno obrađene površine masivnog drva filtrom utemeljenim na brzoj Fourierovoj transformaciji (FFT)

The article presents the method for an objective determination of threshold value, needed for filtering out the anatomical roughness signal, with filter based on fast Fourier Transform (FFT), from surface roughness profile after machining. The method includes experimental preparation of solid wood surface by cutting in such a way to get a surface that can be considered to represent only anatomical roughness, with no other influence. Experiments were performed on radial cross section of solid oak wood (Quercus robur L.) so that the results could be compared with roughness profiles that were previously obtained in experiments after sawing with circular saw. From these samples and based on frequency analysis of anatomical roughness signals, the threshold value was determined to be 1.6 μm. The average value of Ra parameter of anatomical roughness for specimens of radial cross section of solid oak wood was 2.1 μm with standard deviation of 0.3 μm. The importance of choosing adequate sampling length in threshold determination, based on frequency analysis of anatomical roughness signal, was also established.

Effect of chip thickness, wood cross-sections, and cutting speed on surface roughness and cutting power during up-milling of beech wood

The aim of the conducted experiments was to determine the effect of selected machining parameters on power consumption and surface quality obtained during the milling of beech wood using a computerized numerical control woodworking machine. Surface roughness was tested using the contact roughness measurement method, while roughness parameters Ra and Rz were recorded and cutting energy was determined. Tests were conducted for two variants of cutting speed (7.5 and 15 m·s-1) as well as three variants of chip thickness (0.10, 0.06, and 0.02 mm); additionally, the tests examined different cross-sections of wood. It was found that greater chip thickness and feed speed caused an increase in surface roughness and cutting power. In turn, cutting speed had no effect on surface roughness, whereas its increase resulted in increased cutting power. Surface roughness at the radial and tangential cross-sections was comparable, while it was greater at the transverse cross-section. It was also found that cutting power was lowest at the radial cross-section, while it was greater at the tangential and the greatest at the transverse cross-section.

Nanomechanical/Micromechanical Approach to the Problems of Dendrochronology and Dendroclimatology

The most widespread approach in dendrochronology (wood dating) and dendroclimatology (climate reconstruction) is based on measurement of the width of annual growth rings by analyzing optical images of wood cross sections. This approach is quite efficient and easy to implement but it has inherent drawbacks. Raw data for these techniques originate from the optical properties of the wood surface, which are not directly related to other properties of wood, mechanical properties in particular. This paper describes a new quantitative approach applicable to dendrochronology and dendroclimatology based upon measurement of the micromechanical properties of wood by employing nanoindendation and digital sclerometry. It yields not only the width of annual growth rings and early and late wood layers with an accuracy not inferior to optical methods, but also rich data on the mechanical properties of the wood with a high spatial resolution that could be brought to subcellular scale if necessary. This data can be used for the dendrochronological analysis of archeological finds and the evaluation of climatic parameters during tree growth with a time resolution of up to a month or even better, which is unlike other common methods with a time resolution of one year. Moreover, the detailed continuous profiling of local mechanical properties can form a basis for improving our understanding of the nature and mechanisms of the formation of macromechanical properties important for applications and can clarify the climate factors that have the greatest impact on such properties.

Wood species recognition in open set framework using fuzzy classifier and generalised basic probability assignment

It seems impossible and unnecessary to recognise all tree species within a wood classification system. In practice, the special tree species in special areas need to be recognised and simultaneously other species rejected. These special species are of interest and are included in our training dataset, whereas the other species rejected are not interesting to us and are not in the training dataset. To correctly and simultaneously classify known wood species and reject unknown species, a novel wood species recognition system in an open set framework is proposed. A Flame-NIR spectrometer was used to obtain the near-infrared (NIR) spectral curve of wood cross sections. The spectral feature dimension reduction was performed using a principal component analysis (PCA) processing. The fuzzy if-then classifier was revised to extend its use from a closed set to an open set. A novel generalised basic probability assignment (GBPA) is proposed based on the product of membership degree values and the grade of certainty of a fuzzy rule. The comparison experimental results on both balanced and imbalanced datasets indicated that our proposed scheme outperforms the classification schemes using one class classifier in open set and the state-of-the-art wood classification schemes in closed set.

Ophiostomatální houby v porostech borovice lesní (Pinus sylvestris L.) postižených dlouhodobým suchem

In this study, presence of ophiostomatiod fungi (absence, presence) on wood cross-section samples (total 72) from freshly cut Scots pine (Pinus sylvestris L.) trees (total 24) at four sites (Valtice, Příšťpo, Brodce, Vrbová Lhota) affected by long-term drought was evaluated in relation to: sampling period (spring, summer, autumn), tree age (30–40, 50–90 years), wood sample origin (bottom trunk, middle trunk, twigs), tree defoliation (>25–60%, >60–99%), and presence of other taxa. Ophiostomatoid fungi were present on 33% wood cross-section samples from 50% trees. Presence of ophiostomatoid fungi was significantly different in relation to sampling period (i.e. the highest in autumn, the lowest in spring), and was directly proportional to both presence of mites and Nematocera larvae; it was insignificantly different in relation to site, tree age, wood sample origin, defoliation, and presence of other taxa. These results show: (1) frequent presence of ophiostomatoid fungi in wood tissues of Scots pine trees, (2) insignificant effect of ophiostomatoid fungi on health status of the trees, (3) relationship of presence of ophiostomatoid fungi with both presence of mites and Nematocera larvae.

Using Optimization Algorithms-Based ANN to Determine the Temperatures in Timber Exposed to Fire for a Long Duration

The article investigates the temperature prediction in rectangular timber cross-sections exposed to fire. Timber density, exposure time, and the point coordinates within the cross-section are treated as inputs to determine the temperatures. A total of 54,776 samples of wood cross-sections with a variety of characteristics were considered in this study. Of the sample data, 70% was dedicated to training the networks, while the remaining 30% was used for testing the networks. Feed-forward networks with various topologies were employed to examine the temperatures of timber exposed to fire for more than 1500 s. The weight of the artificial neural network was optimized using bat and genetic algorithms. The results conclude that both algorithms are efficient and accurate tools for determining the temperatures, with the bat algorithm being marginally superior in accuracy than the genetic algorithm.

Ant Colony Optimization for Estimating Pith Position on Images of Tree Log Ends

The pith location is one of the most important features to detect in order to determine the quality of wood. Indeed, it allows to extract other important features. In this paper, we address the problem of pith detection on images of wood cross-sections. Taking such images can be done at little cost and with a high resolution. However, contrary to computed tomographic images, digital images exhibit disturbances like sawing marks, dirt or ambient light variations which make difficult the image analysis. Few studies have focused on such images. Furthermore these studies do some prior segmentation or cropping before the detection. We propose an approach for estimating the pith location without any requirements. Our method is based on an ant colony optimization algorithm. It is a probabilistic approach for solving this task. We validate our algorithm on images of Douglas fir captured after harvesting. The efficiency of this algorithm has been demonstrated by performance comparisons with other approaches. Experiments show an accurate and fast estimation and the algorithm could be used in real time, at sawmill environment or in forest, with a smartphone.

Extraction of plant parenchyma by computer image processing technology

People are increasingly using different kinds of plant products, such as wood, but there are many kinds of wood and it is difficult to analyze and identify them, so how to use auxiliary equipment to analyze wood and achieve the goal of accurate wood identification without damaging the product itself has become one of the important problems to be solved in the field of wood research. The axial thin-walled tissue has important wood grain information and it is one of the important features for wood identification. In this paper, we studied the microscopic images of broadleaf wood, and obtained the microstructure images of wood cross-section by photographing, and extracted the complete axial thin-walled tissue morphology of wood by using computer image processing technology and other ways about computer vision. Firstly, the axial thin-walled wood images were de-noised to eliminate some noise effects, so as to facilitate the separation of the axial thin-walled wood; then the images were processed by mathematical morphology to successfully extract the axial thin-walled wood and duct morphology from the cross-sectional images of broadleaf wood; finally, the axial thin-walled wood was separated from the duct by calculating the area of the closed area.

Interfacial solar steam generator by MWCNTs/carbon black nanoparticles coated wood

In order to further improve the efficiency of radiation steam generation and the stability in practical application, multi-walled carbon nanotubes (MWCNTs)/carbon black nanoparticles were used to coat the delignified wood cross section. The results showed that the multi-walled carbon nanotubes and carbon black nanoparticles are cross-linked and uniformly attached to the cross section of wood, forming a relatively rough coating. Through comparative experiments, the sample device displayed a favorable effect of radiation evaporation, with a 24-hour evaporation efficiency of 51.1%, which was 8.9%, 13.0% and 8.4% higher than that of natural wood device, delignified wood device and natural wood device coated with multi-walled carbon nanotubes-carbon black mixed solution, respectively. On the one hand, it benefited from the high broadband absorption efficiency of multi-walled carbon nanotubes-carbon black coating, which exhibited an absorption efficiency of ∼97.5% and an extremely low transmittance of <2.5% in the visible light and ultraviolet region, and on the other hand, it benefited from the unique surface nanostructure of multi-walled carbon nanotubes-carbon black surface coating, which could effectively capture light.

Incidence and epidemiology of wood disease in Algerian citrus orchards

The wood diseases are very damaging to the culture of citrus and many hosts around the world. It is considered as a complex pathosystem that requires the analysis of its various aspects. In this context, we conducted epidemiological and etiological studies. Our studies were conducted for four consecutive years (2017-2020) on 25 orchards from five localities in Algeria. The results of symptom diagnosis showed the presence of different categories of symptoms; these are the total and/or partial dieback. The examination of the cross-sections of infected wood showed the presence of different forms of inner necrosis. The isolations from the necrotic tissues of the infected trees put often in evidence the presence of a diversified fungal flora dominated by Botryosphaeriaceae fungi. We also recorded an overall infection rate of 23.28% representing a severity index of 1.77 on a scale of four degrees, giving an incidence of 10.76%. The overall assessment of the dieback situation in the studied orchards showed a rapid increase in all epidemiological indices. The statistical analyzes showed that the factors region, age, rootstock, type of irrigation and soil texture had a highly significant effect on the variation of epidemiological parameters. However, the factor year is only moderately significant. On the other hand, the factor cultivar, has no significant effect on these indices. The epidemiological behavior of dieback in these orchards confirms that the spread of the disease is favored by cultural techniques such as irrigation and pruning.

Study on infection behavior and characteristics of poplar wood dyed by Lasiodiplodia theobromae.

The technology of dyeing wood by microorganisms is a kind of pollution-free and sustainable wood dyeing technology. To achieve fast and rich dyeing of Lasiodiplodia theobromae on the surface of poplar wood, tyrosinase and tricyclazole were used as induction factors in this experiment. The results showed that L. theobromae had a better induction effect in the cross-section of poplar wood and induced with tricyclazole. The surface color of poplar ranged from light yellow dyeing to gray and brown, the chromatic aberration of the cross-section of wood was above 44.5 NBS, and the infected area was over 50%, while the dyed parts of radial and tangential sections of wood were only on the surface of the wood after 30 days of infection. The induced infection of L. theobromae on poplar wood had little effect on the chemical components of poplar and had good colorfastness to washing and light. Therefore, microbial dyeing of wood showed a beneficial application prospect in the field of wood dyeing.

The Characteristics of Moisture and Shrinkage of Eucalyptus urophylla × E. Grandis Wood during Conventional Drying.

High quality lumbers produced from Eucalyptus plantations can be used to make higher value-added solid wood products. Moisture flow affects shrinkage, deformation, and quality of Eucalyptus wood during conventional drying. In this study, 50 and 100 mm long samples were dried using a conventional drying method. The drying curves, drying rate, moisture content (MC) gradient and distribution, moisture flow, and shrinkage during the drying process were investigated. The results show: Drying was much faster in the first 15 h for all samples and became slow as MC decreased. The drying rate above fiber saturated point (FSP) was about 3.5 times of that below FSP for all samples. The drying rate of 50 mm samples above and below FSP is 1.40 and 1.33 times of 100 mm samples; MC gradients are greater in tangential, radial directions, and cross-sections for both samples when the MC is above FSP, especially at an average MC of 50%. MC gradient along the tangential and radial direction depends on the samples size and MC stages. The short samples have much greater MC gradients than the longer samples above FSP. Moisture distributions on the cross-sections of wood coincide with the moisture gradient in the cross-sections. At an average MC of 50%, the moisture distributions of 50 mm are highly uneven, while they are relatively even in the middle of 100 mm samples, and become much more even at the end of the sample. Moisture distributions become even as MC decreases in all of the samples. Water migration directions vary by state of water. In the short samples, most free water migrates more in the fiber direction from the wood center toward the end surfaces, but bound water diffusion becomes weak. The collapse in the 50 mm samples is significantly larger than that in the 100 mm samples, indicating that the collapse is affected by the dimension of the sample.

Using Deep Learning to Identify Costa Rican Native Tree Species From Wood Cut Images.

Tree species identification is critical to support their conservation, sustainable management and, particularly, the fight against illegal logging. Therefore, it is very important to develop fast and accurate identification systems even for non-experts. In this research we have achieved three main results. First, we developed—from scratch and using new sample collecting and processing protocols—an dataset called CRTreeCuts that comprises macroscopic cross-section images of 147 native tree species from Costa Rica. Secondly, we implemented a CNN for automated tree species identification based on macroscopic images of cross-sections of wood. For this CNN we apply the fine-tuning technique with VGG16 as a base model, pre-trained with the ImageNet data set. This model is trained and tested with a subset of 75 species from CRTreeCuts. The top-1 and top-3 accuracies achieved in the testing phase are 70.5% and 80.3%, respectively. The Same-Specimen-Picture Bias (SSPB), which is known to erroneously increase accuracy, is absent in all experiments. Finally, the third result is Cocobolo, an Android mobile application that uses the developed CNN as back-end to identify Costa Rican tree species from images of cross-sections of wood.