Earticle

This study focused on improving lignin for hydrogel production through oxypropylation with glycidol (GLY). Lignin is an amorphous natural aromatic polymer in which a phenylpropane (C6-C3) precursor is condensed by a carbon-carbon covalent bond or an ether bond. However, the study of lignin faces great problems such as non-uniformity and lack of functionality of lignin. To address this, lignin was modified using GLY, and its chemical structure was analyzed with FTIR and XPS to confirm that oxypropylation was successful. In addition, the results of NMR and GPC analyses showed that the molecular weight and hydroxyl group content increased compared to kraft lignin. Moreover, TGA analysis results showed that the more GLY there was, the higher the pyrolysis temperature. As a result, the hydrogel made with oxypropylated lignin had better structural integrity and a porous morphology, unlike one made with only kraft lignin. Therefore, the results of this study suggest potential for lignin modification and hydrogel applications.

Oregonin, a glycoside of diarylheptanoid, is a distinctive compound in Alnus japonica renowned for its anti-inflammatory and antioxidant properties. We investigated aimed in vitro tissue culture conditions at mass-propagation of in vitro plantlets and enhancing Oregonin production. Cultures were initiated in WPM supplemented with plant growth regulators (PGRs) including BA, 2IP, TDZ, zeatin at 1μM, and gibberellin (GA3) at 1μM. Growth parameters such as fresh weight, number of shoots, shoot length, and leaf count were evaluated, and oregonin content was quantified using HPLC. The BA treatment demonstrated superior growth, followed by zeatin, whereas the control and GA3 treatments exhibited inferior performance. Interestingly, despite lower growth, the control group showed the highest Oregonin content. Zeatin treatments generally resulted in higher Oregonin levels. In subsequent experiments comparing various concentrations of BA (1, 5, 10, 15μM), and zeatin (1, 5, 10, 15μM), the 5μM BA treatment showed optimal growth, and among zeatin treatments, 10μM. However, zeatin exhibited superior growth and Oregonin content than BA treatment. Thus, zeatin at 10μM is recommended as the optimal condition for Oregonin production.

Sodium alginate (AL), a natural polysaccharide derived from algae, is widely used in hydrogels due to its excellent biocompatibility and gel-forming abilities. However, the low mechanical properties of AL hydrogels limit their broader applications. TEMPO-oxidized cellulose nanofibrils (TOCNF) are known for their superior mechanical strength and the presence of abundant surface carboxyl groups, which facilitate ionic bonding with cations. In this study, a natural polymer composite hydrogel was developed by crosslinking AL with TOCNF using Ca²⁺ ions as a crosslinking agent. TOCNF served as a reinforcing material, and the effects of TOCNF content and its carboxyl group concentration on the hydrogel’s properties were investigated. The results demonstrate a synergistic enhancement of gel strength due to the interaction between TOCNF and AL, highlighting the potential of these composite hydrogels for advanced applications in natural polymer-based materials.

Mechanized timber harvesting operations often cause soil disturbance, such as compaction and rutting. The extent of soil disturbance is highly dependent on environmental factors and operation methods. As soil disturbance has a long-term impact on forest productivity, it is critical to assess its effects. The objective of this study was to investigate soil surface deformation caused by forest machinery traffic in a steep slope clear-cut area and to compare manual methods with remote sensing. Following the timber harvesting operation design, we established the experimental treatments representing the number and direction of forest machinery passes (1D, 1-downward; 1U, 1-upward; 3R, 3-round-trip; 5R, 5-round-trip). Soil rut depth and cross-section were manually measured using pinboard and estimated by mobile LiDAR system (MLS) and unmanned aerial vehicle structure from motion algorithm (UAV SfM). There was a significant difference in soil rut depth based on the number of passes (p = 0.00), while no significant difference based on the direction of passes. Rut depth in 1D (22.2cm) was significantly higher than 3R (15.7cm), with no significant differences among 1D, 1U (20.0cm), and 5R (19.6cm) or among 3R, 1U, and 5R. These findings suggest that most soil disturbance occurs during the initial passes of forest machinery. The comparison of pinboard and MLS data revealed a significant relationship (R2 = 0.74, slope = 1.00, p = 0.00). Comparing pinboard and UAV SfM data, we found that MLS is more accurate than UAV SfM in assessing soil surface deformation (R2 = 0.60, slope = 0.81, p = 0.00). The results reveal the need to establish optimized driving routes for forest machinery to minimize soil disturbance and suggest the potential of using MLS and UAV SfM for future soil disturbance assessments.

Synanthedon bicingulata is considered as a wood-boring pest on Prunus spp., particularly infesting the cambium layer under barks. Since the inner part of tree stem is infested, wood-rot fungi enter, causing sap wood and heart wood to decay. The host species, cherry tree, is widely planted in in urban areas across Korea, and its population continues to increase nationwide. However, occurrence pattern of S. bicingulata in Gangwon province has not been investigated. The study was conducted from April 2023 to October 2024 in roadside areas in Chuncheon-si. For sampling, delta traps with sex pheromone lures were used to capture male adults of S. bicingulata. In 2023, two peaks in adult activity were observed, one in mid-May and the other in late July, whereas in 2024, adult occurrence was steady throughout the year compared to the previous year. The total number of individuals also declined in 2024.

Urban trees are increasingly recognized as a source of carbon uptake in net-zero initiatives globally. To accurately estimate the carbon reduction of urban trees, it is essential to obtain both carbon uptake coefficients and comprehensive inventory data. The tree inventory includes tree species, stem diameter, tree height, crown width, stem volume, and crown volume. Traditionally, urban tree inventories have relied on field surveys; however, this approach necessitates considerable labor and financial investment. In this study, we conducted a comparative analysis of urban tree dimensions utilizing various measurement methods, specifically focusing on LiDAR, which has recently emerged as an innovative technique for urban tree inventory. A total of ten sample trees were selected, and their dimensions were measured using both field equipment and LiDAR. The measured variables were statistically evaluated for differences between methods using paired t-test. The results indicated that there were no statistically significant differences in stem diameter, tree height, and stem volume between the two measurement methods (p> 0.05). However, crown width and crown volume exhibited significant differences, with variations of up to 1.5 times and 6.0 times, respectively (p< 0.05). Overall, the tree dimensions obtained through LiDAR in this study were generally consistent with those measured in the field, except for crown width and crown volume. LiDAR will be useful in the future as a way to inventory urban trees. Nonetheless, it is important to note that LiDAR is constrained by the substantial volume of data generated and the time required for tree classification. Future advancements in data processing technology will be essential to enhance the utility of LiDAR in urban greenspaces.

In this study, aminated lignin (AL) was evaluated as an eco-friendly adsorbent for dye removal, addressing water pollution caused by industrialization. The introduction of amine groups enhanced the lignin's functionality, increasing its surface area compared to kraft lignin. As a result, AL selectively adsorbed Congo Red (CR) and Methyl Green (MG) under different pH conditions. In addition, the adsorption kinetics followed a pseudo-second-order model, with isotherms for CR and MG fitting the Langmuir and Freundlich equations, respectively. Notably, AL maintained high efficiency after repeated use, with adsorption mechanisms attributed to electrostatic, NH-π, and π-π interactions. These results demonstrate AL's potential in sustainable wastewater treatment.

Forest virology is an underdeveloped field of study, with viruses affecting forest trees barely explored. Recent studies have just begun to investigate the presence of tree viruses using next-generation sequencing (NGS) analysis. In this study, using high-throughput NGS analysis, we identified pinus nigra virus 1 (PNV1) in Korean red pine (Pinus densiflora), which has not been previously reported in Korea. PNV1 is an unclassified DNA virus belonging to the Caulimoviridae family, carrying a double-stranded DNA genome. We found that the virus is distributed nationwide and even found in pollen, suggesting that it has a high potential for transmission via pollen. Together, our findings suggest that this newly identified Pinus virus may have spread widely through pollen and seed transmission.

Forest biomass, which offers eco-friendliness and sustainability, has been highlighted due to the limitations of fossil fuel reserves and the environmental pollution they cause. Wood powder, a by-product of wood processing, is currently reprocessed for use in wood pellets, pulp, and plywood. Composed of lignocellulose, wood powder is rich in carbon, making it a potential resource for producing various high-value-added products. In this study, we explored the feasibility of wood powder extract (WPE) as a microbial culture medium. We prepared 10% (w/v) extracts using larch powder, which is abundantly produced in Korea, and performed elemental analysis. Based on the composition comparison with Minimal 9 (M9) medium, commonly used for prokaryote cultures, specific supplements were added to enhance cell growth in the WPE-based medium. Notably, WPE-based media supplemented with disodium phosphate and magnesium sulfate at concentrations of 1,000, and 120 mg/L, respectively, supported the growth of Escherichia coli, the most widely used microorganism in bio-industries. In addition, calorimetric analysis of the residual solid fraction separated after extract preparation showed 17.1 MJ/kg, meeting the standard for wood pellets in Korea. Taken together, this study demonstrates that if WPE is produced during wood powder processing, it can serve as an effective industrial microbial culture medium, while the residual solid can be utilized as a biofuel.

VOCs (Volatile Organic Compounds) are hydrocarbon compounds that easily volatilize into the atmosphere in gas form. They are classified into AVOCs (Anthropogenic Volatile Organic Compounds), emitted from anthropogenic sources, and BVOCs (Biogenic Volatile Organic Compounds), released from natural sources such as trees and herbaceous plants. Phytoncides, a component of BVOCs, are known for their beneficial effects on human health as forest therapy substances. However, from an atmospheric chemistry perspective, BVOCs are highly reactive and contribute to ozone (O₃) formation through photochemical reactions with nitrogen oxides (NOₓ). BVOCs are categorized into isoprene (C₅H₈), monoterpenes (C₁₀H₁₆), sesquiterpenes (C₁₅Hₓ), other reactive VOCs (ORVOCs, CₓHᵧOₓ), and other VOCs (OVOCs). The global emissions of BVOCs are estimated at approximately 1007 TgC/year, which is reported to be 7 to 10 times higher than AVOCs. Measurements were conducted for over two weeks using PTR-ToF-MS (Proton-Transfer-Reaction Time-of-Flight Mass Spectrometer) equipment on the Kangwon National University campus (in December 2023 and April 2024) and at the Gangwon Regional Air Environment Research Center (in June 2024). The study analyzed seasonal trends in BVOCs concentrations, their relationship with meteorological factors, and the correlation with ozone (O₃) concentrations in Chuncheon City. As a result of performing one-way ANOVA to analyze the seasonal differences in BVOCs concentrations, the concentration of isoprene showed a significant difference depending on the season (F₂, 1263 = 989.9, p < 0.001), and pinene also showed a significant difference (F₂, 1263 = 267, p < 0.001).

Fallen leaves are often viewed as a nuisance unused forest biomass, contributing to wildfire risks and sewer blockages. However, they also present a valuable resource for producing high-value-added products. In a previous study, we demonstrated the economic feasibility of cultivating Pseudomonas species microorganisms using a hardwood fallen leaf extract (HLE)-based medium. This study focuses on further utilization of the HLE medium to produce levan, a functional biopolymer, by addition of sucrose as a carbon source and cultivation of Pseudomonas chlororaphis. Over a 72-hour cultivation, the cell growth-dependent levan production was monitored, resulting in a yield of 7.1 g/L from 19.6 g/L of sucrose (36.7% conversion yield). The crude levan was purified through a straightforward filtration process. However, the purified levan exhibited a dark-brown color due to the inherent pigmentation of the HLE, which could limit its industrial applications. To address this, we conducted decolorization experiments using eight different materials, with activated charcoal designed for water treatment showing the highest efficacy. Under the optimal decolorization conditions, the produced levan achieved a clear, colorless appearance. Taken together, this study confirms the industrial feasibility of using fallen leaf-based media for the production of high-value bioproducts like levan.

The purpose of this study was to develop and evaluate Point Cloud Data (PCD) deep learning models and a rule-based system for segmenting tree structures (stems and crowns) using fixed terrestrial LiDAR data. The dataset comprised 48 Larix Kaemferi trees, which were collected and preprocessed. For the PCD deep learning models, three downsampled datasets consisting of 1024, 4096, and 16384 points were constructed from the original data. The data was divided into training (70%) and validation (30%) sets. Models were built using PointNet and PointNet++ architectures, resulting in a total of 12 tree structure segmentation models for accuracy comparison. The rule-based system was developed using the original data, applying techniques such as verticality checks, cylindrical structure detection, and slice-based circular fitting to detect the stem. It then segmented the stem through repetitive circle fitting and validation processes based on height. The average accuracy of the PCD deep learning tree structure segmentation models was approximately 95%, with the PointNet++ model using 16384 points achieving the highest classification accuracy of about 98%. The rule-based system achieved high classification accuracy of over 99% for both tree species. This study is expected to contribute to precise measurement and efficient management of forest resources by presenting automated methods for tree structure segmentation using AI technology and rule-based approaches. It is anticipated that this research will serve as a foundation for the advancement of forest digitalization, precision forest management technologies, forest structure analysis, and timber production estimation in various fields.

This study aimed to develop a hybrid stem taper and volume estimation model using multi-platform LiDAR data for Pinus koraiensis (PK) and Larix kaempferi (LK) in a forest located in Gangwon Province, Republic of Korea. The research employed Terrestrial Laser Scanning (TLS) to capture detailed point cloud data of tree stems and Airborne Laser Scanning (ALS) for precise height measurements. By integrating the stem profiles derived from TLS with Kozak’s stem taper model, a hybrid estimation model was constructed to improve the accuracy of calculating individual tree taper curves and stem volumes. The proposed model was tested against traditional volume estimation methods, specifically the Korea Forest Service's standard volume table, to assess its accuracy. The standard volume table method exhibited root mean square error (RMSE) values of 0.12 m³ for PK and 0.13 m³ for LK. In contrast, the hybrid model showed significantly lower RMSE values of 0.07 m³ for PK and 0.05 m³ for LK, representing an accuracy improvement of approximately 42% for PK and 62% for LK. Additionally, the study estimated log production based on individual tree profiles generated from the hybrid model, accounting for factors such as stem length, diameter, and curvature. The increased accuracy of the hybrid model highlights its potential for providing more precise stem volume estimations and improving the reliability of forest inventories. The results suggest that this hybrid approach, leveraging the strengths of both TLS and ALS, offers a more efficient and accurate alternative to traditional volume estimation methods. The precise taper curves and volume estimates derived from this method can significantly contribute to sustainable forest management practices, particularly in assessing timber production and monitoring forest growth. By eliminating the need for destructive sampling, this method provides a non-invasive solution for estimating tree volumes. In conclusion, the multi-platform LiDAR-based hybrid model offers a promising solution for more accurate stem volume estimation, supporting forest inventory development and enhancing decision-making in forest management and timber production.

The Rhododendron mucronulatum is a deciduous shrub, native to forests across South Korea and has traditionally been used for medicinal plants. Secondary metabolites from medicinal plants, natural compounds, are valuable for the development of functional health foods and pharmaceuticals. However, R.mucronulatum faces challenges in mass propagation due to the difficulty of vegetative propagation and the slow growth of seedlings. To address these challenges, this study aimed to identify optimal conditions for in vitro mass propagation, focusing on medium composition and form. To determine suitable cytokinins, four growth characteristics were compared on solid media without hormones, with Zeatin, 2iP, and TDZ. Through a liquid medium, the optimal Zeatin concentration was determined. Zeatin at 3 μM resulted in the highest fresh weight, as measured at both 2 and 4 weeks. Using a temporary immersion bioreactor, shoot fresh weights were compared at different immersion cycles. Results showed the 4-hour cycle (15 minutes immersion + 3 hours 45 minutes exposure) yielded the highest fresh weight. Through a solid medium, Zeatin was found effective and a concentration of 3 μM in a liquid medium proved efficient for growth. In the bioreactor, the fresh weight with a 4-hour immersion cycle was highest; however, the liquid medium experiment of the same composition exhibited even higher fresh weight. Consequently, a continuous immersion method through a liquid medium is deemed more effective for the mass propagation of R.mucronulatum.

TEMPO-oxidized cellulose nanofibril (TOCNF)-based porous structures offer exceptional properties but face structural instability under various conditions. This study introduces a novel approach to improve the stability and adsorption capacity of TOCNF-based aerogels by incorporating chitosan (Ch) and crosslinking with dialdehyde cellulose (DAC). DAC can crosslink with TOCNF through hemiacetal formation and Ch via Schiff base formation, leading to significant improvement structural integrity and pH stability. The resulted aerogels enhanced adsorption capacity for Congo Red and showed excellent reusability for methylene blue adsorption, making them promising materials for various environmental and biomedical applications.

Polylactic acid(PLA) is a biodegradable polymer with biocompatibility and low toxicity, making it suitable for a wide range of applications such as food packaging and 3D printing filaments. However, PLA exhibits limitations including low thermal stability and insufficient mechanical strength. To address these defects, this study focused on improving the mechanical properties and thermal stability of PLA by grafting with cellulose fibrils. Dialdehyde cellulose(DAC) was synthesized by oxidizing cellulose fibrils with sodium periodate, introducing reactive aldehyde groups to enable grafting with PLA. The DAC was subsequently modified with octadecylamine(ODA), an eco-friendly hydrophobic surface modifier, to promote efficient grafting between ODA-DAC and PLA. This modification facilitated direct grafting of alkyl amine onto the aldehyde groups of DAC through a Schiff base reaction without the use of additional crosslinkers. The resulting ODA-DAC/PLA composite was fabricated via the solvent casting method, and its properties were evaluated to assess its potential for improving the performance of biodegradable plastics.

Although bamboo is a herbaceous plant, it shares many characteristics with wood, making it a versatile material for various timber applications. Its rapid growth rate also makes it an ideal species for bio-circular forest establishment, adding to its afforestation value. As the climate warms, bamboo's growing range is expanding, and its role as a carbon sink is increasing due to its fast growth. However, after harvesting bamboo's culm parts, a large amount of branches and leaves remain, which have limited uses and incur significant costs for disposal. A potential solution to this issue is to propose utilizing of bamboo by-products, which are produced in large quantities on-site, as ash. The ash of the plant contains many inorganic nutrients. This study analyzes the nutrients contained in the ash from bamboo by-products (branches and leaves), and investigates its effects on plant growth. We evaluated the usability of ash recovered after incinerating (500℃<) bamboo (Phyllostachys pubesens) by-products. The analysis revealed that the incineration ash contained high concentrations of potassium (>80,000 ppm), calcium (>50,000 ppm), phosphorus (>20,000 ppm), magnesium (>20,000 ppm), manganese (>10,000 ppm), and iron (>10,000 ppm), with aluminum, sulfur, sodium, and silicon also identified as major elements. In the plant growth evaluation, the survival rates of Alnus incana were similar across all treatments (94%-100%), but root induction decreased in the ash-treated group. In contrast, the survival rate of Rhododendron mucronulatum was lower in the ash-treated groups, and no root induction occurred. A. incana adapts well to a wide range of soil pH, while R. mucronulatum typically thrives in acidic soils. The high cation content of the ash likely increased the pH of the medium, affecting the growth of R. mucronulatum. Based on these results, future studies will focus on selecting appropriate plants and adjusting concentrations and pH levels to further assess the potential of bamboo by-product ash as a soil fertilizer. Through these efforts, we aim to minimize the environmental impact of bamboo by-products and maximize their practical value as a renewable resource.

The analysis of meteorological factors in forested and non-forested areas reveals significant differences that impact biodiversity, ecosystem functions, and wildfire behavior. This study quantified monthly variations in mean temperature and relative humidity between forested and non-forested areas. Meteorological data were collected from 96 Automatic Synoptic Observing Stations (ASOS) and 341 Automatic Mountain Meteorology Observation Stations (AMOS). The classification of stations was based on MODIS NDVI(Normalized Difference Vegetation Index) stations with an NDVI value of 0.33 or higher were classified as forested, while those below 0.33 were classified as non-forested. Additionally, weather data were collected using weather recording devices (HOBO data loggers) installed in a forested area and a deforested area at Kangwon National University, and the data were compared with existing ASOS and AMOS datasets. The analysis showed that from January to May, average temperatures were higher in forested areas than in non-forested areas, while relative humidity was higher in forested areas from July to September. The data collected using HOBO could not be utilized for analysis for the period between January and April due to partial loss. However, a comparative analysis of the available HOBO data showed that the mean temperature was lower in forested areas compared to non-forested areas in all months, while relative humidity was consistently higher in forested areas throughout the year.

This study focused on analyzing changes in forest fuel based on the structural characteristics of forests. From 2020 to 2023, a monitoring survey was conducted at a managed experimental site in a three ageclass pine forest in the fire-prone Yeongdong region of Gangwon Province, Korea. The experiment included thinning intensity treatments of 40%, 20%, and a control plot. A comparative analysis of forest growth in the study area revealed that the diameter at breast height (cm/year) was 1.51 cm for the 40% thinning treatment, 1.21 cm for the 20% thinning treatment, and 0.71 cm for the control plot. Height growth (m/year) was 0.33 m for the 40% thinning treatment, 0.29 m for the 20% thinning treatment, and 0.22 m for the control plot. Forest fuel analysis showed that the total fuel load (canopy + surface) was 2.96 kg/m² for the 40% thinning treatment, 3.51 kg/m² for the 20% thinning treatment, and 4.21 kg/m² for the control plot. This indicates that the 40% thinning plot had up to 1.4 times less fuel than the control plot. Canopy fuel density was measured at 0.145kg/m³ for the 40% thinning treatment, 0.237 kg/m³ for the 20% thinning treatment, and 0.290kg/m³ for the control plot, demonstrating that higher thinning intensity resulted in lower fuel accumulation within the forest. Additionally, annual litter deposition (ton/ha) was 4.13 tons in the control plot, 4.29 tons in the 20% thinning plot, and 3.68 tons in the 40% thinning plot, with the control plot showing 1.1 times higher litter deposition than the high-intensity thinning plot. This study intends to periodically analyze changes in forest fuel loads based on thinning intensity through forest management monitoring for the development of forest fuel technologies. The findings will contribute to establishing a comprehensive forest management database.

To widen the applications of cellulose beads, sulfonated cellulose beads were prepared by chemically modifying HwBKP fibers with sulfur trioxide pyridine complex (STP), dissolving in tetraethylammonium hydroxide (TEAOH)/urea solvent, and dropping into acetic acid solution. Herein, the effects of the added STP amount on the properties of sulfonated cellulose solution and cellulose beads were investigated. It was observed that the sulfonated cellulose beads exhibited anionic surface charge in a fairly wide pH range, and the degree of substitution of sulfonic acid groups and the zeta potential of the cellulose beads could be controlled by adjusting the amount of STP added. In addition, as the added STP amount increased, the crystallinity of cellulose decreased, the viscosity and surface tension of sulfonated cellulose/TEAOH/urea solution decreased, and the size of cellulose beads increased.

In this study, lignin byproducts are converted into high-performance porous carbon materials for various applications, including CO2 adsorption. The main focus of the research was to explore optimal thermal treatment processes using activating agents such as hydroxides (NaOH, KOH) and carbonates (Na2CO3, K2CO3). The resulting carbonized lignin exhibited different pore structures and specific surface areas depending on the activating agents and temperature used. In particular, when hydroxides were applied, the highest surface area achieved was 2,700 m2/g, about 150 times higher than that of kraft lignin. In addition, the optimized carbonized lignin also significantly increased its CO2 adsorption capacity, reaching 3.6 mmol/g, which is 21 times higher than that of kraft lignin. It also exhibited excellent performances in removing dyes and chromium. Therefore, these findings suggest that lignin-derived carbon materials have great potential as efficient dyes, metal ions, and CO2 adsorbents.

High-resolution land cover maps are essential in fields such as forest resource management, urban green space planning, and environmental protection. In recent years, Unmanned Aerial Vehicles (UAVs) have increasingly become influential in land cover mapping due to their flexibility, low cost, and fast data acquisition capability. However, accurately classifying high-resolution image data collected by UAVs remains a challenge due to the complexity of the data and the substantial computational resources required for processing. To address this problem, this study combines UAV remote sensing data with Object-Based Image Analysis (OBIA) to optimize feature selection to improve the accuracy of land cover classification and provide more reliable data support. In this study, combinations of four feature types were evaluated using a Decision Tree (DT) algorithm in eight scenarios. The results showed that a comparison with spectral features alone and the combination of other feature types can significantly improve the classification accuracy. Height features contribute the most to enhancing the classification results, followed by spectral and geometric features, while the contribution of texture features is relatively limited. In addition, the optimal feature combination selected by the Recursive Feature Elimination (RFE) method further validates its effectiveness in improving land cover classification results. Finally, the best feature combination achieved a classification accuracy of 72.00% and a Kappa coefficient of 0.6543, proving the effectiveness of the feature selection and optimization strategy.