Research Articles

Surface properties of wood materials were determined before and after coating with cellulosic varnish doped with aloe vera gel. For this purpose, samples were prepared from Anatolian black pine (Pinus nigra subsp. pallasiana), fir (Abies nordmanniana subsp. bornmulleriana Mattf.), Ayous (Triplochiton scleroxylon K. Schum), and Scotch pine (Pinus sylvestris L.) woods in accordance with TS 53 (1981) and TS ISO 3129 (2021) principles and then coated with cellulosic varnishes doped with 0%, 5%, 10% and 15% aloe vera (L.) gel according to ASTM D3023-98 (2017) principles. Color changes according to ASTM D2244-21 (2021) and surface glosses according to TS EN ISO 2813 (2014) were determined on varnished surfaces. As the percentage of aloe vera gel in the varnish increased, the red color tone, yellow color tone, total color change, glossiness perpendicular and parallel to the fibers, and difference values decreased. Aloe vera gel can be preferred as an additive in cellulosic varnish in applications where the objective is no change or minimal change in the color and glossiness values, depending on type of wood and area of use.

Separate and combined effects of nanocellulose, cationic polyacrylamide, cationic starch, and bleached softwood kraft fibers were evaluated when producing recycled packaging fluting paper. The focus was on enhancing the structural integrity and performance of this paper product, which is essential for packaging applications. Treatments included 10% refined bleached softwood kraft pulp, 5% cellulose nanofibers, 2% cationic starch, and 0.2% cationic polyacrylamide. Combined treatments involved 5% cellulose nanofibers with 2% starch and 5% cellulose nanofibers with 0.2% cationic polyacrylamide. Handsheets with a grammage of 127 g/m² were produced and tested for physical, mechanical, and microscopic properties. Results showed that these additives, either independently or in combination, improved the properties of the paper. The combination of 5% nanocellulose and 0.2% cationic polyacrylamide yielded the highest density and tensile strength, along with the lowest water absorption. This treatment also enhanced critical strengths in the ring crush and corrugated medium tests, making it optimal for packaging paper production. Electron microscopy revealed reduced porosity in handsheets from combined treatments, which may negatively impact water absorption. Further research is needed to optimize these additives while addressing their effects on water absorption.

Grounded Theory was employed to analyze consumer perceived value of sustainable bamboo-woven fashion accessories in Chinese e-commerce, emphasizing green consumption behaviors, awareness of resource reuse, and integration of cultural significance. Unlike prior research focusing on design-stage preferences, the study investigated real consumer feedback from e-commerce reviews, social media comments, and interviews. Findings revealed four key perceived value dimensions: functional, emotional, social, and green value. Among them, emotional value (aesthetic experience and design innovation) was indisputably the strongest driver of consumer attitudes, while functional value highlights craftsmanship, durability, and usability. Social value relates to cultural identity and service experience, whereas green value, despite consumer awareness, has a weaker direct impact on purchasing decisions. The study also explored bamboo’s adaptability in sustainable fashion, offering insights for product innovation, material development, and branding strategies. Through addressing post-market consumer demand, it contributes to the integration of eco-friendly craftsmanship into circular fashion and sustainable industries.

Tomatoes are widely consumed but highly perishable due to their rapid respiration and delicate skin, causing significant post-harvest losses. Sustainable preservation is essential to maintain quality and reduce food waste. This study investigated aloe vera gel (AVG) as a natural, edible coating to extend tomato shelf life. Tomatoes at the pink ripening stage were coated with AVG for 3 and 6 minutes, then stored at 10 °C and 85% relative humidity for 16 days. The physicochemical traits pH, firmness, moisture content, total soluble solids (TSS), and microbial load were assessed every four days. AVG coatings slowed declines in pH, firmness, and moisture content compared to controls (p<0.05). Non-coated tomatoes dropped from pH 4.48 to 2.87, while 3- and 6-minute coated samples retained higher pH (3.28 and 3.65). Firmness fell to 0.56 kg/cm² in controls, but coated samples retained 1.18 and 1.50 kg/cm². Coated tomatoes had higher final moisture (78.35 to 80.25%) than controls (70.45%) and less weight loss (29.55 to 30.26 g vs. 28.11 g). TSS levels remained higher in coated tomatoes (3.10 to 3.40 °Brix vs. 2.40 °Brix), with lower microbial counts (2.95 and 2.16 vs. 4.24 log CFU/g). These results support AVG as an effective, eco-friendly method for preserving tomato quality.

The near-infrared (NIR) spectral reflectance characteristics of wood cross sections are commonly employed for wood species classification. Both specular and diffuse reflectance spectral curves of wood cross sections can be used. However, which one is more effective for classification and whether classification models trained on these two spectra can be used interchangeably have not yet been explored. In this study, the NIR spectral curves of wood cross sections from 64 common timber species were used to evaluate the specular and diffuse reflectance spectral profiles through five classifier models—namely, the support vector machine (SVM), k-nearest neighbors (KNN), convolutional neural network (CNN), decision tree (DT), and nearest class mean (NCM) classifiers. The classification accuracies of specular and diffuse reflectance curves using SVM classifier were 88.43% and 88.02%, respectively, whereas other classifiers exhibited lower classification accuracy, with specular reflectance spectral classification accuracy consistently outperforming diffuse spectral classification. Additionally, experimental results demonstrated that correct classification rate of the testing dataset after cross-use was less than 16%, indicating that classifier models trained on these two spectra could not be used interchangeably. In conclusion, this study suggested that specular reflectance NIR spectral curves are more suitable for wood species classification.

Winter pruning of grapevine branches is essential vineyard management, and knowledge of the biomechanical properties of branches is crucial for effective pruning. This study analyzed the dynamic behavior of grapevine shoots through axial–radial tensile, three-point bending, and shear tests. The axial elastic modulus, the radial elastic modulus, and the flexural modulus of grapevine shoots were 797 MPa, 79.8 MPa, and 5890 MPa, respectively. A finite element model of the grapevine shoot was established using the measured data, and a three-point bending simulation was conducted. The flexural modulus value obtained from the simulation was 5700 MPa, with a deviation of 3.37% from the experimental average, demonstrating the model’s accuracy. Moreover, a mathematical regression model was developed to describe the relationship of the branch diameter with its maximum shear force and shear torque. Shear test simulations revealed the stress distribution during the shear process, with the maximum shear force and torque deviating 9.60% and 12.11%, respectively, from the experimental averages. This study provides data support for grapevine pruning automation. In the future, these findings may contribute to the development of automated mechanical pruning equipment for grapevines.

Wood plays an essential role in civil construction due to its structural and sustainable properties. The longitudinal (E) and the transverse (G) modulus of elasticity are crucial for designing beams under bending, where combined deformations occur due to normal and shear stresses. However, the estimation of G for native Brazilian species still lacks standardized experimental procedures, with the simplified normative relation G = E/16 being commonly adopted. This study aims to estimate both E and G based on the Euler-Bernoulli and Timoshenko beam theories through three-point and four-point static bending tests. Four native Brazilian species and five ratios between the length and height of the cross-section (L/h) were analyzed. The results showed that, for L/h ratios below 18, the apparent modulus of elasticity was significantly affected by shear effects, exhibiting reductions of up to 18.47%. The E/G ratio ranged from 14.84 to 21.15, corresponding to a reduction of up to 7% and an increase of up to 32%, respectively, about the value proposed by ABNT NBR 7190-1 (2022). These results highlight the importance of considering specimen proportions and shear effects in the estimation of wood elasticity moduli obtained from bending tests.

Core user demands of wardrobe furniture design are becoming increasingly complex. Traditional design methods fail to systematically analyze the interrelationships among these multidimensional factors. This study integrated web text mining, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method, and the Analytic Network Process (ANP) to construct a causal network model for wardrobe design, and further optimized design proposals through the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). By applying Python technology, user evaluation data were extracted from mainstream e-commerce platforms, with high-frequency user demand keywords being identified and categorized into four key dimensions. DEMATEL was employed to quantify the causal intensity and centrality of the identified factors; ANP was subsequently utilized to construct a network hierarchy, revealing the feedback mechanisms between functional modules and user experience. Finally, TOPSIS was applied to rank three design proposals, among which Option 3—featuring flexible space partitioning, auto-sensing lighting, and anti-tip design—was selected as the optimal solution. The findings demonstrate that integrating text mining with the DEMATEL-ANP-TOPSIS framework can effectively identify the prioritization of user needs, thereby providing scientific decision support for furniture design.

Under environmental stress, the migration and accumulation of heavy metals in soil profoundly affect ecosystem dynamics and environmental risks. This study applied CiteSpace bibliometric methods to visually analyze 1,768 publications from 2000 to 2024, based on the Web of Science Core Collection. The analysis included publication trends, keyword frequencies, international collaboration, core authors, and institutions. Results show a shift in focus from pollution identification and mechanisms to health risk assessment and material-based remediation. Notably, increasing attention has been given to lignocellulose-derived amendments such as humic acid and biochar for their potential in stabilizing soils under compound environmental stressors. Leading institutions such as the Chinese Academy of Sciences and U.S. research bodies have played prominent roles, while high-impact journals, including the Journal of Biogeography, reflect strong academic output. Keyword clustering and burst analysis highlight emerging cores like “speciation,” “health risk,” and “biochar,” showing a phase-based evolution of research themes. The field’s short citation half-life, frequent keyword bursts, and multidisciplinary integration confirm its status as a research frontier. This study provides a comprehensive knowledge map and valuable insight into the dynamic behavior of soil heavy metals under environmental stress.

To improve the efficiency of holly pruning, effectively solve the labor intensity of manual handheld pruning machines or scissors for pruning holly, and the frequent replacement of tools when pruning different shapes of hollies with small holly pruning machines, this study designed a holly pruning machine with adaptive tool adjustment. A combination of theoretical calculations, fluid dynamics simulation and analysis, and field testing was employed to design spray application mechanisms and verify their feasibility. Visual distance measurement and target recognition algorithms were used to design visual mechanisms, which were experimentally validated. Based on the principles of kinematics and dynamic simulation analysis, adaptive tool adjustment mechanisms were designed, and the key factors influencing the pruning smoothness rate and residual branch rate of the pruning equipment were identified. Based on the force analysis and parameters from the experimental results, the machine performed well, with a cutting mechanism motor speed of 20.941 kr/min, a tool tilt angle of 50.472°, and a walking speed of 0.914 m/s. The machine achieved a pruning smoothness rate of 79.266% and a residual branch rate of 8.101%, meeting the requirements for holly pruning in horticultural operations.