Research Articles

This study aimed to assess the economic efficiency of laurel harvesting (Laurus nobilis L.) in Andırın, Kahramanmaraş, Türkiye. To achieve this, a household survey with 51 participants involved in laurel harvesting was conducted to identify the socio-economic factors influencing laurel harvesting. Principal component analysis (PCA), Sperman’s correlation analysis, and multiple linear regression modeling were conducted to analyze the relationships between socio-economic factors and laurel harvesting. Exploratory analysis of the dataset showed that laurel is an essential income source for almost 90% of households, particularly during agricultural off-seasons. However, only about 10% of the respondents considered laurel harvesting a profitable business. Statistical analyses revealed that distance to the town-city center, daily harvest earnings, and selling location are key factors in determining profitability from laurel harvesting. The current study’s evidence strongly supported the conclusion that market asymmetries and socio-economic heterogeneity shaped the viability of non-timber forest product-based livelihoods. On the other hand, the findings directly supported the Multiple United Nations Sustainable Development Goals (SDGs), particularly SDG 1 (No Poverty), SDG 8 (Decent Work and Economic Growth), SDG 12 (Responsible Consumption and Production), and SDG 15 (Life on Land). Enhancing local producer autonomy in pricing and market access emerged as a crucial factor in promoting equitable and sustainable laurel utilization in rural forest economies.

Engineering properties of Turkish pine wood were evaluated to determine effects of a bio-oil thermal immersion process. Wood samples were impregnated with linseed oil, castor oil, and a mix of both oils. The investigation encompassed antilarvicidal activity, bending and compressive strength, anisotropic swelling, thermogravimetric analysis (TGA), and Fourier transform infrared (FTIR) spectroscopy. Linseed and castor oils demonstrated potent antilarvicidal properties, achieving 100% and 92% mortality rates, respectively. The mixed oil exhibited 79.2% mortality. The thermal immersion treatment significantly enhanced the bending and compressive strength, and linseed oil yielded the highest improvements at 28.7% and 77.0%, respectively. Anisotropic swelling notably decreased. The linseed oil showed the greatest reduction (7.1%) and the mixed oil the least (2.7%). TGA results indicated improved thermal stability, with weight losses of 1.7%, 2.0%, and 2.2% for linseed oil, castor oil, and mixed oil, respectively. FTIR analysis revealed new peak regions ranging from 1159 to 3398 cm⁻¹ and suggested significant interactions between the bio-oils and the cell wall components, particularly for linseed oil. In conclusion, the thermal bio-oil immersion treatment effectively improved the selected properties of this wood.

This study explores the colorimetric sensing of chlorpyrifos (CP) pesticides using neem root extracts-synthesized silver nanoparticles (NRE-AgNPs). The NRE-AgNPs were synthesized via a cost-effective bio-reduction method from neem (Azadirachta indica) and evaluated for their pesticide’s  colorimetric sensing property. Phytochemical analysis confirmed the presence of tannins (80.4 mg/mL), phenols (60.8 mg/mL), flavonoids (54.6 mg/mL), alkaloids (28.9 mg/mL), reducing sugars (59.1 mg/mL), and cardiac glycosides (47.6 mg/mL), which facilitated nanoparticle formation and stability. Scanning electron microscopy revealed nanoparticles with an average particle size of 68.3 nm, while energy-dispersive X-ray spectrum confirmed the presence of silver (0.14% atomic, 0.25% weight) alongside stabilizing organic compounds. UV-Vis spectroscopy confirmed NRE-AgNP synthesis with a surface plasmon resonance peak at 405 nm. The nanoparticles responded sensitively to the presence of the chlorpyrifos, especially at 300 to 350 nm, marking a clear deviation from their original 405 nm signature, thus confirming the viability of AgNPs as an optical sensor. This study underscores the potential of neem root-based AgNPs as a sustainable and eco-friendly solution for pesticide sensing, offering promising applications in the environmental field.

Wastepaper-derived fibers, natural starch binders, and micro-fibrillated cellulose (MFC) additives were preliminarily studied as key components in injection-moldable bio-composite formulations. Commercially available paper cups coated with polyethylene, corn starch, and MFC prepared in a laboratory were selected as raw materials. Since the injection molding machine is yet to be developed, handsheets were prepared as a substitute for the future injection-molded composites, and their physical properties were evaluated to assess the promising formulation candidates of recycled fibers, binder, and reinforcing agent. The optimal paper cup powder–starch ratio was 60:40, which balanced the tensile strength, elongation at break, and burst strength of the material while maintaining good processing characteristics and avoiding problems related to dewatering and adhesion to equipment during drying. The incorporation of up to 5% (by weight) MFC considerably improved the mechanical properties of the sheets by enhancing their fiber–fiber bonding. However, increasing the MFC content above 5% prolonged the dewatering time, compromising process efficiency, and making handsheet preparation impossible. These findings suggested that used paper cups, when combined with starch and MFC, could be effectively recycled into injection-molded composite materials, thereby contributing to environmental conservation and the advancement of resource circulation in manufacturing.

Recycling of residual biomass in the form of carbonaceous materials is a sustainable and economically viable management option with zero net carbon dioxide emissions. Mesoporous bamboo biochars were produced via microwave-assisted hydrothermal/soft template treatment. Then they were characterized and evaluated for their adsorption capabilities for three organics. The biochars were found to have mesoporous structures with BET surface areas of 13.0 to 288 m²/g, total pore volumes in the range of 0.017 to 0.313 cm³/g, and average pore diameters between 4.0 and 6.7 nm in size. The surface areas and pore volumes were highly related to the hydrothermal treatment conditions. The mesoporous bamboo biochars showed adsorption amounts for 2-naphthol, berberine hydrocholoride, and Congo red in the range of 35.0 to 155.7, 76.1 to 129.6, 57.9 to 114.4 mg/g, respectively, at the adsorbate concentration of 0.5 mg/mL, and their adsorption capabilities depended on both the porosity and the surface groups. The adsorption of the three organics on the selected sample was a spontaneous and exothermic process with physical adsorption as the dominant mechanism. The adsorption could achieve equilibrium within 20, 40, and 60 min for 2-naphthol, berberine hydrochloride, and Congo red, respectively. This study provides a prospective method to produce biomass-derived mesoporous carbon adsorbents for adsorptive separation of organics from water.

Two rolls of PETG filament (1^# and 2^# filament) from the same manufacturer were placed in a constant temperature and humidity test chamber for moisture absorption pre-treatment for 12 h. The 2^# filament was dried in a special dryer for 8 h. The physical and mechanical properties of the printed samples of 1^# filament (without drying treatment) and 2^# filament (with drying treatment) were compared. The R_a and R_z values of the samples printed on 2^# filament were lower than those of the samples printed on 1^# filament, and the samples printed on 2^# filament were less rough. The light transmission of the samples printed on 2^# filament was higher than that of the samples printed on 1^# filament, and the light transmission properties of the samples printed on 2^# filament were better. The tensile strength and elastic modulus of the samples printed on 2^# filament were higher than those of the samples printed on 1^# filament, and the mechanical properties of the samples printed on 2^# filament were better. Therefore, the drying treatment improved the physical and mechanical properties of ME-3DP models, and this method has high application value.

Bamboo is increasingly recognized as a sustainable biomass resource, supporting the global transition toward renewable raw materials for construction, landscaping, pulp and cellulose production, and high-performance bio-composites. However, intensive harvesting and processing leave behind substantial quantities of leaves, branches, and stem tips that are typically left in the field or incinerated, undermining the material’s overall environmental benefits. Valorizing these by-products is therefore essential to closing the bamboo value loop, yet systematic data on their composition and reuse options remain limited. To address this gap, this work examined the chemical compositions of the by-products (i.e., leaves and branches) of three bamboo species  native to Korea —Giant Bamboo (Phyllostachys bambusoides), Henon Bamboo (P. nigra), and Moso Bamboo (P. edulis)—and characterized the ashes obtained after controlled combustion. All ashes were strongly alkaline (pH 10 to 11) and exceptionally rich in plant-essential nutrients (K, Ca, Mg and P). This is particularly significant, as it is the first study to demonstrate that bamboo by-product ash is a nutrient-dense material with inherent liming properties, making it suitable for use as a fertilizer or soil amendment. These findings lay an important foundation for the future agricultural and industrial utilization of bamboo residues.

In serviceability limit state, one-dimensional approaches are commonly used to estimate the bending stiffness and vertical displacement of cross-laminated timber (CLT) panels, such as the shear analogy method combined with mechanics of materials equations. Despite their simplicity, these equations disregard the orthotropic nature of wood’s elastic properties and the actual dimensions of CLT panels (treated as beams), affecting displacement predictions. In this context, a parametric study was conducted in this paper using the finite element method. Then, symbolic regression was applied to propose a correction factor for adjusting the stiffness of CLT panels obtained using the shear analogy method. The symbolic regression model for the correction factor demonstrated high accuracy (R² = 0.9834). Adjusting the shear analogy stiffness with the proposed correction factor reduced the maximum error from 18% to 2% compared to the original method and numerical results. The model retained its accuracy in additional simulations, with percentage errors ranging from 0 to 1%.

Biological yield and quality are critical indicators for evaluating silage corn (Zea mays). Among these, biological yield is closely associated with multiple traits of the crop. This study recorded data of 10 traits over two years for 37 silage corn varieties cultivated in hilly mountainous regions of China. Multivariate analysis revealed correlations among all 10 traits. Using correlation data, principal component analysis, cluster analysis, and ridge regression were applied to classify the 37 silage corn varieties into six distinct groups. Key findings identified plant height, ear height, greenness retention rate, and dry weight as critical variables for developing a mathematical model to evaluate silage corn yield and estimate its biological fresh weight. Results indicated that when screening for high-biological-fresh-weight silage corn varieties, priority should be given to those with longer growing periods, compact plant types, superior greenness retention, and higher dry weight. Finally, comparative analysis of biological yields of high-yielding silage corn in Sichuan Province, China, provided actionable references for optimizing silage corn cultivation in local hilly regions.

Raw sawmill wood adsorbent (RSWA) and sawmill wood biochar adsorbent (SWBA) were evaluated as eco-friendly materials for removing cadmium ions (Cd²⁺) from aqueous solutions. The sawmill waste was thermally treated, and the resulting biochar was characterized using FT-IR, SEM, and BET analyses, revealing a rough, porous structure comprising functional groups that enhance adsorption. Batch adsorption experiments demonstrated that SWBA exhibited a higher adsorption capacity (85.4 mg/g at 45 °C) compared to RSWA (78.6 mg/g at 40 °C), with equilibrium times of 180 min for SWBA and 150 min for RSWA. Adsorption efficiency was pH-dependent, with optimal removal occurring at pH 6 for SWBA and pH 5 for RSWA. Kinetic modeling confirmed that adsorption followed the pseudo-second-order model, while isotherm studies indicated a stronger correlation with the Freundlich model. Thermodynamic analysis confirmed the process to be endothermic and spontaneous. Desorption studies revealed a decline in adsorption efficiency over multiple cycles, with RSWA exhibiting slightly better desorption performance than SWBA. These findings highlight sawmill wood biochar as a cost-effective and sustainable solution for wastewater treatment, particularly in heavy metal removal.