Volume 21 Issue 3

Developing sustainable regional agro-industrial practices is essential for countries like Indonesia. Cassava (Manihot esculenta Crantz), significant for food security and commercial use, continues to demonstrate productivity levels beneath worldwide benchmarks. This research assesses the sustainability of Lampung’s cassava agro-industry by integrating Multidimensional Scaling (MDS) and Cross-Impact Matrix Multiplication Applied for Classification (MICMAC). MDS generates a sustainability index including ecological, economic, social, technological, and institutional dimensions. MICMAC analysis determines causal interdependencies among attributes and categorizes them based on driving power and dependence. Data obtained from expert questionnaires and focus group discussions conducted between January and March 2024 indicated a moderate sustainability index of 63.5%. The environmental dimension achieved the highest score of 72.7%, while the technological and institutional dimensions obtained the lowest at 55.03% and 55.2% respectively. The main variables influencing sustainability consist of energy efficiency, waste management, market orientation, and the skill levels of the workforce. The combination of MDS and MICMAC offers an extensive diagnostic and structural perspective. This study proposes recommendations for energy schemes, the development of managerial training programs, and the strengthening of institutional policies. The insights have significance for the development of the cassava agro-industry in Lampung and comparable regions.

Bamboo has become increasingly attractive for applications in construction and engineering due to its rapid growth, renewability, and a high strength-to-weight ratio. However, the poor natural resistance to mold limits its potential in the building industry. Conventional antifungal and decay-resistant treatments developed by domestic and international researchers often suffer from drawbacks such as human and environmental toxicity or poor leaching resistance. In this study, aiming to enhance the decay and mold resistance of moso bamboo (Phyllostachys edulis), a high-voltage electrostatic field was employed to excite metallic particles and embed them into the bamboo surface and interior, where they formed stable chemical bonds with active functional groups. White-rot fungi, brown-rot fungi, and Aspergillus flavus were used to assess resistance, with environmental scanning electron microscopy (ESEM) and other techniques employed to evaluate antifungal performance. Results indicated that bamboo treated at the voltage of 60 kV for 12 h exhibited decay and mold resistance slightly lower than that of chromated copper arsenate (CCA)-treated bamboo but higher than that of untreated bamboo; while high-voltage electrostatic-treated bamboo possessed superior leaching resistance compared with CCA-treated bamboo.

Thymol, a natural active compound, is recognized for its remarkable antimicrobial properties, making it a suitable choice for active agents in food packaging applications. This study focuses on the encapsulation of thymol in chitosan phosphate nanoparticles (CNP) to overcome its limitations, particularly volatility, and incorporates it into bio-nanocomposite films via solvent casting. Moreover, comparison of the effects of pure thymol, CNP, and encapsulated thymol-loaded chitosan phosphate nanoparticle (TCNP) on the film’s properties were also assessed. The film’s chemical interaction (Fourier transform infrared, FTIR), thermal, mechanical, light transmittance, water barrier, antibacterial, toxicity properties, and release test were evaluated. The results disclosed that the incorporation of 5 wt% of TCNP1.0 into the PLA/PBS/NFC films matrix improved thermal stability (0.76%), tensile strength (46.8%), and enhanced water barrier properties, as evidenced by a reduction in water vapor permeability (WVP) by 10.1%. The FTIR analysis demonstrated the presence of intermolecular hydrogen bonds, indicating the compatibility between TCNP and the PLA/PBS/NFC matrix. The bio-nanocomposite films also exhibited noteworthy antibacterial effects and had an inhibitory rate against S. aureus. In summary, bio-nanocomposite films have significant potential as an antibacterial agent in the advancement of innovative bio-based active packaging systems.

People living in densely populated settlements face inadequate sanitation and rising incidences of acute bacterial infections, underscoring the urgent need for effective and sustainable hygienic products. The amphiphilic molecular architecture of β-cyclodextrin (β-CD), characterized by a hydrophobic internal cavity and a hydrophilic external surface, offers a unique platform for designing sustainable additives for hygiene products. This study employs β-CD to improve the mechanical performance and end-of-life management of old corrugated container (OCC)-derived recycled fibers for tissue and towel applications. β-CD operates through dual interactions: its hydrophobic cavity associates with lignin and other hydrophobic moieties via van der Waals interactions, while its hydrophilic exterior forms hydrogen bonds with cellulose, enhancing fiber–water interactions and hydrogen bonding. These coupled molecular interactions enhance dry strength while promoting fiber swelling, water penetration, and rapid disintegration, which is essential for flushability and recyclability. In dual-stage systems combining β-CD with low dosage of glyoxalated polyacrylamide (g-PAM), pretreated OCC (POCC) fibers achieved an immediate wet tensile comparable to g-PAM-only at a higher dosage while exhibiting substantially reduced disintegration time. Overall, this work demonstrates a viable pathway for producing recyclable and flushable recycled-fiber hygiene products that maintain high dry and immediate wet tensile strength during use, yet disintegrate rapidly during flushing or repulping.

This study examined how elevation, habitat diversity, and soil nitrogen interact to influence forest biomass across ecological zones. A field survey was conducted using 300 plots, systematically allocated across three habitat types with equal representation. The relationships were measured using bivariate analysis, correlation study, and structural equation modeling (SEM). The habitat-unified model revealed that elevation had a statistically significant direct effect on biomass (β = 0.71, p < 0.001), as well as indirect effects through species richness (β = 0.37, p < 0.001) and soil nitrogen (β = 0.15, p < 0.05). Moist forest habitats were shown to increase soil nitrogen content  (β = 0.37, p < 0.001) and species richness (β = 0.28, p < 0.001) significantly. Habitat-specific models revealed that the strength and direction of these relationships varied between forest types. Degradation had a strong negative effect on biomass in subtropical ecosystems (β = 0.34, p < 0.0001) and in moist temperate forests (β = 0.61, p < 0.0001). Degradation reduced biomass in subtropical and moist temperate forests but had no significant effect in dry temperate forests. However, it strongly decreased soil nitrogen and, together with elevation, constrained biomass.

Dielectric properties of tree samples belonging to Anatolian chestnut, sessile oak, and Scots pine species were measured in the frequency range of 100 Hz to 1 MHz. Test samples were subjected to three different surface conditions, namely control (CW), two-week water-soaked (SW), and two-coat varnish application (VW). The test samples were characterized by analyzing capacitance (C), dielectric properties (ε′, ε″, and tanδ), AC electrical conductivity (σ_ac), normalized conductance (G/ω), and impedance components (Z′ and Z″). Frequency analysis revealed that the SW samples exhibited higher C, ε′, ε″, tanδ, and σ_ac values, whereas the VW samples maintained low and stable dielectric properties because of the insulating effect of the varnish layer. The σ_ac values reached approximately 10⁻³ S cm⁻¹ in the SW samples but remained around 10⁻⁷ S cm⁻¹ in the CW and VW samples, confirming their insulating behavior. In addition, the G/ω and impedance (Z′ and Z″) analyses demonstrated distinct electrical responses among the conditioning treatments, with the impedance values following the order VW > CW > SW. These findings provide insights into the dielectric behavior of wood under varying surface conditions. Biologically based dielectric materials could facilitate future advancements in insulation components and moisture-sensitive sensing technologies.

The flexural behavior and intrinsic mechanical properties were studied for polypropylene (PP) composites reinforced with 20 to 50 wt.% henequen strands, using maleic anhydride grafted polypropylene (MAPP) as compatibilizer. The maximum strain at break of the fibers was estimated by regression-based extrapolation (ε = 8%), which enabled calculation of the microfibrillar angle (MFA = 22.8°) using a modified Satyanarayana approach. Together with cellulose content and crystallinity, the resulting structural parameter (δ = 1.72) confirmed the suitability of henequen strands as reinforcement for thermoplastic composites. The composite flexural modulus exhibited a linear increase with fiber volume fraction (R² = 0.99), rising from 1.15 GPa for neat PP to 3.75 GPa at 50 wt.% fiber content, while the strain at break decreased consistently with increasing reinforcement content. Predictions obtained using the Hirsch model and the modified rule of mixtures, with efficiency factors (η_e) ranging from 0.45 to 0.55, showed good agreement with experimental results. Furthermore, three micromechanical models, Hirsch, Tsai–Pagano, and Nielsen, yielded consistent intrinsic flexural moduli for the henequen strands, in the range of 16 to 17 GPa. These results highlight the reinforcing potential of henequen strands and reveal their effectiveness in increasing the flexural stiffness of polypropylene-based composites.

This study presents a novel approach to mitigating the environmental impact of non-degradable industrial insulators used in air conditioning pipe. It focused on evaluating and optimizing polymer composites reinforced with rice husks and coconut husks as sustainable thermal insulation materials. This study involved two main phases: First, evaluation of the thermal and mechanical properties of rice and coconut husks reinforced polyurethane composites. Second, determination of the optimal reinforcement ratio using a hybrid multi-criteria decision-making (MCDM) methodology that integrates the Analytical Hierarchy Process (AHP) and the Additive Ratio Assessment (ARAS) techniques. Composites were fabricated with reinforcement ratios ranging from 5% to 25% by weight. Thermal conductivity results, ranging from 0.041 to 0.0486 W/m·K, confirmed the insulative potential of all composite samples, which corresponded to the range reported for industrial thermal insulators. Mechanical testing revealed enhanced tensile strength, particularly with 25 wt% coconut husks, achieving a value of 0.744 MPa. The ARAS method concluded that the optimal composition for insulation performance is 10% rice husk and 25% coconut husk reinforcements. This study advances sustainable thermal insulation materials. In addition, it offers a systematic framework for selecting the optimal reinforcement ratio for biocomposites.

Machine Vision (MV) software has emerged as a powerful tool for timber species identification, offering significant advantages including species-level accuracy, cost-effectiveness, and the elimination of human errors. The development of MV software relies on three major supporting technologies: computer vision, machine learning (ML), and deep learning (DL). This paper provides an in-depth exploration of the role of DL, with a particular focus on convolutional neural networks (CNNs), in enhancing MV software for timber identification. The potential of CNN architectures is examined in detail, including a review of commonly used CNN models and their effectiveness in identifying different timber species. This paper also discusses current practices in developing CNN models for integration into MV software for timber identification tasks, highlighting the standards and procedures researchers should follow to ensure optimal performance and reliability. Additionally, the challenges associated with implementing CNN models for timber identification are addressed. They include limited model usability due to the diversity of timber species and geographical variation. Variability in methodologies, imaging devices, and data processing approaches across studies further complicates the comparison and integration of results. This paper emphasises the need for standardised practices and further empirical research to address these inconsistencies and improve CNN-based MV systems for timber identification.

Drought is one of the most significant environmental stress factors negatively affecting fruit tree cultivation because they are highly water-dependent. Water shortage adversely affects the growth and development of fruit trees, leading to a severe reduction in productivity and fruit quality. In particular, drought harms photosynthesis, which is essential to produce carbohydrates. Therefore, developing mitigation strategies and effective water management is vital for maintaining fruit tree health and sustainability. This study was conducted to investigate the influence of adding soil compost individually and in combination with spraying of magnesium sulphate (MgSO₄) on improving the soil fertility, productivity, and fruit quality of date palm cv. Barhi. The date trees were fertilized with 5 and 10 kg of compost, and then they were sprayed with 0.5, 0.75, and 1 % MgSO₄ four times: starting from mid-February with one-month intervals between sprays, as compared to untreated trees as a control. The results revealed that combining soil-applied compost with foliar spraying of MgSO₄ enhanced the productivity and fruit quality of date palm. The best results were obtained by adding 10 kg compost + 1% MgSO₄, followed by 10 kg compost + 0.75% MgSO₄ and 5 kg compost + 1%  MgSO₄.