Search Results (1,657)

This study integrates microbial biotechnology, bioprocess optimization, and circular bioeconomy principles to valorize oilseed agro-industrial coproducts as low-cost inducing substrates for lipase production. Palm kernel cake (PKC), canola cake, andiroba cake, and brewer’s spent grain were evaluated as carbon sources for extracellular lipase production by the wild-type strain Trichoderma sp. LEPM-711 under submerged fermentation. Qualitative screening in olive oil/rhodamine B medium confirmed the strain’s lipolytic potential. Among the substrates tested, PKC showed the strongest induction, reaching 4.68 U mL⁻¹, and was therefore selected for nitrogen supplementation and statistical optimization. Peptone supplementation increased lipolytic activity to 8.41 U mL⁻¹ after 72 h. A Plackett–Burman design identified CaCl₂·2H₂O, CoCl₂·6H₂O, and peptone as significant medium components, while response surface methodology established the optimal operational conditions as pH 6.0, 10⁶ spores mL⁻¹, and 2% (w/v) PKC. Under these conditions, the crude enzymatic extract reached 18.31 U mL⁻¹ at pH 7.0 and 45 °C, corresponding to an approximately 3.9-fold increase over the initial PKC fermentation. These findings support the use of Trichoderma sp. LEPM-711 and oilseed coproducts as a sustainable platform for enzyme production and residue upgrading within applied natural sciences. Full article

Accurate classification of oil palm fruit maturity is critical for optimizing harvest schedules and maximizing yield. To address the limited discrimination accuracy caused by subtle color variations, this paper proposes an LAB dual-branch feature fusion method for five-class oil palm fruit maturity classification. A classification model named CMF-Net is constructed, in which the luminance (L) and chrominance (ab) components are decoupled into two parallel branches to separately extract structural and color information. An input adaptation module is introduced to perform channel mapping and feature enhancement. During feature fusion, a gated fusion mechanism is employed for adaptive integration of the dual-branch features, followed by a BiFPN module for multi-scale feature interaction. A multi-level attention enhancement module composed of coordinate attention and self-attention is designed to strengthen key-region perception and global contextual modeling. An auxiliary color regression constraint and ordinal supervision are incorporated to improve the model’s sensitivity to subtle chromatic changes and the progressive relationship among maturity stages. The proposed algorithm provides a color-decoupled and order-aware representation framework for gradual fruit maturity classification, offering a useful reference for fine-grained agricultural visual classification tasks involving continuous color transitions. Experimental results on a public dataset show that CMF-Net achieves a validation accuracy of 94.66%, outperforming mainstream models by 1.3–6.1 percentage points, while also yielding superior recall and F1-score. Full article

The precision of oil palm fresh fruit bunch (FFB) ripeness classification directly determines the extraction efficiency and chemical quality of the resulting crude palm oil (CPO). Traditional manual inspection at reception ramps remains labour-intensive, time-consuming, and subjective. To address these issues, this study presents a lightweight deep learning framework for automated oil palm FFB ripeness classification trained on a field-collected dataset of 857 images covering four ripeness classes (Over-ripe, Ripe, Under-ripe, and Unripe). Six lightweight classification backbones are evaluated, including MobileNetV2, EfficientNetV2B0/B1, and YOLO variants. An intra-class half-mixing augmentation with geometric transformation is proposed to address minority-class imbalance. Overall, YOLOv8n-cls achieved the highest accuracy (95.6%), followed by EfficientNetV2B0/B1, YOLO11n-cls, YOLO26n-cls, and MobileNetV2, respectively. In addition, all YOLO-family models achieved a recall score of 1.00 for the minority class while obtaining the highest $F_1$ scores for the other classes. The experimental results suggest that the proposed augmentation method enables lightweight deep learning models to achieve promising classification performance on an imbalanced field-collected FFB dataset while improving minority-class detection. Full article

Bacterial and fungal skin infections are common in companion animals and often require antimicrobial therapy, contributing to antimicrobial resistance. This study developed shampoos containing red palm oil (RPO) and extracts of Rhinacanthus nasutus (RN), Curcuma longa (CL), Zingiber montanum (ZM), and Zingiber officinale (ZO), which provide antibacterial, antifungal, antioxidant, and anti-inflammatory activities. Extracts were obtained using MAE and were evaluated for phytochemical composition, total phenolic content, antioxidant activity (DPPH assay), anti-inflammatory activity (COX-2 inhibition), and antimicrobial activity. RPO contained high levels of vitamin E and β-carotene. Rhinacanthin, curcumin, terpinen-4-ol, and 6-gingerol were the major phytochemical constituents of RN, CL, ZM, and ZO extracts, respectively. All extracts significantly reduced COX-2 expression (p < 0.05), while RN exhibited the strongest antioxidant activity (DPPH IC₅₀ = 15.23 ± 0.53 µg/mL). RN and ZM demonstrated the strongest antibacterial activity against Staphylococcus aureus and methicillin-resistant Staphylococcus aureus (MIC = 8 µg/mL; MBC = 8–16 µg/mL), while ZO exhibited the strongest antifungal activity against Malassezia pachydermatis and Microsporum gypseum (MIC = 2, 2 µg/mL; MFC = 2, 16 µg/mL). The developed shampoos containing RPO and the four herb extracts showed suitable pH values, stable viscosity, antibacterial inhibition, and antifungal inhibition (p < 0.05). Full article

The instability of marine low-sulfur fuel oil caused by asphaltene precipitation poses significant operational challenges in the shipping industry. This study systematically investigates the dispersing effects of biodiesel derived from three different feedstocks—palm oil, waste cooking oil (WCO), and microalgae oil—and their individual fatty acid methyl ester components on asphaltenes extracted from VLSFO. Biodiesel was selected as a dispersant due to its renewable nature, polar ester functional groups, and variable unsaturation levels, which enable favorable interactions with asphaltene molecules through hydrogen bonding and π-π stacking. Using UV–Visible spectrophotometry, the dispersion performance was quantitatively evaluated under various conditions including dispersant concentration, temperature, storage time, and molecular structural characteristics. The results demonstrate that microalgae oil biodiesel exhibits the most superior asphaltene dispersion capability among the three biodiesels, with a dispersion improvement index of 35% at 12 g/L, compared to 28% and 22% for waste cooking and palm oil biodiesels. Optimal performance is achieved at 80 °C, where the asphaltene concentration increases by 68% relative to the control, and remains stable within the first 10 days of storage but deteriorates significantly after 30 days due to oxidative degradation. Among individual FAME components, the dispersion effectiveness increases with alkyl chain length from C10 to C20, with the latter reaching a 30% improvement index. Functional group polarity plays a critical role, with carboxylic acid exhibiting a 45% improvement at 14 g/L, substantially outperforming alcohol at 32% and ester at 28%. The degree of unsaturation further enhances dispersion, as the improvement index rises progressively from 20% for saturated methyl stearate to 42% for tri-unsaturated methyl linolenate, representing a 2.1-fold increase. Dynamic light scattering (DLS) measurements confirm that biodiesel addition reduces asphaltene particle size from the micrometer range of 2 to 5 μm down to submicron levels of 200 to 500 nm, while microscopic observations reveal inhibited aggregation. These findings provide theoretical foundations for biodiesel application in marine fuel systems. Full article

Maintaining food systems in the face of climate change (CC) is a major concern. Palm oil is included in many commodities, and oil palms (OPs) will be adversely affected by an inclement future climate, which could cause OPs to experience increases in disease incidence, higher mortality and a decline in growth. Basal stem rot, bud rot and Fusarium wilt of the OP are considered in the present paper, as attempts to control these diseases have been unsuccessful. A new approach may be the replacement of compromised OPs with different crops better suited to the future climate and which may exhibit fewer diseases initially because of the “parasites lost” phenomenon. Maintaining a vegetable oil product is an important advantage of this approach. How CC will affect OPs has been determined previously by CLIMEX modelling. The modelling of a future suitable climate has also been carried out for soybeans, maize and the common bean using the same modelling parameters. This enables direct comparisons with the OP production in countries such as Colombia, Nigeria and Papua New Guinea. Limited data for rapeseed are also available. The results show that the suitability of future suitable climate for OPs was much reduced in these countries and that for soybeans remained beneficial. Under these conditions, soybeans may exhibit fewer diseases, as they would be an introduced and annual crop. Maize exhibited far fewer advantages, and the common bean and rapeseed showed none. Maize exhibited potential advantages in Nigeria until 2050. A novel method for adapting to the serious diseases, poor growth and mortality of OPs would be to grow soybeans in regions similar to those in which OPs currently grow, but for which modelling suggests that their health will become limited. Plans, which could be modified when real-time data become available, could be made for replacing OPs with soybeans. This current paper provides a novel method for mitigating the future diseases, poor growth and mortality of OPs whilst maintaining valuable oil production. Full article

Accurate monitoring of oil palm plantations is important for balancing economic development with environmental conservation in Southeast Asia. However, existing plantation maps often suffer from low spatial resolution and a lack of recent temporal coverage, impeding effective surveillance of rapid land-use changes. In this study, we propose a deep learning framework to generate 10 m resolution oil palm plantation maps for Indonesia and Malaysia from 2020 to 2024, utilizing Sentinel-2 imagery without requiring new manual annotations. To address the resolution mismatch between coarse 100 m historical labels and 10 m imagery, we employ a U-Net architecture optimized with Determinant-based Mutual Information (DMI). This approach effectively mitigates the influence of label noise. We validated our method against 2058 manually verified points, achieving overall accuracies of 70.64%, 63.53%, and 60.06% for the years 2020, 2022, and 2024, respectively. The gradual decline in accuracy with time is consistent with a growing temporal mismatch between the 2016 historical reference labels and the later prediction years. At the regional scale, the mapped oil palm area suggests a peak in 2022 followed by a lower mapped extent in 2024. Land cover transition analysis further indicates exchanges with cropland and flooded vegetation, which should be interpreted together with the reported accuracy and uncertainty. Given the moderate per-year accuracies and the temporal mismatch between the 2016 supervision and the later prediction years, these results should be interpreted as regional-scale indicators rather than pixel-level change maps. The generated maps can support regional monitoring, sustainability assessment, and prioritization of areas for further validation. Full article

The rapid expansion of oil palm cultivation in the Colombian Orinoquia has generated economic benefits but also environmental and social pressures associated with biomass residue management. In this context, residue valorization through bioproduct production has gained relevance as a strategy linked to circular bioeconomy and regional sustainability. This article analyzes the prioritization of socioeconomic impacts associated with the reuse of oil palm residues in the department of Meta, Colombia, using a participatory multicriteria approach. The method combined the Analytic Hierarchy Process (AHP), the Ratings technique, and the DEMATEL method to evaluate social, economic, and environmental dimensions identified together with territorial stakeholders. The assessment process involved 31 participants representing academia, public institutions, productive sectors, financial entities, and civil society organizations. The results showed greater prioritization of impacts associated with employment generation and local economic development. The DEMATEL analysis revealed that economic and employment-related criteria exerted stronger influence within the evaluated system. Environmental sustainability also reached high relevance, whereas gender equity and post-pandemic regional resilience obtained lower relative weights in the prioritization process. Full article

This study applies a screening, prospective social life cycle assessment, integrating process-simulation-derived inventory data with worker-hour-based impact metrics and country–sector social risk profiles from the SOCA/PSILCA database to estimate potential risk and opportunity exposure across the avocado oil supply chain in Colombia. For the local community and societal categories, indicators such as unemployment and contribution to economic development are interpreted based on national statistics, while worker-related indicators, including fair salary and working time, are assessed in relation to sectoral wage structures and living wage benchmarks. Results suggest that potential social risk exposure is primarily associated with worker-related indicators, with contributions concentrated in refining and upstream agricultural stages, reflecting underlying labor conditions and sectoral characteristics. In comparison with a palm oil baseline scenario, increases of up to 62% in medium-risk hours for fair salary and 49% for working time are observed in the avocado oil case. Other indicators show more moderate variation, with unemployment indicator impact increasing by 24% and contribution to economic development decreasing by 7%. However, these findings largely reflect the redistribution of pre-existing country–sector risk profiles rather than system-specific or empirically validated social impacts. Consequently, the results should be interpreted as indicative of potential exposure under screening conditions, rather than definitive measures of social performance. Full article

Sophorolipids (SLs) produced from Starmerella bombicola using four different secondary substrates such as refined, bleached, and deodorized palm olein (RBD PO), RBD palm kernel olein (RBD PKO), RBD coconut olein (RBD CO) and fatty acid methyl ester (FAME) waste are reported. Their interfacial characteristics at medium-chain triglyceride (MCT) oil-water interface and ability to form nano/submicron emulsions were studied. The effects of SLs from different sources, SL concentrations and blend ratios of SLs and soybean lecithin on characteristics of emulsions produced by ultrasonication were examined. Initially, emulsion formed using SLs coded (from F2 to F5) showed large droplets (d₃₂ > 1000 nm) and poor stability. They were then blended with soybean lecithin at a ratio of 3:1 to produce emulsions coded F6 to F9 with smaller droplets (d₃₂ < 400 nm) and great stability over a range of temperatures (from 40 °C to 90 °C) and pH values (from 3 to 9). However, highly acidic (pH 2) and low ionic strength (1 mM NaCl) processing caused the separation of the emulsions. These emulsions also displayed potential antimicrobial activities towards Bacillus cereus and Pseudomonas aeruginosa, as well as cytotoxic effects against the human epithelial colorectal adenocarcinoma cell line (Caco-2). These results illustrated that stable emulsions required a mixture of SLs and soybean lecithin. Full article

The present paper highlights a critical assessment of the large-scale production and accumulation of date palm (Phoenix dactylifera) by-products. These have been identified as both serious environmental problems and potential renewable energy sources. Landfilling, burning in fields, and other such poor methods are common among many of the countries producing dates as ways to dispose of huge amounts of date palm by-products. The current literature has been assessed for their utilization in energy generation in the form of a circular bioeconomy with respect to the characteristics and composition of date palm seeds, leaflets, rachis and fibers. The study reveals that thermochemical conversion methods such as pyrolysis, gasification and hydrothermal processes are very efficient for the conversion of date palm residues into bio-oil, syngas and biochar. The resulting bio-oils are, however, rich in oxygen, acidic and unstable in nature and need to be upgraded using a catalytic process. Moreover, the review highlights that advanced catalytic technologies can greatly improve the quality of fuel through deoxygenation and the synthesis of hydrocarbons, resulting in the production of “drop-in” gasoline components and SAFs that have characteristics close to those of regular petroleum-based fuels. Also, artificial intelligence- and machine learning-based modeling techniques appear to offer considerable prospects in the realm of thermokinetic studies, process design, and large-scale implementation. Furthermore, the results point out two environmental advantages that accrue from the date palm valorization process, since biochar generated via thermochemical transformation can be used for seawater desalination. Lastly, the techno-economic evaluation and roadmap of future development directions are provided. Full article

Oleogel-based fat systems were developed using citrus fiber (CF) and cold-pressed pumpkin seed oil by-product (PSB) through an emulsion-template approach and evaluated as palm oil substitutes in a model chocolate sauce system. Oleogels were prepared by varying CF (4–5%) and PSB (0–2%) concentrations and characterized in terms of rheological, textural, and sensory properties and oxidative stability. The emulsions exhibited predominant elastic behavior (G′ > G″), with storage modulus (K′) values increasing from 694.12 to 2242.54 Pasⁿ as CF and PSB concentrations increased. Chocolate sauces formulated with CF–PSB oleogels showed pseudoplastic flow behavior and solid-like viscoelastic characteristics, with K′ values ranging from 89.32 to 356.56 Pasⁿ, compared to 34.84 and 16.95 Pasⁿ for the palm oil (C1) and sunflower oil (C2) controls, respectively. Temperature sweep and thermal loop tests demonstrated improved thermal resistance and emulsion stability in oleogel-containing chocolate sauces. Oleogel-based chocolate sauces also showed superior emulsion stability under thermal cycling and greater oxidative stability compared to the C2 sample. Texture profile analysis revealed increased hardness and spreadability with higher CF and PSB contents, consistent with rheological findings. Oleogel-based chocolate sauces also demonstrated enhanced oxidative stability, with induction period values reaching 18:55 h compared to 5:13 h for the sunflower oil control and approaching the palm oil control (20:13 h). Texture profile analysis revealed increased hardness and spreadability with higher CF and PSB contents. Sensory evaluation indicated that sauces containing 5% CF and 1–2% PSB received the highest scores for flavor, consistency, and overall acceptability. Full article

This study evaluates the life cycle assessment (LCA) of Lufenuron 50-EC pesticide adsorption from aqueous solution using oil palm shell (OPS)-derived activated carbon produced through two activation routes: physical and chemical. The assessment covers environmental impacts associated with feedstock collection, transportation, pre-processing, and post-processing stages involved in producing activated carbon for pesticide removal. The cradle-to-grave LCA technique was applied using the ELCD 3.2 Greendelta v2.18 database and processed with OpenLCA v2.4 using CML-IA baseline method to perform the quantitative life cycle impact assessment. The results for treating 1 m³ of contaminated water show that physical activation route (Route 1) generates a higher environmental burden across all evaluated impact categories compared to chemical route (Route 2). Notably, global warming potential (GWP) reached 117.62 kg CO₂ eq for Route 1 compared to 75.86 kg CO₂ eq for Route 2. This represents a 35.5% reduction with the chemical route, suggesting that the high energy demand associated with thermal process in physical activation generates more significant greenhouse gas emissions. Overall, this study helped identify critical performance points and opportunities for improvement in converting the OPS to an activated carbon transformation process and its application in pesticide contamination control. Full article

Tropical wetlands are highly sensitive to climatic and anthropogenic disturbances, and their macrophyte communities provide valuable information about environmental conditions and habitat structure. This study evaluated the relationship between aquatic macrophyte richness, community composition, and habitat vulnerability to climate change in aquatic ecosystems of the San Luis rural district, Barrancabermeja municipality (Santander, Colombia). Macrophyte communities were characterized at 47 monitoring sites distributed across six mesohabitats: floodplain depressions, swamp, wetland, artificial ponds, naturalized ponds, and stream riparian zones. A total of 63 species belonging to 30 families and 51 genera were recorded. Contrary to theoretical expectations, correlation analyses showed no significant relationship between macrophyte species richness and habitat vulnerability indices (Spearman ρ = −0.118, p = 0.428; Pearson r = −0.069, p = 0.646). However, species richness differed significantly among mesohabitats (Kruskal–Wallis, p < 0.05), indicating strong spatial heterogeneity in aquatic plant distribution. In addition, multivariate analyses using Principal Component Analysis (PCA) revealed that macrophyte community composition was strongly structured by local anthropogenic activities, including livestock farming, oil palm cultivation, and wastewater inputs. Floodplain depressions and artificial ponds were dominated by disturbance-tolerant and eutrophication-resistant species such as Urochloa plantaginea and Salvinia minima, reflecting higher levels of environmental pressure. These results demonstrate that macrophyte community composition, rather than species richness alone, is a more reliable indicator of habitat conditions and anthropogenic disturbance in tropical wetland systems. Overall, this study highlights that taxonomic richness is not a robust predictor of climate-related vulnerability in highly disturbed wetlands and emphasizes the importance of considering species composition and environmental context when assessing ecosystem conditions. Full article

This article describes the development of a compact and affordable variable-temperature NMR instrument designed primarily to measure dynamic molecular motion in solids and liquids. The instrument consists of Lab-Tools’ Mk4 palm-top time-domain NMR spectrometer fitted with a Peltier-cooled variable-temperature probe inside a shimmed Halbach magnet. Measurement of NMR relaxation times T₁, T₂, and ${\mathrm{T}}_1\rho$ is possible over the temperature range −20 °C to 70 °C with cooling and heating rates, and data acquisition is controlled from an integrated mini-PC. The overall footprint of the instrument is roughly that of a shoe box, making both in-the-field and bench-top measurements possible. Applications of this instrument include measuring pore-size distribution in porous rocks, the viscosity of oils and tars trapped in porous rock, the properties of polymers, and the viscosity of the liquid components of foods (e.g. fruits, vegetables and seeds). Results of test measurements for calibrated oils and olive oil are presented together with measurements of molecular mobility in a solid polymer. Full article