Search Results (396)

The research aimed to evaluate the effect of high monounsaturated cold-pressed oil addition on the inhibition of refined rapeseed oil degradation during heating at frying temperature. Cold-pressed rapeseed, coriander seed, and apricot kernel oils were added in amounts of 5 and 25%. Refined rapeseed oil without additives and refined rapeseed oil supplemented with tert-butylhydroquinone (TBHQ) were negative and positive control samples, respectively. Blends were heated in a thin layer at 170 and 200 °C. Considering the increase in total polar compounds (TPCs) and oxidized triacylglycerol monomer (oxTAG) content, natural additives demonstrated protective properties and were more effective than the TBHQ additive, especially at 200 °C. The lowest increases in TPC and oxTAG were found in AO5% at 170 °C (10.17% and 1.40 mg/g oil, respectively) and in AO25% at 200 °C (5.71% and 47.53 mg/g oil, respectively). The presence of triacylglycerol (TAG) dimers was found only in samples heated at 200 °C, and the lowest was in the sample with 25% coriander oil. It can be concluded that the addition of cold-pressed oils limited the TAG oxidation process. The addition of 25% coriander oil was effective in inhibiting the TAG polymerization process, and it may be a powerful alternative to synthetic antioxidants in improving stabilization of frying oils. Full article

This study analyzes the valorization of oil palm biomass residues within the framework of industrial symbiosis (IS), emphasizing their role in circular economy strategies and sustainable industrial development. Through a systematic literature review and snowball sampling, 156 articles indexed in Scopus and Web of Science were examined, classifying evidence by country, type of residue, derived products, economic sector (ISIC Rev. 4), and technological approach. The results show a strong geographical concentration of IS experiences in Asia, particularly Malaysia, Indonesia, and Thailand, where residues such as empty fruit bunches (EFB), palm kernel shells (PKS), oil palm mesocarp fibers, palm oil mill effluent (POME), and oil palm trunks (OPT) are integrated into processes for bioenergy, biochemicals, composite materials, construction products, biochar, and bioplastics. In contrast, applications in Latin America and Africa remain incipient, with high potential but limited industrial implementation due to infrastructural and regulatory gaps. Technological trends point toward thermo-chemical and biological conversion routes (pyrolysis, gasification, hydrothermal carbonization, anaerobic digestion), development of advanced materials and catalysts, and the emergence of integrated biorefinery models supported by computational optimization tools. The analysis highlights that palm biomass residues, far from being an environmental liability, constitute strategic resources for low-carbon value chains. However, scaling IS initiatives requires clear public policies, economic incentives, and stronger coordination between industry, government, and academia. The study provides a structured overview of current knowledge, identifies research gaps, and outlines future directions for leveraging oil palm residues as a key input for sustainable IS. Full article

The functional properties of high-pressure processing (HPP)-assisted protein hydrolysate from tamarind kernel powder (TKP-HD) and the physicochemical characteristics of its foam-mat powder were studied. TKP-HD consisted of more non-polar than polar amino acids, with higher solubility at pH 5 and 7 than soy protein isolate (SPI) but lower than egg white (EW). The water-binding capacity of TKP-HD increased at pH 5 while TKP-HD had a higher foaming capacity than SPI at pH 5, and the highest oil-binding capacity. The physicochemical properties of TKP-HD after foam-mat drying were investigated using 1 and 1.5% (w/w) hydroxypropyl methylcellulose (HPMC), with drying at 60, 70, and 80 °C. Samples with 1.5% HPMC had lower water activity than those with 1% HPMC at all drying temperatures. The sample with 1% HPMC had higher antioxidant capacity at 60 °C than at 70 °C, but this decreased at 1.5% HPMC. Samples with 1.5% HPMC and dried at 60 °C recorded the highest solubility and viscosity, with increased porosity of the powder structure. The most suitable foam-mat drying conditions for TKP-HD were the addition of 1.5% HPMC and drying at 60 °C. Full article

In Colombia, two main palm varieties, Elaeis guineensis and Elaeis oleifera, are cultivated for the production of crude palm oil (CPO). During the CPO extraction process, several residues are generated, including empty fruit bunches (EFB), nut fiber, palm kernel cake, and Palm Oil Mill Effluent (POME), among others. These residues are commonly used for biochar and compost production to improve soil quality, for biogas generation, and for energy production through biomass combustion. Because the rachis is rich in lignocellulosic material and exhibits physicochemical properties suitable for thermochemical processes, it is proposed as a feedstock for hydrogen synthesis through gasification. In this study, a techno-economic analysis and an FP²O resilience assessment were conducted for a hydrogen production process based on the utilization of palm rachis generated in María la Baja, northern Colombia. The economic evaluation results indicate that the capital investment required for plant installation is USD 10,111,255.23. The economic indicators show favorable performance with a Return on Investment (ROI) of 58.83%, a Net Present Value (NPV) of USD 25.01 million, a B/C ratio of 3.29, and a Discounted Payback Period (DPBP) of 4.54 years. Regarding techno-economic resilience, critical values for processing capacity, selling price, and feedstock cost were identified through parameter variation. The findings suggest that the process has opportunities for improvement, since small changes in these variables could significantly reduce its resilience. Finally, an On-Stream efficiency of 39.65% at the break-even point was obtained, indicating that the process can operate at less than 50% of its maximum capacity while still generating significant profits. Full article

The increasing demand for plant-based alternatives, driven by veganism, lactose intolerance, and greater health consciousness, has intensified research into dairy-free frozen desserts. This study investigates the development of a plant-based ice cream alternative utilizing oleosomes extracted from sunflower seed kernels as natural emulsifiers, eliminating the need for synthetic additives. Oleosomes were obtained through aqueous extraction from raw kernels, incorporated into emulsions in three levels (0, 12, and 24%), and combined with sunflower seed oil, tahini, date paste, and water to create the ice cream (IC) formulations. The physicochemical properties of three formulations of a sugar-free frozen dessert were studied. Physicochemical analyses assessed nutritional value, color (CIELab), melting time, stability, overrun, viscosity, and texture profile (TPA). Sensory evaluation was conducted using a hedonic test to assess the impact of tahini type (sunflower seed tahini or pumpkin seed kernel tahini) on the product acceptance. Results showed that higher oleosome content improved emulsion stability and melting resistance, while also producing a softer (30.74 ± 0.28 N), less adhesive (1.87 ± 0.20 mJ) texture, suitable for plant-based ice cream. Sensory analysis revealed a clear preference for the pumpkin tahini formulation, which scored 8.21 ± 0.62 for overall appreciation. The findings demonstrate that the addition of oleosome might improve textural attributes of the products, while the consumer preference could also be influenced by the type of tahini involved in the formulation. However, further studies are necessary to corroborate the proposed interaction mechanisms of ingredients. Full article

The present study evaluates the impact of cavitation on the performance of the chemical refining of rapeseed oils and the enzymatic interesterification of fat blends using a powerful UP400S ultrasonicator (400 W, 20 kHz). Ultrasound-assisted alkali neutralization achieved efficiency comparable to that of the conventional 60 min process in only 7 min, with similar refining losses (5.04–6.80 wt.%), although slightly higher lipid peroxidation was observed. Performing the ultrasound cavitation under a protective nitrogen atmosphere minimized the formation of lipid peroxides and their breakdown products (i.e., hexanal, nonanal), partially protected tocopherols, and improved oxidative stability (IP at 120 °C = 3.9–4.4 h). Ultrasound-assisted enzymatic interesterification (EIE) of palm kernel fat and a palm stearin blend catalyzed by immobilized lipases (Lipozyme TL IM, Lipozyme RM IM, Novozyme 435) was carried out for the first time. Cavitation accelerated triacylglycerol rearrangement, reduced reaction time from 6 h (9.0·10⁻³ to 1.6·10⁻² min⁻¹) to only 1 h (5.5·10⁻² to 1.2·10⁻¹ min⁻¹), and significantly affected melting point stabilization and solid fat content profile. In summary, ultrasound cavitation substantially enhanced mass transfer and reaction kinetics, demonstrating strong potential for process intensification in the edible oil industry. Further optimization of reaction conditions is required before large-scale industrial implementation. Full article

Background: The Chinese dwarf cherry (CDC) has been valued for over 2000 years for its medicinal and nutritional properties, particularly its kernels. Despite its recognition as a rich source of oil, the potential health benefits of CDC kernel oil remain unclear. Method: Initially, we evaluated the preventive effectiveness of CDC in a mouse model of constipation induced by loperamide. Results: The findings indicated that CDC kernel oil alleviated constipation by reducing the first black fecal defecation time and increasing the fecal number, wet weight, water content and gastrointestinal transit rate in model mice. Additionally, CDC kernel oil reduced inhibitory neurotransmitters and increased excitability neurotransmitters, two anti-oxidases’ activity and fecal short-chain fatty acid (SCFA) content. Histological analysis revealed an improved mucus cell morphology in the intestinal tract. Furthermore, CDC kernel oil increased the abundance of some beneficial bacteria. It was identified that the gut microbiota was associated with neurotransmitters, mediators of inflammation and SCFAs. Conclusion: The findings offer a scientific foundation for considering CDC kernel oil as a potential functional food for the alleviation of constipation. Full article

Numerous sectors of the food processing and oleochemical industries require oils with specific physicochemical properties. Fruit processing generates substantial waste potentially containing valuable raw materials for oil extraction. The significant volumes of apples and cherries processed in Poland prompted an assessment of their seeds’ suitability as oil sources. Seed dry matter, protein, and oil content were determined. The extracted oils were analyzed for acid value (AV), peroxide value (PV), oxidative stability, fatty acid composition, and sterol and tocopherol content. The predominant higher fatty acids identified in the sour cherry and sweet cherry kernel oils were linoleic acid (C18:2, n-6), with mean concentrations of 45.82% and 29.23%, respectively, and oleic acid (C18:1, n-9), accounting for 41.54% and 46.59%, respectively. Additional fatty acids detected included palmitic acid C16:0 (6.23% and 5.91%), palmitoleic acid C16:1, n-7 (0.29%), stearic acid C18:0 (1.36% and 3.11%), arachidic acid C20:0 (1.13%), α-eleostearic acid C18:3 (5.07% and 9.48%), and α-linolenic acid C18:3, n-3 (4.09%). Given the substantial proportion of the oil fraction containing numerous potentially biologically active compounds, including nutritionally valuable fatty acids, tocopherols, and phytosterols, apple, sour cherry, and sweet cherry seeds demonstrate considerable potential as raw materials for applications in the food, pharmaceutical, and cosmetics industries. Full article

Accurate segmentation of marine oil spills in synthetic aperture radar (SAR) images is crucial for emergency response and environmental remediation. However, current deep learning methods are still limited by two long-standing bottlenecks: first, multiplicative speckle noise and complex background clutter make it difficult to accurately delineate actual oil spills; and second, limited receptive fields often lead to the geometric fragmentation of elongated, irregular oil films. To surmount these challenges, this paper proposes a novel framework termed the Frequency-Spatial Coordinate and Strip-Augmented Network (FCS-Net). First, we leverage the ConvNeXt-Small backbone to extract robust hierarchical features, utilizing its large kernel design to capture broad contextual information. Second, a Frequency-Spatial Coordinate Attention (FS-CA) module is proposed to integrate spatial coordinate encoding with global frequency-domain information. Third, to maintain the morphological integrity of elongated targets, we introduce a Strip-Augmented Pyramid Pooling (SAPP) module which employs anisotropic strip pooling to model long-range dependencies. Extensive experiments on the multi-source SOS dataset demonstrate the effectiveness of FCS-Net. The proposed method achieves state-of-the-art performance, reaching an mIoU of 87.78% in the Gulf of Mexico and 89.62% in the challenging Persian Gulf, outperforming strong baselines and demonstrating superior robustness in complex ocean scenarios. Full article

Reliable estimation of oil palm carbon stock is essential for climate mitigation, concession management, and sustainability certification. While satellite-based approaches offer scalable solutions, redundancy among spectral indices and inter-sensor variability complicate model development. This study evaluates machine learning regressors for predicting oil palm carbon stock at tree (CO_tree, kg C tree⁻¹) and hectare (CO_ha, Mg C ha⁻¹) scales using spectral indices derived from Landsat-8, Landsat-9, and Sentinel-2. Fourteen vegetation indices were screened for multicollinearity, resulting in a lean feature set dominated by NDMI, EVI, MSI, NDWI, and sensor-specific indices such as NBR2 and ARVI. Ten regression algorithms were benchmarked through cross-validation. Ensemble models, particularly Random Forest, Gradient Boosting, and XGBoost, outperformed linear and kernel methods, achieving R² values of 0.86–0.88 and RMSE of 59–64 kg tree⁻¹ or 8–9 Mg ha⁻¹. Feature importance analysis consistently identified NDMI as the strongest predictor of standing carbon. Spatial predictions showed stable carbon patterns across sensors, with CO_tree ranging from 200–500 kg C tree⁻¹ and CO_ha from 20–70 Mg C ha⁻¹, consistent with published values for mature plantations. The study demonstrates that ensemble learning with sensor-specific index sets provides accurate, dual-scale carbon monitoring for oil palm. Limitations include geographic scope, dependence on allometric equations, and omission of belowground carbon. Future work should integrate age dynamics, multi-year composites, and deep learning approaches for operational carbon accounting. Full article

The stability of nanolubricants is critical for ensuring effective performance under extreme pressure (EP) conditions, where severe boundary lubrication governs friction and wear behaviour. This study examines palm kernel oil (PKO)-based nanolubricants enhanced with carbon graphene (CG), hexagonal boron nitride (hBN), and molybdenum disulfide (MoS₂), with and without oleic acid (OA) as a surfactant. OA incorporation improved CG dispersion stability, reducing agglomerate size by 30.4% (17.61 μm to 12.23 μm) and increasing the viscosity index from ~176 to 188, compared to 152 for the commercial hydrogen engine oil baseline. Under EP conditions, PKO + CG + OA achieved a 51.7% reduction in the coefficient of friction (0.58 to 0.28) and 18.2% improvement in weld load resistance, while wear scar diameter decreased by 13.4%. Surface and elemental analyses indicated the formation of a composite tribofilm containing oxide species, graphene platelets, and carboxylate-derived compounds from OA, consistent with iron–oleate-like chemistry that enhances load-carrying capacity and wear protection. These findings demonstrate the potential of OA-assisted PKO nanolubricants as sustainable, high-performance formulations for extreme pressure boundary lubrication, contributing to the advancement of green tribology. Full article

Aspergillus flavus colonizes oil-seed crops, contaminating them with aflatoxins; highly carcinogenic mycotoxins that cause severe health and economic losses. Genetic studies may reveal new targets for effective control strategies. Here, we characterized a putative WOPR transcription factor gene, osaA, in A. flavus. Our results revealed that osaA regulates conidiation and sclerotial formation. Importantly, deletion of osaA reduces aflatoxin B₁ production, while, unexpectedly, transcriptome analysis indicated upregulation of aflatoxin biosynthetic genes, suggesting post-transcriptional or cofactor-mediated regulation. Cyclopiazonic acid production also decreased in the absence of osaA. In addition, the osaA mutant exhibited upregulation of genes in the imizoquin and aspirochlorine clusters. Moreover, osaA is indispensable for normal seed colonization; deletion of osaA significantly reduced fungal burden in corn kernels. Aflatoxin content in seeds also decreased in the absence of osaA. Furthermore, deletion of osaA caused a reduction in cell-wall chitin content, as well as alterations in oxidative stress sensitivity, which could in part contribute to the observed reduction in pathogenicity. Additionally, promoter analysis of osaA-dependent genes indicated potential interactions with stress-responsive regulators, indicated by an enrichment in Sko1 and Cst6 binding motifs. Understanding the osaA regulatory scope provides insight into fungal biology and identifies potential targets for controlling aflatoxin contamination and pathogenicity. Full article

Squalene and lanosterol are bioactive compounds with diverse physiological effects, found in relatively high concentrations in tea seed oil. Their levels are significantly influenced by cultivar and fruit maturity. As leaf-color specific tea cultivars gain popularity, parts of them tend to have a higher flower and fruit ratio than green-leaf tea cultivars. However, their fruit characteristics remain underexplored. This study investigated 15 tea cultivars with different leaf colors, analyzing phenotypic changes in seeds during maturation, and examining the variation patterns of squalene and lanosterol. The crude water content, dry kernel content, and oil content were closely related to the maturity and effectively reflected seed development. Lanosterol content showed an overall downward trend with increased maturity. Squalene content fluctuated sharply before the seeds fully matured, but gradually decreased once they were fully matured. At full maturity, leaf-color specific tea cultivars generally exhibited higher concentrations of squalene and lanosterol than those with green leaf. Full article

Accurate identification of lithology is considered very important in oil and gas exploration because it has a direct impact on the evaluation and development planning of any reservoir. In complex reservoirs where extreme class imbalance occurs, as critical minority lithologies cover less than 5%, the identification accuracy is severely constrained. Recent deep learning methods include convolutional neural networks, recurrent architectures, and transformer-based models that have achieved substantial improvements over traditional machine learning approaches in identifying lithology. These methods demonstrate great performance in catching spatial patterns and sequential dependencies from well log data, and they show great recognition accuracy, up to 85–88%, in the case of a moderate imbalance scenario. However, when these methods are extended to complex reservoirs under extreme class imbalance, the following three major limitations have been identified: (1) single-scale architectures, such as CNNs or standard Transformers, cannot capture thin-layer details less than 0.5 m and regional geological trends larger than 2 m simultaneously; (2) generic imbalance handling techniques, including focal loss alone or basic SMOTE, prove to be insufficient for extreme ratios larger than 50:1; and (3) conventional Transformers lack depth-dependent attention mechanisms incorporating stratigraphic continuity principles. This paper is dedicated to proposing a geological-constrained multi-scale Transformer framework tailored for 1D well-log sequences under extreme imbalance larger than 50:1. The systematic approach addresses the extreme imbalance by deep-feature fusion and advanced class-rebalancing strategies. Accordingly, this framework integrates multi-scale convolutional feature extraction using 1 × 3, 1 × 5, 1 × 7 kernels, hierarchical attention mechanisms with depth-aware position encoding based on Walther’s Law to model long-range dependencies, and adaptive three-stage class-rebalancing through SMOTE–Tomek hybrid resampling, focal loss, and CReST self-training. The experimental validation based on 32,847 logging samples demonstrates significant improvements: overall accuracy reaches 90.3% with minority class F1 scores improving by 20–25% percentage points (argillaceous siltstone 73.5%, calcareous sandstone 68.2%, coal seams 65.8%), and G-mean of 0.804 confirming the balanced recognition. Of note, the framework maintains stable performance even when there is extreme class imbalance at a ratio of up to 100:1 with minority class F1 scores above 64%, representing a two-fold improvement over the state-of-the-art methods, where former Transformer-based approaches degrade below. This paper provides the fundamental technical development for the intelligent transformation of oil and gas exploration, with extensive application prospects. Full article

Walnut (Juglans regia L.) is an important economic and oil-bearing tree species, and the nutritional quality of its kernels is influenced by multiple environmental factors. Elevation is an ecological gradient that integratively reflects variations in environmental conditions such as temperature and light availability and shows a certain degree of correlation with kernel nutritional quality. The aim of this study was to clarify the regulatory effect of elevation on the nutritional quality of walnut kernels in Chongqing and to optimize the layout of high-quality walnut production areas. This study used 181 walnut germplasm resources collected from 16 natural populations (production areas) in Chongqing. Six elevation ranges were defined (I: 200–600 m, II: 600–900 m, III: 900–1200 m, IV: 1200–1400 m, V: 1400–1600 m, VI: 1600–1800 m), and twelve nutritional traits of walnut kernels were systematically analyzed, including total fat, protein, soluble sugar, tannin, saturated fatty acids (stearic acid, palmitic acid, arachidic acid), and unsaturated fatty acids (oleic acid, palmitoleic acid, cis-11-eicosenoic acid, linoleic acid, α-linolenic acid). The results showed that the fat content of walnut kernels was generally higher than 60%, with the highest value in zone VI (62.93%). The protein content was the highest in zone III (17.71%) and the lowest in zone VI (16.06%). Soluble sugar and tannin contents were relatively low, both peaking in zone II (3.10% and 10.85%, respectively). The overall content of saturated fatty acids was low, being slightly higher in zone II, with little variation among components across elevations. Among monounsaturated fatty acids, oleic acid was dominant, showing a decreasing–increasing trend with rising elevation, with the lowest value in zone II (20.98%) and the highest in zone VI (26.93%), while palmitoleic acid and cis-11-eicosenoic acid were maintained at low levels. Polyunsaturated fatty acids were dominated by linoleic acid, ranging from 51.22% to 61.04%, with the highest content in zone II and the lowest in zone VI. Comprehensive evaluation and cluster analysis grouped the six elevation zones into three categories, with zone II showing the best nutritional quality, particularly in terms of soluble sugar, stearic acid, and linoleic acid, while zone I had the lowest score. These findings provide a theoretical basis for the selection of high-quality walnut production areas and the precision cultivation of nutrient-rich walnut fruits, as well as important data support for the scientific planning and high-quality development of the walnut industry in Chongqing. Full article