Search Results (1,723)

The aim of this study was to present a comprehensive analysis of honey varieties from different botanical origins, focusing on their phenolic compounds’ composition, volatile profiles, and antioxidant activity. We simultaneously identified and quantified 37 bioactive compounds, including anthocyanins, flavonols, flavones, flavan-3-ols, proanthocyanidins, and phenolic acids, across various honey samples by HPLC-MS/MS. Total phenolic content (TPC), total flavonoid content (TFC), and antioxidant activity (AOA) were determined using UV-Vis spectrophotometric analysis. The content of phenolic compounds quantified by HPLC-MS/MS ranged from 19.56 to 243.94 mg·kg⁻¹, highlighting a high presence of these antioxidant compounds (mainly phenolic acids), confirmed also by the positive correlation between TPC and DPPH values. Among volatiles compounds, analyzed by HS-SPME-GC-MS, benzene acetaldehyde and furfural resulted specific for two types of honey samples (H-7 and H-9), highlighting the possibility of searching for chemical markers to characterize honeys of different specie/origin. This study enhances our understanding of the bioactive potential of honey from different botanical origins and provides a foundation for future research on its health benefits. Full article

Wind power forecasting remains a major challenge for renewable energy integration, as conventional models often perform poorly when confronted with complex atmospheric dynamics. This study addresses the problem by developing a Spectral-Attentive Spatio-Temporal Graph Convolutional Network (SA-STGCN) designed to capture the intricate temporal and spatial dependencies of wind systems. The approach first applies wavelet transform decomposition to separate volatile wind signals into distinct frequency components, enabling more interpretable representation of rapidly changing conditions. A dynamic temporal attention mechanism is then employed to adaptively identify historical patterns that are most relevant for prediction, moving beyond the fixed temporal windows used in many existing methods. In addition, spectral graph convolution is conducted in the frequency domain to capture farm-wide spatial correlations, thereby modeling long-range atmospheric interactions that conventional localized methods overlook. Although this design increases computational complexity, it proves critical for representing wind variability. Evaluation on real-world datasets demonstrates that SA-STGCN achieves substantial accuracy improvements, with a mean absolute error of 1.52 and a root mean square error of 2.31. These results suggest that embracing more expressive architectures can yield reliable forecasting performance, supporting the stable integration of wind power into modern energy systems. Full article

Propolis is a valuable natural product whose chemical composition and bioactivity are strongly dependent on its geographical and botanical origin. This study presents a comprehensive comparative analysis of the volatile profiles and antibacterial properties of propolis from Romania, Australia, and Uruguay, benchmarked against previously published data from samples from Poland and Turkey. Volatile compounds were profiled using headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry. The resulting data were interrogated using multivariate chemometric analyses (HCA, PCA), and antibacterial activity was assessed via the disk diffusion method against five bacterial strains. Chemometric analysis revealed a clear demarcation into two primary chemotypes: a European type (Poland, Romania, Turkey) dominated by aromatic compounds such as benzoic acid, and a non-European type (Australia, Uruguay) characterized by a high abundance of terpenes. The Australian propolis exhibited a complex terpene profile rich in α-copaene and pinenes, while the Uruguayan sample was distinguished by an exceptionally high concentration of α-pinene. All active extracts showed selective, concentration-dependent inhibition against Gram-positive Staphylococcus aureus and Streptococcus mutans. The terpene-rich Australian propolis displayed the highest antibacterial potency, particularly against S. mutans. Crucially, Pearson correlation analysis revealed a counter-intuitive relationship: the most abundant terpenes in the non-European samples (e.g., α-pinene, verbenone) were significantly negatively correlated with antibacterial activity (r ≈ −0.99). Conversely, less abundant compounds, including linalool and acetic acid, were identified as strong positive predictors of inhibition (r > 0.90). These findings underscore a complex geography-chemotype-bioactivity relationship, where the overall synergistic effect of a mixed chemical profile, rather than the dominance of a single compound, determines antibacterial potency. The initially proposed markers provide a basis for origin-based standardization and highlight Australian propolis as a promising source of natural antibacterial agents. Full article

Spontaneous combustion of charcoal is still not fully understood, generating uncertainties among producers, regulatory agencies, and the scientific community. This study evaluated the influence of final pyrolysis temperature (350, 450, 550, and 650 °C) on the properties of Eucalyptus spp. charcoal and its relation to ignition behavior. Gravimetric yield, proximate composition, calorific value, and ignition temperature were determined. Charcoal yield decreased by 31% between 350 °C and 650 °C. Fixed carbon content increased from ~65% to ~93%, accompanied by a reduction in volatile matter (~35% to ~6%) and a corresponding rise in calorific value. Step-heating experiments, conducted in a furnace with infrared camera monitoring, showed that ignition temperature increased from ~273 °C in charcoal produced at 350 °C to ~424 °C in charcoal produced at 650 °C. Strong correlations indicated that higher fixed carbon and lower volatile matter contents are directly associated with higher ignition temperatures. These results demonstrate that increasing the final pyrolysis temperature improves both the thermal stability and the energy quality of charcoal, although at the expense of gravimetric yield. Since the methodology was based on forced heating rather than spontaneous combustion under near-ambient conditions, complementary tests are required to evaluate spontaneous combustion propensity. Overall, the findings provide practical insights to balance yield, quality, and safety while reinforcing the importance of standardized assessment protocols to ensure safer storage and transport of charcoal. Full article

The taste, aroma, and sensory characteristics of cherries are key factors influencing consumer acceptance. In this study, the sensory evaluation, biochemical characteristics, and their relationships with consumer satisfaction of several representative cherry cultivars were analyzed during cold storage to establish systematic quality evaluation parameters. Targeted metabolomics analysis revealed significant differences in physiological quality and metabolic profiles among the tested cultivars. Specifically, ‘Benitemari’ demonstrated more contents of soluble solids and titratable acid, while ‘Tieton’ and ‘Skeena’ showed higher concentrations of volatile organic compounds and polyphenolics. Furthermore, hexanal and (E)-2-hexenal were identified as the dominant VOCs, while cyanidin-3-O-rutinoside was confirmed as a major phenolic component across the cultivars. Finally, the comprehensive score of the principal component model was significantly positively correlated with the scores of firmness, chewiness, sweetness, sourness, and taste and bitterness in the sensory evaluation. The results were expected to provide valuable guidance for standardizing the sweet cherry supply chain and cultivating high-quality sweet cherry cultivars. Full article

In this study, inter-brand variations in volatile flavor compound profiles of four lager beers were systematically investigated by integrating sensory evaluation with GC-MS, GC×GC-TOF-MS, and GC-O-MS. A total of 594 volatile compounds were identified, of which 71 with odor activity values (OAV) ≥ 1 were found to contribute directly to aroma expression. Additionally, 59 compounds with taste activity values (TAV) ≥ 1 were identified and may also contribute to taste perception. Furthermore, 53 aroma-active compounds were confirmed through GC-O-MS, providing additional evidence for their sensory contribution. Partial least squares discriminant analysis (PLS-DA), correlation analysis, and flavor addition experiments revealed brand-specific differential flavor compounds. Ultimately, twenty key differential flavor compounds, encompassing esters, alcohols, aromatic compounds, acids, lactones, and others, were confirmed to contribute to fruity, floral, burnt, and sweet notes. Phenethyl alcohol, with concentrations varying from 1377.1 mg/L in QD to 3297.5 mg/L in HR, showed a more than 2.4-fold difference across brands and was strongly associated with fruity (r = 0.553) and floral (r = 0.564) aroma. These compounds acted in combination to shape distinct aroma profiles. This study provides a molecular-level basis for understanding lager beer flavor and offers practical guidance for targeted flavor modulation in brewing. Full article

Gasoline is the most common ignitable liquid used to initiate fires, making its detection and identification in fire debris crucial for determining incendiary origins. Fire debris is typically collected after extinguishment and safety clearance, often resulting in gasoline weathering, especially when delayed. Most research on gasoline weathering has been conducted in controlled laboratory settings in temperate climates. However, the effects of tropical conditions on the rate of gasoline weathering and the resulting chemical composition of volatiles remain largely unexplored. Understanding how tropical environmental factors alter gasoline weathering is essential for accurate fire debris interpretation in such regions. This study investigates how tropical climates impact gasoline weathering indoors and outdoors. Weathered samples were prepared by volume reduction method, gradually evaporating gasoline from 10% to 95%. Indoor samples were exposed to room temperature, while outdoor samples were left in open space under natural tropical conditions. Gas Chromatography/Mass Spectrometry (GC-MS) analysis revealed chromatographic shifts in heavier compounds (C₃–C₄ alkylbenzenes) compared to lighter ones like toluene as weathering progressed. Correlation between indoor and outdoor samples was high (>0.970) at 10–50% weathering but declined (<0.600) at 90–95%, indicating differing patterns. All target compounds remained detectable across all samples. Full article

The seafood industry is increasingly adopting intelligent packaging to preserve product quality and improve freshness transparency. This study developed and evaluated a pH-sensitive freshness indicator (FI) for skate sashimi (Zearaja chilensis). This product is consumed at varying stages of fermentation. The FI incorporated bromothymol blue (BTB) and bromocresol purple (BCP) in a polymer matrix. It targeted volatile basic nitrogen (VBN) compounds, with trimethylamine (TMA) as the primary marker. As freshness declined, VBN compounds accumulated in the package headspace and caused a gradual FI color change from yellow to blue through pH variation. ΔE increased from 7.72 on day 2 to 23.52 on day 3. This marked the onset of visible color change and the FI reached full blue by day 7. Headspace solid-phase microextraction (HS-SPME) and gas chromatography–flame ionization detection (GC-FID) quantified monomethylamine (MMA), dimethylamine (DMA) and TMA throughout storage. ΔE correlated strongly with total bacterial count (TBC, r = 0.978), pH (r = 0.901) and TMA (r = 0.888). These results indicate that microbial growth, alkalinity increase and amine production were closely associated with color transitions. The FI reliably tracked freshness loss in skate sashimi. It has potential to enhance consumer transparency and strengthen quality control in the seafood supply chain. Full article

The prediction of stock prices is challenging due to their volatility, irregular patterns, and complex time-series structure. Reliably forecasting stock market data plays a crucial role in minimizing financial risk and optimizing investment strategies. However, traditional models often struggle to capture temporal dependencies and extract relevant features from noisy inputs, which limits their predictive performance. To improve this, we developed an enhanced recursive feature elimination (RFE) method that blends the importance of impurity-based features from random forest and gradient boosting models with Kendall tau correlation analysis, and we applied SHapley Additive exPlanations (SHAP) analysis to externally validate the reliability of the selected features. This approach leads to more consistent and reliable feature selection for short-term stock prediction over 1-, 3-, and 7-day intervals. The proposed deep learning (DL) architecture integrates a temporal convolutional network (TCN) for long-term pattern recognition, a gated recurrent unit (GRU) for sequence capture, and multi-head attention (MHA) for focusing on critical information, thereby achieving superior predictive performance. We evaluate the proposed approach using daily stock price data from three leading companies—HDFC Bank, Tata Consultancy Services (TCS), and Tesla—and two major stock indices: Nifty 50 and S&P 500. The performance of our model is compared against five benchmark models: temporal convolutional network (TCN), long short-term memory (LSTM), GRU, Bidirectional GRU, and a hybrid TCN–GRU model. Our method consistently shows lower error rates and higher predictive accuracy across all datasets, as measured by four commonly used performance metrics. Full article

This study investigates the evolution of the chemical components of kombucha aroma during refrigerated storage. Two preparation methods (MT1 and MT2) were used to produce kombucha from a 1:1 mixture of black and green tea. The bottled beverages were stored at 4 °C for three months, and changes in headspace (HS) volatiles were monitored at different time points using solid-phase microextraction (SPME) and GC-MS. A total of 68 volatile substances were identified, with alcohols, acids, and esters dominating the aroma profile. The study revealed significant changes in flavor composition during cold storage, particularly in the first two weeks, with an increase in the number of esters, acids, ketones and terpenoids, as well as the total amount of esters and alkanols. While some changes contribute to the desirable “cider-like” characteristics, others, like certain volatile acids, aliphatic aldehydes and ketones, are associated with off-flavors. These findings suggest that refrigeration alone is not sufficient to completely inhibit microbial activity in freshly prepared kombucha, highlighting the need for further research to correlate chemical changes with sensory properties to establish optimal organoleptic standards and shelf life. Full article

The results from previous environmental studies on the physicochemical properties of bottom sediments from the Odra River estuary (SW Baltic Sea) and their contamination by pharmaceutically active compounds (PhACs) were compiled and analyzed by the use of various statistical methods (Principal Component Analysis, ANOVA/Kruskal–Wallis, Spearman correlation analysis, Partial Least Squares Discriminant Analysis, and Cluster Analysis). These studies included data on 130 PhACs determined in sediment samples collected from 70 sites across the Odra River estuary as well as the site distance to wastewater treatment plant discharge, PhACs’ physicochemical properties (Kd, Kow, pKa, solubility, metabolism), and sales data. Additionally, total organic carbon, total nitrogen, total phosphorus, acid volatile sulfides, clay mineral content, and trace elements such as As, Ba, Cd, Co, Cr, Cu, Fe, Hg, Mn, Mo, Ni, Pb, Sn, and Zn were analyzed. Clay mineral content and TP were identified as the key physicochemical factors influencing the spatial distribution of PhACs in bottom sediments, exerting a greater impact than the distance of sampling sites from WWTP discharge points. The distribution of PhACs in the estuary was also influenced by the Kd and solubility of the compounds. More soluble pharmaceuticals with low adsorption affinity to sediments were detected more frequently and transported to distant locations, whereas less soluble compounds with high adsorption affinity settled down in bottom sediments near contamination sources. Neither the proportion of a drug excreted unchanged, nor its prescription frequency and sales volume, influenced the spatial distribution of PhACs. In general, Kd may be a useful parameter in the planning of environmental monitoring and tracing migration of PhACs in aquatic environments. Full article

In this study, we provide, to our knowledge, one of the first multidimensional, data-driven evaluations of green education performance in Turkish higher education, combining the THE Education Score, THE Impact Score, and the UI GreenMetric Education & Research Score (GM-ED) with institutional characteristics, and situating the analysis within SDG 4 (Quality Education). While universities worldwide increasingly integrate sustainability into their missions, systematic evidence from middle-income systems remains scarce. To address this gap, we compile a dataset of 50 Turkish universities combining three global indicators—the Times Higher Education (THE) Education Score, THE Impact Score, and the UI GreenMetric Education & Research Score (GM-ED)—with institutional characteristics such as ownership and student enrollment. We employ descriptive statistics; correlation analysis; robust regression models; composite indices under equal, PCA, and entropy-based weighting; and exploratory k-means clustering. Results show that integration of sustainability into curricula and research is the most consistent predictor of SDG-oriented performance, while institutional size and ownership exert limited influence. In addition, we propose composite indices (GECIs). GECIs confirm stable top performers across methods, but mid-ranked universities are volatile, indicating that governance and strategic orientation matter more than structural capacity. The study contributes to international debates by framing green education as both a measurable indicator and a transformative institutional practice. For Türkiye, our findings highlight the need to move beyond symbolic initiatives toward systemic reforms that link accreditation, funding, and governance with green education outcomes. More broadly, we demonstrate how universities in middle-income contexts can institutionalize sustainability and provide a replicable framework for assessing progress toward SDG 4. Full article

Investigating atmospheric volatile organic compounds (VOCs) is critical for understanding their sources, chemical reactivity, and impacts on air quality, climate, and human health, especially in remote regions like the Tibetan Plateau where baseline data remains scarce. In this study, ambient VOCs species were simultaneously measured at four remote background sites on the Tibetan Plateau (Nyingchi, Namtso, Ngari, and Mount Everest) from 2012 to 2014 to investigate their concentration, composition, sources, and chemical reactivity. Weekly integrated samples were collected and analyzed using a Gas Chromatograph-Mass Spectrometer/Flame Ionization Detector (GC-MS/FID) system. The total VOC mixing ratios exhibited site-dependent variability, with the highest levels observed in Nyingchi, followed by Mount Everest, Ngari and Namtso. The VOC composition in those remote sites was dominated by alkanes (25.7–48.5%) and aromatics (11.4–34.7%), followed by halocarbons (19.1–28.1%) and alkenes (11.5–18.5%). A distinct seasonal trend was observed, with higher VOC concentrations in summer and lower levels in spring and autumn. Source analysis based on correlations between specific VOC species suggests that combustion emissions (e.g., biomass burning or residential heating) were a major contributor during winter and spring, while traffic-related emissions influenced summer VOC levels. In addition, long-range transport of pollutants from South Asia also significantly impacted VOC concentrations across the plateau. Furthermore, reactivity assessments indicated that alkenes were the dominant contributors to OH radical loss rates, whereas aromatics were the largest drivers of ozone formation potential (OFP). These findings highlight the complex interplay of local emissions and regional transport in shaping VOC chemistry in this high-altitude background environment, with implications for atmospheric oxidation capacity and secondary pollutant formation. Full article

This study evaluated ten drought indices focusing on their ability to monitor drought events in Marathwada, a semi-arid region of India. High-resolution gridded monthly total precipitation data for 75 years (1950–2024) from the European Centre for Medium-Range Weather Forecasts (ECMWF) were used to evaluate the drought indices. These indices were computed across six timescales: 1, 3, 4, 6, 9, and 12 months. A Generalized Autoregressive Conditional Heteroscedastic (GARCH) model was employed to detect temporal volatility in precipitation, followed by a second-order geospatial autocorrelation eigenfunction eigendecomposition using Global Moran’s Index statistics to geolocate both aggregated and non-aggregated precipitation locations. The performance of drought indices was assessed using non-parametric Spearman’s correlation to identify the strength, direction, and similarity of regional-specific drought events. The temporal lag interdependence between meteorological and agricultural droughts was assessed using a non-parametric Spearman’s cross correlation function (SCCF). The findings revealed that the GARCH model with a skewed Student’s t distribution effectively captured conditional temporal volatility and asymptotic behavior in the precipitation series. The model’s sensitivity enabled the incorporation of temporal fluctuations related to droughts and extreme meteorological events. The Bhalme and Mooley Drought Index (BMDI-6) and Z-Score Index (ZSI-6) were the most applicable indices for drought monitoring. Spearman’s cross-correlation analysis revealed that meteorological droughts influenced agricultural droughts with a time lag of up to 4 months. Full article

In this work, a lemon essential oil–rutin composite nanoemulsion was formed and integrated into a chitosan (CS) matrix to form a coating for pork preservation. The introduction of rutin decreased the particle size of the nanoemulsion and suppressed the volatilization of the encapsulated essential oil. The rheological properties of the coating showed that it was a pseudoplastic fluid with shear-thinning behavior, and the apparent viscosity of the system was lower than 0.7 Pa·s. The incorporation of the nanoemulsion significantly (p < 0.05) increased the antioxidant and bacteriostatic properties of the CS coating, which was positively correlated with the content of the incorporated nanoemulsion. Pork preservation experiments revealed that the changes in color, the increase in pH, drip loss, thiobarbituric acid-reactive substances, total volatile basic nitrogen and total viable count were significantly (p < 0.05) delayed by the coating treatment. These results suggest that the formed lemon essential oil/rutin/CS coating has promising applications in pork preservation. Full article