Search Results (2,964)

Efficient monitoring of pork freshness is essential to minimize spoilage-related losses in the meat industry. To address the limitations of existing detection technologies, namely high cost, poor timeliness and high environmental sensitivity, this study developed a novel electronic nose system integrating a hybrid sensor array with dynamic gas path control. By combining metal oxide semiconductor (MOS) and electrochemical sensors (e.g., MQ137, MQ136), the system exhibits high sensitivity to the key volatile organic compounds (VOCs) released during pork spoilage, achieving a detection accuracy of over 90% in identifying spoilage stages. Combined with a dual-mode gas circuit design (solenoid valve switching time: 0.85 s), the reliability of the system was further demonstrated. This technology offers an economical and efficient real-time monitoring solution for slaughterhouses and cold chain logistics, providing a new low-cost scientific approach for pork freshness assessment. Full article

Microbial biocontrol agents often exhibit limited shelf life, which restricts their commercialization, storage, and large-scale agricultural application. In this study, freeze-drying (FD) microencapsulation was evaluated as a strategy to improve the stability of a wettable powder (WP) formulation based on Bacillus subtilis fermented broth using maltodextrin (MD) as a carrier. The physicochemical, structural, morphological, and antifungal properties of the resulting formulation were characterized. Physical characterization revealed complete solubility (100% at 0.1 g mL⁻¹), rapid wettability (2 s), and low hygroscopicity (3.86%), indicating favorable properties for handling and application. Scanning electron microscopy revealed irregular glass-like particles of different sizes, while Fourier transform infrared spectroscopy indicated the distribution of components within the maltodextrin matrix. The antifungal activity of the WP and the effects of its volatile organic compounds (VOCs) were evaluated against the phytopathogenic fungi Fusarium oxysporum, Fusarium solani, Fusarium graminearum, Rhizoctonia solani, and Sclerotinia sclerotiorum. The formulation inhibited fungal growth within the tested concentration range (0.1–0.2 g mL⁻¹), although no clear inhibition zone was observed for S. sclerotiorum. Furthermore, the WP maintained 65% viability after 24 months of storage at 4 °C. These results demonstrate the potential of FD microencapsulation to enhance the storage stability of Bacillus subtilis formulations while preserving their antifungal activity. Full article

Background/Objectives: Exercise is increasingly recognized as a modulator of host–microbiome interactions, yet its role in irritable bowel syndrome (IBS) remains poorly characterized. Methods: In this prospective, single-arm, before-and-after interventional study, we used an integrated multi-omics approach based on metataxonomics and metabolomics to assess the effects of a structured 12-week moderate aerobic exercise program in 80 patients with mild-to-moderate IBS, stratified by Global Physical Capacity Score (GPCS). Biochemical and inflammatory markers have been gathered. Results: Exercise did not alter overall microbial diversity but selectively enriched short-chain fatty acid (SCFA)-producing taxa and remodeled the volatile organic compound (VOC) profile toward a more efficient metabolic state. Notably, conventional biochemical and inflammatory markers failed to distinguish response subgroups, whereas GPCS stratification revealed distinct microbial and metabolomic trajectories. Individuals with higher baseline physical capacity had higher acetate levels and lower levels of VOCs associated with dysbiosis and oxidative stress. Conclusions: Our results suggest that baseline physical capacity is a primary determinant of the microbiome’s responsiveness to exercise, challenging the reliance on static biochemical profiling. Despite the lack of a control group and the exploratory nature of some metabolomic signals, this study provides a framework for precision exercise interventions in IBS. Our work identifies GPCS as a clinically relevant stratification tool. The full trial protocol is registered on ClinicalTrials.gov under the identifier NCT05453084. Full article

Black tea quality is governed by aroma chemistry: terpene alcohols (linalool, geraniol, nerolidol), methyl salicylate, and short-chain aldehydes whose abundance and release kinetics from the polyphenol-rich leaf matrix shape perceived grade. Grade information lies not only in the average headspace concentration but in the temporal shape of volatile organic compound (VOC) release under controlled heating. Conventional electronic noses obscure this signal: they rely on multi-sensor arrays, compress each response into summary statistics, and report accuracy only at the level of individual measurements. Whether a single low-cost metal–oxide–semiconductor (MOS) gas sensor can recover grade-defining aroma chemistry, and whether waveform-level modeling can exploit it, was therefore investigated. A portable electronic nose built around a Bosch BME688 sensor recorded 90 time series, each comprising four directly measured channels (temperature, humidity, pressure, gas sensor resistance) and a derived indoor-air-quality (IAQ) proxy computed from them by the on-chip BSEC library, from 16 commercial Turkish black teas across three quality grades. Two representations were compared on the same data: a feature-based pipeline reducing 25 statistical descriptors to seven principal components for six classifiers (best F1-macro = 0.624, MLP), and a raw-waveform Multi-Scale 1D-CNN with Squeeze–Excitation and temporal self-attention (MS-CNN-Attention). Under product-grouped cross-validation, the deep model reached F1-macro = 0.811 (+30%) and graded 14 of 16 products correctly by majority vote, against 11 of 16 for the MLP, with the largest gain in the medium grade (F1: 0.52 → 0.79), where summary-statistic compression destroys the release-kinetic signal. The contributions are threefold: one programmable MOS sensor operated as a thermal-desorption profiler rather than a sensor array; a direct comparison of feature-based classical learning against raw-waveform deep learning on the same small, non-normally distributed dataset; and a product-level decision-consistency metric suited to batch screening. Pairing a low-cost MOS sensor with waveform-level modeling offers a rapid, non-destructive route to aroma-chemistry-based tea quality screening. Full article

A2 milk has recently gained popularity, mainly due to its different beneficial effects on the human digestive system compared to popular A1 milk. Because of these structural differences, A2 milk exhibits characteristics that need to be investigated to design processes appropriately. The effects of β-casein genotype and heat treatment method (LTLT, HTST, and HTLT: a high-temperature preparatory treatment applied in fermented dairy production) on the fatty acid profile, volatile organic compounds (VOCs), composition, emulsion stability, acidification kinetics, and color parameters were investigated. Fatty acid composition was determined exclusively by milk type. A1 milk exhibited higher saturated fatty acids, higher total PUFA content, higher Σn-3 fatty acids, and a more favorable n-6/n-3 ratio, while A2 milk showed higher monounsaturated fatty acids and higher CLA (Conjugated Linoleic Acid) in a trait-dependent manner. VOC profiling identified 29 compounds. Significant genotype × treatment interactions were observed: A1 milk was characterized by high diacetyl in fresh samples and exclusive methanethiol formation upon pasteurization, while A2 milk showed enhanced Maillard-derived volatile formation and high ester accumulation after LTLT treatment. Emulsion stability was highest after LTLT treatment regardless of milk type. A1 milk reached the coagulation threshold of pH 4.6 within 45 min, whereas A2 exhibited delayed acidification. HTLT induced the greatest color changes in both types of milk. Full article

The use of insect-based protein sources in aquaculture is gaining increasing attention with Hermetia illucens (black soldier fly, BSF) larvae meal representing a promising substitute to fishmeal (FM). This study evaluated the effect of partial dietary inclusion of BSF meal (BSF0, BSF2.5, BSF5, BSF10%) on the volatilome of rainbow trout (Oncorhynchus mykiss) fillets, before and after cooking, using gas chromatography–mass spectrometry (GC–MS) and a metal oxide sensor-(MOX)-based device. Fish were fed diets with increasing BSF inclusion, and both raw and cooked fillets were analyzed to assess changes in volatile organic compounds (VOCs). GC–MS enabled the identification and semi-quantitative analysis of VOC classes, while MOX sensor responses were processed using Linear Discriminant Analysis (LDA) to assess discrimination among dietary treatments. Results showed that BSF inclusion influenced the volatile profile, with clearer separation at higher inclusion levels (BSF5–BSF10%), especially in cooked fillets. Thermal processing enhanced these differences. GC–MS analysis revealed a reduction in aldehydes and ketones and an increase in carboxylic acids with higher BSF inclusion. Key compounds such as hexanal and heptanal decreased, indicating changes in lipid-derived volatile pathways. Overall, the integration of GC–MS and MOX sensors proved effective in detecting diet-induced changes, supporting their application as effective and reliable tools for quality assessment in aquaculture products, with potential implications for sensory quality that should be further confirmed through dedicated sensory studies. Full article

Membrane separation is an efficient approach for volatile organic compound (VOC) recovery from industrial off-gases due to its low energy consumption, compact design, and operational simplicity. Membrane-based VOC recovery critically depends on the membrane material, which must exhibit high VOC permeability and selectivity under mixed-gas conditions. In this study, novel highly selective membranes for VOC removal based on polydecylmethylsiloxane (PAMS-10) were synthesized using both polydimethylsiloxane and various α,ω-dienes as cross-linkers: 1,7-octadiene (OD), 1,9-decadiene (DD), and 1,11-dodecadiene (DdD). The influence of cross-linker concentration and length on mechanical, structural, sorption, and transport properties was examined extensively. The combination of three independent experimental methods (time-lag, vapor permeation, and in situ spectroscopic ellipsometry) revealed that increasing α,ω-diene concentration and decreasing its length led to a reduction in the diffusivity and permeability of permanent gases, gaseous hydrocarbons, and VOC vapors. For VOC/N₂ separation, the slightly cross-linked OD-1 membrane and the DdD-5 membrane, cross-linked with long 1,11-dodecadiene, demonstrated outstanding mixed-gas selectivities of 950/921/314/840 and 940/1084/233/1106 for toluene/n-octane/i-octane/n-butyl acetate, respectively. Notably, the DD-5 membrane, cross-linked with 1,9-decadiene, matching the length of the PAMS-10 side chain substituent, exhibited the best mechanical properties and mixed-gas selectivity comparable to the ideal selectivity, a unique behavior attributed to optimal supramolecular organization. Full article

This study presents the development and field testing of a Pressurized Driving-Down Air Multilevel Sampler (PDA-MLS), an integrated groundwater sampling device designed for depth-discrete sampling in boreholes affected by floating non-aqueous phase liquids (NAPLs). Conventional sampling methods—such as low-flow pumps, bailers, and packer-isolated systems—often fail under these conditions due to limited accessibility, cross-contamination, or disturbance of the water column. The proposed system addresses these limitations through a controlled pressurized-gas actuation mechanism that transfers groundwater from multiple PTFE-membrane chambers installed at discrete depths. This configuration enables low-disturbance sampling below floating contaminant layers. The use of chemically inert materials (stainless steel and PTFE) minimizes sampling artifacts and ensures compatibility with volatile organic compound (VOC) analyses. A simplified hydraulic conceptual framework describing inflow, outflow, and pressure-driven displacement was developed to support purge-duration estimation and operational parameter definition. The device was tested in a 90 m deep fractured limestone aquifer contaminated by tetrachloroethylene (PCE), where floating hydrocarbons limited the applicability of conventional sampling techniques. Field testing showed stable discharge conditions (~145–160 mL/min), repeatable sampling cycles, and successful collection of depth-discrete groundwater samples under the investigated site conditions. No evidence of sampler-related hydrocarbon entrainment was observed in the collected samples within the analytical detection limits of the adopted laboratory methods. To the authors’ knowledge, the PDA-MLS represents one of the few groundwater sampling systems specifically designed to combine low-disturbance multilevel sampling with operation in wells affected by floating NAPL. These features make it a promising tool for environmental monitoring, high-resolution characterization of fractured aquifers, and long-term assessment of contaminated sites. Full article

Triethylamine (TEA), a widely used volatile organic compound (VOC), poses severe threats to environmental safety and human health upon accidental leakage, making the development of high-performance TEA detection techniques urgently needed. Herein, we report a Sn-based metal–organic framework (Sn-MOF) constructed from 4,5-dichloroimidazole ligands synthesized via a solvothermal approach. The resulting MOF-derived SnO₂ materials were obtained by calcination at 400–600 °C, yielding SnO₂ with tunable specific surface area and surface defect-site density. Structural and surface characterizations revealed that the materials consist of primary nanoparticles in the range of 10–50 nm, forming aggregated particles of 1–2 µm. The gas sensing performance toward TEA was systematically evaluated. The SnO₂-400 °C sensor exhibited the highest response (S = 85.0) to 100 ppm TEA at 190 °C, with a low detection limit of 1 ppm, superior selectivity, good repeatability, and excellent long-term stability. The observed performance variation was attributed to the combined effects of specific surface area, abundant defect-associated surface sites, and suitable mesoporous structure. This work not only provides a high-performance TEA sensor for industrial and food safety monitoring but also offers a rational strategy for designing MOF-derived metal oxide gas sensors with tailored microstructures and surface defect chemistry. Full article

Volatile organic compounds (VOCs) are major contributors to air pollution and pose significant risks to both environmental quality and human health. Biochar-based adsorption technology is an efficient and sustainable approach to VOCs removal. Herein, hybrid biochar was prepared from corn stover and municipal sewage sludge using the water vapor activation method, and its physicochemical characteristics and adsorption mechanisms for typical volatile organic compounds commonly produced during biomass-derived energy generation—such as methylbenzene, isopentane, and ethylene—were systematically investigated. The results show that hybrid biochar significantly outperformed single-source biochar, with its ability to adsorb methylbenzene, isopentane, and ethylene exceeding that of pure sludge biochar by 112.21%, 74.53%, and 66.72%, respectively, and surpassing pure corn stover biochar by 74.25%, 62.98%, and 55.25%, respectively. Competitive adsorption analysis indicated that the interaction strength between VOC molecules and the steam-treated hybrid carbon material was associated with their boiling points; compounds with higher boiling points tended to exhibit stronger affinity. This work provides an integrated waste utilization and pollution control strategy for VOCs removal. Full article

Military burn pits used during post-9/11 U.S. military deployments functioned as uncontrolled combustion systems and were widely utilized to dispose of large volumes of outdoor waste by burning. Burn pits involved heterogeneous waste materials burned under variable temperature and oxygen conditions. These combustion environments generated complex, toxic, multipollutant airborne emission mixtures that included particulate matter (PM_2.5), polycyclic aromatic hydrocarbons (PAHs), and volatile organic compounds (VOCs). This narrative review synthesizes epidemiologic, experimental, and mechanistic evidence linking burn pit emissions to disruption of the lung–brain axis and adverse neurological outcomes. We specifically aim to address a critical gap in understanding how combustion-derived toxicants impact brain health and are associated with unfavorable neuropsychiatric outcomes, including increased risk of post-traumatic stress disorder (PTSD) and depression. Combustion-related exposures promote pulmonary inflammation and system-wide immune signaling that propagate to the central nervous system, contributing to neuroinflammation and dysregulation of the hypothalamic–pituitary–adrenal (HPA) axis. These interconnected mechanisms are associated with toxic encephalopathy and related cognitive and mood disturbances, underscoring the need to integrate fire science with military and environmental health services research to better define the systemic and neurological consequences of acute and chronic fire-derived inhalation exposures. Full article

Non-invasive blood glucose estimation from exhaled breath has been proposed as a painless alternative to repeated capillary measurements; however, performance evaluation remains challenging in small-sample settings. This study investigates the estimation of blood glucose from human breath using volatile organic compound (VOC) signals acquired with an electronic nose. Responses from three metal-oxide sensor channels sensitive to CO, alcohol, and acetone were collected from 58 individuals, with one measurement per subject, and analyzed using strictly patient-level five-fold cross-validation, in which test folds comprised only real subjects. Two experimental factors were examined. First, model performance was evaluated with and without an additional interpretable alcohol–acetone log-ratio capturing relative variation between compounds. Second, model training was performed using either real data only or fold-wise tabular synthetic augmentation generated via a Gaussian copula fitted exclusively on training subjects, while evaluation remained strictly real-only. Under real-only training, classical machine learning models achieved the lowest prediction errors (approximately 6–7 mg/dL), whereas under synthetic augmentation FTTransformer was the best-performing deep learning model. This findings should be understood as a constrained proof-of-concept analysis rather than as evidence of diagnostic capability or clinical readiness. Full article

Insects secrete volatile organic compounds (VOCs) for various reasons, such as intra- or inter-species communication, attracting mates, or repelling predators. The volatiles from indoor insect pests, e.g., phenolic secretions, can impact inhabitants in various ways, causing allergies, skin and eye irritations, etc. The Mupli beetle (Luprops tristis Fabricius, 1801) is one such nuisance pest that aggregates in great numbers in indoor spaces, especially near rubber plantations in tropical African and Asian countries. This study aimed to understand the whole-body volatilome of L. tristis, comprising the first detailed study of volatiles in this insect, particularly under aggregation and laboratory conditions. Whole-body VOCs were collected from sets of 500 and 1000 beetles at different time intervals and analysed by solvent-assisted desorption followed by gas chromatography–mass spectrometry (GC-MS). Compounds released by the Mupli beetle, such as 1-Octadecanesulphonyl chloride, Decane-1,1′-oxybis-, n-Nonadecanol-1 and n-Heptadecanol-1, are reported in the literature to be allergens that cause allergic reactions such as skin and eye irritations in humans. This understanding may indicate the possible reasons for the allergic reactions in people living in these insect-inhabited indoor spaces. We also report and describe the design and development of an economically feasible glass chamber for the dynamic headspace collection of volatiles released by these beetles. Full article

Students and workers spend much of their day in school and office environments, where poor indoor air quality (IAQ) can negatively affect health and comfort. Indoor vegetation is increasingly proposed as a low-cost nature-based solution (NBS) to improve IAQ. This study evaluated the effects of phytoremediation on IAQ and indoor microclimate in schools across different regions and educational levels, as well as in office environments, under real-world conditions. Several C₃ plants (e.g., Chamaedorea, Schefflera, Ficus, Epipremnum, Yucca, and Spathiphyllum) were used, with crassulacean acid metabolism (CAM) plants (Sansevieria) included in selected settings. Temperature, relative humidity, CO₂, PM_2.5, and PM₁₀ were continuously monitored using intercalibrated low-cost sensors in absence and presence of vegetation. A comparable plant configuration was implemented in offices to assess its effects on volatile organic compounds (VOC). Indoor greenery reduced particulate matter, especially PM10 (18–20%), and improved microclimatic conditions by lowering air temperature (1–2 °C) and increasing relative humidity (6–15%). However, CO₂ reductions were limited and context-dependent. In the tested office environments, plant introduction was associated with reduced total VOC concentrations (25–50%). Overall, our results further support that indoor vegetation constitutes a robust, cost-effective nature-based solution (NBS) capable of complementing conventional ventilation systems in both school and office environments. Full article

This study investigates the simultaneous elimination of ethyl acetate (EA), a representative volatile organic compound (VOC), and Escherichia coli aerosols from indoor air using a continuous-flow dielectric barrier discharge (DBD) plasma reactor coupled with a photocatalytic luminous textile system (Cu/TiO₂-coated fibers). The effects of applied voltage, relative humidity, and air-flow rate on pollutant removal and disinfection performance were systematically evaluated. Optimal DBD operation at 18 kV, 1 m³ h⁻¹ airflow, and 70% relative humidity achieved single-process removal efficiencies of 77% for EA and 2 log reduction (CFU mL⁻¹) for E. coli. When photocatalysis was coupled with DBD plasma, a significant combined effect was observed, increasing EA degradation to 87% and bacterial inactivation to 3.8 log (CFU mL⁻¹). The coupling enhanced active-species generation, improved CO₂ selectivity (up to 53%), and reduced residual ozone concentration. Humidity positively affected microbial inactivation due to °OH radical formation but slightly decreased VOC degradation by limiting ozone regeneration. Results demonstrate the efficiency and scalability of the DBD–photocatalysis hybrid system for multi-pollutant indoor air purification, offering rapid, low-temperature treatment suitable for industrial-scale applications. Full article