Search Results (200)

Background/Objectives: The YSK olfactory function (YOF) test is a culturally adapted psychophysical tool that assesses threshold, discrimination, and identification. This study evaluated whether functional near-infrared spectroscopy (fNIRS) synchronized with routine YOF testing, combined with machine learning, can predict YOF subdomain performance in healthy adults, providing an objective neural correlate to complement behavioral testing. Methods: In this prospective diagnostic-accuracy (feasibility/validation) study in healthy adults with algorithm development, 100 healthy adults completed the YOF test while undergoing prefrontal/orbitofrontal fNIRS during odor blocks. Feature sets from ΔHbO/ΔHbR included time-domain descriptors, complexity (Lempel–Ziv), and information-theoretic measures (mutual information); the identification task used a hybrid attention–CNN. Separate models were developed for threshold (binary classification), discrimination (binary classification), and identification (binary classification). Performance was summarized with accuracy, area under the curve (AUC), F1-score, and (where applicable) sensitivity/specificity, using participant-level cross-validation. Results: The threshold classifier achieved accuracy 0.86, AUC 0.86, and F1 0.86, indicating strong discrimination of correct vs. incorrect threshold responses. The discrimination model yielded accuracy 0.75, AUC 0.76, and F1 0.75. The identification model (attention–convolutional neural network [CNN]) achieved accuracy 0.88, sensitivity 0.86, specificity 0.91, and F1 0.88. Feature-attribution (e.g., SHapley Additive exPlanations [SHAP]) provided interpretable links between fNIRS features and task performance for threshold and discrimination. Conclusions: Olfactory-evoked fNIRS signals can accurately predict YOF subdomain performance in healthy adults, supporting the feasibility of non-invasive, portable, near–real-time olfactory monitoring. These findings are preliminary and not generalizable to clinical populations; external validation in diverse cohorts is warranted. The approach clarifies the scientific essence of the method by (i) aligning psychophysical outcomes with objective hemodynamic signatures and (ii) introducing a feature-rich modeling pipeline (ΔHbO/ΔHbR + Lempel–Ziv complexity/mutual information; attention–CNN) that advances prior work. Full article

Chemosensory systems are fundamental for insects to regulate behaviors such as prey detection, oviposition, and pollination. Despite their importance, the molecular mechanisms underlying chemosensation remain poorly understood in many insect groups. Hoverflies (Syrphidae), whose larvae are efficient aphid predators and adults act as pollinators, represent a functionally important but understudied lineage. Building on the genome of Eupeodes corollae that we recently published, we selected this dominant and widespread species as a representative model and performed a genome-wide identification and analysis of odorant-binding proteins (OBPs) to provide a molecular foundation for understanding chemosensory recognition mechanisms. Accordingly, a total of 47 OBPs were identified and classified into Classic, Minus-C, and Plus-C subfamilies, with conserved motifs and structural features observed within each group. Next, phylogenetic analysis revealed that several EcorOBPs are homologous to functionally characterized OBPs in other Diptera, suggesting conserved evolutionary roles. Moreover, chromosomal mapping showed that Minus-C EcorOBPs cluster on chromosome 2, and Ka/Ks analysis indicated strong purifying selection, reflecting evolutionary stability. In addition, synteny analysis demonstrated that E. corollae shares more collinear OBP gene pairs with predatory hoverflies (Episyrphus balteatus and Scaeva pyrastri) than with the saprophagous species Eristalis tenax, consistent with ecological divergence. Finally, transcriptomic profiling revealed tissue-specific expression patterns, including antennal-biased EcorOBP1 linked to olfaction and reproductive tissue-biased EcorOBP11 linked to reproduction, highlighting candidate genes for functional studies. Together, these findings provide a comprehensive characterization of OBPs in E. corollae and offer molecular insights into chemosensory mechanisms that support both pest control and pollination services. Full article

In this study, we systematically characterize the volatile and non-volatile flavor profiles of coffee beans. Sensory evaluation demonstrated unique aromatic profiles for each coffee, with Colombia excelling in chocolate and nutty notes, while Bench Maji exhibited pronounced fruity characteristics. Yirgacheffe had a prominent roasted aroma, and Baoshan stood out for its stronger woody and caramel notes. The analysis employed solvent-assisted flavor evaporation (SAFE), gas chromatography–mass spectrometry/olfactometry (GC-MS/O), and high-performance liquid chromatography (HPLC). A total of 85 aroma compounds were identified, with furans, ketones, and pyrazines being the predominant contributors to roasted, nutty, and caramel aromas. Key aroma-active compounds, including furfural, guaiacol, and furaneol, exhibited the highest flavor dilution (FD) factors (up to 2187) and odor activity values, highlighting their pivotal roles in coffee aroma, with 4-vinyl-2-methoxyphenol (OAV = 761 in GL) and furaneol (OAV = 250 in BS) being particularly influential. Recombination and omission experiments validated the significance of these compounds. Non-volatile analysis revealed distinct differences in organic acids and chlorogenic acid content, with Colombia samples showing higher quinic acid levels, likely due to roasting-induced degradation. These findings provide a theoretical basis for understanding coffee flavor diversity and offer insights for quality assessment and origin identification. Full article

Houttuynia cordata is an Asian culinary herb with a characteristic fishy aroma. The most odor-active compounds, which had previously been identified by a comparative aroma extract dilution analysis applied to fresh rhizomes and leaves, were quantitated by GC–MS or GC–FID. Results revealed 23 and 22 compounds with odor activity values (OAVs) > 1, i.e., their concentrations exceeded their odor threshold concentrations, in rhizomes and leaves, respectively. Of these, myrcene (geranium leaf-like) and 3-oxododecanal (metallic, soapy, fishy) showed the highest OAVs. Aroma reconstitution and omission tests revealed that 3-oxododecanal is key to the characteristic fishy note. Results on the effect of tissue disruption suggested that 3-oxododecanal was already present in the intact H. cordata plant and released upon mechanical impact. Full article

Ensuring food quality and safety is a growing challenge in the food industry, where early detection of contamination or spoilage is crucial. Using gas sensors combined with Artificial Intelligence (AI) offers an innovative and effective approach to food identification, improving quality control and minimizing health risks. This study aims to evaluate food identification strategies using supervised learning techniques applied to data collected by the BME Development Kit, equipped with the BME688 sensor. The dataset includes measurements of temperature, pressure, humidity, and, particularly, gas composition, ensuring a comprehensive analysis of food characteristics. The methodology explores two strategies: a neural network model trained using Bosch BME AI-Studio software, and a more flexible, customizable approach that applies multiple predictive algorithms, including DT, LR, kNN, NB, and SVM. The experiments were conducted to analyze the effectiveness of both approaches in classifying different food samples based on gas emissions and environmental conditions. The results demonstrate that combining electronic noses (E-Noses) with machine learning (ML) provides high accuracy in food identification. While the neural network model from Bosch follows a structured and optimized learning approach, the second methodology enables a more adaptable exploration of various algorithms, offering greater interpretability and customization. Both approaches yielded high predictive performance, with strong classification accuracy across multiple food samples. However, performance variations depend on the characteristics of the dataset and the algorithm selection. A critical analysis suggests that optimizing sensor calibration, feature selection, and consideration of environmental parameters can further enhance accuracy. This study confirms the relevance of AI-driven gas analysis as a promising tool for food quality assessment. Full article

Cognitive Odor Source Localization (OSL) strategies are reliable search strategies for turbulent environments, where chemical cues are sparse and intermittent. These methods estimate a probabilistic belief over the source location using Bayesian inference and guide the searching movement by evaluating expected entropy reduction at candidate new positions. By maximizing expected information gain, agents make informed decisions rather than simply reacting to sensor readings. However, computing entropy reductions is computationally expensive, making real-time implementation challenging for resource-constrained platforms. Interestingly, search trajectories produced by cognitive algorithms often resemble those of small insects, suggesting that informative movement patterns might be replicated using simpler, bio-inspired searching strategies. This work investigates that possibility by analysing spatial distribution of entropy reductions across the entire search area. Rather than focusing on searching algorithms and local decisions, the analysis maps information gain over the full environment, identifying consistent high-gain regions that may serve as navigational cues. Results show that these regions often emerge near the source and along plume borders and that expected entropy reduction is strongly influenced by prior belief shape and sensor observations. This global perspective enables identification of spatial patterns and high-gain regions that remain hidden when analysis is restricted to local neighborhoods. These insights enable synthesis of hybrid search strategies that preserve cognitive effectiveness while significantly reducing computational cost. Full article

The quality of white wine is related to sensory attributes like color, odor and taste. This study focused mainly on taste attributes of white wines. The research hypothesis was to find out if taste-related attributes alone, determined by sensory experiment, could discriminate Chardonnay versus non-Chardonnay wines. Sensory analyses were performed with a trained panel on commercial white wines made from single varieties. Black glasses and nose clips were used to remove sensory interference and to first assess only taste attributes. Initial tests were then performed to evaluate the possibility to discriminate against Chardonnay wines only due to taste. In a second series of experiments, Rate All That Apply (RATA) experiments were performed in a set of Chardonnay versus non-Chardonnay wines. An initial sensory experiment revealed that some of the Chardonnay wines could be discriminated against by taste only but that recognition by using olfaction was more powerful which confirmed our research hypothesis in part. The second series of RATA sensory analysis revealed that some specific descriptors such as fat, salt, bitter and acid are involved in the taste discrimination of Chardonnay versus non-Chardonnay wines, especially with Sauvignon Blanc wines. These findings suggest that while modal sensory approach remains more robust for varietal identification, taste alone offers some discriminatory power. Full article

Flavor, as one of the primary factors that attracts consumers, has always been a crucial indicator for evaluating the quality of food. From processing to final consumption, the conditions that affect consumers’ perception of the aroma of aquatic products can be divided into three stages: aroma formation, release, and signal transmission. Currently, there are few reviews on the formation, release, and perception of aroma in aquatic products, which has affected the product development of aquatic products. This review summarizes aroma formation pathways, the effects of processing methods, characteristic volatile compounds, various identification techniques, aroma-release influencing factors, and the aroma perception mechanisms of aquatic products. The Maillard reaction and lipid oxidation are the main pathways for the formation of aromas in aquatic products. The extraction, identification, and quantitative analysis of volatile compounds reveal the odor changes in aquatic products. The composition of aquatic products and oral processing mainly influence the release of odorants. The characteristic odorants perceived from the nasal cavity should be given more attention. Moreover, the relationship between various olfactory receptors (ORs) and the composition of multiple aromatic compounds remains to be understood. It is necessary to clarify the relationship between nasal cavity metabolism and odor perception, reveal the binding and activation mode of ORs and odor molecules, and establish an accurate aroma prediction model. Full article

Investigating the volatiles isolated from a commercial spirulina (Arthrospira platensis) dietary supplement by gas chromatography–olfactometry (GC–O) in combination with an aroma extract dilution analysis (AEDA) resulted in 29 odor events with flavor dilution (FD) factors between 8 and 2048. Identification experiments, including various offline and online fractionation approaches, led to the structure assignment of 30 odorants, among which the most potent were sweaty 2- and 3-methylbutanoic acid (FD 2048), roasty, earthy, shrimp-like 2-ethyl-3,5-dimethylpyrazine (FD 2048), vinegar-like acetic acid (FD 1024), and floral, violet-like β-ionone (FD 1024). Static headspace dilution analysis revealed sulfuric, cabbage-like methanethiol (FD factor ≥ 32) as an additional potent odorant. In summary, 31 important spirulina odorants were identified in this study, and 14 were reported for the first time as spirulina constituents. Our data will provide a basis for future odor optimization of spirulina-based food products. Full article

This study aimed to investigate phytoplankton dynamics and water quality at three drinking water intakes (Duchang, Hukou, and Xingzi) in Poyang Lake through monthly monitoring from May 2023 to April 2024. The results showed that a total of 168 species of phytoplankton were identified in nine phyla, and there were significant spatial and temporal differences in the abundance of phytoplankton at the three waterworks intakes, with a spatial trend of annual mean values of Duchang > Xingzi > Hukou and a seasonal trend of summer and autumn > spring and winter. The dominant species of phytoplankton in the waterworks intakes of the three waterworks also showed obvious spatial and temporal differences. Cyanobacteria (particularly Pseudanabaena sp. and Microcystis sp.) dominated the phytoplankton communities during summer and autumn, demonstrating significant water degradation potential. In contrast, Cyclotella sp. prevailed in winter and spring assemblages. Based on water quality assessments at the three intake sites, the Duchang County intake exhibited year-round mild eutrophication with persistent mild cyanobacterial blooms (June–October), while the other two sites maintained no obvious bloom conditions. Further analyzing the toxic/odor-producing algal strains, the numbers of dominant species of Pseudanabaena sp. and Microcystis sp. in June–October in Duchang County both exceeded 1.0 × 10⁷ cells·L⁻¹. It is necessary to focus on their release of ATX-a (ichthyotoxin-a), 2MIB (2-Methylisoborneol), MCs (microcystins), etc., to ensure the safety of the water supply at the intake. Building upon these findings, we propose a generalized algal monitoring framework, encompassing three operational pillars: (1) key monitoring area identification, (2) high-risk period determination, and (3) harmful algal warnings. Each of these is substantiated by our empirical observations in Poyang Lake. Full article

Cat owners are involved in their cats’ healthcare, including the prevention of parasitic diseases. However, a comprehensive understanding of their preferences for feline antiparasitics is lacking. This study addresses this gap through a multifaceted methodology comprising three phases. In Phase 1, the physical properties and usability aspects of seven topical antiparasitic formulations were assessed. Within Phase 2, an ease-of-use study was conducted to evaluate the cat owners’ application experience with deidentified products representing three topical antiparasitics. Phase 3 included the identification and validation of product attributes most valued by pet owners through interviews with cat owners and veterinary experts. The product attributes identified informed the subsequent quantitative discrete choice experiment (DCE), which involved 1040 cat owners from different countries (Australia/New Zealand, Canada, Greece/Spain, and the UK) and aimed to analyze their preferences based on choices among product profiles mirroring four topical antiparasitics: selamectin–sarolaner, moxidectin–fluralaner, moxidectin–imidacloprid, and eprinomectin–esafoxolaner–praziquantel. Phase 1 showed that the selamectin–sarolaner formulation exhibits minimal odor, less stickiness, and less drying time. The ease-of-use study (Phase 2) showed that the blinded product representing the selamectin–sarolaner formulation was characterized by seamless application, rapid dispensing, and a sense of control during application. The quantitative DCE study (Phase 3) indicated a preference for the product profile mirroring the selamectin–sarolaner formulation among a global sample of cat owners. Demographic characteristics such as gender, age, and insurance status influenced their preferences. Key predictors for preferring the selamectin–sarolaner formulation over at least one comparator treatment included the ability to confirm successful administration, age restrictions, ease of application, and the time before the cat could sit on furniture following administration. These findings suggest that cat owners prioritize ease of use, safety, and overall user experience, providing valuable guidance for veterinary practitioners to make informed treatment recommendations. Full article

Objectives: The study aimed to investigate the differences in odor, color, and taste characteristics between raw and bran-fried Acori tatarinowii Rhizoma (RATR and BATR) using advanced sensory evaluation technologies. The objective was to establish a reliable differential analysis method for distinguishing RATR and BATR slices to support quality control in herbal processing. Methods: The Heracles NEO ultra-fast gas-phase electronic nose was employed to analyze odor profiles, while electronic eye and electronic tongue technologies were used to assess color and taste differences, respectively. Odor fingerprint analysis identified key volatile components, and colorimetric and taste measurements were conducted to compare RATR and BATR samples. Results: Fifteen characteristic odor components were identified, with methanol, 2-propanol, and 2-cyclopentenone potentially serving as discriminant markers differentiating RATR and BATR. PCA demonstrated exceptional separation efficacy, with a cumulative contribution rate of 99.937% for the primary components. Conclusions: The integration of Heracles NEO electronic nose, electronic eye, and electronic tongue technologies effectively distinguished RATR from BATR. This approach provides a novel strategy for online quality monitoring in herbal slice production and offers a robust analytical framework for the identification and quality assessment of processed herbal medicines. Full article

Background: Chemical odor profiling within forensic entomology is an emerging tool given its potential for species identification and larval aging and its ability to identify decomposition stages. A volatile analysis of larval masses across species of distinctive developmental stages was carried out with extraction techniques to identify odor signatures. However, it is unknown how larval sample handling (i.e., live samples in research vs. hot-water-killed samples in casework) affects odor signatures or the possibility of obtaining relevant volatiles from a single larva. Method: This study utilized solid-phase microextraction (SPME) with gas chromatography–mass spectrometry (GC/MS) for the analysis of odor volatiles emanating from single larval samples of Cochliomyia macellaria. Fifty (50) larvae (25 live; 25 boiled) were analyzed. Results: The SPME-GC/MS method allowed for odor volatile detection from a single maggot regardless of the sample handling group. The main compounds identified across both groups included those previously reported as emanating from larvae and decomposition substrates. When comparing treatments, the boiled larval samples had a 6-fold decrease in compound abundance compared to the live samples. The identified odor volatiles observed in the hot-water-killed treatment group included indole, p-cresol, and phenol. Conclusions: These results suggest that the handling technique impacts odor detection. Additionally, the heterocyclic aromatics and alcohols identified in the boiled samples are potentially odor markers of a higher intrinsic nature to the maggot rather than a cross-transfer from the decomposition substrate given their survival post elevated temperature treatment. This work shows the plausibility of carrying out an odor analysis of a single maggot following both common research and casework handling practices. Full article

The main root, reed head, and fibrous root are three different main edible medicinal parts of ginseng (Panax ginseng C. A. Meyer). When processed into ginseng products, such as ginseng powder, they exhibit similar colors and odors, easily confused in market circulation. However, there are differences in their pharmacological activity and clinical indications. Therefore, the identification of the different parts of ginseng powder is crucial for ensuring the quality, safety, and efficacy of medicinal ginseng products. In this study, we utilized gas chromatography–ion mobility spectrometry (GC–IMS) to analyze volatile organic components (VOCs) in main root, reed head, and fibrous root of ginseng. It was found that the composition of VOCs in different parts of ginseng powder was similar, but the content was different in all samples, and a total of 68 signal peaks was detected and 65 VOCs identified. In addition, combined with fingerprint analysis, principal component analysis (PCA), Euclidean distance, partial-least squares discriminant analysis (PLS-DA), and cluster analysis (CA), it clearly showed the significant differences between VOCs in different parts of ginseng powder. Our findings reveal that GC–IMS combined with chemometrics is a reliable method for distinguishing the active parts of ginseng powder, and provides essential data support for different parts of ginseng processing and functional product development. Full article

The problem of the foul odor caused by H₂S in livestock farms has become a major complaints. In this study, optimal sulfur-oxidizing bacteria (SOB) strains were screened from dairy farm wastewater and the adjacent soil for odor treatment. The strains and physiological functions were determined by identification and genome comparison, and the optimal operating conditions were determined by experiments under different conditions. The identification results showed that the strain that had the highest homology with Halomonas mongoliensis was Halomonas sp. AEB2. The comparative genomic results showed that the average nucleotide identity and DNA–DNA hybridization value were 95.8% and 68.6%, respectively. The optimization results were as follows: sodium succinate-carbon (10 g/L) and ammonium chloride-nitrogen (0.07 g/L). The optimal operating conditions were as follows: seeding rate 4%, temperature 30 °C, stirring speed 90 rpm, and pH 8. The oxidation products of AEB2 were mainly elemental sulfur and tetrathionate, and the metabolic pathway of AEB2 was constructed accordingly. This study suggests a feasible path to reduce H₂S emissions from dairy farms, and it provides theoretical support for the restoration of livestock environment and sustainability. Full article