Effect of jujube powder addition on the aroma profile of quinoa snacks (QS).

Quinoa is a full-nutrition food; however, its poor flavor and small size make it not the best food option for direct consumption. In this study, a quinoa snack (QS, a cake) was developed, and the aroma profile of the products was improved by adding jujube fruit powder (made from dried jujube fruits, from 5% to 30%). Gas chromatography mass spectrum (GC-MS) combined with electronic nose (e-nose) was applied for characterizing the aroma profiles of QS samples. Results showed a total of 26 aroma compounds were identified in QS samples by GC-MS, and 3-methylbutanol (from 1525 µg/kg in QS-30 to 3487 µg/kg in QS-0), ethanol (from 1126 µg/kg in QS-0 to 3581 µg/kg in QS-30), hexanal (from 125.6 µg/kg in QS-30 to 984.1 µg/kg in QS-0), and acetaldehyde (from 531.9 µg/kg in QS-30 to 191.1 µg/kg in QS-0) were common. The e-nose response of W1S (sensitive to methane, from 17.50 of QS-0 to 93.85 of QS-30) and W1W (sensitive to sulfur-organic compounds of e-nose, from 15.57 of QS-0 to 39.50 of QS-30) were significantly higher, and significant differences were presented among QS samples. In conclusion, the aroma profile of the QS sample was significantly (p < .05) enhanced by the addition of jujube powder, and QS-30 with the highest jujube content (30%) presented the strongest aroma profile. Moreover, QS samples with different additions of jujube powders could be well distinguished by principal component analysis (PCA), and the combination of e-nose and GC-MS was effective in the volatile profile analysis of QS samples.

Identification of characteristic flavor compounds of boletus edulis from different regions based on by E-nose, HS-GC-IMS and HS-SPME-GC-MS.

In this study, E-nose, HS-GC-IMS, and HS-SPME-GC-MS technologies were used to evaluate the flavor characteristics of the pileus and stipe of Boletus edulis from eight origins. 23 key Volatile organic compounds (VOCs) with odor activity values (OAVs) > 1 were identified, and 19 aroma types have been identified in Boletus edulis at the same time. Vegetable and earthy were defined as the dominant aroma types for all pileus and stipe samples. Balsamic and musty were the main and characteristic aroma types for the pileus. The highest concentrations of VOCs in the pileus and stipe were originated from Chuxiong Prefecture and Aba Prefecture, respectively. 19 and 16 key VOCs were detected Chuxiong pileus and Aba stipe, respectively, and Methional was the decisive compound that influenced the vegetable aroma type. The results of this study could be helpful for flavor identification and application of pileus and stipe from Boletus edulis.

Distinguishing between Wheat Grains Infested by Four Fusarium Species by Measuring with a Low-Cost Electronic Nose.

An electronic device based on the detection of volatile substances was developed in response to the need to distinguish between fungal infestations in food and was applied to wheat grains. The most common pathogens belong to the fungi of the genus Fusarium: F. avenaceum, F. langsethiae, F. poae, and F. sporotrichioides. The electronic nose prototype is a low-cost device based on commercially available TGS series sensors from Figaro Corp. Two types of gas sensors that respond to the perturbation are used to collect signals useful for discriminating between the samples under study. First, an electronic nose detects the transient response of the sensors to a change in operating conditions from clean air to the presence of the gas being measured. A simple gas chamber was used to create a sudden change in gas composition near the sensors. An inexpensive pneumatic system consisting of a pump and a carbon filter was used to supply the system with clean air. It was also used to clean the sensors between measurement cycles. The second function of the electronic nose is to detect the response of the sensor to temperature disturbances of the sensor heater in the presence of the gas to be measured. It has been shown that features extracted from the transient response of the sensor to perturbations by modulating the temperature of the sensor heater resulted in better classification performance than when the machine learning model was built from features extracted from the response of the sensor in the gas adsorption phase. By combining features from both phases of the sensor response, a further improvement in classification performance was achieved. The E-nose enabled the differentiation of F. poae from the other fungal species tested with excellent performance. The overall classification rate using the Support Vector Machine model reached 70 per cent between the four fungal categories tested.

A Prototype of Graphene E-Nose for Exhaled Breath Detection and Label-Free Diagnosis of Helicobacter Pylori Infection.

Helicobacter pylori (HP), a common microanaerobic bacteria that lives in the human mouth and stomach, is reported to infect ≈50% of the global population. The current diagnostic methods for HP are either invasive, time-consuming, or harmful. Therefore, a noninvasive and label-free HP diagnostic method needs to be developed urgently. Herein, reduced graphene oxide (rGO) is composited with different metal-based materials to construct a graphene-based electronic nose (e-nose), which exhibits excellent sensitivity and cross-reactive response to several gases in exhaled breath (EB). Principal component analysis (PCA) shows that four typical types of gases in EB can be well discriminated. Additionally, the potential of the e-nose in label-free detection of HP infection is demonstrated through the measurement and analysis of EB samples. Furthermore, a prototype of an e-nose device is designed and constructed for automatic EB detection and HP diagnosis. The accuracy of the prototype machine integrated with the graphene-based e-nose can reach 92% and 91% in the training and validation sets, respectively. These results demonstrate that the highly sensitive graphene-based e-nose has great potential for the label-free diagnosis of HP and may become a novel tool for non-invasive disease screening and diagnosis.

Characterization of volatile profile from different coriander (Coriandrum sativum L.) varieties via HS-SPME/GC-MS combined with E-nose analyzed by chemometrics.

Headspace-solid phase microextraction/gas chromatography-mass spectrometry (HS-SPME/GC-MS) and electronic nose (E-nose) technologies were implemented to characterize the volatile profile of aerial part from 40 coriander varieties. A total of 207 volatile compounds were identified and quantified, including aldehydes, alcohols, terpenes, hydrocarbons, esters, ketones, acids, furans, phenols and others. E-nose results showed that W5S and W2W were representative sensors responding to coriander odor. Among all varieties, the number (21-30 species) and content (449.94-1050.55 µg/g) of aldehydes were the highest, and the most abundant analytes were (Z)-9-hexadecenal or (E)-2-tetratecenal, which accounted for approximately one-third of the total content. In addition, 37 components were determined the characteristic constituents with odor activity values (OAVs) ≥ 1, mainly presenting citrusy, fatty, soapy and floral smells. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) could effectively distinguish different varieties. This study provided a crucial theoretical basis for flavor evaluation and quality improvement of coriander germplasm resources.

Real time detection and identification of fish quality using low-power multimodal artificial olfaction system.

Single gas quantification and mixed gas identification have been the major challenges in the field of gas detection. To address the shortcomings of chemo-resistive gas sensors, sensor arrays have been the subject of recent research. In this work, the research focused on both optimization of gas-sensing materials and further analysis of pattern recognition algorithms. Four bimetallic oxide-based gas sensors capable of operating at room temperature were first developed by introducing different modulating techniques on the sensing layer, including constructing surface oxygen defects, polymerizing conducting polymers, modifying Nano-metal, and compositing flexible substrates. The signals derived from the gas sensor array were then processed to eliminate noise and reduce dimension with the feature engineering. The gases of were qualitatively identified by support vector machine (SVM) model with an accuracy of 98.86 %. Meanwhile, a combined model of convolutional neural network and long short-term memory network (CNN-LSTM) was established to remove the interference samples and quantitatively estimate the concentration of the target gases. The combined model based on deep learning, which avoids the overfitting with local optimal solutions, effectively boosts the performance of concentration recognition with the lowest root mean square error (RMSE) of 2.3. Finally, a low-power artificial olfactory system was established by merging the multi-sensor data and applied for real-time and accurate judgment of the food freshness.

Comprehensive Analysis Reveals the Difference in Volatile Oil between Bupleurum marginatum var. stenophyllum (Wolff) Shan et Y. Li and the Other Four Medicinal Bupleurum Species.

Volatile oil serves as a traditional antipyretic component of Bupleuri Radix. Bupleurum marginatum var. stenophyllum (Wolff) Shan et Y. Li belongs to the genus Bupleurum and is distinguished for its high level of saikosaponins and volatile oils; nonetheless, prevailing evidence remains inconclusive regarding its viability as an alternative resource of other official species. This study aims to systematically compare the volatile oil components of both dried and fresh roots of B. marginatum var. stenophyllum and the four legally available Bupleurum species across their chemical, molecular, bionics, and anatomical structures. A total of 962 compounds were determined via GC-MS from the dried roots; B. marginatum var. stenophyllum showed the greatest differences from other species in terms of hydrocarbons, esters, and ketones, which was consistent with the results of fresh roots and the e-nose analysis. A large number of DEGs were identified from the key enzyme family of the monoterpene synthesis pathway in B. marginatum var. stenophyllum via transcriptome analysis. The microscopic observation results, using different staining methods, further showed the distinctive high proportion of phloem in B. marginatum var. stenophyllum, the structure which produces volatile oils. Together, these pieces of evidence hold substantial significance in guiding the judicious development and utilization of Bupleurum genus resources.

Real-Time Monitoring of Odour Emissions at the Fenceline of a Waste Treatment Plant by Instrumental Odour Monitoring Systems: Focus on Training Methods.

Waste treatment plants (WTPs) often generate odours that may cause nuisance to citizens living nearby. In general, people are becoming more sensitive to environmental issues, and particularly to odour pollution. Instrumental Odour Monitoring Systems (IOMSs) represent an emerging tool for continuous odour measurement and real-time identification of odour peaks, which can provide useful information about the process operation and indicate the occurrence of anomalous conditions likely to cause odour events in the surrounding territories. This paper describes the implementation of two IOMSs at the fenceline of a WTP, focusing on the definition of a specific experimental protocol and data processing procedure for dealing with the interferences of humidity and temperature affecting sensors' responses. Different approaches for data processing were compared and the optimal one was selected based on field performance testing. The humidity compensation model developed proved to be effective, bringing the IOMS classification accuracy above 95%. Also, the adoption of a class-specific regression model compared to a global regression model resulted in an odour quantification capability comparable with those of the reference method (i.e., dynamic olfactometry). Lastly, the validated models were used to process the monitoring data over a period of about one year.

Characterizing the composition of volatile compounds in different types of Chinese bacon using GC-MS, E-nose, and GC-IMS.

Chinese bacon is highly esteemed by consumers worldwide due to its unique aroma. The composition of volatile organic compounds (VOCs) varies significantly among different types of Chinese bacon. This study analyzed the VOCs of Chinese bacon from Sichuan, Hunan, Guangxi, and Shaanxi provinces using gas chromatography-mass spectrometry (GC-MS), an electronic nose (E-nose), and gas chromatography-ion mobility spectrometry (GC-IMS). The results demonstrate that the combination of GC-MS and GC-IMS effectively distinguishes Chinese bacon from different regions. Notably, Guangxi bacon lacks a smoky aroma, which sets it apart from the other types. However, it contains many esters that play a crucial role in its flavor profile. In contrast, phenols, including guaiacol, which is typical in smoked bacon, were present in the bacon from Sichuan, Hunan, and Shaanxi but were absent in Guangxi bacon. Furthermore, Hunan bacon exhibited a higher aldehyde content than Sichuan bacon. 2-methyl-propanol and 3-methyl-butanol were identified as characteristic flavor compounds of Zhenba bacon. This study provides a theoretical foundation for understanding and identifying the flavor profiles of Chinese bacon. Using various analytical techniques to investigate the flavor compounds is essential for effectively distinguishing bacon from different regions.

Clinical Application of Exhaled Breath Condensate in Diagnosis of Diseases.

Respiratory diseases are highly prevalent in the general population, and the morbidity, mortality, and healthcare burden on society at large have been on the rise worldwide. For example, lung cancer is a major contributor to cancer-related mortality around the globe, and identifying clinically relevant biomarkers for lung cancer detection at both early and metastatic stages has been a pressing need. Human metabolism is complicated and may vary with different individuals. Despite advances in the treatment and the early screening of respiratory diseases, most diagnoses are established at a late stage, i.e., when genetic and epigenetic changes have developed. A promising source of biomarkers indicative of the pathogenesis of respiratory diseases is exhaled breath condensate (EBC), a biological fluid and a natural matrix of the respiratory tract. Molecules, such as DNAs, RNAs, proteins, metabolites, and others, are found in EBC, and their presence/absence or changes in concentrations can serve as biomarkers. This review discusses the exhaled breath composition, candidate EBC biomarkers, and the potential to use EBC for diagnosing diseases, therapeutic monitoring, and screening high-risk individuals.

Evaluation of the quality grade of Congou black tea by the fusion of GC-E-Nose, E-tongue, and E-eye.

In the present study, the comprehensive quality of Congou black tea (CBT) including aroma, taste, and liquid color was investigated by a combination of gas chromatography electronic nose (GC-E-Nose), electronic tongue (E-tongue), and electronic eye (E-eye). An excellent discrimination of different quality grades of CBT was accomplished through the fusion of GC-E-Nose, E-tongue, and E-eye combined with orthogonal partial least squares discriminant analysis, with parameters of R2Y = 0.803 and Q2 = 0.740. Moreover, the quantitative evaluation of CBT quality was successfully achieved by partial least squares regression analysis, with the absolute error within 1.39 point, and the relative error within 1.62%. Additionally, 12 key variables were screened out by stepwise multiple linear regression analysis, which significantly contributed to the comprehensive quality score of CBT. Our results suggest that the fusion of multiple intelligent sensory technologies offers great potential and practicability in the quality evaluation of black tea.

Diagnostic performance of volatile organic compounds analysis and electronic noses for detecting colorectal cancer: a systematic review and meta-analysis.

Introduction: The detection of Volatile Organic Compounds (VOCs) could provide a potential diagnostic modality for the early detection and surveillance of colorectal cancers. However, the overall diagnostic accuracy of the proposed tests remains uncertain. Objective: This systematic review is to ascertain the diagnostic accuracy of using VOC analysis techniques and electronic noses (e-noses) as noninvasive diagnostic methods for colorectal cancer within the realm of clinical practice. Methods: A systematic search was undertaken on PubMed, EMBASE, Web of Science, and the Cochrane Library to scrutinize pertinent studies published from their inception to September 1, 2023. Only studies conducted on human subjects were included. Meta-analysis was performed using a bivariate model to obtain summary estimates of sensitivity, specificity, and positive and negative likelihood ratios. The Quality Assessment of Diagnostic Accuracy Studies 2 tool was deployed for quality assessment. The protocol for this systematic review was registered in PROSPERO, and PRISMA guidelines were used for the identification, screening, eligibility, and selection process. Results: This review encompassed 32 studies, 22 studies for VOC analysis and 9 studies for e-nose, one for both, with a total of 4688 subjects in the analysis. The pooled sensitivity and specificity of VOC analysis for CRC detection were 0.88 (95% CI, 0.83-0.92) and 0.85 (95% CI, 0.78-0.90), respectively. In the case of e-nose, the pooled sensitivity was 0.87 (95% CI, 0.83-0.90), and the pooled specificity was 0.78 (95% CI, 0.62-0.88). The area under the receiver operating characteristic analysis (ROC) curve for VOC analysis and e-noses were 0.93 (95% CI, 0.90-0.95) and 0.90 (95% CI, 0.87-0.92), respectively. Conclusion: The outcomes of this review substantiate the commendable accuracy of VOC analysis and e-nose technology in detecting CRC. VOC analysis has a higher specificity than e-nose for the diagnosis of CRC and a sensitivity comparable to that of e-nose. However, numerous limitations, including a modest sample size, absence of standardized collection methods, lack of external validation, and a notable risk of bias, were identified. Consequently, there exists an imperative need for expansive, multi-center clinical studies to elucidate the applicability and reproducibility of VOC analysis or e-nose in the noninvasive diagnosis of colorectal cancer. Systematic review registration: https://www.crd.york.ac.uk/prospero/#recordDetails, identifier CRD42023398465.

Evaluating the Non-Invasive Measurement of Apple Aroma Using Electronic Nose Device through Comparison with Direct Mass Spectrometry, Sugar Content, and Ripeness Measurements.

To compare apple aroma intensities, apples were analyzed from the calyx side (on the opposite side of the stem) using an electronic nose (e-nose) sensor device and direct mass spectrometry. The results indicated that the sensor value tended to increase in accordance with the total intensity of apple aroma components measured by direct mass spectrometry. In addition, the e-nose sensor values for apple aroma did not correlate with the sugar content and ripeness measurements using optical sensors. Moreover, the relative standard deviations of repeatability and intermediate precision in the measurement of apple flavor (apple lip balm) were within 1.36-9.96%. Similar to the utilization of sugar content and ripeness values, the aroma measured from the calyx side can be potentially used for apple evaluation.

Ammonia Detection by Electronic Noses for a Safer Work Environment.

Providing employees with proper work conditions should be one of the main concerns of any employer. Even so, in many cases, work shifts chronically expose the workers to a wide range of potentially harmful compounds, such as ammonia. Ammonia has been present in the composition of products commonly used in a wide range of industries, namely production in lines, and also laboratories, schools, hospitals, and others. Chronic exposure to ammonia can yield several diseases, such as irritation and pruritus, as well as inflammation of ocular, cutaneous, and respiratory tissues. In more extreme cases, exposure to ammonia is also related to dyspnea, progressive cyanosis, and pulmonary edema. As such, the use of ammonia needs to be properly regulated and monitored to ensure safer work environments. The Occupational Safety and Health Administration and the European Agency for Safety and Health at Work have already commissioned regulations on the acceptable limits of exposure to ammonia. Nevertheless, the monitoring of ammonia gas is still not normalized because appropriate sensors can be difficult to find as commercially available products. To help promote promising methods of developing ammonia sensors, this work will compile and compare the results published so far.

Insights into the Volatile Flavor Profiles of Two Types of Beef Tallow via Electronic Nose and Gas Chromatography-Ion Mobility Spectrometry Analysis.

In the current study, an electronic nose (E-nose) and gas chromatography-ion mobility spectrometry (GC-IMS) were employed to investigate the volatile flavor compounds (VFCs) of intense flavor beef tallow (L) and ordinary beef tallow (P). The study results indicate that an E-nose combined with an LDA and GC-IMS combined with an OPLS-DA can effectively distinguish between the two types of beef tallow. Compared with ordinary beef tallow, the E-nose sensors of intense flavor beef tallow have stronger response signals to sulfides, terpenes, and nitrogen oxides. A total of 22 compounds contribute to making the flavor of intense flavor beef tallow more typical and richer; in contrast, ethyl acetate was the main aroma-active compound found in the ordinary beef tallow. Sulfur-containing compounds and terpenoids might be the key substances that cause sensory flavor differences between the two types of beef tallow. In conclusion, the results of this study clarify the characteristics and differences of the two types of beef tallow and provide an enhanced understanding of the differences in the flavors of the two types of beef tallow.

A Real-World Assessment of Stage I Lung Cancer Through Electronic Nose Technology.

INTRODUCTION: Electronic nose (E-nose) technology has reported excellent sensitivity and specificity in the setting of lung cancer screening. However, the performance of E-nose specifically for early-stage tumors remains unclear. Therefore, the aim of our study was to assess the diagnostic performance of E-nose technology in clinical stage I lung cancer. METHODS: This phase IIc trial (NCT04734145) included patients diagnosed with a single greater than or equal to 50% solid stage I nodule. Exhalates were prospectively collected from January 2020 to August 2023. Blinded bioengineers analyzed the exhalates, using E-nose technology to determine the probability of malignancy. Patients were stratified into three risk groups (low-risk, [<0.2]; moderate-risk, [≥0.2-0.7]; high-risk, [≥0.7]). The primary outcome was the diagnostic performance of E-nose versus histopathology (accuracy and F1 score). The secondary outcome was the clinical performance of the E-nose versus clinicoradiological prediction models. RESULTS: Based on the predefined cutoff (<0.20), E-nose agreed with histopathologic results in 86% of cases, achieving an F1 score of 92.5%, based on 86 true positives, two false negatives, and 12 false positives (n = 100). E-nose would refer fewer patients with malignant nodules to observation (low-risk: 2 versus 9 and 11, respectively; p = 0.028 and p = 0.011) than would the Swensen and Brock models and more patients with malignant nodules to treatment without biopsy (high-risk: 27 versus 19 and 6, respectively; p = 0.057 and p < 0.001). CONCLUSIONS: In the setting of clinical stage I lung cancer, E-nose agrees well with histopathology. Accordingly, E-nose technology can be used in addition to imaging or as part of a "multiomics" platform.

Volatolomics-assisted characterization of the key odorants in green off-flavor black tea and their dynamic changes during processing.

Aroma plays a pivotal role in the quality of black tea. However, the acceptability of black tea is greatly limited by the green off-flavor (GOF) resulting from the inappropriate processing control. In this study, the key odorants causing GOF were investigated by volatolomics, and their dynamic changes and formation pathways were in-depth understood. Significant alterations in volatile metabolites were observed in the withering stage. A total of 14 key odorants were identified as contributors to GOF, including 2-methylpropanal, 3-methylbutanal, 1-hexanol, nonanal, (E, E)-2,4-heptadienal, benzaldehyde, linalool, (E, E)-3,5-octadiene-2-one, ß-cyclocitral, phenylacetaldehyde, (E, E)-2,4-nonadienal, methyl salicylate, geraniol, and ß-ionone. Among them, (E, E)-2,4-heptadienal (OAV = 3913), characterized by fatty, green, and oily aromas, was considered to be the most important contributor causing GOF. Moreover, it was found that lipid degradation served as the primary metabolic pathway for GOF. This study provides a theoretical foundation for off-flavor control and quality improvement of black tea.

Comprehensive investigation on the dynamic changes of volatile metabolites in fresh scent green tea during processing by GC-E-Nose, GC-MS, and GC × GC-TOFMS.

Processing technology plays a crucial role in the formation of tea aroma. The dynamic variations in volatile metabolites across different processing stages of fresh scent green tea (FSGT) were meticulously tracked utilizing advanced analytical techniques such as GC-E-Nose, GC-MS, and GC × GC-TOFMS. A total of 244 volatile metabolites were identified by GC-MS and GC × GC-TOFMS, among which 37 volatile compounds were concurrently detected by both methods. Spreading and fixation stages were deemed as pivotal processes for shaping the volatile profiles in FSGT. Notably, linalool, heptanal, 2-pentylfuran, nonanal, ß-myrcene, hexanal, 2-heptanone, pentanal, 1-octen-3-ol, and 1-octanol were highlighted as primary contributors to the aroma profiles of FSGT by combining odor activity value assessment. Furthermore, lipid degradation and glycoside hydrolysis were the main pathways for aroma formation of FSGT. The results not only elucidate the intricate variations in volatile metabolites but also offer valuable insights into enhancing the processing techniques for improved aroma quality of green tea.

Rapid quantitative authentication and analysis of camellia oil adulterated with edible oils by electronic nose and FTIR spectroscopy.

Camellia oil, recognized as a high-quality edible oil endorsed by the Food and Agriculture Organization, is confronted with authenticity issues arising from fraudulent adulteration practices. These practices not only pose health risks but also lead to economic losses. This study proposes a novel machine learning framework, referred to as a transformer encoder backbone with a support vector machine regressor (TES), coupled with an electronic nose (E-nose), for detecting varying adulteration levels in camellia oil. Experimental results indicate that the proposed TES model exhibits the best performance in identifying the adulterated concentration of camellia oi, compared with five other machine learning models (the support vector machine, random forest, XGBoost, K-nearest neighbors, and backpropagation neural network). The results obtained by E-nose detection are verified by complementary Fourier transform infrared (FTIR) spectroscopy analysis for identifying functional groups, ensuring accuracy and providing a comprehensive assessment of the types of adulterants. The proposed TES model combined with E-nose offers a rapid, effective, and practical tool for detecting camellia oil adulteration. This technique not only safeguards consumer health and economic interests but also promotes the application of E-nose in market supervision.

Characterization of flavor and taste profile of different radish (Raphanus Sativus L.) varieties by headspace-gas chromatography-ion mobility spectrometry (GC/IMS) and E-nose/tongue.

A comprehensive study of the overall flavor and taste profile of different radishes is lacking. This study systematically compared the volatile profile of six radish varieties using HS-GC-IMS and their correlation with the E-nose analysis. Organic acids and amino acids were quantified, and their association with the E-tongues analysis was explored. A total of 73 volatile compounds were identified, with diallyl sulfide and dimethyl disulfide being the primary sulfides responsible for the unpleasant flavor in radish. Compared to other varieties, cherry radishes boast a significantly higher concentration of allyl isothiocyanate, which likely contributes to their characteristic radish flavor. Moreover, oxalic acid was identified as the most abundant organic acid in radish, accounting for over 97% of its content, followed by malic acid and succinic acid. In conclusion, the distinct flavor and taste characteristics of different radish varieties partially explain their suitability for diverse culinary preferences.