Search

Introduction Volatile organic compounds (VOCs) in breath serve as a source of biomarkers for medical conditions relevant to warfighter health including Corona Virus Disease and other potential biological threats. Electronic noses are integrated arrays of gas sensors that are cost-effective and miniaturized devices that rapidly respond to VOCs in exhaled breath. The current study seeks to qualify healthy breath baselines of exhaled VOC profiles through analysis using a commercialized array of metal oxide (MOX) sensors. Materials and Methods Subjects were recruited/consented through word of mouth and using posters. For each sample, breath was analyzed using an array of MOX sensors with parameters that were previously established. Data were also collected using a lifestyle questionnaire and from a blood test to assess markers of general health. Sensor data were processed using a feature extraction algorithm, which were analyzed through statistical approaches to identify correlations with confounding factors. Reproducibility was also assessed through relative standard deviation values of sensor features within a single subject and between different volunteers. Results A total of 164 breath samples were collected from different individuals, and 10 of these volunteers provided an additional 9 samples over 6 months for the longitudinal study. First, data from different subjects were analyzed, and the trends of the 17 extracted features were elucidated. This revealed not only a high degree of correlation between sensors within the array but also between some of the features extracted within a single sensor. This helped guide the removal of multicollinear features for multivariate statistical analyses. No correlations were identified between sensor features and confounding factors of interest (age, body mass index, smoking, and sex) after P -value adjustment, indicating that these variables have an insignificant impact on the observed sensor signal. Finally, the longitudinal replicates were analyzed, and reproducibility assessment showed that the variability between subjects was significantly higher than within replicates of a single volunteer (P -value = .002). Multivariate analyses within the longitudinal data displayed that subjects could not be distinguished from one another, indicating that there may be a universal healthy breath baseline that is not specific to particular individuals. Conclusions The current study sought to qualify healthy baselines of VOCs in exhaled breath using a MOX sensor array that can be leveraged in the future to detect medical conditions relevant to warfighter health. For example, the results of the study will be useful, as the healthy breath VOC data from the sensor array can be cross-referenced in future studies aiming to use the device to distinguish disease states. Ultimately, the sensors may be integrated into a portable breathalyzer or current military gear to increase warfighter readiness through rapid and noninvasive health monitoring. [ABSTRACT FROM AUTHOR]

In this study, shrimp paste was prepared using Antarctic krill and fermented Antarctic krill shrimp paste as raw materials. Two commonly used heating methods, stir‐fried and steaming, were analyzed, the main difference between the two methods being that stir‐frying involves putting the shrimp paste into a wok and stir‐frying it for different periods of time, while steaming involves putting the shrimp paste into a steamer and steaming it for different periods of time. The effects of different salt concentrations and processing techniques on the volatile flavor compounds of shrimp paste were also observed. Electronic nose and gas chromatography–ion mobility spectrometry (GC‐IMS) were employed to analyze the volatile flavor compounds. A total of 52 volatile flavor compounds were detected by GC‐IMS, of which 38 were identified (including monomers, dimers, and polymers). The identified compounds included 11 aldehydes, 6 ketones, 14 alcohols, 2 esters, 2 acids, 1 pyridine compound, and 2 sulfur compounds. In addition, 14 compounds were identifiable. Using the results of the electronic nose analysis, we were also able to differentiate between the volatile flavor compounds in shrimp pastes produced by different processing methods. [ABSTRACT FROM AUTHOR]

Fruit aroma of Japanese apricot is distinct, and the specific volatile compounds are not clearly known during fruit development and during post‐harvest stage. This study therefore aimed to explore the volatile compounds present during these stages. The volatile compounds were analysed by headspace solid‐phase microextraction and gas chromatography–mass spectrometry. OAV, PCA and electronic nose techniques were used to determine the characteristic aroma components. Enzyme‐linked immunoassay (ELISA) was also applied to determine the activity of enzymes. The results showed that in the cultivars 'Xiyeqing' a total of 52 components that included 20 terpenes, 15 aldehydes, 9 esters, 3 ketones and 5 other substances were detected during fruit development and post‐harvest stage. While in the cultivar 'Xiaoyezhugan' a total of 49 components that included 25 terpenes, 7 aldehydes, 11 esters, 1 alcohol, 3 ketones and 2 other substances were also detected during fruit development and post‐harvest stage. We concluded that the characteristic volatile compounds of mature Japanese apricot fruit were (+)‐limonene, linalool, damascenone, β‐damascenone and nonanal, finding the basis for the fruity, floral and sweet aroma of the Japanese apricot fruit. Further analysis indicated that low temperature inhibited the synthesis of esters and terpenes, and dark conditions were more favourable to the synthesis of volatile compounds than light conditions. Short‐term storage of Japanese apricot fruit at room temperature and dark conditions was conducive for the maintenance of volatile compounds, and low‐temperature storage was the most destructive to the fruit volatile compounds. These findings form a theoretical foundation for exploring the specific volatile compound of Japanese apricot and helped to determine the optimal storage condition of post‐harvest stage for Japanese apricot fruit. [ABSTRACT FROM AUTHOR]

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this study, the odour values of rosemary, mint, black cumin, lavender, and thyme oils were determined by an electronic nose working with an Arduino microprocessor. The components of the plants were compared with the sensor data, and the most sensitive sensors were determined by sorting according to the highest components. The study data indicated that the MQ3 sensor exhibited the highest sensitivity for thyme, black cumin, and lavender oils, which contain 63% carvacrol, 38% thymoquinone, and 36% linalool, respectively. Also, MQ7 was the most sensitive sensor for menthone (68%) in mint oil and eucalyptol (45%) in rosemary oil. In addition, a low-cost and non-contact device that works with an infrared sensor has been developed to detect the identity of the oil added into the vial. The study data showed that low-cost Arduino-based IR and odour sensors can determine the identity and component percentage of oils. The fact that the developed device can detect with 100 percent accuracy even in case of peppermint and rosemary oils, which are very similar in appearance, shows that the study data will be an inspiration for contactless determination of oil quality and type. [ABSTRACT FROM AUTHOR]

BACKGROUND: In Thailand, the scaly grain mite, Suidasia pontifica Oudemans, impacts the feed industry by emitting a lemongrass‐like odor in contaminated feed, reducing its palatability. This study focused on identifying volatile organic compounds (VOCs) associated with this odor in contaminated chicken feeds and ground maize, as well as individual mites using gas chromatography–mass spectrometry (GC–MS). We explored the relationship between VOC concentration and mite population size in chicken feed cultures, aiming to detect minimal mite presence through regression models. Additionally, we tested the sensitivity of nine electronic odor sensors in detecting these VOCs. RESULTS: Our results showed Z‐citral and E‐citral present in mite‐contaminated ground maize, chicken feeds, but absent in uncontaminated samples. Mite populations in chicken feed followed a normal distribution, increasing rapidly, peaking, and then declining, a pattern mirrored in the concentrations of Z‐citral and E‐citral. Simple linear regression models confirmed a positive correlation between mite density and citral concentrations. Polynomial regression models indicated Z‐citral is detectable at mite densities over 67 individuals per gram and E‐citral over 3.89 individuals per gram. Odor sensors showed varying readings across different citral concentrations, uncontaminated, and mite‐infested chicken feeds. CONCLUSIONS: Our study confirms that S. pontifica are responsible for the lemongrass‐like odor in infested samples, due to Z‐citral and E‐citral. The citral concentrations increase with mite population growth and are detectable at low mite densities, suggesting their effectiveness as biomarkers for early mite infestation detection. Additionally, MQ series odor sensors detected these VOCs, indicating their potential for monitoring mite infestations in storage environments. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

After thermal treatment, quail eggs pruduce an attractive flavor that is favored by consumers. In this study, the key aroma volatiles and their lipid precursors during thermal treatment were investigated by the electronic nose, GC-MS, GC-O-MS and UPLC-Q-Exactive HF-X. The results exhibited that the raw and fresh flavor of raw egg yolks came from 1-Octen-3-ol, 2-Ethyl-1-hexanol, 1-Decene, and 1-Undecene. 2-Methyl-3-octanone, Toluene, and some aromatic compounds worked synergistically to contribute to the aroma profile of boiled eggs. (+)-2-Bornanone, Octanal, 2-Methyl-butanal, Nonanal, (.+Dihydro-3-hydroxy-4,4-dimethyl-2(3 H)-furanone, 6,7-Dihydro-2,5-dimethyl-5 H-cyclopentapyrazine, (E)-2-methyl-6-(1-propenyl)-pyrazine, 2-Ethyl-3,5-dimethyl-pyrazine, 3,5-Diethyl-2-methyl-pyrazine, 2,5-Dimethyl-pyrazine were the key flavor compounds in the fried egg and gave it the popcorn and roasted flavors. The statistical analysis of the lipid profile revealed that brief, high-temperature heating (100 or 200 °C for 10 min) in typical boiled and fried quail eggs had minor effects on the lipid nutritional value. PE-related lipids, particularly those containing 18-carbon fatty acids, contributed to the aroma formation of fried quail eggs. [ABSTRACT FROM AUTHOR]

Copyright of Science & Technology of Food Industry is the property of Science & Technology of Food Industry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Composting is an integral component of sustainable Municipal Solid Waste (MSW) management within the circular bio-economy platform. However, it faces challenges due to malodorous emissions that impact environmental and societal equilibrium. The present study aims to minimize odorous emissions and expedite compost maturation using a novel, efficient microbial consortium. Bacteria sourced from open dump sites in Sri Lanka were carefully screened based on concurrent enzyme production. Five developed consortia were tested for their performance in reducing malodors during the composting process of MSW. Consortium No. 5 (C5), comprised of Bacillus haynesii, Bacillus amyloliquefaciens, and Bacillus safensis, demonstrated outstanding performance with a significant (p < 0.05) reduction in odorous emissions. Additionally, consortium C5 exhibited impressive control over gas emissions, maintaining VOC, CH4, NH3, and H2S concentrations within ranges of 0.5-6 ppm, 0.5-0.8 ppm, 0.3-0.5 ppm, and 0.5-0.6 ppm, respectively, compared to control concentrations of 4.5-10.2 ppm, 0.5-5.5 ppm, 0.3-5.5 ppm, and 0.5-6.4 ppm, respectively. Additionally, comprehensive Electronic nose (E-nose) analysis substantiated C5's efficiency in attenuating Methane-Aliphatic compounds, Sulfur and Aromatic compounds, along with low-polarity aromatic and alkane compounds, all with statistical significance (p < 0.05). Further, the developed consortium could reduce the composting time from 110 ± 10 days to 17 ± 3 days, offering a sustainable solution for global MSW management. [ABSTRACT FROM AUTHOR]

This study investigated the effects of hot air drying (HAD), infrared-assisted hot air drying (IR-HAD), vacuum freeze drying (VFD), and pulsed-vacuum drying (PVD) on the drying characteristics, color, microstructure, total phenolic content (TPC), total flavonoid content (TFC), vitamin C (Vc) content, and the odor analysis using electronic nose of sea buckthorn pomace. The results showed that IR-HAD exhibited the highest drying rate and the shortest drying time (250"min). PVD exhibited the highest TPC, TFC, and Vc content while maintaining a color difference Î"E value closest to that of the fresh sample. PVD microstructure exhibited no collapse, fewer pores, and smaller cracks than the IR-HAD and VFD microstructures. Furthermore, the PVD pomace displayed the lowest reactivity to sulfides and ethanol compounds. The comprehensive analysis suggests that PVD holds promise as a drying method for sea buckthorn pomace and provides valuable insights for selecting an appropriate drying method for sea buckthorn pomace. [ABSTRACT FROM AUTHOR]

This study evaluates the performance advancement of electronic noses, on-chip engineered multisensor systems, exploiting a combinatorial approach. We analyze a spectrum of metal oxide semiconductor materials produced by individual methods of liquid-phase synthesis and a combination of chemical deposition and sol–gel methods with hydrothermal treatment. These methods are demonstrated to enable obtaining a fairly wide range of nanomaterials that differ significantly in chemical composition, crystal structure, and morphological features. While synthesis routes foster diversity in material properties, microplotter printing ensures targeted precision in making on-chip arrays for evaluation of a combinatorial selectivity concept in the task of organic vapor, like alcohol homologs, acetone, and benzene, classification. The synthesized nanomaterials demonstrate a high chemiresistive response, with a limit of detection beyond ppm level. A specific combination of materials is demonstrated to be relevant when the number of sensors is low; however, such importance diminishes with an increase in the number of sensors. We show that on-chip material combinations could favor selectivity to a specific analyte, disregarding the others. Hence, modern synthesis methods and printing protocols supported by combinatorial analysis might pave the way for fabricating on-chip orthogonal multisensor systems. [ABSTRACT FROM AUTHOR]

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Simple Summary: Research on broiler feeding has increasingly focused on finding effective alternatives to antibiotic growth promoters (AGPs) due to concerns about antibiotic resistance and antibiotic residues in food products. A total EU-wide ban on AGPs was implemented in 2006. However, 70% of antibiotics are still used in animal treatment, contributing to 700,000 deaths worldwide annually due to antibiotic-resistant infections. As a result, researchers have sought natural alternatives, such as probiotics, prebiotics, enzymes, and plant-based preparations like essential oils, which have shown promise in improving broiler production traits and meat quality. The experiment in this study demonstrated that phytogenic supplements improved the European Production Efficiency Factor (EPEF). Additionally, meat from chickens on the phytogenic diet had better water-holding capacity, higher collagen content, and a favorable profile of amines, ketones, and aldehydes, indicating improved quality. These findings suggest that alternatives to AGPs can enhance broiler chicken production and meat physicochemical properties when used in appropriate doses and proportions. The primary objective of this study was to investigate the impact of a phytogenic additive (PA) in broiler chickens' diet on production, physiochemical parameters, and the profile of volatile organic compounds present in broiler chickens' meat. The experiment was conducted in a commercial chicken house, where Ross 308 broiler chickens were divided into two groups, each consisting of 65,000 broilers. One group was fed a diet supplemented with 100 ppm of PA throughout the rearing period. The primary chemical composition of the meat and its physicochemical parameters were determined. A visual assessment of breast muscles for defects and volatile organic compounds were evaluated using an electronic nose system. No statistically significant differences were shown in the production performance of the chickens; while summarizing all production parameters, a higher EPEF index of 31 points in the experimental group was highlighted. Breast muscle quality showed differences in drip loss and WHC (p ≤ 0.01) in favor of the experimental group, and a lower cutting force value (p ≤ 0.05) was found for breast muscles from the experimental group. The group also had a lower proportion of muscles with a white striping defect, and the results of volatile organic compound profiling showed the most aroma units. [ABSTRACT FROM AUTHOR]

The electronic nose aims to emulate the olfactory capabilities of osmatic animals, utilizing olfactory sensing array with different sensing characteristics to perceive odors. However, the separate precursors and preparation methods of sensing materials pose challenges in the fabrication of an olfactory sensing array. In this work, the customization of the surface crystal phase of Sr─Fe─O materials (SFO) is demonstrated through the control of annealing temperature, enabling the simple fabrication of an olfactory sensing array using a single precursor. Significantly, the SFO materials exhibit diverse proportions of surface crystal phases, showcasing varied selective characteristics toward volatile organic compounds (VOCs). The materials also demonstrate remarkable responsiveness, linearity, and response/recovery times. Furthermore, this study unraveles the intricate gas‐sensor mechanism through first principle calculations, revealing that Fe spin‐down d band center of Sr3Fe2O7, located near the Fermi level, significantly enhances the binding strength of intermediates, leading to a higher response specifically to certain VOCs. Integrating these materials into a unified device, the sensor array quantitatively and discriminatively detected different VOCs. The results indicate that SFO materials hold tremendous potential as a promising and easily manufacturable olfactory material system. [ABSTRACT FROM AUTHOR]

In this study, we experimentally evaluated a signal-processing method for the stable use of an insect antenna as an odor sensor for a robot because of its excellent sensitivity and selectivity to odors. Changes in potential in response to an odor stimulus can be measured when the electrodes are connected to both ends of an insect antenna. This is called an electroantennogram (EAG), and is a type of physiological response. Hence, we must extract only the EAG waveform using appropriate signal processing because it has a low signal-to-noise ratio. Accordingly, we applied signal processing based on an exponentially weighted moving average (EWMA), which demonstrates excellent real-time performance, to an EAG to eliminate high-frequency noise. Moreover, we experimentally investigated the sampling rate to properly measure the EAG. From the results, the EAG-driven robot with the designed signal processing demonstrated a search performance of more than 70 $ \% $ % , even in odor-source localization experiments with different types of moths and environments. [ABSTRACT FROM AUTHOR]

Changes in the flavor and taste profiles of Paddy Field Carp after deodorization with perilla juice (PJ), cooking wine (CW) and a mixture of the two (PJ-CW) were analyzed using the E-nose, E-tongue, gas chromatography–ion mobility spectrometry (GC-IMS), free amino acid analysis and taste nucleotide analysis. The E-nose and E-tongue revealed that deodorization reduced the content of sulfur-containing compounds, enhanced umami, bitterness, sourness and astringency, and decreased saltiness. PCA and OPLS-DA analysis successfully distinguished between the effects of the treatments. Free amino acids increased from 8777.67 to 11,125.98 mg/100 g and umami amino acids increased from 128.24 to 150.37 mg/100 g after PJ-CW deodorization (p < 0.05). Equivalent umami concentration (EUC) comparisons showed that PJ-CW treatment produced the greatest synergistic umami enhancement (to 3.15 g MSG equiv./100 g). GC-IMS detected 52 aroma compounds; PJ treatment produced the greatest diversity of aldehydes, including heptanal, nonanal, hexanal, 3-methylbutanal, (E)-2-heptenal and (E,E)-2,4-heptadienal. The total content of volatile flavor compounds was the highest after PJ-CW treatment, and the content of many characteristic flavor substances (3-hydroxy-2-butanone, benzaldehyde, 5-methyl-2(3H)-furanone) increased. These findings provided a theoretical basis for the further development of deodorization methods for Paddy Field Carp. [ABSTRACT FROM AUTHOR]

To further develop Liupao tea products and enhance their flavor, this study investigated the effects of different fermentation methods on the aroma quality of Liupao tea. The aroma quality of Liupao tea was comprehensively analyzed using HS-SPME in combination with GC-Q-TOF-MS, electronic nose, and sensory evaluations. Electronic nose detection showed that the aroma fingerprints of Liupao tea samples with different fermentation methods were different. Sulfides, alcohols, ketones, and methyls were the main aroma categories affecting the aroma of the four groups of Liupao tea samples. GC-Q-TOF-MS analysis revealed significant differences in the composition of aroma components among the four fermentation methods of Liupao tea (p < 0.05). Furthermore, the total amount of aroma compounds was found to be highest in the group subjected to hot fermentation combined with the inoculation of Monascus purpureus (DMl group). Based on the OPLS-DA model, candidate differential aroma components with VIP > 1 were identified, and characteristic aroma compounds were selected based on OAV > 10. The key characteristic aroma compounds shared by the four groups of samples were 1,2,3-Trimethoxybenzene with a stale aroma and nonanal with floral and fruity aromas. The best sensory evaluation results were obtained for the DMl group, and its key characteristic aroma compounds mainly included 1,2,3-Trimethoxybenzene, nonanal, and cedrol. The results of this study can guide the development of Liupao tea products and process optimization. [ABSTRACT FROM AUTHOR]

This study focused on improving the flavor quality of seasonings, and enzymatic hydrolysis of soybean protein isolate (SPI) seasoning via traditional technology may lead to undesirable flavors. Herein, we aimed to develop a new type of SPI seasoning through microbial fermentation to improve its flavor quality. The effect of Corynebacterium glutamicum fermentation on the flavoring compounds of seasonings in SPI enzymatic hydrolysate was examined. Sensory evaluation showed that the SPI seasoning had mainly aromatic and roasted flavor, and the response signals of S18 (aromatic compounds), S24 (alcohols and aldehydes), and S25 (esters and ketones) sensors of the electronic nose differed significantly. Overall, 91 volatile compounds were identified via gas chromatography–mass spectrometry. SPI seasonings contained a higher number of alcohols, ketones, aromatics, and heterocyclic compounds than traditional seasonings, which had stronger cheese, fatty, and roasted aromas. According to the relative odor activity value (ROAV) analysis, n-pentylpyrzine, 2,6-dimethylpyrazine, and tetramethylpyrazine are the key flavoring compounds (ROAV ≥ 1) of SPI seasoning, which may impart a unique roasted and meaty aroma. Therefore, the fermentation of SPI enzymatic hydrolysate with C. glutamicum may improve the flavor quality of its products, providing a new method for the development and production of new seasoning products. [ABSTRACT FROM AUTHOR]

Consumers often face a lack of information regarding the quality of apples available in supermarkets. General appearance factors, such as color, mechanical damage, or microbial attack, influence consumer decisions on whether to purchase or reject the apples. Recently, devices known as electronic noses provide an easy-to-use and non-destructive assessment of ripening stages based on Volatile Organic Compounds (VOCs) emitted by the fruit. In this study, the 'Golden Delicious' apples, stored and monitored at the ambient temperature, were analyzed in the years 2022 and 2023 to collect data from four Metal Oxide Semiconductor (MOS) sensors (MQ3, MQ135, MQ136, and MQ138). Three ripening stages (less ripe, ripe, and overripe) were identified using Principal Component Analysis (PCA) and the K-means clustering approach from various datasets based on sensor measurements in four experiments. After applying the K-Nearest Neighbors (KNN) model, the results showed successful classification of apples for specific datasets, achieving an accuracy higher than 75%. For the dataset with measurements from all experiments, an impressive accuracy of 100% was achieved on specific test sets and on the evaluation set from new, completely independent experiments. Additionally, correlation and PCA analysis showed that choosing two or three sensors can provide equally successful results. Overall, the e-nose results highlight the importance of analyzing data from several experiments performed over a longer period after the harvest of apples. There are similarities and differences in investigated VOC parameters (ethylene, esters, alcohols, and aldehydes) for less or more mature apples analyzed during autumn or spring, which can improve the determination of the ripening stage with higher predicting success for apples investigated in the spring. [ABSTRACT FROM AUTHOR]

Steamed bread is a traditional staple food in China, and it has gradually become loved by people all over the world because of its healthy production methods. With the improvement in people's living standards, the light flavor of steamed bread fermented by single yeast cannot meet people's needs. Multi-strain co-fermentation is a feasible way to improve the flavor of steamed bread. Here, the dynamic change profiles of volatile substances in steamed bread co-fermented by Saccharomyces cerevisiae SQJ20 and Wickerhamomyces anomalus GZJ2 were analyzed using the electronic nose (E-nose) and headspace solid-phase microextraction combined with gas chromatography–mass spectrometry (HS-SPME-GC-MS). The five detectors of the E-nose rapidly detected the changes in volatile substances in different dough or steamed bread with the highest response value in co-fermented dough. A total of 236 volatile substances were detected in all the samples using HS-SPME-GC-MS, and alcohols were the most variable component, especially Phenylethyl alcohol. Significantly, more alcohols and esters were upregulated in co-fermented dough, and the addition of W. anomalus GZJ2 improved the key volatile aroma compounds of steamed bread using the relative odor activity value method (ROAV), especially the aldehydes and alcohols. Moreover, these key volatile aroma compounds can be quickly distinguished using the W2S detector of the E-nose, which can be used for the rapid detection of aroma components in steamed bread. [ABSTRACT FROM AUTHOR]

Copyright of Food & Fermentation Industries is the property of Food & Fermentation Industries and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food & Fermentation Industries is the property of Food & Fermentation Industries and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Artificial olfaction, also known as an electronic nose, is a gas identification device that replicates the human olfactory organ. This system integrates sensor arrays to detect gases, data acquisition for signal processing, and data analysis for precise identification, enabling it to assess gases both qualitatively and quantitatively in complex settings. This article provides a brief overview of the research progress in electronic nose technology, which is divided into three main elements, focusing on gas-sensitive materials, electronic nose applications, and data analysis methods. Furthermore, the review explores both traditional MOS materials and the newer porous materials like MOFs for gas sensors, summarizing the applications of electronic noses across diverse fields including disease diagnosis, environmental monitoring, food safety, and agricultural production. Additionally, it covers electronic nose pattern recognition and signal drift suppression algorithms. Ultimately, the summary identifies challenges faced by current systems and offers innovative solutions for future advancements. Overall, this endeavor forges a solid foundation and establishes a conceptual framework for ongoing research in the field. [ABSTRACT FROM AUTHOR]

Cornus officinalis and Dioscorea opposita were used as raw materials, and oolong tea powder, peach powder and mango powder were used as auxiliary ingredients to make C. officinalis and D. opposita compound bagged tea, and polysaccharide content and sensory scores were used as the indexes of examination, the formulation was optimized by single factor test combined with orthogonal test, and the volatile flavor components were extracted in the tea broth by the solvent extraction ( methylene chloride extraction) method, and the volatile flavor components were analyzed by the electronic nose technique combined with the gas chromatography-mass spectrometry (GC-MS) method. The results showed that the optimal formulation of C. officinalis and D. opposita compound bagged tea was 12 g of C. officinalis powder, 30 g of D. opposita powder, 10 g of oolong tea powder, 14 g of mango powder, 14 g of peach powder, and the polysaccharide content of the product was (1. 25±0. 74) mg/3 g, the organoleptic score was (83. 83±4. 56), and the overall score was 91. 91. The tea bags maintained their integrity and did not disintegrate after brewing, the tea broth was delicate, sweet and sour, clarified and transparent without precipitation, and the smell was fresh and fragrant. There were sulfide, aromatic components, nitrogen oxides and other flavor substances in the tea broth, and a total of 53 volatile flavor components were further identified, including 40 alkanes, 4 esters, 2 alcohols, 2 aldehydes, 2 ketones, and 3 other types, of which alkanes, esters, alcohols, aldehydes, and ketones were the typical aroma components. [ABSTRACT FROM AUTHOR]

Concomitant with people beginning to understand their legal rights or entitlement to complain, complaints of offensive odors and smell pollution have increased significantly. Consequently, monitoring gases and identifying their types and causes in real time has become a critical issue in the modern world. In particular, toxic gases that may be generated at industrial sites or odors in daily life consist of hybrid gases made up of various chemicals. Understanding the types and characteristics of these mixed gases is an important issue in many areas. However, mixed gas classification is challenging because the gas sensor arrays for mixed gases must process complex nonlinear high-dimensional data. In addition, obtaining sufficient training data is expensive. To overcome these challenges, this paper proposes a novel method for mixed gas classification based on analogous image representations with multiple sensor-specific channels and a convolutional neural network (CNN) classifier. The proposed method maps a gas sensor array into a multichannel image with data augmentation, and then utilizes a CNN for feature extraction from such images. The proposed method was validated using public mixture gas data from the UCI machine learning repository and real laboratory experiments. The experimental results indicate that it outperforms the existing classification approaches in terms of the balanced accuracy and weighted F1 scores. Additionally, we evaluated the performance of the proposed method in various experimental settings in terms of data representation, data augmentation, and parameter initialization, so that practitioners can easily apply it to artificial olfactory systems. [ABSTRACT FROM AUTHOR]

BACKGROUND: Roasting is an important process in the formation of coffee flavor characteristics, which determines the quality of coffee and consumer acceptance. However, the influence of roasting degree on the flavor characteristics of cold brew coffee has not been fully described. RESULTS: In the present study, the flavor characteristics of cold brew coffee with different roasting degrees were compared in detail by using chromatographic and electronic sensory approaches, and the flavor changes induced by freeze‐drying were investigated. Pyrazine and heterocyclic compounds were the main aroma compounds in coffee, and gradually dominated with the increase of roasting. Pyridine was consistently present in cold brew coffees of different roasting degrees and showed significant gradient of quantity accumulation. Aroma compounds such as pyrazine, linalool and furfuryl acetate were the main contributors to coffee roasting, floral and fruity flavor. Freeze‐drying preserved the fruity and floral aromas of medium‐roasted cold brew coffee, whereas reducing the bitterness, astringency and acidity properties that are off‐putting to consumers. CONCLUSION: The higher consumer acceptance and enjoyment in medium roast cold brew coffee may be related to its stronger floral and fruity aroma. The aroma profile qualities of freeze‐drying processed medium roasted cold brewed coffee were more dominant and more suitable for freeze‐drying processing than medium dark roasting. Application of freeze‐drying for cold brew coffee will promote the convenience of drinking. The present study provides valuable technical guidance in improving the flavor and quality of cold brew coffee, and also promotes its commercialization process. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

To characterize the spoilage of tilapia under super-chilled storage, the bacterial profile and odor and volatile compounds were analyzed. Results showed that the shelf life and bacterial profile of tilapia from different sources varied remarkably, with Pseudomonas being the most dominant organism in tilapia under super-chilled storage (−1.5°C). The correlation analysis showed that the volatile compounds from the spoiled samples were closely related to the bacterial profile. Therefore, no volatile compounds or the response of the electronic nose significantly correlated with sensory spoilage although some of them correlated with that of some specific samples. On the other hand, the total volatile basic nitrogen (TVB-N) was significantly correlated with the sensory spoilage of all samples. In conclusion, under super-chilled storage, the volatile compounds in tilapia, except TVB-N, are sample dependent due to the variation of bacterial profile and therefore cannot be used as a spoilage indicator. [ABSTRACT FROM AUTHOR]

Mycotoxins are toxic secondary metabolites produced by certain molds and fungi that contaminate various food commodities, posing serious adverse effects on humans and animals. Aflatoxin, ochratoxin, trichothecene, fumonisin, zearalenone, patulin, and citrinin are some of the major mycotoxins affecting food and feed. The scientific community has focused on regulating food and feed materials due to their potential risks. Conventional techniques for mycotoxin detection have certain limitations in terms of sensitivity, specificity, and speed. In recent years, nanotechnology has emerged as a promising approach to revolutionize mycotoxin detection. This review provides an overview of nanotechnology‐based detection methods for mycotoxins in food and feed, discussing the basic aspects of mycotoxins, their health hazards, and conventional methods. It also explores various nanosensors and nanodevices developed to improve the sensitivity, selectivity, and speed of mycotoxin detection, thereby enhancing food safety and security. [ABSTRACT FROM AUTHOR]

To improve the classification and regression performance of the total volatile basic nitrogen (TVB‐N) and acid value (AV) of different freshness fish meal samples detected by a metal‐oxide semiconductor electronic nose (MOS e‐nose), 402 original features, 62 manually extracted features, manually extracted and selected features by the RFRFE method, and the features extracted by the long short‐term memory (LSTM) network were used as inputs to identify the freshness. The classification performance of the freshness grades and the estimation performance of the TVB‐N and AV values of fish meal with different freshness were compared. According to the sensor response curve, preprocessing and feature extraction steps were first applied to the original data. Then, five classification algorithms and four regression algorithms were used for modeling. The results showed that a total of 30 features were extracted using the LSTM network, and the number of extracted features was significantly reduced. In the classification, the highest accuracy rate of 95.4% was obtained using the support vector machine method. In the regression, the least squares support vector regression method obtained the best root mean square error (RMSE). The coefficient of determination (R2), RMSE, and relative standard deviation (RSD) between the predicted value of TVBN and the actual value were 0.963, 11.01, and 7.9%, respectively. The R2, RMSE, and RSD between the predicted value of AV and the actual value were 0.972, 0.170, and 6.05%, respectively. The LSTM feature extraction method provided a new method and reference for feature extraction using an E‐nose to identify other animal‐derived material samples. [ABSTRACT FROM AUTHOR]

The effect of fuel (hydrogen vs. butane) on the formation of volatile organic compounds (VOCs) and polycyclic aromatic hydrocarbons (PAHs) was evaluated for grilled horse meat (very low-fat and low-fat) cooking vertically. Gas chromatography-mass spectrometry was used to analyze PAHs and VOCs. An electronic nose was used to evaluate the odor profile. Total high-molecular-weight PAHs ranged from 19.59 to 28.65 µg/kg with butane and from 1.83 to 1.61 µg/kg with hydrogen. Conversely, total low-molecular-weight PAHs went from 184.41 to 286.03 µg/kg with butane and from 36.88 to 41.63 µg/kg with hydrogen. Aldehydes and alkanes were the predominant family in a total of 59 VOCs. Hydrogen gas-grilling reduced significantly (p < 0.05) the generation of VOCs related to lipid oxidation. The odor profile was not modified significantly despite the change of PAHs and VOCs. The findings indicate that hydrogen is a viable alternative to butane for grilling horse meat. Hydrogen gas-grilling may be regarded as a safe cooking procedure of meat from a PAH contamination point and perhaps sustainable environmentally compared to a conventional technique. The present study provides the basis for the use of hydrogen gas in grilled meat. [ABSTRACT FROM AUTHOR]

The growing demand for alternative sources of non-animal proteins has stimulated research in this area. Mushrooms show potential in the innovation of plant-based food products. In this study, the aim was to develop prototype fish fillets analogues from Pleurotus ostreatus mushrooms applying enzymatic treatment (β-glucanase and transglutaminase-TG). A Plackett–Burman 20 experimental design was used to optimize forty variables. Oat flour (OF) exerted a positive effect on the hardness and gumminess texture parameters but a negative effect on cohesiveness and resilience. Soy protein isolate (SPI) exhibited a positive effect on elasticity, gumminess and chewiness, while acacia gum had a negative effect on elasticity, cohesiveness and resilience. After sensory analysis the assay with 1% cassava starch, 5% OF, 5% SPI, 0.1% transglutaminase (240 min/5 °C), 1% coconut oil, 1% soybean oil, 0.2% sodium tripolyphosphate, 0.6% β-glucanase (80 °C/10 min) and without β-glucanase inactivation was found to exhibit greater similarity to fish fillet. The classes hydrocarbons, alcohols and aldehydes are the predominant ones in aromatic profile analysis by chromatography and electronic nose. It is concluded that a mushroom-based analogue of fish fillet can be prepared using enzymatic treatment with TG. [ABSTRACT FROM AUTHOR]

Copyright of Science & Technology of Food Industry is the property of Science & Technology of Food Industry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Science & Technology of Food Industry is the property of Science & Technology of Food Industry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Science & Technology of Food Industry is the property of Science & Technology of Food Industry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Volatile organic compounds (VOCs) are secondary metabolites emitted by all living carbon-based organisms. These VOCs are of great importance in the agricultural sector due to their use as biofungicides and biopesticides. In addition, they can also be used as indicators of microbial contamination. The latter has rarely been studied; however, such a role is very relevant because it allows the timely application of corrective treatments that avoid food waste, the development of toxins dangerous to humans, and the design of biosensors. Gas chromatography–mass spectrometry (GC-MS), electronic nose (e-nose), and proton transfer reaction mass spectrometry (PTR-MS) are some of the techniques used to detect VOCs in fruits and vegetables contaminated by microorganisms. Therefore, the objective of this work is to deepen our knowledge of VOCs emitted by microorganisms in terms of their use as an indicator of microbial contamination of fresh agricultural products, as well as the analytical techniques used for their detection. [ABSTRACT FROM AUTHOR]

Gardenia fruit is a popular functional food and raw material for natural pigments. It comes from a wide range of sources, and different products sharing the same name are very common. Volatile organic compounds (VOCs) are important factors that affect the flavor and quality of gardenia fruit. This study used the Heracles NEO ultra-fast gas phase electronic nose with advanced odor analysis performance and high sensitivity to analyze six batches of gardenia fruit from different sources. This study analyzed the VOCs to find a way to quickly identify gardenia fruit. The results show that this method can accurately distinguish the odor characteristics of various gardenia fruit samples. The VOCs in gardenia fruit are mainly organic acid esters, ketones, and aldehyde compounds. By combining principal component analysis (PCA) and discriminant factor analysis (DFA), this study found that the hexanal content varied the most in different gardenia fruit samples. The VOCs allowed for the fruit samples to be grouped into two main categories. One fruit sample was quite different from the fruits of other origins. The results provide theoretical support for feasibility of rapid identification and quality control of gardenia fruit and related products in the future. [ABSTRACT FROM AUTHOR]

In the Internet of Things (IoT) environment, verifying the authenticity of beverages is an important issue. Baijiu, a unique Chinese distilled liquor, has gained popularity among people due to its distinctive flavor. In recent years, there has been increasing concern about the adulteration of baijiu. Many studies in this field have attempted to combine chemometrics, electronic nose, Raman spectroscopy, and other detection technologies with machine learning for baijiu detection. However, no research has yet applied the mature detection technology of fluorescence hyperspectral technology to this field. Additionally, existing studies have mainly focused on branded baijiu, without addressing the problem of adulteration in bulk baijiu, which remains a long-standing issue. In this study, a combination of fluorescence hyperspectral and machine learning was used for rapid and nondestructive adulteration detection of bulk liquor in Chengdu. The fluorescence hyperspectral data of three types of samples, namely, original liquor, adulterated liquor with water, and adulterated liquor with industrial alcohol, were obtained, and the raw data were preprocessed using Savitzky–Golay (SG), baseline correction (BL), multivariate scatter correction (MSC), and the combination of Savitzky–Golay and baseline correction (SG-BL). Finally, PCA and MDS are also used to extract spectral data characteristics, respectively. For model selection, three models were chosen: back-propagation artificial neural network (BP-ANN), support vector machine (SVM), and one-dimensional convolutional neural network (1D-CNN). For model evaluation, we choose accuracy, recall, precision, F1-score, memory occupied, and time consumed by the model to evaluate. The experiments show that the combination of fluorescence hyperspectral technology and machine learning can provide a new method, MSC-PCA-SVM, for bulk liquor detection, with a final classification accuracy, recall, precision, and F1-score all reaching 100%, The effectiveness and application potential of this method in the IoT environment have been demonstrated. The results of this study can not only be applied to liquor detection but also have the value of reference for the adulthood and detection of the entire food industry. It is of great significance to standardize the market and protect consumer rights. [ABSTRACT FROM AUTHOR]

Although there are significant advancements in device‐level artificial tactile and visual perception systems based on in‐sensor computing paradigms, the development of hardware‐implemented neuromorphic olfactory system is still in its early stages. One of the primary challenges in this field is that most of the gas sensors lack the capability to fuse the sensing and computing functions in a single sensor. Through surface passivation and interface engineering, this work introduces a device‐level artificial olfactory system utilizing array of PCBM‐MAPbI3 heterostructure transistors. Noteworthly, the formation of metastable intermediate phase NH3PbI3•MA can occur at room temperature and can be used to store gas sensory information. Both gas pulse and electrical pulse can dynamically modulate the amount of this intermediate phase, and then change the channel conductance (weight), realizing the fusion of the sensing and synaptic functions in single device. Based on these excellent properties, the spatiotemporal information of gas diffusion can be encoded and processed simultaneously. As a result, an in‐sensor olfactory perception system is successfully demonstrated based on 5 × 5 PCBM‐MAPbI3 heterostructure transistor array, which can be used for detecting the distance and direction of the hazardous gas. This work paves the way for future application of real‐time and data‐intensive machine‐olfactory system. [ABSTRACT FROM AUTHOR]

Supramolecules are considered as promising materials for volatile organic compounds (VOCs) sensing applications. The proper understanding of the sorption process taking place in host-guest interactions is critical in improving the pattern recognition of supramolecules-based sensing arrays. Here, we report a novel approach to investigate the dynamic host-guest recognition process by employing a bulk acoustic wave (BAW) resonator capable of producing multiple oscillation amplitudes and simultaneously recording multiple responses to VOCs. Self-assembled monolayers (SAMs) of β-cyclodextrin (β-CD) were modified on four BAW sensors to demonstrate the gas-surface interactions regarding oscillation amplitude and SAM length. Based on the method, a virtual sensor array (VSA) type electronic nose (e-nose) can be realized by pattern recognition of multiple responses at different oscillation amplitudes of a single sensor. VOCs analysis was realized respectively by using principal component analysis (PCA) for individual VOC identification and linear discriminant analysis (LDA) for VOCs mixtures classification. [ABSTRACT FROM AUTHOR]

Currently, the market for wearable devices is expanding, with a growing trend towards the use of these devices for continuous-monitoring applications. Among these, real-time posture monitoring and assessment stands out as a crucial application given the rising prevalence of conditions like forward head posture (FHP). This paper proposes a wearable device that combines the acquisition of electromyographic signals from the cervical region with inertial data from inertial measurement units (IMUs) to assess the occurrence of FHP. To improve electronics integration and wearability, e-textiles are explored for the development of surface electrodes and conductive tracks that connect the different electronic modules. Tensile strength and abrasion tests of 22 samples consisting of textile electrodes and conductive tracks produced with three fiber types (two from Shieldex and one from Imbut) were conducted. Imbut's Elitex fiber outperformed Shieldex's fibers in both tests. The developed surface electromyography (sEMG) acquisition hardware and textile electrodes were also tested and benchmarked against an electromyography (EMG) gold standard in dynamic and isometric conditions, with results showing slightly better root mean square error (RMSE) values (for 4 × 2 textile electrodes (10.02%) in comparison to commercial Ag/AgCl electrodes (11.11%). The posture monitoring module was also validated in terms of joint angle estimation and presented an overall error of 4.77° for a controlled angular velocity of 40°/s as benchmarked against a UR10 robotic arm. [ABSTRACT FROM AUTHOR]

Reconstituted tobacco (RT) is a product made by reprocessing tobacco waste, experiencing a growing demand for heat‐not‐burn products. The purpose of this study is to analyze the main flavor ingredients in RT aerosol, as well as the transfer behavior of key flavor substances from substrates to aerosol and the concentrations of these compounds in the substrate after heating. First, we demonstrated that the odor of four RT aerosol samples could be distinguished using an electronic nose. Through non‐targeted analysis, 93 volatile compounds were detected by gas chromatography‐mass spectrometry, and 286 non/semi‐volatile compounds were identified by ultra‐high‐performance liquid electrophoresis chromatography‐mass spectrometry in aerosol. Furthermore, we found that the formation of RT aerosol involves primarily evaporation and distillation, however, the total content delivered from unheated RT samples to aerosol remains relatively low due to compound volatility and cigarette filtration. Thermal reactions during heating indicated the pyrolysis of chlorogenic acid to generate catechol and resorcinol, while Maillard reactions involving glucose and proline produced 2,3‐dihydro‐3,5‐dihydroxy‐6‐methyl‐4h‐pyran‐4‐one. The study highlighted that heating RT at approximately 300°C could mitigate the production of harmful substances while still providing a familiar sensory experience with combusted tobacco. [ABSTRACT FROM AUTHOR]

Copyright of Science & Technology of Food Industry is the property of Science & Technology of Food Industry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Science & Technology of Food Industry is the property of Science & Technology of Food Industry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Many odors, like perfumes, are complex mixtures of chiral and achiral molecules where the cost‐efficient (enantio−)selective sensing represents a major technical challenge. Here, we present a colorimetric sensor array of surface‐mounted metal‐organic‐framework (SURMOF) films in Fabry‐Pérot (FP) cavities. The optical properties of the FP‐SURMOF films with different chiral and achiral structures are affected by the (enantio−)selective adsorption of the analytes in the SURMOF pores, resulting in different responses to the analyte molecules. The read‐out of the sensor array is performed by the digital camera of a common smartphone, where the RGB values are determined. By analyzing the sensor array data with simple machine learning algorithms, the analytes are discriminated. After demonstrating the enantioselective response for a pair of pure chiral odor molecules, we apply the sensor array to detect and discriminate a large number (16) of common commercial perfumes and eau de toilettes. While our untrained human nose is not able to discriminate all perfumes, the presented colorimetric sensor array can classify all perfumes with great classification accuracy. Moreover, the sensor array was used to identify unlabeled samples correctly. We foresee such an FP‐chiral‐SURMOF‐based sensor array as a powerful approach toward inexpensive selective odors sensing applications. [ABSTRACT FROM AUTHOR]

The quality detection of alfalfa hay is crucial for the development of animal husbandry. In this study, a method for quality detection of alfalfa hay based on the fusion of multisource information including near-infrared spectroscopy, image processing techniques, and electronic nose is proposed. After SG convolution smoothing, feature wavelengths were extracted using Competitive Adaptive Re-weighting Scheme and Successive Projections Algorithm from the spectral data. The image data were denoised using adaptive wavelet thresholding, and color and texture features were extracted using color histograms and random forest algorithms, respectively. Electronic nose data using principal component analysis was used for data dimensionality reduction. Support Vector Machine, Extreme Learning Machine, and Multi-Layer Perceptron were employed to establish quality detection models of alfalfa hay based on spectroscopy, image, gas information, and their combination, respectively. Experimental results demonstrate that the fusion of near-infrared spectroscopy, image data, and gas information effectively enhances the classification accuracy of the model. The accuracy of the test set reaches 100%, with root mean square error and determination coefficient values of 0.1728 and 0.9239, respectively, surpassing prediction models established solely on individual information. This study provides new insights into alfalfa hay quality detection. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In the electronic nose (E-nose) systems, gas type recognition and accurate concentration prediction are some of the most challenging issues. This study introduced an innovative pattern recognition method of time–frequency attention convolutional neural network (TFA-CNN). A time–frequency attention block was designed in the network, aiming to excavate and effectively integrate the temporal and frequency domain information in the E-nose signals to enhance the performance of gas classification and concentration prediction tasks. Additionally, a novel data augmentation strategy was developed, manipulating the feature channels and time dimensions to reduce the interference of sensor drift and redundant information, thereby enhancing the model's robustness and adaptability. Utilizing two types of metal-oxide-semiconductor gas sensors, this research conducted qualitative and quantitative analysis on five target gases. The evaluation results showed that the classification accuracy could reach 100%, and the coefficient of the determination (R2) score of the regression task was up to 0.99. The Pearson correlation coefficient (r) was 0.99, and the mean absolute error (MAE) was 1.54 ppm. The experimental test results were almost consistent with the system predictions, and the MAE was 1.39 ppm. This study provides a method of network learning that combines time–frequency domain information, exhibiting high performance in gas classification and concentration prediction within the E-nose system. [ABSTRACT FROM AUTHOR]

Summary: Ensuring the freshness of fish is essential to guaranteeing safer products for consumers. A classification model was developed using the PEN3 electronic nose to predict fish freshness with its storage day. Frigate tuna (Auxis thazard) was used for odour sampling along with the total volatile base nitrogen (TVB‐N), at 4 °C for 14 days every other day. Random forest and support vector machine (SVM) were performed to develop freshness classification models based on PEN3 data and 100% and 99.8% accuracies were obtained, respectively, in distinguishing the eight storage day classes. The PEN3 sensors including W2S, W1S, W1W, W3S, and W6S were identified as key sensors for fish freshness. TVB‐N analysis advances the freshness prediction of e‐nose and three freshness levels were identified as 'Fresh', applicable from the 0th to the 6th day; 'Moderately fresh', lasting from the 7th to the 9th day; and 'Unsuitable for consumption', applicable from the 10th day onwards. [ABSTRACT FROM AUTHOR]