Search Results (26)

Codonopsis Radix (CR), an important species of “medicine-food homology”, exhibits broad market prospects, underscoring the urgency and importance of research on its quality. This study specifically measured the alcohol-soluble extract and polysaccharide extract of 77 samples from mainstream producing areas of CR, which serve as key fractions for assessing its quality. Additionally, to gain a comprehensive understanding of the sensory characteristics of samples, the study employed electronic tongue technology to obtain sweetness values, used a colorimeter to determine yellowness values, and captured odor fingerprint information through an electronic nose (E-nose). In the data analysis phase, the study compared the accuracy of various regression prediction models, including Multiple Linear Regression (MLR), Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN). After comprehensive evaluation, an SVM algorithm was selected due to its superior prediction performance. To further enhance prediction accuracy, the study utilized a Particle Swarm Optimization (PSO) algorithm to optimize the SVM, resulting in a significant improvement in the prediction accuracy of sweetness values. In conclusion, regression prediction models for chemical composition and sensory information of CR based on an E-nose were established. It represents an enhancement of traditional morphological identification methods for Chinese medicinal herbs and provides new ideas and means for quality evaluation of CR. Furthermore, it offers a reference for quality evaluation of other similar Chinese medicinal herbs. Full article

The anticipated diagnosis of cancers and other fatal diseases from the simple analysis of the volatiles emitted by the body (volatolome) is getting closer and closer from becoming reality. The promises of vapour sensor arrays are to provide a rapid, reliable, non-invasive and ready-to-use method for clinical applications by making an olfactive fingerprint characteristic of people’s health state, to increase their chance of early recovery. However, the different steps of this complex and ambitious process are still paved with difficulties needing innovative answers. The purpose of this review is to provide a statement of the blocs composing the diagnostic chain to identify the improvements still needed. Nanocomposite chemo-resistive transducers have unique prospects to enhance both the selectivity and sensitivity to volatile biomarkers. The variety of their formulations offers multiple possibilities to chemical functionalization and conductive architectures that should provide solutions to discriminations and stability issues. A focus will be made on the protocols for the collection of organic volatile compounds (VOC) from the body, the choice of vapour sensors assembled into an array (e-nose), in particular, chemo-resistive vapour sensors, their principle, fabrication and characteristics, and the way to extract pertinent features and analyse them with suitable algorithms that are able to find and produce a health diagnosis. Full article

The efficient, economical, and sustainable production of biodiesel from waste cooking oils (WCOs) depends on the availability of simple, rapid, and low-cost methods to test the quality of potential feedstocks. The aim of this study was to establish the applicability of stochastic modeling of e-nose profiles in the evaluation of recycled WCO characteristics. Olfactory profiles of 10 WCOs were determined using a Sensigent Cyranose^® 320 chemical vapor-sensing device with a 32 sensor-array, and a stepwise multiple linear regression (MLR) analysis was performed to select stochastic parameters (explanatory variables) for inclusion in the final predictive models of the physicochemical properties of the WCOs. The most important model parameters for the characterization of WCOs were those relating to the time of inception of the e-nose signal “plateau” and to the concentration of volatile organic compounds (VOCs) in the sensor region. A comparison of acid values, peroxide values, water contents, and kinematic viscosities predicted by the MLR models with those determined by conventional laboratory methods revealed that goodness of fit and predictor accuracy varied from good to excellent, with all metric values >90%. Combining e-nose profiling with stochastic modeling was successful in predicting the physicochemical characteristics of WCOs and could be used to select suitable raw materials for efficient and sustainable biodiesel production. Full article

The research investigates the influence of different lighting conditions and soil treatments, in particular the application of food polymers separately and in combination with spores of Trichoderma consortium, on the growth and development of herbs—Thymus vulgaris and Thymus serpyllum. The metabolic analysis focuses on detecting changes in the levels of biologically active compounds such as chlorophyll a and b, anthocyanins, carotenoids, phenolic compounds (including flavonoids), terpenoids, and volatile organic compounds with potential health-promoting properties. By investigating these factors, the study aims to provide insights into how environmental conditions affect the growth and chemical composition of selected plants and to shed light on potential strategies for optimising the cultivation of these herbs for the improved quality and production of bioactive compounds. Under the influence of additional lighting, the growth of T. vulgaris and T. serpyllum seedlings was greatly accelerated, resulting in an increase in shoot biomass and length, and in the case of T. vulgaris, an increase in carotenoid and anthocyanin contents. Regarding secondary metabolites, the most pronounced changes were observed in total antioxidant capacity and flavonoid content, which increased significantly under the influence of additional lighting. The simultaneous or separate application of Trichoderma and food polymers resulted in an increase in flavonoid content in the leaves of both Thymus species. The increase in terpenoid content under supplemental light appears to be related to the presence of Trichoderma spores as well as food polymers added to the soil. However, the nature of these changes depends on the thyme species. Volatile compounds were analysed using an electronic nose (E-nose). Eight volatile compounds (VOCs) were tentatively identified in the vapours of T. vulgaris and T. serpyllum: α-pinene, myrcene, α-terpinene, γ-terpinene; 1,8-cineole (eucalyptol), thymol, carvacrol, and eugenol. Tendencies to increase the percentage of thymol and γ-terpinene under supplemental lighting were observed. The results also demonstrate a positive effect of food polymers and, to a lesser extent, Trichoderma fungi on the synthesis of VOCs with health-promoting properties. The effect of Trichoderma and food polymers on individual VOCs was positive in some cases for thymol and γ-terpinene. Full article

Sepsis is a severe condition and the major cause of mortality in the ICU. Prompt intervention decreases mortality, and non-invasive systems for early diagnosis in ICU patients are necessary. This work presents a customized e-Nose system based on non-selective chemical sensors for exhaled breath analysis. The system comprises two units: a sampling device able to collect exhaled breath from mechanically ventilated patients and an e-Nose in which the gas is analyzed. Preliminary results from a porcine model support the possibility of discriminating between healthy and sepsis subjects. Full article

The flower buds of three Panax species (PGF: P. ginseng; PQF: P. quinquefolius; PNF: P. notoginseng) widely consumed as health tea are easily confused in market circulation. We aimed to develop a green, fast, and easy analysis strategy to distinguish PGF, PQF, and PNF. In this work, fast gas chromatography electronic nose (fast GC e-nose), headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), and headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) were utilized to comprehensively analyze the volatile organic components (VOCs) of three flowers. Meanwhile, a principal component analysis (PCA) and heatmap were applied to distinguish the VOCs identified in PGF, PQF, and PNF. A random forest (RF) analysis was used to screen key factors affecting the discrimination. As a result, 39, 68, and 78 VOCs were identified in three flowers using fast GC e-nose, HS-GC-IMS, and HS-SPME-GC-MS. Nine VOCs were selected as potential chemical markers based on a model of RF for distinguishing these three species. Conclusively, a complete VOC analysis strategy was created to provide a methodological reference for the rapid, simple, and environmentally friendly detection and identification of food products (tea, oil, honey, etc.) and herbs with flavor characteristics and to provide a basis for further specification of their quality and base sources. Full article

Fresh fish is a perishable food in which chemical (namely oxidation) and microbiological degradation result in undesirable odor. Non-processed fish (i.e., raw fish) is increasingly commercialized in packaging systems which are convenient for its retailing and/or which can promote an extension of its shelf-life. Compared to fish sent to its retail unpackaged, fish packaging results in a modification of the gaseous composition of the atmosphere surrounding it. These modifications of atmosphere composition may affect both chemical and microbiological degradation pathways of fish constituents and thereby the volatile organic compounds produced. In addition to monitoring Total Volatile Basic Nitrogen (TVB-N), which is a common indicator to estimate non-processed fish freshness, analytical techniques such as gas chromatography coupled to mass spectrometry or techniques referred to as “electronic nose” allow either the identification of the entire set of these volatile compounds (the volatilome) and/or to selectively monitor some of them, respectively. Interestingly, monitoring these volatile organic compounds along fish storage might allow the identification of early-stage markers of fish alteration. In this context, to provide relevant information for the identification of volatile markers of non-processed packaged fish quality evolution during its storage, the following items have been successively reviewed: (1) inner atmosphere gaseous composition and evolution as a function of fish packaging systems; (2) fish constituents degradation pathways and analytical methods to monitor fish degradation with a focus on volatilome analysis; and (3) the effect of different factors affecting fish preservation (temperature, inner atmosphere composition, application of hurdle technology) on volatilome composition. Full article

Relative humidity (RH) is a common interferent in chemical gas sensors, influencing their baselines and sensitivity, which can limit the performance of e-nose systems. Tuning the composition of the sensing materials is a possible strategy to control the impact of RH in gas sensors. Hybrid gel materials used as gas sensors contain self-assembled droplets of ionic liquid and liquid crystal molecules encapsulated in a polymeric matrix. In this work, we assessed the effect of the matrix hydrophobic properties in the performance of hybrid gel materials for VOC sensing in humid conditions (50% RH). We used two different polymers, the hydrophobic PDMS and the hydrophilic bovine gelatin, as polymeric matrices in hybrid gel materials containing imidazolium-based ionic liquids, [BMIM][Cl] and [BMIM][DCA], and the thermotropic liquid crystal 5CB. Better accuracy of VOC prediction is obtained for the hybrid gels composed of a PDMS matrix combined with the [BMIM][Cl] ionic liquid, and the use of this hydrophobic matrix reduces the effect of humidity on the sensing performance when compared to the gelatin counterpart. VOCs interact with all the moieties of the hybrid gel multicomponent system; thus, VOC correct classification depends not only on the polymeric matrix used, but also on the IL selected, which seems to be key to achieve VOCs discrimination at 50% RH. Thus, hybrid gels’ tunable formulation offers the potential for designing complementary sensors for e-nose systems operable under different RH conditions. Full article

The aroma of wine is traditionally analyzed by sensory methods or by using gas chromatography; both analytical methodologies are slow and expensive and do not allow continuous monitoring. For this reason, interest in rapid methods has increased in recent times. Electronic noses (e-noses) stand out for their high sensitivity, speed, low cost, and little or no sample preparation. They present, however, low selectivity, which requires advance analytical methods to distinguish compounds. Here, we present a low-cost e-nose device for the analysis and identification of distinct varieties of wine. Chemical analysis data are compared to e-nose data through a principal component analysis (PCA) and a k-means clustering algorithm to establish relationships between varieties of wines and the e-nose classification capability. The results show that e-nose technology found significant differences between the analyzed samples, and furthermore, classifying the samples in accordance with the chemical analysis classification. The maximal accuracy obtained was 100% using the k-means algorithm for binary classification with N = 21 samples. Thus the potential of e-nose technology was shown in the wine industry for the identification and classification of wine varieties or quality. Full article

Magnolia officinalis Rehd. et Wils. and Magnolia officinalis Rehd. et Wils. var. biloba Rehd. et Wils, as the legal botanical origins of Magnoliae Officinalis Cortex, are almost impossible to distinguish according to their appearance traits with respect to medicinal bark. The application of AFLP molecular markers for differentiating the two origins has not yet been successful. In this study, a combination of e-nose measurements, e-tongue measurements, and chemical analyses coupled with multiple-source data fusion was used to differentiate the two origins. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were applied to compare the discrimination results. It was shown that the e-nose system presented a good discriminant ability with a low classification error for both LDA and QDA compared with e-tongue measurements and chemical analyses. In addition, the discriminating capacity of LDA for low-level fusion with original data, similar to a combined system, was superior or equal to that acquired individually with the three approaches. For mid-level fusion, the combination of different principals extracted by PCA and variables obtained on the basis of PLS-VIP exhibited an analogous discrimination ability for LDA (classification error 0.0%) and was significantly superior to QDA (classification error 1.67–3.33%). As a result, the combined e-nose, e-tongue, and chemical analysis approach proved to be a powerful tool for differentiating the two origins of Magnoliae Officinalis Cortex. Full article

We investigated functionalized graphene materials to create highly sensitive sensors for volatile organic compounds (VOCs) such as formaldehyde, methanol, ethanol, acetone, and isopropanol. First, we prepared VOC-sensitive films consisting of mechanically exfoliated graphene (eG) and chemical graphene oxide (GO), which have different concentrations of structural defects. We deposited the films on silver interdigitated electrodes on Kapton substrate and submitted them to thermal treatment. Next, we measured the sensitive properties of the resulting sensors towards specific VOCs by impedance spectroscopy. We obtained the eG- and GO-based electronic nose composed of two eG films- and four GO film-based sensors with variable sensitivity to individual VOCs. The smallest relative change in impedance was 5% for the sensor based on eG film annealed at 180 °C toward 10 ppm formaldehyde, whereas the highest relative change was 257% for the sensor based on two-layers deposited GO film annealed at 200 °C toward 80 ppm ethanol. At 10 ppm VOC, the GO film-based sensors were sensitive enough to distinguish between individual VOCs, which implied excellent selectivity, as confirmed by Principle Component Analysis (PCA). According to a PCA-Support Vector Machine-based signal processing method, the electronic nose provided identification accuracy of 100% for individual VOCs. The proposed electronic nose can be used to detect multiple VOCs selectively because each sensor is sensitive to VOCs and has significant cross-selectivity to others. Full article

Environmental chemicals and contaminants coming from multiple external sources enter the human body, determining a potential risk for human health. Human biomonitoring (HBM), measuring the concentrations of biomarkers in human specimens, has become an emerging approach for assessing population-wide exposure to hazardous chemicals and health risk through large-scale studies in many countries. However, systematic mapping of HBM studies, including their characteristics, targeted hazardous pollutants, analytical techniques, and sample population (general population and occupationally exposed workers), has not been done so far. We conducted a systematic review of the literature related to airborne hazardous pollutants in biofluids to answer the following questions: Which main chemicals have been included in the literature, which bodily fluids have been used, and what are the main findings? Following PRISMA protocol, we summarized the publications published up to 4 February 2021 of studies based on two methods: gas-chromatography/mass spectrometry (GC/MS) and electronic noses (e-noses). We screened 2606 records and 117 publications were included in the analysis, the most based on GC/MS analysis. The selected HBM studies include measurements of biomarkers in different bodily fluids, such as blood, urine, breast milk, and human semen as well as exhaled air. The papers cover numerous airborne hazardous pollutants that we grouped in chemical classes; a lot of hazardous and noxious compounds, mainly persistent organic pollutants (POPs) and volatile organic compounds (VOCs), have been detected in biological fluids at alarming levels. The scenario that emerged from this survey demonstrates the importance of HBM in human exposure to hazardous pollutants and the need to use it as valid tool in health surveillance. This systematic review represents a starting point for researchers who focus on the world of pollutant biomonitoring in the human body and gives them important insights into how to improve the methods based on GC/MS. Moreover, it makes a first overview of the use of gas sensor array and e-noses in HBM studies. Full article

A hairpin DNA (hpDNA) piezoelectric gas sensors array with heptamer loops as sensing elements was designed, realized, and challenged with pure volatile organic compounds VOCs and real samples (beer). The virtual binding versus five chemical classes (alcohols, aldehydes, esters, hydrocarbons, and ketones) of the entire combinatorial library of heptamer loops (16,384 elements) was studied by molecular modelling. Six heptamer loops, having the largest variance in binding the chemical classes, were selected to build the array. The six gas sensors were realized by immobilizing onto gold nanoparticles (AuNPs) via a thiol spacer the hpDNA constituted by the heptamer loops and the same double helix stem of four base pairs (GAAG at 5′ and CTTC at 3′ end). The HpDNA-AuNP was used to modify the surface of 20 MHz quartz crystal microbalances (QCMs). The realized E-nose was able to clearly discriminate among 15 pure VOCs of different chemical classes, as demonstrated by hierarchical cluster analysis. The analysis of real beer samples during fermentation was also carried out. In such a challenging matrix consisting of 23 different VOCs, the hpDNA E-nose with heptamer loops was able to discriminate among different fermentation times with high success rate. Class assignment using the Bayes theorem gave an excellent 98% correct beer samples classification in cross-validation. Full article

An electronic nose (Enose) relies on the use of an array of partially selective chemical gas sensors for identification of various chemical compounds, including volatile organic compounds in gas mixtures. They have been proposed as a portable low-cost technology to analyse complex odours in the food industry and for environmental monitoring. Recent advances in nanofabrication, sensor and microcircuitry design, neural networks, and system integration have considerably improved the efficacy of Enose devices. Here, we highlight different types of semiconducting metal oxides as well as their sensing mechanism and integration into Enose systems, including different pattern recognition techniques employed for data analysis. We offer a critical perspective of state-of-the-art commercial and custom-made Enoses, identifying current challenges for the broader uptake and use of Enose systems in a variety of applications. Full article

Current available methods for the clinical diagnosis of urinary tract infection (UTI) rely on a urine dipstick test or culturing of pathogens. The dipstick test is rapid (available in 1–2 min), but has a low positive predictive value, while culturing is time-consuming and delays diagnosis (24–72 h between sample collection and pathogen identification). Due to this delay, broad-spectrum antibiotics are often prescribed immediately. The over-prescription of antibiotics should be limited, in order to prevent the development of antimicrobial resistance. As a result, there is a growing need for alternative diagnostic tools. This paper reviews applications of chemical-analysis instruments, such as gas chromatography–mass spectrometry (GC-MS), selected ion flow tube mass spectrometry (SIFT-MS), ion mobility spectrometry (IMS), field asymmetric ion mobility spectrometry (FAIMS) and electronic noses (eNoses) used for the diagnosis of UTI. These methods analyse volatile organic compounds (VOCs) that emanate from the headspace of collected urine samples to identify the bacterial pathogen and even determine the causative agent’s resistance to different antibiotics. There is great potential for these technologies to gain wide-spread and routine use in clinical settings, since the analysis can be automated, and test results can be available within minutes after sample collection. This could significantly reduce the necessity to prescribe broad-spectrum antibiotics and allow the faster and more effective use of narrow-spectrum antibiotics. Full article