Identification of Mint Scents Using a QCM Based E-Nose

Mints emit diverse scents that exert specific biological functions and are relevance for applications. The current work strives to develop electronic noses that can electronically discriminate the scents emitted by different species of Mint as alternative to conventional profiling by gas chromatography. Here, 12 different sensing materials including 4 different metal oxide nanoparticle dispersions (AZO, ZnO, SnO2, ITO), one Metal Organic Frame as Cu(BPDC), and 7 different polymer films, including PVA, PEDOT:PSS, PFO, SB, SW, SG, and PB were used for functionalizing of Quartz Crystal Microbalance (QCM) sensors. The purpose was to discriminate six economically relevant Mint species (Mentha x piperita, Mentha spicata, Mentha spicata ssp. crispa, Mentha longifolia, Agastache rugosa, and Nepeta cataria). The adsorption and desorption datasets obtained from each modified QCM sensor were processed by three different classification models, including Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and k-Nearest Neighbor Analysis (k-NN). This allowed discriminating the different Mints with classification accuracies of 97.2% (PCA), 100% (LDA), and 99.9% (k-NN), respectively. Prediction accuracies with a repeating test measurement reached up to 90.6% for LDA, and 85.6% for k-NN. These data demonstrate that this electronic nose can discriminate different Mint scents in a reliable and efficient manner

Combining Two Selection Principles: Sensor Arrays Based on Both Biomimetic Recognition and Chemometrics

Electronic noses mimic smell and taste senses by using sensor arrays to assess complex samples and to simultaneously detect multiple analytes. In most cases, the sensors forming such arrays are not highly selective. Selectivity is attained by pattern recognition/chemometric data treatment of the response pattern. However, especially when aiming at quantifying analytes rather than qualitatively detecting them, it makes sense to implement chemical recognition via receptor layers, leading to increased selectivity of individual sensors. This review focuses on existing sensor arrays developed based on biomimetic approaches to maximize chemical selectivity. Such sensor arrays for instance use molecularly imprint polymers (MIPs) in both e-noses and e-tongues, for example, to characterize headspace gas compositions or to detect protein profiles. Other array types employ entire cells, proteins, and peptides, as well as aptamers, respectively, in multisensor systems. There are two main reasons for combining chemoselectivity and chemometrics: First, this combined approach increases the analytical quality of quantitative data. Second, the approach helps in gaining a deeper understanding of the olfactory processes in nature

Ensuring food safety with molecularly imprinted polymers: innovative methods for the detection of aflatoxins in food and feed samples

Aflatoxins, a group of mycotoxins, represent a heterogeneous class of secondary metabolites that pose a significant risk to food safety and public health due to their potent toxicity. Aflatoxins are widely distributed in the environment, with high levels frequently observed in hot and humid conditions. There is an ongoing development of various methods for detecting aflatoxins in food and feed samples. Herein, a review of these methods is presented with special emphasis on molecularly imprinted polymers (MIPs) as selective materials for aflatoxins’ detection. The key findings of various methods for real-time analysis of food and feed samples are presented and analyzed, providing a comparative assessment of their performance. Furthermore, the challenges and limitations of these methods are discussed, considering their commercialization prospects and real-world requirements

QCM-Arrays for sensing terpenes in fresh and dried herbs via bio-mimetic MIP layers

A piezoelectric 10 MHz multichannel quartz crystal microbalance (MQCM), coated with six molecularly imprinted polystyrene artificial recognition membranes have been developed for selective quantification of terpenes emanated from fresh and dried Lamiaceae family species, i.e., rosemary (Rosmarinus Officinalis L.), basil (Ocimum Basilicum) and sage (Salvia Officinalis). Optimal e-nose parameters, such as layer heights (1-6 KHz), sensitivity <20 ppm of analytes, selectivity at 50 ppm of terpenes, repeatability and reproducibility were thoroughly adjusted prior to online monitoring. Linearity in reversible responses over a wide concentration range <20-250 ppm has been achieved. Discrimination between molecules of similar molar masses, even for isomers, e.g. a-pinene and P-pinene is possible. The array has proven its sensitive and selective properties of sensor responses (20-1,200 Hz) for the difference of fresh and dried herbs. The sensor data attained was validated by GC-MS, to analyze the profiles of sensor emanation patterns. The shelf-life of herbs was monitored via emanation of organic volatiles during a few days. Such an array in association with data analysis tools can be utilized for characterizing complex mixtures

QCM-Arrays for Sensing Terpenes in Fresh and Dried Herbs via Bio-Mimetic MIP Layers

A piezoelectric 10 MHz multichannel quartz crystal microbalance (MQCM), coated with six molecularly imprinted polystyrene artificial recognition membranes have been developed for selective quantification of terpenes emanated from fresh and dried Lamiaceae family species, i.e., rosemary (Rosmarinus Officinalis L.), basil (Ocimum Basilicum) and sage (Salvia Officinalis). Optimal e-nose parameters, such as layer heights (1–6 KHz), sensitivit

Peptides, DNA and MIPs in gas sensing. From the realization of the sensors to sample analysis

Detection and monitoring of volatiles is a challenging and fascinating issue in environmental analysis, agriculture and food quality, process control in industry, as well as in ‘point of care’ diagnostics. Gas chromatographic approaches remain the reference method for the analysis of volatile organic compounds (VOCs); however, gas sensors (GSs), with their advantages of low cost and no or very little sample preparation, have become a reality. Gas sensors can be used singularly or in array format (e.g., e-noses); coupling data output with multivariate statical treatment allows un-target analysis of samples headspace. Within this frame, the use of new binding elements as recognition/interaction elements in gas sensing is a challenging hot-topic that allowed unexpected advancement. In this review, the latest development of gas sensors and gas sensor arrays, realized using peptides, molecularly imprinted polymers and DNA is reported. This work is focused on the description of the strategies used for the GSs development, the sensing elements function, the sensors array set-up, and the application in real cases

QCM sensor arrays for monitoring volatile plant emanations via molecularly imprinted polymers

Zur Überwachung flüchtiger organischer Verbindungen (VOC volatile organic component) wurde ein Sensorarray bestehend aus mehrkanaligen Schwingquarzen (MQCM multichannel quartz crystal microbalance) entwickelt. Als selektive Schicht für den jeweiligen Analyten kamen molekular geprägte Polymerbeschichtungen zum Einsatz. Diese Sensor Arrays wurden vorerst zur kontinuierlichen online Überwachung und selektiven Quantifizierung von Terpenen eingesetzt, die von Arten der Familie Lamiaceae, wie beispielsweise Pfefferminze (Mentha x piperinta) und Basilikum (Ocimum Basilicum) freigesetzt werden. Dabei erzielten die Sensoren bei der Bestimmung des Frischegrades bemerkenswerte Reproduzierbarkeit der Emanationsmuster. Diese waren vergleichbar zu GC-MS Messungen, mit einem Detektionslimit unter 70 ppm. Zusätzlich können diese Muster mit Erkennungsmethoden wie zum Beispiel der Hauptkomponentenanalyse (PCA principal component analyses), der PLS (partial least squares) und mittels künstlichen neuronalen Netzwerken (ANN artifical neuronal networks) untersucht werden. Des Weiteren wurde eine elektronische Nase mit einer molekular geprägten, biomimetischen Polymerschicht (MIP molecular imprinted polymer) entwickelt, die das Terpenemissionsmuster von frischen und getrockneten Kräutern charakterisiert. Hierzu wurden Rosmarin (Rosmarinus Officinalis L.), Basilikum (Ocimum Basilicum) und Salbei (Salvia Officinalis) eingesetzt. Die dazu notwendigen Optimierungsparamater der elektronischen Nase sind: Schichtdicken, Sensitivität der Analyte <20 ppm, Selektivität bei einer Konzentration von 50 ppm der Terpene und Reproduzierbarkeit. Die reversiblen Sensorantworten sind in einem Konzentrationsbereich von <20 ppm bis 200 ppm linear. Die Isomere α- und β-Pinen sind signifikant unterscheidbar. Die Unterscheidbarkeit zwischen frischen und getrockneten Kräutern konnte durch die entsprechenden Messeffekte (20-1200 Hz) der elektronischen Nasen realisiert werden. Die erhaltenen Daten wurden zur Mustererkennung mittels PCA und ANN analysiert und durch Ergebnisse der GC-MS Messungen, welche einen ähnlichen Trend darstellen, validiert. Die Haltbarkeitsdauer der Kräuter konnte durch die Emanation der flüchtigen organischen Bestandteile über einen Zeitraum von mehreren Tagen bestimmt werden. Die Detektionslimits sind besser als 20 ppm und erlauben die Überwachung der Lagerung über mehrere Tage. Zusätzlich wurde eine MIP Screening Methode zur chemischen Bestimmung von Ethlyacetat entwickelt. Dazu wurden sechs MIPs mit unterschiedlichen Monomer¬zusammensetzungen aus VP, PS und DVB hergestellt und getestet. Als das am besten geeignete Sensormaterial für Ethylacetat erwies sich das Polymer mit einer Monomer¬zusam¬mensetzung von VP:PS:DVB 1:2:7 etabliert. Damit konnten Sensitivitäten und Selektivitäten über einen weiten Konzentrationsbereich von 25-3000 ppm für Ethylacetat erreicht werden. Die Querselektivität dieses MIP zwischen 250 und 750 ppm zu 1-Propanol erwies sich als sehr gering (≤ 1 Hz). Schlussendlich wurde ein Sensor Array mit vier Elektroden pro Substrat konstruiert. Dessen Herstellung wurde durch die Optimierung der Elektrodengröße, deren Geometrie und dem Kalibrieren der Heizwendel bestimmt. Diese neu entwickelte Strategie wurde zur massensensitiven real-time Bestimmung und Unterscheidung von Terpenen, welche von Thymian freigesetzt werden, eingesetzt. Die Muster der freigesetzten Terpene, welche mittels vier-Elektroden QCM Arrays erhalten wurden, sind mit den GC-MS Daten vergleichbar. Somit können derartige QCM Sensorarrays in der Praxis zur sensitiven und selektiven Bestimmung einer Vielzahl von biologischen Analyten im mikro- und makro-Bereich, wie beispielsweise die DNA Bestimmung, die Überwachung von VOCs von Pflanzen, bei der Kompostierung oder bei Abbauprozessen, die Qualitätskontrolle, die Haltbarkeit und Frische von Lebensmittel und in zahlreichen Industriebereichen, in unterschiedlichen Phasen zum Einsatz kommen.Arrays of chemical sensors derived from 10 MHz piezoelectric multichannel quartz crystal microbalance (MQCM) have been developed for selective monitoring of volatile organic compounds. Molecularly imprinted artificial recognition membranes have been used for imprinting the analytes of interest. At first the designed sensor array was used for continuous online surveillance and selective quantification of terpenes emanated from species of Lamiaceae family, i.e., peppermint (Mentha × piperita)and basil (Ocimum Basilicum). In terms of monitoring freshness, appreciable reproducibility in emanation patterns comparable to GC-MS analysis was attained with a limit of detection below 70 ppm. Hence, its competency to be explored jointly with pattern recognition tools, i.e., PCA, PLS and ANN. Furthermore, an e-nose with MIP coated biomimetic sensitive layers for comparative study of emanating terpenes of fresh and dried: rosemary (Rosmarinus Officinalis L.), basil (Ocimum Basilicum) and sage (Salvia Officinalis) was made. The optimal e-nose parameters: layer heights, sensitivity <20 ppm of analytes, selectivity at 50 ppm of terpenes, repeatability and reproducibility were systematically achieved. Linearity in reversible responses over a concentration range of ≤ 20-200 ppm has been observed. Isomers, α-pinene and β-pinene can be significantly differentiated by the sensor system. Sensitive and selective properties of e-nose for sensor effects (20–1,200 Hz) have been established which distinguish fresh herbs from dried. The sensor data was analyzed for pattern recognition via PCA and ANN and corroborated with GC-MS results which revealed a similar trend. Moreover, the limit of detection to ≤ 20 ppm and shelf-life of herbs to few days have been examined via designed e-nose. In addition, an ethyl acetate MIP screening strategy has been successfully developed for its chemical sensing. Six MIPs with different monomer compositions of VP, PS and DVB were prepared and tested. Polymer B with monomers ratio (VP: PS: DVB, 1:2:7) was observed as most favorable sensing material for ethyl acetate. Sensitivity and selectivity from a broad range of concentration 25-3000ppm of ethyl acetate was achieved. Cross selectivity of this MIP at 250-750 ppm against 1-propanol was observed to be quite low, i.e., ≤ 1Hz. Finally a tetra-electrode QCM sensor array has been designed. Its fabrication was done through optimizing electrodes size, geometry and with calibration of heating coil. This novel strategy was used for real-time differential mass sensing of terpenes emitted from thyme plant. Patterns of emanating terpenes observed from tetra-electrode QCM array and GC-MS were comparable. Such QCM sensors arrays in practice can explore sensitive and selective concerts for a variety of analytes in different phase’s ranging from bio- micro to macromolecules, e.g., in DNA sensing, monitoring VOCs of plants, composting and degradation process, estimating quality , shelf-life and freshness of food products and in various industries

Bulk and Surface Acoustic Wave Sensor Arrays for Multi-Analyte Detection: A Review

Bulk acoustic wave (BAW) and surface acoustic wave (SAW) sensor devices have successfully been used in a wide variety of gas sensing, liquid sensing, and biosensing applications. Devices include BAW sensors using thickness shear modes and SAW sensors using Rayleigh waves or horizontally polarized shear waves (HPSWs). Analyte specificity and selectivity of the sensors are determined by the sensor coatings. If a group of analytes is to be detected or if only selective coatings (i.e., coatings responding to more than one analyte) are available, the use of multi-sensor arrays is advantageous, as the evaluation of the resulting signal patterns allows qualitative and quantitative characterization of the sample. Virtual sensor arrays utilize only one sensor but combine itwith enhanced signal evaluation methods or preceding sample separation, which results in similar results as obtained with multi-sensor arrays. Both array types have shown to be promising with regard to system integration and low costs. This review discusses principles and design considerations for acoustic multi-sensor and virtual sensor arrays and outlines the use of these arrays in multi-analyte detection applications, focusing mainly on developments of the past decade

Determining aroma differences among basil, parsley, and dill grown under varied supplemental light wavelengths using consumer sensory and flash gas chromatograph-electronic nose analyses

Greenhouse herb producers may use artificial lighting to supplement the natural light available to their crops. High-pressure sodium (HPS) lights are the most common supplemental lighting systems employed in such operations, but light-emitting diode (LED) lighting is increasing in popularity because of its energy efficiency, customizability, and environmental friendliness. LED lights can be customized to emit specific proportions of light wavelengths, but many herb producers do not know how these “light recipes” affect their crops, specifically their crops’ aroma. This research utilized consumer sensory difference panels and flash gas chromatograph-electronic nose (GC-EN) analysis to evaluate the aroma of fresh basil, parsley, and dill herbs after cultivation under one of three supplemental light treatments: HPS, LED with a high proportion of blue to red diodes (high blue LED), or LED with a low proportion of blue to red diodes (low blue LED). Consumer sensory panels using triangle difference tests found that consumers could not determine the difference between herbs grown under HPS and high blue LED. Preliminary work suggests a similar result for HPS and low blue LED, but further research is required to confirm this. GC-EN analysis revealed no significant chemical differences between lighting treatments among basil or parsley. Subtle chemical differences were uncovered in dill GC-EN data, especially when nonpolar and mid-polar column data were examined separately to prevent false correlation from multiple detections of a single compound. Consistent with literature findings, linear discriminant analysis of these data subsets revealed that multiple volatile compounds in dill are affected by the supplemental lighting wavelengths available to the herb. In the scope of this study, there appears to be no overall aroma difference between herbs grown under HPS light and those grown under LED light, but more research must be conducted to confirm and expand upon these findings. Future research including sensory preference tests, descriptive analyses, GC-olfactometry, and GC-MS studies will make research like this more practical for herb farmers