Search

Extra virgin olive oil (EVOO) is the best vegetable oil worldwide but, at the same time, is one of the product victims of fraud in the agri-food sector, and the differences about quality within the extra-virgin olive oil category are often missed. Several scientific techniques were applied in order to guarantee the authenticity and quality of this EVOO. In the present study, the volatile compounds (VOCs) by gas chromatography–mass spectrometry with solid-phase micro-extraction detection (GC–MS SPME), organoleptic analysis by the official Slow Food panel and the detection by a Small Sensor System (S3) were applied. Ten EVOOs from Umbria, a central Italian region, were selected from the 2021 Slow Food Italian extra virgin olive oil official guide, which includes hundreds of high-quality olive oils. The results demonstrated the possibility to discriminate the ten EVOOs, even if they belong to the same Italian region, by all three techniques. The result of GC–MS SPME detection was comparable at the discrimination level to the organoleptic test with few exceptions, while the S3 was able to better separate some EVOOs, which were not discriminated perfectly by the other two methods. The correlation analysis performed among and between the three methodologies allowed us to identify 388 strong associations with a p value less than 0.05. This study has highlighted how much the mix of VOCs was different even among few and localized EVOOs. The correlation with the sensor detection, which is faster and chipper compared to the other two techniques, elucidated the similarities and discrepancies between the applied methods. [ABSTRACT FROM AUTHOR]

Coffee capsules have become one of the most used methods to have a coffee in the last few years. In this work, coffee was prepared using a professional espresso coffee machine. We investigated the volatilome of four different polypropylene coffee capsule typologies (Biologico, Dolce, Deciso, Guatemala) with and without capsules in order to reveal the possible differences in the VOCs spectra. The volatilome of each one was singularly studied through an analysis by gas chromatography and mass spectrometry (GC–MS), checking the abundance of different VOCs in coffee extracted with and without a capsule protection and compared to its related sample. Furthermore, ANOVA and Tukey tests were applied to statistically identify and individuate the possible differences. As a result, it was found that coffee capsules, offer advantages of protecting coffee from oxidation or rancidity and, consequently extended shelf life as well as did not cause a reduction of volatile compounds intensity. Therefore, it is possible to conclude that the aroma of polypropylene coffee capsule extraction is not damaged compared to a traditional espresso. [ABSTRACT FROM AUTHOR]

This work illustrates the potentiality of a mixed array merging the Nanowire and thin film metal oxide technologies to develop an electronic nose as a tool to monitor the human skin and food pathogen microbiota. Nanowire and thin film sensors have been fabricated, characterized and then integrated together to develop a hybrid device that can enhance the sensing performance. Different blends of microorganisms grown in artificial sweat have been tested. Classical techniques, like GC–MS (Gas Chromatography–Mass Spectrometry) with SPME (Solid Phase Micro Extraction) have been employed in parallel, in order to have a multidisciplinary approach and a consistent data set. The obtained results show the potentiality of the proposed electronic nose to discriminate between the different blends of microorganisms and to follow up microbiota growth inside the blends. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Bacterial cellulose as organic substrate for a new generation of MOX sensors. • ZnO integration on bacterial cellulose as semiconductor sensing material. • MOS semiconductor organic sensor prototype assembly. • Room temperature sensor activation through the UV light and measurement. • Room temperature measurements. • Good response to gas test as NO 2 , Acetone, Ethanol and H 2. Abstract Recently a high interest has grown around the use of organic materials, as cellulose, in engineering and electronic fields due to the possibility to create hybrid devices. The objective of this work was to create a new generation of biocompatible bacterial cellulose Metal Oxides (MOX) gas sensors. ZnO semiconductor sensing material was used due to its well-known functional performances and the UV light activation possibility at room temperature. Bacterial cellulose membranes have been produced, active ZnO layer was deposited and the final sensing device was assembled and tested in presence of different chemical compounds. The prototypes showed good response to nitrogen dioxide, acetone and ethanol at room temperature, demonstrating the possibility to use bacterial cellulose as eco and environmental friendly composite transducers material for, but not limited to, chemical sensors. [ABSTRACT FROM AUTHOR]

Tea is the second most consumed beverage, and its aroma, determined by volatile compounds (VOCs) present in leaves or developed during the processing stages, has a great influence on the final quality. The goal of this study is to determine the volatilome of different types of tea to provide a competitive tool in terms of time and costs to recognize and enhance the quality of the product in the food chain. Analyzed samples are representative of the three major types of tea: black, green, and white. VOCs were studied in parallel with different technologies and methods: gas chromatography coupled with mass spectrometer and solid phase microextraction (SPME-GC-MS) and a device called small sensor system, (S3). S3 is made up of tailor-made metal oxide gas sensors, whose operating principle is based on the variation of sensor resistance based on volatiloma exposure. The data obtained were processed through multivariate statistics, showing the full file of the pre-established aim. From the results obtained, it is understood how supportive an innovative technology can be, remotely controllable supported by machine learning (IoF), aimed in the future at increasing food safety along the entire production chain, as an early warning system for possible microbiological or chemical contamination. [ABSTRACT FROM AUTHOR]

Vinegar is a fermented product that is appreciated world-wide. It can be obtained from different kinds of matrices. Specifically, it is a solution of acetic acid produced by a two stage fermentation process. The first is an alcoholic fermentation, where the sugars are converted in ethanol and lower metabolites by the yeast action, generally Saccharomyces cerevisiae. This was performed through a technique that is expanding more and more, the so-called "pied de cuve". The second step is an acetic fermentation where acetic acid bacteria (AAB) action causes the conversion of ethanol into acetic acid. Overall, the aim of this research is to follow wine vinegar production step by step through the volatiloma analysis by metal oxide semiconductor MOX sensors developed by Nano Sensor Systems S.r.l. This work is based on wine vinegar monitored from the grape must to the formed vinegar. The monitoring lasted 4 months and the analyses were carried out with a new generation of Electronic Nose (EN) engineered by Nano Sensor Systems S.r.l., called Small Sensor Systems Plus (S3+), equipped with an array of six gas MOX sensors with different sensing layers each. In particular, real-time monitoring made it possible to follow and to differentiate each step of the vinegar production. The principal component analysis (PCA) method was the statistical multivariate analysis utilized to process the dataset obtained from the sensors. A closer look to PCA graphs affirms how the sensors were able to cluster the production steps in a chronologically correct manner. [ABSTRACT FROM AUTHOR]

Food poisoning is still the first cause of hospitalization worldwide and the most common microbial agent, Campylobacter jejuni, is the most commonly reported gastrointestinal disease in humans in the EU (European Union) as is reported by the European Union One Health 2018 Zoonoses Report styled by the EFSA (European Food Safety Authority) and ECDC (European Center for Disease Prevention and Control). One of the vehicles of transmission of this disease is milk. Nanostructured MOS (Metal Oxide Semiconductor) sensors have extensively demonstrated their ability to reveal the presence and follow the development of microbial species. The main objective of this work was to find a set up for the detection and development follow up of C. jejuni in milk samples. The work was structured in two different studies, the first one was a feasibility survey and the second one was to follow up the development of the bacteria inside milk samples. The obtained results of the first study demonstrate the ability of the sensor array to differentiate the contaminated samples from the control ones. Thanks to the second study, it has been possible to find the limit of microbial safety of the contaminated milk samples. [ABSTRACT FROM AUTHOR]

Extra virgin olive oil (EVOO) is characterized by its aroma and other sensory attributes. These are determined by the geographical origin of the oil, extraction process, place of cultivation, soil, tree varieties, and storage conditions. In the present work, an array of metal oxide gas sensors (called S3), in combination with the SPME-GC-MS technique, was applied to the discrimination of different types of olive oil (phase 1) and to the identification of four varieties of Garda PDO extra virgin olive oils coming from west and east shores of Lake Garda (phase 2). The chemical analysis method involving SPME-GC-MS provided a complete volatile component of the extra virgin olive oils that was used to relate to the S3 multisensory responses. Furthermore, principal component analysis (PCA) and k-Nearest Neighbors (k-NN) analysis were carried out on the set of data acquired from the sensor array to determine the best sensors for these tasks and to assess the capability of the system to identify various olive oil samples. k-NN classification rates were found to be 94.3% and 94.7% in the two phases, respectively. These first results are encouraging and show a good capability of the S3 instrument to distinguish different oil samples. [ABSTRACT FROM AUTHOR]

Parmigiano Reggiano cheese is one of the most appreciated and consumed foods worldwide, especially in Italy, for its high content of nutrients and taste. However, these characteristics make this product subject to counterfeiting in different forms. In this study, a novel method based on an electronic nose has been developed to investigate the potentiality of this tool to distinguish rind percentages in grated Parmigiano Reggiano packages that should be lower than 18%. Different samples, in terms of percentage, seasoning and rind working process, were considered to tackle the problem at 360°. In parallel, GC-MS technique was used to give a name to the compounds that characterize Parmigiano and to relate them to sensors responses. Data analysis consisted of two stages: Multivariate analysis (PLS) and classification made in a hierarchical way with PLS-DA ad ANNs. Results were promising, in terms of correct classification of the samples. The correct classification rate (%) was higher for ANNs than PLS-DA, with correct identification approaching 100 percent. [ABSTRACT FROM AUTHOR]

Nowadays, it is well known that sensors have an enormous impact on our life, using streams of data to make life-changing decisions. Every single aspect of our day is monitored via thousands of sensors, and the benefits we can obtain are enormous. With the increasing demand for food quality, food safety has become one of the main focuses of our society. However, fresh foods are subject to spoilage due to the action of microorganisms, enzymes, and oxidation during storage. Nanotechnology can be applied in the food industry to support packaged products and extend their shelf life. Chemical composition and sensory attributes are quality markers which require innovative assessment methods, as existing ones are rather difficult to implement, labour-intensive, and expensive. E-sensing devices, such as vision systems, electronic noses, and electronic tongues, overcome many of these drawbacks. Nanotechnology holds great promise to provide benefits not just within food products but also around food products. In fact, nanotechnology introduces new chances for innovation in the food industry at immense speed. This review describes the food application fields of nanotechnologies; in particular, metal oxide sensors (MOS) will be presented. [ABSTRACT FROM AUTHOR]

In this paper, we present the investigations on metal oxide-based gas sensors considering the works performed at SENSOR lab, University of Brescia (Italy). We reported the developments in synthesis techniques for the preparation of doped and functionalized low-dimensional metal oxide materials. Furthermore, we discussed our achievements in the fabrication of heterostructures with unique functional features. In particular, we focused on the strategies to improve the sensing performance of metal oxides at relatively low operating temperatures. We presented our studies on surface photoactivation of sensing structures considering the application of biocompatible materials in the architecture of the functional devices as well. [ABSTRACT FROM AUTHOR]