1
|
Sangiorgi L, Sberveglieri V, Carnevale C, De Nardi S, Nunez-Carmona E, Raccagni S. Data-Driven Virtual Sensing for Electrochemical Sensors. Sensors (Basel) 2024; 24:1396. [PMID: 38474932 DOI: 10.3390/s24051396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 02/19/2024] [Accepted: 02/20/2024] [Indexed: 03/14/2024]
Abstract
In recent years, the application of machine learning for virtual sensing has revolutionized the monitoring and management of information. In particular, electrochemical sensors generate large amounts of data, allowing the application of complex machine learning/AI models able to (1) reproduce the measured data and (2) predict and manage faults in the measuring sensor. In this work, data-driven models based on an autoregressive model and an artificial neural network have been identified and used to (i) evaluate sensor redundancy and (ii) predict and manage faults in the context of electrochemical sensors for the measurement of ethanol. The approach shows encouraging results in terms of both performance and sensitivity analyses, allowing for the reconstruction of the values measured by two sensors in a series of six sensors with different dopant levels and to reproduce their values after a fault.
Collapse
Affiliation(s)
- Lucia Sangiorgi
- Department of Mechanical and Industrial Engineering, University of Brescia, 25123 Brescia, Italy
| | - Veronica Sberveglieri
- National Research Council, Institute of Bioscience and Bioresources (CNR-IBBR), Via J.F. Kennedy, 42124 Reggio Emilia, Italy
- Nano Sensor System srl (NASYS), Via Alfonso Catalani, 42124 Reggio Emilia, Italy
| | - Claudio Carnevale
- Department of Mechanical and Industrial Engineering, University of Brescia, 25123 Brescia, Italy
| | - Sabrina De Nardi
- Department of Mechanical and Industrial Engineering, University of Brescia, 25123 Brescia, Italy
| | - Estefanía Nunez-Carmona
- National Research Council, Institute of Bioscience and Bioresources (CNR-IBBR), Via J.F. Kennedy, 42124 Reggio Emilia, Italy
| | - Sara Raccagni
- Department of Mechanical and Industrial Engineering, University of Brescia, 25123 Brescia, Italy
| |
Collapse
|
2
|
Wätjen AP, De Vero L, Núñez Carmona E, Sberveglieri V, Huang W, Turner MS, Bang-Berthelsen CH. Corrigendum to: Leuconostoc performance in soy-based fermentations - Survival, acidification, sugar metabolism, and flavor comparisons [Food Microbiol. 115 (2023) 104337]. Food Microbiol 2024; 117:104371. [PMID: 37918994 DOI: 10.1016/j.fm.2023.104371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2023]
Affiliation(s)
- Anders Peter Wätjen
- National Food Institute, Technical University of Denmark, 2800, Kgs. Lyngby, Denmark
| | - Luciana De Vero
- Department of Life Sciences, University of Modena and Reggio Emilia, 42122, Reggio Emilia, Italy
| | - Estefania Núñez Carmona
- National Research Council, Institute of Bioscience and Bioresources (CNR-IBBR), Via J.F. Kennedy, 17/i, 42124, Reggio Emilia, Italy
| | - Veronica Sberveglieri
- National Research Council, Institute of Bioscience and Bioresources (CNR-IBBR), Via J.F. Kennedy, 17/i, 42124, Reggio Emilia, Italy; Nano Sensor Systems, NASYS Spin-Off University of Brescia, 25125, Brescia, Italy
| | - Wenkang Huang
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, Queensland, Australia
| | - Mark S Turner
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, Queensland, Australia
| | | |
Collapse
|
3
|
Poeta E, Liboà A, Mistrali S, Núñez-Carmona E, Sberveglieri V. Nanotechnology and E-Sensing for Food Chain Quality and Safety. Sensors (Basel) 2023; 23:8429. [PMID: 37896524 PMCID: PMC10610592 DOI: 10.3390/s23208429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 10/02/2023] [Accepted: 10/07/2023] [Indexed: 10/29/2023]
Abstract
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.
Collapse
Affiliation(s)
- Elisabetta Poeta
- Department of Life Sciences, University of Modena and Reggio Emilia, Via J.F. Kennedy, 17/i, 42124 Reggio Emilia, RE, Italy
| | - Aris Liboà
- Department of Chemistry, Life Science and Environmental Sustainability, University of Parma, Parco Area delle Scienze, 11/a, 43124 Parma, PR, Italy;
| | - Simone Mistrali
- Nano Sensor System srl (NASYS), Via Alfonso Catalani, 9, 42124 Reggio Emilia, RE, Italy;
| | - Estefanía Núñez-Carmona
- National Research Council, Institute of Bioscience and Bioresources (CNR-IBBR), Via J.F. Kennedy, 17/i, 42124 Reggio Emilia, RE, Italy;
| | - Veronica Sberveglieri
- Nano Sensor System srl (NASYS), Via Alfonso Catalani, 9, 42124 Reggio Emilia, RE, Italy;
- National Research Council, Institute of Bioscience and Bioresources (CNR-IBBR), Via J.F. Kennedy, 17/i, 42124 Reggio Emilia, RE, Italy;
| |
Collapse
|
4
|
Wätjen AP, De Vero L, Carmona EN, Sberveglieri V, Huang W, Turner MS, Bang-Berthelsen CH. Leuconostoc performance in soy-based fermentations - Survival, acidification, sugar metabolism, and flavor comparisons. Food Microbiol 2023; 115:104337. [PMID: 37567639 DOI: 10.1016/j.fm.2023.104337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 07/06/2023] [Accepted: 07/10/2023] [Indexed: 08/13/2023]
Abstract
Leuconostoc spp. is often regarded as the flavor producer, responsible for the production of acetoin and diacetyl in dairy cheese. In this study, we investigate seven plant-derived Leuconostoc strains, covering four species, in their potential as a lyophilized starter culture for flavor production in fermented soy-based cheese alternatives. We show that the process of lyophilization of Leuconostoc can be feasible using a soy-based lyoprotectant, with survivability up to 63% during long term storage. Furthermore, the storage in this media improves the subsequent growth in a soy-based substrate in a strain specific manner. The utilization of individual raffinose family oligosaccharides was strain dependent, with Leuconostoc pseudomesenteroides NFICC99 being the best consumer. Furthermore, we show that all investigated strains were able to produce a range of volatile flavor compounds found in dairy cheese products, as well as remove certain dairy off-flavors from the soy-based substrate like hexanal and 2-pentylfuran. Also here, NFICC99 was strain producing most cheese-related volatile flavor compounds, followed by Leuconostoc mesenteroides NFICC319. These findings provide initial insights into the development of Leuconostoc as a potential starter culture for plant-based dairy alternatives, as well as a promising approach for generation of stable, lyophilized cultures.
Collapse
Affiliation(s)
- Anders Peter Wätjen
- National Food Institute, Technical University of Denmark, 2800, Kgs. Lyngby, Denmark
| | - Luciana De Vero
- Department of Life Sciences, University of Modena and Reggio Emilia, 42122, Reggio Emilia, Italy
| | - Estefania Núñez Carmona
- National Research Council, Institute of Bioscience and Bioresources (CNR-IBBR), Via J.F. Kennedy, 17/i, 42124, Reggio Emilia, Italy
| | - Veronica Sberveglieri
- National Research Council, Institute of Bioscience and Bioresources (CNR-IBBR), Via J.F. Kennedy, 17/i, 42124, Reggio Emilia, Italy; Nano Sensor Systems, NASYS Spin-Off University of Brescia, 25125, Brescia, Italy
| | - Wenkang Huang
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, Queensland, Australia
| | - Mark S Turner
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, Queensland, Australia
| | | |
Collapse
|
5
|
Mariotti R, Núñez-Carmona E, Genzardi D, Pandolfi S, Sberveglieri V, Mousavi S. Volatile Olfactory Profiles of Umbrian Extra Virgin Olive Oils and Their Discrimination through MOX Chemical Sensors. Sensors (Basel) 2022; 22:7164. [PMID: 36236259 PMCID: PMC9572317 DOI: 10.3390/s22197164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 09/12/2022] [Accepted: 09/16/2022] [Indexed: 06/16/2023]
Abstract
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.
Collapse
Affiliation(s)
- Roberto Mariotti
- Institute of Biosciences and Bioresources, National Research Council, 06128 Perugia, Italy
| | - Estefanía Núñez-Carmona
- Institute of Biosciences and Bioresources, National Research Council, URT-Reggio Emilia, Via J. F. Kennedy 17/I, 42124 Reggio Emilia, Italy
| | - Dario Genzardi
- Institute of Biosciences and Bioresources, National Research Council, URT-Reggio Emilia, Via J. F. Kennedy 17/I, 42124 Reggio Emilia, Italy
| | - Saverio Pandolfi
- Institute of Biosciences and Bioresources, National Research Council, 06128 Perugia, Italy
| | - Veronica Sberveglieri
- Institute of Biosciences and Bioresources, National Research Council, URT-Reggio Emilia, Via J. F. Kennedy 17/I, 42124 Reggio Emilia, Italy
| | - Soraya Mousavi
- Institute of Biosciences and Bioresources, National Research Council, 06128 Perugia, Italy
| |
Collapse
|
6
|
Genzardi D, Greco G, Núñez-Carmona E, Sberveglieri V. Real Time Monitoring of Wine Vinegar Supply Chain through MOX Sensors. Sensors (Basel) 2022; 22:s22166247. [PMID: 36016008 PMCID: PMC9412311 DOI: 10.3390/s22166247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 08/15/2022] [Accepted: 08/15/2022] [Indexed: 05/08/2023]
Abstract
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.
Collapse
Affiliation(s)
- Dario Genzardi
- National Research Council, Institute of Bioscience and Bioresources (CNR-IBBR), Via J.F. Kennedy, 17/i, 42124 Reggio Emilia, RE, Italy
| | - Giuseppe Greco
- Nano Sensor Systems S.r.l., (NASYS) Spin-Off University of Brescia, Via Camillo Brozzoni, 9, 25125 Brescia, BR, Italy
- Correspondence:
| | - Estefanía Núñez-Carmona
- National Research Council, Institute of Bioscience and Bioresources (CNR-IBBR), Via J.F. Kennedy, 17/i, 42124 Reggio Emilia, RE, Italy
| | - Veronica Sberveglieri
- National Research Council, Institute of Bioscience and Bioresources (CNR-IBBR), Via J.F. Kennedy, 17/i, 42124 Reggio Emilia, RE, Italy
| |
Collapse
|
7
|
Abbatangelo M, Núñez-Carmona E, Sberveglieri V, Zappa D, Comini E, Sberveglieri G. An Array of MOX Sensors and ANNs to Assess Grated Parmigiano Reggiano Cheese Packs' Compliance with CFPR Guidelines. Biosensors (Basel) 2020; 10:bios10050047. [PMID: 32370241 PMCID: PMC7277510 DOI: 10.3390/bios10050047] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 04/28/2020] [Accepted: 04/29/2020] [Indexed: 12/21/2022]
Abstract
Parmigiano Reggiano cheese is one of the most appreciated Italian foods on account of its high nutrient content and taste. Due to its high cost, these characteristics make this product subject to counterfeiting in different forms. In this study, an approach based on an array of gas sensors has been employed to assess if it was possible to distinguish different samples based on their aroma. Samples were characterized in terms of rind percentage, seasoning, and rind working process. From the responses of the sensors, five features were extracted and the capability of these parameters to recognize target classes was tested with statistical analysis. Hence, the performance of the sensors’ array was quantified using artificial neural networks. To simplify the problem, a hierarchical approach has been used: three steps of classification were performed, and in each step one parameter of the grated cheese was identified (firstly, seasoning; secondly, rind working process; finally, rind percentage). The accuracies ranged from 88.24% to 100%.
Collapse
Affiliation(s)
- Marco Abbatangelo
- Department of Information Engineering, University of Brescia, Brescia, via Branze, 38, 25123 Brescia, BS, Italy; (D.Z.); (E.C.); (G.S.)
- Correspondence:
| | - Estefanía Núñez-Carmona
- CNR-IBBR, Institute of Bioscience and Bioresources, via Madonna del Piano, 10, 50019 Sesto Fiorentino, FI, Italy; (E.N.-C.); (V.S.)
| | - Veronica Sberveglieri
- CNR-IBBR, Institute of Bioscience and Bioresources, via Madonna del Piano, 10, 50019 Sesto Fiorentino, FI, Italy; (E.N.-C.); (V.S.)
- NANO SENSOR SYSTEMS, NASYS Spin-Off University of Brescia, Brescia, via Camillo Brozzoni, 9, 25125 Brescia, BS, Italy
| | - Dario Zappa
- Department of Information Engineering, University of Brescia, Brescia, via Branze, 38, 25123 Brescia, BS, Italy; (D.Z.); (E.C.); (G.S.)
| | - Elisabetta Comini
- Department of Information Engineering, University of Brescia, Brescia, via Branze, 38, 25123 Brescia, BS, Italy; (D.Z.); (E.C.); (G.S.)
- NANO SENSOR SYSTEMS, NASYS Spin-Off University of Brescia, Brescia, via Camillo Brozzoni, 9, 25125 Brescia, BS, Italy
| | - Giorgio Sberveglieri
- Department of Information Engineering, University of Brescia, Brescia, via Branze, 38, 25123 Brescia, BS, Italy; (D.Z.); (E.C.); (G.S.)
- NANO SENSOR SYSTEMS, NASYS Spin-Off University of Brescia, Brescia, via Camillo Brozzoni, 9, 25125 Brescia, BS, Italy
| |
Collapse
|
8
|
Núñez-Carmona E, Abbatangelo M, Zappa D, Comini E, Sberveglieri G, Sberveglieri V. Nanostructured MOS Sensor for the Detection, Follow up, and Threshold Pursuing of Campylobacter Jejuni Development in Milk Samples. Sensors (Basel) 2020; 20:E2009. [PMID: 32260084 PMCID: PMC7180930 DOI: 10.3390/s20072009] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 03/23/2020] [Accepted: 04/02/2020] [Indexed: 11/19/2022]
Abstract
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.
Collapse
Affiliation(s)
| | - Marco Abbatangelo
- Department of Information Engineering, University of Brescia, 25123 Brescia (BS), Italy; (M.A.); (D.Z.); (E.C.); (G.S.)
| | - Dario Zappa
- Department of Information Engineering, University of Brescia, 25123 Brescia (BS), Italy; (M.A.); (D.Z.); (E.C.); (G.S.)
| | - Elisabetta Comini
- Department of Information Engineering, University of Brescia, 25123 Brescia (BS), Italy; (M.A.); (D.Z.); (E.C.); (G.S.)
- NANO SENSOR SYSTEMS, Dep. Information Engineering, NASYS spin-off University of Brescia, 25123 Brescia (BS), Italy
| | - Giorgio Sberveglieri
- Department of Information Engineering, University of Brescia, 25123 Brescia (BS), Italy; (M.A.); (D.Z.); (E.C.); (G.S.)
- NANO SENSOR SYSTEMS, Dep. Information Engineering, NASYS spin-off University of Brescia, 25123 Brescia (BS), Italy
| | - Veronica Sberveglieri
- Institute of Bioscience and Bioresources, CNR-IBBR, 50019 Sesto Fiorentino (FI), Italy;
- NANO SENSOR SYSTEMS, Dep. Information Engineering, NASYS spin-off University of Brescia, 25123 Brescia (BS), Italy
| |
Collapse
|
9
|
Núñez-Carmona E, Abbatangelo M, Zottele I, Piccoli P, Tamanini A, Comini E, Sberveglieri G, Sberveglieri V. Nanomaterial Gas Sensors for Online Monitoring System of Fruit Jams. Foods 2019; 8:E632. [PMID: 31810272 PMCID: PMC6963516 DOI: 10.3390/foods8120632] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Revised: 11/21/2019] [Accepted: 11/22/2019] [Indexed: 12/25/2022] Open
Abstract
Jams are appreciated worldwide and have become a growing market, due to the greater attention paid by consumers for healthy food. The selected products for this study represent a segment of the European market that addresses natural products without added sucrose or with a low content of natural sugars. This study aims to identify volatile organic compounds (VOCs) that characterize three flavors of fruit and five recipes using gas chromatography-mass spectrometry (GC-MS) and solid-phase micro-extraction (SPME) analysis. Furthermore, an innovative device, a small sensor system (S3), based on gas sensors with nanomaterials has been used; it may be particularly advantageous in the production line. Results obtained with linear discriminant analysis (LDA) show that S3 can distinguish among the different recipes thanks to the differences in the VOCs that are present in the specimens, as evidenced by the GC-MS analysis. Finally, this study highlights how the thermal processes for obtaining the jam do not alter the natural properties of the fruit.
Collapse
Affiliation(s)
- Estefanía Núñez-Carmona
- CNR-IBBR, Institute of Bioscience and Bioresources, via Madonna del Piano, 10, 50019 Sesto Fiorentino, FI, Italy; (E.N.-C.); (V.S.)
| | - Marco Abbatangelo
- Department of Information Engineering, University of Brescia, Brescia, via Branze, 38, 25123 Brescia, BS, Italy;
| | - Ivano Zottele
- Menz&Gasser S.p.A., Sede Legale Zona Industriale, 38050 Novaledo (TN), Italy; (I.Z.); (P.P.); (A.T.)
| | - Pierpaolo Piccoli
- Menz&Gasser S.p.A., Sede Legale Zona Industriale, 38050 Novaledo (TN), Italy; (I.Z.); (P.P.); (A.T.)
| | - Armando Tamanini
- Menz&Gasser S.p.A., Sede Legale Zona Industriale, 38050 Novaledo (TN), Italy; (I.Z.); (P.P.); (A.T.)
| | - Elisabetta Comini
- Department of Information Engineering, University of Brescia, Brescia, via Branze, 38, 25123 Brescia, BS, Italy;
- Nano Sensor Systems, NASYS Spin-Off University of Brescia, Brescia, via Camillo Brozzoni, 9, 25125 Brescia, BS, Italy;
| | - Giorgio Sberveglieri
- Nano Sensor Systems, NASYS Spin-Off University of Brescia, Brescia, via Camillo Brozzoni, 9, 25125 Brescia, BS, Italy;
| | - Veronica Sberveglieri
- CNR-IBBR, Institute of Bioscience and Bioresources, via Madonna del Piano, 10, 50019 Sesto Fiorentino, FI, Italy; (E.N.-C.); (V.S.)
- Nano Sensor Systems, NASYS Spin-Off University of Brescia, Brescia, via Camillo Brozzoni, 9, 25125 Brescia, BS, Italy;
| |
Collapse
|
10
|
Abbatangelo M, Núñez-Carmona E, Duina G, Sberveglieri V. Multidisciplinary Approach to Characterizing the Fingerprint of Italian EVOO. Molecules 2019; 24:E1457. [PMID: 31013836 PMCID: PMC6515353 DOI: 10.3390/molecules24081457] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 04/10/2019] [Accepted: 04/11/2019] [Indexed: 01/07/2023] Open
Abstract
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.
Collapse
Affiliation(s)
- Marco Abbatangelo
- Department of Information Engineering, University of Brescia, Brescia, via Branze, 38, 25123 Brescia, BS, Italy.
| | - Estefanía Núñez-Carmona
- CNR-IBBR, Institute of Bioscience and Bioresources, via Madonna del Piano, 10, 50019 Sesto Fiorentino, FI, Italy.
| | - Giorgio Duina
- Department of Information Engineering, University of Brescia, Brescia, via Branze, 38, 25123 Brescia, BS, Italy.
| | - Veronica Sberveglieri
- CNR-IBBR, Institute of Bioscience and Bioresources, via Madonna del Piano, 10, 50019 Sesto Fiorentino, FI, Italy.
- NANO SENSOR SYSTEMS, NASYS Spin-Off University of Brescia, Brescia, via Camillo Brozzoni, 9, 25125 Brescia, BS, Italy.
| |
Collapse
|
11
|
Abbatangelo M, Núñez-Carmona E, Sberveglieri V. Application of a novel S3 nanowire gas sensor device in parallel with GC-MS for the identification of Parmigiano Reggiano from US and European competitors. J FOOD ENG 2018. [DOI: 10.1016/j.jfoodeng.2018.05.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
|
12
|
Abbatangelo M, Núñez-Carmona E, Sberveglieri V, Zappa D, Comini E, Sberveglieri G. Application of a Novel S3 Nanowire Gas Sensor Device in Parallel with GC-MS for the Identification of Rind Percentage of Grated Parmigiano Reggiano. Sensors (Basel) 2018; 18:s18051617. [PMID: 29783673 PMCID: PMC5981319 DOI: 10.3390/s18051617] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Revised: 05/11/2018] [Accepted: 05/15/2018] [Indexed: 12/20/2022]
Abstract
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.
Collapse
Affiliation(s)
- Marco Abbatangelo
- Department of Information Engineering, University of Brescia, Via Branze 38, 25123 Brescia, Italy.
| | - Estefanía Núñez-Carmona
- Department of Information Engineering, University of Brescia, Via Branze 38, 25123 Brescia, Italy.
| | - Veronica Sberveglieri
- CNR-IBBR, Institute of Biosciences and Bioresources, Via Madonna del Piano 10, 50019 Sesto Fiorentino (FI), Italy.
- NANO SENSOR SYSTEMS S.r.l., Via Branze 38, 25123 Brescia, Italy.
| | - Dario Zappa
- Department of Information Engineering, University of Brescia, Via Branze 38, 25123 Brescia, Italy.
| | - Elisabetta Comini
- Department of Information Engineering, University of Brescia, Via Branze 38, 25123 Brescia, Italy.
- NANO SENSOR SYSTEMS S.r.l., Via Branze 38, 25123 Brescia, Italy.
| | - Giorgio Sberveglieri
- Department of Information Engineering, University of Brescia, Via Branze 38, 25123 Brescia, Italy.
- NANO SENSOR SYSTEMS S.r.l., Via Branze 38, 25123 Brescia, Italy.
| |
Collapse
|
13
|
Zappa D, Bertuna A, Comini E, Kaur N, Poli N, Sberveglieri V, Sberveglieri G. Metal oxide nanostructures: preparation, characterization and functional applications as chemical sensors. Beilstein J Nanotechnol 2017; 8:1205-1217. [PMID: 28685121 PMCID: PMC5480349 DOI: 10.3762/bjnano.8.122] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2016] [Accepted: 04/28/2017] [Indexed: 05/27/2023]
Abstract
Preparation and characterization of different metal oxide (NiO, WO3, ZnO, SnO2 and Nb2O5) nanostructures for chemical sensing are presented. p-Type (NiO) and n-type (WO3, SnO2, ZnO and Nb2O5) metal oxide nanostructures were grown on alumina substrates using evaporation-condensation, thermal oxidation and hydrothermal techniques. Surface morphologies and crystal structures were investigated through scanning electron microscopy and Raman spectroscopy. Furthermore, different batches of sensors have been prepared, and their sensing performances towards carbon monoxide and nitrogen dioxide have been explored. Moreover, metal oxide nanowires have been integrated into an electronic nose and successfully applied to discriminate between drinking and contaminated water.
Collapse
Affiliation(s)
- Dario Zappa
- SENSOR, Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Brescia and CNR-INO, via Valotti 9, 25123 Brescia, Italy
| | - Angela Bertuna
- SENSOR, Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Brescia and CNR-INO, via Valotti 9, 25123 Brescia, Italy
| | - Elisabetta Comini
- SENSOR, Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Brescia and CNR-INO, via Valotti 9, 25123 Brescia, Italy
| | - Navpreet Kaur
- SENSOR, Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Brescia and CNR-INO, via Valotti 9, 25123 Brescia, Italy
| | - Nicola Poli
- SENSOR, Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Brescia and CNR-INO, via Valotti 9, 25123 Brescia, Italy
| | - Veronica Sberveglieri
- SENSOR, Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Brescia and CNR-INO, via Valotti 9, 25123 Brescia, Italy
| | - Giorgio Sberveglieri
- SENSOR, Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Brescia and CNR-INO, via Valotti 9, 25123 Brescia, Italy
| |
Collapse
|
14
|
Galstyan V, Comini E, Kholmanov I, Ponzoni A, Sberveglieri V, Poli N, Faglia G, Sberveglieri G. A composite structure based on reduced graphene oxide and metal oxide nanomaterials for chemical sensors. Beilstein J Nanotechnol 2016; 7:1421-1427. [PMID: 27826516 PMCID: PMC5082476 DOI: 10.3762/bjnano.7.133] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2016] [Accepted: 09/19/2016] [Indexed: 05/19/2023]
Abstract
A hybrid nanostructure based on reduced graphene oxide and ZnO has been obtained for the detection of volatile organic compounds. The sensing properties of the hybrid structure have been studied for different concentrations of ethanol and acetone. The response of the hybrid material is significantly higher compared to pristine ZnO nanostructures. The obtained results have shown that the nanohybrid is a promising structure for the monitoring of environmental pollutants and for the application of breath tests in assessment of exposure to volatile organic compounds.
Collapse
Affiliation(s)
- Vardan Galstyan
- Sensor Lab, CNR, National Institute of Optics (INO), Via Valotti 9, 25133 Brescia, Italy
- Sensor Lab, Department of Information Engineering, University of Brescia, Via Valotti 9, 25133 Brescia, Italy
| | - Elisabetta Comini
- Sensor Lab, CNR, National Institute of Optics (INO), Via Valotti 9, 25133 Brescia, Italy
- Sensor Lab, Department of Information Engineering, University of Brescia, Via Valotti 9, 25133 Brescia, Italy
| | - Iskandar Kholmanov
- Sensor Lab, CNR, National Institute of Optics (INO), Via Valotti 9, 25133 Brescia, Italy
- Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX 78712, USA
| | - Andrea Ponzoni
- Sensor Lab, CNR, National Institute of Optics (INO), Via Valotti 9, 25133 Brescia, Italy
- Sensor Lab, Department of Information Engineering, University of Brescia, Via Valotti 9, 25133 Brescia, Italy
| | - Veronica Sberveglieri
- Sensor Lab, CNR, National Institute of Optics (INO), Via Valotti 9, 25133 Brescia, Italy
| | - Nicola Poli
- Sensor Lab, Department of Information Engineering, University of Brescia, Via Valotti 9, 25133 Brescia, Italy
| | - Guido Faglia
- Sensor Lab, CNR, National Institute of Optics (INO), Via Valotti 9, 25133 Brescia, Italy
- Sensor Lab, Department of Information Engineering, University of Brescia, Via Valotti 9, 25133 Brescia, Italy
| | - Giorgio Sberveglieri
- Sensor Lab, CNR, National Institute of Optics (INO), Via Valotti 9, 25133 Brescia, Italy
- Sensor Lab, Department of Information Engineering, University of Brescia, Via Valotti 9, 25133 Brescia, Italy
| |
Collapse
|
15
|
Zambotti G, Sberveglieri V, Gobbi E, Falasconi M, Nunez E, Pulvirenti A. Fast Identification of Microbiological Contamination in Vegetable Soup by Electronic Nose. ACTA ACUST UNITED AC 2014. [DOI: 10.1016/j.proeng.2014.11.686] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
|
16
|
Ponzoni A, Comini E, Concina I, Ferroni M, Falasconi M, Gobbi E, Sberveglieri V, Sberveglieri G. Nanostructured metal oxide gas sensors, a survey of applications carried out at SENSOR lab, Brescia (Italy) in the security and food quality fields. Sensors (Basel) 2012; 12:17023-45. [PMID: 23235445 PMCID: PMC3571824 DOI: 10.3390/s121217023] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2012] [Revised: 12/05/2012] [Accepted: 12/06/2012] [Indexed: 11/16/2022]
Abstract
In this work we report on metal oxide (MOX) based gas sensors, presenting the work done at the SENSOR laboratory of the CNR-IDASC and University of Brescia, Italy since the 80s up to the latest results achieved in recent times. In particular we report the strategies followed at SENSOR during these 30 years to increase the performance of MOX sensors through the development of different preparation techniques, from Rheotaxial Growth Thermal Oxidation (RGTO) to nanowire technology to address sensitivity and stability, and the development of electronic nose systems and pattern recognition techniques to address selectivity. We will show the obtained achievement in the context of selected applications such as safety and security and food quality control.
Collapse
Affiliation(s)
- Andrea Ponzoni
- SENSOR, CNR-IDASC, UOS Brescia, Via Branze 45, 25123 Brescia, Italy
- SENSOR, Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Brescia, Via Valotti 9, 25133 Brescia, Italy; E-Mails: (E.C.); (I.C.); (M.F.); (M.F.); (G.S.)
| | - Elisabetta Comini
- SENSOR, CNR-IDASC, UOS Brescia, Via Branze 45, 25123 Brescia, Italy
- SENSOR, Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Brescia, Via Valotti 9, 25133 Brescia, Italy; E-Mails: (E.C.); (I.C.); (M.F.); (M.F.); (G.S.)
| | - Isabella Concina
- SENSOR, CNR-IDASC, UOS Brescia, Via Branze 45, 25123 Brescia, Italy
- SENSOR, Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Brescia, Via Valotti 9, 25133 Brescia, Italy; E-Mails: (E.C.); (I.C.); (M.F.); (M.F.); (G.S.)
| | - Matteo Ferroni
- SENSOR, CNR-IDASC, UOS Brescia, Via Branze 45, 25123 Brescia, Italy
- SENSOR, Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Brescia, Via Valotti 9, 25133 Brescia, Italy; E-Mails: (E.C.); (I.C.); (M.F.); (M.F.); (G.S.)
| | - Matteo Falasconi
- SENSOR, CNR-IDASC, UOS Brescia, Via Branze 45, 25123 Brescia, Italy
- SENSOR, Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Brescia, Via Valotti 9, 25133 Brescia, Italy; E-Mails: (E.C.); (I.C.); (M.F.); (M.F.); (G.S.)
| | - Emanuela Gobbi
- SENSOR, CNR-IDASC, UOS Brescia, Via Branze 45, 25123 Brescia, Italy
- DISA, Università di Udine, Via Scienze 208, 33100 Udine, Italy; E-Mail:
| | - Veronica Sberveglieri
- Dipartimento di Scienze Agrarie e degli Alimenti, Università di Modena e Reggio Emilia, Via Amendola 2, 42100 Reggio Emilia, Italy; E-Mail:
| | - Giorgio Sberveglieri
- SENSOR, CNR-IDASC, UOS Brescia, Via Branze 45, 25123 Brescia, Italy
- SENSOR, Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Brescia, Via Valotti 9, 25133 Brescia, Italy; E-Mails: (E.C.); (I.C.); (M.F.); (M.F.); (G.S.)
| |
Collapse
|
17
|
Sberveglieri V, Concina I, Falasconi M, Ongo E, Pulvirenti A, Fava P, Gouma P. Identification Of Geographical Origin Of Coffee Before And After Roasting By Electronic Noses. ACTA ACUST UNITED AC 2011. [DOI: 10.1063/1.3626316] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
|