1
|
Lee SW, Yoon JA, Kim MD, Kim BH, Seo YH. A machine learning-based electronic nose system using numerous low-cost gas sensors for real-time alcoholic beverage classification. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2024; 16:5909-5919. [PMID: 39158403 DOI: 10.1039/d4ay00964a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/20/2024]
Abstract
This study introduces numerous low-cost gas sensors and a real-time alcoholic beverage classification system based on machine learning. Dogs possess a superior sense of smell compared to humans due to having 30 times more olfactory receptors and three times more olfactory receptor types than humans. Thus, in odor classification, the number of olfactory receptors is a more influential factor than the number of receptor types. From this perspective, this study proposes a system that utilizes distinctive data patterns resulting from heterogeneous responses among numerous low-cost homogeneous MOS-based sensors with poor gas selectivity. To evaluate the performance of the proposed system, learning data were gathered using three alcoholic beverage groups including different aged whiskeys, Korean soju with 99% same compositions, and white wines made from the Sauvignon blanc variety, sourced from various countries. The electronic nose system was developed to classify alcoholic samples measured using 30 gas sensors in real time. The samples were injected into a gas chamber for 60 seconds, followed by a 60-second injection of clean air. After preprocessing the time-series data into four distinct datasets, the data were analyzed using a machine learning algorithm, and the classification results were compared. The results showed a high classification accuracy of over 99%, and it was observed that classification performance varied depending on data preprocessing. As the number of gas sensors increased, the prediction accuracy improved, reaching up to 99.83 ± 0.21%. These experimental results indicated that the proposed electronic nose system's classification performance was comparable to that of commercial electronic nose systems. Additionally, the implementation of an alcoholic beverage classification system based on a pretrained LDA model demonstrated the feasibility of real-time classification using the proposed system.
Collapse
Affiliation(s)
- Sang Woo Lee
- Department of Smart Health Science and Technology, Kangwon National University, Chuncheon, Gangwon-do, Republic of Korea.
- Department of Mechatronics Engineering, Kangwon National University, Chuncheon, Gangwon-do, Republic of Korea
| | - Jeong Ah Yoon
- Department of Food Biotechnology and Environmental Science, Kangwon National University, Chuncheon, Gangwon-do, Republic of Korea
| | - Myoung Dong Kim
- Department of Food Science and Biotechnology, Kangwon National University, Chuncheon, Gangwon-do, Republic of Korea
| | - Byeong Hee Kim
- Department of Smart Health Science and Technology, Kangwon National University, Chuncheon, Gangwon-do, Republic of Korea.
- Department of Mechatronics Engineering, Kangwon National University, Chuncheon, Gangwon-do, Republic of Korea
| | - Young Ho Seo
- Department of Smart Health Science and Technology, Kangwon National University, Chuncheon, Gangwon-do, Republic of Korea.
- Department of Mechatronics Engineering, Kangwon National University, Chuncheon, Gangwon-do, Republic of Korea
| |
Collapse
|
2
|
Madhubhashini MN, Liyanage CP, Alahakoon AU, Liyanage RP. Current applications and future trends of artificial senses in fish freshness determination: A review. J Food Sci 2024; 89:33-50. [PMID: 38051021 DOI: 10.1111/1750-3841.16865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/16/2023] [Accepted: 11/16/2023] [Indexed: 12/07/2023]
Abstract
Fish is a highly demanding food product and the determination of fish freshness is crucial as it is a fundamental factor in fish quality. Therefore, the fishery industry has been working on developing rapid fish freshness determination methods to monitor freshness levels. Artificial senses that mimic human senses are developed as convenient emerging technologies for fish freshness determination. Computer vision, electronic nose (e-nose), and electronic tongue (e-tongue) are the emerging artificial senses for fish freshness determination. This review article is uniquely worked upon to investigate the current applications of the artificial senses in fish freshness determination while describing the steps, and fundamental principles behind each artificial sense, comparing them with their advantages and limitations, and future trends related to fish freshness determination. Among the artificial senses, computer vision determines the freshness of fish in a completely nondestructive way while the e-tongue determines the freshness of fish in a completely destructive way. There are developed e-noses for fish freshness determination in both destructive and nondestructive ways. By analyzing visual cues such as color, computer vision systems can assess fish quality without the need for physical contact and it makes computer vision suitable for large-scale industrial fish quality assessing applications. Overall, this review study reveals artificial senses as a proven replacement for traditional sensory panels in determining fish freshness precisely and conveniently. As future trends, there is a demand for developing applications for consumers to determine fish freshness based on artificial senses.
Collapse
Affiliation(s)
- M Nerandi Madhubhashini
- Department of Information and Communication Technology, Faculty of Technology, University of Sri Jayewardenepura, Nugegoda, Sri Lanka
| | - Chamara P Liyanage
- Department of Information and Communication Technology, Faculty of Technology, University of Sri Jayewardenepura, Nugegoda, Sri Lanka
| | - Amali U Alahakoon
- Department of Biosystems Technology, Faculty of Technology, University of Sri Jayewardenepura, Nugegoda, Sri Lanka
| | - Rumesh Prasanga Liyanage
- Department of Biosystems Technology, Faculty of Technology, University of Sri Jayewardenepura, Nugegoda, Sri Lanka
| |
Collapse
|
3
|
Lee SW, Kim BH, Seo YH. Olfactory system-inspired electronic nose system using numerous low-cost homogenous and hetrogenous sensors. PLoS One 2023; 18:e0295703. [PMID: 38064527 PMCID: PMC10707488 DOI: 10.1371/journal.pone.0295703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Accepted: 11/27/2023] [Indexed: 12/18/2023] Open
Abstract
This paper presents an electronic nose system inspired by the biological olfactory system. When comparing the human olfactory system to that of a dog, it's worth noting that dogs have 30 times more olfactory receptors and three times as many types of olfactory receptors. This implies that the number of olfactory receptors could be a more important parameter for classifying chemical compounds than the number of receptor types. Instead of using expensive precision sensors, the proposed electronic nose system relies on numerous low-cost homogeneous and heterogeneous sensors with poor cross-interference characteristics due to their low gas selectivity. Even if the same type of sensor shows a slightly different output for the same chemical compound, this variation becomes a unique signal for the target gas being measured. The electronic nose system comprises 30 sensors, the e-nose had 6 differing sensors with 5 replicates of each type. The characteristics of the electronic nose system are evaluated using three different volatile alcoholic compounds, more than 99% of which are the same. Liquid samples are supplied to the sensor chamber for 60 seconds using an air bubbler, followed by a 60-second cleaning of the chamber. Sensor signals are acquired at a sampling rate of 100 Hz. In this experimental study, the effects of data preprocessing methods and the number of sensors of the same type are investigated. By increasing the number of sensors of the same type, classification accuracy exceeds 99%, regardless of the deep learning model. The proposed electronic nose system, based on low-cost sensors, demonstrates similar results to commercial expensive electronic nose systems.
Collapse
Affiliation(s)
- Sang Woo Lee
- Department of Smart Health Science and Technology, Kangwon National University, Chuncheon, Gangwon-do, Republic of Korea
- Department of Mechatronics Engineering, Kangwon National University, Chuncheon, Gangwon-do, Republic of Korea
| | - Byeong Hee Kim
- Department of Smart Health Science and Technology, Kangwon National University, Chuncheon, Gangwon-do, Republic of Korea
- Department of Mechatronics Engineering, Kangwon National University, Chuncheon, Gangwon-do, Republic of Korea
| | - Young Ho Seo
- Department of Smart Health Science and Technology, Kangwon National University, Chuncheon, Gangwon-do, Republic of Korea
- Department of Mechatronics Engineering, Kangwon National University, Chuncheon, Gangwon-do, Republic of Korea
| |
Collapse
|
4
|
Vinicius da Silva Ferreira M, Barbosa JL, Kamruzzaman M, Barbin DF. Low-cost electronic-nose (LC-e-nose) systems for the evaluation of plantation and fruit crops: recent advances and future trends. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2023; 15:6120-6138. [PMID: 37937362 DOI: 10.1039/d3ay01192e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2023]
Abstract
An electronic nose (e-nose) is a device designed to recognize and classify odors. The equipment is built around a series of sensors that detect the presence of odors, especially volatile organic compounds (VOCs), and generate an electric signal (voltage), known as e-nose data, which contains chemical information. In the food business, the use of e-noses for analyses and quality control of fruits and plantation crops has increased in recent years. Their use is particularly relevant due to the lack of non-invasive and inexpensive methods to detect VOCs in crops. However, the majority of reports in the literature involve commercial e-noses, with only a few studies addressing low-cost e-nose (LC-e-nose) devices or providing a data-oriented description to assist researchers in choosing their setup and appropriate statistical methods to analyze crop data. Therefore, the objective of this study is to discuss the hardware of the two most common e-nose sensors: electrochemical (EC) sensors and metal oxide sensors (MOSs), as well as a critical review of the literature reporting MOS-based low-cost e-nose devices used for investigating plantations and fruit crops, including the main features of such devices. Miniaturization of equipment from lab-scale to portable and convenient gear, allowing producers to take it into the field, as shown in many appraised systems, is one of the future advancements in this area. By utilizing the low-cost designs provided in this review, researchers can develop their own devices based on practical demands such as quality control and compare results with those reported in the literature. Overall, this review thoroughly discusses the applications of low-cost e-noses based on MOSs for fruits, tea, and coffee, as well as the key features of their equipment (i.e., advantages and disadvantages) based on their technical parameters (i.e., electronic and physical parts). As a final remark, LC-e-nose technology deserves significant attention as it has the potential to be a valuable quality control tool for emerging countries.
Collapse
Affiliation(s)
- Marcus Vinicius da Silva Ferreira
- Universidade Federal Rural do Rio de Janeiro (UFRRJ), Departamento de Tecnologia de Alimentos, Seropédica 23890-000, Rio de Janeiro, Brazil.
- Department of Agriculture and Biological Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Jose Lucena Barbosa
- Universidade Federal Rural do Rio de Janeiro (UFRRJ), Departamento de Tecnologia de Alimentos, Seropédica 23890-000, Rio de Janeiro, Brazil.
| | - Mohammed Kamruzzaman
- Department of Agriculture and Biological Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Douglas Fernandes Barbin
- Department of Food Engineering and Technology, School of Food Engineering, University of Campinas, Campinas, SP, Brazil
| |
Collapse
|
5
|
Poeta E, Liboà A, Mistrali S, Núñez-Carmona E, Sberveglieri V. Nanotechnology and E-Sensing for Food Chain Quality and Safety. SENSORS (BASEL, SWITZERLAND) 2023; 23:8429. [PMID: 37896524 PMCID: PMC10610592 DOI: 10.3390/s23208429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [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
|
6
|
Im H, Choi J, Lee H, Al Balushi ZY, Park DH, Kim S. Colorimetric Multigas Sensor Arrays and an Artificial Olfactory Platform for Volatile Organic Compounds. ACS Sens 2023; 8:3370-3379. [PMID: 37642461 DOI: 10.1021/acssensors.3c00350] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Herein, we develop colorimetric multigas sensor arrays assembling chemo-reactive fluorescent patch arrays and 10 × 10 indium gallium zinc oxide phototransistor arrays and apply them to an artificial olfactory platform to recognize five different volatile organic compounds (VOCs). Porous nanofibers, coupled with two organic emitters and emitting fluorescence, rapidly respond to gas-phased VOCs and offer unique fluorescent patterns associated with particular gas conditions, including gas kinds, concentrations, and exposure times by forming patch arrays with different fluorophore component ratios. These VOC-induced fluorescent patterns could be quantified and amplified by indium gallium zinc oxide (IGZO) phototransistor arrays functioning as a signal-generating component, resulting in gas-fingerprint patterns regarding electrical signals. Thus, the pattern library associated with VOCs and their concentration enables us to determine each airborne analyte as the artificial olfactory platform. Therefore, this system could achieve rapid, early quantitative recognition of hazardous gases and be applied as a preventative, portable, and wearable multigas identifier in various fields.
Collapse
Affiliation(s)
- Healin Im
- Department of Materials Science and Engineering, University of California, Berkeley, California 94720, United States
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon-Si, Gyeonggi-do 16419, Republic of Korea
| | - Jinho Choi
- Department of Chemical Engineering, Inha University, Incheon 22212, Republic of Korea
- Program in Biomedical Science and Engineering, Inha University, Incheon 22212, Republic of Korea
| | - Hyeyun Lee
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon-Si, Gyeonggi-do 16419, Republic of Korea
| | - Zakaria Y Al Balushi
- Department of Materials Science and Engineering, University of California, Berkeley, California 94720, United States
| | - Dong-Hyuk Park
- Department of Chemical Engineering, Inha University, Incheon 22212, Republic of Korea
- Program in Biomedical Science and Engineering, Inha University, Incheon 22212, Republic of Korea
| | - Sunkook Kim
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon-Si, Gyeonggi-do 16419, Republic of Korea
| |
Collapse
|
7
|
Meléndez F, Sánchez R, Fernández JÁ, Belacortu Y, Bermúdez F, Arroyo P, Martín-Vertedor D, Lozano J. Design of a Multisensory Device for Tomato Volatile Compound Detection Based on a Mixed Metal Oxide-Electrochemical Sensor Array and Optical Reader. MICROMACHINES 2023; 14:1761. [PMID: 37763924 PMCID: PMC10537342 DOI: 10.3390/mi14091761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 09/04/2023] [Accepted: 09/08/2023] [Indexed: 09/29/2023]
Abstract
Insufficient control of tomato ripening before harvesting and infection by fungal pests produce large economic losses in world tomato production. Aroma is an indicative parameter of the state of maturity and quality of the tomato. This study aimed to design an electronic system (TOMATO-NOSE) consisting of an array of 12 electrochemical sensors, commercial metal oxide semiconductor sensors, an optical camera for a lateral flow reader, and a smartphone application for device control and data storage. The system was used with tomatoes in different states of ripeness and health, as well as tomatoes infected with Botrytis cinerea. The results obtained through principal component analysis of the olfactory pattern of tomatoes and the reader images show that TOMATO-NOSE is a good tool for the farmer to control tomato ripeness before harvesting and for the early detection of Botrytis cinerea.
Collapse
Affiliation(s)
- Félix Meléndez
- Industrial Engineering School, University of Extremadura, 06006 Badajoz, Spain; (F.M.); (J.Á.F.); (P.A.)
- Alianza Nanotecnología Diagnóstica ASJ S.L. (ANT), 28703 San Sebastián de los Reyes, Spain; (Y.B.); (F.B.)
| | - Ramiro Sánchez
- Centro de Investigaciones Científicas y Tecnológicas de Extremadura (CICYTEX), 06006 Badajoz, Spain; (R.S.); (D.M.-V.)
| | - Juan Álvaro Fernández
- Industrial Engineering School, University of Extremadura, 06006 Badajoz, Spain; (F.M.); (J.Á.F.); (P.A.)
| | - Yaiza Belacortu
- Alianza Nanotecnología Diagnóstica ASJ S.L. (ANT), 28703 San Sebastián de los Reyes, Spain; (Y.B.); (F.B.)
| | - Francisco Bermúdez
- Alianza Nanotecnología Diagnóstica ASJ S.L. (ANT), 28703 San Sebastián de los Reyes, Spain; (Y.B.); (F.B.)
| | - Patricia Arroyo
- Industrial Engineering School, University of Extremadura, 06006 Badajoz, Spain; (F.M.); (J.Á.F.); (P.A.)
| | - Daniel Martín-Vertedor
- Centro de Investigaciones Científicas y Tecnológicas de Extremadura (CICYTEX), 06006 Badajoz, Spain; (R.S.); (D.M.-V.)
| | - Jesús Lozano
- Industrial Engineering School, University of Extremadura, 06006 Badajoz, Spain; (F.M.); (J.Á.F.); (P.A.)
| |
Collapse
|
8
|
Xing Z, Zogona D, Wu T, Pan S, Xu X. Applications, challenges and prospects of bionic nose in rapid perception of volatile organic compounds of food. Food Chem 2023; 415:135650. [PMID: 36868065 DOI: 10.1016/j.foodchem.2023.135650] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 01/27/2023] [Accepted: 02/05/2023] [Indexed: 02/11/2023]
Abstract
Bionic nose, a technology that mimics the human olfactory system, has been widely used to assess food quality due to their high sensitivity, low cost, portability and simplicity. This review briefly describes that bionic noses with multiple transduction mechanisms are developed based on gas molecules' physical properties: electrical conductivity, visible optical absorption, and mass sensing. To enhance their superior sensing performance and meet the growing demand for applications, a range of strategies have been developed, such as peripheral substitutions, molecular backbones, and ligand metals that can finely tune the properties of sensitive materials. In addition, challenges and prospects coexist are covered. Cross-selective receptors of bionic nose will help and guide the selection of the best array for a particular application scenario. It provides an odour-based monitoring tool for rapid, reliable and online assessment of food safety and quality.
Collapse
Affiliation(s)
- Zheng Xing
- Key Laboratory of Environment Correlative Dietology (Ministry of Education), Huazhong Agricultural University, Wuhan, Hubei 430072, China; Hubei Key Laboratory of Fruit & Vegetable Processing & Quality Control, Huazhong Agricultural University, Wuhan, Hubei 430072, China; Shenzhen Institute of Nutrition and Health, Shenzhen, Guangdong 518038, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture,Genome Analysis Laboratory of the Ministry of Agriculture,Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong 518038, China
| | - Daniel Zogona
- Key Laboratory of Environment Correlative Dietology (Ministry of Education), Huazhong Agricultural University, Wuhan, Hubei 430072, China; Hubei Key Laboratory of Fruit & Vegetable Processing & Quality Control, Huazhong Agricultural University, Wuhan, Hubei 430072, China
| | - Ting Wu
- Key Laboratory of Environment Correlative Dietology (Ministry of Education), Huazhong Agricultural University, Wuhan, Hubei 430072, China; Hubei Key Laboratory of Fruit & Vegetable Processing & Quality Control, Huazhong Agricultural University, Wuhan, Hubei 430072, China
| | - Siyi Pan
- Key Laboratory of Environment Correlative Dietology (Ministry of Education), Huazhong Agricultural University, Wuhan, Hubei 430072, China; Hubei Key Laboratory of Fruit & Vegetable Processing & Quality Control, Huazhong Agricultural University, Wuhan, Hubei 430072, China
| | - Xiaoyun Xu
- Key Laboratory of Environment Correlative Dietology (Ministry of Education), Huazhong Agricultural University, Wuhan, Hubei 430072, China; Hubei Key Laboratory of Fruit & Vegetable Processing & Quality Control, Huazhong Agricultural University, Wuhan, Hubei 430072, China; Shenzhen Institute of Nutrition and Health, Shenzhen, Guangdong 518038, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture,Genome Analysis Laboratory of the Ministry of Agriculture,Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong 518038, China.
| |
Collapse
|
9
|
Viciano-Tudela S, Parra L, Navarro-Garcia P, Sendra S, Lloret J. Proposal of a New System for Essential Oil Classification Based on Low-Cost Gas Sensor and Machine Learning Techniques. SENSORS (BASEL, SWITZERLAND) 2023; 23:5812. [PMID: 37447662 DOI: 10.3390/s23135812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 06/13/2023] [Accepted: 06/20/2023] [Indexed: 07/15/2023]
Abstract
Essential oils are valuable in various industries, but their easy adulteration can cause adverse health effects. Electronic nasal sensors offer a solution for adulteration detection. This article proposes a new system for characterising essential oils based on low-cost sensor networks and machine learning techniques. The sensors used belong to the MQ family (MQ-2, MQ-3, MQ-4, MQ-5, MQ-6, MQ-7, and MQ-8). Six essential oils were used, including Cistus ladanifer, Pinus pinaster, and Cistus ladanifer oil adulterated with Pinus pinaster, Melaleuca alternifolia, tea tree, and red fruits. A total of up to 7100 measurements were included, with more than 118 h of measurements of 33 different parameters. These data were used to train and compare five machine learning algorithms: discriminant analysis, support vector machine, k-nearest neighbours, neural network, and naive Bayesian when the data were used individually or when hourly mean values were included. To evaluate the performance of the included machine learning algorithms, accuracy, precision, recall, and F1-score were considered. The study found that using k-nearest neighbours, accuracy, recall, F1-score, and precision values were 1, 0.99, 0.99, and 1, respectively. The accuracy reached 100% with k-nearest neighbours using only 2 parameters for averaged data or 15 parameters for individual data.
Collapse
Affiliation(s)
- Sandra Viciano-Tudela
- Instituto de Investigación para la Gestión Integrada de Zonas Costeras, Universitat Politècnica de València, C/Paranimf, 1, 46730 Gandia, Spain
| | - Lorena Parra
- Instituto de Investigación para la Gestión Integrada de Zonas Costeras, Universitat Politècnica de València, C/Paranimf, 1, 46730 Gandia, Spain
| | - Paula Navarro-Garcia
- Instituto de Investigación para la Gestión Integrada de Zonas Costeras, Universitat Politècnica de València, C/Paranimf, 1, 46730 Gandia, Spain
| | - Sandra Sendra
- Instituto de Investigación para la Gestión Integrada de Zonas Costeras, Universitat Politècnica de València, C/Paranimf, 1, 46730 Gandia, Spain
| | - Jaime Lloret
- Instituto de Investigación para la Gestión Integrada de Zonas Costeras, Universitat Politècnica de València, C/Paranimf, 1, 46730 Gandia, Spain
| |
Collapse
|
10
|
Peters R, Beijer N, 't Hul BV, Bruijns B, Munniks S, Knotter J. Evaluation of a Commercial Electronic Nose Based on Carbon Nanotube Chemiresistors. SENSORS (BASEL, SWITZERLAND) 2023; 23:s23115302. [PMID: 37300031 DOI: 10.3390/s23115302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 05/23/2023] [Accepted: 06/01/2023] [Indexed: 06/12/2023]
Abstract
Recently a hand-held, carbon-nanotube-based electronic nose became available on the market. Such an electronic nose could be interesting for applications in the food industry, health monitoring, environmental monitoring, and security services. However, not much is known about the performance of such an electronic nose. In a series of measurements, the instrument was exposed to low ppm vapor concentrations of four volatile organic compounds with different scent profiles and polarities. Detection limits, linearity of response, repeatability, reproducibility, and scent patterns were determined. The results indicate detection limits in the range of 0.1-0.5 ppm and a linear signal response in the range of 0.5-8.0 ppm. The repeatability of the scent patterns at compound concentrations of 2 ppm allowed the identification of the tested volatiles based on their scent pattern. However, the reproducibility was not sufficient, since different scent profiles were produced on different measurement days. In addition, it was noted that the response of the instrument diminished over time (over several months) possibly by sensor poisoning. The latter two aspects limit the use of the current instrument and make future improvements necessary.
Collapse
Affiliation(s)
- Ruud Peters
- Lectorate Technologies for Criminal Investigations, Saxion University of Applied Sciences, Handelskade 75, 7417 DH Deventer, The Netherlands
| | - Niels Beijer
- Lectorate Technologies for Criminal Investigations, Saxion University of Applied Sciences, Handelskade 75, 7417 DH Deventer, The Netherlands
| | - Bauke van 't Hul
- Academy of Applied Biosciences and Chemistry, HAN University of Applied Sciences, Laan van Scheut 2, 6525 EM Nijmegen, The Netherlands
| | - Brigitte Bruijns
- Lectorate Technologies for Criminal Investigations, Saxion University of Applied Sciences, Handelskade 75, 7417 DH Deventer, The Netherlands
| | - Sandra Munniks
- Wageningen Food Safety Research, Wageningen University and Research, Akkermaalsbos 2, 6708 WB Wageningen, The Netherlands
| | - Jaap Knotter
- Lectorate Technologies for Criminal Investigations, Saxion University of Applied Sciences, Handelskade 75, 7417 DH Deventer, The Netherlands
- Dutch Police Academy, Arnhemseweg 348, 7334 AC Apeldoorn, The Netherlands
| |
Collapse
|
11
|
Osmólska E, Stoma M, Starek-Wójcicka A. Juice Quality Evaluation with Multisensor Systems-A Review. SENSORS (BASEL, SWITZERLAND) 2023; 23:4824. [PMID: 37430738 DOI: 10.3390/s23104824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 05/10/2023] [Accepted: 05/15/2023] [Indexed: 07/12/2023]
Abstract
E-nose and e-tongue are advanced technologies that allow for the fast and precise analysis of smells and flavours using special sensors. Both technologies are widely used, especially in the food industry, where they are implemented, e.g., for identifying ingredients and product quality, detecting contamination, and assessing their stability and shelf life. Therefore, the aim of this article is to provide a comprehensive review of the application of e-nose and e-tongue in various industries, focusing in particular on the use of these technologies in the fruit and vegetable juice industry. For this purpose, an analysis of research carried out worldwide over the last five years, concerning the possibility of using the considered multisensory systems to test the quality and taste and aroma profiles of juices is included. In addition, the review contains a brief characterization of these innovative devices through information such as their origin, mode of operation, types, advantages and disadvantages, challenges and perspectives, as well as the possibility of their applications in other industries besides the juice industry.
Collapse
Affiliation(s)
- Emilia Osmólska
- Department of Power Engineering and Transportation, Faculty of Production Engineering, University of Life Sciences in Lublin, 20-612 Lublin, Poland
| | - Monika Stoma
- Department of Power Engineering and Transportation, Faculty of Production Engineering, University of Life Sciences in Lublin, 20-612 Lublin, Poland
| | - Agnieszka Starek-Wójcicka
- Department of Biological Bases of Food and Feed Technologies, Faculty of Production Engineering, University of Life Sciences in Lublin, 20-612 Lublin, Poland
| |
Collapse
|
12
|
Wu C, Li J. Portable FBAR based E-nose for cold chain real-time bananas shelf time detection. NANOTECHNOLOGY AND PRECISION ENGINEERING 2023. [DOI: 10.1063/10.0016870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Being cheap, nondestructive, and easy to use, gas sensors play important roles in the food industry. However, most gas sensors are suitable more for laboratory-quality fast testing rather than for cold-chain continuous and cumulative testing. Also, an ideal electronic nose (E-nose) in a cold chain should be stable to its surroundings and remain highly accurate and portable. In this work, a portable film bulk acoustic resonator (FBAR)-based E-nose was built for real-time measurement of banana shelf time. The sensor chamber to contain the portable circuit of the E-nose is as small as a smartphone, and by introducing an air-tight FBAR as a reference, the E-nose can avoid most of the drift caused by surroundings. With the help of porous layer by layer (LBL) coating of the FBAR, the sensitivity of the E-nose is 5 ppm to ethylene and 0.5 ppm to isoamyl acetate and isoamyl butyrate, while the detection range is large enough to cover a relative humidity of 0.8. In this regard, the E-nose can easily discriminate between yellow bananas with green necks and entirely yellow bananas while allowing the bananas to maintain their biological activities in their normal storage state, thereby showing the possibility of real-time shelf time detection. This portable FBAR-based E-nose has a large testing scale, high sensitivity, good humidity tolerance, and low frequency drift to its surroundings, thereby meeting the needs of cold-chain usage.
Collapse
Affiliation(s)
- Chen Wu
- Frontier Science Center for Smart Materials, College of Chemical Engineering, Dalian University of Technology, Dalian 116024, China
| | - Jiuyan Li
- Frontier Science Center for Smart Materials, College of Chemical Engineering, Dalian University of Technology, Dalian 116024, China
- Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing, Yantai Economic and Technological Development Zone, 300 Changjiang Road, Yantai, China
| |
Collapse
|
13
|
Neo YT, Chia WY, Lim SS, Ngan CL, Kurniawan TA, Chew KW. Smart systems in producing algae-based protein to improve functional food ingredients industries. Food Res Int 2023; 165:112480. [PMID: 36869493 DOI: 10.1016/j.foodres.2023.112480] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 12/29/2022] [Accepted: 01/11/2023] [Indexed: 01/15/2023]
Abstract
Production and extraction systems of algal protein and handling process of functional food ingredients need to control several parameters such as temperature, pH, intensity, and turbidity. Many researchers have investigated the Internet of Things (IoT) approach for enhancing the yield of microalgae biomass and machine learning for identifying and classifying microalgae. However, there have been few specific studies on using IoT and artificial intelligence (AI) for production and extraction of algal protein as well as functional food ingredients processing. In order to improve the production of algal protein and functional food ingredients, the implementation of smart system is a must to have real-time monitoring, remote control system, quick response to sudden events, prediction and characterisation. Techniques of IoT and AI are expected to help functional food industries to have a big breakthrough in the future. Manufacturing and implementation of beneficial smart systems are important to provide convenience and to increase the efficiency of work by using the interconnectivity of IoT devices to have good capturing, processing, archiving, analyzing, and automation. This review investigates the possibilities of implementation of IoT and AI in production and extraction of algal protein and processing of functional food ingredients.
Collapse
Affiliation(s)
- Yi Ting Neo
- Department of Chemical and Environmental Engineering, Faculty of Science and Engineering, University of Nottingham Malaysia, Jalan Broga, 43500 Semenyih, Selangor Darul Ehsan, Malaysia
| | - Wen Yi Chia
- Department of Chemical and Environmental Engineering, Faculty of Science and Engineering, University of Nottingham Malaysia, Jalan Broga, 43500 Semenyih, Selangor Darul Ehsan, Malaysia
| | - Siew Shee Lim
- Department of Chemical and Environmental Engineering, Faculty of Science and Engineering, University of Nottingham Malaysia, Jalan Broga, 43500 Semenyih, Selangor Darul Ehsan, Malaysia
| | - Cheng Loong Ngan
- School of Energy and Chemical Engineering, Xiamen University Malaysia, Jalan Sunsuria, Bandar Sunsuria, 43900 Sepang, Selangor Darul Ehsan, Malaysia
| | | | - Kit Wayne Chew
- School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, 62, Nanyang Drive, Singapore 637459, Singapore.
| |
Collapse
|
14
|
Epping R, Koch M. On-Site Detection of Volatile Organic Compounds (VOCs). Molecules 2023; 28:1598. [PMID: 36838585 PMCID: PMC9966347 DOI: 10.3390/molecules28041598] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 02/03/2023] [Accepted: 02/05/2023] [Indexed: 02/11/2023] Open
Abstract
Volatile organic compounds (VOCs) are of interest in many different fields. Among them are food and fragrance analysis, environmental and atmospheric research, industrial applications, security or medical and life science. In the past, the characterization of these compounds was mostly performed via sample collection and off-site analysis with gas chromatography coupled to mass spectrometry (GC-MS) as the gold standard. While powerful, this method also has several drawbacks such as being slow, expensive, and demanding on the user. For decades, intense research has been dedicated to find methods for fast VOC analysis on-site with time and spatial resolution. We present the working principles of the most important, utilized, and researched technologies for this purpose and highlight important publications from the last five years. In this overview, non-selective gas sensors, electronic noses, spectroscopic methods, miniaturized gas chromatography, ion mobility spectrometry and direct injection mass spectrometry are covered. The advantages and limitations of the different methods are compared. Finally, we give our outlook into the future progression of this field of research.
Collapse
Affiliation(s)
- Ruben Epping
- Division of Organic Trace and Food Analysis, Bundesanstalt für Materialforschung und -Prüfung, 12489 Berlin, Germany
| | - Matthias Koch
- Division of Organic Trace and Food Analysis, Bundesanstalt für Materialforschung und -Prüfung, 12489 Berlin, Germany
| |
Collapse
|
15
|
Lu L, Hu Z, Hu X, Li D, Tian S. Electronic tongue and electronic nose for food quality and safety. Food Res Int 2022; 162:112214. [DOI: 10.1016/j.foodres.2022.112214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 11/02/2022] [Accepted: 11/15/2022] [Indexed: 11/18/2022]
|
16
|
Prasad P, Raut P, Goel S, Barnwal RP, Bodhe GL. Electronic nose and wireless sensor network for environmental monitoring application in pulp and paper industry: a review. ENVIRONMENTAL MONITORING AND ASSESSMENT 2022; 194:855. [PMID: 36207610 DOI: 10.1007/s10661-022-10479-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 09/10/2022] [Indexed: 06/16/2023]
Abstract
Pulp and paper industries emit various odorous gases during the pulp production and paper-making phase, which are unpleasant and have harmful effects on the human body. The working staffs are continuously exposed to these gases and develop various health issues. Hence, regular monitoring and analysis of such gases are necessary to avoid any sudden high concentration exposure and to prevent adverse health effects on the staff. An electronic nose (EN) has an array of gas sensors with an alert system for early detection of gases. Various ENs have been developed for varying applications till date. The detailed knowledge of the sensors used, their sensitivity and technology is helpful in development of any EN. The objective of this study is to comprehensively review various developed ENs with respect to their gas sensing and pattern recognition (PR) technologies. The information on gases released from pulp and paper industries is also compiled. The evolution of EN technology, its various applications, challenges in developing EN and its utility in safeguarding the industrial workers' life have been described. Further, gap analysis among previously developed EN, contemporary EN and wireless sensor network (WSN) is elaborated. It will facilitate future researchers for better selection of sensors and PR technologies while developing EN. The commonly used sensing technologies are described with their advantages, disadvantages and working principles. Metal oxide semiconductor (MOS) gas sensor and ANN algorithm show better result and hence recommended in the development of EN, whereas ZigBee protocol has been widely used for WSN.
Collapse
Affiliation(s)
- Poonam Prasad
- Cleaner Technology and Modelling Division, CSIR-National Environmental Engineering Research Institute, Nagpur, MS, India.
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.
| | - Piyush Raut
- Cleaner Technology and Modelling Division, CSIR-National Environmental Engineering Research Institute, Nagpur, MS, India
| | - Sangita Goel
- Environmental Audit and Policy Implementation Division, CSIR-National Environmental Engineering Research Institute, Nagpur, MS, India
| | - Rajesh P Barnwal
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
- Information Technology Division, CSIR-Central Mechanical Engineering Research Institute, Durgapur, WB, India
| | - G L Bodhe
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
- Quality Management System Division, CSIR-National Environmental Engineering Research Institute, Nagpur, MS, India
| |
Collapse
|
17
|
Fast and noninvasive electronic nose for sniffing out COVID-19 based on exhaled breath-print recognition. NPJ Digit Med 2022; 5:115. [PMID: 35974062 PMCID: PMC9379872 DOI: 10.1038/s41746-022-00661-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Accepted: 07/22/2022] [Indexed: 12/25/2022] Open
Abstract
The reverse transcription-quantitative polymerase chain reaction (RT-qPCR) approach has been widely used to detect the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, instead of using it alone, clinicians often prefer to diagnose the coronavirus disease 2019 (COVID-19) by utilizing a combination of clinical signs and symptoms, laboratory test, imaging measurement (e.g., chest computed tomography scan), and multivariable clinical prediction models, including the electronic nose. Here, we report on the development and use of a low cost, noninvasive method to rapidly sniff out COVID-19 based on a portable electronic nose (GeNose C19) integrating an array of metal oxide semiconductor gas sensors, optimized feature extraction, and machine learning models. This approach was evaluated in profiling tests involving a total of 615 breath samples composed of 333 positive and 282 negative samples. The samples were obtained from 43 positive and 40 negative COVID-19 patients, respectively, and confirmed with RT-qPCR at two hospitals located in the Special Region of Yogyakarta, Indonesia. Four different machine learning algorithms (i.e., linear discriminant analysis, support vector machine, stacked multilayer perceptron, and deep neural network) were utilized to identify the top-performing pattern recognition methods and to obtain a high system detection accuracy (88–95%), sensitivity (86–94%), and specificity (88–95%) levels from the testing datasets. Our results suggest that GeNose C19 can be considered a highly potential breathalyzer for fast COVID-19 screening.
Collapse
|
18
|
Shi T, Hussain S, Ge C, Liu G, Wang M, Qiao G. ZIF-X (8, 67) based nanostructures for gas-sensing applications. REV CHEM ENG 2022. [DOI: 10.1515/revce-2021-0100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Abstract
ZIF-8 and ZIF-67 are the most investigated zeolitic imidazolate frameworks (ZIFs) materials that have aroused enormous scientific interests in numerous areas of application including electrochemistry, gas storage, separation, and sensors by reason of their fascinating structural properties. Recently, there is a rapidly growing demand for chemical gas sensors for the detection of various analytes in widespread applications including environmental pollution monitoring, clinical analysis, wastewater analysis, industrial applications, food quality, consumer products, and automobiles. In general, the key to the development of superior gas sensors is exploring innovative sensing materials. ZIF-X (8, 67) based nanostructures have demonstrated great potential as ideal sensing materials for high-performance sensing applications. In this review, the general properties and applications of ZIF-X (8, 67) including gas storage and gas adsorption are first summarized, and then the recent progress of ZIF-X (8, 67) based nanostructures for gas-sensing applications and the structure-property correlations are summarized and analyzed.
Collapse
Affiliation(s)
- Tengfei Shi
- School of Materials Science and Engineering , Jiangsu University , Zhenjiang , 212013 , China
| | - Shahid Hussain
- School of Materials Science and Engineering , Jiangsu University , Zhenjiang , 212013 , China
| | - Chuanxin Ge
- School of Materials Science and Engineering , Jiangsu University , Zhenjiang , 212013 , China
| | - Guiwu Liu
- School of Materials Science and Engineering , Jiangsu University , Zhenjiang , 212013 , China
| | - Mingsong Wang
- School of Materials Science and Engineering , Jiangsu University , Zhenjiang , 212013 , China
| | - Guanjun Qiao
- School of Materials Science and Engineering , Jiangsu University , Zhenjiang , 212013 , China
- State Key Laboratory for Mechanical Behavior of Materials , Xi’an Jiaotong University , Xi’an 710049 , China
| |
Collapse
|
19
|
Abstract
This paper provides an overview of recent developments in the field of volatile organic compound (VOC) sensors, which are finding uses in healthcare, safety, environmental monitoring, food and agriculture, oil industry, and other fields. It starts by briefly explaining the basics of VOC sensing and reviewing the currently available and quickly progressing VOC sensing approaches. It then discusses the main trends in materials' design with special attention to nanostructuring and nanohybridization. Emerging sensing materials and strategies are highlighted and their involvement in the different types of sensing technologies is discussed, including optical, electrical, and gravimetric sensors. The review also provides detailed discussions about the main limitations of the field and offers potential solutions. The status of the field and suggestions of promising directions for future development are summarized.
Collapse
Affiliation(s)
- Muhammad Khatib
- Department of Chemical Engineering, Stanford University, Stanford, California 94305, United States
| | - Hossam Haick
- Department of Chemical Engineering and Russell Berrie Nanotechnology Institute, Technion-Israel Institute of Technology, Haifa 3200003, Israel
| |
Collapse
|
20
|
Meléndez F, Arroyo P, Gómez-Suárez J, Palomeque-Mangut S, Suárez JI, Lozano J. Portable Electronic Nose Based on Digital and Analog Chemical Sensors for 2,4,6-Trichloroanisole Discrimination. SENSORS (BASEL, SWITZERLAND) 2022; 22:3453. [PMID: 35591143 PMCID: PMC9102965 DOI: 10.3390/s22093453] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 04/25/2022] [Accepted: 04/28/2022] [Indexed: 06/15/2023]
Abstract
2,4,6-trichloroanisole (TCA) is mainly responsible for cork taint in wine, which causes significant economic losses; therefore, the wine and cork industries demand an immediate, economic, noninvasive and on-the-spot solution. In this work, we present a novel prototype of an electronic nose (e-nose) using an array of digital and analog metal-oxide gas sensors with a total of 31 signals, capable of detecting TCA, and classifying cork samples with low TCA concentrations (≤15.1 ng/L). The results show that the device responds to low concentrations of TCA in laboratory conditions. It also differentiates among the inner and outer layers of cork bark (81.5% success) and distinguishes among six different samples of granulated cork (83.3% success). Finally, the device can predict the concentration of a new sample within a ±10% error margin.
Collapse
Affiliation(s)
| | | | | | | | | | - Jesús Lozano
- Industrial Engineering School, University of Extremadura, 06006 Badajoz, Spain; (F.M.); (P.A.); (J.G.-S.); (S.P.-M.); (J.I.S.)
| |
Collapse
|
21
|
Zhang WL, Liu ZY, Liang K, Wang Y, Chen KF, Sun YW, Wang S. Experimental realization of visible gas sensing technology based on spatial heterodyne spectroscopy. Sci Rep 2022; 12:1423. [PMID: 35082371 PMCID: PMC8791975 DOI: 10.1038/s41598-022-05510-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 01/13/2022] [Indexed: 11/28/2022] Open
Abstract
Based on the characteristics of optical absorption gas sensing technology (OA-GST) and spatial heterodyne spectroscopy (SHS), a novel type of visual gas sensing technology (V-GST) can present the invisible gas information in the form of two-dimensional visual fingerprint, which has attracted people's attention. In this paper, we have realized the NO2 detection of V-GST in the laboratory environment for the first time. Experimental results show that: V-GST not only has different interferogram response to different spectra, but also has good response to different concentrations of NO2, which lays a foundation for the application of this technology in gas sensing. And the average classification recognition rate of the system for different band NO2 response data is over 80%, which verifies the effectiveness of the V-GST in gas detection.
Collapse
|
22
|
Qin P, Okur S, Li C, Chandresh A, Mutruc D, Hecht S, Heinke L. A photoprogrammable electronic nose with switchable selectivity for VOCs using MOF films. Chem Sci 2021; 12:15700-15709. [PMID: 35003601 PMCID: PMC8654041 DOI: 10.1039/d1sc05249g] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 11/12/2021] [Indexed: 02/02/2023] Open
Abstract
Advanced analytical applications require smart materials and sensor systems that are able to adapt or be configured to specific tasks. Based on reversible photochemistry in nanoporous materials, we present a sensor array with a selectivity that is reversibly controlled by light irradiation. The active material of the sensor array, or electronic nose (e-nose), is based on metal-organic frameworks (MOFs) with photoresponsive fluorinated azobenzene groups that can be optically switched between their trans and cis state. By irradiation with light of different wavelengths, the trans-cis ratio can be modulated. Here we use four trans-cis values as defined states and employ a four-channel quartz-crystal microbalance for gravimetrically monitoring the molecular uptake by the MOF films. We apply the photoprogrammable e-nose to the sensing of different volatile organic compounds (VOCs) and analyze the sensor array data with simple machine-learning algorithms. When the sensor array is in a state with all sensors either in the same trans- or cis-rich state, cross-sensitivity between the analytes occurs and the classification accuracy is not ideal. Remarkably, the VOC molecules between which the sensor array shows cross-sensitivity vary by switching the entire sensor array from trans to cis. By selectively programming the e-nose with light of different colors, each sensor exhibits a different isomer ratio and thus a different VOC affinity, based on the polarity difference between the trans- and cis-azobenzenes. In such photoprogrammed state, the cross-sensitivity is reduced and the selectivity is enhanced, so that the e-nose can perfectly identify the tested VOCs. This work demonstrates for the first time the potential of photoswitchable and thus optically configurable materials as active sensing material in an e-nose for intelligent molecular sensing. The concept is not limited to QCM-based azobenzene-MOF sensors and can also be applied to diverse sensing materials and photoswitches.
Collapse
Affiliation(s)
- Peng Qin
- Karlsruhe Institute of Technology (KIT), Institute of Functional Interfaces (IFG) Hermann-von-Helmholtz-Platz 1 76344 Eggenstein-Leopoldshafen Germany
| | - Salih Okur
- Karlsruhe Institute of Technology (KIT), Institute of Functional Interfaces (IFG) Hermann-von-Helmholtz-Platz 1 76344 Eggenstein-Leopoldshafen Germany
| | - Chun Li
- Karlsruhe Institute of Technology (KIT), Institute of Functional Interfaces (IFG) Hermann-von-Helmholtz-Platz 1 76344 Eggenstein-Leopoldshafen Germany
| | - Abhinav Chandresh
- Karlsruhe Institute of Technology (KIT), Institute of Functional Interfaces (IFG) Hermann-von-Helmholtz-Platz 1 76344 Eggenstein-Leopoldshafen Germany
| | - Dragos Mutruc
- Humboldt-Universität zu Berlin, Department of Chemistry & IRIS Adlershof Brook-Taylor-Strasse 2 12489 Berlin Germany
| | - Stefan Hecht
- Humboldt-Universität zu Berlin, Department of Chemistry & IRIS Adlershof Brook-Taylor-Strasse 2 12489 Berlin Germany
- DWI - Leibniz Institute for Interactive Materials Forckenbeckstr. 50 52074 Aachen Germany
- RWTH Aachen University, Institute of Technical and Macromolecular Chemistry Worringer Weg 2 52074 Aachen Germany
| | - Lars Heinke
- Karlsruhe Institute of Technology (KIT), Institute of Functional Interfaces (IFG) Hermann-von-Helmholtz-Platz 1 76344 Eggenstein-Leopoldshafen Germany
| |
Collapse
|
23
|
Zaki Dizaji H, Adibzadeh A, Aghili Nategh N. Application of E-nose technique to predict sugarcane syrup quality based on purity and refined sugar percentage. Journal of Food Science and Technology 2021; 58:4149-4156. [PMID: 34538899 DOI: 10.1007/s13197-020-04879-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Revised: 10/21/2020] [Accepted: 10/28/2020] [Indexed: 10/23/2022]
Abstract
Rapid test methods with portable devices along with standard chemical tests are necessary to determine raw syrup quality in the sugarcane agro-industries. On this account, a special e-nose device was developed to test the sugarcane syrup and its association with the odor emitted from it to determine the amount of sucrose (purity) in the sugarcane syrup. Samples were obtained from the farms of Hakim-Farabi agro-industry, including four varieties (CP57, CP69, IRC99-02, and CP48). Experiments included chemical tests to determine the percentage of purity (PTY) and refined sugar (RS) plus an electronic nose test. Partial least squares (PLS), principle component regression (PCR), multiple linear regression (MLR), and artificial neural network (ANN) methods were used to evaluate the correlation between the gained signals from the sensor array and chemical analysis results of the samples. In the case of PTY, among 8 sensors, MQ3, MQ5, and MQ9 had the highest response compared to the others, while regarding RS, all the sensors except for MQ8 indicated a great contribution. Also, all models for PTY and RS showed a good prediction performance. The results revealed that ANN model, with topology 8-1-2, outperformed others for prediction of the quality indices of sugarcane, with high correlation coefficients (R2 = 0.96 for RS; 0.99 for PTY), and relatively low RMSE values of 0.33 for RS; 0.4 for RTY. Finally, findings indicated that e-nose technique has the potential to become an authentic tool to assess chemical features of sugarcane syrup from e-nose system signals.
Collapse
Affiliation(s)
- Hassan Zaki Dizaji
- Department of Biosystems Engineering, Faculty of Agriculture, Shahid Chamran University of Ahvaz, Ahvaz, Iran
| | - Abdullah Adibzadeh
- Department of Biosystems Engineering, Faculty of Agriculture, Shahid Chamran University of Ahvaz, Ahvaz, Iran
| | - Nahid Aghili Nategh
- Department of Agricultural Machinery Engineering, Sonqor Agriculture Faculty, Razi University, Kermanshah, Iran
| |
Collapse
|
24
|
Abstract
The evaluation of volatiles in food is an important aspect of food production. It gives knowledge about the quality of foods and their relationship to consumers’ choices. Alcohols, aldehydes, acids, esters, terpenes, pyrazines, and furans are the main chemical groups that are involved in aroma formation. They are products of food processing: thermal treatment, fermentation, storage, etc. Food aroma is a mixture of varied molecules. Because of this, the analysis of aroma composition can be challenging. The four main steps can be distinguished in the evaluation of the volatiles in the food matrix as follows: (1) isolation and concentration; (2) separation; (3) identification; and (4) sensory characterization. The most commonly used techniques to separate a fraction of volatiles from non-volatiles are solid-phase micro-(SPME) and stir bar sorptive extractions (SBSE). However, to study the active components of food aroma by gas chromatography with olfactometry detector (GC-O), solvent-assisted flavor evaporation (SAFE) is used. The volatiles are mostly separated on GC systems (GC or comprehensive two-dimensional GCxGC) with the support of mass spectrometry (MS, MS/MS, ToF–MS) for chemical compound identification. Besides omics techniques, the promising part could be a study of aroma using electronic nose. Therefore, the main assumptions of volatolomics are here described.
Collapse
|
25
|
Single Nanowire Gas Sensor Able to Distinguish Fish and Meat and Evaluate Their Degree of Freshness. CHEMOSENSORS 2021. [DOI: 10.3390/chemosensors9090249] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
A non-invasive, small, and fast device is needed for food freshness monitoring, as current techniques do not meet these criteria. In this study, a resistive sensor composed of a single semiconductor nanowire was used at different temperatures, combining the responses and processing them with multivariate statistical analysis techniques. The sensor, very sensitive to ammonia and total volatile basic nitrogen, proved to be able to distinguish samples of fish (marble trout, Salmo trutta marmoratus) and meat (pork, Sus scrofa domesticus), both stored at room temperature and 4 °C in the refrigerator. Once separated, the fish and meat samples were classified by the degree of freshness/degradation with two different classifiers. The sensor classified the samples (trout and pork) correctly in 95.2% of cases. The degree of freshness was correctly assessed in 90.5% of cases. Considering only the errors with repercussions (when a fresh sample was evaluated as degraded, or a degraded sample was evaluated as edible) the accuracy increased to 95.2%. Considering the size (less than a square millimeter) and the speed (less than a minute), this type of sensor could be used to monitor food production and distribution chains.
Collapse
|
26
|
Mavani NR, Ali JM, Othman S, Hussain MA, Hashim H, Rahman NA. Application of Artificial Intelligence in Food Industry—a Guideline. FOOD ENGINEERING REVIEWS 2021. [PMCID: PMC8350558 DOI: 10.1007/s12393-021-09290-z] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Artificial intelligence (AI) has embodied the recent technology in the food industry over the past few decades due to the rising of food demands in line with the increasing of the world population. The capability of the said intelligent systems in various tasks such as food quality determination, control tools, classification of food, and prediction purposes has intensified their demand in the food industry. Therefore, this paper reviews those diverse applications in comparing their advantages, limitations, and formulations as a guideline for selecting the most appropriate methods in enhancing future AI- and food industry–related developments. Furthermore, the integration of this system with other devices such as electronic nose, electronic tongue, computer vision system, and near infrared spectroscopy (NIR) is also emphasized, all of which will benefit both the industry players and consumers.
Collapse
Affiliation(s)
- Nidhi Rajesh Mavani
- Department of Chemical and Process Engineering, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia, UKM, Selangor 43600 Bangi, Malaysia
| | - Jarinah Mohd Ali
- Department of Chemical and Process Engineering, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia, UKM, Selangor 43600 Bangi, Malaysia
| | - Suhaili Othman
- Department of Chemical and Process Engineering, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia, UKM, Selangor 43600 Bangi, Malaysia
- Department of Biological and Agricultural Engineering, Faculty of Engineering, Universiti Putra Malaysia, UPM Serdang, 43400 Selangor, Malaysia
| | - M. A. Hussain
- Department of Chemical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia
| | - Haslaniza Hashim
- Department of Food Sciences, Faculty of Science & Technology, Universiti Kebangsaan Malaysia, UKM, Selangor 43600 Bangi, Malaysia
| | - Norliza Abd Rahman
- Department of Chemical and Process Engineering, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia, UKM, Selangor 43600 Bangi, Malaysia
| |
Collapse
|
27
|
Sniff Species: SURMOF-Based Sensor Array Discriminates Aromatic Plants beyond the Genus Level. CHEMOSENSORS 2021. [DOI: 10.3390/chemosensors9070171] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Lamiaceae belong to the species-richest family of flowering plants and harbor many species that are used as herbs or in medicinal applications such as basils or mints. The evolution of this group has been driven by chemical speciation, mainly volatile organic compounds (VOCs). The commercial use of these plants is characterized by adulteration and surrogation to a large extent. Authenticating and discerning this species is thus relevant for consumer safety but usually requires cumbersome analytics, such as gas chromatography, often coupled with mass spectroscopy. Here, we demonstrate that quartz-crystal microbalance (QCM)-based electronic noses provide a very cost-efficient alternative, allowing for fast, automated discrimination of scents emitted from the leaves of different plants. To explore the range of this strategy, we used leaf material from four genera of Lamiaceae along with lemongrass, which is similarly scented but from an unrelated outgroup. To differentiate the scents from different plants unambiguously, the output of the six different SURMOF/QCM sensors was analyzed using machine learning (ML) methods together with a thorough statistical analysis. The exposure and purging of data sets (four cycles) obtained from a QCM-based, low-cost homemade portable e-Nose were analyzed using a linear discriminant analysis (LDA) classification model. Prediction accuracy with repeated test measurements reached values of up to 0%. We show that it is possible not only to discern and identify plants at the genus level but also to discriminate closely related sister clades within a genus (basil), demonstrating that an e-Nose is a powerful device that can safeguard consumer safety against dangers posed by globalized trade.
Collapse
|
28
|
Huang Y, Doh IJ, Bae E. Design and Validation of a Portable Machine Learning-Based Electronic Nose. SENSORS 2021; 21:s21113923. [PMID: 34200440 PMCID: PMC8201040 DOI: 10.3390/s21113923] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 06/03/2021] [Accepted: 06/04/2021] [Indexed: 11/16/2022]
Abstract
Volatile organic compounds (VOCs) are chemicals emitted by various groups, such as foods, bacteria, and plants. While there are specific pathways and biological features significantly related to such VOCs, detection of these is achieved mostly by human odor testing or high-end methods such as gas chromatography-mass spectrometry that can analyze the gaseous component. However, odor characterization can be quite helpful in the rapid classification of some samples in sufficient concentrations. Lower-cost metal-oxide gas sensors have the potential to allow the same type of detection with less training required. Here, we report a portable, battery-powered electronic nose system that utilizes multiple metal-oxide gas sensors and machine learning algorithms to detect and classify VOCs. An in-house circuit was designed with ten metal-oxide sensors and voltage dividers; an STM32 microcontroller was used for data acquisition with 12-bit analog-to-digital conversion. For classification of target samples, a supervised machine learning algorithm such as support vector machine (SVM) was applied to classify the VOCs based on the measurement results. The coefficient of variation (standard deviation divided by mean) of 8 of the 10 sensors stayed below 10%, indicating the excellent repeatability of these sensors. As a proof of concept, four different types of wine samples and three different oil samples were classified, and the training model reported 100% and 98% accuracy based on the confusion matrix analysis, respectively. When the trained model was challenged against new sets of data, sensitivity and specificity of 98.5% and 98.6% were achieved for the wine test and 96.3% and 93.3% for the oil test, respectively, when the SVM classifier was used. These results suggest that the metal-oxide sensors are suitable for usage in food authentication applications.
Collapse
|
29
|
Sempionatto JR, Montiel VRV, Vargas E, Teymourian H, Wang J. Wearable and Mobile Sensors for Personalized Nutrition. ACS Sens 2021; 6:1745-1760. [PMID: 34008960 DOI: 10.1021/acssensors.1c00553] [Citation(s) in RCA: 73] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
While wearable and mobile chemical sensors have experienced tremendous growth over the past decade, their potential for tracking and guiding nutrition has emerged only over the past three years. Currently, guidelines from doctors and dietitians represent the most common approach for maintaining optimal nutrition status. However, such recommendations rely on population averages and do not take into account individual variability in responding to nutrients. Precision nutrition has recently emerged to address the large heterogeneity in individuals' responses to diet, by tailoring nutrition based on the specific requirements of each person. It aims at preventing and managing diseases by formulating personalized dietary interventions to individuals on the basis of their metabolic profile, background, and environmental exposure. Recent advances in digital nutrition technology, including calories-counting mobile apps and wearable motion tracking devices, lack the ability of monitoring nutrition at the molecular level. The realization of effective precision nutrition requires synergy from different sensor modalities in order to make timely reliable predictions and efficient feedback. This work reviews key opportunities and challenges toward the successful realization of effective wearable and mobile nutrition monitoring platforms. Non-invasive wearable and mobile electrochemical sensors, capable of monitoring temporal chemical variations upon the intake of food and supplements, are excellent candidates to bridge the gap between digital and biochemical analyses for a successful personalized nutrition approach. By providing timely (previously unavailable) dietary information, such wearable and mobile sensors offer the guidance necessary for supporting dietary behavior change toward a managed nutritional balance. Coupling of the rapidly emerging wearable chemical sensing devices-generating enormous dynamic analytical data-with efficient data-fusion and data-mining methods that identify patterns and make predictions is expected to revolutionize dietary decision-making toward effective precision nutrition.
Collapse
Affiliation(s)
- Juliane R. Sempionatto
- Department of Nanoengineering, University of California San Diego, La Jolla, California 92093, United States
| | | | - Eva Vargas
- Department of Nanoengineering, University of California San Diego, La Jolla, California 92093, United States
| | - Hazhir Teymourian
- Department of Nanoengineering, University of California San Diego, La Jolla, California 92093, United States
| | - Joseph Wang
- Department of Nanoengineering, University of California San Diego, La Jolla, California 92093, United States
| |
Collapse
|
30
|
Zarezadeh MR, Aboonajmi M, Varnamkhasti MG, Azarikia F. Olive Oil Classification and Fraud Detection Using E-Nose and Ultrasonic System. FOOD ANAL METHOD 2021. [DOI: 10.1007/s12161-021-02035-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
|
31
|
Lee J, Boo C, Hong SJ, Shin EC. Chemosensory Device Assisted-Estimation of the Quality of Edible Oils with Repetitive Frying. Foods 2021; 10:foods10050972. [PMID: 33946677 PMCID: PMC8146517 DOI: 10.3390/foods10050972] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 04/26/2021] [Accepted: 04/27/2021] [Indexed: 11/16/2022] Open
Abstract
This study investigated chemosensory degradations of soybean and canola oils with repeated frying in order to estimate the quality of the oils. Methods: Chemical parameters including oxygen induction time, acid value, p-anisidine value, malondialdehyde, and total polar compounds were measured. Electronic nose and electronic tongue analyses were performed to assess sensory properties. Multivariate analyses were employed to investigate relationships among tastes and volatile compounds using principal component analysis (PCA) and Pearson’s correlation analysis. Results: All chemical parameters increased with repeated frying in both oils. Electronic nose analysis found ethyl butyrate, 2-heptenal, and 2,4-pentanedione as major volatiles for soybean oil and ethyl butyrate and linalool for canola oil. As the numbers of frying increased, all volatiles showed an increased concentration in various extents. In multivariate analyses, ethyl butyrate revealed strong positive correlations with sourness, umami, and sweetness, and umami showed strong positive correlations with sourness and saltiness (p < 0.05). PCA confirmed that in PC1 with 49% variance, sourness, saltiness, and umami were at similar rates while acetyl pyrazine, 2,4-pentadieone, and 1-octanol were found at similar rates. Canola oil was chemically more stable and less susceptible to deterioration in all chemical parameters compared to soybean oil, resulting in a relatively better quality oil when repeatedly fried. Conclusion: The results suggested that minimum repeated frying (5 times) degrades chemosensory characteristics of both oils, thereby compromising their quality. The findings of this study will be utilized as a foundation for quality control of fried foods in food industry, fried food development, and fast-food industry.
Collapse
Affiliation(s)
- Jookyeong Lee
- CASS Food Research Centre, School of Exercise and Nutrition Sciences, Faculty of Health, Deakin University, 221 Burwood Highway, Burwood, VIC 3125, Australia;
| | - Changguk Boo
- Department of Food Science/Institute for Food Sensory & Cognitive Science, Gyeongsang National University, Jinju, Gyeongnam 52725, Korea; (C.B.); (S.-j.H.)
| | - Seong-jun Hong
- Department of Food Science/Institute for Food Sensory & Cognitive Science, Gyeongsang National University, Jinju, Gyeongnam 52725, Korea; (C.B.); (S.-j.H.)
| | - Eui-Cheol Shin
- Department of Food Science/Institute for Food Sensory & Cognitive Science, Gyeongsang National University, Jinju, Gyeongnam 52725, Korea; (C.B.); (S.-j.H.)
- Correspondence: ; Tel.: +82-55-772-3271; Fax: +82-55-772-3279
| |
Collapse
|
32
|
Intelligent Packaging for Real-Time Monitoring of Food-Quality: Current and Future Developments. APPLIED SCIENCES-BASEL 2021. [DOI: 10.3390/app11083532] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Food packaging encompasses the topical role of preserving food, hence, extending the shelf-life, while ensuring the highest quality and safety along the production chain as well as during storage. Intelligent food packaging further develops the functions of traditional packages by introducing the capability of continuously monitoring food quality during the whole chain to assess and reduce the insurgence of food-borne disease and food waste. To this purpose, several sensing systems based on different food quality indicators have been proposed in recent years, but commercial applications remain a challenge. This review provides a critical summary of responsive systems employed in the real-time monitoring of food quality and preservation state. First, food quality indicators are briefly presented, and subsequently, their exploitation to fabricate intelligent packaging based on responsive materials is discussed. Finally, current challenges and future trends are reviewed to highlight the importance of concentrating efforts on developing new functional solutions.
Collapse
|
33
|
John AT, Murugappan K, Nisbet DR, Tricoli A. An Outlook of Recent Advances in Chemiresistive Sensor-Based Electronic Nose Systems for Food Quality and Environmental Monitoring. SENSORS (BASEL, SWITZERLAND) 2021; 21:2271. [PMID: 33804960 PMCID: PMC8036444 DOI: 10.3390/s21072271] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 03/16/2021] [Accepted: 03/17/2021] [Indexed: 01/05/2023]
Abstract
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.
Collapse
Affiliation(s)
- Alishba T. John
- Nanotechnology Research Laboratory, Research School of Chemistry, College of Science, The Australian National University, Canberra 2601, Australia;
| | - Krishnan Murugappan
- Nanotechnology Research Laboratory, Research School of Chemistry, College of Science, The Australian National University, Canberra 2601, Australia;
| | - David R. Nisbet
- Laboratory of Advanced Biomaterials, Research School of Chemistry and the John Curtin School of Medical Research, The Australian National University, Canberra 2601, Australia;
| | - Antonio Tricoli
- Nanotechnology Research Laboratory, Research School of Chemistry, College of Science, The Australian National University, Canberra 2601, Australia;
- Nanotechnology Research Laboratory, Faculty of Engineering, The University of Sydney, Camperdown 2006, Australia
| |
Collapse
|
34
|
Energy Harvesting Strategies for Wireless Sensor Networks and Mobile Devices: A Review. ELECTRONICS 2021. [DOI: 10.3390/electronics10060661] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Wireless sensor network nodes and mobile devices are normally powered by batteries that, when depleted, must be recharged or replaced. This poses important problems, in particular for sensor nodes that are placed in inaccessible areas or biomedical sensors implanted in the human body where the battery replacement is very impractical. Moreover, the depleted battery must be properly disposed of in accordance with national and international regulations to prevent environmental pollution. A very interesting alternative to power mobile devices is energy harvesting where energy sources naturally present in the environment (such as sunlight, thermal gradients and vibrations) are scavenged to provide the power supply for sensor nodes and mobile systems. Since the presence of these energy sources is discontinuous in nature, electronic systems powered by energy harvesting must include a power management system and a storage device to store the scavenged energy. In this paper, the main strategies to design a wireless mobile sensor system powered by energy harvesting are reviewed and different sensor systems powered by such energy sources are presented.
Collapse
|
35
|
Xu E, Pérez-Torres D, Fragkou PC, Zahar JR, Koulenti D. Nosocomial Pneumonia in the Era of Multidrug-Resistance: Updates in Diagnosis and Management. Microorganisms 2021; 9:534. [PMID: 33807623 PMCID: PMC8001201 DOI: 10.3390/microorganisms9030534] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 02/25/2021] [Accepted: 03/03/2021] [Indexed: 12/11/2022] Open
Abstract
Nosocomial pneumonia (NP), including hospital-acquired pneumonia in non-intubated patients and ventilator-associated pneumonia, is one of the most frequent hospital-acquired infections, especially in the intensive care unit. NP has a significant impact on morbidity, mortality and health care costs, especially when the implicated pathogens are multidrug-resistant ones. This narrative review aims to critically review what is new in the field of NP, specifically, diagnosis and antibiotic treatment. Regarding novel imaging modalities, the current role of lung ultrasound and low radiation computed tomography are discussed, while regarding etiological diagnosis, recent developments in rapid microbiological confirmation, such as syndromic rapid multiplex Polymerase Chain Reaction panels are presented and compared with conventional cultures. Additionally, the volatile compounds/electronic nose, a promising diagnostic tool for the future is briefly presented. With respect to NP management, antibiotics approved for the indication of NP during the last decade are discussed, namely, ceftobiprole medocaril, telavancin, ceftolozane/tazobactam, ceftazidime/avibactam, and meropenem/vaborbactam.
Collapse
Affiliation(s)
- Elena Xu
- Burns, Trauma and Critical Care Research Centre, University of Queensland Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Brisbane, QLD 4029, Australia;
| | - David Pérez-Torres
- Servicio de Medicina Intensiva, Hospital Universitario Río Hortega, 47012 Valladolid, Spain;
| | - Paraskevi C. Fragkou
- Fourth Department of Internal Medicine, Attikon University Hospital, 12462 Athens, Greece;
| | - Jean-Ralph Zahar
- Microbiology Department, Infection Control Unit, Hospital Avicenne, 93000 Bobigny, France;
| | - Despoina Koulenti
- Burns, Trauma and Critical Care Research Centre, University of Queensland Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Brisbane, QLD 4029, Australia;
- Second Critical Care Department, Attikon University Hospital, 12462 Athens, Greece
| |
Collapse
|
36
|
Majchrzak T, Wojnowski W, Głowacz-Różyńska A, Wasik A. On-line assessment of oil quality during deep frying using an electronic nose and proton transfer reaction mass spectrometry. Food Control 2021. [DOI: 10.1016/j.foodcont.2020.107659] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
|
37
|
Detection of Mackerel Fish Spoilage with a Gas Sensor Based on One Single SnO2 Nanowire. CHEMOSENSORS 2020. [DOI: 10.3390/chemosensors9010002] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
A chemosensor consisting of one single tin oxide nanowire is used to determine the freshness status of mackerel fish (Scomber scombrus) in a quick and non-invasive way. The tiny chemoresistive sensor is first tested with pure ammonia and then used to measure the total volatile basic nitrogen from different samples of fish at different degrees of freshness. The sensor has proved capable of determining the freshness of a sample in few seconds compared to traditional methods such as microbial count and chromatography, which take hours. The sensor response is well correlated with the total viable count (TVC), proving that the total volatile basic nitrogen is a good way to quickly test the bacterial population in the sample. After calibrating the sensor (following the degradation of the fish during almost two days), it has been tested with random double blind samples, proving that it can well discriminate the degree of freshness of the fish preserved at different temperatures.
Collapse
|
38
|
Piccoli JP, Soares AC, Oliveira ON, Cilli EM. Nanostructured functional peptide films and their application in C-reactive protein immunosensors. Bioelectrochemistry 2020; 138:107692. [PMID: 33291002 DOI: 10.1016/j.bioelechem.2020.107692] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 10/25/2020] [Accepted: 10/27/2020] [Indexed: 12/31/2022]
Abstract
Peptides with an active redox molecule are incorporated into nanostructured films for electrochemical biosensors with stable and controllable physicochemical properties. In this study, we synthesized three ferrocene (Fc)-containing peptides with the sequence Fc-Glu-(Ala)n-Cys-NH2, which could form self-assembled monolayers on gold and be attached to antibodies. The peptide with two alanines (n = 2) yielded the immunosensor with the highest performance in detecting C-reactive protein (CRP), a biomarker of inflammation. Using electrochemical impedance-derived capacitive spectroscopy, the limit of detection was 240 pM with a dynamic range that included clinically relevant CRP concentrations. With a combination of electrochemical methods and polarization-modulated infrared reflection-absorption spectroscopy, we identified the chemical groups involved in the antibody-CRP interaction, and were able to relate the highest performance for the peptide with n = 2 to chain length and efficient packing in the organized films. These strategies to design peptides and methods to fabricate the immunosensors are generic, and can be applied to other types of biosensors, including in low cost platforms for point-of-care diagnostics.
Collapse
Affiliation(s)
- Julia P Piccoli
- São Carlos Institute of Physics, University of São Paulo, 13566-590 São Carlos - SP, Brazil
| | - Andrey C Soares
- São Carlos Institute of Physics, University of São Paulo, 13566-590 São Carlos - SP, Brazil; Nanotechnology National Laboratory for Agriculture (LNNA), Embrapa Instrumentação, 13560-970 São Carlos - SP, Brazil
| | - Osvaldo N Oliveira
- São Carlos Institute of Physics, University of São Paulo, 13566-590 São Carlos - SP, Brazil.
| | - Eduardo M Cilli
- Institute of Chemistry, São Paulo State University, 14800-060 Araraquara - SP, Brazil.
| |
Collapse
|
39
|
Low-Cost Methods to Assess Beer Quality Using Artificial Intelligence Involving Robotics, an Electronic Nose, and Machine Learning. FERMENTATION 2020. [DOI: 10.3390/fermentation6040104] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Beer quality is a difficult concept to describe and assess by physicochemical and sensory analysis due to the complexity of beer appreciation and acceptability by consumers, which can be dynamic and related to changes in climate affecting raw materials, consumer preference, and rising quality requirements. Artificial intelligence (AI) may offer unique capabilities based on the integration of sensor technology, robotics, and data analysis using machine learning (ML) to identify specific quality traits and process modifications to produce quality beers. This research presented the integration and implementation of AI technology based on low-cost sensor networks in the form of an electronic nose (e-nose), robotics, and ML. Results of ML showed high accuracy (97%) in the identification of fermentation type (Model 1) based on e-nose data; prediction of consumer acceptability from near-infrared (Model 2; R = 0.90) and e-nose data (Model 3; R = 0.95), and physicochemical and colorimetry of beers from e-nose data. The use of the RoboBEER coupled with the e-nose and AI could be used by brewers to assess the fermentation process, quality of beers, detection of faults, traceability, and authentication purposes in an affordable, user-friendly, and accurate manner.
Collapse
|
40
|
Wojnowski W, Kalinowska K, Gębicki J, Zabiegała B. Monitoring the BTEX Volatiles during 3D Printing with Acrylonitrile Butadiene Styrene (ABS) Using Electronic Nose and Proton Transfer Reaction Mass Spectrometry. SENSORS 2020; 20:s20195531. [PMID: 32992544 PMCID: PMC7582819 DOI: 10.3390/s20195531] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 09/09/2020] [Accepted: 09/23/2020] [Indexed: 12/28/2022]
Abstract
We describe a concept study in which the changes of concentration of benzene, toluene, ethylbenzene, and xylene (BTEX) compounds and styrene within a 3D printer enclosure during printing with different acrylonitrile butadiene styrene (ABS) filaments were monitored in real-time using a proton transfer reaction mass spectrometer and an electronic nose. The quantitative data on the concentration of the BTEX compounds, in particular the concentration of carcinogenic benzene, were then used as reference values for assessing the applicability of an array of low-cost electrochemical sensors in monitoring the exposure of the users of consumer-grade fused deposition modelling 3D printers to potentially harmful volatiles. Using multivariate statistical analysis and machine learning, it was possible to determine whether a set threshold limit value for the concentration of BTEX was exceeded with a 0.96 classification accuracy and within a timeframe of 5 min based on the responses of the chemical sensors.
Collapse
Affiliation(s)
- Wojciech Wojnowski
- Department of Analytical Chemistry, Faculty of Chemistry, Gdańsk University of Technology, 11/12 Gabriela Narutowicza Street, 80-233 Gdańsk, Poland;
- Correspondence: (W.W.); (K.K.)
| | - Kaja Kalinowska
- Department of Analytical Chemistry, Faculty of Chemistry, Gdańsk University of Technology, 11/12 Gabriela Narutowicza Street, 80-233 Gdańsk, Poland;
- Correspondence: (W.W.); (K.K.)
| | - Jacek Gębicki
- Department of Process Engineering and Chemical Technology, Faculty of Chemistry, Gdańsk University of Technology, 11/12 Gabriela Narutowicza Street, 80-233 Gdańsk, Poland;
| | - Bożena Zabiegała
- Department of Analytical Chemistry, Faculty of Chemistry, Gdańsk University of Technology, 11/12 Gabriela Narutowicza Street, 80-233 Gdańsk, Poland;
| |
Collapse
|
41
|
Ollé EP, Farré-Lladós J, Casals-Terré J. Advancements in Microfabricated Gas Sensors and Microanalytical Tools for the Sensitive and Selective Detection of Odors. SENSORS (BASEL, SWITZERLAND) 2020; 20:E5478. [PMID: 32987904 PMCID: PMC7583964 DOI: 10.3390/s20195478] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 09/14/2020] [Accepted: 09/21/2020] [Indexed: 12/15/2022]
Abstract
In recent years, advancements in micromachining techniques and nanomaterials have enabled the fabrication of highly sensitive devices for the detection of odorous species. Recent efforts done in the miniaturization of gas sensors have contributed to obtain increasingly compact and portable devices. Besides, the implementation of new nanomaterials in the active layer of these devices is helping to optimize their performance and increase their sensitivity close to humans' olfactory system. Nonetheless, a common concern of general-purpose gas sensors is their lack of selectivity towards multiple analytes. In recent years, advancements in microfabrication techniques and microfluidics have contributed to create new microanalytical tools, which represent a very good alternative to conventional analytical devices and sensor-array systems for the selective detection of odors. Hence, this paper presents a general overview of the recent advancements in microfabricated gas sensors and microanalytical devices for the sensitive and selective detection of volatile organic compounds (VOCs). The working principle of these devices, design requirements, implementation techniques, and the key parameters to optimize their performance are evaluated in this paper. The authors of this work intend to show the potential of combining both solutions in the creation of highly compact, low-cost, and easy-to-deploy platforms for odor monitoring.
Collapse
Affiliation(s)
- Enric Perarnau Ollé
- Department of Mechanical Engineering, Polytechnical University of Catalonia (UPC), MicroTech Lab, Colom street 11, 08222 Terrassa, Spain; (J.F.-L.); (J.C.-T.)
- SEAT S.A., R&D Department in Future Urban Mobility Concepts, A-2, Km 585, 08760 Martorell, Spain
| | - Josep Farré-Lladós
- Department of Mechanical Engineering, Polytechnical University of Catalonia (UPC), MicroTech Lab, Colom street 11, 08222 Terrassa, Spain; (J.F.-L.); (J.C.-T.)
| | - Jasmina Casals-Terré
- Department of Mechanical Engineering, Polytechnical University of Catalonia (UPC), MicroTech Lab, Colom street 11, 08222 Terrassa, Spain; (J.F.-L.); (J.C.-T.)
| |
Collapse
|
42
|
Sobrinho ASF, Scalassara PR, Dajer ME. Low-Cost Joystick for Pediatric Respiratory Exercises. J Med Syst 2020; 44:186. [PMID: 32926332 PMCID: PMC7488224 DOI: 10.1007/s10916-020-01655-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 08/28/2020] [Indexed: 11/28/2022]
Abstract
The use of body signals for health care applications has become ubiquitous in the last decade. One utilization of such measurements is the monitoring of respiratory flow for physiotherapy assistance. This application is based on relative flow measures which can rely on inexpensive sensors. Based on that, we present a low-cost electronic device that detects blows and suctions with a pressure sensor and emulates a keyboard for interfacing with computers. This joystick allows children to control free internet games by associating blows and suctions with different intensities to keyboard actions. Also, the intensity can be calibrated according to the user’s pulmonary capacities. This feature is adequate for gradual respiratory physiotherapy and can be customized for each patient. In order to verify the operation of the proposed device, practical tests were performed with three online free games, where the joystick functionality was assessed with different therapeutic configurations.
Collapse
Affiliation(s)
| | - Paulo Rogério Scalassara
- Department of Electrical Engineering, Federal University of Technology - Paraná, Cornélio Procópio, Brazil
| | - María Eugenia Dajer
- Department of Electrical Engineering, Federal University of Technology - Paraná, Cornélio Procópio, Brazil
| |
Collapse
|
43
|
Afik N, Yadgar O, Volison-Klimentiev A, Peretz-Damari S, Ohayon-Lavi A, Alatawna A, Yosefi G, Bitton R, Fuchs N, Regev O. Sensing Exposure Time to Oxygen by Applying a Percolation-Induced Principle. SENSORS (BASEL, SWITZERLAND) 2020; 20:s20164465. [PMID: 32785077 PMCID: PMC7471990 DOI: 10.3390/s20164465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Revised: 07/27/2020] [Accepted: 08/06/2020] [Indexed: 06/11/2023]
Abstract
The determination of food freshness along manufacturer-to-consumer transportation lines is a challenging problem that calls for cheap, simple, reliable, and nontoxic sensors inside food packaging. We present a novel approach for oxygen sensing in which the exposure time to oxygen-rather than the oxygen concentration per se-is monitored. We developed a nontoxic hybrid composite-based sensor consisting of graphite powder (conductive filler), clay (viscosity control filler) and linseed oil (the matrix). Upon exposure to oxygen, the insulating linseed oil is oxidized, leading to polymerization and shrinkage of the matrix and hence to an increase in the concentration of the electrically conductive graphite powder up to percolation, which serves as an indicator of food spoilage. In the developed sensor, the exposure time to oxygen (days to weeks) is obtained by measuring the electrical conductivity though the sensor. The sensor functionality could be tuned by changing the oil viscosity, the aspect ratio of the conductive filler, and/or the concentration of the clay, thereby adapting the sensor to monitoring the quality of food products with different sensitivities to oxygen exposure time (e.g., fish vs grain).
Collapse
Affiliation(s)
- Noa Afik
- Department of Chemical Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel; (O.Y.); (A.V.-K.); (S.P.-D.); (A.O.-L.); (A.A.); (G.Y.); (R.B.)
- Department of Chemistry, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
| | - Omri Yadgar
- Department of Chemical Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel; (O.Y.); (A.V.-K.); (S.P.-D.); (A.O.-L.); (A.A.); (G.Y.); (R.B.)
| | - Anastasiya Volison-Klimentiev
- Department of Chemical Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel; (O.Y.); (A.V.-K.); (S.P.-D.); (A.O.-L.); (A.A.); (G.Y.); (R.B.)
| | - Sivan Peretz-Damari
- Department of Chemical Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel; (O.Y.); (A.V.-K.); (S.P.-D.); (A.O.-L.); (A.A.); (G.Y.); (R.B.)
| | - Avia Ohayon-Lavi
- Department of Chemical Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel; (O.Y.); (A.V.-K.); (S.P.-D.); (A.O.-L.); (A.A.); (G.Y.); (R.B.)
| | - Amr Alatawna
- Department of Chemical Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel; (O.Y.); (A.V.-K.); (S.P.-D.); (A.O.-L.); (A.A.); (G.Y.); (R.B.)
| | - Gal Yosefi
- Department of Chemical Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel; (O.Y.); (A.V.-K.); (S.P.-D.); (A.O.-L.); (A.A.); (G.Y.); (R.B.)
| | - Ronit Bitton
- Department of Chemical Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel; (O.Y.); (A.V.-K.); (S.P.-D.); (A.O.-L.); (A.A.); (G.Y.); (R.B.)
- The Ilse Katz Institute for Meso and Nanoscale Science and Technology, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
| | - Naomi Fuchs
- Department of Biotechnology Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel;
| | - Oren Regev
- Department of Chemical Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel; (O.Y.); (A.V.-K.); (S.P.-D.); (A.O.-L.); (A.A.); (G.Y.); (R.B.)
- The Ilse Katz Institute for Meso and Nanoscale Science and Technology, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
| |
Collapse
|
44
|
He S, Yuan Y, Nag A, Feng S, Afsarimanesh N, Han T, Mukhopadhyay SC, Organ DR. A Review on the Use of Impedimetric Sensors for the Inspection of Food Quality. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E5220. [PMID: 32698330 PMCID: PMC7400391 DOI: 10.3390/ijerph17145220] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 07/06/2020] [Accepted: 07/16/2020] [Indexed: 01/02/2023]
Abstract
This paper exhibits a thorough review of the use of impedimetric sensors for the analysis of food quality. It helps to understand the contribution of some of the major types of impedimetric sensors that are used for this application. The deployment of impedimetric sensing prototypes has been advantageous due to their wide linear range of responses, detection of the target analyte at low concentrations, good stability, high accuracy and high reproducibility in the results. The choice of these sensors was classified on the basis of structure and the conductive material used to develop them. The first category included the use of nanomaterials such as graphene and metallic nanowires used to form the sensing devices. Different forms of graphene nanoparticles, such as nano-hybrids, nanosheets, and nano-powders, have been largely used to sense biomolecules in the micro-molar range. The use of conductive materials such as gold, copper, tungsten and tin to develop nanowire-based prototypes for the inspection of food quality has also been shown. The second category was based on conventional electromechanical circuits such as electronic noses and other smart systems. Within this sector, the standardized systems, such as electronic noses, and LC circuit -based systems have been explained. Finally, some of the challenges posed by the existing sensors have been listed out, along with an estimate of the increase in the number of sensors employed to assess food quality.
Collapse
Affiliation(s)
- Shan He
- School of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou 510006, China; (S.H.); (Y.Y.)
- Flinders Institute of Nanoscale Science and Technology, College of Science and Engineering, Flinders University, Bedford Park, South Australia 5042, Australia
| | - Yang Yuan
- School of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou 510006, China; (S.H.); (Y.Y.)
| | - Anindya Nag
- DGUT-CNAM Institute, Dongguan University of Technology, Dongguan 523000, China; (N.A.); (T.H.)
| | - Shilun Feng
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore
| | - Nasrin Afsarimanesh
- DGUT-CNAM Institute, Dongguan University of Technology, Dongguan 523000, China; (N.A.); (T.H.)
| | - Tao Han
- DGUT-CNAM Institute, Dongguan University of Technology, Dongguan 523000, China; (N.A.); (T.H.)
| | | | - Dominic Rowan Organ
- Department of Social Sciences, Heriot-Watt University, Edinburgh SC000278, UK;
| |
Collapse
|
45
|
Bernardo YAA, Rosario DKA, Delgado IF, Conte-Junior CA. Fish Quality Index Method: Principles, weaknesses, validation, and alternatives-A review. Compr Rev Food Sci Food Saf 2020; 19:2657-2676. [PMID: 33336975 DOI: 10.1111/1541-4337.12600] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Revised: 05/23/2020] [Accepted: 06/11/2020] [Indexed: 12/31/2022]
Abstract
Fish is a high nutritional value matrix of which production and consumption have been increasing in the last years. Advancements in the efficient evaluation of freshness are essential to optimize the quality assessment, to improve consumer safety, and to reduce raw material losses. Therefore, it is necessary to use rapid, nondestructive, and objective methodologies to evaluate the quality of this matrix. Quality Index Method (QIM) is a tool applied to indicate fish freshness through a sensory evaluation performed by a group of assessors. However, the use of QIM as an official method for quality assessment is limited by the protocol, sampling size, specificities of the species, storage conditions, and assessor's experience, which make this method subjective. Also, QIM may present divergences regarding the development of microorganisms and chemical analysis. In this way, novel quality evaluation methods such as electronic noses, electronic tongues, machine vision system, and colorimetric sensors have been proposed, and novel technologies such as proteomics and mitochondrial analysis have been developed. In this review, the weaknesses of QIM were exposed, and novel methodologies for quality evaluation were presented. The consolidation of these novel methodologies and their use as methods of quality assessment are an alternative to sensory methods, and their understanding enables a more effective fish quality control.
Collapse
Affiliation(s)
- Yago A A Bernardo
- Post Graduate Program in Sanitary Surveillance, National Institute of Health Quality Control, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.,Center for Food Analysis, Technological Development Support Laboratory (LADETEC), Avenida Horácio Macedo, Polo de Química, Ilha do Fundão, Cidade Universitária, Rio de Janeiro, Brazil
| | - Denes K A Rosario
- Center for Food Analysis, Technological Development Support Laboratory (LADETEC), Avenida Horácio Macedo, Polo de Química, Ilha do Fundão, Cidade Universitária, Rio de Janeiro, Brazil.,Post Graduate Program in Food Science, Institute of Chemistry, Federal University of Rio de Janeiro, Av. Athos da Silveira Ramos, 149, Cidade Universitária, Rio de Janeiro, Brazil
| | - Isabella F Delgado
- Post Graduate Program in Sanitary Surveillance, National Institute of Health Quality Control, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
| | - Carlos A Conte-Junior
- Post Graduate Program in Sanitary Surveillance, National Institute of Health Quality Control, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.,Center for Food Analysis, Technological Development Support Laboratory (LADETEC), Avenida Horácio Macedo, Polo de Química, Ilha do Fundão, Cidade Universitária, Rio de Janeiro, Brazil.,Post Graduate Program in Food Science, Institute of Chemistry, Federal University of Rio de Janeiro, Av. Athos da Silveira Ramos, 149, Cidade Universitária, Rio de Janeiro, Brazil.,Post Graduate Program in Veterinary Hygiene, Faculty of Veterinary Medicine, Fluminense Federal University, Vital Brazil Filho, Niterói, Rio de Janeiro, Brazil
| |
Collapse
|
46
|
Noormohammad A, Molla‐Abbasi P. An analytical investigation on the effect of porous conductive cellulose acetate composite morphology on the detection of organic compounds. POLYM ENG SCI 2020. [DOI: 10.1002/pen.25407] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Affiliation(s)
- Asma Noormohammad
- Department of Chemical Engineering, Faculty of EngineeringUniversity of Isfahan Isfahan Islamic Republic of Iran
| | - Payam Molla‐Abbasi
- Department of Chemical Engineering, Faculty of EngineeringUniversity of Isfahan Isfahan Islamic Republic of Iran
| |
Collapse
|
47
|
Discrimination of geographical origin of camellia seed oils using electronic nose characteristics and chemometrics. J Verbrauch Lebensm 2020. [DOI: 10.1007/s00003-020-01278-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
|
48
|
The Influence of Hydrogen on the Indications of the Electrochemical Carbon Monoxide Sensors. SUSTAINABILITY 2019. [DOI: 10.3390/su12010014] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
This article examines electrochemical carbon monoxide (CO) sensors used as mobile devices by rescue and firefighting units in Poland. The conducted research indicates that the presence of chlorine (Cl2), ammonia (NH3), hydrogen sulfide (H2S), hydrogen chloride (HCl), hydrogen cyanide (HCN), nitrogen (IV) oxide (NO2), and sulfur (IV) oxide (SO2) in the atmosphere does not affect the functioning of the electrochemical CO sensor. In the case of this sensor, there was a significant cross effect in relation to hydrogen (H2). It was found that the time and manner of using the sensor affects the behavior in relation to H2. Such a relationship was not recorded for CO. Measurements in a mixture of CO and H2 confirm the effect of hydrogen on the changes taking place inside the sensor. Independently of the ratio of H2 to CO, readings of CO were flawed. All analyses showed a significant difference between the electrochemical CO sensor readings and the expected values. Only in experiments with a 1:3 mixture of CO and H2 was the relative error less than 15%. The relative error in the analyzed concentration range for a sensor with an additional compensation electrode ranged from 7% to 38%; for a sensor without this electrode, it ranged from 23% to 55%. It was ascertained that in the cases of measurements for tests carried out at higher concentrations of H2 in relation to CO, a sensor with an additional electrode is significantly better (more accurate) than a sensor without such an electrode. Differences at the significance level p = 0.01 for measurements made in the CO:H2 mixture at a ratio of 1:3 were ascertained.
Collapse
|
49
|
Exploring the Ability of Electronic Nose Technology to Recognize Interstitial Lung Diseases (ILD) by Non-Invasive Breath Screening of Exhaled Volatile Compounds (VOC): A Pilot Study from the European IPF Registry (eurIPFreg) and Biobank. J Clin Med 2019; 8:jcm8101698. [PMID: 31623141 PMCID: PMC6832325 DOI: 10.3390/jcm8101698] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2019] [Revised: 10/06/2019] [Accepted: 10/14/2019] [Indexed: 12/27/2022] Open
Abstract
Background: There is an increasing interest in employing electronic nose technology in the diagnosis and monitoring of lung diseases. Interstitial lung diseases (ILD) are challenging in regard to setting an accurate diagnosis in a timely manner. Thus, there is a high unmet need in non-invasive diagnostic tests. This single-center explorative study aimed to evaluate the usefulness of electronic nose (Aeonose®) in the diagnosis of ILDs. Methods: Exhaled volatile organic compound (VOC) signatures were obtained by Aeonose® in 174 ILD patients, 23 patients with chronic obstructive pulmonary disease (COPD), and 33 healthy controls (HC). Results: By dichotomous comparison of VOC’s between ILD, COPD, and HC, a discriminating algorithm was established. In addition, direct analyses between the ILD subgroups, e.g., cryptogenic organizing pneumonia (COP, n = 28), idiopathic pulmonary fibrosis (IPF, n = 51), and connective tissue disease-associated ILD (CTD-ILD, n = 25) were performed. Area under the Curve (AUC) and Matthews’s correlation coefficient (MCC) were used to interpret the data. In direct comparison of the different ILD subgroups to HC, the algorithms developed on the basis of the Aeonose® signatures allowed safe separation between IPF vs. HC (AUC of 0.95, MCC of 0.73), COP vs. HC (AUC 0.89, MCC 0.67), and CTD-ILD vs. HC (AUC 0.90, MCC 0.69). Additionally, to a case-control study design, the breath patterns of ILD subgroups were compared to each other. Following this approach, the sensitivity and specificity showed a relevant drop, which results in a poorer performance of the algorithm to separate the different ILD subgroups (IPF vs. COP with MCC 0.49, IPF vs. CTD-ILD with MCC 0.55, and COP vs. CT-ILD with MCC 0.40). Conclusions: The Aeonose® showed some potential in separating ILD subgroups from HC. Unfortunately, when applying the algorithm to distinguish ILD subgroups from each other, the device showed low specificity. We suggest that artificial intelligence or principle compound analysis-based studies of a much broader data set of patients with ILDs may be much better suited to train these devices.
Collapse
|
50
|
Saktiawati AMI, Putera DD, Setyawan A, Mahendradhata Y, van der Werf TS. Diagnosis of tuberculosis through breath test: A systematic review. EBioMedicine 2019; 46:202-214. [PMID: 31401197 PMCID: PMC6712009 DOI: 10.1016/j.ebiom.2019.07.056] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Revised: 07/20/2019] [Accepted: 07/22/2019] [Indexed: 12/28/2022] Open
Abstract
Background Breath tests may diagnose tuberculosis (TB) through detecting specific volatile organic compounds produced by Mycobacterium tuberculosis or the infected host. Methods To estimate the diagnostic accuracy of breath test with electronic-nose and other devices against culture or other tests for TB, we screened multiple databases until January 6, 2019. Findings We included fourteen studies, with 1715 subjects in the analysis. The pooled sensitivity and specificity of electronic-nose were 0.93 (95% CI 0.82–0.97) and 0.93 (95% CI 0.82–0.97), respectively, and no heterogeneity was found. The sensitivity and specificity of other breath test devices ranged from 0.62 to 1.00, and 0.11 to 0.84, respectively. Interpretation The low to moderate evidence of these studies shows that breath tests can diagnose TB accurately, however, to give a real-time test result, additional development is needed. Research should also focus on sputum smear negative TB, children, and the positioning of breath testing in the diagnostic work flow. Funding The authors received no specific funding for this work.
Collapse
Affiliation(s)
- Antonia M I Saktiawati
- Department of Internal Medicine, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia; University of Groningen, University Medical Centre Groningen, Department of Pulmonary Diseases and Tuberculosis, Groningen, the Netherlands; Center for Tropical Medicine, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | | | - Althaf Setyawan
- Department of Biostatistics, Epidemiology, and Population Health, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Yodi Mahendradhata
- Center for Tropical Medicine, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia; Department of Health Policy and Management, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Tjip S van der Werf
- University of Groningen, University Medical Centre Groningen, Department of Pulmonary Diseases and Tuberculosis, Groningen, the Netherlands; University of Groningen, University Medical Center Groningen, Department of Internal Medicine-Infectious Diseases, Groningen, the Netherlands.
| |
Collapse
|