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Khorramifar A, Karami H, Lvova L, Kolouri A, Łazuka E, Piłat-Rożek M, Łagód G, Ramos J, Lozano J, Kaveh M, Darvishi Y. Environmental Engineering Applications of Electronic Nose Systems Based on MOX Gas Sensors. SENSORS (BASEL, SWITZERLAND) 2023; 23:5716. [PMID: 37420880 PMCID: PMC10300923 DOI: 10.3390/s23125716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 06/05/2023] [Accepted: 06/12/2023] [Indexed: 07/09/2023]
Abstract
Nowadays, the electronic nose (e-nose) has gained a huge amount of attention due to its ability to detect and differentiate mixtures of various gases and odors using a limited number of sensors. Its applications in the environmental fields include analysis of the parameters for environmental control, process control, and confirming the efficiency of the odor-control systems. The e-nose has been developed by mimicking the olfactory system of mammals. This paper investigates e-noses and their sensors for the detection of environmental contaminants. Among different types of gas chemical sensors, metal oxide semiconductor sensors (MOXs) can be used for the detection of volatile compounds in air at ppm and sub-ppm levels. In this regard, the advantages and disadvantages of MOX sensors and the solutions to solve the problems arising upon these sensors' applications are addressed, and the research works in the field of environmental contamination monitoring are overviewed. These studies have revealed the suitability of e-noses for most of the reported applications, especially when the tools were specifically developed for that application, e.g., in the facilities of water and wastewater management systems. As a general rule, the literature review discusses the aspects related to various applications as well as the development of effective solutions. However, the main limitation in the expansion of the use of e-noses as an environmental monitoring tool is their complexity and lack of specific standards, which can be corrected through appropriate data processing methods applications.
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Affiliation(s)
- Ali Khorramifar
- Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199, Iran; (A.K.); (A.K.)
| | - Hamed Karami
- Department of Petroleum Engineering, Knowledge University, Erbil 44001, Iraq;
| | - Larisa Lvova
- Department of Chemical Science and Technologies, University of Rome “Tor Vergata”, 00133 Rome, Italy
| | - Alireza Kolouri
- Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199, Iran; (A.K.); (A.K.)
| | - Ewa Łazuka
- Department of Applied Mathematics, Faculty of Technology Fundamentals, Lublin University of Technology, 20-618 Lublin, Poland; (E.Ł.); (M.P.-R.)
| | - Magdalena Piłat-Rożek
- Department of Applied Mathematics, Faculty of Technology Fundamentals, Lublin University of Technology, 20-618 Lublin, Poland; (E.Ł.); (M.P.-R.)
| | - Grzegorz Łagód
- Department of Water Supply and Wastewater Disposal, Faculty of Environmental Engineering, Lublin University of Technology, 20-618 Lublin, Poland;
| | - Jose Ramos
- College of Computing and Engineering, Nova Southeastern University (NSU), 3301 College Avenue, Fort Lauderdale, FL 33314-7796, USA;
| | - Jesús Lozano
- Department of Electric Technology, Electronics and Automation, University of Extremadura, Avda. De Elvas S/n, 06006 Badajoz, Spain;
| | - Mohammad Kaveh
- Department of Petroleum Engineering, Knowledge University, Erbil 44001, Iraq;
| | - Yousef Darvishi
- Department of Biosystems Engineering, University of Tehran, Tehran P.O. Box 113654117, Iran;
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Khorramifar A, Rasekh M, Karami H, Lozano J, Gancarz M, Łazuka E, Łagód G. Determining the shelf life and quality changes of potatoes (Solanum tuberosum) during storage using electronic nose and machine learning. PLoS One 2023; 18:e0284612. [PMID: 37115737 PMCID: PMC10146475 DOI: 10.1371/journal.pone.0284612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Accepted: 04/04/2023] [Indexed: 04/29/2023] Open
Abstract
The activities of alpha-amylase, beta-amylase, sucrose synthase, and invertase enzymes are under the influence of storage conditions and can affect the structure of starch, as well as the sugar content of potatoes, hence altering their quality. Storage in a warehouse is one of the most common and effective methods of storage to maintain the quality of potatoes after their harvest, while preserving their freshness and sweetness. Smart monitoring and evaluation of the quality of potatoes during the storage period could be an effective approach to improve their freshness. This study is aimed at assessing the changes in the potato quality by an electronic nose (e-nose) in terms of the sugar and carbohydrate contents. Three potato cultivars (Agria, Santé, and Sprite) were analyzed and their quality variations were separately assessed. Quality parameters (i.e. sugar and carbohydrate contents) were evaluated in six 15-day periods. The e-nose data were analyzed by means of chemometric methods, including principal component analysis (PCA), linear data analysis (LDA), support vector machine (SVM), and artificial neural network (ANN). Quadratic discriminant analysis (QDA) and multivariate discrimination analysis (MDA) offer the highest accuracy and sensitivity in the classification of data. The accuracy of all methods was higher than 90%. These results could be applied to present a new approach for the assessment of the quality of stored potatoes.
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Affiliation(s)
- Ali Khorramifar
- Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil, Iran
| | - Mansour Rasekh
- Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil, Iran
| | - Hamed Karami
- Department of Petroleum Engineering, College of Engineering, Knowledge University, Erbil, Iraq
| | - Jesús Lozano
- Escuela de Ingenierías Industriales, Universidad de Extremadura, Badajoz, Spain
| | - Marek Gancarz
- Institute of Agrophysics, Polish Academy of Sciences, Lublin, Poland
- Faculty of Production and Power Engineering, University of Agriculture in Kraków, Kraków, Poland
| | - Ewa Łazuka
- Faculty of Technology Fundamentals, Lublin University of Technology, Lublin, Poland
| | - Grzegorz Łagód
- Faculty of Environmental Engineering, Lublin University of Technology, Lublin, Poland
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Khorramifar A, Sharabiani VR, Karami H, Kisalaei A, Lozano J, Rusinek R, Gancarz M. Investigating Changes in pH and Soluble Solids Content of Potato during the Storage by Electronic Nose and Vis/NIR Spectroscopy. Foods 2022; 11:foods11244077. [PMID: 36553819 PMCID: PMC9778509 DOI: 10.3390/foods11244077] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 12/13/2022] [Accepted: 12/13/2022] [Indexed: 12/23/2022] Open
Abstract
Potato is an important agricultural product, ranked as the fourth most common product in the human diet. Potato can be consumed in various forms. As customers expect safe and high-quality products, precise and rapid determination of the quality and composition of potatoes is of crucial significance. The quality of potatoes may alter during the storage period due to various phenomena. Soluble solids content (SSC) and pH are among the quality parameters experiencing alteration during the storage process. This study is thus aimed to assess the variations in SSC and pH during the storage of potatoes using an electronic nose and Vis/NIR spectroscopic techniques with the help of prediction models including partial least squares (PLS), multiple linear regression (MLR), principal component regression (PCR), support vector regression (SVR) and an artificial neural network (ANN). The variations in the SSC and pH are ascending and significant. The results also indicate that the SVR model in the electronic nose has the highest prediction accuracy for the SSC and pH (81, and 92%, respectively). The artificial neural network also managed to predict the SSC and pH at accuracies of 83 and 94%, respectively. SVR method shows the lowest accuracy in Vis/NIR spectroscopy while the PLS model exhibits the best performance in the prediction of the SSC and pH with respective precision of 89 and 93% through the median filter method. The accuracy of the ANN was 85 and 90% in the prediction of the SSC and pH, respectively.
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Affiliation(s)
- Ali Khorramifar
- Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran
| | - Vali Rasooli Sharabiani
- Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran
| | - Hamed Karami
- Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran
- Correspondence: (H.K.); or (M.G.)
| | - Asma Kisalaei
- Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran
| | - Jesús Lozano
- Department of Electric Technology, Electronics and Automation, University of Extremadura, Avda. de Elvas S/n, 06006 Badajoz, Spain
| | - Robert Rusinek
- Institute of Agrophysics, Polish Academy of Sciences, Doświadczalna 4, 20-290 Lublin, Poland
| | - Marek Gancarz
- Institute of Agrophysics, Polish Academy of Sciences, Doświadczalna 4, 20-290 Lublin, Poland
- Faculty of Production and Power Engineering, University of Agriculture in Kraków, Balicka 116B, 30-149 Krakow, Poland
- Correspondence: (H.K.); or (M.G.)
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Detection of fraud in sesame oil with the help of artificial intelligence combined with chemometrics methods and chemical compounds characterization by gas chromatography–mass spectrometry. Lebensm Wiss Technol 2022. [DOI: 10.1016/j.lwt.2022.113863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Steglińska A, Pielech-Przybylska K, Janas R, Grzesik M, Borowski S, Kręgiel D, Gutarowska B. Volatile Organic Compounds and Physiological Parameters as Markers of Potato ( Solanum tuberosum L.) Infection with Phytopathogens. Molecules 2022; 27:molecules27123708. [PMID: 35744835 PMCID: PMC9230024 DOI: 10.3390/molecules27123708] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 06/06/2022] [Accepted: 06/06/2022] [Indexed: 11/17/2022] Open
Abstract
The feasibility of early disease detection in potato seeds storage monitoring of volatile organic compounds (VOCs) and plant physiological markers was evaluated using 10 fungal and bacterial pathogens of potato in laboratory-scale experiments. Data analysis of HS-SPME-GC-MS revealed 130 compounds released from infected potatoes, including sesquiterpenes, dimethyl disulfide, 1,2,4-trimethylbenzene, 2,6,11-trimethyldodecane, benzothiazole, 3-octanol, and 2-butanol, which may have been associated with the activity of Fusarium sambucinum, Alternaria tenuissima and Pectobacterium carotovorum. In turn, acetic acid was detected in all infected samples. The criteria of selection for volatiles for possible use as incipient disease indicators were discussed in terms of potato physiology. The established physiological markers proved to demonstrate a negative effect of phytopathogens infecting seed potatoes not only on the kinetics of stem and root growth and the development of the entire root system, but also on gas exchange, chlorophyll content in leaves, and yield. The negative effect of phytopathogens on plant growth was dependent on the time of planting after infection. The research also showed different usefulness of VOCs and physiological markers as the indicators of the toxic effect of inoculated phytopathogens at different stages of plant development and their individual organs.
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Affiliation(s)
- Aleksandra Steglińska
- Department of Environmental Biotechnology, Lodz University of Technology, Wólczańska 171/173, 90-530 Łódź, Poland; (S.B.); (D.K.); (B.G.)
- Correspondence:
| | - Katarzyna Pielech-Przybylska
- Institute of Fermentation Technology and Microbiology, Lodz University of Technology, Wólczańska 171/173, 90-530 Łódź, Poland;
| | - Regina Janas
- The National Institute of Horticultural Research, Konstytucji 3 Maja 1/3, 96-100 Skierniewice, Poland; (R.J.); (M.G.)
| | - Mieczysław Grzesik
- The National Institute of Horticultural Research, Konstytucji 3 Maja 1/3, 96-100 Skierniewice, Poland; (R.J.); (M.G.)
| | - Sebastian Borowski
- Department of Environmental Biotechnology, Lodz University of Technology, Wólczańska 171/173, 90-530 Łódź, Poland; (S.B.); (D.K.); (B.G.)
| | - Dorota Kręgiel
- Department of Environmental Biotechnology, Lodz University of Technology, Wólczańska 171/173, 90-530 Łódź, Poland; (S.B.); (D.K.); (B.G.)
| | - Beata Gutarowska
- Department of Environmental Biotechnology, Lodz University of Technology, Wólczańska 171/173, 90-530 Łódź, Poland; (S.B.); (D.K.); (B.G.)
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