1
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Deng J, Zhao X, Luo W, Bai X, Xu L, Jiang H. Microwave detection technique combined with deep learning algorithm facilitates quantitative analysis of heavy metal Pb residues in edible oils. J Food Sci 2024; 89:6005-6015. [PMID: 39136980 DOI: 10.1111/1750-3841.17259] [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: 03/14/2024] [Revised: 06/26/2024] [Accepted: 06/30/2024] [Indexed: 10/09/2024]
Abstract
The heavy metal content in edible oils is intricately associated with their suitability for human consumption. In this study, standard soybean oil was used as a sample to quantify the specified concentration of heavy metals using microwave sensing technique. In addition, an attention-based deep residual neural network model was developed as an alternative to traditional modeling methods for predicting heavy metals in edible oils. In the process of microwave data processing, this work continued to discuss the impact of depth on convolutional neural networks. The results demonstrated that the proposed attention-based residual network model outperforms all other deep learning models in all metrics. The performance of this model was characterized by a coefficient of determination (R2) of 0.9605, a relative prediction deviation (RPD) of 5.0479, and a root mean square error (RMSE) of 3.1654 mg/kg. The research findings indicate that the combination of microwave detection technology and chemometrics holds significant potential for assessing heavy metal levels in edible oils.
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Affiliation(s)
- Jihong Deng
- School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, PR China
| | - Xinke Zhao
- School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, PR China
| | - Wangfei Luo
- School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, PR China
| | - Xue Bai
- School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, PR China
| | - Leijun Xu
- School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, PR China
| | - Hui Jiang
- School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, PR China
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2
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Wang X, Gu Y, Lin W, Zhang Q. Rapid quantitative authentication and analysis of camellia oil adulterated with edible oils by electronic nose and FTIR spectroscopy. Curr Res Food Sci 2024; 8:100732. [PMID: 38699681 PMCID: PMC11063990 DOI: 10.1016/j.crfs.2024.100732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 03/19/2024] [Accepted: 04/04/2024] [Indexed: 05/05/2024] Open
Abstract
Camellia oil, recognized as a high-quality edible oil endorsed by the Food and Agriculture Organization, is confronted with authenticity issues arising from fraudulent adulteration practices. These practices not only pose health risks but also lead to economic losses. This study proposes a novel machine learning framework, referred to as a transformer encoder backbone with a support vector machine regressor (TES), coupled with an electronic nose (E-nose), for detecting varying adulteration levels in camellia oil. Experimental results indicate that the proposed TES model exhibits the best performance in identifying the adulterated concentration of camellia oi, compared with five other machine learning models (the support vector machine, random forest, XGBoost, K-nearest neighbors, and backpropagation neural network). The results obtained by E-nose detection are verified by complementary Fourier transform infrared (FTIR) spectroscopy analysis for identifying functional groups, ensuring accuracy and providing a comprehensive assessment of the types of adulterants. The proposed TES model combined with E-nose offers a rapid, effective, and practical tool for detecting camellia oil adulteration. This technique not only safeguards consumer health and economic interests but also promotes the application of E-nose in market supervision.
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Affiliation(s)
- Xiaoran Wang
- College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Yu Gu
- College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China
- School of Automation, Guangdong University of Petrochemical Technology, Maoming, 525000, China
- School of Biomedical Engineering, Capital Medical University, Beijing, 100069, China
- Beijing Key Laboratory of Basic Research in Clinical Applied Biomechanics, China
| | - Weiqi Lin
- Xiamen Products Quality Supervision and Inspection Institute, Xiamen, 361004, China
| | - Qian Zhang
- Xiamen Products Quality Supervision and Inspection Institute, Xiamen, 361004, China
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3
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Okechukwu VO, Adelusi OA, Kappo AP, Njobeh PB, Mamo MA. Aflatoxins: Occurrence, biosynthesis, mechanism of action and effects, conventional/emerging detection techniques. Food Chem 2024; 436:137775. [PMID: 37866099 DOI: 10.1016/j.foodchem.2023.137775] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 10/11/2023] [Accepted: 10/14/2023] [Indexed: 10/24/2023]
Abstract
Aflatoxins (AFs) are toxic secondary metabolites prevalent in various food and agricultural products, posing significant challenges to global food safety. The detection and quantification of AFs through high-precision analytical techniques are crucial in mitigating AF contamination levels and associated health risks. Variousmethods,including conventional and emerging techniques, have been developed for detecting and quantifyingAFsinfood samples. This review provides an in-depth analysis of the global occurrence of AF in food commodities, covering their biosynthesis, mode of action, and effects on humans and animals. Additionally, the review discusses different conventional strategies, including chromatographic and immunochemical approaches, for AF quantification and identification in food samples. Furthermore, emerging AF detection strategies, such as solid-state gas sensors and electronic nose technologies, along with their applications, limitations, and future perspectives, were reviewed. Sample purification, along with their respective advantages and limitations, are also discussed herein.
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Affiliation(s)
- Viola O Okechukwu
- Department of Biochemistry, Auckland Park Kingsway Campus, University of Johannesburg, South Africa
| | - Oluwasola A Adelusi
- Department of Biotechnology and Food Technology, PO Box 17011, Doornfontein Campus, University of Johannesburg, South Africa
| | - Abidemi P Kappo
- Department of Biochemistry, Auckland Park Kingsway Campus, University of Johannesburg, South Africa
| | - Patrick B Njobeh
- Department of Biotechnology and Food Technology, PO Box 17011, Doornfontein Campus, University of Johannesburg, South Africa
| | - Messai A Mamo
- Department of Chemical Sciences, PO Box 2028, Doornfontein Campus, University of Johannesburg, South Africa.
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4
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Geng D, Chen X, Lu D, Chen B. Discrimination of different edible vegetable oils based on GC-IMS and SIMCA. CYTA - JOURNAL OF FOOD 2023. [DOI: 10.1080/19476337.2022.2160827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Affiliation(s)
- Dechun Geng
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, Jiangsu, China
| | - Xinyu Chen
- Department of Physical Chemistry, University of Duisburg-Essen, Essen, Germany
| | - Daoli Lu
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, Jiangsu, China
| | - Bin Chen
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, Jiangsu, China
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5
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Lu WC, Chiu CS, Chan YJ, Mulio AT, Li PH. New perspectives on different Sacha inchi seed oil extractions and its applications in the food and cosmetic industries. Crit Rev Food Sci Nutr 2023:1-19. [PMID: 37950645 DOI: 10.1080/10408398.2023.2276882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2023]
Abstract
Sacha inchi oil is growing in demand worldwide owing to its high fatty acid content of linolenic acid (44.30%-51.62%) and linoleic acid (34.08%-36.13%). In addition, Sacha inchi oil also contains phytosterols, such as stigmasterols (346- 456 μg/g), sitosterols (435-563 μg/g), and campesterols (10.47% ± 4.36%). Its main tocopherol is gamma-tocopherol (120.41-125.69 mg/100 g). The antinutrients in Sacha inchi seeds can be reduced by roasting prior to extraction. Various extractions, including both conventional and novel methods, have been used to extract Sacha inchi oil. However, the variety of extraction methods and origins of the seeds change the nutrient profiles, antinutrient content, and physicochemical properties. Incorporation of Sacha inchi oil into food products can increase its nutritional value, and it works as a moisturizing agent in cosmetic products. To obtain Sacha inchi oil with the desired properties and nutritional profile, this review summarizes the effects of different Sacha inchi seed oil extraction methods and processes on chemical compounds, antinutrient content, and physicochemical properties, including their potential and recent applications in food and cosmetic industries.
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Affiliation(s)
- Wen-Chien Lu
- Department of Food and Beverage Management, Chung-Jen Junior College of Nursing, Health Sciences and Management, Chia-Yi City, Taiwan
| | - Chien-Shan Chiu
- Department of Dermatology, Taichung Veterans General Hospital, Taichung city, Taiwan
| | - Yung-Jia Chan
- College of Biotechnology and Bioresources, Da-Yeh University, Changhua county, Taiwan
| | | | - Po-Hsien Li
- Department of Food and Nutrition, Providence University, Taichung City, Taiwan
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6
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Abi-Rizk H, Jouan-Rimbaud Bouveresse D, Chamberland J, Cordella CBY. Recent developments of e-sensing devices coupled to data processing techniques in food quality evaluation: a critical review. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2023; 15:5410-5440. [PMID: 37818969 DOI: 10.1039/d3ay01132a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/13/2023]
Abstract
A greater demand for high-quality food is being driven by the growth of economic and technological advancements. In this context, consumers are currently paying special attention to organoleptic characteristics such as smell, taste, and appearance. Motivated to mimic human senses, scientists developed electronic devices such as e-noses, e-tongues, and e-eyes, to spot signals relative to different chemical substances prevalent in food systems. To interpret the information provided by the sensors' responses, multiple chemometric approaches are used depending on the aim of the study. This review based on the Web of Science database, endeavored to scrutinize three e-sensing systems coupled to chemometric approaches for food quality evaluation. A total of 122 eligible articles pertaining to the e-nose, e-tongue and e-eye devices were selected to conduct this review. Most of the performed studies used exploratory analysis based on linear factorial methods, while classification and regression techniques came in the second position. Although their applications have been less common in food science, it is to be noted that nonlinear approaches based on artificial intelligence and machine learning deployed in a big-data context have generally yielded better results for classification and regression purposes, providing new perspectives for future studies.
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Affiliation(s)
- Hala Abi-Rizk
- LAboratoire de Recherche et de Traitement de l'Information Chimiosensorielle - LARTIC, Institute of Nutrition and Functional Foods (INAF), Université Laval, Québec, QC, G1V 0A6, Canada.
| | | | - Julien Chamberland
- Department of Food Sciences, STELA Dairy Research Center, Institute of Nutrition and Functional Foods (INAF), Université Laval, Québec, QC, G1V 0A6, Canada
| | - Christophe B Y Cordella
- LAboratoire de Recherche et de Traitement de l'Information Chimiosensorielle - LARTIC, Institute of Nutrition and Functional Foods (INAF), Université Laval, Québec, QC, G1V 0A6, Canada.
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7
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Galvan D, de Aguiar LM, Bona E, Marini F, Killner MHM. Successful combination of benchtop nuclear magnetic resonance spectroscopy and chemometric tools: A review. Anal Chim Acta 2023; 1273:341495. [PMID: 37423658 DOI: 10.1016/j.aca.2023.341495] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 05/20/2023] [Accepted: 06/05/2023] [Indexed: 07/11/2023]
Abstract
Low-field nuclear magnetic resonance (NMR) has three general modalities: spectroscopy, imaging, and relaxometry. In the last twelve years, the modality of spectroscopy, also known as benchtop NMR, compact NMR, or just low-field NMR, has undergone instrumental development due to new permanent magnetic materials and design. As a result, benchtop NMR has emerged as a powerful analytical tool for use in process analytical control (PAC). Nevertheless, the successful application of NMR devices as an analytical tool in several areas is intrinsically linked to its coupling with different chemometric methods. This review focuses on the evolution of benchtop NMR and chemometrics in chemical analysis, including applications in fuels, foods, pharmaceuticals, biochemicals, drugs, metabolomics, and polymers. The review also presents different low-resolution NMR methods for spectrum acquisition and chemometric techniques for calibration, classification, discrimination, data fusion, calibration transfer, multi-block and multi-way.
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Affiliation(s)
- Diego Galvan
- Chemistry Institute, Universidade Federal de Mato Grosso do Sul (UFMS), 79070-900, Campo Grande, MS, Brazil; Chemistry Departament, Universidade Estadual de Londrina (UEL), 86.057-970, Londrina, PR, Brazil.
| | | | - Evandro Bona
- Post-Graduation Program of Food Technology (PPGTA), Universidade Tecnológica Federal do Paraná (UTFPR), Campus Campo Mourão, 87301-899, Campo Mourão, PR, Brazil; Post-Graduation Program of Chemistry (PPGQ), Universidade Tecnológica Federal do Paraná (UTFPR), Campus Curitiba, 80230-901, Curitiba, PR, Brazil
| | - Federico Marini
- Department of Chemistry, University of Rome "La Sapienza", Piazzale Aldo Moro 5, 00185, Rome, Italy
| | - Mário Henrique M Killner
- Chemistry Departament, Universidade Estadual de Londrina (UEL), 86.057-970, Londrina, PR, Brazil
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8
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Aghili NS, Rasekh M, Karami H, Edriss O, Wilson AD, Ramos J. Aromatic Fingerprints: VOC Analysis with E-Nose and GC-MS for Rapid Detection of Adulteration in Sesame Oil. SENSORS (BASEL, SWITZERLAND) 2023; 23:6294. [PMID: 37514589 PMCID: PMC10383484 DOI: 10.3390/s23146294] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 07/02/2023] [Accepted: 07/10/2023] [Indexed: 07/30/2023]
Abstract
Food quality assurance is an important field that directly affects public health. The organoleptic aroma of food is of crucial significance to evaluate and confirm food quality and origin. The volatile organic compound (VOC) emissions (detectable aroma) from foods are unique and provide a basis to predict and evaluate food quality. Soybean and corn oils were added to sesame oil (to simulate adulteration) at four different mixture percentages (25-100%) and then chemically analyzed using an experimental 9-sensor metal oxide semiconducting (MOS) electronic nose (e-nose) and gas chromatography-mass spectroscopy (GC-MS) for comparisons in detecting unadulterated sesame oil controls. GC-MS analysis revealed eleven major VOC components identified within 82-91% of oil samples. Principle component analysis (PCA) and linear detection analysis (LDA) were employed to visualize different levels of adulteration detected by the e-nose. Artificial neural networks (ANNs) and support vector machines (SVMs) were also used for statistical modeling. The sensitivity and specificity obtained for SVM were 0.987 and 0.977, respectively, while these values for the ANN method were 0.949 and 0.953, respectively. E-nose-based technology is a quick and effective method for the detection of sesame oil adulteration due to its simplicity (ease of application), rapid analysis, and accuracy. GC-MS data provided corroborative chemical evidence to show differences in volatile emissions from virgin and adulterated sesame oil samples and the precise VOCs explaining differences in e-nose signature patterns derived from each sample type.
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Affiliation(s)
- Nadia Sadat Aghili
- Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran
| | - Mansour Rasekh
- Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran
| | - Hamed Karami
- Department of Petroleum Engineering, Knowledge University, Erbil 44001, Iraq
| | - Omid Edriss
- Department of Computer, Rafsanjan Branch, Islamic Azad University, Rafsanjan 77181-84483, Iran
| | - Alphus Dan Wilson
- Southern Hardwoods Laboratory, Pathology Department, Center for Forest Health & Disturbance, Forest Genetics & Ecosystems Biology, Southern Research Station, USDA Forest Service, 432 Stoneville Road, Stoneville, MS 38776-0227, USA
| | - Jose Ramos
- College of Computing and Engineering, Nova Southeastern University (NSU), 3301 College Avenue, Fort Lauderdale, FL 33314-7796, USA
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9
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Mao J, Fu J, Zhu Z, Cao Z, Zhang M, Yuan Y, Chai T, Chen Y. Flavor characteristics of semi-dried yellow croaker (Pseudosciaena crocea) with KCl and ultrasound under sodium-reduced conditions before and after low temperature vacuum heating. Food Chem 2023; 426:136574. [PMID: 37302305 DOI: 10.1016/j.foodchem.2023.136574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 05/28/2023] [Accepted: 06/05/2023] [Indexed: 06/13/2023]
Abstract
This study investigated the flavor characteristics of semi-dried yellow croaker made by KCl instead of partial NaCl combined with ultrasound treatment before and after low temperature vacuum heating. The electronic tongue, electronic nose, free amino acids, 5'-nucleotides, and gas chromatography-ion mobility spectrometry were employed. Electronic nose and electronic tongue results showed that different treatment groups had different sensitive signals to smell and taste. The odor and taste of each group were mainly affected by Na+ and K+. The difference between the groups becomes larger after thermal treatment. Ultrasound and thermal treatment both changed the content of taste components. In addition, each group contained 54 volatile flavor compounds. Among them, the combined treatment method gave semi-dried large yellow croaker pleasant flavor characteristics. Besides, it also improved the content of flavor substances. In conclusion, the semi-dried yellow croaker under sodium-reduced conditions showed better performance in flavor characteristics.
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Affiliation(s)
- Junlong Mao
- School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, Zhejiang 310035, People's Republic of China; Zhejiang Provincial Collaborative Innovation Center of Food Safety and Nutrition, Zhejiang Gongshang University, Hangzhou, Zhejiang 310035, People's Republic of China
| | - Jingjing Fu
- School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, Zhejiang 310035, People's Republic of China; Zhejiang Provincial Collaborative Innovation Center of Food Safety and Nutrition, Zhejiang Gongshang University, Hangzhou, Zhejiang 310035, People's Republic of China
| | - Zhengyu Zhu
- School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, Zhejiang 310035, People's Republic of China; Zhejiang Provincial Collaborative Innovation Center of Food Safety and Nutrition, Zhejiang Gongshang University, Hangzhou, Zhejiang 310035, People's Republic of China
| | - Zhenzhi Cao
- School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, Zhejiang 310035, People's Republic of China; Zhejiang Provincial Collaborative Innovation Center of Food Safety and Nutrition, Zhejiang Gongshang University, Hangzhou, Zhejiang 310035, People's Republic of China
| | - Min Zhang
- School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, Zhejiang 310035, People's Republic of China; Zhejiang Provincial Collaborative Innovation Center of Food Safety and Nutrition, Zhejiang Gongshang University, Hangzhou, Zhejiang 310035, People's Republic of China
| | - Yanwei Yuan
- School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, Zhejiang 310035, People's Republic of China; Zhejiang Provincial Collaborative Innovation Center of Food Safety and Nutrition, Zhejiang Gongshang University, Hangzhou, Zhejiang 310035, People's Republic of China
| | - Tingting Chai
- School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, Zhejiang 310035, People's Republic of China; Zhejiang Provincial Collaborative Innovation Center of Food Safety and Nutrition, Zhejiang Gongshang University, Hangzhou, Zhejiang 310035, People's Republic of China
| | - Yuewen Chen
- School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, Zhejiang 310035, People's Republic of China; Zhejiang Provincial Collaborative Innovation Center of Food Safety and Nutrition, Zhejiang Gongshang University, Hangzhou, Zhejiang 310035, People's Republic of China.
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10
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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.
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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
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11
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Wang Y, Fu Q, Hu Y, Hua L, Li H, Xu G, Ni Q, Zhang Y. Determination of oxidative deterioration in edible oils by high-pressure photoionization time-of-flight mass spectrometry. Food Chem 2023; 424:136260. [PMID: 37244184 DOI: 10.1016/j.foodchem.2023.136260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 04/24/2023] [Accepted: 04/25/2023] [Indexed: 05/29/2023]
Abstract
Since lipid oxidation often causes serious food safety issues worldwide, determination of oil's oxidative deterioration becomes quite significant, which still calls for efficient analytical methods. In this work, high-pressure photoionization time-of-flight mass spectrometry (HPPI-TOFMS) was firstly introduced for rapid detection of oxidative deterioration in edible oils. Through non-targeted qualitative analysis, oxidized oils with various oxidation levels were successfully discriminated for the first time by coupling HPPI-TOFMS with the orthogonal partial least squares discriminant analysis (OPLS-DA). Furthermore, by targeted interpretation of the HPPI-TOFMS mass spectra and the subsequent regression analysis (signal intensities vs TOTOX values), good linear correlations were observed for several predominant VOCs. Those specific VOCs were promising oxidation indicators, which would play important roles as TOTOX to judge the oxidation states of tested samples. The proposed HPPI-TOFMS methodology can be used as an innovative tool for accurate and effective assessment of lipid oxidation in edible oils.
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Affiliation(s)
- Yan Wang
- The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, College of Food and Health, Zhejiang A & F University, Linan 311300, China.
| | - Qianwen Fu
- The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, College of Food and Health, Zhejiang A & F University, Linan 311300, China
| | - Yu Hu
- The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, College of Food and Health, Zhejiang A & F University, Linan 311300, China
| | - Lei Hua
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Haiyang Li
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Guangzhi Xu
- The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, College of Food and Health, Zhejiang A & F University, Linan 311300, China
| | - Qinxue Ni
- The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, College of Food and Health, Zhejiang A & F University, Linan 311300, China
| | - Youzuo Zhang
- The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, College of Food and Health, Zhejiang A & F University, Linan 311300, China.
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12
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Dou X, Zhang L, Chen Z, Wang X, Ma F, Yu L, Mao J, Li P. Establishment and evaluation of multiple adulteration detection of camellia oil by mixture design. Food Chem 2023; 406:135050. [PMID: 36462349 DOI: 10.1016/j.foodchem.2022.135050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 11/01/2022] [Accepted: 11/21/2022] [Indexed: 11/27/2022]
Abstract
Multiple adulteration is a common trick to mask adulteration detection methods. In this study, the representative multiple adulterated camellia oils were prepared according to the mixture design. Then, these representative oils were employed to build two-class classification models and validate one-class classification model combined with fatty acid profiles. The cross-validation results indicated that the recursive SVM model possessed higher classification accuracy (97.9%) than PLS-DA. In OCPLS model, the optimal percentage of RO, SO, CO and SUO was 2.8%, 0%, 7.2%, 0% respectively in adulterated camellia oil, which is the most similar to the authentic camellia oils. Further validation showed that five adulterated oils with the optimal percentage could be correctly identified, indicating that the OCPLS model could identify multiple adulterated oils with these four cheaper oils. Moreover, this study serves as a reference for one class classification model evaluation and a solution for multiple adulteration detection of other foods.
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Affiliation(s)
- Xinjing Dou
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Laboratory of Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Quality Inspection and Test Center for Oilseed Products, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Liangxiao Zhang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Laboratory of Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Quality Inspection and Test Center for Oilseed Products, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China; College of Food Science and Engineering, Nanjing University of Finance and Economics/Collaborative Innovation Center for Modern Grain Circulation and Safety, Nanjing 210023, China; Hubei Hongshan Laboratory, Wuhan 430070, China.
| | - Zhe Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Laboratory of Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Quality Inspection and Test Center for Oilseed Products, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Xuefang Wang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Laboratory of Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Quality Inspection and Test Center for Oilseed Products, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Fei Ma
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Laboratory of Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Quality Inspection and Test Center for Oilseed Products, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Li Yu
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Laboratory of Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Quality Inspection and Test Center for Oilseed Products, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Jin Mao
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Laboratory of Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Quality Inspection and Test Center for Oilseed Products, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China; Hubei Hongshan Laboratory, Wuhan 430070, China
| | - Peiwu Li
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Laboratory of Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Quality Inspection and Test Center for Oilseed Products, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China; Hubei Hongshan Laboratory, Wuhan 430070, China; Xianghu Laboratory, Hangzhou 311231, China
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13
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Yuan L, Meng X, Xin K, Ju Y, Zhang Y, Yin C, Hu L. A comparative study on classification of edible vegetable oils by infrared, near infrared and fluorescence spectroscopy combined with chemometrics. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 288:122120. [PMID: 36473296 DOI: 10.1016/j.saa.2022.122120] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 11/07/2022] [Accepted: 11/11/2022] [Indexed: 06/17/2023]
Abstract
Driven by economic benefits like any other foods, vegetable oil has long been plagued by mislabeling and adulteration. Many studies have addressed the field of classification and identification of vegetable oils by various analysis techniques, especially spectral analysis. A comparative study was performed using Fourier transform infrared spectroscopy (FTIR), visible near-infrared spectroscopy (Vis-NIR) and excitation-emission matrix fluorescence spectroscopy (EEMs) combined with chemometrics to distinguish different types of edible vegetable oils. FTIR, Vis-NIR and EEMs datasets of 147 samples of five vegetable oils from different brands were analyzed. Two types of pattern recognition methods, principal component analysis (PCA)/multi-way principal component analysis (M-PCA) and partial least squares discriminant analysis (PLS-DA)/multilinear partial least squares discriminant analysis (N-PLS-DA), were used to resolve these data and distinguish vegetable oil types, respectively. PCA/M-PCA analysis exhibited that three spectral data of five vegetable oils showed a clustering trend. The total correct recognition rate of the training set and prediction set of FTIR spectra of vegetable oil based on PLS-DA method are 100%. The total recognition rate of Vis-NIR based on PLS-DA are 100% and 97.96%. However, the total correct recognition rate of training set and prediction set of EEMs data based on N-PLS-DA method is 69.39% and 75.51%, respectively. The comparative study showed that FTIR and Vis-NIR combined with chemometrics were more suitable for vegetable oil species identification than EEMs technique. The reason may be concluded that almost all chemical components in vegetable oil can produce FTIR and NIR absorption, while only a small amount of fluorophores can produce fluorescence. That is, FTIR and NIR can provide more spectral information than EEMs. Analysis of EEMs data using self-weighted alternating trilinear decomposition (SWATLD) also showed that fluorophores were a few and irregularly distributed in vegetable oils.
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Affiliation(s)
- Libo Yuan
- School of Chemistry and Chemical Engineering, Henan University of Technology, Zhengzhou 450001, China
| | - Xiangru Meng
- School of Chemistry and Chemical Engineering, Henan University of Technology, Zhengzhou 450001, China
| | - Kehui Xin
- School of Chemistry and Chemical Engineering, Henan University of Technology, Zhengzhou 450001, China
| | - Ying Ju
- School of Chemistry and Chemical Engineering, Henan University of Technology, Zhengzhou 450001, China
| | - Yan Zhang
- School of Chemistry and Chemical Engineering, Henan University of Technology, Zhengzhou 450001, China
| | - Chunling Yin
- School of Chemistry and Chemical Engineering, Henan University of Technology, Zhengzhou 450001, China
| | - Leqian Hu
- School of Chemistry and Chemical Engineering, Henan University of Technology, Zhengzhou 450001, China.
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14
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The Effect of Data Fusion on Improving the Accuracy of Olive Oil Quality Measurement. Food Chem X 2023; 18:100622. [DOI: 10.1016/j.fochx.2023.100622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 02/08/2023] [Accepted: 02/28/2023] [Indexed: 03/08/2023] Open
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15
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Guo D, Yang Y, Wu Y, Liu Y, Cao L, Shi Y, Wan N, Wu Z. Chemical Composition Analysis and Discrimination of Essential Oils of Artemisia Argyi Folium from Different Germplasm Resources Based on Electronic Nose and GC/MS Combined with Chemometrics. Chem Biodivers 2023; 20:e202200991. [PMID: 36650717 DOI: 10.1002/cbdv.202200991] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 01/02/2023] [Accepted: 01/17/2023] [Indexed: 01/19/2023]
Abstract
In this study, the electronic nose and GC/MS were used to analyze the chemical components of essential oils from different germplasm resources of Artemisia argyi Folium (A. argyi), in order to quickly identify essential oils of A. argyi from different germplasm resources and clarify the differences among different A. argyi samples. The essential oils of A. argyi were extracted by steam distillation. This article describes for the first time that electronic nose combined with chemometrics can distinguish the essential oils of A. argyi from different germplasm, which proves the reliability and potential of this technology. GC/MS was used to identify 134 volatile components from the essential oil of A. argyi. The main bioactive components were cineole, thujarone, artemisia ketone, β-caryophyllene, (-)-4-terpinol, 3,3,6-trimethyl-1,5-heptadien-4-ol, (-)-α-thujone, camphor, borneol. In addition, the results of principal component analysis (PCA) and hierarchical cluster analysis (HCA) showed that there were significant differences in the essential oils of A. argyi from different germplasm resources, terpenes, alcohols and ketones played an important role in identifying the essential oils of A. argyi from different germplasm resources. This indicates that electronic nose and GC/MS combined with chemometrics can be used as reliable techniques to identify different germplasm resources of A. argyi, and provide certain reference value for quality evaluation, selection of high-quality varieties and rational development of resources of A. argyi.
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Affiliation(s)
- Dongyun Guo
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang, 330004, China
- Affiliated Stomatological Hospital of Nanchang University, The Key Laboratory of Oral Biomedicine, Jiangxi Province, Nanchang, 330004, China
| | - Yiqin Yang
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang, 330004, China
| | - Yi Wu
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang, 330004, China
| | - Yang Liu
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang, 330004, China
| | - Lan Cao
- Research Center for Traditional Chinese Medicine Resourcing and Ethnic Minority Medicine, Jiangxi University of Chinese Medicine, Nanchang, 330004, China
| | - Yan Shi
- Affiliated Stomatological Hospital of Nanchang University, The Key Laboratory of Oral Biomedicine, Jiangxi Province, Nanchang, 330004, China
| | - Na Wan
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang, 330004, China
| | - Zhenfeng Wu
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang, 330004, China
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16
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Zhang J, Zhang M, Bhandari B, Wang M. Basic sensory properties of essential oils from aromatic plants and their applications: a critical review. Crit Rev Food Sci Nutr 2023; 64:6990-7003. [PMID: 36803316 DOI: 10.1080/10408398.2023.2177611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2023]
Abstract
With higher standards in terms of diet and leisure enjoyment, spices and essential oils of aromatic plants (APEOs) are no longer confined to the food industry. The essential oils (EOs) produced from them are the active ingredients that contribute to different flavors. The multiple odor sensory properties and their taste characteristics of APEOs are responsible for their widespread use. The research on the flavor of APEOs is an evolving process attracting the attention among scientists in the past decades. For APEOs, which are used for a long time in the catering and leisure industries, it is necessary to analyze the components associated with the aromas and the tastes. It is important to identify the volatile components and assure quality of APEOs in order to expand their application. It is worth celebrating the different means by which the loss of flavor of APEOs can be retarded in practice. Unfortunately, relatively little research has been done on the structure and flavor mechanisms of APEOs. This also points the way to future research on APEOs.Therefore, this paper reviews the principles of flavor, identification of components and sensory pathways in humans for APEOs. Moreover, the article outlines the means of increasing the efficiency of using of APEOs. Finally, with respect to the sensory applications of APEOs, the review focuses on the practical application of APEOs in food sector and in aromatherapy.
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Affiliation(s)
- Jiong Zhang
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi, China
- China General Chamber of Commerce Key Laboratory on Fresh Food Processing & Preservation, Jiangnan University, Wuxi, China
| | - Min Zhang
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi, China
- Jiangsu Province International Joint Laboratory on Fresh Food Smart Processing and Quality Monitoring, Jiangnan University, Wuxi, China
| | - Bhesh Bhandari
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, Queensland, Australia
| | - Mingqi Wang
- R & D Center, Zhengzhou Xuemailong Food Flavor Co, Zhengzhou, China
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17
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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.
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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
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18
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P H, Rangarajan M, Pandya HJ. Breath VOC analysis and machine learning approaches for disease screening: a review. J Breath Res 2023; 17. [PMID: 36634360 DOI: 10.1088/1752-7163/acb283] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 01/12/2023] [Indexed: 01/14/2023]
Abstract
Early disease detection is often correlated with a reduction in mortality rate and improved prognosis. Currently, techniques like biopsy and imaging that are used to screen chronic diseases are invasive, costly or inaccessible to a large population. Thus, a non-invasive disease screening technology is the need of the hour. Existing non-invasive methods like gas chromatography-mass spectrometry, selected-ion flow-tube mass spectrometry, and proton transfer reaction-mass-spectrometry are expensive. These techniques necessitate experienced operators, making them unsuitable for a large population. Various non-invasive sources are available for disease detection, of which exhaled breath is preferred as it contains different volatile organic compounds (VOCs) that reflect the biochemical reactions in the human body. Disease screening by exhaled breath VOC analysis can revolutionize the healthcare industry. This review focuses on exhaled breath VOC biomarkers for screening various diseases with a particular emphasis on liver diseases and head and neck cancer as examples of diseases related to metabolic disorders and diseases unrelated to metabolic disorders, respectively. Single sensor and sensor array-based (Electronic Nose) approaches for exhaled breath VOC detection are briefly described, along with the machine learning techniques used for pattern recognition.
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Affiliation(s)
- Haripriya P
- Department of Electronic Systems Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Madhavan Rangarajan
- Department of Electronic Systems Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Hardik J Pandya
- Department of Electronic Systems Engineering, Indian Institute of Science, Bangalore 560012, India.,Centre for Product Design and Manufacturing, Indian Institute of Science, Bangalore 560012, India
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19
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Cho S, Park TH. Advances in the Production of Olfactory Receptors for Industrial Use. Adv Biol (Weinh) 2023; 7:e2200251. [PMID: 36593488 DOI: 10.1002/adbi.202200251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 12/11/2022] [Indexed: 01/04/2023]
Abstract
In biological olfactory systems, olfactory receptors (ORs) can recognize and discriminate between thousands of volatile organic compounds with very high sensitivity and specificity. The superior properties of ORs have led to the development of OR-based biosensors that have shown promising potential in many applications over the past two decades. In particular, newly designed technologies in gene synthesis, protein expression, solubilization, purification, and membrane mimetics for membrane proteins have greatly opened up the previously inaccessible industrial potential of ORs. In this review, gene design, expression and solubilization strategies, and purification and reconstitution methods available for modern industrial applications are examined, with a focus on ORs. The limitations of current OR production technology are also estimated, and future directions for further progress are suggested.
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Affiliation(s)
- Seongyeon Cho
- School of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, Republic of Korea
| | - Tai Hyun Park
- School of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, Republic of Korea
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20
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Rozman M, Lukšič M. Stainless Steel Foil-Based Label-Free Modular Thin-Film Electrochemical Detector for Solvent Identification. MICROMACHINES 2022; 13:2256. [PMID: 36557555 PMCID: PMC9780910 DOI: 10.3390/mi13122256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 12/12/2022] [Accepted: 12/16/2022] [Indexed: 06/17/2023]
Abstract
Most organic solvents are colorless liquids, usually stored in sealed containers. In many cases, their identification depends on the appropriate description on the container to prevent mishandling or mixing with other materials. Although modern laboratories rely heavily on identification technologies, such as digitized inventories and spectroscopic methods (e.g., NMR or FTIR), there may be situations where these cannot be used due to technical failure, lack of equipment, or time. An example of a portable and cost-effective solution to this problem is an electrochemical sensor. However, these are often limited to electrochemical impedance spectroscopy (EIS) or voltammetry methods. To address this problem, we present a novel modular electrochemical sensor for solvent identification that can be used with either an EIS-enabled potentiostat/galvanostat or a simple multimeter. A novel method of fabricating and using a sensor consisting of a thin-film coating of an organic substance on a stainless-steel electrode substrate is presented. The differences in the solubility of the thin film in different solvents are used to distinguish between common organic solvents such as water, ethanol, and tetrahydrofuran.
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Affiliation(s)
- Martin Rozman
- FunGlass—Centre for Functional and Surface Functionalized Glass, Alexander Dubček University of Trenčín, Študentská 2, SK-91150 Trenčín, Slovakia
| | - Miha Lukšič
- Faculty of Chemistry and Chemical Technology, University of Ljubljana , Večna pot 113, SI-1000 Ljubljana, Slovenia
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21
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Quality control of woody edible oil: The application of fluorescence spectroscopy and the influencing factors of fluorescence. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.109275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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22
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Liu X, Wang X, Cheng Y, Wu Y, Yan Y, Li Z. Variations in volatile organic compounds in Zhenyuan Daocai samples at different storage durations evaluated using E-nose, E-tongue, gas chromatography, and spectrometry. Lebensm Wiss Technol 2022. [DOI: 10.1016/j.lwt.2022.114186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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23
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Chen Y, Du L, Tian Y, Zhu P, Liu S, Liang D, Liu Y, Wang M, Chen W, Wu C. Progress in the Development of Detection Strategies Based on Olfactory and Gustatory Biomimetic Biosensors. BIOSENSORS 2022; 12:858. [PMID: 36290995 PMCID: PMC9599203 DOI: 10.3390/bios12100858] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 10/01/2022] [Accepted: 10/08/2022] [Indexed: 06/16/2023]
Abstract
The biomimetic olfactory and gustatory biosensing devices have broad applications in many fields, such as industry, security, and biomedicine. The development of these biosensors was inspired by the organization of biological olfactory and gustatory systems. In this review, we summarized the most recent advances in the development of detection strategies for chemical sensing based on olfactory and gustatory biomimetic biosensors. First, sensing mechanisms and principles of olfaction and gustation are briefly introduced. Then, different biomimetic sensing detection strategies are outlined based on different sensing devices functionalized with various molecular and cellular components originating from natural olfactory and gustatory systems. Thereafter, various biomimetic olfactory and gustatory biosensors are introduced in detail by classifying and summarizing the detection strategies based on different sensing devices. Finally, the future directions and challenges of biomimetic biosensing development are proposed and discussed.
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Affiliation(s)
- Yating Chen
- Institute of Medical Engineering, Department of Biophysics, School of Basic Medical Sciences, Health Science Center, Xi’an Jiaotong University, Xi’an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases, Xi’an Jiaotong University, Ministry of Education of China, Xi’an 710061, China
| | - Liping Du
- Institute of Medical Engineering, Department of Biophysics, School of Basic Medical Sciences, Health Science Center, Xi’an Jiaotong University, Xi’an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases, Xi’an Jiaotong University, Ministry of Education of China, Xi’an 710061, China
| | - Yulan Tian
- Institute of Medical Engineering, Department of Biophysics, School of Basic Medical Sciences, Health Science Center, Xi’an Jiaotong University, Xi’an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases, Xi’an Jiaotong University, Ministry of Education of China, Xi’an 710061, China
| | - Ping Zhu
- Institute of Medical Engineering, Department of Biophysics, School of Basic Medical Sciences, Health Science Center, Xi’an Jiaotong University, Xi’an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases, Xi’an Jiaotong University, Ministry of Education of China, Xi’an 710061, China
| | - Shuge Liu
- Institute of Medical Engineering, Department of Biophysics, School of Basic Medical Sciences, Health Science Center, Xi’an Jiaotong University, Xi’an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases, Xi’an Jiaotong University, Ministry of Education of China, Xi’an 710061, China
| | - Dongxin Liang
- Institute of Medical Engineering, Department of Biophysics, School of Basic Medical Sciences, Health Science Center, Xi’an Jiaotong University, Xi’an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases, Xi’an Jiaotong University, Ministry of Education of China, Xi’an 710061, China
| | - Yage Liu
- Institute of Medical Engineering, Department of Biophysics, School of Basic Medical Sciences, Health Science Center, Xi’an Jiaotong University, Xi’an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases, Xi’an Jiaotong University, Ministry of Education of China, Xi’an 710061, China
| | - Miaomiao Wang
- Institute of Medical Engineering, Department of Biophysics, School of Basic Medical Sciences, Health Science Center, Xi’an Jiaotong University, Xi’an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases, Xi’an Jiaotong University, Ministry of Education of China, Xi’an 710061, China
| | - Wei Chen
- Institute of Medical Engineering, Department of Biophysics, School of Basic Medical Sciences, Health Science Center, Xi’an Jiaotong University, Xi’an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases, Xi’an Jiaotong University, Ministry of Education of China, Xi’an 710061, China
| | - Chunsheng Wu
- Institute of Medical Engineering, Department of Biophysics, School of Basic Medical Sciences, Health Science Center, Xi’an Jiaotong University, Xi’an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases, Xi’an Jiaotong University, Ministry of Education of China, Xi’an 710061, China
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24
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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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25
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Effects of ultrasound pretreatment at different powers on flavor characteristics of enzymatic hydrolysates of cod (Gadus macrocephalus) head. Food Res Int 2022; 159:111612. [DOI: 10.1016/j.foodres.2022.111612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 06/25/2022] [Accepted: 06/29/2022] [Indexed: 11/22/2022]
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26
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Sánchez R, Fernández A, Martín-Tornero E, Meléndez F, Lozano J, Martín-Vertedor D. Application of Digital Olfaction for Table Olive Industry. SENSORS (BASEL, SWITZERLAND) 2022; 22:5702. [PMID: 35957258 PMCID: PMC9370875 DOI: 10.3390/s22155702] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 07/22/2022] [Accepted: 07/28/2022] [Indexed: 06/15/2023]
Abstract
The International Olive Council (IOC) established that olives must be free of odors, off-flavors, and absent of abnormal ongoing alterations or fermentations. The use of electronic devices could help when classifying defects in a fast, non-destructive, cheap, and environmentally friendly way. For all of that, table olives were evaluated according to IOC regulation in order to classify the defect predominant perceiving (DPP) of the table olives and their intensity. Abnormal fermentation defects of Spanish-style table olives were assessed previously by an IOC-validated tasting panel. 'Zapateria', 'Putrid', and 'Butyric' were the defects found at different concentrations. Different volatile compounds were identified by gas chromatography in altered table olives. The same samples were measured with an electronic nose device (E-nose). E-nose data combined with chemometrics algorithms, such as PCA and PLS-DA, were able to successfully discriminate between healthy and non-healthy table olives, being this last one also separated between the first and second categories. Volatile compounds obtained with gas chromatography could be related to the E-nose measuring and sensory analysis, being capable of matching the different defects with their correspondents' volatile compounds.
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Affiliation(s)
- Ramiro Sánchez
- Technological Institute of Food and Agriculture CICYTEX-INTAEX, Junta of Extremadura, Avda. Adolfo Suárez s/n, 06007 Badajoz, Spain;
| | - Antonio Fernández
- Technological Institute of Food and Agriculture CICYTEX-INTAEX, Junta of Extremadura, Avda. Adolfo Suárez s/n, 06007 Badajoz, Spain;
| | | | - Félix Meléndez
- Industrial Engineering School, University of Extremadura, 06006 Badajoz, Spain; (F.M.); (J.L.)
| | - Jesús Lozano
- Industrial Engineering School, University of Extremadura, 06006 Badajoz, Spain; (F.M.); (J.L.)
- Research Institute of Agricultural Resources (INURA), Avda. de la Investigación s/n, Campus Universitario, 06071 Badajoz, Spain
| | - Daniel Martín-Vertedor
- Technological Institute of Food and Agriculture CICYTEX-INTAEX, Junta of Extremadura, Avda. Adolfo Suárez s/n, 06007 Badajoz, Spain;
- Research Institute of Agricultural Resources (INURA), Avda. de la Investigación s/n, Campus Universitario, 06071 Badajoz, Spain
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27
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Yang Y, Zhao X, Wang R. Research progress on the formation mechanism and detection technology of bread flavor. J Food Sci 2022; 87:3724-3736. [PMID: 35894512 DOI: 10.1111/1750-3841.16254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 06/08/2022] [Accepted: 06/27/2022] [Indexed: 11/29/2022]
Abstract
With a long history of fermentation technology and rich flavors, bread is widely consumed by people all around the world. The consumer market is huge and the demand is wide. However, the formation mechanism of bread baking flavor has not been completely defined. In order to improve the breadmaking process and the quality of bread, the main flavor substances produced in bread baking, the formation mechanism, and the detection technology of bread baking flavor are carefully summarized in this paper. The generation conditions and formation mechanism of flavor substances during the bread baking process are expounded, and the limitations of some current bread flavor detection technologies are proposed, which will provide theoretical basis for effectively regulating the generation of flavor substances in the bread baking process and making bread with good flavor and rich nutrition in the future.
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Affiliation(s)
- Yuxia Yang
- College of Grain Science and Technology, Shenyang Normal University, Shenyang, China
| | - Xiuhong Zhao
- College of Grain Science and Technology, Shenyang Normal University, Shenyang, China
| | - Rong Wang
- College of Grain Science and Technology, Shenyang Normal University, Shenyang, China
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28
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Zhu L, Ma Q, Chen J, Zhao G. Current progress on innovative pest detection techniques for stored cereal grains and thereof powders. Food Chem 2022; 396:133706. [PMID: 35868281 DOI: 10.1016/j.foodchem.2022.133706] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Revised: 07/10/2022] [Accepted: 07/12/2022] [Indexed: 12/12/2022]
Abstract
For stored grains and their powders, pest infestation has always been a knotty problem and thus comprises a serious threat to global food security. Obviously, timely, rapid and accurate pest detection methods are of extreme importance to protect grains from pest mouth. In facing the defects of traditional methods, such as visual inspection, grain flotation and pest trap, diverse innovative approaches progressed fast alternatively, either targeting pest itself or diagnosing pest-induced changes. The former includes machine vision, metabolite analysis, pest-specific protein techniques, molecular techniques, bioacoustics analysis, conductive roller mill, low-field nuclear magnetic resonance spectroscopy and imaging, while the latter consists of thermal imaging, near-infrared spectroscopy and hyperspectral imaging, impact acoustics analysis, soft X-ray imaging and tomography. The principle, operation procedure, pros and cons and application scenarios were discussed for each method. The results herein hope to promote the technical revolution of pest inspection in stored cereal grains and their powders.
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Affiliation(s)
- Lijun Zhu
- College of Food Science, Southwest University, Chongqing 400715, People's Republic of China
| | - Qian Ma
- College of Food Science, Southwest University, Chongqing 400715, People's Republic of China
| | - Jia Chen
- College of Food Science, Southwest University, Chongqing 400715, People's Republic of China
| | - Guohua Zhao
- College of Food Science, Southwest University, Chongqing 400715, People's Republic of China; Chongqing Key Laboratory of Speciality Food Co-Built by Sichuan and Chongqing, Chongqing 400715, People's Republic of China.
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29
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Abstract
A lab-made electronic nose (Enose) with vacuum sampling and a sensor array, comprising nine metal oxide semiconductor Figaro gas sensors, was tested for the quantitative analysis of vapor–liquid equilibrium, described by Henry’s law, of aqueous solutions of organic compounds: three alcohols (i.e., methanol, ethanol, and propanol) or three chemical compounds with different functional groups (i.e., acetaldehyde, ethanol, and ethyl acetate). These solutions followed a fractional factorial design to guarantee orthogonal concentrations. Acceptable predictive ridge regression models were obtained for training, with RSEs lower than 7.9, R2 values greater than 0.95, slopes varying between 0.84 and 1.00, and intercept values close to the theoretical value of zero. Similar results were obtained for the test data set: RSEs lower than 8.0, R2 values greater than 0.96, slopes varying between 0.72 and 1.10, and some intercepts equal to the theoretical value of zero. In addition, the total mass of the organic compounds of each aqueous solution could be predicted, pointing out that the sensors measured mainly the global contents of the vapor phases. The satisfactory quantitative results allowed to conclude that the Enose could be a useful tool for the analysis of volatiles from aqueous solutions containing organic compounds for which Henry’s law is applicable.
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30
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Determination of the Masking Effect of the ‘Zapateria’ Defect in Flavoured Stuffed Olives Using E-Nose. Molecules 2022; 27:molecules27134300. [PMID: 35807543 PMCID: PMC9267996 DOI: 10.3390/molecules27134300] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 06/26/2022] [Accepted: 06/30/2022] [Indexed: 11/27/2022] Open
Abstract
Spanish-style table olives are one of the most common processed foods in the Mediterranean countries. Lack of control during fermentation can lead to one of the main defects of the olive, called ‘Zapateria’, caused by the combination of volatile fatty acids reminiscent of rotten leather. In this study, table olives altered with ‘Zapateria’ defect were stuffed with a hydrocolloid flavoured with the aroma ‘Mojo picón’ to improve consumer acceptance. Sensory analysis, determination of volatile compounds and electronic nose (E-nose) were used to evaluate the quality of the olives. The control samples had a high concentration of the defect ‘Zapateria’ and were classified in the second commercial category, while higher ‘Mojo picón’ flavour concentrations resulted in these olives being classified as ‘extra category’ (a masking effect). The main volatile compounds in olives with ‘Zapateria’ defect were cyclohexanecarboxylic acid and pentanoic acid. E-nose allowed discrimination between stuffed olives without added flavouring and olives with ‘Mojo picón’ flavouring at different concentrations. Finally, PLS regression allowed a predictive linear model to be established between E-nose and sensory analysis values. The RP2 values were 0.74 for perceived defect and 0.86 for perceived aroma. The E-nose was successfully applied for the first time to classify Spanish-style table olives with ‘Zapateria’ defect intensity and with the addition of the ‘Mojo picón’ aroma masking the defect.
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31
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Wang Y, Hua L, Fu Q, Wu C, Zhang C, Li H, Xu G, Ni Q, Zhang Y. Rapid Identification of Adulteration in Extra Virgin Olive Oil via Dynamic Headspace Sampling and High-Pressure Photoionization Time-of-Flight Mass Spectrometry. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2022; 70:6775-6784. [PMID: 35623031 DOI: 10.1021/acs.jafc.2c01361] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
High-pressure photoionization time-of-flight mass spectrometry (HPPI-TOFMS) combined with dynamic headspace sampling was developed for rapid identification of adulteration in extra virgin olive oil (EVOO). The volatile organic compound (VOC) fingerprints of EVOO, refined rapeseed oil (r-RO), peanut oil (PO), corn oil (CO), fragrant rapeseed oil (f-RO), and sunflower oil (SO) were obtained in just 1.5 min, which enabled satisfactory classification of different edible oils. 1,4-Bis(methylene)cyclohexane and dimethyl disulfide were unique VOCs in r-RO and f-RO, respectively, while 2,5-dimethylpyrazine and 2-methylpyrazine were distinctive VOCs in PO. Percentages as low as 3% r-RO, 1% PO, and 1% f-RO in r-RO-EVOO, PO-EVOO, and f-RO-EVOO mixtures, respectively, were successfully identified based on the characteristic VOCs. Linear regression equations of these VOCs were established and utilized for predicting the adulteration proportions. The good agreements between the actual adulteration proportions and the predicted ones demonstrated that HPPI-TOFMS was reliable for the quantification of EVOO adulteration.
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Affiliation(s)
- Yan Wang
- The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, College of Food and Health, Zhejiang A & F University, Linan, Hangzhou 311300, China
| | - Lei Hua
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, People's Republic of China
- Dalian Key Laboratory for Online Analytical Instrumentation, Dalian, Liaoning 116023, People's Republic of China
| | - Qianwen Fu
- The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, College of Food and Health, Zhejiang A & F University, Linan, Hangzhou 311300, China
| | - Chenxin Wu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, People's Republic of China
- Dalian Key Laboratory for Online Analytical Instrumentation, Dalian, Liaoning 116023, People's Republic of China
| | - Chong Zhang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, People's Republic of China
- Dalian Key Laboratory for Online Analytical Instrumentation, Dalian, Liaoning 116023, People's Republic of China
| | - Haiyang Li
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, People's Republic of China
- Dalian Key Laboratory for Online Analytical Instrumentation, Dalian, Liaoning 116023, People's Republic of China
| | - Guangzhi Xu
- The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, College of Food and Health, Zhejiang A & F University, Linan, Hangzhou 311300, China
| | - Qinxue Ni
- The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, College of Food and Health, Zhejiang A & F University, Linan, Hangzhou 311300, China
| | - Youzuo Zhang
- The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, College of Food and Health, Zhejiang A & F University, Linan, Hangzhou 311300, China
- Zhejiang Jiaozhi Technology Co., Ltd., Linan, Hangzhou 311300, China
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32
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Zero Defect Manufacturing in the Food Industry: Virgin Olive Oil Production. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12105184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
This paper provides a zero defect manufacturing (ZDM) approach designed for the virgin olive oil (VOO) industry, with the objective of producing the best possible product using sustainable methods. A deep analysis of related work for ZDM and the current state-of-the-art technology in the VOO elaboration process is presented, along with the implications of the well-known trade-off between quality and extraction yield and the importance of having the right information on the state of the fruits and the main technological variables of the process. Currently available new technologies, such as smart devices with cloud connectivity, enable having the required amount of data and information in real-time, thus making the concept of ZDM possible. Together with the proposed ZDM approach and strategies, the basic requirements and the first steps towards the implementation of ZDM in this productive sector are identified.
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33
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Tian H, Chen B, Lou X, Yu H, Yuan H, Huang J, Chen C. Rapid detection of acid neutralizers adulteration in raw milk using FGC E-nose and chemometrics. JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION 2022. [DOI: 10.1007/s11694-022-01403-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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34
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Tan WK, Husin Z, Yasruddin ML, Ismail MAH. Recent technology for food and beverage quality assessment: a review. JOURNAL OF FOOD SCIENCE AND TECHNOLOGY 2022; 60:1681-1694. [PMID: 35463865 PMCID: PMC9014778 DOI: 10.1007/s13197-022-05439-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Revised: 03/13/2022] [Accepted: 03/16/2022] [Indexed: 12/02/2022]
Abstract
Food and beverage assessment is an evaluation method used to measure the strengths and weaknesses of a food and beverage system to make improvements. These assessments had become crucial, especially in the issues of adulteration, replacement, and contamination that happened in artificial adjustment relating to the quality, weight and volume. Thus, this review will examine and describe features recently applied in image, odour, taste and electromagnetic, relevant to the food and beverages assessment. This review will also compare and discuss each technique and provides suggestions based on the current technology. This review will deliberate technology integration and the involvement of deep learning to enable several types of current technologies, such as imaging, odour and taste senses, and electromagnetic sensing, to be used in food evaluation applications for inspection and packaging.
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Affiliation(s)
- Wei Keong Tan
- Faculty of Electronic Engineering Technology, Universiti Malaysia Perlis, 02600 Arau, Perlis Malaysia
| | - Zulkifli Husin
- Faculty of Electronic Engineering Technology, Universiti Malaysia Perlis, 02600 Arau, Perlis Malaysia
| | - Muhammad Luqman Yasruddin
- Faculty of Electronic Engineering Technology, Universiti Malaysia Perlis, 02600 Arau, Perlis Malaysia
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35
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Sánchez R, Martín-Tornero E, Lozano J, Fernández A, Arroyo P, Meléndez F, Martín-Vertedor D. Electronic nose application for the discrimination of sterilization treatments applied to Californian-style black olive varieties. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2022; 102:2232-2241. [PMID: 34622476 DOI: 10.1002/jsfa.11561] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 09/07/2021] [Accepted: 10/08/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Olive oil continues to be the main destination for olives. The production of table olives is increasing. 'Californian-style' processes are among the most frequently employed to produce oxidized olives. Sensory evaluation requires the development of an instrumental detection method that can be used as an adjunct to traditional tasting panels. RESULTS An electronic nose (E-nose) was used to classify two varieties of olives following exposure to different sterilization. Principal component analysis (PCA) revealed that both varieties had different volatile profiles. Sensory panel evaluations were similar for both. Partial least squares-discriminant analysis (PLS-DA) obtained from the E-nose was able to separate the two varieties and explained 82% of total variance. Moreover, volatile profiles correctly classified olives according to sterilization times recorded up to 121 °C . The only exception was at F0 ≥ 22 min, at which a plot of PCA outcomes failed to differentiate scores. E-nose data showed similar results to those produced from the volatile analysis when grouping samples were sterilized to F0 ≥ 18 min, at the same time distinguishing these samples from those subjected to less intense thermal treatments. A partial least squares (PLS) chemometric approach was evaluated for quantifying important olive quality parameters. With regards to validation parameters, R P 2 pertaining to perceived defect was 0.88, whilst R P 2 pertaining to overall assessment was 0.78. CONCLUSIONS E-nose offers a fast, inexpensive and non-destructive method for discriminating between varieties and thermal treatments up to a point at which cooking defects are highly similar (from F0 = 18 onwards). © 2021 Society of Chemical Industry.
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Affiliation(s)
- Ramiro Sánchez
- Technological Institute of Food and Agriculture CICYTEX-INTAEX. Junta of Extremadura, Badajoz, Spain
| | - Elísabet Martín-Tornero
- Department of Agricultural and Forestry Engineering, School of Agrarian Engineering, University of Extremadura, Badajoz, Spain
| | - Jesús Lozano
- Industrial Engineering School, University of Extremadura, Badajoz, Spain
- Research Institute of Agricultural Resources (INURA), Campus Universitario, Badajoz, Spain
| | - Antonio Fernández
- Technological Institute of Food and Agriculture CICYTEX-INTAEX. Junta of Extremadura, Badajoz, Spain
| | - Patricia Arroyo
- Industrial Engineering School, University of Extremadura, Badajoz, Spain
| | - Félix Meléndez
- Industrial Engineering School, University of Extremadura, Badajoz, Spain
| | - Daniel Martín-Vertedor
- Technological Institute of Food and Agriculture CICYTEX-INTAEX. Junta of Extremadura, Badajoz, Spain
- Research Institute of Agricultural Resources (INURA), Campus Universitario, Badajoz, Spain
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36
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Lin H, Jiang H, Adade SYSS, Kang W, Xue Z, Zareef M, Chen Q. Overview of advanced technologies for volatile organic compounds measurement in food quality and safety. Crit Rev Food Sci Nutr 2022; 63:8226-8248. [PMID: 35357234 DOI: 10.1080/10408398.2022.2056573] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Food quality and nutrition have received much attention in recent decades, thanks to changes in consumer behavior and gradual increases in food consumption. The demand for high-quality food necessitates stringent quality assurance and process control measures. As a result, appropriate analytical tools are required to assess the quality of food and food products. VOCs analysis techniques may meet these needs because they are nondestructive, convenient to use, require little or no sample preparation, and are environmentally friendly. In this article, the main VOCs released from various foods during transportation, storage, and processing were reviewed. The principles of the most common VOCs analysis techniques, such as electronic nose, colorimetric sensor array, migration spectrum, infrared and laser spectroscopy, were discussed, as well as the most recent research in the field of food quality and safety evaluation. In particular, we described data processing algorithms and data analysis captured by these techniques in detail. Finally, the challenges and opportunities of these VOCs analysis techniques in food quality analysis were discussed, as well as future development trends and prospects of this field.
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Affiliation(s)
- Hao Lin
- School of Food and Biological Engineering, Jiangsu University, Jiangsu, P. R. China
| | - Hao Jiang
- School of Food and Biological Engineering, Jiangsu University, Jiangsu, P. R. China
| | | | - Wencui Kang
- School of Food and Biological Engineering, Jiangsu University, Jiangsu, P. R. China
| | - Zhaoli Xue
- School of Chemistry and Chemical Engineering, Jiangsu University, Jiangsu, P. R. China
| | - Muhammad Zareef
- School of Food and Biological Engineering, Jiangsu University, Jiangsu, P. R. China
| | - Quansheng Chen
- School of Food and Biological Engineering, Jiangsu University, Jiangsu, P. R. China
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37
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Jońca J, Pawnuk M, Arsen A, Sówka I. Electronic Noses and Their Applications for Sensory and Analytical Measurements in the Waste Management Plants-A Review. SENSORS 2022; 22:s22041510. [PMID: 35214407 PMCID: PMC8877425 DOI: 10.3390/s22041510] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 02/03/2022] [Accepted: 02/09/2022] [Indexed: 02/06/2023]
Abstract
Waste management plants are one of the most important sources of odorants that may cause odor nuisance. The monitoring of processes involved in the waste treatment and disposal as well as the assessment of odor impact in the vicinity of this type of facilities require two different but complementary approaches: analytical and sensory. The purpose of this work is to present these two approaches. Among sensory techniques dynamic and field olfactometry are considered, whereas analytical methodologies are represented by gas chromatography–mass spectrometry (GC-MS), single gas sensors and electronic noses (EN). The latter are the core of this paper and are discussed in details. Since the design of multi-sensor arrays and the development of machine learning algorithms are the most challenging parts of the EN construction a special attention is given to the recent advancements in the sensitive layers development and current challenges in data processing. The review takes also into account relatively new EN systems based on mass spectrometry and flash gas chromatography technologies. Numerous examples of applications of the EN devices to the sensory and analytical measurements in the waste management plants are given in order to summarize efforts of scientists on development of these instruments for constant monitoring of chosen waste treatment processes (composting, anaerobic digestion, biofiltration) and assessment of odor nuisance associated with these facilities.
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Affiliation(s)
- Justyna Jońca
- Department of Environment Protection Engineering, Faculty of Environmental Engineering, Wroclaw University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland; (J.J.); (M.P.)
| | - Marcin Pawnuk
- Department of Environment Protection Engineering, Faculty of Environmental Engineering, Wroclaw University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland; (J.J.); (M.P.)
| | - Adalbert Arsen
- calval.pl sp. z o.o., Emili Plater 7F/8, 65-395 Zielona Góra, Poland;
| | - Izabela Sówka
- Department of Environment Protection Engineering, Faculty of Environmental Engineering, Wroclaw University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland; (J.J.); (M.P.)
- Correspondence: ; Tel.: +48-71-320-25-60
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38
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Voss A, Schroeder R, Schulz S, Haueisen J, Vogler S, Horn P, Stallmach A, Reuken P. Detection of Liver Dysfunction Using a Wearable Electronic Nose System Based on Semiconductor Metal Oxide Sensors. BIOSENSORS 2022; 12:bios12020070. [PMID: 35200331 PMCID: PMC8869535 DOI: 10.3390/bios12020070] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 01/21/2022] [Accepted: 01/24/2022] [Indexed: 05/04/2023]
Abstract
The purpose of this exploratory study was to determine whether liver dysfunction can be generally classified using a wearable electronic nose based on semiconductor metal oxide (MOx) gas sensors, and whether the extent of this dysfunction can be quantified. MOx gas sensors are attractive because of their simplicity, high sensitivity, low cost, and stability. A total of 30 participants were enrolled, 10 of them being healthy controls, 10 with compensated cirrhosis, and 10 with decompensated cirrhosis. We used three sensor modules with a total of nine different MOx layers to detect reducible, easily oxidizable, and highly oxidizable gases. The complex data analysis in the time and non-linear dynamics domains is based on the extraction of 10 features from the sensor time series of the extracted breathing gas measurement cycles. The sensitivity, specificity, and accuracy for distinguishing compensated and decompensated cirrhosis patients from healthy controls was 1.00. Patients with compensated and decompensated cirrhosis could be separated with a sensitivity of 0.90 (correctly classified decompensated cirrhosis), a specificity of 1.00 (correctly classified compensated cirrhosis), and an accuracy of 0.95. Our wearable, non-invasive system provides a promising tool to detect liver dysfunctions on a functional basis. Therefore, it could provide valuable support in preoperative examinations or for initial diagnosis by the general practitioner, as it provides non-invasive, rapid, and cost-effective analysis results.
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Affiliation(s)
- Andreas Voss
- Institute of Innovative Health Technologies IGHT, Ernst-Abbe-Hochschule Jena, 07745 Jena, Germany; (R.S.); (S.S.)
- Institute of Biomedical Engineering and Informatics (BMTI), Technische Universität Ilmenau, 98693 Ilmenau, Germany;
- Correspondence: ; Tel.: +49-3677-69-2861
| | - Rico Schroeder
- Institute of Innovative Health Technologies IGHT, Ernst-Abbe-Hochschule Jena, 07745 Jena, Germany; (R.S.); (S.S.)
- UST Umweltsensortechnik GmbH, 99331 Geratal, Germany
| | - Steffen Schulz
- Institute of Innovative Health Technologies IGHT, Ernst-Abbe-Hochschule Jena, 07745 Jena, Germany; (R.S.); (S.S.)
| | - Jens Haueisen
- Institute of Biomedical Engineering and Informatics (BMTI), Technische Universität Ilmenau, 98693 Ilmenau, Germany;
| | - Stefanie Vogler
- Clinic for Internal Medicine IV, University Hospital Jena, 07747 Jena, Germany; (S.V.); (P.H.); (A.S.); (P.R.)
| | - Paul Horn
- Clinic for Internal Medicine IV, University Hospital Jena, 07747 Jena, Germany; (S.V.); (P.H.); (A.S.); (P.R.)
| | - Andreas Stallmach
- Clinic for Internal Medicine IV, University Hospital Jena, 07747 Jena, Germany; (S.V.); (P.H.); (A.S.); (P.R.)
| | - Philipp Reuken
- Clinic for Internal Medicine IV, University Hospital Jena, 07747 Jena, Germany; (S.V.); (P.H.); (A.S.); (P.R.)
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Calvini R, Pigani L. Toward the Development of Combined Artificial Sensing Systems for Food Quality Evaluation: A Review on the Application of Data Fusion of Electronic Noses, Electronic Tongues and Electronic Eyes. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22020577. [PMID: 35062537 PMCID: PMC8778015 DOI: 10.3390/s22020577] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 01/03/2022] [Accepted: 01/10/2022] [Indexed: 05/02/2023]
Abstract
Devices known as electronic noses (ENs), electronic tongues (ETs), and electronic eyes (EEs) have been developed in recent years in the in situ study of real matrices with little or no manipulation of the sample at all. The final goal could be the evaluation of overall quality parameters such as sensory features, indicated by the "smell", "taste", and "color" of the sample under investigation or in the quantitative detection of analytes. The output of these sensing systems can be analyzed using multivariate data analysis strategies to relate specific patterns in the signals with the required information. In addition, using suitable data-fusion techniques, the combination of data collected from ETs, ENs, and EEs can provide more accurate information about the sample than any of the individual sensing devices. This review's purpose is to collect recent advances in the development of combined ET, EN, and EE systems for assessing food quality, paying particular attention to the different data-fusion strategies applied.
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Affiliation(s)
- Rosalba Calvini
- Department of Life Sciences, University of Modena and Reggio Emilia, Pad. Besta Via Amendola 2, 42122 Reggio Emilia, Italy;
| | - Laura Pigani
- Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Via G. Campi 103, 41125 Modena, Italy
- Correspondence:
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40
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Wojnowski W, Kalinowska K. Machine Learning and Electronic Noses for Medical Diagnostics. Artif Intell Med 2022. [DOI: 10.1007/978-3-030-64573-1_329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2023]
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41
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Tan CH, Kong I, Irfan U, Solihin MI, Pui LP. Edible Oils Adulteration: A Review on Regulatory Compliance and Its Detection Technologies. J Oleo Sci 2021; 70:1343-1356. [PMID: 34497179 DOI: 10.5650/jos.ess21109] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Various events of edible oils adulteration with inferior ingredients were reported regularly in recent years. This review is aimed to provide an overview of edible oils adulteration practices, regulatory compliance and detection technologies. Many detection technologies for edible oils adulteration were developed in the past such as methods that are based on chromatography or spectroscopy. Electrochemical sensors like electric nose and tongue are also gaining popularity in the detection of adulterated virgin olive oil and virgin coconut oil. It can be concluded that these detection technologies are essential in the combat with food adulterers and can be improved.
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Affiliation(s)
- Choon Hui Tan
- Functional Food Research Group, Faculty of Applied Sciences, UCSI University.,Department of Food Science and Nutrition, Faculty of Applied Sciences, UCSI University
| | - Ianne Kong
- Functional Food Research Group, Faculty of Applied Sciences, UCSI University
| | - Umair Irfan
- Department of Food Science and Nutrition, Faculty of Applied Sciences, UCSI University
| | - Mahmud Iwan Solihin
- Mechanical and Mechatronics Department, Faculty of Engineering, Technology and Built Environment, UCSI University
| | - Liew Phing Pui
- Functional Food Research Group, Faculty of Applied Sciences, UCSI University.,Department of Food Science and Nutrition, Faculty of Applied Sciences, UCSI University
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42
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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.
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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
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Optimization of Electronic Nose Sensor Array for Tea Aroma Detecting Based on Correlation Coefficient and Cluster Analysis. CHEMOSENSORS 2021. [DOI: 10.3390/chemosensors9090266] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The electronic nose system is widely used in tea aroma detecting, and the sensor array plays a fundamental role for obtaining good results. Here, a sensor array optimization (SAO) method based on correlation coefficient and cluster analysis (CA) is proposed. First, correlation coefficient and distinguishing performance value (DPV) are calculated to eliminate redundant sensors. Then, the sensor independence is obtained through cluster analysis and the number of sensors is confirmed. Finally, the optimized sensor array is constructed. According to the results of the proposed method, sensor array for green tea (LG), fried green tea (LF) and baked green tea (LB) are constructed, and validation experiments are carried out. The classification accuracy using methods of linear discriminant analysis (LDA) based on the average value (LDA-ave) combined with nearest-neighbor classifier (NNC) can almost reach 94.44~100%. When the proposed method is used to discriminate between various grades of West Lake Longjing tea, LF can show comparable performance to that of the German PEN2 electronic nose. The electronic nose SAO method proposed in this paper can effectively eliminate redundant sensors and improve the quality of original tea aroma data. With fewer sensors, the optimized sensor array contributes to the miniaturization and cost reduction of the electronic nose system.
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E-Nose Discrimination of Abnormal Fermentations in Spanish-Style Green Olives. Molecules 2021; 26:molecules26175353. [PMID: 34500786 PMCID: PMC8434181 DOI: 10.3390/molecules26175353] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 08/28/2021] [Accepted: 08/30/2021] [Indexed: 01/24/2023] Open
Abstract
Current legislation in Spain indicates that table olives must be free of off-odors and off-flavors and without symptoms of ongoing alteration or abnormal fermentations. In this regard, the International Olive Council (IOC) has developed a protocol for the sensory classification of table olives according to the intensity of the predominantly perceived defect (PPD). An electronic nose (e-nose) was used to assess the abnormal fermentation defects of Spanish-style table olives that were previously classified by a tasting panel according to the IOC protocol, namely zapateria, butyric, putrid, and musty or humidity. When olives with different defects were mixed, the putrid defect had the greatest sensory impact on the others, while the butyric defect had the least sensory dominance. A total of 49 volatile compounds were identified by gas chromatography, and each defect was characterized by a specific profile. The e-nose data were analyzed using principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA). The different defects were clearly separated from each other and from the control treatment, independently of PPD intensity. Moreover, the e-nose differentiated control olives from table olives with combined sensory defects despite the dilution effect resulting from the combination. These results demonstrate that e-nose can be used as an olfactory sensor for the organoleptic classification of table olives and can successfully support the tasting panel.
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Borowik P, Adamowicz L, Tarakowski R, Wacławik P, Oszako T, Ślusarski S, Tkaczyk M. Development of a Low-Cost Electronic Nose for Detection of Pathogenic Fungi and Applying It to Fusarium oxysporum and Rhizoctonia solani. SENSORS (BASEL, SWITZERLAND) 2021; 21:5868. [PMID: 34502763 PMCID: PMC8433741 DOI: 10.3390/s21175868] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 08/21/2021] [Accepted: 08/24/2021] [Indexed: 02/06/2023]
Abstract
Electronic noses can be applied as a rapid, cost-effective option for several applications. This paper presents the results of measurements of samples of two pathogenic fungi, Fusarium oxysporum and Rhizoctonia solani, performed using two constructions of a low-cost electronic nose. The first electronic nose used six non-specific Figaro Inc. metal oxide gas sensors. The second one used ten sensors from only two models (TGS 2602 and TGS 2603) operating at different heater voltages. Sets of features describing the shapes of the measurement curves of the sensors' responses when exposed to the odours were extracted. Machine learning classification models using the logistic regression method were created. We demonstrated the possibility of applying the low-cost electronic nose data to differentiate between the two studied species of fungi with acceptable accuracy. Improved classification performance could be obtained, mainly for measurements using TGS 2603 sensors operating at different voltage conditions.
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Affiliation(s)
- Piotr Borowik
- Faculty of Physics, Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warszawa, Poland; (P.B.); (R.T.); (P.W.)
| | - Leszek Adamowicz
- Faculty of Physics, Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warszawa, Poland; (P.B.); (R.T.); (P.W.)
| | - Rafał Tarakowski
- Faculty of Physics, Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warszawa, Poland; (P.B.); (R.T.); (P.W.)
| | - Przemysław Wacławik
- Faculty of Physics, Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warszawa, Poland; (P.B.); (R.T.); (P.W.)
| | - Tomasz Oszako
- Forest Protection Department, Forest Research Institute, ul. Braci Leśnej 3, 05-090 Sękocin Stary, Poland; (T.O.); (S.Ś.); (M.T.)
| | - Sławomir Ślusarski
- Forest Protection Department, Forest Research Institute, ul. Braci Leśnej 3, 05-090 Sękocin Stary, Poland; (T.O.); (S.Ś.); (M.T.)
| | - Miłosz Tkaczyk
- Forest Protection Department, Forest Research Institute, ul. Braci Leśnej 3, 05-090 Sękocin Stary, Poland; (T.O.); (S.Ś.); (M.T.)
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Kang W, Lin H, Jiang H, Yao-Say Solomon Adade S, Xue Z, Chen Q. Advanced applications of chemo-responsive dyes based odor imaging technology for fast sensing food quality and safety: A review. Compr Rev Food Sci Food Saf 2021; 20:5145-5172. [PMID: 34409725 DOI: 10.1111/1541-4337.12823] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 06/24/2021] [Accepted: 07/06/2021] [Indexed: 01/18/2023]
Abstract
Public attention to foodquality and safety has been increased significantly. Therefore, appropriate analytical tools are needed to analyze and sense the food quality and safety. Volatile organic compounds (VOCs) are important indicators for the quality and safety of food products. Odor imaging technology based on chemo-responsive dyes is one of the most promising methods for analysis of food products. This article reviews the sensing and imaging fundamentals of odor imaging technology based on chemo-responsive dyes. The aim is to give detailed outlines about the theory and principles of using odor imaging technology for VOCs detection, and to focus primarily on its applications in the field of quality and safety evaluation of food products, as well as its future applicability in modern food industries and research. The literatures presented in this review clearly demonstrated that imaging technology based on chemo-responsive dyes has the exciting effect to inspect such as quality assessment of cereal , wine and vinegar flavored foods , poultry meat, aquatic products, fruits and vegetables, and tea. It has the potential for the rapid, reliable, and inline assessment of food safety and quality by providing odor-image-basedmonitoring tool. Practical Application: The literatures presented in this review clearly demonstrated that imaging technology based on chemo-responsive dyes has the exciting effect to inspect such as quality assessment of cereal , wine and vinegar flavored foods, poultry meat, aquatic products, fruits and vegetables, and tea.
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Affiliation(s)
- Wencui Kang
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, P. R. China
| | - Hao Lin
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, P. R. China
| | - Hao Jiang
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, P. R. China
| | | | - Zhaoli Xue
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, P. R. China
| | - Quansheng Chen
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, P. R. China
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Martínez Gila DM, Sanmartin C, Navarro Soto J, Mencarelli F, Gómez Ortega J, Gámez García J. Classification of olive fruits and oils based on their fatty acid ethyl esters content using electronic nose technology. JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION 2021. [DOI: 10.1007/s11694-021-01103-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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48
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Sudhakar A, Chakraborty SK, Mahanti NK, Varghese C. Advanced techniques in edible oil authentication: A systematic review and critical analysis. Crit Rev Food Sci Nutr 2021; 63:873-901. [PMID: 34347552 DOI: 10.1080/10408398.2021.1956424] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Adulteration of edible substances is a potent contemporary food safety issue. Perhaps the overt concern derives from the fact that adulterants pose serious ill effects on human health. Edible oils are one of the most adulterated food products. Perpetrators are adopting ways and means that effectively masks the presence of the adulterants from human organoleptic limits and traditional oil adulteration detection techniques. This review embodies a detailed account of chemical, biosensors, chromatography, spectroscopy, differential scanning calorimetry, non-thermal plasma, dielectric spectroscopy research carried out in the area of falsification assessment of edible oils for the past three decades and a collection of patented oil adulteration detection techniques. The detection techniques reviewed have some advantages and certain limitations, chemical tests are simple; biosensors and nuclear magnetic resonance are rapid but have a low sensitivity; chromatography and spectroscopy are highly accurate with a deterring price tag; dielectric spectroscopy is rapid can be portable and has on-line compatibility; however, the results are susceptible to variation of electric current frequency and intrinsic factors (moisture, temperature, structural composition). This review paper can be useful for scientists or for knowledge seekers eager to be abreast with edible oil adulteration detection techniques.
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Affiliation(s)
- Anjali Sudhakar
- Agro Produce Processing Division, ICAR-Central Institute of Agricultural Engineering, Bhopal, India
| | - Subir Kumar Chakraborty
- Agro Produce Processing Division, ICAR-Central Institute of Agricultural Engineering, Bhopal, India
| | - Naveen Kumar Mahanti
- Agro Produce Processing Division, ICAR-Central Institute of Agricultural Engineering, Bhopal, India
| | - Cinu Varghese
- Rural Development Centre, Indian Institute of Technology, Kharagpur, India
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Jurado-Campos N, Rodríguez-Gómez R, Arroyo-Manzanares N, Arce L. Instrumental Techniques to Classify Olive Oils according to Their Quality. Crit Rev Anal Chem 2021; 53:139-160. [PMID: 34260314 DOI: 10.1080/10408347.2021.1940829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
This review includes an update of the publications on quality classification of olive oils into extra, virgin or lampante olive oil categories. Nowadays, the official method to carry out this classification is time-consuming and, sometimes, it is not systematic and/or objective. It is based on conventional physicochemical analysis and on a sensorial tasting of olive oils carried out by a panel of experts. The aim of this review was to explore and give value to the alternative techniques reported in the bibliography to complement the current official methods established for that classification of olive oils. Specifically considered were non-separation and separation analytical techniques which could contribute to correctly classify olive oils according to their physicochemical and/or sensorial characteristics. An in-depth description has been written on the methods used to differentiate these three types of olive oils and the main advantages and disadvantages of the proposed procedures. The techniques here reviewed could be a real and fast option to complement or even substitute some of the analysis included in the official method. Finally, general trends and detected difficulties found to address this issue have been discussed throughout the article.
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Affiliation(s)
- Natividad Jurado-Campos
- Department of Analytical Chemistry, Institute of Fine Chemistry and Nanochemistry, International Agrifood Campus of Excellence (ceiA3), University of Córdoba, Córdoba, Spain
| | - Rocío Rodríguez-Gómez
- Department of Analytical Chemistry, Institute of Fine Chemistry and Nanochemistry, International Agrifood Campus of Excellence (ceiA3), University of Córdoba, Córdoba, Spain
| | - Natalia Arroyo-Manzanares
- Department of Analytical Chemistry, Faculty of Chemistry, Regional Campus of International Excellence "Campus Mare-Nostrum", University of Murcia, Murcia, Spain
| | - Lourdes Arce
- Department of Analytical Chemistry, Institute of Fine Chemistry and Nanochemistry, International Agrifood Campus of Excellence (ceiA3), University of Córdoba, Córdoba, Spain
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50
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Cangialosi F, Bruno E, De Santis G. Application of Machine Learning for Fenceline Monitoring of Odor Classes and Concentrations at a Wastewater Treatment Plant. SENSORS 2021; 21:s21144716. [PMID: 34300455 PMCID: PMC8309642 DOI: 10.3390/s21144716] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 07/06/2021] [Accepted: 07/08/2021] [Indexed: 11/16/2022]
Abstract
The development of low-cost sensors, the introduction of technical performance specifications, and increasingly effective machine learning algorithms for managing big data have led to a growing interest in the use of instrumental odor monitoring systems (IOMS) for odor measurements from industrial plants. The classification and quantification of odor concentration are the main goals of IOMS installed inside industrial plants in order to identify the most important odor sources and to assess whether the regulatory thresholds have been exceeded. This paper illustrates the use of two machine learning algorithms applied to the concurrent classification and quantification of odors. Random Forest was employed, which is a machine learning algorithm that thus far has not been used in the field of odor quantification and classification for complex industrial situations. Furthermore, the results were compared with commonly used algorithms in this field, such as artificial neural network (ANN), which was here employed in the form of a deep neural network. Both techniques were applied to the data collected from an IOMS installed for fenceline monitoring at a wastewater treatment plant. Cohen’s kappa and Normalized RMSE are used as specifical performance indicators for classification and regression: the indicators were calculated for the test dataset, and the results were compared with data in the literature obtained in contexts of similar complexity. A Cohen’s kappa of 97% was reached for the classification task, while the best Normalized RMSE, namely 4%, for the interval 20–2435 ouE/m3 was obtained with Random Forest.
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