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Yang H, Huang X, Yang M, Zhang X, Tang F, Gao B, Gong M, Liang Y, Liu Y, Qian X, Li H. Advanced analytical techniques for authenticity identification and quality evaluation in Essential oils: A review. Food Chem 2024; 451:139340. [PMID: 38678649 DOI: 10.1016/j.foodchem.2024.139340] [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] [Received: 11/28/2023] [Revised: 03/25/2024] [Accepted: 04/09/2024] [Indexed: 05/01/2024]
Abstract
Essential oils (EO), secondary metabolites of plants are fragrant oily liquids with antibacterial, antiviral, anti-inflammatory, anti-allergic, and antioxidant effects. They are widely applied in food, medicine, cosmetics, and other fields. However, the quality of EOs remain uncertain owing to their high volatility and susceptibility to oxidation, influenced by factors such as the harvesting season, extraction, and separation techniques. Additionally, the huge economic value of EOs has led to a market marked by widespread and varied adulteration, making the assessment of their quality challenging. Therefore, developing simple, quick, and effective identification techniques for EOs is essential. This review comprehensively summarizes the techniques for assessing EO quality and identifying adulteration. It covers sensory evaluation, physical and chemical property evaluation, and chemical composition analysis, which are widely used and of great significance for the quality evaluation and adulteration detection of EOs.
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Affiliation(s)
- Huda Yang
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang 330004, China
| | - Xiaoying Huang
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang 330004, China; Jiangxi Guxiangjinyun Great Health Industry Co. Ltd, Nanchang 330096, China.
| | - Ming Yang
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang 330004, China
| | - Xiaofei Zhang
- Jiangxi Guxiangjinyun Great Health Industry Co. Ltd, Nanchang 330096, China; College of Pharmacy, Shaanxi University of Chinese Medicine, Xianyang 712046, China
| | - Fangrui Tang
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang 330004, China; Jiangxi Guxiangjinyun Great Health Industry Co. Ltd, Nanchang 330096, China
| | - Beibei Gao
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang 330004, China
| | - Mengya Gong
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang 330004, China
| | - Yong Liang
- 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
| | - Xingyi Qian
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang 330004, China
| | - Huiting Li
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang 330004, China; Jiangxi Guxiangjinyun Great Health Industry Co. Ltd, Nanchang 330096, China.
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Lujun Z, Nuo C, Xiaodong H, Xinmin F, Juanjuan G, Jin G, Sensen L, Yan W, Chunyan W. Adulteration Detection and Quantification in Olive Oil Using Excitation-Emission Matrix Fluorescence Spectroscopy and Chemometrics. J Fluoresc 2024:10.1007/s10895-024-03613-z. [PMID: 38457079 DOI: 10.1007/s10895-024-03613-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 02/08/2024] [Indexed: 03/09/2024]
Abstract
This research investigates the use of excitation-emission matrix fluorescence (EEMF) in conjunction with chemometric models to rapidly identify and quantify adulteration in olive oil, a critical concern where sample availability is limited. Adulteration is simulated by blending soybean, peanut, and linseed oils into olive oil, creating diverse adulterated samples. Principal component analysis (PCA) was applied to the EEMF spectral data as an initial exploratory measure to cluster and differentiate adulterated samples. Spatial clustering enabled vivid visualization of the variations and trends in the spectra. The novel application of parallel factor analysis (PARAFAC) for data decomposition in this paper focuses on unraveling correlations between the decomposed components and the actual adulterated components, which offers a novel perspective for accurately quantifying adulteration levels. Additionally, a comparative analysis was conducted between the PCA and PARAFAC methodologies. Our study not only unveils a new avenue for the quantitative analysis of adulterants in olive oil through spectral detection but also highlights the potential for applying these insights in practical, real-world scenarios, thereby enhancing detection capabilities for various edible oil samples. This promises to improve the detection of adulteration across a range of edible oil samples, offering significant contributions to food safety and quality assurance.
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Affiliation(s)
- Zhang Lujun
- Department of Physics and Electronic Information, Weifang University, Weifang, 261061, China
| | - Cai Nuo
- Department of Physics and Electronic Information, Weifang University, Weifang, 261061, China
| | - Huang Xiaodong
- Department of Physics and Electronic Information, Weifang University, Weifang, 261061, China
| | - Fan Xinmin
- Department of Physics and Electronic Information, Weifang University, Weifang, 261061, China
| | - Gao Juanjuan
- Department of Physics and Electronic Information, Weifang University, Weifang, 261061, China
| | - Gao Jin
- Department of Physics and Electronic Information, Weifang University, Weifang, 261061, China
| | - Li Sensen
- Science and Technology on Electro-Optical Information Security Control Laboratory, Tianjin, 300308, China
| | - Wang Yan
- Department of Physics and Electronic Information, Weifang University, Weifang, 261061, China.
| | - Wang Chunyan
- Department of Physics and Electronic Information, Weifang University, Weifang, 261061, China.
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Reyrolle M, Bareille G, Epova EN, Barre J, Bérail S, Pigot T, Desauziers V, Gautier L, Le Bechec M. Authenticating teas using multielement signatures, strontium isotope ratios, and volatile compound profiling. Food Chem 2023; 423:136271. [PMID: 37167668 DOI: 10.1016/j.foodchem.2023.136271] [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: 11/06/2022] [Revised: 04/17/2023] [Accepted: 04/27/2023] [Indexed: 05/13/2023]
Abstract
High value food products are subject to adulterations and frauds. This study aimed to combine, in our knowledge for the first time, inorganic chemical tracers (multi-elements and Sr isotopy) with volatile organic compound (VOCs) to discriminate the geographic origin, the varieties and transformation processes to authenticate 26 tea samples. By measuring Sr isotope ratio using the multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS), 6 out of 11 regions were successfully discriminated. The combination with the ICP-MS inorganic pattern allowed to discriminate 4 more regions with a significance level of 0.05. VOCs fingerprints, obtained with selected ion flow tube mass spectrometer (SIFT-MS), were not correlated with origin but with the cultivar and transformation processes. Green, oolong, and dark teas were clearly differentiated, with hexanal and hexanol contributing to the discrimination of oxidation levels. With this multi-instrumental approach, it is possible to certify the geographical origin and the tea conformity.
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Affiliation(s)
- Marine Reyrolle
- Universite de Pau et des Pays de l'Adour, E2S UPPA, CNRS, IMT Mines Ales, IPREM, Pau, France; Institut des sciences analytiques et de Physicochimie pour l'environnement et les Matériaux, UMR5254, Hélioparc, 2 avenue du Président Angot, 64053, Pau cedex 9, France
| | - Gilles Bareille
- Universite de Pau et des Pays de l'Adour, E2S UPPA, CNRS, IMT Mines Ales, IPREM, Pau, France; Institut des sciences analytiques et de Physicochimie pour l'environnement et les Matériaux, UMR5254, Hélioparc, 2 avenue du Président Angot, 64053, Pau cedex 9, France
| | - Ekaterina N Epova
- Advanced Isotopic Analysis (A.I.A.), Hélioparc, 2 avenue du Président Angot, 64000, Pau, France
| | - Julien Barre
- Advanced Isotopic Analysis (A.I.A.), Hélioparc, 2 avenue du Président Angot, 64000, Pau, France
| | - Sylvain Bérail
- Advanced Isotopic Analysis (A.I.A.), Hélioparc, 2 avenue du Président Angot, 64000, Pau, France
| | - Thierry Pigot
- Universite de Pau et des Pays de l'Adour, E2S UPPA, CNRS, IMT Mines Ales, IPREM, Pau, France; Institut des sciences analytiques et de Physicochimie pour l'environnement et les Matériaux, UMR5254, Hélioparc, 2 avenue du Président Angot, 64053, Pau cedex 9, France
| | - Valerie Desauziers
- Universite de Pau et des Pays de l'Adour, E2S UPPA, CNRS, IMT Mines Ales, IPREM, Pau, France; Institut des sciences analytiques et de Physicochimie pour l'environnement et les Matériaux, UMR5254, Hélioparc, 2 avenue du Président Angot, 64053, Pau cedex 9, France
| | - Lydia Gautier
- T Edition, 63 rue Vercingétorix, 75014 Paris, France
| | - Mickael Le Bechec
- Universite de Pau et des Pays de l'Adour, E2S UPPA, CNRS, IMT Mines Ales, IPREM, Pau, France; Institut des sciences analytiques et de Physicochimie pour l'environnement et les Matériaux, UMR5254, Hélioparc, 2 avenue du Président Angot, 64053, Pau cedex 9, France.
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Wang Y, Yu L, Shehzad Q, Kong W, Wu G, Jin Q, Zhang H, Wang X. A comprehensive comparison of Chinese olive oils from different cultivars and geographical origins. Food Chem X 2023; 18:100665. [PMID: 37091515 PMCID: PMC10114164 DOI: 10.1016/j.fochx.2023.100665] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 03/20/2023] [Accepted: 03/26/2023] [Indexed: 03/31/2023] Open
Abstract
China has become increasingly interested in producing olive oil in recent years. In this study, we determined the characteristics of virgin olive oil in five typical cultivars (cv. 'Arbequina,' 'Coratina,' 'Ezhi 8,' 'Frantoio,' and 'Koroneiki') from two of the most suitable production areas for olive cultivation in China. In addition, linear discriminant analysis (LDA) was used to differentiate oils originating from various cultivars and geographical origins. Heatmap was also constructed to describe the differences straightly. Compared to Xichang oils, Longnan oils generally contained higher levels of C18:0, lignans, total esters and total furans, and lower levels of phenolic acids and phenolic alcohols. A variety of cultivars differed in total sterols, hydroxytyrosol derivatives, and volatile compounds. Coratina oils showed excellent properties in two regions. Our findings are closely related to select the optimum olive cultivars in different regions to promote the development of Chinese olive industry scientifically.
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Smith D, Španěl P, Demarais N, Langford VS, McEwan MJ. Recent developments and applications of selected ion flow tube mass spectrometry (SIFT-MS). MASS SPECTROMETRY REVIEWS 2023:e21835. [PMID: 36776107 DOI: 10.1002/mas.21835] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 10/09/2022] [Accepted: 12/12/2022] [Indexed: 06/18/2023]
Abstract
Selected ion flow tube mass spectrometry (SIFT-MS) is now recognized as the most versatile analytical technique for the identification and quantification of trace gases down to the parts-per-trillion by volume, pptv, range. This statement is supported by the wide reach of its applications, from real-time analysis, obviating sample collection of very humid exhaled breath, to its adoption in industrial scenarios for air quality monitoring. This review touches on the recent extensions to the underpinning ion chemistry kinetics library and the alternative challenge of using nitrogen carrier gas instead of helium. The addition of reagent anions in the Voice200 series of SIFT-MS instruments has enhanced the analytical capability, thus allowing analyses of volatile trace compounds in humid air that cannot be analyzed using reagent cations alone, as clarified by outlining the anion chemistry involved. Case studies are reviewed of breath analysis and bacterial culture volatile organic compound (VOC), emissions, environmental applications such as air, water, and soil analysis, workplace safety such as transport container fumigants, airborne contamination in semiconductor fabrication, food flavor and spoilage, drugs contamination and VOC emissions from packaging to demonstrate the stated qualities and uniqueness of the new generation SIFT-MS instrumentation. Finally, some advancements that can be made to improve the analytical capability and reach of SIFT-MS are mentioned.
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Affiliation(s)
- David Smith
- J. Heyrovský Institute of Physical Chemistry, Czech Academy of Sciences, Prague, Czechia
| | - Patrik Španěl
- J. Heyrovský Institute of Physical Chemistry, Czech Academy of Sciences, Prague, Czechia
| | | | | | - Murray J McEwan
- Syft Technologies Limited, Christchurch, New Zealand
- Department of Chemistry, University of Canterbury, Christchurch, New Zealand
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Tarapoulouzi M, Agriopoulou S, Koidis A, Proestos C, Enshasy HAE, Varzakas T. Recent Advances in Analytical Methods for the Detection of Olive Oil Oxidation Status during Storage along with Chemometrics, Authenticity and Fraud Studies. Biomolecules 2022; 12:biom12091180. [PMID: 36139019 PMCID: PMC9496477 DOI: 10.3390/biom12091180] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 08/16/2022] [Accepted: 08/23/2022] [Indexed: 11/16/2022] Open
Abstract
Olive oil is considered to be a food of utmost importance, especially in the Mediterranean countries. The quality of olive oil must remain stable regarding authenticity and storage. This review paper emphasizes the detection of olive oil oxidation status or rancidity, the analytical techniques that are usually used, as well as the application and significance of chemometrics in the research of olive oil. The first part presents the effect of the oxidation of olive oil during storage. Then, lipid stability measurements are described in parallel with instrumentation and different analytical techniques that are used for this particular purpose. The next part presents some research publications that combine chemometrics and the study of lipid changes due to storage published in 2005–2021. Parameters such as exposure to light, air and various temperatures as well as different packaging materials were investigated to test olive oil stability during storage. The benefits of each chemometric method are provided as well as the overall significance of combining analytical techniques and chemometrics. Furthermore, the last part reflects on fraud in olive oil, and the most popular analytical techniques in the authenticity field are stated to highlight the importance of the authenticity of olive oil.
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Affiliation(s)
- Maria Tarapoulouzi
- Department of Chemistry, Faculty of Pure and Applied Science, University of Cyprus, P.O. Box 20537, Nicosia CY-1678, Cyprus
| | - Sofia Agriopoulou
- Department of Food Science and Technology, University of the Peloponnese, Antikalamos, 24100 Kalamata, Greece
- Correspondence: (S.A.); (T.V.)
| | - Anastasios Koidis
- Institute for Global Food Security, School of Biological Science, Queen’s University Belfast, Belfast BT9 5DL, Northern Ireland, UK
| | - Charalampos Proestos
- Food Chemistry Laboratory, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece
| | - Hesham Ali El Enshasy
- Institute of Bioproduct Development (IBD), Universiti Teknologi Malaysia (UTM), Johor 81310, Malaysia
- School of Chemical and Energy Engineering, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), Johor 81310, Malaysia
- City of Scientific Research and Technology Applications (SRTA), New Borg Al Arab 21934, Egypt
| | - Theodoros Varzakas
- Department of Food Science and Technology, University of the Peloponnese, Antikalamos, 24100 Kalamata, Greece
- Institute of Bioproduct Development (IBD), Universiti Teknologi Malaysia (UTM), Johor 81310, Malaysia
- Correspondence: (S.A.); (T.V.)
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7
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Violino S, Taiti C, Marone E, Pallottino F, Costa C. A statistical tool to determine the quality of extra virgin olive oil (EVOO). Eur Food Res Technol 2022. [DOI: 10.1007/s00217-022-04092-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Kharbach M, Yu H, Kamal R, Marmouzi I, Alaoui K, Vercammen J, Bouklouze A, Vander Heyden Y. Authentication of extra virgin Argan oil by selected-ion flow-tube mass-spectrometry fingerprinting and chemometrics. Food Chem 2022; 383:132565. [PMID: 35245834 DOI: 10.1016/j.foodchem.2022.132565] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 02/22/2022] [Accepted: 02/23/2022] [Indexed: 11/04/2022]
Abstract
Recognized for its nutritional and therapeutic use, extra-virgin Argan Oil (EVAO) is frequently adulterated. Selected-Ion Flow-Tube Mass Spectrometry (SIFT-MS) spectra were applied to quantify adulterants (i.e., Argan oil of lower quality (LQAO), olive oil (OO), and sunflower oil (SO)) in EVAO. Four data sets, i.e., using H3O+, NO+, O2+ reagent ions, and the combined data were considered. Soft independent modelling of class analogy (SIMCA), and partial least squares discriminant analysis (PLS-DA) were assessed to distinguish adulterated- from pure EVAO. The effectiveness of SIFT-MS associated with PLS and support vector machine (SVM) regression to quantify trace adulterants in EVAO was evaluated. Variable Importance in Projection (VIP), and interval-PLS (iPLS) were also investigated to extract useful features. Different models were built to predict the EVAO authenticity and the degree of adulteration. High accuracy was achieved. SIFT-MS spectra handled with the appropriate chemometric tools were found suitable for the quality evaluation of EVAO.
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Affiliation(s)
- Mourad Kharbach
- Research Unit of Mathematical Sciences, University of Oulu, FI-90014 Oulu, Finland; Department of Food and Nutrition, P.O. Box 66, FI-00014, University of Helsinki, Finland; Department of Analytical Chemistry, Applied Chemometrics and Molecular Modelling, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, B-1090 Brussels, Belgium.
| | - Huiwen Yu
- Chemometrics and Analytical Technology, Faculty of Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg, Denmark
| | - Rabie Kamal
- Pharmacodynamics Research Team, Laboratory of Pharmacology and Toxicology, Faculty of Medicine and Pharmacy, University Mohammed V in Rabat, Morocco
| | - Ilias Marmouzi
- Biopharmaceutical and Toxicological Analysis Research Team, Laboratory of Pharmacology and Toxicology, Faculty of Medicine and Pharmacy, University Mohammed V in Rabat, Morocco
| | - Katim Alaoui
- Pharmacodynamics Research Team, Laboratory of Pharmacology and Toxicology, Faculty of Medicine and Pharmacy, University Mohammed V in Rabat, Morocco
| | - Joeri Vercammen
- Interscience Expert Center (IS-X), Avenue Jean-Etienne Lenoir 2, 1348 Louvain-la-Neuve, Belgium; Industrial Catalysis and Adsorption Technology (INCAT), Faculty of Engineering and Architecture, Ghent University, Valentin Vaerwyckweg 1, 9000, Ghent, Belgium
| | - Abdelaziz Bouklouze
- Biopharmaceutical and Toxicological Analysis Research Team, Laboratory of Pharmacology and Toxicology, Faculty of Medicine and Pharmacy, University Mohammed V in Rabat, Morocco
| | - Yvan Vander Heyden
- Department of Analytical Chemistry, Applied Chemometrics and Molecular Modelling, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, B-1090 Brussels, Belgium.
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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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10
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Baerenzung dit Baron T, Yobrégat O, Jacques A, Simon V, Geffroy O. A novel approach to discriminate the volatilome of Vitis vinifera berries by Selected Ion Flow Tube Mass Spectrometry analysis and chemometrics. Food Res Int 2022; 157:111434. [DOI: 10.1016/j.foodres.2022.111434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 05/20/2022] [Accepted: 05/25/2022] [Indexed: 11/27/2022]
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11
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Lozano‐Castellón J, López‐Yerena A, Domínguez‐López I, Siscart‐Serra A, Fraga N, Sámano S, López‐Sabater C, Lamuela‐Raventós RM, Vallverdú‐Queralt A, Pérez M. Extra virgin olive oil: A comprehensive review of efforts to ensure its authenticity, traceability, and safety. Compr Rev Food Sci Food Saf 2022; 21:2639-2664. [DOI: 10.1111/1541-4337.12949] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 02/28/2022] [Accepted: 03/04/2022] [Indexed: 01/19/2023]
Affiliation(s)
- Julián Lozano‐Castellón
- Department of Nutrition, Food Science and Gastronomy, XIA, Faculty of Pharmacy and Food Sciences Institute of Nutrition and Food Safety (INSA‐UB) University of Barcelona Barcelona Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn) Instituto de Salud Carlos III (ISCIII) Madrid Spain
| | - Anallely López‐Yerena
- Department of Nutrition, Food Science and Gastronomy, XIA, Faculty of Pharmacy and Food Sciences Institute of Nutrition and Food Safety (INSA‐UB) University of Barcelona Barcelona Spain
| | - Inés Domínguez‐López
- Department of Nutrition, Food Science and Gastronomy, XIA, Faculty of Pharmacy and Food Sciences Institute of Nutrition and Food Safety (INSA‐UB) University of Barcelona Barcelona Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn) Instituto de Salud Carlos III (ISCIII) Madrid Spain
| | - Aina Siscart‐Serra
- Department of Nutrition, Food Science and Gastronomy, XIA, Faculty of Pharmacy and Food Sciences Institute of Nutrition and Food Safety (INSA‐UB) University of Barcelona Barcelona Spain
| | - Nathalia Fraga
- Department of Nutrition, Food Science and Gastronomy, XIA, Faculty of Pharmacy and Food Sciences Institute of Nutrition and Food Safety (INSA‐UB) University of Barcelona Barcelona Spain
| | - Samantha Sámano
- Department of Nutrition, Food Science and Gastronomy, XIA, Faculty of Pharmacy and Food Sciences Institute of Nutrition and Food Safety (INSA‐UB) University of Barcelona Barcelona Spain
| | - Carmen López‐Sabater
- Department of Nutrition, Food Science and Gastronomy, XIA, Faculty of Pharmacy and Food Sciences Institute of Nutrition and Food Safety (INSA‐UB) University of Barcelona Barcelona Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn) Instituto de Salud Carlos III (ISCIII) Madrid Spain
| | - Rosa M Lamuela‐Raventós
- Department of Nutrition, Food Science and Gastronomy, XIA, Faculty of Pharmacy and Food Sciences Institute of Nutrition and Food Safety (INSA‐UB) University of Barcelona Barcelona Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn) Instituto de Salud Carlos III (ISCIII) Madrid Spain
| | - Anna Vallverdú‐Queralt
- Department of Nutrition, Food Science and Gastronomy, XIA, Faculty of Pharmacy and Food Sciences Institute of Nutrition and Food Safety (INSA‐UB) University of Barcelona Barcelona Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn) Instituto de Salud Carlos III (ISCIII) Madrid Spain
| | - Maria Pérez
- Department of Nutrition, Food Science and Gastronomy, XIA, Faculty of Pharmacy and Food Sciences Institute of Nutrition and Food Safety (INSA‐UB) University of Barcelona Barcelona Spain
- Laboratory of Organic Chemistry, Faculty of Pharmacy and Food Sciences University of Barcelona Barcelona Spain
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Quantitative Detection of Extra Virgin Olive Oil Adulteration, as Opposed to Peanut and Soybean Oil, Employing LED-Induced Fluorescence Spectroscopy. SENSORS 2022; 22:s22031227. [PMID: 35161972 PMCID: PMC8840102 DOI: 10.3390/s22031227] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 02/02/2022] [Accepted: 02/04/2022] [Indexed: 01/27/2023]
Abstract
As it is high in value, extra virgin olive oil (EVOO) is frequently blended with inferior vegetable oils. This study presents an optical method for determining the adulteration level of EVOO with soybean oil as well as peanut oil using LED-induced fluorescence spectroscopy. Eight LEDs with central wavelengths from ultra-violet (UV) to blue are tested to induce the fluorescence spectra of EVOO, peanut oil, and soybean oil, and the UV LED of 372 nm is selected for further detection. Samples are prepared by mixing olive oil with different volume fractions of peanut or soybean oil, and their fluorescence spectra are collected. Different pre-processing and regression methods are utilized to build the prediction model, and good linearity is obtained between the predicted and actual adulteration concentration. This result, accompanied by the non-destruction and no pre-treatment characteristics, proves that it is feasible to use LED-induced fluorescence spectroscopy as a way to investigate the EVOO adulteration level, and paves the way for building a hand-hold device that can be applied to real market conditions in the future.
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Valli E, Milani A, Srbinovska A, Moret E, Moret S, Bendini A, Moreda W, Toschi TG, Lucci P. In-House Validation of an SPE-GC-FID Method for the Detection of Free and Esterified Hydroxylated Minor Compounds in Virgin Olive Oils. Foods 2021; 10:foods10061260. [PMID: 34199349 PMCID: PMC8230319 DOI: 10.3390/foods10061260] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2021] [Revised: 05/27/2021] [Accepted: 05/29/2021] [Indexed: 12/31/2022] Open
Abstract
Minor compounds in vegetable oils are distributed between free and esterified forms, and the ratio of these two fractions could represent an important parameter for assessment of oil authenticity. A simple method based on offline SPE-GC-FID for the analysis of free and esterified hydroxylated minor compounds in olive and sunflower oils has been developed and in-house validated. A satisfactory repeatability relative standard deviation (<7.5%) was obtained in all cases. The method, which requires simple instrumentation, allows for reliable quantification in a single chromatographic run with the advantages of minimizing sample manipulation, use of toxic solvents and reagents, and time consumption. The analytical procedure was applied to pure oil samples, including 15 authentic extra virgin olive oils collected from different European countries (Spain, Italy, Greece, and Portugal). Finally, the proposed SPE-GC-FID methodology could detect changes in the ratio between the free and esterified forms in pure extra virgin olive oil when mixed with refined sunflower oil at different percentages of 2, 5, 10, 15, and 20% (w/w) to simulate adulteration.
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Affiliation(s)
- Enrico Valli
- Department of Agricultural and Food Sciences, Alma Mater Studiorum—Università di Bologna, 40127 Bologna, Italy; (E.V.); (A.B.); (T.G.T.)
| | - Andrea Milani
- Department of Agri-Food, Animal and Environmental Sciences, University of Udine, via Sondrio 2/a, 33100 Udine, Italy; (A.M.); (A.S.); (E.M.); (S.M.)
| | - Ana Srbinovska
- Department of Agri-Food, Animal and Environmental Sciences, University of Udine, via Sondrio 2/a, 33100 Udine, Italy; (A.M.); (A.S.); (E.M.); (S.M.)
| | - Erica Moret
- Department of Agri-Food, Animal and Environmental Sciences, University of Udine, via Sondrio 2/a, 33100 Udine, Italy; (A.M.); (A.S.); (E.M.); (S.M.)
| | - Sabrina Moret
- Department of Agri-Food, Animal and Environmental Sciences, University of Udine, via Sondrio 2/a, 33100 Udine, Italy; (A.M.); (A.S.); (E.M.); (S.M.)
| | - Alessandra Bendini
- Department of Agricultural and Food Sciences, Alma Mater Studiorum—Università di Bologna, 40127 Bologna, Italy; (E.V.); (A.B.); (T.G.T.)
| | - Wenceslao Moreda
- Department of Characterization and Quality of Lipids, Instituto de la Grasa-CSIC, Campus of Universidad Pablo de Olavide, E-41013 Sevilla, Spain;
| | - Tullia Gallina Toschi
- Department of Agricultural and Food Sciences, Alma Mater Studiorum—Università di Bologna, 40127 Bologna, Italy; (E.V.); (A.B.); (T.G.T.)
| | - Paolo Lucci
- Department of Agri-Food, Animal and Environmental Sciences, University of Udine, via Sondrio 2/a, 33100 Udine, Italy; (A.M.); (A.S.); (E.M.); (S.M.)
- Correspondence: or ; Tel.: +39-0432-55817
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Laser-induced breakdown spectroscopy coupled with machine learning as a tool for olive oil authenticity and geographic discrimination. Sci Rep 2021; 11:5360. [PMID: 33686131 PMCID: PMC7970888 DOI: 10.1038/s41598-021-84941-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 02/18/2021] [Indexed: 02/06/2023] Open
Abstract
Olive oil is a basic element of the Mediterranean diet and a key product for the economies of the Mediterranean countries. Thus, there is an added incentive in the olive oil business for fraud through practices like adulteration and mislabeling. In the present work, Laser Induced Breakdown Spectroscopy (LIBS) assisted by machine learning is used for the classification of 139 virgin olive oils in terms of their geographical origin. The LIBS spectra of these olive oil samples were used to train different machine learning algorithms, namely LDA, ERTC, RFC, XGBoost, and to assess their classification performance. In addition, the variable importance of the spectral features was calculated, for the identification of the most important ones for the classification performance and to reduce their number for the algorithmic training. The algorithmic training was evaluated and tested by means of classification reports, confusion matrices and by external validation procedure as well. The present results demonstrate that machine learning aided LIBS can be a powerful and efficient tool for the rapid authentication of the geographic origin of virgin olive oil.
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Cecchi L, Migliorini M, Mulinacci N. Virgin Olive Oil Volatile Compounds: Composition, Sensory Characteristics, Analytical Approaches, Quality Control, and Authentication. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2021; 69:2013-2040. [PMID: 33591203 DOI: 10.1021/acs.jafc.0c07744] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Volatile organic compounds strongly contribute to both the positive and negative sensory attributes of virgin olive oil, and more and more studies have been published in recent years focusing on several aspects regarding these molecules. This Review is aimed at giving an overview on the state of the art about the virgin olive oil volatile compounds. Particular emphasis was given to the composition of the volatile fraction, the analytical issues and approaches for analysis, the sensory characteristics and interaction with phenolic compounds, and the approaches for supporting the Panel Test in virgin olive oil classification and in authentication of the botanical and geographic origin based on volatile compounds. A pair of detailed tables with a total of approximately 700 volatiles identified or tentatively identified to date and tables dealing with analytical procedures, sensory characteristics of volatiles, and specific chemometric approaches for quality assessment are also provided.
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Affiliation(s)
- Lorenzo Cecchi
- Department of NEUROFARBA, Pharmaceutical and Nutraceutical Section, University of Florence, Via Ugo Schiff 6, 50019 Sesto F.no, Florence, Italy
| | - Marzia Migliorini
- Carapelli Firenze S.p.A., Via Leonardo da Vinci 31, 50028 Tavarnelle Val di Pesa, Florence, Italy
| | - Nadia Mulinacci
- Department of NEUROFARBA, Pharmaceutical and Nutraceutical Section, University of Florence, Via Ugo Schiff 6, 50019 Sesto F.no, Florence, Italy
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State-of-the-Art of Analytical Techniques to Determine Food Fraud in Olive Oils. Foods 2021; 10:foods10030484. [PMID: 33668346 PMCID: PMC7996354 DOI: 10.3390/foods10030484] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 02/13/2021] [Accepted: 02/18/2021] [Indexed: 12/26/2022] Open
Abstract
The benefits of the food industry compared to other sectors are much lower, which is why producers are tempted to commit fraud. Although it is a bad practice committed with a wide variety of foods, it is worth noting the case of olive oil because it is a product of great value and with a high percentage of fraud. It is for all these reasons that the authenticity of olive oil has become a major problem for producers, consumers, and legislators. To avoid such fraud, it is necessary to develop analytical techniques to detect them. In this review, we performed a complete analysis about the available instrumentation used in olive fraud which comprised spectroscopic and spectrometric methodology and analyte separation techniques such as liquid chromatography and gas chromatography. Additionally, other methodology including protein-based biomolecular techniques and analytical approaches like metabolomic, hhyperspectral imaging and chemometrics are discussed.
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Li L, Jin S, Wang Y, Liu Y, Shen S, Li M, Ma Z, Ning J, Zhang Z. Potential of smartphone-coupled micro NIR spectroscopy for quality control of green tea. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 247:119096. [PMID: 33166782 DOI: 10.1016/j.saa.2020.119096] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 10/14/2020] [Accepted: 10/15/2020] [Indexed: 06/11/2023]
Abstract
Green tea adulterated with sugar and glutinous rice flour has an increased sensitivity to water, which affects the safety of the tea. A total of 475 samples of pure tea, sugar-adulterated tea, and glutinous-rice-flour-adulterated tea were prepared and scanned using micro near infrared spectroscopy (NIRS). The collected NIRS data were qualitatively and quantitatively detected by a multi-layer algorithm model. Principal component analysis indicated that the three sample groups had an obvious separation trend. The discriminate rate of the optimal qualitative model, namely support vector machine, was 97.47% for the prediction set. A total of three wavelength selection methods were used to improve the performances of partial least squares regression and support vector machine regression (SVR) models. The nonlinear SVR models based on characteristic wavelengths selected by iteratively retaining informative variables algorithm provided satisfactory results for the identification of sugar and glutinous rice flour adulteration. The correlation coefficients for prediction (Rp) were >0.94, and the residual prediction deviation were >3. The results indicated that smartphone-based micro NIRS can be effectively used to qualitatively and quantitatively analyze adulterants in green tea.
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Affiliation(s)
- Luqing Li
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei 230036, China
| | - Shanshan Jin
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei 230036, China
| | - Yujie Wang
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei 230036, China
| | - Ying Liu
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei 230036, China
| | - Shanshan Shen
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei 230036, China
| | - Menghui Li
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei 230036, China
| | - Zhiyu Ma
- School of Information & Computer, Anhui Agricultural University, Hefei 230036, China
| | - Jingming Ning
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei 230036, China.
| | - Zhengzhu Zhang
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei 230036, China.
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