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Ahmad NA. Numerically stable locality-preserving partial least squares discriminant analysis for efficient dimensionality reduction and classification of high-dimensional data. Heliyon 2024; 10:e26157. [PMID: 38404905 PMCID: PMC10884865 DOI: 10.1016/j.heliyon.2024.e26157] [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: 01/16/2023] [Revised: 01/29/2024] [Accepted: 02/08/2024] [Indexed: 02/27/2024] Open
Abstract
Dimensionality reduction plays a pivotal role in preparing high-dimensional data for classification and discrimination tasks by eliminating redundant features and enhancing the efficiency of classifiers. The effectiveness of a dimensionality reduction algorithm hinges on its numerical stability. When data projections are numerically stable, they lead to enhanced class separability in the lower-dimensional embedding, consequently yielding higher classification accuracy. This paper investigates the numerical attributes of dimensionality reduction and discriminant subspace learning, with a specific focus on Locality-Preserving Partial Least Squares Discriminant Analysis (LPPLS-DA). High-dimensional data frequently introduce singularity in the scatter matrices, posing a significant challenge. To tackle this issue, the paper explores two robust implementations of LPPLS-DA. These approaches not only optimize data projections but also capture more discriminative features, resulting in a marked improvement in classification accuracy. Empirical evidence supports these findings through numerical experiments conducted on synthetic and spectral datasets. The results demonstrate the superior performance of the proposed methods when compared to several state-of-the-art dimensionality reduction techniques in terms of both classification accuracy and dimension reduction.
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Affiliation(s)
- Noor Atinah Ahmad
- School of Mathematical Sciences, Universiti Sains Malaysia, 11800, Penang, Malaysia
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2
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Christopoulou NM, Mamoulaki V, Mitsiakou A, Samolada E, Kalogianni DP, Christopoulos TK. Screening Method for the Visual Discrimination of Olive Oil from Other Vegetable Oils by a Multispecies DNA Sensor. Anal Chem 2024; 96:1803-1811. [PMID: 38243913 DOI: 10.1021/acs.analchem.3c05507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2024]
Abstract
Olive oil is a prominent agricultural product which, in addition to its nutritional value and unique organoleptic characteristics, offers a variety of health benefits protecting against cardiovascular disease, cancer, and neurodegenerative diseases. The assessment of olive oil authenticity is an extremely important and challenging process aimed at protecting consumers and producers. The most frequent adulteration involves blending with less expensive and readily available vegetable/seed oils. The methods for adulteration detection, whether based on changes in metabolite profiles or based on DNA markers, require advanced and expensive instrumentation combined with powerful chemometric and statistical tools. To this end, we present a simple, multiplex, and inexpensive screening method based on the development of a multispecies DNA sensor for sample interrogation with the naked eye. It is the first report of a DNA sensor for olive oil adulteration detection with other plant oils. The sensor meets the 2-fold challenge of adulteration detection, i.e., determining whether the olive oil sample is adulterated and identifying the added vegetable oil. We have identified unique, nucleotide variations, which enable the discrimination of seven plant species (olive, corn, sesame, soy, sunflower, almond, and hazelnut). Following a single PCR step, a 20 min multiplex plant-discrimination reaction is performed, and the products are applied directly to the sensing device. The plant species are visualized as red spots using functionalized gold nanoparticles as reporters. The spot position reveals the identity of the plant species. As low as <5-10% of adulterant was detected with particularly good reproducibility and specificity.
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Affiliation(s)
- Natalia-Maria Christopoulou
- Analytical/Bioanalytical Chemistry & Nanotechnology Group, Department of Chemistry, University of Patras, Rio, Patras 26504, Greece
| | - Vasiliki Mamoulaki
- Analytical/Bioanalytical Chemistry & Nanotechnology Group, Department of Chemistry, University of Patras, Rio, Patras 26504, Greece
| | - Aglaia Mitsiakou
- Analytical/Bioanalytical Chemistry & Nanotechnology Group, Department of Chemistry, University of Patras, Rio, Patras 26504, Greece
| | - Eleni Samolada
- Analytical/Bioanalytical Chemistry & Nanotechnology Group, Department of Chemistry, University of Patras, Rio, Patras 26504, Greece
| | - Despina P Kalogianni
- Analytical/Bioanalytical Chemistry & Nanotechnology Group, Department of Chemistry, University of Patras, Rio, Patras 26504, Greece
| | - Theodore K Christopoulos
- Analytical/Bioanalytical Chemistry & Nanotechnology Group, Department of Chemistry, University of Patras, Rio, Patras 26504, Greece
- Institute of Chemical Engineering Sciences, Foundation for Research and Technology Hellas (FORTH/ICE-HT), Patras 26504, Greece
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3
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The detection of goat milk adulteration with cow milk using a combination of voltammetric fingerprints and chemometrics analysis. CHEMICAL PAPERS 2023. [DOI: 10.1007/s11696-023-02780-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/21/2023]
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4
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Mechanisms and Health Aspects of Food Adulteration: A Comprehensive Review. Foods 2023; 12:foods12010199. [PMID: 36613416 PMCID: PMC9818512 DOI: 10.3390/foods12010199] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 12/26/2022] [Accepted: 12/28/2022] [Indexed: 01/04/2023] Open
Abstract
Food adulteration refers to the alteration of food quality that takes place deliberately. It includes the addition of ingredients to modify different properties of food products for economic advantage. Color, appearance, taste, weight, volume, and shelf life are such food properties. Substitution of food or its nutritional content is also accomplished to spark the apparent quality. Substitution with species, protein content, fat content, or plant ingredients are major forms of food substitution. Origin misrepresentation of food is often practiced to increase the market demand of food. Organic and synthetic compounds are added to ensure a rapid effect on the human body. Adulterated food products are responsible for mild to severe health impacts as well as financial damage. Diarrhea, nausea, allergic reaction, diabetes, cardiovascular disease, etc., are frequently observed illnesses upon consumption of adulterated food. Some adulterants have shown carcinogenic, clastogenic, and genotoxic properties. This review article discusses different forms of food adulteration. The health impacts also have been documented in brief.
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5
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Bian X, Wang Y, Wang S, Johnson JB, Sun H, Guo Y, Tan X. A Review of Advanced Methods for the Quantitative Analysis of Single Component Oil in Edible Oil Blends. Foods 2022; 11:foods11162436. [PMID: 36010436 PMCID: PMC9407567 DOI: 10.3390/foods11162436] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 08/04/2022] [Accepted: 08/11/2022] [Indexed: 12/21/2022] Open
Abstract
Edible oil blends are composed of two or more edible oils in varying proportions, which can ensure nutritional balance compared to oils comprising a single component oil. In view of their economical and nutritional benefits, quantitative analysis of the component oils in edible oil blends is necessary to ensure the rights and interests of consumers and maintain fairness in the edible oil market. Chemometrics combined with modern analytical instruments has become a main analytical technology for the quantitative analysis of edible oil blends. This review summarizes the different oil blend design methods, instrumental techniques and chemometric methods for conducting single component oil quantification in edible oil blends. The aim is to classify and compare the existing analytical techniques to highlight suitable and promising determination methods in this field.
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Affiliation(s)
- Xihui Bian
- School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China
- Shandong Provincial Key Laboratory of Olefin Catalysis and Polymerization, Shandong Chambroad Holding Group Co., Ltd., Binzhou 256500, China
- Correspondence: ; Tel./Fax: +86-22-83955663
| | - Yao Wang
- School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China
| | - Shuaishuai Wang
- Shandong Provincial Key Laboratory of Olefin Catalysis and Polymerization, Shandong Chambroad Holding Group Co., Ltd., Binzhou 256500, China
| | - Joel B. Johnson
- School of Health, Medical & Applied Sciences, Central Queensland University, Bruce Hwy, North Rockhampton, QLD 4701, Australia
| | - Hao Sun
- School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China
| | - Yugao Guo
- School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China
| | - Xiaoyao Tan
- School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China
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6
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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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7
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Electronic nose for detection of food adulteration: a review. JOURNAL OF FOOD SCIENCE AND TECHNOLOGY 2022; 59:846-858. [PMID: 35185196 PMCID: PMC8814237 DOI: 10.1007/s13197-021-05057-w] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Revised: 02/24/2021] [Accepted: 02/26/2021] [Indexed: 10/21/2022]
Abstract
The food products may attract unscrupulous vendors to dilute it with inexpensive alternative food sources to achieve more profit. The risk of high value food adulteration with cheaper substitutes has reached an alarming stage in recent years. Commonly available detection methods for food adulteration are costly, time consuming and requires high degree of technical expertise. However, a rapid and suitable detection method for possible adulterant is being evolved to tackle the aforesaid issues. In recent years, electronic nose (e-nose) system is being evolved for falsification detection of food products with reliable and rapid way. E-nose has the ability to artificially perceive aroma and distinguish them. The use of chemometric analysis together with gas sensor arrays have shown to be a significant procedure for quality monitoring in food. E-nose techniques with numerous provisions are reliable and favourable for food industry in food fraud detection. In the present review, the contributions of gas sensor based e-nose system are discussed extensively with a view to ascertain the adulteration of food products.
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8
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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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9
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Rifna EJ, Pandiselvam R, Kothakota A, Subba Rao KV, Dwivedi M, Kumar M, Thirumdas R, Ramesh SV. Advanced process analytical tools for identification of adulterants in edible oils - A review. Food Chem 2022; 369:130898. [PMID: 34455326 DOI: 10.1016/j.foodchem.2021.130898] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 07/16/2021] [Accepted: 08/16/2021] [Indexed: 12/16/2022]
Abstract
This review summarizes the use of spectroscopic processes-based analytical tools coupled with chemometric techniques for the identification of adulterants in edible oil. Investigational approaches of process analytical tools such asspectroscopy techniques, nuclear magnetic resonance (NMR), hyperspectral imaging (HSI), e-tongue and e-nose combined with chemometrics were used to monitor quality of edible oils. Owing to the variety and intricacy of edible oil properties along with the alterations in attributes of the PAT tools, the reliability of the tool used and the operating factors are the crucial components which require attention to enhance the efficiency in identification of adulterants. The combination of process analytical tools with chemometrics offers a robust technique with immense chemotaxonomic potential. These involves identification of adulterants, quality control, geographical origin evaluation, process evaluation, and product categorization.
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Affiliation(s)
- E J Rifna
- Department of Food Process Engineering, National Institute of Technology, Rourkela 769008, Odisha, India
| | - R Pandiselvam
- Physiology, Biochemistry and Post-Harvest Technology Division, ICAR - Central Plantation Crops Research Institute, Kasaragod 671 124, Kerala, India.
| | - Anjineyulu Kothakota
- Agro-Processing & Technology Division, CSIR-National Institute for Interdisciplinary Science and Technology (NIIST), Trivandrum 695 019, Kerala, India.
| | - K V Subba Rao
- Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur, West Bengal 721302, India
| | - Madhuresh Dwivedi
- Department of Food Process Engineering, National Institute of Technology, Rourkela 769008, Odisha, India
| | - Manoj Kumar
- Chemical and Biochemical Processing Division, ICAR-Central Institute for Research on Cotton Technology, Matunga, Mumbai 400019, India
| | - Rohit Thirumdas
- Department of Food Process Technology, College of Food Science and Technology, PJTSAU, Telangana, India
| | - S V Ramesh
- Physiology, Biochemistry and Post-Harvest Technology Division, ICAR - Central Plantation Crops Research Institute, Kasaragod 671 124, Kerala, India
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10
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Ramirez-Montes S, Santos EM, Galan-Vidal CA, Tavizon-Pozos JA, Rodriguez JA. Classification of Edible Vegetable Oil Degradation Using Multivariate Data Analysis From Electrochemical Techniques. FOOD ANAL METHOD 2021. [DOI: 10.1007/s12161-021-02083-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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11
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Moe Htet TT, Cruz J, Khongkaew P, Suwanvecho C, Suntornsuk L, Nuchtavorn N, Limwikrant W, Phechkrajang C. PLS-regression-model-assisted raman spectroscopy for vegetable oil classification and non-destructive analysis of alpha-tocopherol contents of vegetable oils. J Food Compost Anal 2021. [DOI: 10.1016/j.jfca.2021.104119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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12
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Yang TL, Huang CL, Lee CP. Utilizing AgNPt-SALDI to Classify Edible Oils by Multivariate Statistics of Triacylglycerol Profile. Molecules 2021; 26:molecules26195880. [PMID: 34641425 PMCID: PMC8510378 DOI: 10.3390/molecules26195880] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 09/24/2021] [Accepted: 09/25/2021] [Indexed: 11/16/2022] Open
Abstract
Edible oils are valuable sources of nutrients, and their classification is necessary to ensure high quality, which is essential to food safety. This study reports the establishment of a rapid and straightforward SALDI-TOF MS platform used to detect triacylglycerol (TAG) in various edible oils. Silver nanoplates (AgNPts) were used to optimize the SALDI samples for high sensitivity and reproducibility of TAG signals. TAG fingerprints were combined with multivariate statistics to identify the critical features of edible oil discrimination. Eleven various edible oils were discriminated using principal component analysis (PCA). The results suggested the creation of a robust platform that can examine food adulteration and food fraud, potentially ensuring high-quality foods and agricultural products.
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Affiliation(s)
- Tzu-Ling Yang
- Department of Applied Chemistry, National Chiayi University, Chiayi City 60004, Taiwan; (T.-L.Y.); (C.-L.H.)
| | - Cheng-Liang Huang
- Department of Applied Chemistry, National Chiayi University, Chiayi City 60004, Taiwan; (T.-L.Y.); (C.-L.H.)
| | - Chu-Ping Lee
- Department of Chemistry, Fu Jen Catholic University, New Taipei City 24205, Taiwan
- Correspondence:
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13
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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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Unlocking the full potential of voltammetric data analysis: A novel peak recognition approach for (bio)analytical applications. Talanta 2021; 233:122605. [PMID: 34215092 DOI: 10.1016/j.talanta.2021.122605] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 06/07/2021] [Accepted: 06/08/2021] [Indexed: 11/23/2022]
Abstract
Bridging the gap between complex signal data output and clear interpretation by non-expert end-users is a major challenge many scientists face when converting their scientific technology into a real-life application. Currently, pattern recognition algorithms are the most frequently encountered signal data interpretation algorithms to close this gap, not in the least because of their straight-forward implementation via convenient software packages. Paradoxically, just because their implementation is so straight-forward, it becomes cumbersome to integrate the expert's domain-specific knowledge. In this work, a novel signal data interpretation approach is presented that uses this domain-specific knowledge as its fundament, thereby fully exploiting the unique expertise of the scientist. The new approach applies data preprocessing in an innovative way that transcends its usual purpose and is easy to translate into a software application. Multiple case studies illustrate the straight-forward application of the novel approach. Ultimately, the approach is highly suited for integration in various (bio)analytical applications that require interpretation of signal data.
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Radovanović M, Ilić M, Pastor K, Ačanski M, Panić S, Srdić VV, Randjelović D, Kojić T, Stojanović GM. Rapid detection of olive oil blends using a paper-based portable microfluidic platform. Food Control 2021. [DOI: 10.1016/j.foodcont.2021.107888] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
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16
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Coulometrically determined antioxidant capacity (CDAC) as a possible parameter to categorize extra virgin olive oil. Food Chem 2021; 354:129564. [PMID: 33756334 DOI: 10.1016/j.foodchem.2021.129564] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 02/15/2021] [Accepted: 03/08/2021] [Indexed: 11/22/2022]
Abstract
Antioxidant capacity of extra virgin olive oil (EVOO) is associated with the overall content of health-promoting compounds, including biophenols. In this work, antioxidant capacity of polar extracts from 42 EVOO and 3 edible seed oil samples was evaluated by constant-current coulometry, using Br2 electrogenerated at a Pt anode as the titrant and bioamperometric detection of the end-point through Br2 excess. The Coulometrically Determined Antioxidant Capacity (CDAC) of EVOO extracts covered the 8-25 mmol electrons (e-) kg-1 range, while it was lower for seeds oils (≤5 mmol e- kg-1). Average CDAC of EVOO with biophenols ≥ 250 mg kg-1 (15 ± 4 mmol e- kg-1) was significantly higher than EVOO with biophenols < 250 mg kg-1 (10 ± 2 mmol e- kg-1). CDAC is a robust, cheap, and rapid test that could be exploited to classify EVOO relying on antioxidant capacity rather than on HPLC-determined content of biophenols.
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Chemometric Discrimination of the Geographical Origin of Three Greek Cultivars of Olive Oils by Stable Isotope Ratio Analysis. Foods 2021; 10:foods10020336. [PMID: 33557322 PMCID: PMC7914497 DOI: 10.3390/foods10020336] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Revised: 01/29/2021] [Accepted: 01/29/2021] [Indexed: 01/11/2023] Open
Abstract
Α stable isotope ratio mass spectrometer was used for stable isotope ratio (i.e., δ13C, δ18O, and δ2H) measurements, achieving geographical discrimination using orthogonal projections to latent structures discriminant analysis. A total of 100 Greek monovarietal olive oil samples from three different olive cultivars (cv. Koroneiki, cv. Lianolia Kerkyras, and cv. Maurolia), derived from Central Greece and Peloponnese, were collected during the 2019-2020 harvest year aiming to investigate the effect of botanical and geographical origin on their discrimination through isotopic data. The selection of these samples was made from traditionally olive-growing areas in which no significant research has been done so far. Samples were discriminated mainly by olive cultivar and, partially, by geographical origin, which is congruent with other authors. Based on this model, correct recognition of 93.75% in the training samples and correct prediction of 100% in the test set were achieved. The overall correct classification of the model was 91%. The predictability based on the externally validated method of discrimination was good (Q2 (cum) = 0.681) and illustrated that δ18O and δ2H were the most important isotope markers for the discrimination of olive oil samples. The authenticity of olive oil based on the examined olive varieties can be determined using this technique.
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18
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Salah WA, Nofal M. Review of some adulteration detection techniques of edible oils. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2021; 101:811-819. [PMID: 32833235 DOI: 10.1002/jsfa.10750] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Revised: 08/19/2020] [Accepted: 08/24/2020] [Indexed: 05/27/2023]
Abstract
Edible oils have economical and nutritional benefits. These oils offer nutrients that are essential to human health because they are the primary source of mono- and poly-unsaturated fats. Moreover, edible oils are used in home cooking and industrial food manufacturing. Therefore, edible oils have a considerable demand worldwide. However, some edible oils, such as olive oil, are more expensive than any other vegetable oils. Thus, oils such as olive oil are mixed with cheap edible oils as a result of the high price difference. Accordingly, adulteration in edible oils to obtain additional profit for the producer becomes a major issue of high concern for consumers. Moreover, adulteration in edible oils can cause several problems that affect consumer health. Therefore, the need for a sensitive, accurate and suitable method to detect the adulteration is highly considered. We provide a brief review of the different methods and techniques used to detect adulteration in edible oils, especially olive oil, with the aim of promoting consumer awareness of the authenticity of edible oils. © 2020 Society of Chemical Industry.
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Affiliation(s)
- Wael A Salah
- Department of Electrical Engineering, College of Engineering and Technology, Palestine Technical University - Kadoorie (PTUK), Tulkarm, Palestine
| | - Mays Nofal
- Faculty of Graduate Studies, Palestine Technical University - Kadoorie (PTUK), Tulkarm, Palestine
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19
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Wang X, Wang G, Hou X, Nie S. A Rapid Screening Approach for Authentication of Olive Oil and Classification of Binary Blends of Olive Oils Using Low-Field Nuclear Magnetic Resonance Spectra and Support Vector Machine. FOOD ANAL METHOD 2020. [DOI: 10.1007/s12161-020-01799-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
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20
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Oliinyk B, Isaieva K, Manilov AI, Nychyporuk T, Geloen A, Joffre F, Skryshevsky VA, Litvinenko SV, Lysenko V. Silicon-Based Optoelectronic Tongue for Label-Free and Nonspecific Recognition of Vegetable Oils. ACS OMEGA 2020; 5:5638-5642. [PMID: 32226839 PMCID: PMC7097904 DOI: 10.1021/acsomega.9b03196] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2019] [Accepted: 02/24/2020] [Indexed: 05/08/2023]
Abstract
A special electronic tongue system based on photoelectric measurements on Si-Si/SiN X sensitive structures is reported. The sensing approach is based on measuring of minority carrier lifetime in silicon-based substrates using microwave-detected photoconductance decay. This inexpensive and environmentally friendly combinatorial electronic sensing platform is able to create characteristic electronic fingerprints of liquids, detect, and recognize them. In particular, an application of the optoelectronic tongue for recognition of vegetable oils and their mixtures is described.
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Affiliation(s)
- Bohdan
V. Oliinyk
- Institute
of Analytical Sciences (ISA), UMR CNRS 5280,
UCBL, University of Lyon, 69100 Villeurbanne, France
- OlisensTech, 5, Place
Maréchal Lyautey, 69006 Lyon, France
| | - Karyna Isaieva
- IADI,
Université de Lorraine, INSERM U1254, Nancy F-54000, France
| | - Anton I. Manilov
- Institute
of High Technologies, Taras Shevchenko National
University of Kyiv, 01033 Kyiv, Ukraine
- Corporation
Science Park Taras Shevchenko University of Kyiv, 01033 Kyiv, Ukraine
| | - Tetyana Nychyporuk
- Nanotechnology
Institute of Lyon (INL), UMR CNRS 5270,
INSA de Lyon, University of Lyon, 69621 Lyon, France
| | - Alain Geloen
- CarMeN
Laboratory, INRA UMR1397, INSERM U1060,
INSA de Lyon, IMBL, University of Lyon, 69621 Lyon, France
| | | | - Valeriy A. Skryshevsky
- Institute
of High Technologies, Taras Shevchenko National
University of Kyiv, 01033 Kyiv, Ukraine
- Corporation
Science Park Taras Shevchenko University of Kyiv, 01033 Kyiv, Ukraine
| | - Sergii V. Litvinenko
- Institute
of High Technologies, Taras Shevchenko National
University of Kyiv, 01033 Kyiv, Ukraine
- Corporation
Science Park Taras Shevchenko University of Kyiv, 01033 Kyiv, Ukraine
| | - Vladimir Lysenko
- Light-Matter
Institute (ILM), UMR CNRS 5306, University
of Lyon (UCBL), 69622 Lyon, France
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21
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Salamanca-Neto CAR, Marcheafave GG, Scremin J, Barbosa ECM, Camargo PHC, Dekker RFH, Scarminio IS, Barbosa-Dekker AM, Sartori ER. Chemometric-assisted construction of a biosensing device to measure chlorogenic acid content in brewed coffee beverages to discriminate quality. Food Chem 2020; 315:126306. [PMID: 32035315 DOI: 10.1016/j.foodchem.2020.126306] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Revised: 01/24/2020] [Accepted: 01/26/2020] [Indexed: 12/24/2022]
Abstract
In this work we propose the use of statistical mixture design in the construction of a biosensor device based on graphite oxide, platinum nanoparticles and biomaterials obtained from Botryosphaeria rhodina MAMB-05. The biosensor was characterized by electrochemical impedance spectroscopy. Under optimized experimental parameters by factorial design, the biosensor was applied to the voltammetric determination of chlorogenic acid (CGA) measured as 5-O-caffeoylquinic acid (5-CQA). The biosensor response was linear (R2 = 0.998) for 5-CQA in the concentration range 0.56-7.3 µmol L-1, with limit of detection and quantification of 0.18 and 0.59 µmol L-1, respectively. The new biosensing device was applied to quality control analysis based upon the determination of CGA content in specialty and traditional coffee beverages. The results indicated that specialty coffee had a significantly higher content of CGA. Principal component analysis of the voltammetric fingerprint of brewed coffees revealed that the laccase-based biosensor can be used for their discrimination.
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Affiliation(s)
- Carlos A R Salamanca-Neto
- Departamento de Química, Centro de Ciências Exatas, Universidade Estadual de Londrina, CEP 86057-970 Londrina, PR, Brazil.
| | - Gustavo G Marcheafave
- Departamento de Química, Centro de Ciências Exatas, Universidade Estadual de Londrina, CEP 86057-970 Londrina, PR, Brazil
| | - Jessica Scremin
- Departamento de Química, Centro de Ciências Exatas, Universidade Estadual de Londrina, CEP 86057-970 Londrina, PR, Brazil
| | - Eduardo C M Barbosa
- Departamento de Química Fundamental, Instituto de Química, Universidade de São Paulo, CEP 05508-000 São Paulo, SP, Brazil
| | - Pedro H C Camargo
- Departamento de Química Fundamental, Instituto de Química, Universidade de São Paulo, CEP 05508-000 São Paulo, SP, Brazil
| | - Robert F H Dekker
- Programa de Pós-Graduação em Engenharia Ambiental, Universidade Tecnológica Federal do Paraná, Câmpus Londrina, CEP 86036-370 Londrina, PR, Brazil
| | - Ieda S Scarminio
- Departamento de Química, Centro de Ciências Exatas, Universidade Estadual de Londrina, CEP 86057-970 Londrina, PR, Brazil
| | - Aneli M Barbosa-Dekker
- Departamento de Química, Centro de Ciências Exatas, Universidade Estadual de Londrina, CEP 86057-970 Londrina, PR, Brazil
| | - Elen R Sartori
- Departamento de Química, Centro de Ciências Exatas, Universidade Estadual de Londrina, CEP 86057-970 Londrina, PR, Brazil.
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A Preliminary Study on Metabolome Profiles of Buffalo Milk and Corresponding Mozzarella Cheese: Safeguarding the Authenticity and Traceability of Protected Status Buffalo Dairy Products. Molecules 2020; 25:molecules25020304. [PMID: 31940896 PMCID: PMC7024333 DOI: 10.3390/molecules25020304] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 01/06/2020] [Accepted: 01/10/2020] [Indexed: 01/11/2023] Open
Abstract
The aim of this study is to combine advanced GC-MS and metabolite identification in a robust and repeatable technology platform to characterize the metabolome of buffalo milk and mozzarella cheese. The study utilized eleven dairies located in a protected designation of origin (PDO) region and nine dairies located in non-PDO region in Italy. Samples of raw milk (100 mL) and mozzarella cheese (100 g) were obtained from each dairy. A total of 185 metabolites were consistently detected in both milk and mozzarella cheese. The PLS-DA score plots clearly differentiated PDO and non-PDO milk and mozzarella samples. For milk samples, it was possible to divide metabolites into two classes according to region: those with lower concentrations in PDO samples (galactopyranoside, hydroxybuthyric acid, allose, citric acid) and those with lower concentrations in non-PDO samples (talopyranose, pantothenic acid, mannobiose, etc.,). The same was observed for mozzarella samples with the proportion of some metabolites (talopyranose, 2, 3-dihydroxypropyl icosanoate, etc.,) higher in PDO samples while others (tagatose, lactic acid dimer, ribitol, etc.,) higher in non-PDO samples. The findings establish the utility of GC-MS together with mass spectral libraries as a powerful technology platform to determine the authenticity, and create market protection, for “Mozzarella di Bufala Campana.”
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23
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Nikolaou P, Deskoulidis E, Topoglidis E, Kakoulidou AT, Tsopelas F. Application of chemometrics for detection and modeling of adulteration of fresh cow milk with reconstituted skim milk powder using voltammetric fingerpriting on a graphite/ SiO2 hybrid electrode. Talanta 2020; 206:120223. [DOI: 10.1016/j.talanta.2019.120223] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 07/31/2019] [Accepted: 08/02/2019] [Indexed: 12/31/2022]
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24
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Sun L, Liu F, You G, Feng T, Wang M, Liu Y, Ren X, Deng Y. A comparative analysis of Aconiti Lateralis Radix and processed products using UHPLC-Q-TOF-MS combined with multivariate chemometrics strategies. J LIQ CHROMATOGR R T 2019. [DOI: 10.1080/10826076.2019.1659150] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
- Lili Sun
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Fan Liu
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Guangjiao You
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Tao Feng
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Meng Wang
- Tianjin State Key Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yanan Liu
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Xiaoliang Ren
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yanru Deng
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, China
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25
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Meenu M, Cai Q, Xu B. A critical review on analytical techniques to detect adulteration of extra virgin olive oil. Trends Food Sci Technol 2019. [DOI: 10.1016/j.tifs.2019.07.045] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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26
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Assessment of Virgin Olive Oil Adulteration by a Rapid Luminescent Method. Foods 2019; 8:foods8080287. [PMID: 31349694 PMCID: PMC6723203 DOI: 10.3390/foods8080287] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2019] [Revised: 07/23/2019] [Accepted: 07/23/2019] [Indexed: 11/24/2022] Open
Abstract
The adulteration of virgin olive oil with hazelnut oil is a common fraud in the food industry, which makes mandatory the development of accurate methods to guarantee the authenticity and traceability of virgin olive oil. In this work, we demonstrate the potential of a rapid luminescent method to characterize edible oils and to detect adulterations among them. A regression model based on five luminescent frequencies related to minor oil components was designed and validated, providing excellent performance for the detection of virgin olive oil adulteration.
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27
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Baldo MA, Oliveri P, Fabris S, Malegori C, Daniele S. Fast determination of extra-virgin olive oil acidity by voltammetry and Partial Least Squares regression. Anal Chim Acta 2019; 1056:7-15. [DOI: 10.1016/j.aca.2018.12.050] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Revised: 12/22/2018] [Accepted: 12/26/2018] [Indexed: 10/27/2022]
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