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Kanwal N, Musharraf SG. Analytical approaches for the determination of adulterated animal fats and vegetable oils in food and non-food samples. Food Chem 2024; 460:140786. [PMID: 39142208 DOI: 10.1016/j.foodchem.2024.140786] [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: 04/17/2024] [Revised: 08/01/2024] [Accepted: 08/05/2024] [Indexed: 08/16/2024]
Abstract
Edible oils and fats are crucial components of everyday cooking and the production of food products, but their purity has been a major issue for a long time. High-quality edible oils are contaminated with low- and cheap-quality edible oils to increase profits. The adulteration of edible oils and fats also produces many health risks. Detection of main and minor components can identify adulterations using various techniques, such as GC, HPLC, TLC, FTIR, NIR, NMR, direct mass spectrometry, PCR, E-Nose, and DSC. Each detection technique has its advantages and disadvantages. For example, chromatography offers high precision but requires extensive sample preparation, while spectroscopy is rapid and non-destructive but may lack resolution. Direct mass spectrometry is faster and simpler than chromatography-based MS, eliminating complex preparation steps. DNA-based oil authentication is effective but hindered by laborious extraction processes. E-Nose only distinguishes odours, and DSC directly studies lipid thermal properties without derivatization or solvents. Mass spectrometry-based techniques, particularly GC-MS is found to be highly effective for detecting adulteration of oils and fats in food and non-food samples. This review summarizes the benefits and drawbacks of these analytical approaches and their use in conjunction with chemometric tools to detect the adulteration of animal fats and vegetable oils. This combination provides a powerful technique with enormous chemotaxonomic potential that includes the detection of adulterations, quality assurance, assessment of geographical origin, assessment of the process, and classification of the product in complex matrices from food and non-food samples.
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Affiliation(s)
- Nayab Kanwal
- H. E. J. Research Institute of Chemistry, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan
| | - Syed Ghulam Musharraf
- H. E. J. Research Institute of Chemistry, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan; Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan..
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2
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Haji A, Desalegn K, Hassen H. Selected food items adulteration, their impacts on public health, and detection methods: A review. Food Sci Nutr 2023; 11:7534-7545. [PMID: 38107123 PMCID: PMC10724644 DOI: 10.1002/fsn3.3732] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 09/07/2023] [Accepted: 09/18/2023] [Indexed: 12/19/2023] Open
Abstract
Every living thing requires food to survive. Clean, fresh, and healthy foods are important to human health. Today, food is affected by various counterfeits. Adulteration of food is the intentional deterioration of the quality of food offered for sale by either the addition or substitution of an inferior substance or by the omission of a valuable ingredient. Economically motivated adulteration is the intentional adulteration of food for financial gain, and has enormous public health implications, making it an important issue in food science. Almost every food, including milk and dairy products, fats and oils, fruits and vegetables, grain foods, coffee, tea, honey, etc., is susceptible to adulteration. It is difficult to find food that is free from adulteration. Consumption of adulterated food contributes to numerous diseases in society, ranging from mild to life threatening. Therefore, detection of adulteration in food is essential to ensure the safety of the food we consume. To provide consumers with food that is free of adulterants, various detection methods such as physical, chemical, biochemical, and molecular techniques are used to identify adulterants in food. This review aims to provide up-to-date information on food adulteration, its impact on health, and the analytical techniques used to detect adulteration in food.
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Affiliation(s)
- Abdulmajid Haji
- Department of Post‐Harvest ManagementCollege of Agriculture and Veterinary Medicine, Jimma UniversityJimmaEthiopia
| | - Kasahun Desalegn
- Department of Post‐Harvest ManagementCollege of Agriculture and Veterinary Medicine, Jimma UniversityJimmaEthiopia
| | - Hayat Hassen
- Department of Post‐Harvest ManagementCollege of Agriculture and Veterinary Medicine, Jimma UniversityJimmaEthiopia
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Ordoudi SA, Strani L, Cocchi M. Toward the Non-Targeted Detection of Adulterated Virgin Olive Oil with Edible Oils via FTIR Spectroscopy & Chemometrics: Research Methodology Trends, Gaps and Future Perspectives. MOLECULES (BASEL, SWITZERLAND) 2023; 28:molecules28010337. [PMID: 36615530 PMCID: PMC9822006 DOI: 10.3390/molecules28010337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/23/2022] [Accepted: 12/23/2022] [Indexed: 01/04/2023]
Abstract
Fourier-Transform mid-infrared (FTIR) spectroscopy offers a strong candidate screening tool for rapid, non-destructive and early detection of unauthorized virgin olive oil blends with other edible oils. Potential applications to the official anti-fraud control are supported by dozens of research articles with a "proof-of-concept" study approach through different chemometric workflows for comprehensive spectral analysis. It may also assist non-targeted authenticity testing, an emerging goal for modern food fraud inspection systems. Hence, FTIR-based methods need to be standardized and validated to be accepted by the olive industry and official regulators. Thus far, several literature reviews evaluated the competence of FTIR standalone or compared with other vibrational techniques only in view of the chemometric methodology, regardless of the inherent characteristics of the product spectra or the application scope. Regarding authenticity testing, every step of the methodology workflow, and not only the post-acquisition steps, need thorough validation. In this context, the present review investigates the progress in the research methodology on FTIR-based detection of virgin olive oil adulteration over a period of more than 25 years with the aim to capture the trends, identify gaps or misuses in the existing literature and highlight intriguing topics for future studies. An extensive search in Scopus, Web of Science and Google Scholar, combined with bibliometric analysis, helped to extract qualitative and quantitative information from publication sources. Our findings verified that intercomparison of literature results is often impossible; sampling design, FTIR spectral acquisition and performance evaluation are critical methodological issues that need more specific guidance and criteria for application to product authenticity testing.
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Affiliation(s)
- Stella A. Ordoudi
- Laboratory of Food Chemistry and Technology, School of Chemistry, Aristotle University of Thessaloniki (AUTh), GR-54124 Thessaloniki, Greece
- Correspondence:
| | - Lorenzo Strani
- Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia (UNIMORE), Via Campi 103, 41125 Modena, Italy
| | - Marina Cocchi
- Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia (UNIMORE), Via Campi 103, 41125 Modena, Italy
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Ordoudi SA, Özdikicierler O, Tsimidou MZ. Detection of ternary mixtures of virgin olive oil with canola, hazelnut or safflower oils via non-targeted ATR-FTIR fingerprinting and chemometrics. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.109240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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5
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Adulteration Detection of Edible Bird’s Nests Using Rapid Spectroscopic Techniques Coupled with Multi-Class Discriminant Analysis. Foods 2022; 11:foods11162401. [PMID: 36010401 PMCID: PMC9407431 DOI: 10.3390/foods11162401] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 07/30/2022] [Accepted: 08/03/2022] [Indexed: 11/25/2022] Open
Abstract
Edible bird’s nests (EBNs) are vulnerable to adulteration due to their huge demand for traditional medicine and high market price. Presently, there are pressing needs to explore field-deployable rapid screening techniques to detect adulteration of EBNs. The objective of this study is to explore the feasibility of using a handheld near-infrared (VIS/SW-NIR) spectroscopic device for the determination of EBN authenticity against the benchmark performance of a benchtop mid-infrared (MIR) spectrometer. Forty-nine authentic EBNs from the different states in Malaysia and 13 different adulterants (five types) were obtained and used to simulate the adulteration of EBNs at 1, 5 and 10% adulteration by mass (a total of 15 adulterated samples). The VIS/SW-NIR and MIR spectra collated were subsequently processed, modelled and classified using multi-class discriminant analysis. The VIS/SW-NIR results showed 100% correct classification for the collagen and nutrient agar classes in authenticity classification, while for the other classes, the lowest correct classification rate was 96.3%. For MIR analysis, only the karaya gum class had 100% correct classification whilst for the other four classes, the lowest rate of correct classification was at 94.4%. In conclusion, the combination of spectroscopic analysis with chemometrics can be a powerful screening tool to detect EBN adulteration.
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Sen M. Food Chemistry: Role of Additives, Preservatives, and Adulteration. Food Chem 2021. [DOI: 10.1002/9781119792130.ch1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Negi A, Lakshmi P, Praba K, Meenatchi R, Pare A. Detection of Food Adulterants in Different Foodstuff. Food Chem 2021. [DOI: 10.1002/9781119792130.ch5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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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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Authentication of the Botanical and Geographical Origin and Detection of Adulteration of Olive Oil Using Gas Chromatography, Infrared and Raman Spectroscopy Techniques: A Review. Foods 2021; 10:foods10071565. [PMID: 34359435 PMCID: PMC8306465 DOI: 10.3390/foods10071565] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 07/01/2021] [Accepted: 07/02/2021] [Indexed: 01/18/2023] Open
Abstract
Olive oil is among the most popular supplements of the Mediterranean diet due to its high nutritional value. However, at the same time, because of economical purposes, it is also one of the products most subjected to adulteration. As a result, authenticity is an important issue of concern among authorities. Many analytical techniques, able to detect adulteration of olive oil, to identify its geographical and botanical origin and consequently guarantee its quality and authenticity, have been developed. This review paper discusses the use of infrared and Raman spectroscopy as candidate tools to examine the authenticity of olive oils. It also considers the volatile fraction as a marker to distinguish between different varieties and adulterated olive oils, using SPME combined with gas chromatography technique.
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10
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Zarezadeh MR, Aboonajmi M, Varnamkhasti MG, Azarikia F. Olive Oil Classification and Fraud Detection Using E-Nose and Ultrasonic System. FOOD ANAL METHOD 2021. [DOI: 10.1007/s12161-021-02035-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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11
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Hou X, Wang G, Wang X, Ge X, Fan Y, Jiang R, Nie S. Rapid screening for hazelnut oil and high-oleic sunflower oil in extra virgin olive oil using low-field nuclear magnetic resonance relaxometry and machine learning. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2021; 101:2389-2397. [PMID: 33011981 DOI: 10.1002/jsfa.10862] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 09/30/2020] [Accepted: 10/04/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND As extra virgin olive oil (EVOO) has high commercial value, it is routinely adulterated with other oils. The present study investigated the feasibility of rapidly identifying adulterated EVOO using low-field nuclear magnetic resonance (LF-NMR) relaxometry and machine learning approaches (decision tree, K-nearest neighbor, linear discriminant analysis, support vector machines and convolutional neural network (CNN)). RESULTS LF-NMR spectroscopy effectively distinguished pure EVOO from that which was adulterated with hazelnut oil (HO) and high-oleic sunflower oil (HOSO). The applied CNN algorithm had an accuracy of 89.29%, a precision of 81.25% and a recall of 81.25%, and enabled the rapid (2 min) discrimination of pure EVOO that was adulterated with HO and HOSO in the volumetric ratio range of 10-100%. CONCLUSIONS LF-NMR coupled with the CNN algorithm is a viable candidate for rapid EVOO authentication. © 2020 Society of Chemical Industry.
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Affiliation(s)
- Xuewen Hou
- School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Guangli Wang
- School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Xin Wang
- School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Xinmin Ge
- School of Geosciences, China University of Petroleum, Qingdao, China
| | - Yiren Fan
- School of Geosciences, China University of Petroleum, Qingdao, China
| | - Rui Jiang
- School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Shengdong Nie
- School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China
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12
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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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13
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Liu Y, Yao L, Xia Z, Gao Y, Gong Z. Geographical discrimination and adulteration analysis for edible oils using two-dimensional correlation spectroscopy and convolutional neural networks (CNNs). SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 246:118973. [PMID: 33017793 DOI: 10.1016/j.saa.2020.118973] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 09/03/2020] [Accepted: 09/16/2020] [Indexed: 06/11/2023]
Abstract
Geographical discrimination and adulteration analysis play significant roles in edible oil analysis. A novel method for discrimination and adulteration analysis of edible oils were proposed in this study. The two-dimensional correlation spectra of edible oils were obtained by solvents perturbation and the convolutional neural networks (CNNs) were constructed to analyze the synchronous and asynchronous correlation spectra of the edible oils. The differences for geographical origins of oils or oil types could be amplificated through the networks. For different networks, the layer sequences and the filter number of convolutional layers may affect the analysis results. A group of sesame oils from different geographical origins and a group of olive oils adulterated by other vegetable oils were adopted to evaluate the proposed method. The results show that the proposed method may provide an alternative method for edible oil discrimination and adulteration analysis in practical applications. For the two datasets, the prediction accuracy could be 97.3% and 88.5%, respectively.
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Affiliation(s)
- Yan Liu
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China; Key Laboratory for Deep Processing of Major Grain and Oil (Wuhan Polytechnic University), Ministry of Education, College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, PR China; Hubei Key Laboratory for Processing and Transformation of Agricultural Products (Wuhan Polytechnic University), College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, PR China.
| | - Liyun Yao
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China
| | - Zhenzhen Xia
- Institute of Agricultural Quality Standards and Testing Technology Research, Hubei Academy of Agricultural Science, Wuhan 430064, China
| | - Yonggui Gao
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China; Key Laboratory for Deep Processing of Major Grain and Oil (Wuhan Polytechnic University), Ministry of Education, College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, PR China; Hubei Key Laboratory for Processing and Transformation of Agricultural Products (Wuhan Polytechnic University), College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, PR China
| | - Zhiyong Gong
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China; Key Laboratory for Deep Processing of Major Grain and Oil (Wuhan Polytechnic University), Ministry of Education, College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, PR China; Hubei Key Laboratory for Processing and Transformation of Agricultural Products (Wuhan Polytechnic University), College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, PR China
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Rapid Screening of Mentha spicata Essential Oil and L-Menthol in Mentha piperita Essential Oil by ATR-FTIR Spectroscopy Coupled with Multivariate Analyses. Foods 2021; 10:foods10020202. [PMID: 33498340 PMCID: PMC7909401 DOI: 10.3390/foods10020202] [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: 12/31/2020] [Revised: 01/10/2021] [Accepted: 01/11/2021] [Indexed: 01/13/2023] Open
Abstract
Mentha piperita essential oil (EO) has high economic importance because of its wide usage area and health-beneficial properties. Besides health-beneficial properties, Mentha piperita EO has great importance in the flavor and food industries because of its unique sensory and quality properties. High-valued essential oils are prone to being adulterated with economic motivations. This kind of adulteration deteriorates the quality of authentic essential oil, injures the consumers, and causes negative effects on the whole supply chain from producer to the consumer. The current research used fast, economic, robust, reliable, and effective ATR-FTIR spectroscopy coupled chemometrics of hierarchical cluster analysis(HCA), principal component analysis (PCA), partial least squares regression (PLSR) and principal component regression (PCR) for monitoring of Mentha spicata EO and L-menthol adulteration in Mentha piperita EOs. Adulterant contents (Mentha spicata and L-menthol) were successfully calculated using PLSR and PCR models. Standard error of the cross-validation SECV values changed between 0.06 and 2.14. Additionally, bias and press values showed alteration between 0.06 and1.43 and 0.03 and 41.15, respectively. Authentic Mentha piperita was successfully distinguished from adulterated samples, Mentha spicata and L-menthol, by HCA and PCA analysis. The results showed that attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, coupled with chemometrics could be effectively used for monitoring various adulterants in essential oils.
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Arendse E, Nieuwoudt H, Magwaza LS, Nturambirwe JFI, Fawole OA, Opara UL. Recent Advancements on Vibrational Spectroscopic Techniques for the Detection of Authenticity and Adulteration in Horticultural Products with a Specific Focus on Oils, Juices and Powders. FOOD BIOPROCESS TECH 2020. [DOI: 10.1007/s11947-020-02505-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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16
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RUFINO MDSM, NAZARENO LSQ, ALVES RE, FERNANDES FAN. Kinetic modeling and evaluation of free radical-scavenging behavior in oils: application to four tropical and subtropical fruits in a DPPH system. FOOD SCIENCE AND TECHNOLOGY 2020. [DOI: 10.1590/fst.03819] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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17
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Rydlewski AA, Pizzo JS, Manin LP, Galuch MB, Santos PDS, Zapiello C, Santos OO, Visentainer JV. Evaluation of possible fraud in avocado oil-based products from the composition of fatty acids by GC-FID and lipid profile by ESI-MS. CHEMICAL PAPERS 2020. [DOI: 10.1007/s11696-020-01119-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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18
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Capar TD, Kavuncuoglu H, Yalcin H, Toga G. Rheological analysis for detection of extra virgin olive oil adulteration with vegetable oils: predicting oil type by artificial neural network. QUALITY ASSURANCE AND SAFETY OF CROPS & FOODS 2019. [DOI: 10.3920/qas2018.1404] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- T. Dursun Capar
- Food Engineering Department, Engineering Faculty, Erciyes University, 38039 Kayseri, Turkey
| | - H. Kavuncuoglu
- Food Engineering Department, Engineering Faculty, Erciyes University, 38039 Kayseri, Turkey
| | - H. Yalcin
- Food Engineering Department, Engineering Faculty, Erciyes University, 38039 Kayseri, Turkey
| | - G. Toga
- Industrial Engineering Department, Engineering Faculty, Erciyes University, 38039 Kayseri, Turkey
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Rodríguez SD, Gagneten M, Farroni AE, Percibaldi NM, Buera MP. FT-IR and untargeted chemometric analysis for adulterant detection in chia and sesame oils. Food Control 2019. [DOI: 10.1016/j.foodcont.2019.05.025] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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20
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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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21
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Determining the Arrhenius Kinetics of Avocado Oil: Oxidative Stability under Rancimat Test Conditions. Foods 2019; 8:foods8070236. [PMID: 31261986 PMCID: PMC6679119 DOI: 10.3390/foods8070236] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Revised: 06/25/2019] [Accepted: 06/26/2019] [Indexed: 11/24/2022] Open
Abstract
Avocado is a highly potential functional fruit with significant health benefits which has high demand for consumption with a preferable taste. The fruit is one of the oil sources that still needs further examination on its probable kinetic behavior and oxidative stability as well as some characteristic behavior to commercialize and increase the market demand as functional oil. Hence, this study was motivated primarily for obtaining the Arrhenius kinetic information about avocado oil to evaluate the oxidative stability and provide predictive information about the shelf life by using the Rancimat method which is an accelerated shelf life test. Specifically, this research paper presents the study of the physical, physicochemical, chemical, and oxidative stability tests with the shelf life expectancy and kinetic property of avocado oil. According to the analyses, avocado oil has 210 days of predicted shelf life at 25 °C. This gives it a greater chance to be considered a good alternative to other oils as well as its antioxidant and phenolic content. According to the findings presented in this study, avocado oil has a very similar profile to olive oil and can be used as an alternative functional oil source.
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22
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Rapid detection of authenticity and adulteration of cold pressed black cumin seed oil: A comparative study of ATR–FTIR spectroscopy and synchronous fluorescence with multivariate data analysis. Food Control 2019. [DOI: 10.1016/j.foodcont.2018.11.055] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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23
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Detection of quinoa flour adulteration by means of FT-MIR spectroscopy combined with chemometric methods. Food Chem 2019; 274:392-401. [DOI: 10.1016/j.foodchem.2018.08.140] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Revised: 07/30/2018] [Accepted: 08/31/2018] [Indexed: 12/31/2022]
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Uncu O, Ozen B, Tokatli F. Mid-infrared spectroscopic detection of sunflower oil adulteration with safflower oil. GRASAS Y ACEITES 2019. [DOI: 10.3989/gya.0579181] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The oil industry is in need of rapid analysis techniques to differentiate mixtures of safflower-sunflower oils from pure oils. The current adulteration detection methods are generally cumbersome and detection limits are questionable. The aim of this study was to test the capability of a mid-infrared spectroscopic method to detect the adulteration of sunflower oil with safflower oil compared to fatty acid analysis. Mid-infrared spectra of pure oils and their mixtures at the 10–60% range were obtained at 4000–650 cm-1 wavenumber and fatty acid profiles were determined. Data were analyzed by multivariate statistical analysis techniques. The lowest level of detection was obtained with mid-infrared spectroscopy at 30% while the fatty acid profile could determine adulteration at around 60%. Adulteration levels were predicted successfully using PLS regression analysis of infrared data with R2 (calibration) = 0.96 and R2 (validation) = 0.93. As a rapid and minimum waste generating technique, mid-infrared spectroscopy could be a useful tool for the screening of raw material to detect safflower-sunflower oil mixtures.
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25
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Determination of three quality parameters in vegetable oils using potentiometric e-tongue. J Food Compost Anal 2019. [DOI: 10.1016/j.jfca.2018.09.015] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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26
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Prediction of Lard in Palm Olein Oil Using Simple Linear Regression (SLR), Multiple Linear Regression (MLR), and Partial Least Squares Regression (PLSR) Based on Fourier-Transform Infrared (FTIR). J CHEM-NY 2018. [DOI: 10.1155/2018/7182801] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Fourier-transform infrared (FTIR) offers the advantages of rapid analysis with minimal sample preparation. FTIR in combination with multivariate approach, particularly partial least squares regression (PLSR), has been widely used for adulterant analysis. Limited study has been done to compare PLSR with other regression strategies. In this paper, we apply simple linear regression (SLR), multiple linear regression (MLR), and PLSR for prediction of lard in palm olein oil. Pure palm olein oil was adulterated with lard at different concentrations and subjected to analysis with FTIR. The marker bands distinguishing lard and palm olein oil were determined using Fisher’s weights. The marker regions were then subjected to regression analysis with the models verified based on 100 training/test sets. The prediction performance was measured based on the percentage root mean square error (%RMSE). The absorption bands at 3006 cm−1, 2852 cm−1, 1117 cm−1, 1236 cm−1, and 1159 cm−1 were identified as the marker bands. The bands at 3006 and 1117 cm−1 were found with satisfactory predictive ability, with PLSR demonstrating better prediction yielding %RMSE of 16.03 and 13.26%, respectively.
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27
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Vanstone N, Moore A, Martos P, Neethirajan S. Detection of the adulteration of extra virgin olive oil by near-infrared spectroscopy and chemometric techniques. FOOD QUALITY AND SAFETY 2018. [DOI: 10.1093/fqsafe/fyy018] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Nick Vanstone
- BioNano Laboratory, School of Engineering, University of Guelph, Guelph, Ontario, Canada
- Agriculture & Food Laboratory, Laboratory Services Division, University of Guelph, Guelph, Ontario, Canada
| | - Andrew Moore
- Agriculture & Food Laboratory, Laboratory Services Division, University of Guelph, Guelph, Ontario, Canada
| | - Perry Martos
- Agriculture & Food Laboratory, Laboratory Services Division, University of Guelph, Guelph, Ontario, Canada
| | - Suresh Neethirajan
- BioNano Laboratory, School of Engineering, University of Guelph, Guelph, Ontario, Canada
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28
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Ozulku G, Yildirim RM, Toker OS, Karasu S, Durak MZ. Rapid detection of adulteration of cold pressed sesame oil adultered with hazelnut, canola, and sunflower oils using ATR-FTIR spectroscopy combined with chemometric. Food Control 2017. [DOI: 10.1016/j.foodcont.2017.06.034] [Citation(s) in RCA: 81] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Bansal S, Singh A, Mangal M, Mangal AK, Kumar S. Food adulteration: Sources, health risks, and detection methods. Crit Rev Food Sci Nutr 2017; 57:1174-1189. [PMID: 26054861 DOI: 10.1080/10408398.2014.967834] [Citation(s) in RCA: 108] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
Adulteration in food has been a concern since the beginning of civilization, as it not only decreases the quality of food products but also results in a number of ill effects on health. Authentic testing of food and adulterant detection of various food products is required for value assessment and to assure consumer protection against fraudulent activities. Through this review we intend to compile different types of adulterations made in different food items, the health risks imposed by these adulterants and detection methods available for them. Concerns about food safety and regulation have ensured the development of various techniques like physical, biochemical/immunological and molecular techniques, for adulterant detection in food. Molecular methods are more preferable when it comes to detection of biological adulterants in food, although physical and biochemical techniques are preferable for detection of other adulterants in food.
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Affiliation(s)
- Sangita Bansal
- a Central Institute of Post Harvest Engineering and Technology , Ludhiana , Punjab , India
| | - Apoorva Singh
- a Central Institute of Post Harvest Engineering and Technology , Ludhiana , Punjab , India
| | - Manisha Mangal
- b Indian Agricultural Research Institute , New Delhi , India
| | - Anupam K Mangal
- c Central Council for Research in Ayurvedic Sciences , New Delhi , India
| | - Sanjiv Kumar
- d National Medicinal Plant Board , New Delhi , India
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30
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A critical evaluation of the analytical techniques in the photodegradation monitoring of edible oils. Lebensm Wiss Technol 2017. [DOI: 10.1016/j.lwt.2016.10.055] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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31
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Georgouli K, Martinez Del Rincon J, Koidis A. Continuous statistical modelling for rapid detection of adulteration of extra virgin olive oil using mid infrared and Raman spectroscopic data. Food Chem 2017; 217:735-742. [DOI: 10.1016/j.foodchem.2016.09.011] [Citation(s) in RCA: 75] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2016] [Revised: 08/11/2016] [Accepted: 09/03/2016] [Indexed: 01/24/2023]
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32
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Dymińska L, Calik M, Albegar AMM, Zając A, Kostyń K, Lorenc J, Hanuza J. Quantitative determination of the iodine values of unsaturated plant oils using infrared and Raman spectroscopy methods. INTERNATIONAL JOURNAL OF FOOD PROPERTIES 2017. [DOI: 10.1080/10942912.2016.1230744] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Lucyna Dymińska
- Department of Bioorganic Chemistry, Institute of Chemistry and Food Technology, Faculty of Engineering and Economics, Wrocław University of Economics, Wrocław, Poland
| | - Maciej Calik
- Department of Bioorganic Chemistry, Institute of Chemistry and Food Technology, Faculty of Engineering and Economics, Wrocław University of Economics, Wrocław, Poland
| | | | - Adam Zając
- Department of Bioorganic Chemistry, Institute of Chemistry and Food Technology, Faculty of Engineering and Economics, Wrocław University of Economics, Wrocław, Poland
| | - Kamil Kostyń
- Faculty of Biotechnology Sciences, Wrocław University, Przybyszewskiego, Poland
| | - Jadwiga Lorenc
- Department of Bioorganic Chemistry, Institute of Chemistry and Food Technology, Faculty of Engineering and Economics, Wrocław University of Economics, Wrocław, Poland
| | - Jerzy Hanuza
- Institute of Low Temperature and Structure Research, Polish Academy of Sciences, Wrocław, Poland
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33
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Al-Kahtani H, Ahmed M, Abou-Arab A, Hayat K. Identification of lard in vegetable oil binary mixtures and commercial food products by FTIR. QUALITY ASSURANCE AND SAFETY OF CROPS & FOODS 2017. [DOI: 10.3920/qas2015.0692] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- H.A. Al-Kahtani
- Department of Food Science and Nutrition, College of Food and Agriculture Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia
| | - M.A. Ahmed
- Department of Food Science and Nutrition, College of Food and Agriculture Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia
| | - A.A. Abou-Arab
- Department of Food Science and Technology, Faculty of Agriculture, Ain Shams University, P.O. Box 11241, Cairo, Egypt
| | - K. Hayat
- Department of Food Science and Nutrition, College of Food and Agriculture Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia
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34
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A detection method of vegetable oils in edible blended oil based on three-dimensional fluorescence spectroscopy technique. Food Chem 2016; 212:72-7. [DOI: 10.1016/j.foodchem.2016.05.158] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2014] [Revised: 05/21/2016] [Accepted: 05/24/2016] [Indexed: 11/22/2022]
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35
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Chemometrics Methods for Specificity, Authenticity and Traceability Analysis of Olive Oils: Principles, Classifications and Applications. Foods 2016; 5:foods5040077. [PMID: 28231172 PMCID: PMC5302435 DOI: 10.3390/foods5040077] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2016] [Revised: 11/07/2016] [Accepted: 11/10/2016] [Indexed: 11/23/2022] Open
Abstract
Background. Olive oils (OOs) show high chemical variability due to several factors of genetic, environmental and anthropic types. Genetic and environmental factors are responsible for natural compositions and polymorphic diversification resulting in different varietal patterns and phenotypes. Anthropic factors, however, are at the origin of different blends’ preparation leading to normative, labelled or adulterated commercial products. Control of complex OO samples requires their (i) characterization by specific markers; (ii) authentication by fingerprint patterns; and (iii) monitoring by traceability analysis. Methods. These quality control and management aims require the use of several multivariate statistical tools: specificity highlighting requires ordination methods; authentication checking calls for classification and pattern recognition methods; traceability analysis implies the use of network-based approaches able to separate or extract mixed information and memorized signals from complex matrices. Results. This chapter presents a review of different chemometrics methods applied for the control of OO variability from metabolic and physical-chemical measured characteristics. The different chemometrics methods are illustrated by different study cases on monovarietal and blended OO originated from different countries. Conclusion. Chemometrics tools offer multiple ways for quantitative evaluations and qualitative control of complex chemical variability of OO in relation to several intrinsic and extrinsic factors.
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36
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Detection of goat body fat adulteration in pure ghee using ATR-FTIR spectroscopy coupled with chemometric strategy. Journal of Food Science and Technology 2016; 53:3752-3760. [PMID: 28017990 DOI: 10.1007/s13197-016-2353-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Revised: 09/23/2016] [Accepted: 09/29/2016] [Indexed: 10/20/2022]
Abstract
Ghee forms an important component of the diet of human beings due to its rich flavor and high nutritive value. This high priced fat is prone to adulteration with cheaper fats. ATR-FTIR spectroscopy coupled with chemometrics was applied for determining the presence of goat body fat in ghee (@1, 3, 5, 10, 15 and 20% level in the laboratory made/spiked samples). The spectra of pure (ghee and goat body fat) and spiked samples were taken in the wavenumber range of 4000-500 cm-1. Separated clusters of pure ghee and spiked samples were obtained on applying principal component analysis at 5% level of significance in the selected wavenumber range (1786-1680, 1490-919 and 1260-1040 cm-1). SIMCA was applied for classification of samples and pure ghee showed 100% classification efficiency. The value of R2 was found to be >0.99 for calibration and validation sets using partial least square method at all the selected wavenumber range which indicate that the model was well developed. The study revealed that the spiked samples of goat body fat could be detected even at 1% level in ghee.
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37
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Hu Y, Pan ZJ, Liao W, Li J, Gruget P, Kitts DD, Lu X. Determination of antioxidant capacity and phenolic content of chocolate by attenuated total reflectance-Fourier transformed-infrared spectroscopy. Food Chem 2016; 202:254-61. [DOI: 10.1016/j.foodchem.2016.01.130] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2015] [Revised: 01/23/2016] [Accepted: 01/29/2016] [Indexed: 12/28/2022]
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38
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De Luca M, Restuccia D, Clodoveo ML, Puoci F, Ragno G. Chemometric analysis for discrimination of extra virgin olive oils from whole and stoned olive pastes. Food Chem 2016; 202:432-7. [DOI: 10.1016/j.foodchem.2016.02.018] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2015] [Revised: 09/29/2015] [Accepted: 02/01/2016] [Indexed: 10/22/2022]
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39
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Mabood F, Boqué R, Folcarelli R, Busto O, Jabeen F, Al-Harrasi A, Hussain J. The effect of thermal treatment on the enhancement of detection of adulteration in extra virgin olive oils by synchronous fluorescence spectroscopy and chemometric analysis. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2016; 161:83-87. [PMID: 26963728 DOI: 10.1016/j.saa.2016.02.032] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2015] [Revised: 01/25/2016] [Accepted: 02/28/2016] [Indexed: 06/05/2023]
Abstract
In this study the effect of thermal treatment on the enhancement of synchronous fluorescence spectroscopic method for discrimination and quantification of pure extra virgin olive oil (EVOO) samples from EVOO samples adulterated with refined oil was investigated. Two groups of samples were used. One group was analyzed at room temperature (25 °C) and the other group was thermally treated in a thermostatic water bath at 75 °C for 8h, in contact with air and with light exposure, to favor oxidation. All the samples were then measured with synchronous fluorescence spectroscopy. Synchronous fluorescence spectra were acquired by varying the wavelength in the region from 250 to 720 nm at 20 nm wavelength differential interval of excitation and emission. Pure and adulterated olive oils were discriminated by using partial least-squares discriminant analysis (PLS-DA). It was found that the best PLS-DA models were those built with the difference spectra (75 °C-25 °C), which were able to discriminate pure from adulterated oils at a 2% level of adulteration of refined olive oils. Furthermore, PLS regression models were also built to quantify the level of adulteration. Again, the best model was the one built with the difference spectra, with a prediction error of 3.18% of adulteration.
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Affiliation(s)
- F Mabood
- Department of Biological Sciences & Chemistry, College of Arts and Sciences, University of Nizwa, Oman.
| | - R Boqué
- Department of Analytical Chemistry and Organic Chemistry, Universitat Rovira i Virgili, Tarragona, Spain
| | - R Folcarelli
- Department of Chemistry, University of Rome "Sapienza", P.e Aldo Moro 5, I-00185 Rome, Italy
| | - O Busto
- Department of Analytical Chemistry and Organic Chemistry, Universitat Rovira i Virgili, Tarragona, Spain
| | - F Jabeen
- Department of Chemistry, University of Malakand, KPK, Pakistan
| | - Ahmed Al-Harrasi
- UoN Chair of Oman Medicinal Plants and Marine Products, University of Nizwa, Sultanate of Oman
| | - J Hussain
- Department of Biological Sciences & Chemistry, College of Arts and Sciences, University of Nizwa, Oman
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40
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A rapid method to authenticate vegetable oils through surface-enhanced Raman scattering. Sci Rep 2016; 6:23405. [PMID: 26987802 PMCID: PMC4796845 DOI: 10.1038/srep23405] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2015] [Accepted: 02/29/2016] [Indexed: 01/18/2023] Open
Abstract
Vegetable oils are essential in our daily diet. Among various vegetable oils, the major difference lies in the composition of fatty acids, including unsaturated fatty acids (USFA) and saturated fatty acids (SFA). USFA include oleic acid (OA), linoleic acid (LA), and α-linolenic acid (ALA), while SFA are mainly palmitic acid (PA). In this study, the most typical and abundant USFA present with PA in vegetable oils were quantified. More importantly, certain proportional relationships between the integrated intensities of peaks centered at 1656 cm−1 (S1656) in the surface-enhanced Raman scattering spectra of different USFA were confirmed. Therefore, the LA or ALA content could be converted into an equivalent virtual OA content enabling the characterization of the USFA content in vegetable oils using the equivalent total OA content. In combination with the S1656 of pure OA and using peanut, sesame, and soybean oils as examples, the ranges of S1656 corresponding to the National Standards of China were established to allow the rapid authentication of vegetable oils. Gas chromatograph-mass spectrometer analyses verified the accuracy of the method, with relative errors of less than 5%. Moreover, this method can be extended to other detection fields, such as diseases.
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41
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Lohumi S, Lee S, Lee H, Cho BK. A review of vibrational spectroscopic techniques for the detection of food authenticity and adulteration. Trends Food Sci Technol 2015. [DOI: 10.1016/j.tifs.2015.08.003] [Citation(s) in RCA: 278] [Impact Index Per Article: 30.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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42
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Shao X, Li H, Wang N, Zhang Q. Comparison of different classification methods for analyzing electronic nose data to characterize sesame oils and blends. SENSORS 2015; 15:26726-42. [PMID: 26506350 PMCID: PMC4634481 DOI: 10.3390/s151026726] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/06/2015] [Accepted: 08/13/2015] [Indexed: 11/28/2022]
Abstract
An electronic nose (e-nose) was used to characterize sesame oils processed by three different methods (hot-pressed, cold-pressed, and refined), as well as blends of the sesame oils and soybean oil. Seven classification and prediction methods, namely PCA, LDA, PLS, KNN, SVM, LASSO and RF, were used to analyze the e-nose data. The classification accuracy and MAUC were employed to evaluate the performance of these methods. The results indicated that sesame oils processed with different methods resulted in different sensor responses, with cold-pressed sesame oil producing the strongest sensor signals, followed by the hot-pressed sesame oil. The blends of pressed sesame oils with refined sesame oil were more difficult to be distinguished than the blends of pressed sesame oils and refined soybean oil. LDA, KNN, and SVM outperformed the other classification methods in distinguishing sesame oil blends. KNN, LASSO, PLS, and SVM (with linear kernel), and RF models could adequately predict the adulteration level (% of added soybean oil) in the sesame oil blends. Among the prediction models, KNN with k = 1 and 2 yielded the best prediction results.
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Affiliation(s)
- Xiaolong Shao
- College of Food Science and Engineering/Collaborative Innovation Center for Modern Grain Circulation, Safety/Key Laboratory of Grains and Oils Quality Control and Processing, Nanjing University of Finance and Economics, Nanjing 210023, China.
| | - Hui Li
- College of Food Science and Engineering/Collaborative Innovation Center for Modern Grain Circulation, Safety/Key Laboratory of Grains and Oils Quality Control and Processing, Nanjing University of Finance and Economics, Nanjing 210023, China.
| | - Nan Wang
- College of Food Science and Engineering/Collaborative Innovation Center for Modern Grain Circulation, Safety/Key Laboratory of Grains and Oils Quality Control and Processing, Nanjing University of Finance and Economics, Nanjing 210023, China.
| | - Qiang Zhang
- Department of Biosystems Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada.
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43
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Hirri A, Bassbasi M, Platikanov S, Tauler R, Oussama A. FTIR Spectroscopy and PLS-DA Classification and Prediction of Four Commercial Grade Virgin Olive Oils from Morocco. FOOD ANAL METHOD 2015. [DOI: 10.1007/s12161-015-0255-y] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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44
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Li B, Wang H, Zhao Q, Ouyang J, Wu Y. Rapid detection of authenticity and adulteration of walnut oil by FTIR and fluorescence spectroscopy: A comparative study. Food Chem 2015; 181:25-30. [DOI: 10.1016/j.foodchem.2015.02.079] [Citation(s) in RCA: 57] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2014] [Revised: 01/24/2015] [Accepted: 02/14/2015] [Indexed: 10/24/2022]
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45
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Rohman A, Windarsih A, Riyanto S, Sudjadi, Shuhel Ahmad SA, Rosman AS, Yusoff FM. Fourier Transform Infrared Spectroscopy Combined with Multivariate Calibrations for the Authentication of Avocado Oil. INTERNATIONAL JOURNAL OF FOOD PROPERTIES 2015. [DOI: 10.1080/10942912.2015.1039029] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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46
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Mabood F, Boqué R, Folcarelli R, Busto O, Al-Harrasi A, Hussain J. Thermal oxidation process accelerates degradation of the olive oil mixed with sunflower oil and enables its discrimination using synchronous fluorescence spectroscopy and chemometric analysis. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2015; 143:298-303. [PMID: 25748285 DOI: 10.1016/j.saa.2015.01.119] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2014] [Revised: 12/15/2014] [Accepted: 01/31/2015] [Indexed: 06/04/2023]
Abstract
We have investigated the effect of thermal treatment on the discrimination of pure extra virgin olive oil (EVOO) samples from EVOO samples adulterated with sunflower oil. Two groups of samples were used. One group was analyzed at room temperature (25°C) and the other group was thermally treated in a thermostatic water bath at 75°C for 8h, in contact with air and with light exposure, to favor oxidation. All samples were then measured with synchronous fluorescence spectroscopy. Fluorescence spectra were acquired by varying the excitation wavelength in the region from 250 to 720nm. In order to optimize the differences between excitation and emission wavelengths, four constant differential wavelengths, i.e., 20nm, 40nm, 60nm and 80nm, were tried. Partial least-squares discriminant analysis (PLS-DA) was used to discriminate between pure and adulterated oils. It was found that the 20nm difference was the optimal, at which the discrimination models showed the best results. The best PLS-DA models were those built with the difference spectra (75-25°C), which were able to discriminate pure from adulterated oils at a 2% level of adulteration. Furthermore, PLS regression models were built to quantify the level of adulteration. Again, the best model was the one built with the difference spectra, with a prediction error of 1.75% of adulteration.
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Affiliation(s)
- Fazal Mabood
- Department of Biological Sciences & Chemistry, College of Arts and Sciences, University of Nizwa, Oman.
| | - Ricard Boqué
- Department of Analytical Chemistry and Organic Chemistry, Universitat Rovira i Virgili, Tarragona, Spain
| | - Rita Folcarelli
- Department of Chemistry, University of Rome "Sapienza", P.e Aldo Moro 5, I-00185 Rome, Italy
| | - Olga Busto
- Department of Analytical Chemistry and Organic Chemistry, Universitat Rovira i Virgili, Tarragona, Spain
| | - Ahmed Al-Harrasi
- Department of Biological Sciences & Chemistry, College of Arts and Sciences, University of Nizwa, Oman
| | - Javid Hussain
- Department of Biological Sciences & Chemistry, College of Arts and Sciences, University of Nizwa, Oman
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47
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Zhong J, Qin X. Rapid Quantitative Analysis of Corn Starch Adulteration in Konjac Glucomannan by Chemometrics-Assisted FT-NIR Spectroscopy. FOOD ANAL METHOD 2015. [DOI: 10.1007/s12161-015-0176-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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48
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Vergara-Barberán M, Lerma-García MJ, Herrero-Martínez JM, Simó-Alfonso EF. Cultivar discrimination of Spanish olives by using direct FTIR data combined with linear discriminant analysis. EUR J LIPID SCI TECH 2015. [DOI: 10.1002/ejlt.201400425] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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49
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Osorio MT, Haughey SA, Elliott CT, Koidis A. Evaluation of methodologies to determine vegetable oil species present in oil mixtures: Proposition of an approach to meet the EU legislation demands for correct vegetable oils labelling. Food Res Int 2014. [DOI: 10.1016/j.foodres.2013.12.013] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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50
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Parker T, Limer E, Watson AD, Defernez M, Williamson D, Kemsley EK. 60 MHz 1H NMR spectroscopy for the analysis of edible oils. Trends Analyt Chem 2014; 57:147-158. [PMID: 24850979 PMCID: PMC4024201 DOI: 10.1016/j.trac.2014.02.006] [Citation(s) in RCA: 80] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
We present the first results from a new 60 MHz 1H NMR bench-top spectrometer. Using chemometrics, we detected hazelnut oil adulteration of olive oil at 11.2%w/w. Bench-top 60 MHz NMR performs at least as well as FTIR for this type of application.
We report the first results from a new 60 MHz 1H nuclear magnetic resonance (NMR) bench-top spectrometer, Pulsar, in a study simulating the adulteration of olive oil with hazelnut oil. There were qualitative differences between spectra from the two oil types. A single internal ratio of two isolated groups of peaks could detect hazelnut oil in olive oil at the level of ∼13%w/w, whereas a whole-spectrum chemometric approach brought the limit of detection down to 11.2%w/w for a set of independent test samples. The Pulsar’s performance was compared to that of Fourier transform infrared (FTIR) spectroscopy. The Pulsar delivered comparable sensitivity and improved specificity, making it a superior screening tool. We also mapped NMR onto FTIR spectra using a correlation-matrix approach. Interpretation of this heat-map combined with the established annotations of the NMR spectra suggested a hitherto undocumented feature in the IR spectrum at ∼1130 cm−1, attributable to a double-bond vibration.
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Affiliation(s)
- T Parker
- School of Chemistry, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK
| | - E Limer
- Oriel College, University of Oxford, Oxford OX1 4EW, UK
| | - A D Watson
- Analytical Sciences Unit, Institute of Food Research, Norwich Research Park, Norwich NR4 7UA, UK
| | - M Defernez
- Analytical Sciences Unit, Institute of Food Research, Norwich Research Park, Norwich NR4 7UA, UK
| | - D Williamson
- Oxford Instruments Industrial Analysis, Tubney Woods, Abingdon, Oxford, UK
| | - E Kate Kemsley
- Analytical Sciences Unit, Institute of Food Research, Norwich Research Park, Norwich NR4 7UA, UK
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