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Chen H, Tan C, Lin Z, Chen M, Cheng B. Applying virtual sample generation and ensemble modeling for improving the spectral diagnosis of cancer. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 318:124518. [PMID: 38796889 DOI: 10.1016/j.saa.2024.124518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 05/11/2024] [Accepted: 05/23/2024] [Indexed: 05/29/2024]
Abstract
Cancer diagnosis plays a key role in facilitating treatment and improving survival rates of patients. The combination of near-infrared (NIR) spectroscopy with data-driven algorithms offers a rapid and cost-effective approach for such a task. Due to the limitations of objective cases, the number of tumor samples is usually smaller, and the resulting dataset exhibit the issues of class imbalance, which has a more serious impact on the performance of diagnostic models. To deal with class imbalance and improve the sensitivity, this work investigates the feasibility of NIR spectroscopy combined with virtual sample generation (VSG) as well as ensemble strategy for developing diagnostic models. Based on preliminary experiment, several learning algorithms such as discriminant analysis (DA) and partial least square-discriminant analysis (PLS-DA) are screened out as algorithms for constructing prediction models. Three algorithms of VSG including synthetic minority oversampling technique (SMOTE), Borderline-SMOTE and adaptive synthetic sampling (ADASYN) are used for experiment. A fixed sample subset composed of 27 cancer samples and 54 normal samples are hold out as the test set. Three training sets containing 5, 10, 25 minority class samples and 54 majority class samples are used for model development. The experimental result indicates that overall, with PLS-DA algorithm, all VSG approaches can significantly improve the sensitivity of cancer diagnosis for all cases of training sets with different minority samples, but ADASYN performs the best. It reveals that the integration of NIR, PLS-DA, and ADASYN is a promising tool package for developing diagnosis methods.
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Affiliation(s)
- Hui Chen
- Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China; Hospital, Yibin University, Yibin, Sichuan 644000, China
| | - Chao Tan
- Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China; College of Materials and Chemical Engineering, Yibin University, Yibin, Sichuan 644000, China.
| | - Zan Lin
- Department of Knee Sports Injury, Sichuan Province Orthopedic Hospital, Chengdu, Sichuan 610041, China
| | - Maoxian Chen
- Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China
| | - Bin Cheng
- Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China
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2
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Ozen B, Cavdaroglu C, Tokatli F. Trends in authentication of edible oils using vibrational spectroscopic techniques. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2024; 16:4216-4233. [PMID: 38899503 DOI: 10.1039/d4ay00562g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
The authentication of edible oils has become increasingly important for ensuring product quality, safety, and compliance with regulatory standards. Some prevalent authenticity issues found in edible oils include blending expensive oils with cheaper substitutes or lower-grade oils, incorrect labeling regarding the oil's source or type, and falsely stating the oil's origin. Vibrational spectroscopy techniques, such as infrared (IR) and Raman spectroscopy, have emerged as effective tools for rapidly and non-destructively analyzing edible oils. This review paper offers a comprehensive overview of recent advancements in using vibrational spectroscopy for authenticating edible oils. The fundamental principles underlying vibrational spectroscopy are introduced and chemometric approaches that enhance the accuracy and reliability of edible oil authentication are summarized. Recent research trends highlighted in the review include authenticating newly introduced oils, identifying oils based on their specific origins, adopting handheld/portable spectrometers and hyperspectral imaging, and integrating modern data handling techniques into the use of vibrational spectroscopic techniques for edible oil authentication. Overall, this review provides insights into the current state-of-the-art techniques and prospects for utilizing vibrational spectroscopy in the authentication of edible oils, thereby facilitating quality control and consumer protection in the food industry.
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Affiliation(s)
- Banu Ozen
- Izmir Institute of Technology, Department of Food Engineering, Urla, Izmir, Turkiye.
| | - Cagri Cavdaroglu
- Izmir Institute of Technology, Department of Food Engineering, Urla, Izmir, Turkiye.
| | - Figen Tokatli
- Izmir Institute of Technology, Department of Food Engineering, Urla, Izmir, Turkiye.
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3
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De Luca M, Ioele G, Grande F, Occhiuzzi MA, Chieffallo M, Garofalo A, Ragno G. Multivariate Curve Resolution Methodology Applied to the ATR-FTIR Data for Adulteration Assessment of Virgin Coconut Oil. Molecules 2023; 28:4661. [PMID: 37375216 DOI: 10.3390/molecules28124661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 06/05/2023] [Accepted: 06/07/2023] [Indexed: 06/29/2023] Open
Abstract
Virgin coconut oil (VCO) is a functional food with important health benefits. Its economic interest encourages fraudsters to deliberately adulterate VCO with cheap and low-quality vegetable oils for financial gain, causing health and safety problems for consumers. In this context, there is an urgent need for rapid, accurate, and precise analytical techniques to detect VCO adulteration. In this study, the use of Fourier transform infrared (FTIR) spectroscopy combined with multivariate curve resolution-alternating least squares (MCR-ALS) methodology was evaluated to verify the purity or adulteration of VCO with reference to low-cost commercial oils such as sunflower (SO), maize (MO) and peanut (PO) oils. A two-step analytical procedure was developed, where an initial control chart approach was designed to assess the purity of oil samples using the MCR-ALS score values calculated on a data set of pure and adulterated oils. The pre-treatment of the spectral data by derivatization with the Savitzky-Golay algorithm allowed to obtain the classification limits able to distinguish the pure samples with 100% of correct classifications in the external validation. In the next step, three calibration models were developed using MCR-ALS with correlation constraints for analysis of adulterated coconut oil samples in order to assess the blend composition. Different data pre-treatment strategies were tested to best extract the information contained in the sample fingerprints. The best results were achieved by derivative and standard normal variate procedures obtaining RMSEP and RE% values in the ranges of 1.79-2.66 and 6.48-8.35%, respectively. The models were optimized using a genetic algorithm (GA) to select the most important variables and the final models in the external validations gave satisfactory results in quantifying adulterants, with absolute errors and RMSEP of less than 4.6% and 1.470, respectively.
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Affiliation(s)
- Michele De Luca
- Department of Pharmacy, Health and Nutritional Science, University of Calabria, 87036 Rende, Italy
| | - Giuseppina Ioele
- Department of Pharmacy, Health and Nutritional Science, University of Calabria, 87036 Rende, Italy
| | - Fedora Grande
- Department of Pharmacy, Health and Nutritional Science, University of Calabria, 87036 Rende, Italy
| | | | - Martina Chieffallo
- Department of Pharmacy, Health and Nutritional Science, University of Calabria, 87036 Rende, Italy
| | - Antonio Garofalo
- Department of Pharmacy, Health and Nutritional Science, University of Calabria, 87036 Rende, Italy
| | - Gaetano Ragno
- Department of Pharmacy, Health and Nutritional Science, University of Calabria, 87036 Rende, Italy
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4
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Luo K, Shi Y, Huang R, Wei X, Wu Z, Zhou P, Zhang H, Wang Y, Xiong Z, Lai B. Activation of periodate by N-doped iron-based porous carbon for degradation of sulfisoxazole: Significance of catalyst-mediated electron transfer mechanism. JOURNAL OF HAZARDOUS MATERIALS 2023; 457:131790. [PMID: 37295335 DOI: 10.1016/j.jhazmat.2023.131790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 06/02/2023] [Accepted: 06/04/2023] [Indexed: 06/12/2023]
Abstract
Periodate (PI) has recently been studied as an excellent oxidant in advanced oxidation processes, and its reported mechanism is mainly the formation of reactive oxygen species (ROS). This work presents an efficient approach using N-doped iron-based porous carbon (Fe@N-C) to activate periodate for the degradation of sulfisoxazole (SIZ). Characterization results indicated the catalyst has high catalytic activity, stable structure, and high electron transfer activity. In terms of degradation mechanism, it is pointed out that the non-radical pathway is the dominant mechanism. In order to prove this mechanism, we have carried out scavenging experiments, electron paramagnetic resonance (EPR) analysis, salt bridge experiments and electrochemical experiments, which demonstrate the occurrence of mediated electron transfer mechanism. Fe@N-C could mediate the electron transfer from organic contaminant molecules to PI, thus improving the efficiency of PI utilization, rather than simply inducing the activation of PI through Fe@N-C. The overall results of this study provided a new understanding into the application of Fe@N-C activated PI in wastewater treatment.
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Affiliation(s)
- Kaiyuan Luo
- State Key Laboratory of Hydraulics and Mountain River Engineering, College of Architecture and Environment, Sichuan University, Chengdu 610065, China; Sino-German Centre for Water and Health Research, Sichuan University, Chengdu 610065, China
| | - Yang Shi
- State Key Laboratory of Hydraulics and Mountain River Engineering, College of Architecture and Environment, Sichuan University, Chengdu 610065, China; Sino-German Centre for Water and Health Research, Sichuan University, Chengdu 610065, China
| | - Rongfu Huang
- State Key Laboratory of Hydraulics and Mountain River Engineering, College of Architecture and Environment, Sichuan University, Chengdu 610065, China; Sino-German Centre for Water and Health Research, Sichuan University, Chengdu 610065, China.
| | - Xipeng Wei
- Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou 510006, China.
| | - Zelin Wu
- State Key Laboratory of Hydraulics and Mountain River Engineering, College of Architecture and Environment, Sichuan University, Chengdu 610065, China; Sino-German Centre for Water and Health Research, Sichuan University, Chengdu 610065, China
| | - Peng Zhou
- State Key Laboratory of Hydraulics and Mountain River Engineering, College of Architecture and Environment, Sichuan University, Chengdu 610065, China; Sino-German Centre for Water and Health Research, Sichuan University, Chengdu 610065, China
| | - Heng Zhang
- State Key Laboratory of Hydraulics and Mountain River Engineering, College of Architecture and Environment, Sichuan University, Chengdu 610065, China; Sino-German Centre for Water and Health Research, Sichuan University, Chengdu 610065, China
| | - Yin Wang
- Southwest Municipal Engineering Design&Research Institute of China, Chengdu 610081, China
| | - Zhaokun Xiong
- State Key Laboratory of Hydraulics and Mountain River Engineering, College of Architecture and Environment, Sichuan University, Chengdu 610065, China; Sino-German Centre for Water and Health Research, Sichuan University, Chengdu 610065, China.
| | - Bo Lai
- State Key Laboratory of Hydraulics and Mountain River Engineering, College of Architecture and Environment, Sichuan University, Chengdu 610065, China; Sino-German Centre for Water and Health Research, Sichuan University, Chengdu 610065, China
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5
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Ahmmed F, Gordon KC, Killeen DP, Fraser-Miller SJ. Detection and Quantification of Adulteration in Krill Oil with Raman and Infrared Spectroscopic Methods. Molecules 2023; 28:molecules28093695. [PMID: 37175105 PMCID: PMC10180486 DOI: 10.3390/molecules28093695] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 04/14/2023] [Accepted: 04/20/2023] [Indexed: 05/15/2023] Open
Abstract
Raman and infrared spectroscopy, used as individual and low-level fused datasets, were evaluated to identify and quantify the presence of adulterants (palm oil, PO; ω-3 concentrates in ethyl ester, O3C and fish oil, FO) in krill oil. These datasets were qualitatively analysed with principal component analysis (PCA) and classified as adulterated or unadulterated using support vector machines (SVM). Using partial least squares regression (PLSR), it was possible to identify and quantify the adulterant present in the KO mixture. Raman spectroscopy performed better (r2 = 0.98; RMSEP = 2.3%) than IR spectroscopy (r2 = 0.91; RMSEP = 4.2%) for quantification of O3C in KO. A data fusion approach further improved the analysis with model performance for quantification of PO (r2 = 0.98; RMSEP = 2.7%) and FO (r2 = 0.76; RMSEP = 9.1%). This study demonstrates the potential use of Raman and IR spectroscopy to quantify adulterants present in KO.
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Affiliation(s)
- Fatema Ahmmed
- Te Whai Ao-Dodd-Walls Centre for Photonic and Quantum Technologies, Department of Chemistry, University of Otago, P.O. Box 56, Dunedin 9016, New Zealand
| | - Keith C Gordon
- Te Whai Ao-Dodd-Walls Centre for Photonic and Quantum Technologies, Department of Chemistry, University of Otago, P.O. Box 56, Dunedin 9016, New Zealand
| | - Daniel P Killeen
- The New Zealand Institute for Plant and Food Research Limited, P.O. Box 5114, Port Nelson, Nelson 7043, New Zealand
| | - Sara J Fraser-Miller
- Te Whai Ao-Dodd-Walls Centre for Photonic and Quantum Technologies, Department of Chemistry, University of Otago, P.O. Box 56, Dunedin 9016, New Zealand
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6
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Rapid detection of pork oil adulteration in snakehead fish oil using FTIR-ATR spectroscopy and chemometrics for halal authentication. CHEMICAL PAPERS 2023. [DOI: 10.1007/s11696-023-02671-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
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7
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Forooghi E, Vali Zade S, Sahebi H, Abdollahi H, Sadeghi N, Jannat B. Authentication and Discrimination of Tissue Origin of Bovine Gelatin using Combined Supervised Pattern Recognition Strategies. Microchem J 2023. [DOI: 10.1016/j.microc.2023.108417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
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8
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Pastore TC, Braga LR, da C. Kunze DC, Soares LF, Pastore F, de O. Moreira AC, dos Anjos PV, Lara CS, Coradin VT, W. B. Braga J. A green and direct method for authentication of rosewood essential oil by handheld near infrared spectrometer and one-class classification modeling. Microchem J 2022. [DOI: 10.1016/j.microc.2022.107916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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9
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10
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Surya V, Senthilselvi A. An Optimal Faster Region-Based Convolutional Neural Network for Oil Adulteration Detection. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2022. [DOI: 10.1007/s13369-022-07115-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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11
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Priya RB, Rashmitha R, Preetham GS, Chandrasekar V, Mohan RJ, Sinija VR, Pandiselvam R. Detection of Adulteration in Coconut Oil and Virgin Coconut Oil Using Advanced Analytical Techniques: A Review. FOOD ANAL METHOD 2022. [DOI: 10.1007/s12161-022-02342-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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12
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Belyaev I, Marolda A, Praetorius JP, Sarkar A, Medyukhina A, Hünniger K, Kurzai O, Thilo Figge M. Automated Characterisation of Neutrophil Activation Phenotypes in Ex Vivo Human Candida Blood Infections. Comput Struct Biotechnol J 2022; 20:2297-2308. [PMID: 35615019 PMCID: PMC9120255 DOI: 10.1016/j.csbj.2022.05.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 05/04/2022] [Accepted: 05/05/2022] [Indexed: 11/08/2022] Open
Abstract
Candida bloodstream infections are difficult to diagnose and treat in humans. Infection processes give rise to activation of host immune cells. Immune cell activation is reflected by characteristic cell morphology. Neutrophils exhibit distinct morphodynamics for different Candida species.
Rapid identification of pathogens is required for early diagnosis and treatment of life-threatening bloodstream infections in humans. This requirement is driving the current developments of molecular diagnostic tools identifying pathogens from human whole blood after successful isolation and cultivation. An alternative approach is to determine pathogen-specific signatures from human host immune cells that have been exposed to pathogens. We hypothesise that activated immune cells, such as neutrophils, may exhibit a characteristic behaviour — for instance in terms of their speed, dynamic cell morphology — that allows (i) identifying the type of pathogen indirectly and (ii) providing information on therapeutic efficacy. In this feasibility study, we propose a method for the quantitative assessment of static and morphodynamic features of neutrophils based on label-free time-lapse imaging data. We investigate neutrophil activation phenotypes after confrontation with fungal pathogens and isolation from a human whole-blood assay. In particular, we applied a machine learning supported approach to time-lapse microscopy data from different infection scenarios and were able to distinguish between Candida albicans and C. glabrata infection scenarios with test accuracies well above 75%, and to identify pathogen-free samples with accuracy reaching 100%. These results significantly exceed the test accuracies achieved using state-of-the-art deep neural networks to classify neutrophils by their morphodynamics.
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13
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Pizzo JS, Cruz VH, Santos PD, Silva GR, Souza PM, Manin LP, Santos OO, Visentainer JV. Instantaneous characterization of crude vegetable oils via triacylglycerols fingerprint by atmospheric solids analysis probe tandem mass spectrometry with multiple neutral loss scans. Food Control 2022. [DOI: 10.1016/j.foodcont.2021.108710] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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14
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Huang G, Yuan LM, Shi W, Chen X, Chen X. Using one-class autoencoder for adulteration detection of milk powder by infrared spectrum. Food Chem 2022; 372:131219. [PMID: 34601417 DOI: 10.1016/j.foodchem.2021.131219] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 09/17/2021] [Accepted: 09/22/2021] [Indexed: 12/11/2022]
Abstract
Food adulteration detection requires quick and simple methods. Spectral detection can significantly reduce the analysis time, but it needs to construct a detection model. In this study, a one-class classification method based on an autoencoder is proposed for the detection of food adulteration by spectroscopy. In the proposed method, the autoencoder is constructed to extract low-dimensional features from high-dimensional spectral data and reconstruct the original spectrum. Then the coding error and reconstruction error are used to determine the food sample is adulterated or not. The infrared spectral data of milk powder and its adulterated forms are used to verify the performance of the proposed model. Experimental results show that the proposed method has similar effects to soft independent modeling of class analogy and one-class partial least squares, and is significantly better than support vector data description. The proposed method can be flexibly applied to the spectral detection of food adulteration.
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Affiliation(s)
- Guangzao Huang
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou 325035, China
| | - Lei-Ming Yuan
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou 325035, China
| | - Wen Shi
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou 325035, China
| | - Xi Chen
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou 325035, China
| | - Xiaojing Chen
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou 325035, China.
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15
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Ye Q, Meng X. Highly efficient authentication of edible oils by FTIR spectroscopy coupled with chemometrics. Food Chem 2022; 385:132661. [PMID: 35299015 DOI: 10.1016/j.foodchem.2022.132661] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 03/02/2022] [Accepted: 03/06/2022] [Indexed: 11/29/2022]
Abstract
A novel improved method for the authentication of edible oil samples based on Fourier-transform infrared (FTIR) spectroscopy coupled with chemometrics has been developed. A discrimination analysis model has been developed. On this basis, 100% correct classification of 135 samples from eleven species has been achieved. Recognition rates with respect to external validation for 91 pure oil samples and 231 blend samples were 100% and 92.6%, respectively. A general quantitative model for detecting edible oil adulteration (taking Camellia oil as an example) has also been built. An optimal backward interval partial least-squares model, based on the spectral regions ν = 3100-2900, 1800-1700, 1500-1400, and 1200-1100 cm-1, has been determined, giving good performances. A specific sub-model using a single adulterant oil has also been constructed, which showed higher prediction accuracy. Based on the developed qualitative and quantitative FTIR methods, adulterant oils in Camellia blends could be rapidly detected, effectively differentiated, and accurately quantified.
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Affiliation(s)
- Qin Ye
- Institute of Food Sciences, Zhejiang Academy of Agricultural Sciences, Hangzhou 310014, China
| | - Xianghe Meng
- College of Food Science and Technology, Zhejiang University of Technology, Deqing 313200, China.
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16
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De Géa Neves M, Poppi RJ, Breitkreitz MC. Authentication of plant-based protein powders and classification of adulterants as whey, soy protein, and wheat using FT-NIR in tandem with OC-PLS and PLS-DA models. Food Control 2022. [DOI: 10.1016/j.foodcont.2021.108489] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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17
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Pinto FG, Mahmud I, Rubio VY, Máquina ADV, Furtado Durans AF, Neto WB, Garrett TJ. Data-Driven Soft Independent Modeling of Class Analogy in Paper Spray Ionization Mass Spectrometry-Based Metabolomics for Rapid Detection of Prostate Cancer. Anal Chem 2022; 94:1925-1931. [DOI: 10.1021/acs.analchem.1c04004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Frederico G. Pinto
- Institute of Chemistry, Federal University of Viçosa, Campus de Rio Paranaíba, Rio Paranaíba, Minas Gerais 36570-900, Brazil
| | - Iqbal Mahmud
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, Florida 32610, United States
| | - Vanessa Y. Rubio
- Department of Chemistry, University of Florida, Gainesville, Florida 32603, United States
| | - Ademar Domingos Viagem Máquina
- Institute of Chemistry, Federal University of Uberlândia, Campus Santa Mônica, Uberlândia, Minas Gerais 38400-902, Brazil
| | - Anízia Fausta Furtado Durans
- Institute of Chemistry, Federal University of Uberlândia, Campus Santa Mônica, Uberlândia, Minas Gerais 38400-902, Brazil
| | - Waldomiro Borges Neto
- Institute of Chemistry, Federal University of Uberlândia, Campus Santa Mônica, Uberlândia, Minas Gerais 38400-902, Brazil
| | - Timothy J. Garrett
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, Florida 32610, United States
- Southeast Center for Integrated Metabolomics, Clinical and Translational Science Institute, University of Florida, Gainesville, Florida 32610, United States
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18
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Strojnik L, Potočnik D, Jagodic Hudobivnik M, Mazej D, Japelj B, Škrk N, Marolt S, Heath D, Ogrinc N. Geographical identification of strawberries based on stable isotope ratio and multi-elemental analysis coupled with multivariate statistical analysis: A Slovenian case study. Food Chem 2022; 381:132204. [PMID: 35114619 DOI: 10.1016/j.foodchem.2022.132204] [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: 10/12/2021] [Revised: 01/13/2022] [Accepted: 01/17/2022] [Indexed: 11/27/2022]
Abstract
The geographical classification and authentication of strawberries were attempted using discriminant and class-modelling methods applied to stable isotopes of light elements and elemental composition. The work involved creating a database of 92 authentic Slovenian strawberry samples and 32 imported samples. All samples were harvested between 2018 and 2020. A good geographical classification of Slovenian and non-Slovenian strawberries was obtained despite different production years using discriminant approaches. However, for verifying compliance with a given specification (geographical indications), a class-modelling approach was used to build an unbiased verification model. Class models generated by data-driven soft independent modelling of class analogy (DD-SIMCA) had high sensitivity (96% to 97%) and good specificity (81% to 91%) on a yearly basis, while a more generalised model combining total yearly data gave a lower specificity (63%). Of the 33 commercially available samples (test samples) with declared Slovenian origin, 39% were from outside of Slovenia.
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Affiliation(s)
- Lidija Strojnik
- Department of Environmental Sciences, Jožef Stefan Institute, Ljubljana 1000, Slovenia; Jožef Stefan International Postgraduate School, Ljubljana 1000, Slovenia.
| | - Doris Potočnik
- Department of Environmental Sciences, Jožef Stefan Institute, Ljubljana 1000, Slovenia; Jožef Stefan International Postgraduate School, Ljubljana 1000, Slovenia.
| | | | - Darja Mazej
- Department of Environmental Sciences, Jožef Stefan Institute, Ljubljana 1000, Slovenia.
| | | | - Nadja Škrk
- Administration for Food Safety, Veterinary Sector and Plant Protection, Ministry of Agriculture, Forestry and Food of the Republic of Slovenia, Ljubljana 1000, Slovenia.
| | - Suzana Marolt
- Administration for Food Safety, Veterinary Sector and Plant Protection, Ministry of Agriculture, Forestry and Food of the Republic of Slovenia, Ljubljana 1000, Slovenia.
| | - David Heath
- Department of Environmental Sciences, Jožef Stefan Institute, Ljubljana 1000, Slovenia.
| | - Nives Ogrinc
- Department of Environmental Sciences, Jožef Stefan Institute, Ljubljana 1000, Slovenia; Jožef Stefan International Postgraduate School, Ljubljana 1000, Slovenia.
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19
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Manuel MNB, da Silva AC, Lopes GS, Ribeiro LPD. One-class classification of special agroforestry Brazilian coffee using NIR spectrometry and chemometric tools. Food Chem 2021; 366:130480. [PMID: 34284192 DOI: 10.1016/j.foodchem.2021.130480] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Revised: 05/11/2021] [Accepted: 06/24/2021] [Indexed: 02/01/2023]
Abstract
The near-infrared spectrometry combined with the one-class classification method was applied as quality control of the agroforestry-grown specialty coffee. A total of 34 samples were analyzed in this study. Spectral data were obtained using a NIR portable and different pre-treatment strategies for baseline correction were evaluated. Unsupervised pattern recognition (PCA and HCA) techniques were performed. The construction of the classification model was carried out using the dd-SIMCA algorithm with 19 samples acquired directly from producers that are recognized for the best quality control of the specialty type coffee. In order to test the model, 15 samples of non-specialty type, obtained in local markets, were evaluated. The classification model with the highest correct classification rate (CCR) scored 100% and 87% in the validation and test groups, respectively. The results demonstrated that the application of this strategy was successful in verifying the authenticity of specialty type agroforestry-grown coffee samples.
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Affiliation(s)
- Monis Neves Baptista Manuel
- Núcleo Avançado de Tecnologias Analíticas (NATA), Universidade da Integração Internacional da Lusofonia Afro-brasileira (Unilab), Brazil
| | - Adenilton Camilo da Silva
- Laboratório de Estudos em Química Aplicada (LEQA), Departamento de Química Analítica e Físico-Química, Universidade Federal do Ceará (UFC), Brazil
| | - Gisele Simone Lopes
- Laboratório de Estudos em Química Aplicada (LEQA), Departamento de Química Analítica e Físico-Química, Universidade Federal do Ceará (UFC), Brazil
| | - Lívia Paulia Dias Ribeiro
- Núcleo Avançado de Tecnologias Analíticas (NATA), Universidade da Integração Internacional da Lusofonia Afro-brasileira (Unilab), Brazil.
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20
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Ferreira VHC, Hantao LW, Poppi RJ. Use of color based chromatographic images obtained from comprehensive two-dimensional gas chromatography in authentication analyses. Talanta 2021; 234:122616. [PMID: 34364425 DOI: 10.1016/j.talanta.2021.122616] [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: 03/12/2021] [Revised: 06/10/2021] [Accepted: 06/12/2021] [Indexed: 10/21/2022]
Abstract
Comprehensive two-dimensional gas chromatography (GC×GC) has been an important technique used to acquire as much information as possible from a wide variety of samples. Qualitative contour plots analysis provides useful information and in daily use it ends up being handled as images of the volatile organic compounds by analysts. Cachaça samples are used in this paper to showcase the use of two-dimensional chromatographic images as the main source for authentication purposes through one-class classifiers, such as data-driven soft independent modeling of class analogy (DD-SIMCA). The proposed workflow summarizes this fast and easy process, which can be used to certify a specific brand in comparison to other brands, as well as to authenticate if samples have been adulterated. Lower quality cachaças, non-aged cachaças and cachaças aged in different wooden barrels were tested as adulterants. Chromatographic images allowed for the distinction of all brands and nearly every adulteration tested. Sensitivity was estimated at 100% for all models and specificity ranged from 96% to 100%. Different approaches were used, alternating from working with whole-sized images to working with smaller resized versions of those images. Resized chromatographic images could be potentially useful to easily compensate for slight chromatographic misalignments, allowing for faster calculations and the use of simpler software. Reductions to 50% and 25% of the original size were tested and the results did not greatly differ from whole images model. As such, 2D chromatographic images have been found to be an interesting form of evaluating a product's authenticity.
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Affiliation(s)
- Victor H C Ferreira
- Institute of Chemistry, State University of Campinas, POB 6154, 13084-971, Campinas, SP, Brazil
| | - Leandro W Hantao
- Institute of Chemistry, State University of Campinas, POB 6154, 13084-971, Campinas, SP, Brazil.
| | - Ronei J Poppi
- Institute of Chemistry, State University of Campinas, POB 6154, 13084-971, Campinas, SP, Brazil.
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21
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Sanadgol Nezami M, Feizbakhsh A, Bagheri Garmarudi A. Detection of Soybean Powder and Rice Flour Adulterations in Premature Formula by ATR-FTIR Spectroscopy and Chemometrics. IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY, TRANSACTIONS A: SCIENCE 2021. [DOI: 10.1007/s40995-021-01072-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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22
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Mousa MAA, Wang Y, Antora SA, Al-Qurashi AD, Ibrahim OHM, He HJ, Liu S, Kamruzzaman M. An overview of recent advances and applications of FT-IR spectroscopy for quality, authenticity, and adulteration detection in edible oils. Crit Rev Food Sci Nutr 2021; 62:8009-8027. [PMID: 33977844 DOI: 10.1080/10408398.2021.1922872] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Authenticity and adulteration detection are primary concerns of various stakeholders, such as researchers, consumers, manufacturers, traders, and regulatory agencies. Traditional approaches for authenticity and adulteration detection in edible oils are time-consuming, complicated, laborious, and expensive; they require technical skills when interpreting the data. Over the last several years, much effort has been spent in academia and industry on developing vibrational spectroscopic techniques for quality, authenticity, and adulteration detection in edible oils. Among them, Fourier transforms infrared (FT-IR) spectroscopy has gained enormous attention as a green analytical technique for the rapid monitoring quality of edible oils at all stages of production and for detecting and quantifying adulteration and authenticity in edible oils. The technique has several benefits such as rapid, precise, inexpensive, and multi-analytical; hence, several parameters can be predicted simultaneously from the same spectrum. Associated with chemometrics, the technique has been successfully implemented for the rapid detection of adulteration and authenticity in edible oils. After presenting the fundamentals, the latest research outcomes in the last 10 years on quality, authenticity, and adulteration detection in edible oils using FT-IR spectroscopy will be highlighted and described in this review. Additionally, opportunities, challenges, and future trends of FT-IR spectroscopy will also be discussed.
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Affiliation(s)
- Magdi A A Mousa
- Department of Arid Land Agriculture, Faculty of Meteorology, Environment and Arid Land Agriculture, King Abdulaziz University, Jeddah, Saudi Arabia.,Department of Vegetables, Faculty of Agriculture, Assiut University, Assiut, Egypt
| | - Yangyang Wang
- School of Food Science, Henan Institute of Science and Technology, Xinxiang, China
| | - Salma Akter Antora
- Department of Biological Engineering, University of Missouri, Columbia, Missouri, USA
| | - Adel D Al-Qurashi
- Department of Arid Land Agriculture, Faculty of Meteorology, Environment and Arid Land Agriculture, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Omer H M Ibrahim
- Department of Arid Land Agriculture, Faculty of Meteorology, Environment and Arid Land Agriculture, King Abdulaziz University, Jeddah, Saudi Arabia.,Department of Ornamental Plants and Landscape Gardening, Faculty of Agriculture, Assiut University, Egypt
| | - Hong-Ju He
- School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, China
| | - Shu Liu
- Department of Environmental Science and Engineering, School of Space and Environment, Beihang University, Beijing, China
| | - Mohammed Kamruzzaman
- Department of Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
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23
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Si L, Ni H, Pan D, Zhang X, Xu F, Wu Y, Bao L, Wang Z, Xiao W, Wu Y. Nondestructive qualitative and quantitative analysis of Yaobitong capsule using near-infrared spectroscopy in tandem with chemometrics. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 252:119517. [PMID: 33578123 DOI: 10.1016/j.saa.2021.119517] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 01/16/2021] [Accepted: 01/19/2021] [Indexed: 06/12/2023]
Abstract
The purpose of the study is to present a nondestructive qualitative and quantitative approach of hard-shell capsule using near-infrared (NIR) spectroscopy combined with chemometrics. The Yaobitong capsule (YBTC) was used for demonstration of the proposed approach and the NIR spectra were collected using a handheld fiber probe (FP) without the damage of capsule shell. By comparing the differences and similarities of the NIR spectra of capsule shells, contents and intact capsules, a preliminary conclusion can be drawn that the NIR spectra contained the information of the contents. Characteristic variables were selected by competitive adaptive weighted resampling (CARS) method, and least squares support vector machine (LSSVM) method based on particle swarm optimization (PSO) algorithm was applied to the construction of quantitative models. The relative standard error of prediction (RSEP) values of five saponins including notoginsenoside R1, ginsenoside Rg1, Re, Rb1, and Rd were 3.240%, 5.468%, 5.303%, 5.043%, and 3.745%, respectively. In addition, for qualitative model, three different types of adulterated capsules were designed. The model established by data driven version of soft independent modeling of class analogy (DD-SIMCA) demonstrated a satisfactory result that all adulterated capsules were identified accurately after an appropriate number of principal components (PCs) were chosen. The results indicated that although the NIR spectra collection was affected by capsule shell, sufficient content information can be obtained for quantitative and qualitative analysis after combining with chemometrics. It further proved that acquired NIR spectra do contain the effective component information of the capsule. This study provided a reference for the rapid nondestructive quality analysis of traditional Chinese medicine (TCM) capsule without damaging capsule shell.
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Affiliation(s)
- Leting Si
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Hongfei Ni
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Dongyue Pan
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Xin Zhang
- Jiangsu Kanion Pharmaceutical Co., Ltd. Lianyungang, Jiangsu 222001, China; State Key Laboratory of New-tech for Chinese Medicine Pharmaceutical Process, Lianyungang, Jiangsu 222001, China; National & Local Joint Engineering Research Center on Intelligent Manufacturing of Traditional Chinese Medicine, Lianyungang, Jiangsu 222001, China
| | - Fangfang Xu
- Jiangsu Kanion Pharmaceutical Co., Ltd. Lianyungang, Jiangsu 222001, China; State Key Laboratory of New-tech for Chinese Medicine Pharmaceutical Process, Lianyungang, Jiangsu 222001, China; National & Local Joint Engineering Research Center on Intelligent Manufacturing of Traditional Chinese Medicine, Lianyungang, Jiangsu 222001, China
| | - Yun Wu
- Jiangsu Kanion Pharmaceutical Co., Ltd. Lianyungang, Jiangsu 222001, China; State Key Laboratory of New-tech for Chinese Medicine Pharmaceutical Process, Lianyungang, Jiangsu 222001, China; National & Local Joint Engineering Research Center on Intelligent Manufacturing of Traditional Chinese Medicine, Lianyungang, Jiangsu 222001, China
| | - Lewei Bao
- Jiangsu Kanion Pharmaceutical Co., Ltd. Lianyungang, Jiangsu 222001, China; State Key Laboratory of New-tech for Chinese Medicine Pharmaceutical Process, Lianyungang, Jiangsu 222001, China; National & Local Joint Engineering Research Center on Intelligent Manufacturing of Traditional Chinese Medicine, Lianyungang, Jiangsu 222001, China
| | - Zhenzhong Wang
- Jiangsu Kanion Pharmaceutical Co., Ltd. Lianyungang, Jiangsu 222001, China; State Key Laboratory of New-tech for Chinese Medicine Pharmaceutical Process, Lianyungang, Jiangsu 222001, China; National & Local Joint Engineering Research Center on Intelligent Manufacturing of Traditional Chinese Medicine, Lianyungang, Jiangsu 222001, China
| | - Wei Xiao
- Jiangsu Kanion Pharmaceutical Co., Ltd. Lianyungang, Jiangsu 222001, China; State Key Laboratory of New-tech for Chinese Medicine Pharmaceutical Process, Lianyungang, Jiangsu 222001, China; National & Local Joint Engineering Research Center on Intelligent Manufacturing of Traditional Chinese Medicine, Lianyungang, Jiangsu 222001, China.
| | - Yongjiang Wu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
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24
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Oliveri P, Malegori C, Mustorgi E, Casale M. Qualitative pattern recognition in chemistry: Theoretical background and practical guidelines. Microchem J 2021. [DOI: 10.1016/j.microc.2020.105725] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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25
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Identification and evaluation of Polygonatum kingianum with different growth ages based on data fusion strategy. Microchem J 2021. [DOI: 10.1016/j.microc.2020.105662] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
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26
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Comprehensive Review on Application of FTIR Spectroscopy Coupled with Chemometrics for Authentication Analysis of Fats and Oils in the Food Products. Molecules 2020; 25:molecules25225485. [PMID: 33238638 PMCID: PMC7700317 DOI: 10.3390/molecules25225485] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Revised: 11/18/2020] [Accepted: 11/20/2020] [Indexed: 11/16/2022] Open
Abstract
Currently, the authentication analysis of edible fats and oils is an emerging issue not only by producers but also by food industries, regulators, and consumers. The adulteration of high quality and expensive edible fats and oils as well as food products containing fats and oils with lower ones are typically motivated by economic reasons. Some analytical methods have been used for authentication analysis of food products, but some of them are complex in sampling preparation and involving sophisticated instruments. Therefore, simple and reliable methods are proposed and developed for these authentication purposes. This review highlighted the comprehensive reports on the application of infrared spectroscopy combined with chemometrics for authentication of fats and oils. New findings of this review included (1) FTIR spectroscopy combined with chemometrics, which has been used to authenticate fats and oils; (2) due to as fingerprint analytical tools, FTIR spectra have emerged as the most reported analytical techniques applied for authentication analysis of fats and oils; (3) the use of chemometrics as analytical data treatment is a must to extract the information from FTIR spectra to be understandable data. Next, the combination of FTIR spectroscopy with chemometrics must be proposed, developed, and standardized for authentication and assuring the quality of fats and oils.
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