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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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2
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Lorenzo ND, da Rocha RA, Papaioannou EH, Mutz YS, Tessaro LLG, Nunes CA. Feasibility of Using a Cheap Colour Sensor to Detect Blends of Vegetable Oils in Avocado Oil. Foods 2024; 13:572. [PMID: 38397549 PMCID: PMC10888341 DOI: 10.3390/foods13040572] [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: 12/28/2023] [Revised: 02/09/2024] [Accepted: 02/12/2024] [Indexed: 02/25/2024] Open
Abstract
This proof-of-concept study explored the use of an RGB colour sensor to identify different blends of vegetable oils in avocado oil. The main aim of this work was to distinguish avocado oil from its blends with canola, sunflower, corn, olive, and soybean oils. The study involved RGB measurements conducted using two different light sources: UV (395 nm) and white light. Classification methods, such as Linear Discriminant Analysis (LDA) and Least Squares Support Vector Machine (LS-SVM), were employed for detecting the blends. The LS-SVM model exhibited superior classification performance under white light, with an accuracy exceeding 90%, thus demonstrating a robust prediction capability without evidence of random adjustments. A quantitative approach was followed as well, employing Multiple Linear Regression (MLR) and LS-SVM, for the quantification of each vegetable oil in the blends. The LS-SVM model consistently achieved good performance (R2 > 0.9) in all examined cases, both for internal and external validation. Additionally, under white light, LS-SVM models yielded root mean square errors (RMSE) between 1.17-3.07%, indicating a high accuracy in blend prediction. The method proved to be rapid and cost-effective, without the necessity of any sample pretreatment. These findings highlight the feasibility of a cost-effective colour sensor in identifying avocado oil blended with other oils, such as canola, sunflower, corn, olive, and soybean oils, suggesting its potential as a low-cost and efficient alternative for on-site oil analysis.
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Affiliation(s)
- Natasha D. Lorenzo
- Department of Chemistry, Federal University of Lavras, P.O. Box 3037, Lavras 37203-202, MG, Brazil; (N.D.L.); (L.L.G.T.)
| | - Roney A. da Rocha
- Department of Food Science, Federal University of Lavras, P.O. Box 3037, Lavras 37203-202, MG, Brazil; (R.A.d.R.); (Y.S.M.)
| | | | - Yhan S. Mutz
- Department of Food Science, Federal University of Lavras, P.O. Box 3037, Lavras 37203-202, MG, Brazil; (R.A.d.R.); (Y.S.M.)
| | - Leticia L. G. Tessaro
- Department of Chemistry, Federal University of Lavras, P.O. Box 3037, Lavras 37203-202, MG, Brazil; (N.D.L.); (L.L.G.T.)
| | - Cleiton A. Nunes
- Department of Food Science, Federal University of Lavras, P.O. Box 3037, Lavras 37203-202, MG, Brazil; (R.A.d.R.); (Y.S.M.)
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3
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Coria‐Hernández J, Arjona‐Román JL, Meléndez‐Pérez R. Comparative study of conventional frying and air frying on the quality of potatoes ( Solanum tuberosum L.). Food Sci Nutr 2023; 11:6676-6685. [PMID: 37823140 PMCID: PMC10563671 DOI: 10.1002/fsn3.3617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 07/14/2023] [Accepted: 07/25/2023] [Indexed: 10/13/2023] Open
Abstract
The human being has historically consumed fried foods for centuries; however, conventional frying has a disadvantage, immersion in vegetable and/or animal oils, which leads to the search for different options. This is why air frying is a good alternative, which still has a wide field of study. In this work, frozen French fries of a brand marketed in Mexico that were subjected to frying in canola oil and air frying were compared. They were evaluated through the change in the removed moisture content, water activity, color profile, hardness, fracturability, and surface damage by SEM, thermal analysis by MDSC, and chemical by FTIR-ATR spectroscopy. Air-fried French fries were found to contain about 48% less moisture, fewer perceptible color changes, and less surface damage translated into better crunchiness compared with conventionally fried. It was also found that the changes at the chemical level are smaller, mainly attributed to the absence of canola oil and that the thermal transitions are more stable in terms of temperatures and enthalpies, which makes it possible to emphasize that air frying is a good alternative for developing new fried products that allow expanding the variety of these in the market without sacrificing some quality attributes.
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Affiliation(s)
- Jonathan Coria‐Hernández
- Laboratory 13 Thermal and Structural Analysis of Materials and FoodsNational Autonomous University of Mexico‐Superior Studies Faculty at Cuautitlan (UNAM–FESC) Campus 4Multidisciplinary Research UnitCuautitlan IzcalliMexico
| | - José Luis Arjona‐Román
- Laboratory 13 Thermal and Structural Analysis of Materials and FoodsNational Autonomous University of Mexico‐Superior Studies Faculty at Cuautitlan (UNAM–FESC) Campus 4Multidisciplinary Research UnitCuautitlan IzcalliMexico
| | - Rosalía Meléndez‐Pérez
- Laboratory 13 Thermal and Structural Analysis of Materials and FoodsNational Autonomous University of Mexico‐Superior Studies Faculty at Cuautitlan (UNAM–FESC) Campus 4Multidisciplinary Research UnitCuautitlan IzcalliMexico
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4
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Khodabakhshian R, Seyedalibeyk Lavasani H, Weller P. A methodological approach to preprocessing FTIR spectra of adulterated sesame oil. Food Chem 2023; 419:136055. [PMID: 37027973 DOI: 10.1016/j.foodchem.2023.136055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 03/03/2023] [Accepted: 03/26/2023] [Indexed: 04/08/2023]
Abstract
Fourier transform infrared (FTIR) spectroscopy is established as an effective and fast method for the confirmation of the authenticity of food and among other, edible oils. However, no standard procedure is available for applying preprocessing as a vital step in obtaining accurate results from spectra. This study proposes a methodological approach to preprocessing FTIR spectra of sesame oil adulterated with vegetable oils (canola oil, corn oil, and sunflower oil). The primary preprocessing methods investigated are orthogonal signal correction (OSC), standard normal variate transformation (SNV), and extended multiplicative scatter correction (EMSC). Other preprocessing methods are used both as standalone methods and in combination with the primary preprocessing methods. The preprocessing results are compared using partial least squares regression (PLSR). OSC alone or with detrending were the most accurate in predicting the adulteration level of sesame oil, with a maximum coefficient of prediction (R2p) range of 0.910 to 0.971 for different adulterants.
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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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Guo B, Zou Z, Huang Z, Wang Q, Qin J, Guo Y, Pan S, Wei J, Guo H, Zhu D, Su Z. A simple and green method for simultaneously determining the geographical origin and glycogen content of oysters using ATR–FTIR and chemometrics. J Food Compost Anal 2023. [DOI: 10.1016/j.jfca.2023.105229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2023]
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7
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Gonçalves TR, Galastri Teixeira G, Santos PM, Matsushita M, Valderrama P. Excitation-Emission matrices and PARAFAC in the investigation of the bioactive compound effects from the flavoring process in olive oils. Microchem J 2022. [DOI: 10.1016/j.microc.2022.108360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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8
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Kumar H, Ahuja A, Kadam AA, Rastogi VK, Negi YS. Antioxidant Film Based on Chitosan and Tulsi Essential Oil for Food Packaging. FOOD BIOPROCESS TECH 2022. [DOI: 10.1007/s11947-022-02938-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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9
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Li X, Wang D, Ma F, Yu L, Mao J, Zhang W, Jiang J, Zhang L, Li P. Rapid detection of sesame oil multiple adulteration using a portable Raman spectrometer. Food Chem 2022; 405:134884. [DOI: 10.1016/j.foodchem.2022.134884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 11/02/2022] [Accepted: 11/03/2022] [Indexed: 11/14/2022]
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Bian X, Wang Y, Wang S, Johnson JB, Sun H, Guo Y, Tan X. A Review of Advanced Methods for the Quantitative Analysis of Single Component Oil in Edible Oil Blends. Foods 2022; 11:foods11162436. [PMID: 36010436 PMCID: PMC9407567 DOI: 10.3390/foods11162436] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 08/04/2022] [Accepted: 08/11/2022] [Indexed: 12/21/2022] Open
Abstract
Edible oil blends are composed of two or more edible oils in varying proportions, which can ensure nutritional balance compared to oils comprising a single component oil. In view of their economical and nutritional benefits, quantitative analysis of the component oils in edible oil blends is necessary to ensure the rights and interests of consumers and maintain fairness in the edible oil market. Chemometrics combined with modern analytical instruments has become a main analytical technology for the quantitative analysis of edible oil blends. This review summarizes the different oil blend design methods, instrumental techniques and chemometric methods for conducting single component oil quantification in edible oil blends. The aim is to classify and compare the existing analytical techniques to highlight suitable and promising determination methods in this field.
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Affiliation(s)
- Xihui Bian
- School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China
- Shandong Provincial Key Laboratory of Olefin Catalysis and Polymerization, Shandong Chambroad Holding Group Co., Ltd., Binzhou 256500, China
- Correspondence: ; Tel./Fax: +86-22-83955663
| | - Yao Wang
- School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China
| | - Shuaishuai Wang
- Shandong Provincial Key Laboratory of Olefin Catalysis and Polymerization, Shandong Chambroad Holding Group Co., Ltd., Binzhou 256500, China
| | - Joel B. Johnson
- School of Health, Medical & Applied Sciences, Central Queensland University, Bruce Hwy, North Rockhampton, QLD 4701, Australia
| | - Hao Sun
- School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China
| | - Yugao Guo
- School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China
| | - Xiaoyao Tan
- School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China
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11
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Attia KAM, Serag A, Eid SM, Abbas AEF. A New Chemometrically Assisted UV Spectrophotometric Method for Simultaneous Determination of Tamsulosin and Dutasteride in Their Pharmaceutical Mixture. J AOAC Int 2022; 105:1755-1761. [PMID: 35758559 PMCID: PMC9384409 DOI: 10.1093/jaoacint/qsac080] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Revised: 06/03/2022] [Accepted: 06/19/2022] [Indexed: 11/23/2022]
Abstract
Background Tamsulosin (TAM) and dutasteride (DUT) are ranked among the most frequently prescribed therapies in urology. Interestingly, studies have also been carried out on TAM/DUT in terms of their ability to protect against recent COVID-19. However, very few studies were reported for their simultaneous quantification in their combined dosage form and were mainly based on chromatographic analysis. Subsequently, it is very important to offer a simple, selective, sensitive, and rapid method for the quantification of TAM and DUT in their challenging dosage form. Objective In this study, a new chemometrically assisted ultraviolet (UV) spectrophotometric method has been presented for the quantification of TAM and DUT without any prior separation. Method For the calibration set, a partial factorial experimental design was used, resulting in 25 mixtures with central levels of 20 and 25 μg/mL for TAM and DUT, respectively. In addition, to assess the predictive ability of the developed approaches, another central composite design of 13 samples was used as a validation set. Post-processing by chemometric analysis of the recorded zero-order UV spectra of these sets has been applied. These chemometric approaches include partial least-squares (PLS) and genetic algorithm (GA), as an effective variable selection technique, coupled with PLS. Results The models’ validation criteria displayed excellent recoveries and lower errors of prediction. Conclusions The proposed models were effectively used to determine TAM/DUT in their combined dosage form, and statistical comparison with the reported method revealed satisfactory results. Highlights Overall, this work presents powerful simple, selective, sensitive, and precise methods for simultaneous quantification of TAM/DUT in their dosage form with satisfactory results. The predictive ability and accuracy of the developed methods offer the opportunity to be employed as a quality control technique for the routine analysis of TAM/DUT when chromatographic instruments are not available.
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Affiliation(s)
- Khalid A M Attia
- Al-Azhar University, Faculty of Pharmacy, Pharmaceutical Analytical Chemistry Department , 11751 Nasr City , Cairo, Egypt
| | - Ahmed Serag
- Al-Azhar University, Faculty of Pharmacy, Pharmaceutical Analytical Chemistry Department , 11751 Nasr City , Cairo, Egypt
| | - Sherif M Eid
- October 6 University, Faculty of Pharmacy, Analytical Chemistry Department , 6 October City , Giza 12585, Egypt
| | - Ahmed Emad F Abbas
- October 6 University, Faculty of Pharmacy, Analytical Chemistry Department , 6 October City , Giza 12585, Egypt
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12
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Manzoor S, Masoodi F, Rashid R, Dar MM. Effect of apple pomace-based antioxidants on the stability of mustard oil during deep frying of French fries. Lebensm Wiss Technol 2022. [DOI: 10.1016/j.lwt.2022.113576] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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13
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Improving oxidative stability of soyabean oil by apple pomace extract during deep frying of french fries. FOOD BIOSCI 2022. [DOI: 10.1016/j.fbio.2022.101874] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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14
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Su N, Weng S, Wang L, Xu T. Reflectance Spectroscopy with Multivariate Methods for Non-Destructive Discrimination of Edible Oil Adulteration. BIOSENSORS 2021; 11:bios11120492. [PMID: 34940249 PMCID: PMC8699652 DOI: 10.3390/bios11120492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 11/23/2021] [Accepted: 11/25/2021] [Indexed: 11/16/2022]
Abstract
The visible and near-infrared (Vis-NIR) reflectance spectroscopy was utilized for the rapid and nondestructive discrimination of edible oil adulteration. In total, 110 samples of sesame oil and rapeseed oil adulterated with soybean oil in different levels were produced to obtain the reflectance spectra of 350–2500 nm. A set of multivariant methods was applied to identify adulteration types and adulteration rates. In the qualitative analysis of adulteration type, the support vector machine (SVM) method yielded high overall accuracy with multiple spectra pretreatments. In the quantitative analysis of adulteration rate, the random forest (RF) combined with multivariate scattering correction (MSC) achieved the highest identification accuracy of adulteration rate with the full wavelengths of Vis-NIR spectra. The effective wavelengths of the Vis-NIR spectra were screened to improve the robustness of the multivariant methods. The analysis results suggested that the competitive adaptive reweighted sampling (CARS) was helpful for removing the redundant information from the spectral data and improving the prediction accuracy. The PLSR + MSC + CARS model achieved the best prediction performance in the two adulteration cases of sesame oil and rapeseed oil. The coefficient of determination (RPcv2) and the root mean square error (RMSEPcv) of the prediction set were 0.99656 and 0.01832 in sesame oil adulterated with soybean oil, and the RPcv2 and RMSEPcv were 0.99675 and 0.01685 in rapeseed oil adulterated with soybean oil, respectively. The Vis-NIR reflectance spectroscopy with the assistance of multivariant analysis can effectively discriminate the different adulteration rates of edible oils.
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Affiliation(s)
- Ning Su
- Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China;
- Intelligent Agriculture Engineering Laboratory of Anhui Province, Hefei 230031, China
| | - Shizhuang Weng
- National Engineering Research Center for Agro-Ecological Big Data Analysis and Application, Anhui University, Hefei 230601, China;
| | - Liusan Wang
- Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China;
- Intelligent Agriculture Engineering Laboratory of Anhui Province, Hefei 230031, China
- Correspondence: (L.W.); (T.X.)
| | - Taosheng Xu
- Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China;
- Intelligent Agriculture Engineering Laboratory of Anhui Province, Hefei 230031, China
- Correspondence: (L.W.); (T.X.)
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Yang B, Chen C, Chen F, Chen C, Tang J, Gao R, Lv X. Identification of cumin and fennel from different regions based on generative adversarial networks and near infrared spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 260:119956. [PMID: 34049008 DOI: 10.1016/j.saa.2021.119956] [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: 01/27/2021] [Revised: 04/17/2021] [Accepted: 05/08/2021] [Indexed: 06/12/2023]
Abstract
Cumin (Cuminum cyminum) and fennel (Foeniculum vulgare) are widely used seasonings and play a very important role in industries such as breeding, cosmetics, winemaking, drug discovery, and nano-synthetic materials. However, studies have shown that cumin and fennel from different regions not only differ greatly in the content of lipids, phenols and proteins but also the substances contained in their essential oils are also different. Therefore, realizing precise identification of cumin and fennel from different regions will greatly help in quality control, market fraud and production industrialization. In this experiment, cumin and fennel samples were collected from each region, a total of 480 NIR spectra were collected. We used deep learning and traditional machine learning algorithms combined with near infrared (NIR) spectroscopy to identify their origin. To obtain the model with the best generalization performance and classification accuracy, we used principal component analysis (PCA) to reduce spectral data dimensionality after Rubberband baseline correction, and then established classification models including quadratic discriminant analysis based on PCA (PCA-QDA) and multilayer perceptron based on PCA (PCA-MLP). We also directly input the spectral data after baseline correction into convolutional neural networks (CNN) and generative adversarial networks (GAN). The experimental results show that GAN is more accurate than the PCA-QDA, PCA-MLP and CNN models, and the classification accuracy reached 100%. In the cumin and fennel classification experiment in the same region, the four models achieve great classification results from three regions under the condition that all model parameters remain unchanged. The experimental results show that when the training data are limited and the dimension is high, the model obtained by GAN using competitive learning has more generalization ability and higher classification accuracy. It also provides a new method for solving the problem of limited training data in food research and medical diagnosis in the future.
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Affiliation(s)
- Bo Yang
- College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China
| | - Cheng Chen
- College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China.
| | - Fangfang Chen
- College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China
| | - Chen Chen
- College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China
| | - Jun Tang
- Centre for Physical and Chemical Analysis, Xinjiang University, Urumqi 830046, China
| | - Rui Gao
- College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China
| | - Xiaoyi Lv
- College of Software, Xinjiang University, Urumqi 830046, Xinjiang, China; Key Laboratory of Signal Detection and Processing, Xinjiang University, Urumqi 830046, Xinjiang, China.
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16
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Salim YS, Rashid NA, Halim SIA, Chan CH, Ong CH, Harun MK. Fourier transform infrared (
FTIR)
authentication and batch‐to‐batch consistency for different types of paints using benchtop and handheld
FTIR
spectrophotometers for oil and gas industry. POLYM ENG SCI 2021. [DOI: 10.1002/pen.25746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Yoga Sugama Salim
- Faculty of Applied Sciences Universiti Teknologi MARA Shah Alam Selangor Malaysia
| | | | | | - Chin Han Chan
- Faculty of Applied Sciences Universiti Teknologi MARA Shah Alam Selangor Malaysia
| | - Chong Hup Ong
- Norimax Sdn Bhd Taman Perindustrian Puchong Puchong Selangor Malaysia
| | - Mohamad Kamal Harun
- Faculty of Applied Sciences Universiti Teknologi MARA Shah Alam Selangor Malaysia
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17
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Ahmad MH, Shahbaz Z, Imran M, Khan MK, Muhammad N, Iqbal S, Ahmed W, Ahmad T. Monitoring of frying process in canola oil blend using fourier transform infrared and chemometrics techniques. Food Sci Nutr 2021; 9:6089-6098. [PMID: 34760240 PMCID: PMC8565206 DOI: 10.1002/fsn3.2558] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 08/20/2021] [Accepted: 08/22/2021] [Indexed: 12/02/2022] Open
Abstract
The production of trans-fats and chemical changes during the process of frying are serious public health concerns and must be monitored efficiently. For this purpose, the canola oil was formulated with different ratio of extra virgin olive oil and palm olein using D-optimal mixture design, and the best formulation (67:22:11) based on free fatty acid (FFA) content, peroxide value (PV), and iodine value (IV) as responses was selected for multiple frying process. The data on FFA, PV, and IV along with Fourier transform-infrared (FT-IR) spectra were taken after each frying up to ten frying. The spectral data were preprocessed with standard normal variate followed by principal component analysis which is clearly showing the differentiation for various frying. Similarly, partial least square regression was applied to predict the FFA (0.37%-1.63%), PV (4.47-13.85 meqO2/kg), and IV (111.51-51.39 I2/100 g) which demonstrated high coefficient of determination (R2) 0.84, 0.83, and 0.81, respectively. It can be summarized that FT-IR can be used as a novel tool for fast and noninvasive quality determination of frying oils.
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Affiliation(s)
- Muhammad Haseeb Ahmad
- Department of Food ScienceFaculty of Life SciencesGovernment College UniversityFaisalabadPakistan
| | - Zainab Shahbaz
- Department of Food ScienceFaculty of Life SciencesGovernment College UniversityFaisalabadPakistan
| | - Muhammad Imran
- Department of Food ScienceFaculty of Life SciencesGovernment College UniversityFaisalabadPakistan
| | - Muhammad Kamran Khan
- Department of Food ScienceFaculty of Life SciencesGovernment College UniversityFaisalabadPakistan
| | - Niaz Muhammad
- National Agriculture Education CollegeKabulAfghanistan
| | - Sanaullah Iqbal
- Department of Food Science and Human NutritionFaculty of Bio‐SciencesUniversity of Veterinary & Animal SciencesLahorePakistan
| | - Waqas Ahmed
- Department of Food Science and Human NutritionFaculty of Bio‐SciencesUniversity of Veterinary & Animal SciencesLahorePakistan
| | - Tanvir Ahmad
- Department of StatisticsFaculty of Physical SciencesGovernment College UniversityFaisalabadPakistan
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Yang X, Ou Q, Qian K, Yang J, Bai Z, Yang W, Shi Y, Liu G. Diagnosis of Lung Cancer by ATR-FTIR Spectroscopy and Chemometrics. Front Oncol 2021; 11:753791. [PMID: 34660320 PMCID: PMC8515056 DOI: 10.3389/fonc.2021.753791] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 09/15/2021] [Indexed: 01/06/2023] Open
Abstract
Lung cancer is the leading cause of cancer-related death in the world. Early diagnosis has great significance for the survival of patients with lung cancer. In this paper, attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy combined with chemometrics was used to study the serum samples from patients with lung cancer and healthy people. The results of spectral band area comparison showed that the concentrations of protein, lipid and nucleic acids molecules in serum of patients with lung cancer were increased compared with those in healthy people. The original spectra were preprocessed to improve the accuracy of principal component regression (PCR) and partial least squares-discriminant analysis (PLS-DA) models. PLS-DA results for first derivative spectral data in nucleic acids (1250-1000cm-1) band showed 80% sensitivity, 91.89% specificity and 87.10% accuracy with highR c 2 of 0.8949 andR v 2 of 0.8153, low RMSEC of 0.3136 and RMSEV of 0.4180. It is shown that ATR-FTIR spectroscopy combined with chemometrics might be developed as a simple method for clinical screening and diagnosis of lung cancer.
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Affiliation(s)
- Xien Yang
- School of Physics and Electronic Information, Yunnan Normal University, Kunming, China
| | - Quanhong Ou
- School of Physics and Electronic Information, Yunnan Normal University, Kunming, China
| | - Kai Qian
- Department of Thoracic Surgery, The First People’s Hospital of Yunnan Province, Kunming, China
| | - Jianru Yang
- Department of Clinical Laboratory, Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Zhixun Bai
- Department of Internal Medicine, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Weiye Yang
- School of Physics and Electronic Information, Yunnan Normal University, Kunming, China
| | - Youming Shi
- School of Physics and Electronic Engineering, Qujing Normal University, Qujing, China
| | - Gang Liu
- School of Physics and Electronic Information, Yunnan Normal University, Kunming, China
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19
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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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20
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Yan H, Pu Z, Wang Y, Guo S, Wang T, Li S, Zhang Z, Zhou G, Zhan Z, Duan J. Rapid qualitative identification and quantitative analysis of Flos Mume based on Fourier transform near infrared spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 249:119344. [PMID: 33360057 DOI: 10.1016/j.saa.2020.119344] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Revised: 12/09/2020] [Accepted: 12/10/2020] [Indexed: 06/12/2023]
Abstract
Flos Mume, an ancient Chinese plant, is widely used for food and medicine. There are numerous varieties of Flos Mume, whose main active components are chlorogenic acid, hyperoside and isoquercitrin. Currently, Flos Mume varieties are mainly distinguished by physical appearance and they have not been scientifically indexed for identification. Fourier transform near infrared spectroscopy (FT-NIR) is a technique that when combined with chemometrics, determines internal components of samples and classifies them. Here, to distinguish between different Flos Mume varieties, we used a qualitative identification model based on FT-NIR. Various model parameters indicated its stability and high predictive performance. We developed a rapid, non-destructive method of simultaneously analyzing 8 components but found that only neochlorogenic acid, chlorogenic acid, rutin, hyperoside, and isoquercitrin have application value. Other components were excluded due to low concentration and poor prediction. Chemometric analysis found that chlorogenic acid become an ingredient which is quite different in the different categories. The content of chlorogenic acid were the highest among these components. Different varieties of Flos Mume were distinguished based on chlorogenic acid content, indicating that chlorogenic acid has potential to become a key indicator for application in quality evaluation. The established FT-NIR model for chlorogenic acid detection had excellent predictive capacity. FT-NIR was the first time applied to Flos Mume and our findings offer theoretical reference for the rapid identification and quantitative analysis of Flos Mume based on FT-NIR. Flos Mume could be evaluated for quality quickly and easily by means of FT-NIR spectroscopy.
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Affiliation(s)
- Hui Yan
- Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, and Jiangsu Key Laboratory for High Technology Research of TCM Formulae, and National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu Province, China.
| | - Zongjin Pu
- Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, and Jiangsu Key Laboratory for High Technology Research of TCM Formulae, and National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu Province, China.
| | - Yingjun Wang
- Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, and Jiangsu Key Laboratory for High Technology Research of TCM Formulae, and National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu Province, China.
| | - Sheng Guo
- Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, and Jiangsu Key Laboratory for High Technology Research of TCM Formulae, and National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu Province, China.
| | - Tianshu Wang
- Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, and Jiangsu Key Laboratory for High Technology Research of TCM Formulae, and National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu Province, China.
| | - Simeng Li
- Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, and Jiangsu Key Laboratory for High Technology Research of TCM Formulae, and National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu Province, China.
| | - Zhenyu Zhang
- Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, and Jiangsu Key Laboratory for High Technology Research of TCM Formulae, and National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu Province, China.
| | - Guisheng Zhou
- Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, and Jiangsu Key Laboratory for High Technology Research of TCM Formulae, and National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu Province, China.
| | - Zhilai Zhan
- State Key Laboratory of Dao-di Herbs Breeding Base, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China.
| | - Jinao Duan
- Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, and Jiangsu Key Laboratory for High Technology Research of TCM Formulae, and National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu Province, China.
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21
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Meenu M, Decker EA, Xu B. Application of vibrational spectroscopic techniques for determination of thermal degradation of frying oils and fats: a review. Crit Rev Food Sci Nutr 2021; 62:5744-5765. [PMID: 33645344 DOI: 10.1080/10408398.2021.1891520] [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] [Indexed: 10/22/2022]
Abstract
Deep fried foods are popular among consumers due to their unique taste and texture. During the process of deep-frying, oil is subjected to a high temperature that results into the generation of harmful compounds. The repeated usage of frying oil is a common exercise and associated with various health hazards. Thus, determination of frying oil quality is a critical practice to follow. The chemical methods employed to determine the quality of frying oil are destructive and require large amount of harmful chemical, thus researchers are exploring the application of various vibrational spectroscopic techniques for this purpose. The first part of this review provides a detailed insight into fundamental theoretical aspects of two main vibrational spectroscopic techniques (infrared and Raman spectroscopy) and chemical alteration in frying oils under thermal stress. While in the following parts, the application of near-infrared (NIR) and Fourier transform infrared (FTIR) and Raman spectroscopy for evaluating the quality of various frying oils and fats under thermal stress has been discussed. It is anticipated that this review paper can serve as a reference source for impending research in this field.
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Affiliation(s)
- Maninder Meenu
- Food Science and Technology Program, BNU-HKBU United International College, Zhuhai, China
| | - Eric A Decker
- Department of Food Science, University of Massachusetts Amherst, Amherst, MA, USA
| | - Baojun Xu
- Food Science and Technology Program, BNU-HKBU United International College, Zhuhai, China
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22
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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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23
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Mansoldo FRP, Cardoso VDS, Neves Junior A, Cedrola SML, Maricato V, Rosa MDSS, Vermelho AB. Quantification of schizophyllan directly from the fermented broth by ATR-FTIR and PLS regression. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2020; 12:5468-5475. [PMID: 33141124 DOI: 10.1039/d0ay01585g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Non-destructive methods that allow the quantification of bioproducts in a simple and quick manner during fermentation are extremely desirable from a practical point of view. Therefore, a 9 day fermentation experiment with Schizophyllum commune was carried out to investigate the possibility of using ATR-FTIR to quantify the schizophyllan biopolymer (SPG) directly from the culture medium. On each day, aliquots of the fermentation were taken, and the cell-free supernatant was analyzed by ATR-FTIR. The main objective of this step was to evaluate whether FTIR would be able to detect the appearance of specific peaks related to the production of SPG. The results of the PCA analysis showed that there was a reasonable separation of the days through the FTIR spectra. Then PCA-LDA was applied to the same dataset, which confirmed the formation of groups for each day of fermentation, after which, a calibration and test set was developed. Through a matrix generated by an experimental design with 2 factors and 5 levels, 25 samples were created with variations in the concentration of the culture medium and SPG. The ATR-FTIR spectra of this data set were modeled using PLS regression with backward selection of predictors. The results revealed that the amount of SPG produced can be quantified directly in the culture medium with excellent precision with R2CV = 0.951, R2P = 0.970, RMECV = 0.205 g, RMSEP = 0.170 g, RPDcv = 4.53 and RPDp = 5.88. The traditional method to quantify SPG is time consuming, requires several steps and uses solvents. In contrast, the method proposed in this work is a viable, faster, and a simpler alternative, which does not use reagents and does not require extensive pre-treatment of the samples.
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Affiliation(s)
- Felipe Raposo Passos Mansoldo
- Federal University of Rio de Janeiro (UFRJ), Institute of Microbiology Paulo de Góes, BIOINOVAR - Biocatalysis, Bioproducts and Bioenergy, Rio de Janeiro, Brazil.
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