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Guo M, Lin H, Wang K, Cao L, Sui J. Data fusion of near-infrared and Raman spectroscopy: An innovative tool for non-destructive prediction of the TVB-N content of salmon samples. Food Res Int 2024; 189:114564. [PMID: 38876596 DOI: 10.1016/j.foodres.2024.114564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Revised: 05/21/2024] [Accepted: 05/26/2024] [Indexed: 06/16/2024]
Abstract
Total volatile basic nitrogen (TVB-N) serves as a crucial indicator for evaluating the freshness of salmon. This study aimed to achieve accurate and non-destructive prediction of TVB-N content in salmon fillets stored in multiple temperature settings (-20, 0, -4, 20 °C, and dynamic temperature) using near-infrared (NIR) and Raman spectroscopy. A partial least square support vector machine (LSSVM) regression model was established through the integration of NIR and Raman spectral data using low-level data fusion (LLDF) and mid-level data fusion (MLDF) strategies. Notably, compared to a single spectrum analysis, the LLDF approach provided the most accurate prediction model, achieving an R2P of 0.910 and an RMSEP of 1.922 mg/100 g. Furthermore, MLDF models based on 2D-COS and VIP achieved R2P values of 0.885 and 0.906, respectively. These findings demonstrated the effectiveness of the proposed method for precise quantitative detection of salmon TVB-N, laying a technical foundation for the exploration of similar approaches in the study of other meat products. This approach has the potential to assess and monitor the freshness of seafood, ensuring consumer safety and enhancing product quality.
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Affiliation(s)
- Minqiang Guo
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong 266003, China; College of Food Science and Engineering, Xinjiang Institute of Technology, Aksu, Xinjiang 843100, China
| | - Hong Lin
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong 266003, China
| | - Kaiqiang Wang
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong 266003, China.
| | - Limin Cao
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong 266003, China
| | - Jianxin Sui
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong 266003, China
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2
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Foli LP, Hespanhol MC, Cruz KAML, Pasquini C. Miniaturized Near-Infrared spectrophotometers in forensic analytical science - a critical review. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 315:124297. [PMID: 38640625 DOI: 10.1016/j.saa.2024.124297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 04/13/2024] [Accepted: 04/14/2024] [Indexed: 04/21/2024]
Abstract
The advent of miniaturized NIR instruments, also known as compact, portable, or handheld, is revolutionizing how technology can be employed in forensics. In-field analysis becomes feasible and affordable with these new instruments, and a series of methods has been developed to provide the police and official agents with objective, easy-to-use, tailored, and accurate qualitative and quantitative forensic results. This work discusses the main aspects and presents a comprehensive and critical review of compact NIR spectrophotometers associated with analytical protocols to produce information on forensic matters.
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Affiliation(s)
- Letícia P Foli
- Grupo de Análise e Educação para a Sustentabilidade, Departamento de Química, Centro de Ciências Exatas e Tecnológicas, Universidade Federal de Viçosa, Av. P. H. Rolfs, s/n, Viçosa, MG, 36570-900, Brazil
| | - Maria C Hespanhol
- Grupo de Análise e Educação para a Sustentabilidade, Departamento de Química, Centro de Ciências Exatas e Tecnológicas, Universidade Federal de Viçosa, Av. P. H. Rolfs, s/n, Viçosa, MG, 36570-900, Brazil
| | - Kaíque A M L Cruz
- Grupo de Análise e Educação para a Sustentabilidade, Departamento de Química, Centro de Ciências Exatas e Tecnológicas, Universidade Federal de Viçosa, Av. P. H. Rolfs, s/n, Viçosa, MG, 36570-900, Brazil
| | - Celio Pasquini
- Instituto de Química, Universidade Estadual de Campinas (UNICAMP), Rua Monteiro Lobato, 290, Campinas, SP 13083-862, Brazil.
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3
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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. [PMID: 38899503 DOI: 10.1039/d4ay00562g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [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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4
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Uçar B, Gholami Z, Svobodová K, Hradecká I, Hönig V. A Comprehensive Study for Determination of Free Fatty Acids in Selected Biological Materials: A Review. Foods 2024; 13:1891. [PMID: 38928832 PMCID: PMC11203194 DOI: 10.3390/foods13121891] [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: 05/17/2024] [Revised: 06/13/2024] [Accepted: 06/14/2024] [Indexed: 06/28/2024] Open
Abstract
The quality of oil is highly dependent on its free fatty acid (FFA) content, especially due to increased restrictions on renewable fuels. As a result, there has been a growing interest in free fatty acid determination methods over the last few decades. While various standard methods are currently available, such as the American Oil Chemists Society (AOCS), International Union of Pure and Applied Chemistry (IUPAC), and Japan Oil Chemists' Society (JOCS), to obtain accurate results, there is a pressing need to investigate a fast, accurate, feasible, and eco-friendly methodology for determining FFA in biological materials. This is owing to inadequate characteristics of the methods, such as solvent consumption and reproducibility, among others. This study aims to investigate FFA determination methods to identify suitable approaches and introduce a fresh perspective.
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Affiliation(s)
- Beyza Uçar
- ORLEN UniCRE a.s., Revoluční 1521/84, 400 01 Ústí nad Labem, Czech Republic; (Z.G.); (I.H.)
| | - Zahra Gholami
- ORLEN UniCRE a.s., Revoluční 1521/84, 400 01 Ústí nad Labem, Czech Republic; (Z.G.); (I.H.)
| | - Kateřina Svobodová
- ORLEN UniCRE a.s., Revoluční 1521/84, 400 01 Ústí nad Labem, Czech Republic; (Z.G.); (I.H.)
- Department of Chemistry, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Kamýcká 129, 165 00 Prague, Czech Republic;
| | - Ivana Hradecká
- ORLEN UniCRE a.s., Revoluční 1521/84, 400 01 Ústí nad Labem, Czech Republic; (Z.G.); (I.H.)
- Department of Chemistry, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Kamýcká 129, 165 00 Prague, Czech Republic;
| | - Vladimír Hönig
- Department of Chemistry, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Kamýcká 129, 165 00 Prague, Czech Republic;
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5
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Carolina Souza Andrada Anconi A, de Jesus Fonseca JL, Antônio Nunes C. A digital image-based colorimetric method for measuring free acidity in edible vegetable oils. Food Chem 2024; 443:138555. [PMID: 38281417 DOI: 10.1016/j.foodchem.2024.138555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 01/12/2024] [Accepted: 01/21/2024] [Indexed: 01/30/2024]
Abstract
The standard method used to quantify free acidity (FA) in vegetable oil is neutralization titration, which requires many toxic chemicals and depends on an analyst's experience in detecting endpoints. Here, a digital image colorimetry (DIC) method using a smartphone camera was developed to measure FA in vegetable oils. A cupric acetate solution was used to produce the colorimetric reaction. The coloured solutions were imaged, and R values (from the RGB colour system) were calibrated against the respective FAs in the standards. The FA values of the samples were determined by standard addition calibration. These results were compared to measurements of FA obtained by the standard titrimetric method. An excellent correlation was obtained, with an R2 of 0.98 and a mean absolute error of 0.06%. The chemicals needed for analysis were reduced by approximately 90%. Thus, DIC is a less subjective and more economical method for determining FA in vegetable oils.
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Affiliation(s)
| | - Júlia Letícia de Jesus Fonseca
- Department of Food Science, Federal University of Lavras, University Campus, Post Office Box 3037, 37200-900, Lavras, Minas Gerais, Brazil
| | - Cleiton Antônio Nunes
- Department of Food Science, Federal University of Lavras, University Campus, Post Office Box 3037, 37200-900, Lavras, Minas Gerais, Brazil.
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6
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Duchateau C, Stévigny C, De Braekeleer K, Deconinck E. Characterization of CBD oils, seized on the Belgian market, using infrared spectroscopy: Matrix identification and CBD determination, a proof of concept. Drug Test Anal 2024; 16:537-551. [PMID: 37793648 DOI: 10.1002/dta.3583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 09/04/2023] [Accepted: 09/17/2023] [Indexed: 10/06/2023]
Abstract
The availability of cannabidiol (CBD) oil products has increased in recent years. No analytical controls are mandatory for these products leading to uncertainties about composition and quality. In this paper, a methodology was developed to identify the oil matrix and to estimate the CBD content in such samples, using mid-infrared and near-infrared spectroscopy. Different oils were selected based on the information labeled on products and were bought in food stores in order to create a sample set with a variety of matrices. These oils were spiked with CBD to obtain samples with CBD levels from 0% to 20%. The first part of the study was focused on the qualitative analysis of the oil matrix. A classification model, based on Soft Independent Modeling of Class Analogy, was build using the spiked oils to distinguish between the different oil matrices. For both spectroscopic techniques, the sensitivity, the specificity, the accuracy and the precision were equal to 100%. These models were applied to determine the oil matrix of seized samples. The second part of the study was focused on the quantitative estimation of CBD. After determination of CBD in seized samples using gas chromatography-tandem mass spectrometry, partial least square regression (PLS-R) models were built, one for each matrix in the sample set. Both techniques were able to classify unknown oily samples according to their matrix, and although only few samples were available to evaluate the PLS-R models, the approach clearly showed promising results for the estimation of the CBD content in oil samples.
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Affiliation(s)
- Céline Duchateau
- Pharmacognosy, Bioanalysis and Drug Discovery Unit, RD3, Faculty of Pharmacy, ULB, Brussels, Belgium
- Medicines and Health Products, Scientific Direction Physical and Chemical Health Risks, Sciensano, Brussels, Belgium
| | - Caroline Stévigny
- Pharmacognosy, Bioanalysis and Drug Discovery Unit, RD3, Faculty of Pharmacy, ULB, Brussels, Belgium
| | - Kris De Braekeleer
- Pharmacognosy, Bioanalysis and Drug Discovery Unit, RD3, Faculty of Pharmacy, ULB, Brussels, Belgium
| | - Eric Deconinck
- Pharmacognosy, Bioanalysis and Drug Discovery Unit, RD3, Faculty of Pharmacy, ULB, Brussels, Belgium
- Medicines and Health Products, Scientific Direction Physical and Chemical Health Risks, Sciensano, Brussels, Belgium
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7
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Hwang J, Choi KO, Jeong S, Lee S. Machine learning identification of edible vegetable oils from fatty acid compositions and hyperspectral images. Curr Res Food Sci 2024; 8:100742. [PMID: 38708100 PMCID: PMC11066601 DOI: 10.1016/j.crfs.2024.100742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 04/05/2024] [Accepted: 04/17/2024] [Indexed: 05/07/2024] Open
Abstract
Hyperspectral imaging analysis combined with machine learning was applied to identify eight edible vegetable oils, and its classification performance was compared with the chemical method based on fatty acid compositions. Furthermore, the degree of adulteration in vegetable oils was quantitatively investigated using machine learning-enabled hyperspectral approaches. The hyperspectral absorbance spectra of palm oil with a high degree of saturation were distinctly different from those of the other liquid oils. The flaxseed and olive oils exhibited the dominant hyperspectral intensities at 1170/1671 and 1212/1415 nm, respectively. Linear discriminant analysis demonstrated that two linear discriminants could explain a significant portion of the total variability, accounting for 96.0% (fatty acid compositions) and 98.9% (hyperspectral images). When the hyperspectral results were used as datasets for three machine learning models (decision tree, random forest, and k-nearest neighbor), several instances to incorrectly classify grapeseed and sunflower oils were detected, while olive, palm, and flaxseed oils were successfully identified. The machine learning models showed a great classification performance that exceeded 98.9% from the hyperspectral images of the vegetable oils, which was comparable to the fatty acid composition-based chemical method in identifying edible vegetable oils. In addition, the random forest model was the most effective in ascertaining adulteration levels in binary oil blends (R2 > 0.992 and RMSE < 2.75).
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Affiliation(s)
- Jeongin Hwang
- Department of Food Science and Biotechnology, Seoul, 05006, South Korea
| | - Kyeong-Ok Choi
- Department of Food Science and Technology, Chungnam National University, Daejeon, 34134, South Korea
| | - Sungmin Jeong
- Carbohydrate Bioproduct Research Center, Sejong University, Seoul, 05006, South Korea
| | - Suyong Lee
- Department of Food Science and Biotechnology, Seoul, 05006, South Korea
- Carbohydrate Bioproduct Research Center, Sejong University, Seoul, 05006, South Korea
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8
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Bian X, Liu Y, Zhang R, Sun H, Liu P, Tan X. Rapid quantification of grapeseed oil multiple adulterations using near-infrared spectroscopy coupled with a novel double ensemble modeling method. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 311:124016. [PMID: 38354676 DOI: 10.1016/j.saa.2024.124016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 02/04/2024] [Accepted: 02/07/2024] [Indexed: 02/16/2024]
Abstract
As a high-quality edible oil, grapeseed oil is often adulterated with low-price/quality vegetable oils. A novel ensemble modeling method is proposed for quantitative analysis of grapeseed oil adulterations combined with near-infrared (NIR) spectroscopy. The method combines Monte Carlo (MC) sampling and whale optimization algorithm (WOA) to build numerous partial least squares (PLS) sub-models, named MC-WOA-PLS. A total of 80 adulterated grapeseed oil samples were prepared by mixing grapeseed oil with soybean oil, palm oil, cottonseed oil, and corn oil with the designed mass percentages. NIR spectra of the 80 samples were measured in a transmittance mode in the range of 12,000-4000 cm-1. Parameters in MC-WOA-PLS including the number of latent variables (LVs) in PLS, iteration number of WOA, whale number, number of PLS sub-models, and percentage of training subsets were optimized. To validate the prediction performance of the model, root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV), root mean squared error of prediction (RMSEP), correlation coefficient (R), residual predictive deviation (RPD), and standard deviation (S.D.) were used. Compared with PLS, standard normal variate-PLS (SNV-PLS), uninformative variable elimination-PLS (UVE-PLS), Monte Carlo uninformative variable elimination-PLS (MCUVE-PLS), randomization test-PLS (RT-PLS), variable importance in projection-PLS (VIP-PLS), and WOA-PLS, MC-WOA-PLS achieves the best prediction accuracy and stability for quantification of the five pure oils in adulterated grapeseed oil samples.
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Affiliation(s)
- Xihui Bian
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, PR China; NMPA Key Laboratory for Technology Research and Evaluation of Drug Products, Shandong University, Jinan 250012, PR China.
| | - Yuxia Liu
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, PR China
| | - Rongling Zhang
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, PR China
| | - Hao Sun
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, PR China
| | - Peng Liu
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, PR China
| | - Xiaoyao Tan
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, PR China
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9
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Zhao Y, Zhu Y, Li C, Chen G, Yao Y. Fast analysis of straw proximates based on partial least squares using near-infrared spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 309:123855. [PMID: 38217989 DOI: 10.1016/j.saa.2024.123855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 12/15/2023] [Accepted: 01/04/2024] [Indexed: 01/15/2024]
Abstract
Near-infrared spectroscopy (NIRS) is a rapid measurement technique based on the spectroscopic absorption bands of specific functional groups within biomass. Its main advantages include simple preparation, precise analysis, and the ability to analyze multiple components simultaneously. Fast analysis of straw proximates (moisture, ash, and fixed carbon) has been investigated by means of NIRS. A total of 144 samples were collected, the spectral data were analyzed by partial least squares (PLS) regression and support vector regression (SVR) with four wavelength selection methods. PLS combined with competitive adaptive reweighted sampling (CARS) provided excellent predictive performance for moisture, ash, and fixed carbon. For moisture prediction, the values of RP2, RMSEP and RPD were 0.7202, 0.8196, and 2.11, respectively. For ash prediction, the values of RP2, RMSEP and RPD were 0.9307, 0.5901, and 3.69, respectively. For fixed carbon prediction, the values of RP2, RMSEP and RPD were 0.8504, 0.2735, and 2.76, respectively. Fast analysis of proximates of corn stover was possible using this NIRS system.
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Affiliation(s)
- Yifan Zhao
- Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
| | - Yingying Zhu
- Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China.
| | - Chaoran Li
- Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
| | - Geng Chen
- Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
| | - Yan Yao
- College of Metrology & Measurement Engineering, China Jiliang University, Hangzhou 310018, China.
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10
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Guo M, Wang K, Lin H, Wang L, Cao L, Sui J. Spectral data fusion in nondestructive detection of food products: Strategies, recent applications, and future perspectives. Compr Rev Food Sci Food Saf 2024; 23:e13301. [PMID: 38284587 DOI: 10.1111/1541-4337.13301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 11/27/2023] [Accepted: 12/31/2023] [Indexed: 01/30/2024]
Abstract
In recent years, the food industry has shown a growing interest in the development of rapid and nondestructive analytical methods. However, the utilization of a solitary nondestructive detection technique offers only a constrained extent of physical or chemical insights regarding the sample under examination. To overcome this limitation, the amalgamation of spectroscopy with data fusion strategies has emerged as a promising approach. This comprehensive review delves into the fundamental principles and merits of low-level, mid-level, and high-level data fusion strategies within the domain of food analysis. Various data fusion techniques encompassing spectra-to-spectra, spectra-to-machine vision, spectra-to-electronic nose, and spectra-to-nuclear magnetic resonance are summarized. Moreover, this review also provides an overview of the latest applications of spectral data fusion techniques (SDFTs) for classification, adulteration, quality evaluation, and contaminant detection within the purview of food safety analysis. It also addresses current challenges and future prospects associated with SDFTs in real-world applications. Despite the extant technical intricacy, the ongoing evolution of online data fusion platforms and the emergence of smartphone-based multi-sensor fusion detection technology augur well for the pragmatic realization of SDFTs, endowing them with formidable capabilities for both qualitative and quantitative analysis in the realm of food analysis.
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Affiliation(s)
- Minqiang Guo
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong, China
- College of Food Science and Engineering, Xinjiang Institute of Technology, Aksu, Xinjiang, China
| | - Kaiqiang Wang
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong, China
| | - Hong Lin
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong, China
| | - Lei Wang
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong, China
| | - Limin Cao
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong, China
| | - Jianxin Sui
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong, China
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11
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Bian X, Zhao Z, Liu J, Liu P, Shi H, Tan X. Discretized butterfly optimization algorithm for variable selection in the rapid determination of cholesterol by near-infrared spectroscopy. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2023; 15:5190-5198. [PMID: 37779476 DOI: 10.1039/d3ay01636f] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/03/2023]
Abstract
The blood cholesterol level is strongly associated with cardiovascular disease. It is necessary to develop a rapid method to determine the cholesterol concentration of blood. In this study, a discretized butterfly optimization algorithm-partial least squares (BOA-PLS) method combined with near-infrared (NIR) spectroscopy is firstly proposed for rapid determination of the cholesterol concentration in blood. In discretized BOA, the butterfly vector is described by 1 or 0, which represents whether the variable is selected or not, respectively. In the optimization process, four transfer functions, i.e., arctangent, V-shaped, improved arctangent (I-atan) and improved V-shaped (I-V), are introduced and compared for discretization of the butterfly position. The partial least squares (PLS) model is established between the selected NIR variables and cholesterol concentrations. The iteration number, transfer functions and the performance of butterflies are investigated. The proposed method is compared with full-spectrum PLS, multiplicative scatter correction-PLS (MSC-PLS), max-min scaling-PLS (MMS-PLS), MSC-MMS-PLS, uninformative variable elimination-PLS (UVE-PLS), Monte Carlo uninformative variable elimination-PLS (MCUVE-PLS) and randomization test-PLS (RT-PLS). Results show that the I-V function is the best transfer function for discretization. Both preprocessing and variable selection can improve the prediction performance of PLS. Variable selection methods based on BOA are better than those based on statistics. Furthermore, I-V-BOA-PLS has the highest predictive accuracy among the seven variable selection methods. MSC-MMS can further improve the prediction ability of I-V-BOA-PLS. Therefore, BOA-PLS combined with NIR spectroscopy is promising for the rapid determination of cholesterol concentration in blood.
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Affiliation(s)
- Xihui Bian
- State Key Laboratory of Separation Membranes and Membrane Processes, 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
- NMPA Key Laboratory for Technology Research and Evaluation of Drug Products, Shandong University, Jinan, 250012, China
| | - Zizhen Zhao
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin, 300387, China.
| | - Jianwen Liu
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin, 300387, China.
| | - Peng Liu
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin, 300387, China.
| | - Huibing Shi
- Shandong Provincial Key Laboratory of Olefin Catalysis and Polymerization, Shandong Chambroad Holding Group Co. Ltd., Binzhou 256500, China
| | - Xiaoyao Tan
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin, 300387, China.
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12
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Huo J, Zhang M, Wang D, S Mujumdar A, Bhandari B, Zhang L. New preservation and detection technologies for edible mushrooms: A review. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2023; 103:3230-3248. [PMID: 36700618 DOI: 10.1002/jsfa.12472] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 09/11/2022] [Accepted: 01/26/2023] [Indexed: 06/17/2023]
Abstract
Edible mushrooms are nutritious, tasty, and have medicinal value, which makes them very popular. Fresh mushrooms have a high water content and a crisp texture. They demonstrate strong metabolic activity after harvesting. However, they are prone to textural changes, microbial infestation, and nutritional and flavor loss, and they therefore require appropriate post-harvest processing and preservation. Important factors affecting safety and quality during their processing and storage include their quality, source, microbial contamination, physical damage, and chemical residues. Thus, these aspects should be tested carefully to ensure safety. In recent years, many new techniques have been used to preserve mushrooms, including electrofluidic drying and cold plasma treatment, as well as new packaging and coating technologies. In terms of detection, many new detection techniques, such as nuclear magnetic resonance (NMR), imaging technology, and spectroscopy can be used as rapid and effective means of detection. This paper reviews the new technological methods for processing and detecting the quality of mainstream edible mushrooms. It mainly introduces their working principles and application, and highlights the future direction of preservation, processing, and quality detection technologies for edible mushrooms. Adopting appropriate post-harvest processing and preservation techniques can maintain the organoleptic properties, nutrition, and flavor of mushrooms effectively. The use of rapid, accurate, and non-destructive testing methods can provide a strong assurance of food safety. At present, these new processing, preservation and testing methods have achieved good results but at the same time there are certain shortcomings. So it is recommended that they also be continuously researched and improved, for example through the use of new technologies and combinations of different technologies. © 2023 Society of Chemical Industry.
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Affiliation(s)
- Jingyi Huo
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi, China
- China General Chamber of Commerce Key Laboratory on Fresh Food Processing & Preservation, Jiangnan University, Wuxi, China
| | - Min Zhang
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi, China
- Jiangsu Province International Joint Laboratory on Fresh Food Smart Processing and Quality Monitoring, Jiangnan University, Wuxi, China
| | - Dayuan Wang
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi, China
- China General Chamber of Commerce Key Laboratory on Fresh Food Processing & Preservation, Jiangnan University, Wuxi, China
| | - Arun S Mujumdar
- Department of Bioresource Engineering, Macdonald College, McGill University, Quebec, Canada
| | - Bhesh Bhandari
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, Australia
| | - Lujun Zhang
- R&D Center, Shandong Qihe Biotechnology Co., Ltd, Zibo, China
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13
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Wang Y, Huang C, Lu F, Ye X, Ma H. In-situ and real-time monitoring of two-stage enzymatic preparation of ACE inhibitory peptides from Cordyceps militaris medium residues by ultrasonic-assisted pretreatment. Food Chem 2023; 418:135886. [PMID: 36944307 DOI: 10.1016/j.foodchem.2023.135886] [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: 12/04/2022] [Revised: 01/26/2023] [Accepted: 03/04/2023] [Indexed: 03/09/2023]
Abstract
A protocol for the preparation of angiotensin-Ⅰ-converting enzyme (ACE) inhibitory peptides from Cordyceps militaris medium residues (CMMR) was established by two-stage enzymatic hydrolysis (amylase and protease). In a combination (mono-, dual-, and tri-frequency) of five different frequencies (20, 28, 35, 40 and 50 kHz), ultrasound-assisted pretreatment increased ACE inhibition rate in hydrolysate by 63.30 % under the mode of 20/28 kHz. Afterwards, near-infrared (NIR) spectrometer combined with spectral preprocessing methods and multivariate analysis like partial least square (PLS), synergy interval-PLS (Si-PLS), random frog-PLS (RF-PLS) and competitive adaptive reweighted sampling (CARS-PLS) was used to monitor the ACE inhibitory activity. The performance of models was evaluated by the correlation coefficient (Rp) and root mean square error (RMSEP). CARS-PLS models achieved optimal results for both amylase and protease hydrolysis with Rp = 0.9693, RMSEP = 0.01 for the former and Rp = 0.9454, RMSEP = 0.03 for the latter. NIR spectrometer combined with CARS-PLS models may be employed for in-situ and real-time monitoring of the preparation of ACE inhibitory peptides under ultrasonic-assisted pretreatment.
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Affiliation(s)
- Yining Wang
- School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Road, Zhenjiang, Jiangsu 212013, China
| | - Chang Huang
- School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Road, Zhenjiang, Jiangsu 212013, China
| | - Feng Lu
- School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Road, Zhenjiang, Jiangsu 212013, China
| | - Xiaofei Ye
- Department of Biosystems Engineering and Soil Science, The University of Tennessee, Knoxville, TN 37996, USA
| | - Haile Ma
- School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Road, Zhenjiang, Jiangsu 212013, China; Institute of Food Physical Processing, Jiangsu University, 301 Xuefu Road, Zhenjiang, Jiangsu 212013, China.
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14
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Patil AC, Fernández la Villa A, Mugilvannan AK, Elejalde U. Electrochemical investigation of edible oils: Experimentation, electrical signatures, and a supervised learning–case study of adulterated peanut oils. Food Chem 2023; 402:134143. [DOI: 10.1016/j.foodchem.2022.134143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 08/16/2022] [Accepted: 09/04/2022] [Indexed: 10/14/2022]
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15
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Quality control of woody edible oil: The application of fluorescence spectroscopy and the influencing factors of fluorescence. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.109275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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16
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Feasibility study on prediction of the grain mixtures for black sesame paste recipe with different chemometric methods. Lebensm Wiss Technol 2022. [DOI: 10.1016/j.lwt.2022.114078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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17
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Shihab JM, Rashid KT, Toma MA. A review on membrane technology application for vegetable oil purification processes. INTERNATIONAL JOURNAL OF FOOD ENGINEERING 2022. [DOI: 10.1515/ijfe-2022-0058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
In current paper, a comprehensive review to contribute the present insight an implementations and the recent improvements through the diverse endeavor made by the researchers utilizing a membrane technique for degumming, deacidifying, dewaxing and discoloration edible vegetable oils with and without solvent availability and also the solvent recovery has been evaluated. Endeavors made with NF, UF, MF and non-porous membranes, have shown the capability of these membranes to predicate vegetable oil treatment. A membrane technique is noticeably simple and potentially provides many usefulness in vegetable oil purification. It appears that oils treatment with membranes, which carried out at low temperatures that provides saving energy, with real cancellation of stages, provides a promising alternate to conventional procedure, towards the accomplishment of eco-friendly and cost-effective operations that are technically sophisticated. Generally, the solvent (hexane-dilution) technique enhances the membrane oil flux. For dewaxing undiluted vegetable oils, the effective membrane was MF, whereas in dewaxing solvent-diluted oils process UF membranes were more energetic.
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Affiliation(s)
- Jenan M. Shihab
- Membrane Technology Research Unit, Chemical Engineering Department , University of Technology-Iraq , Alsinaa Street 52, 10066 Baghdad , Iraq
| | - Khalid T. Rashid
- Membrane Technology Research Unit, Chemical Engineering Department , University of Technology-Iraq , Alsinaa Street 52, 10066 Baghdad , Iraq
| | - M. A. Toma
- Membrane Technology Research Unit, Chemical Engineering Department , University of Technology-Iraq , Alsinaa Street 52, 10066 Baghdad , Iraq
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18
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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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19
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Application of visible-near-infrared hyperspectral imaging technology coupled with wavelength selection algorithm for rapid determination of moisture content of soybean seeds. J Food Compost Anal 2022. [DOI: 10.1016/j.jfca.2022.105048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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20
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Zhang Y, Xiao H, Lv X, Wang D, Chen H, Wei F. Comprehensive review of composition distribution and advances in profiling of phenolic compounds in oilseeds. Front Nutr 2022; 9:1044871. [PMID: 36386934 PMCID: PMC9650096 DOI: 10.3389/fnut.2022.1044871] [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: 09/15/2022] [Accepted: 10/12/2022] [Indexed: 11/30/2022] Open
Abstract
A wide range of phenolic compounds participate in oilseed growth, regulate oxidative stability of corresponding vegetable oil, and serve as important minor food components with health-promoting effects. Composition distribution of phenolic compounds varied in oilseeds. Isoflavones, sinapic acid derivatives, catechin and epicatechin, phenolic alcohols, chlorogenic acid, and lignans were the main phenolic compounds in soybean, rapeseed, peanut skin, olive, sunflower seed, sesame and flaxseed, respectively. Among which, the total isoflavones content in soybean seeds reached from 1,431 to 2,130 mg/100 g; the main phenolic compound in rapeseed was sinapine, representing 70–90%; chlorogenic acid as the predominant phenolic compound in sunflower kernels, represented around 77% of the total phenolic content. With the rapid development of analytical techniques, it is becoming possible for the comprehensive profiling of these phenolic compounds from oilseeds. This review aims to provide recently developments about the composition distribution of phenolic compounds in common oilseeds, advanced technologies for profiling of phenolic compounds by the metabolomics approaches based on mass spectrometry. As there is still limited research focused on the comprehensive extraction and determination of phenolics with different bound-forms, future efforts should take into account the non-targeted, pseudo-targeted, and spatial metabolomic profiling of phenolic compounds, and the construction of phenolic compound database for identifying and quantifying new types of phenolic compounds in oilseeds and their derived products.
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21
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Near-infrared spectroscopy and machine learning for classification of food powders under moving conditions. J FOOD ENG 2022. [DOI: 10.1016/j.jfoodeng.2022.111339] [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]
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22
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Bowler AL, Ozturk S, Rady A, Watson N. Domain Adaptation for In-Line Allergen Classification of Agri-Food Powders Using Near-Infrared Spectroscopy. SENSORS (BASEL, SWITZERLAND) 2022; 22:7239. [PMID: 36236338 PMCID: PMC9570570 DOI: 10.3390/s22197239] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 09/14/2022] [Accepted: 09/16/2022] [Indexed: 06/16/2023]
Abstract
The addition of incorrect agri-food powders to a production line due to human error is a large safety concern in food and drink manufacturing, owing to incorporation of allergens in the final product. This work combines near-infrared spectroscopy with machine-learning models for early detection of this problem. Specifically, domain adaptation is used to transfer models from spectra acquired under stationary conditions to moving samples, thereby minimizing the volume of labelled data required to collect on a production line. Two deep-learning domain-adaptation methodologies are used: domain-adversarial neural networks and semisupervised generative adversarial neural networks. Overall, accuracy of up to 96.0% was achieved using no labelled data from the target domain moving spectra, and up to 99.68% was achieved when incorporating a single labelled data instance for each material into model training. Using both domain-adaptation methodologies together achieved the highest prediction accuracies on average, as did combining measurements from two near-infrared spectroscopy sensors with different wavelength ranges. Ensemble methods were used to further increase model accuracy and provide quantification of model uncertainty, and a feature-permutation method was used for global interpretability of the models.
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23
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Bian X, Wu D, Zhang K, Liu P, Shi H, Tan X, Wang Z. Variational Mode Decomposition Weighted Multiscale Support Vector Regression for Spectral Determination of Rapeseed Oil and Rhizoma Alpiniae Offcinarum Adulterants. BIOSENSORS 2022; 12:bios12080586. [PMID: 36004982 PMCID: PMC9406014 DOI: 10.3390/bios12080586] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Revised: 07/26/2022] [Accepted: 07/27/2022] [Indexed: 11/16/2022]
Abstract
The accurate prediction of the model is essential for food and herb analysis. In order to exploit the abundance of information embedded in the frequency and time domains, a weighted multiscale support vector regression (SVR) method based on variational mode decomposition (VMD), namely VMD-WMSVR, was proposed for the ultraviolet-visible (UV-Vis) spectral determination of rapeseed oil adulterants and near-infrared (NIR) spectral quantification of rhizoma alpiniae offcinarum adulterants. In this method, each spectrum is decomposed into K discrete mode components by VMD first. The mode matrix Uk is recombined from the decomposed components, and then, the SVR is used to build sub-models between each Uk and target value. The final prediction is obtained by integrating the predictions of the sub-models by weighted average. The performance of the proposed method was tested with two spectral datasets of adulterated vegetable oils and herbs. Compared with the results from partial least squares (PLS) and SVR, VMD-WMSVR shows potential in model accuracy.
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Affiliation(s)
- Xihui Bian
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China; (D.W.); (K.Z.); (P.L.); (X.T.); (Z.W.)
- State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining 810016, China
- Shandong Provincial Key Laboratory of Olefin Catalysis and Polymerization, Shandong Chambroad Holding Group Co., Ltd., Binzhou 256500, China;
- Correspondence:
| | - Deyun Wu
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China; (D.W.); (K.Z.); (P.L.); (X.T.); (Z.W.)
| | - Kui Zhang
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China; (D.W.); (K.Z.); (P.L.); (X.T.); (Z.W.)
| | - Peng Liu
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China; (D.W.); (K.Z.); (P.L.); (X.T.); (Z.W.)
| | - Huibing Shi
- Shandong Provincial Key Laboratory of Olefin Catalysis and Polymerization, Shandong Chambroad Holding Group Co., Ltd., Binzhou 256500, China;
| | - Xiaoyao Tan
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China; (D.W.); (K.Z.); (P.L.); (X.T.); (Z.W.)
| | - Zhigang Wang
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China; (D.W.); (K.Z.); (P.L.); (X.T.); (Z.W.)
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24
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Wan G, Fan S, Liu G, He J, Wang W, Li Y, lijuan Cheng, Ma C, Guo M. Fusion of spectra and texture data of hyperspectral imaging for prediction of myoglobin content in nitrite-cured mutton. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.109332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
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25
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Du Z, Tian W, Tilley M, Wang D, Zhang G, Li Y. Quantitative assessment of wheat quality using near-infrared spectroscopy: A comprehensive review. Compr Rev Food Sci Food Saf 2022; 21:2956-3009. [PMID: 35478437 DOI: 10.1111/1541-4337.12958] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 03/15/2022] [Accepted: 03/16/2022] [Indexed: 01/15/2023]
Abstract
Wheat is one of the most widely cultivated crops throughout the world. A great need exists for wheat quality assessment for breeding, processing, and products production purposes. Near-infrared spectroscopy (NIRS) is a rapid, low-cost, simple, and nondestructive assessment method. Many advanced studies associated with NIRS for wheat quality assessment have been published recently, either introducing new chemometrics or attempting new assessment parameters to improve model robustness and accuracy. This review provides a comprehensive overview of NIRS methodology including its principle, spectra pretreatments, spectral wavelength selection, outlier disposal, dataset division, regression methods, and model evaluation. More importantly, the applications of NIRS in the determination of analytical parameters, rheological parameters, and end product quality of wheat are summarized. Although NIRS showed great potential in the quantitative determination of analytical parameters, there are still challenges in model robustness and accuracy in determining rheological parameters and end product quality for wheat products. Future model development needs to incorporate larger databases, integrate different spectroscopic techniques, and introduce cutting-edge chemometrics methods. In addition, calibration based on external factors should be considered to improve the predicted results of the model. The NIRS application in micronutrients needs to be extended. Last, the idea of combining standard product sensory attributes and spectra for model development deserves further study.
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Affiliation(s)
- Zhenjiao Du
- Department of Grain Science and Industry, Kansas State University, Manhattan, Kansas, USA
| | - Wenfei Tian
- National Wheat Improvement Centre, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Michael Tilley
- USDA, Agricultural Research Service, Center for Grain and Animal Health Research, Manhattan, Kansas, USA
| | - Donghai Wang
- Department of Biological and Agricultural Engineering, Kansas State University, Manhattan, Kansas, USA
| | - Guorong Zhang
- Agricultural Research Center-Hays, Kansas State University, Hays, Kansas, USA
| | - Yonghui Li
- Department of Grain Science and Industry, Kansas State University, Manhattan, Kansas, USA
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26
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Zhang H, Hu X, Liu L, Wei J, Bian X. Near infrared spectroscopy combined with chemometrics for quantitative analysis of corn oil in edible blend oil. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2022; 270:120841. [PMID: 35033805 DOI: 10.1016/j.saa.2021.120841] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 12/27/2021] [Accepted: 12/29/2021] [Indexed: 06/14/2023]
Abstract
In this study, near infrared (NIR) spectroscopy combined with chemometrics was used for the quantitative analysis of corn oil in binary to hexanary edible blend oil. Sesame oil, soybean oil, rice oil, sunflower oil and peanut oil were mixed with corn oil subsequently to form binary, ternary, quaternary, quinary and hexanary blend oil datasets. NIR spectra for the five order blend oil datasets were measured in a transmittance mode in the range of 12000-4000 cm-1. Partial least square (PLS) was used to build models for the five datasets. Six spectral preprocessing methods and their combinations were investigated to improve the prediction performance. Furthermore, the optimal preprocessing-PLS models were further optimized by uninformative variable elimination (UVE), Monte Carlo uninformative variable elimination (MCUVE) and randomization test (RT) variable selection methods. The optimal models acquire root mean square error of prediction (RMSEP) of 1.7299, 2.2089, 2.3742, 2.5608 and 2.6858 for binary, ternary, quaternary, quinary and hexanary blend oil datasets, respectively. The determination coefficients of prediction set (R2P) and residual predictive deviations (RPDs) for the five datasets are all above 0.93 and 3. Results show that the prediction accuracy is gradually decreased with the increasing of mixture order of blend oil. However, with proper spectral preprocessing and variable selection, the optimal models present good prediction accuracy even for the higher order blend oil. It demonstrates that NIR technology is feasible for determining the pure oil contents in binary to hexanary blend oil.
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Affiliation(s)
- Huan Zhang
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Environment Science and Engineering, Tiangong University, Tianjin 300387, China
| | - Xiaoyun Hu
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Environment Science and Engineering, Tiangong University, Tianjin 300387, China
| | - Limei Liu
- School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China
| | - Junfu Wei
- School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China
| | - Xihui Bian
- State Key Laboratory of Separation Membranes and Membrane Processes, School of Environment Science and Engineering, Tiangong University, Tianjin 300387, China; School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China; Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, 644000, China; State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining 810016, China.
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27
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Siudem P, Zielińska A, Paradowska K. Application of 1H NMR in the study of fatty acids composition of vegetable oils. J Pharm Biomed Anal 2022; 212:114658. [DOI: 10.1016/j.jpba.2022.114658] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 02/06/2022] [Accepted: 02/08/2022] [Indexed: 10/19/2022]
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28
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Multivariate analysis of food fraud: A review of NIR based instruments in tandem with chemometrics. J Food Compost Anal 2022. [DOI: 10.1016/j.jfca.2021.104343] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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29
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Balbino S, Vincek D, Trtanj I, Egređija D, Gajdoš-Kljusurić J, Kraljić K, Obranović M, Škevin D. Assessment of Pumpkin Seed Oil Adulteration Supported by Multivariate Analysis: Comparison of GC-MS, Colourimetry and NIR Spectroscopy Data. Foods 2022; 11:foods11060835. [PMID: 35327258 PMCID: PMC8954646 DOI: 10.3390/foods11060835] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 03/02/2022] [Accepted: 03/08/2022] [Indexed: 02/01/2023] Open
Abstract
Because of its high market value, pumpkin seed oil is occasionally adulterated by cheaper refined oils, usually sunflower oil. The standard method for detecting its authenticity is based on expensive and laborious determination of the sterol composition. Therefore, the objective of this study was to determine the sterol content and authenticity of retail oils labelled as pumpkin seed oil and also to investigate the potential of near-infrared spectroscopy (NIR) and colourimetry in detecting adulteration. The results show that due to the significant decrease in Δ7-sterols and increase in Δ5-sterols, 48% of the analysed oils can be declared as adulterated blends of pumpkin seed and sunflower oil. Significant differences in NIR spectroscopy data, in the range of 904-922 nm and 1675-1699 nm, and colourimetric data were found between the control pumpkin seed oil and sunflower oil, but only the NIR method had the potential to detect the authenticity of pumpkin seed oil, which was confirmed by principal component analysis. Orthogonal projection on latent structures (OPLS) discriminant analysis, resulted in working classification models that were able to discriminate pure and adulterated oil. OPLS models based on NIR spectra were also able to successfully predict the content of β-sitosterol and Δ7,22-stigmastadienol in the analysed oils.
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Affiliation(s)
- Sandra Balbino
- Faculty of Food Technology and Biotechnology, University of Zagreb, Pierottijeva 6, 10000 Zagreb, Croatia; (J.G.-K.); (K.K.); (M.O.); (D.Š.)
- Correspondence:
| | - Dragutin Vincek
- Department of Agriculture, Varazdin County, Franjevački trg 7, 42000 Varaždin, Croatia;
| | - Iva Trtanj
- Podravka Inc., Ante Starčevića 32, 48000 Koprivnica, Croatia;
| | - Dunja Egređija
- Ledo plus Ltd., Marijana Čavića 9, 10000 Zagreb, Croatia;
| | - Jasenka Gajdoš-Kljusurić
- Faculty of Food Technology and Biotechnology, University of Zagreb, Pierottijeva 6, 10000 Zagreb, Croatia; (J.G.-K.); (K.K.); (M.O.); (D.Š.)
| | - Klara Kraljić
- Faculty of Food Technology and Biotechnology, University of Zagreb, Pierottijeva 6, 10000 Zagreb, Croatia; (J.G.-K.); (K.K.); (M.O.); (D.Š.)
| | - Marko Obranović
- Faculty of Food Technology and Biotechnology, University of Zagreb, Pierottijeva 6, 10000 Zagreb, Croatia; (J.G.-K.); (K.K.); (M.O.); (D.Š.)
| | - Dubravka Škevin
- Faculty of Food Technology and Biotechnology, University of Zagreb, Pierottijeva 6, 10000 Zagreb, Croatia; (J.G.-K.); (K.K.); (M.O.); (D.Š.)
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30
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Comprehensive Study of Traditional Plant Ground Ivy ( Glechoma hederacea L.) Grown in Croatia in Terms of Nutritional and Bioactive Composition. Foods 2022; 11:foods11050658. [PMID: 35267291 PMCID: PMC8909519 DOI: 10.3390/foods11050658] [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: 01/27/2022] [Revised: 02/16/2022] [Accepted: 02/22/2022] [Indexed: 01/27/2023] Open
Abstract
In the present study, ground ivy was harvested from different natural habitats in Croatia and subjected to screening analysis for nutritional and bioactive composition. To achieve maximum recovery of phenolic compounds, different extraction techniques were investigated—heat-assisted (HAE), microwave-assisted (MAE) and subcritical water (SWE) extraction. Prepared extracts were analysed by spectrophotometric methods, LC-MS/MS and HPLC-PAD methodologies. Results regarding nutritive analyses, conducted using standard AOAC methods, showed the abundance of samples in terms of insoluble dietary fibre, protein, calcium and potassium, while rutin, chlorogenic, cryptochlorogenic, caffeic and rosmarinic acid were the most dominant phenolic compounds. In addition, LC-MS/MS analysis revealed the presence of apigenin and luteolin in glycosylated form. Maximum recovery of target phenolic compounds was achieved with MAE, while SWE led to the formation of new antioxidants, which is commonly known as neoformation. Moreover, efficient prediction of phenolic composition of prepared extracts was achieved using NIR spectroscopy combined with ANN modelling.
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Salvucci G, Pallottino F, De Laurentiis L, Del Frate F, Manganiello R, Tocci F, Vasta S, Figorilli S, Bassotti B, Violino S, Ortenzi L, Antonucci F. Fast olive quality assessment through RGB images and advanced convolutional neural network modeling. Eur Food Res Technol 2022. [DOI: 10.1007/s00217-022-03971-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Application of near-infrared spectroscopy for the nondestructive analysis of wheat flour: A review. Curr Res Food Sci 2022; 5:1305-1312. [PMID: 36065198 PMCID: PMC9440252 DOI: 10.1016/j.crfs.2022.08.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Revised: 07/13/2022] [Accepted: 08/11/2022] [Indexed: 12/04/2022] Open
Abstract
The quality and safety of wheat flour are of public concern since they are related to the quality of flour products and human health. Therefore, efficient and convenient analytical techniques are needed for the quality and safety controls of wheat flour. Near-infrared (NIR) spectroscopy has become an ideal technique for assessing the quality and safety of wheat flour, as it is a rapid, efficient and nondestructive method. The application of NIR spectroscopy in the quality and safety analysis of wheat flour is addressed in this review. First, we briefly summarize the basic knowledge of NIR spectroscopy and chemometrics. Then, recent advances in the application of NIR spectroscopy for chemical composition, technological parameters, and safety analysis are presented. Finally, the potential of NIR spectroscopy is discussed. Combined with chemometric methods, NIR spectroscopy has been used to detect chemical composition, technological parameters, deoxynivalenol, adulterants and additives of wheat flour. Furthermore, NIR spectroscopy has shown great potential for the rapid and online analysis of the quality and safety of wheat flour. It is anticipated that the current review will serve as a reference for the future analysis of wheat flour by NIR spectroscopy to ensure the quality and safety of flour products. NIR spectroscopy is an ideal technique for analysis of wheat flour due to its rapid and nondestructive nature. Use of NIR spectroscopy for chemical composition, technological parameters, and safety analysis. Online and handheld NIR spectrometers for wheat flour detection are the future trends.
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Windarsih A, Arsanti Lestari L, Erwanto Y, Rosiana Putri A, Irnawati, Ahmad Fadzillah N, Rahmawati N, Rohman A. Application of Raman Spectroscopy and Chemometrics for Quality Controls of Fats and Oils: A Review. FOOD REVIEWS INTERNATIONAL 2021. [DOI: 10.1080/87559129.2021.2014860] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Anjar Windarsih
- Research Division for Natural Product Technology (BPTBA), National Research and Innovation Agency (BRIN), Yogyakarta, 55861, Indonesia
- Center of Excellence Institute for Halal Industry & Systems (IHIS), Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Lily Arsanti Lestari
- Center of Excellence Institute for Halal Industry & Systems (IHIS), Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Yuny Erwanto
- Center of Excellence Institute for Halal Industry & Systems (IHIS), Universitas Gadjah Mada, Yogyakarta, Indonesia
- Division of Animal Products Technology, Faculty of Animal Science, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Anggita Rosiana Putri
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Irnawati
- Study Program of Pharmacy, Faculty of Pharmacy, Halu Oleo University, Kendari, Indonesia
| | - Nurrulhidayah Ahmad Fadzillah
- International Institute for Halal Research and Training (INHART), International Islamic University Malaysia (IIUM), Malaysia
| | - Nuning Rahmawati
- Medicinal Plant and Traditional Medicine, Research and Development Centre, Karanganyar, Indonesia
| | - Abdul Rohman
- Center of Excellence Institute for Halal Industry & Systems (IHIS), Universitas Gadjah Mada, Yogyakarta, Indonesia
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta, Indonesia
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Zhu J, Fan X, Han L, Zhang C, Wang J, Pan L, Tu K, Peng J, Zhang M. Quantitative analysis of caprolactam in sauce-based food using infrared spectroscopy combined with data fusion strategies. J Food Compost Anal 2021. [DOI: 10.1016/j.jfca.2021.104130] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
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35
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Giussani B, Escalante-Quiceno AT, Boqué R, Riu J. Measurement Strategies for the Classification of Edible Oils Using Low-Cost Miniaturised Portable NIR Instruments. Foods 2021; 10:foods10112856. [PMID: 34829136 PMCID: PMC8618161 DOI: 10.3390/foods10112856] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 11/06/2021] [Accepted: 11/15/2021] [Indexed: 11/16/2022] Open
Abstract
Miniaturised near-infrared (NIR) instruments have been increasingly used in the last few years, and they have become useful tools for many applications on different types of samples. The market already offers a wide variety of these instruments, each one having specific requirements for the correct acquisition of the instrumental signal. This paper presents the development and optimisation of different measuring strategies for two miniaturised NIR instruments in order to find the best measuring conditions for the rapid and low-cost analysis of olive oils. The developed strategies have been applied to the classification of different samples of olive oils, obtaining good results in all cases.
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Affiliation(s)
- Barbara Giussani
- Dipartimento di Scienza e Alta Tecnologia, Università degli Studi dell’Insubria, Via Valleggio, 9, 22100 Como, Italy;
| | - Alix Tatiana Escalante-Quiceno
- Department of Analytical Chemistry and Organic Chemistry, Universitat Rovira i Virgili, Carrer Marcel·lí Domingo 1, 43007 Tarragona, Spain; (A.T.E.-Q.); (R.B.)
| | - Ricard Boqué
- Department of Analytical Chemistry and Organic Chemistry, Universitat Rovira i Virgili, Carrer Marcel·lí Domingo 1, 43007 Tarragona, Spain; (A.T.E.-Q.); (R.B.)
| | - Jordi Riu
- Department of Analytical Chemistry and Organic Chemistry, Universitat Rovira i Virgili, Carrer Marcel·lí Domingo 1, 43007 Tarragona, Spain; (A.T.E.-Q.); (R.B.)
- Correspondence: ; Tel.: +34-977-558-491
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36
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Chew SC, Ali MA. Recent advances in ultrasound technology applications of vegetable oil refining. Trends Food Sci Technol 2021. [DOI: 10.1016/j.tifs.2021.08.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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37
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Optimizing Uniaxial Oil Extraction of Bulk Rapeseeds: Spectrophotometric and Chemical Analyses of the Extracted Oil under Pretreatment Temperatures and Heating Intervals. Processes (Basel) 2021. [DOI: 10.3390/pr9101755] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Optimizing the operating factors in edible oil extraction requires a statistical technique such as a response surface methodology for evaluating their effects on the responses. The examined input factors in this study were the diameter of pressing vessel, VD (60, 80, and 100 mm), temperature, TPR (40, 60, and 80 °C), and heating time, HTM (30, 60 and 90 min). The combination of these factors generated 17 experimental runs where the mass of oil, oil yield, oil extraction efficiency, and deformation energy were calculated. Based on the response surface regression analysis, the combination of the optimized factors was VD: 100 (+1) mm; TPR: 80 °C (+1) and HTM: 60 (0) min); VD: 60 (–1) mm; TPR: 80 °C (+1) and HTM: 75 (+0.5) min and VD: 100 (+1) mm; TPR: 80 °C (+1) and HTM: 90 (+1). The absorbance and transmittance values significantly (p < 0.05) correlated with the wavelength and temperature, but they did not correlate significantly (p > 0.05) with heating time. The peroxide value did not correlate significantly with temperature, however, it correlated significantly with heating time. Neither the acid value nor the free fatty acid value correlated with both temperature and heating time. The findings of the present study are part of our continuing research on oilseeds’ processing optimization parameters.
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38
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Development of NIR spectroscopy based prediction models for nutritional profiling of pearl millet (Pennisetum glaucum (L.)) R.Br: A chemometrics approach. Lebensm Wiss Technol 2021. [DOI: 10.1016/j.lwt.2021.111813] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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39
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Su N, Pan F, Wang L, Weng S. Rapid Detection of Fatty Acids in Edible Oils Using Vis-NIR Reflectance Spectroscopy with Multivariate Methods. BIOSENSORS-BASEL 2021; 11:bios11080261. [PMID: 34436063 PMCID: PMC8395004 DOI: 10.3390/bios11080261] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 07/27/2021] [Accepted: 07/28/2021] [Indexed: 12/27/2022]
Abstract
The composition and content of fatty acids are critical indicators to identify the quality of edible oils. This study was undertaken to establish a rapid determination method for quality detection of edible oils based on quantitative analysis of palmitic acid, stearic acid, arachidic acid, and behenic acid. Seven kinds of oils were measured to obtain Vis-NIR spectra. Multivariate methods combined with pretreatment methods were adopted to establish quantitative analysis models for the four fatty acids. The model of support vector machine (SVM) with standard normal variate (SNV) pretreatment showed the best predictive performance for the four fatty acids. For the palmitic acid, the determination coefficient of prediction (RP2) was 0.9504 and the root mean square error of prediction (RMSEP) was 0.8181. For the stearic acid, RP2 and RMSEP were 0.9636 and 0.2965. In the prediction of arachidic acid, RP2 and RMSEP were 0.9576 and 0.0577. In the prediction of behenic acid, the RP2 and RMSEP were 0.9521 and 0.1486. Furthermore, the effective wavelengths selected by successive projections algorithm (SPA) were useful for establishing simplified prediction models. The results demonstrate that Vis-NIR spectroscopy combined with multivariate methods can provide a rapid and accurate approach for fatty acids detection 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
| | - Fangfang Pan
- 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.); (S.W.)
| | - Shizhuang Weng
- National Engineering Research Center for Agro-Ecological Big Data Analysis and Application, Anhui University, Hefei 230601, China;
- Correspondence: (L.W.); (S.W.)
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40
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The use of analytical techniques coupled with chemometrics for tracing the geographical origin of oils: A systematic review (2013-2020). Food Chem 2021; 366:130633. [PMID: 34332421 DOI: 10.1016/j.foodchem.2021.130633] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 06/14/2021] [Accepted: 07/16/2021] [Indexed: 11/20/2022]
Abstract
The global market for imported, high-quality priced foods has grown dramatically in the last decade, as consumers become more conscious of food originating from around the world. Many countries require the origin label of food to protect consumers need about true characteristics and origin. Regulatory authorities are looking for an extended and updated list of the analytical techniques for verification of authentic oils and to support law implementation. This review aims to introduce the efforts made using various analytical tools in combination with the multivariate analysis for the verification of the geographical origin of oils. The popular analytical tools have been discussed, and scientometric assessment that underlines research trends in geographical authentication and preferred journals used for dissemination has been indicated. Overall, we believe this article will be a good guideline for food industries and food quality control authority to assist in the selection of appropriate methods to authenticate oils.
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41
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Agbonkonkon N, Wojciechowski G, Abbott DA, Gaucher SP, Yim DR, Thompson AW, Leavell MD. Faster, reduced cost calibration method development methods for the analysis of fermentation product using near-infrared spectroscopy (NIRS). J Ind Microbiol Biotechnol 2021; 48:6293849. [PMID: 34089321 PMCID: PMC9113423 DOI: 10.1093/jimb/kuab033] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 03/17/2021] [Indexed: 11/18/2022]
Abstract
Recent innovations in synthetic biology, fermentation, and process development have decreased time to market by reducing strain construction cycle time and effort. Faster analytical methods are required to keep pace with these innovations, but current methods of measuring fermentation titers often involve manual intervention and are slow, time-consuming, and difficult to scale. Spectroscopic methods like near-infrared (NIR) spectroscopy address this shortcoming; however, NIR methods require calibration model development that is often costly and time-consuming. Here, we introduce two approaches that speed up calibration model development. First, generalized calibration modeling (GCM) or sibling modeling, which reduces calibration modeling time and cost by up to 50% by reducing the number of samples required. Instead of constructing analyte-specific models, GCM combines a reduced number of spectra from several individual analytes to produce a large pool of spectra for a generalized model predicting all analyte levels. Second, randomized multicomponent multivariate modeling (RMMM) reduces modeling time by mixing multiple analytes into one sample matrix and then taking the spectral measurements. Afterward, individual calibration methods are developed for the various components in the mixture. Time saved from the use of RMMM is proportional to the number of components or analytes in the mixture. When combined, the two methods effectively reduce the associated cost and time for calibration model development by a factor of 10.
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Affiliation(s)
- Nosa Agbonkonkon
- Amyris, Inc., 5885 Hollis Street, Suite 100, Emeryville, CA 94608, USA
| | | | - Derek A Abbott
- Amyris, Inc., 5885 Hollis Street, Suite 100, Emeryville, CA 94608, USA
| | - Sara P Gaucher
- Amyris, Inc., 5885 Hollis Street, Suite 100, Emeryville, CA 94608, USA
| | - Daniel R Yim
- Amyris, Inc., 5885 Hollis Street, Suite 100, Emeryville, CA 94608, USA
| | - Andrew W Thompson
- Amyris, Inc., 5885 Hollis Street, Suite 100, Emeryville, CA 94608, USA
| | - Michael D Leavell
- Amyris, Inc., 5885 Hollis Street, Suite 100, Emeryville, CA 94608, USA
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42
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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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43
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Zhang N, Li Y, Wen S, Sun Y, Chen J, Gao Y, Sagymbek A, Yu X. Analytical methods for determining the peroxide value of edible oils: A mini-review. Food Chem 2021; 358:129834. [PMID: 33933972 DOI: 10.1016/j.foodchem.2021.129834] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 04/12/2021] [Accepted: 04/14/2021] [Indexed: 01/06/2023]
Abstract
Edible oils are prone to oxidation during processing and storage that may negatively affect the oil quality and human health. Determining the peroxide value (PV) of edible oils is essential because PV is one of the most typically used quality parameters to monitor lipid oxidation and control oil quality. Many approaches have been developed to determine the PV of oils. Among them, iodometric titration is the commonly used method for PV determination. Considering the limitations related to titrimetric methods, such as time and environmental concerns, several instrumental techniques have been considered as reliable alternatives. The advantages and limitations of classical titration and instrumental methods are summarized in this review. The prospects and reformative aspects for the future applications of these approaches in PV determination are also discussed.
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Affiliation(s)
- Na Zhang
- College of Food Science and Engineering, Northwest A&F University, 22 Xinong Road Yangling, 712100 Shaanxi, PR China
| | - Yonglin Li
- College of Food Science and Engineering, Northwest A&F University, 22 Xinong Road Yangling, 712100 Shaanxi, PR China
| | - Shasha Wen
- College of Food Science and Engineering, Northwest A&F University, 22 Xinong Road Yangling, 712100 Shaanxi, PR China
| | - Yiwen Sun
- College of Food Science and Engineering, Northwest A&F University, 22 Xinong Road Yangling, 712100 Shaanxi, PR China
| | - Jia Chen
- College of Food Science and Engineering, Northwest A&F University, 22 Xinong Road Yangling, 712100 Shaanxi, PR China
| | - Yuan Gao
- College of Food Science and Engineering, Northwest A&F University, 22 Xinong Road Yangling, 712100 Shaanxi, PR China
| | - Altayuly Sagymbek
- S.Seifullin Kazakh Agro Technical University, 62 Zhenis Avenue, 010011, 14 Nur-Sultan, Kazakhstan
| | - Xiuzhu Yu
- College of Food Science and Engineering, Northwest A&F University, 22 Xinong Road Yangling, 712100 Shaanxi, PR China.
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44
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Castro RC, Ribeiro DSM, Santos JLM, Páscoa RNMJ. Comparison of near infrared spectroscopy and Raman spectroscopy for the identification and quantification through MCR-ALS and PLS of peanut oil adulterants. Talanta 2021; 230:122373. [PMID: 33934802 DOI: 10.1016/j.talanta.2021.122373] [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: 01/04/2021] [Revised: 03/19/2021] [Accepted: 03/25/2021] [Indexed: 12/12/2022]
Abstract
Peanut oil is considered one of the best frying oils, and, consequently there is an increasing worldwide demand. This has led to adulteration practices with unhealthy, synthetic or less expensive oils which raises concerns related with public health safety. Therefore, there is a high need for rapid, versatile, low-cost and reliable analytical methods, such as vibrational spectroscopic techniques, capable of identifying and quantifying the respective adulteration. The objective of this work focused on the application of two different vibrational spectroscopic techniques (NIR and Raman spectroscopy) for the qualitative and quantitative analysis of two adulterants in pure peanut oil, namely corn oil and vegetable oil. For the quantitative analysis two chemometric methods, namely PLS and MCR-ALS, were compared while for the qualitative analysis only MCR-ALS was tested. The analysis of peanut oil adulteration was performed by adding each adulterant individually and also by blending the peanut oil with both adulterants simultaneously. A total of 69 samples were analyzed, which was comprised by two sets of 20 samples each containing just one adulterant and another set of 29 samples containing both adulterants. Several pre-processing techniques were tested. The qualitative analysis performed by MCR-ALS allowed the identification of all the adulterants using both NIR and Raman spectra, with correlation coefficients higher than 0.99. For the quantification, none of the chemometric methods as well as the vibrational spectroscopic techniques tested showed significant better results. Nonetheless, the determination coefficients and the relative percentage errors for the validation samples for most of the developed models were higher than 0.98 and lower than 15%, respectively. Concluding, MCR-ALS was capable of correctly extracting the spectral profiles of all the adulterants in very complex mixtures (as the pure spectra of the adulterants and peanut oil are very similar) and both MCR-ALS and PLS were able to quantify the adulteration with low RE. To the best of our knowledge, it was the first time that MCR-ALS was used for the qualitative analysis of peanut oil adulteration (with all adulterants added simultaneously) and MCR-ALS and PLS were compared for the quantification of peanut oil adulteration using both NIR and Raman spectroscopy.
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Affiliation(s)
- Rafael C Castro
- LAQV, REQUIMTE, Department of Chemical Sciences, Laboratory of Applied Chemistry, Faculty of Pharmacy, University of Porto, Rua de Jorge Viterbo Ferreira Nº 228, 4050-313, Porto, Portugal
| | - David S M Ribeiro
- LAQV, REQUIMTE, Department of Chemical Sciences, Laboratory of Applied Chemistry, Faculty of Pharmacy, University of Porto, Rua de Jorge Viterbo Ferreira Nº 228, 4050-313, Porto, Portugal.
| | - João L M Santos
- LAQV, REQUIMTE, Department of Chemical Sciences, Laboratory of Applied Chemistry, Faculty of Pharmacy, University of Porto, Rua de Jorge Viterbo Ferreira Nº 228, 4050-313, Porto, Portugal
| | - Ricardo N M J Páscoa
- LAQV, REQUIMTE, Department of Chemical Sciences, Laboratory of Applied Chemistry, Faculty of Pharmacy, University of Porto, Rua de Jorge Viterbo Ferreira Nº 228, 4050-313, Porto, Portugal.
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45
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State-of-the-Art of Analytical Techniques to Determine Food Fraud in Olive Oils. Foods 2021; 10:foods10030484. [PMID: 33668346 PMCID: PMC7996354 DOI: 10.3390/foods10030484] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 02/13/2021] [Accepted: 02/18/2021] [Indexed: 12/26/2022] Open
Abstract
The benefits of the food industry compared to other sectors are much lower, which is why producers are tempted to commit fraud. Although it is a bad practice committed with a wide variety of foods, it is worth noting the case of olive oil because it is a product of great value and with a high percentage of fraud. It is for all these reasons that the authenticity of olive oil has become a major problem for producers, consumers, and legislators. To avoid such fraud, it is necessary to develop analytical techniques to detect them. In this review, we performed a complete analysis about the available instrumentation used in olive fraud which comprised spectroscopic and spectrometric methodology and analyte separation techniques such as liquid chromatography and gas chromatography. Additionally, other methodology including protein-based biomolecular techniques and analytical approaches like metabolomic, hhyperspectral imaging and chemometrics are discussed.
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46
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Ouyang Q, Wang L, Park B, Kang R, Chen Q. Simultaneous quantification of chemical constituents in matcha with visible-near infrared hyperspectral imaging technology. Food Chem 2021; 350:129141. [PMID: 33618087 DOI: 10.1016/j.foodchem.2021.129141] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 01/10/2021] [Accepted: 01/16/2021] [Indexed: 01/18/2023]
Abstract
This study aimed to assess the feasibility of identifying multiple chemical constituents in matcha using visible-near infrared hyperspectral imaging (VNIR-HSI) technology. Regions of interest (ROIs) were first defined in order to calculate the representative mean spectrum of each sample. Subsequently, the standard normal variate (SNV) method was applied to correct the characteristic spectra. Competitive adaptive reweighted sampling (CARS) and bootstrapping soft shrinkage (BOSS) were used to optimize the models. They were built based on partial least squares (PLS), creating two models referred to as CARS-PLS and BOSS-PLS. The BOSS-PLS models achieved best predictive accuracy, with coefficients of determination predicted to be 0.8077 for caffeine, 0.7098 for tea polyphenols (TPs), 0.7942 for free amino acids (FAAs), 0.8314 for the ratio of TPs to FAAs, and 0.8473 for chlorophyll. These findings highlight the potential of VNIR-HSI technology as a rapid and nondestructive alternative for simultaneous quantification of chemical constituents in matcha.
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Affiliation(s)
- Qin Ouyang
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China.
| | - Li Wang
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China
| | - Bosoon Park
- United States Department of Agriculture, Agricultural Research Services, U.S. National Poultry Research Center, 950 College Station Rd., Athens, GA 30605, USA.
| | - Rui Kang
- United States Department of Agriculture, Agricultural Research Services, U.S. National Poultry Research Center, 950 College Station Rd., Athens, GA 30605, USA
| | - Quansheng Chen
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China.
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47
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Bwambok DK, Siraj N, Macchi S, Larm NE, Baker GA, Pérez RL, Ayala CE, Walgama C, Pollard D, Rodriguez JD, Banerjee S, Elzey B, Warner IM, Fakayode SO. QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs. SENSORS (BASEL, SWITZERLAND) 2020; 20:E6982. [PMID: 33297345 PMCID: PMC7730680 DOI: 10.3390/s20236982] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 12/01/2020] [Accepted: 12/03/2020] [Indexed: 12/23/2022]
Abstract
Quality checks, assessments, and the assurance of food products, raw materials, and food ingredients is critically important to ensure the safeguard of foods of high quality for safety and public health. Nevertheless, quality checks, assessments, and the assurance of food products along distribution and supply chains is impacted by various challenges. For instance, the development of portable, sensitive, low-cost, and robust instrumentation that is capable of real-time, accurate, and sensitive analysis, quality checks, assessments, and the assurance of food products in the field and/or in the production line in a food manufacturing industry is a major technological and analytical challenge. Other significant challenges include analytical method development, method validation strategies, and the non-availability of reference materials and/or standards for emerging food contaminants. The simplicity, portability, non-invasive, non-destructive properties, and low-cost of NIR spectrometers, make them appealing and desirable instruments of choice for rapid quality checks, assessments and assurances of food products, raw materials, and ingredients. This review article surveys literature and examines current challenges and breakthroughs in quality checks and the assessment of a variety of food products, raw materials, and ingredients. Specifically, recent technological innovations and notable advances in quartz crystal microbalances (QCM), electroanalytical techniques, and near infrared (NIR) spectroscopic instrument development in the quality assessment of selected food products, and the analysis of food raw materials and ingredients for foodborne pathogen detection between January 2019 and July 2020 are highlighted. In addition, chemometric approaches and multivariate analyses of spectral data for NIR instrumental calibration and sample analyses for quality assessments and assurances of selected food products and electrochemical methods for foodborne pathogen detection are discussed. Moreover, this review provides insight into the future trajectory of innovative technological developments in QCM, electroanalytical techniques, NIR spectroscopy, and multivariate analyses relating to general applications for the quality assessment of food products.
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Affiliation(s)
- David K. Bwambok
- Chemistry and Biochemistry, California State University San Marcos, 333 S. Twin Oaks Valley Rd, San Marcos, CA 92096, USA;
| | - Noureen Siraj
- Department of Chemistry, University of Arkansas at Little Rock, 2801 S. University Ave, Little Rock, AR 72204, USA; (N.S.); (S.M.)
| | - Samantha Macchi
- Department of Chemistry, University of Arkansas at Little Rock, 2801 S. University Ave, Little Rock, AR 72204, USA; (N.S.); (S.M.)
| | - Nathaniel E. Larm
- Department of Chemistry, University of Missouri, 601 S. College Avenue, Columbia, MO 65211, USA; (N.E.L.); (G.A.B.)
| | - Gary A. Baker
- Department of Chemistry, University of Missouri, 601 S. College Avenue, Columbia, MO 65211, USA; (N.E.L.); (G.A.B.)
| | - Rocío L. Pérez
- Department of Chemistry, Louisiana State University, 232 Choppin Hall, Baton Rouge, LA 70803, USA; (R.L.P.); (C.E.A.); (I.M.W.)
| | - Caitlan E. Ayala
- Department of Chemistry, Louisiana State University, 232 Choppin Hall, Baton Rouge, LA 70803, USA; (R.L.P.); (C.E.A.); (I.M.W.)
| | - Charuksha Walgama
- Department of Physical Sciences, University of Arkansas-Fort Smith, 5210 Grand Ave, Fort Smith, AR 72913, USA; (C.W.); (S.B.)
| | - David Pollard
- Department of Chemistry, Winston-Salem State University, 601 S. Martin Luther King Jr Dr, Winston-Salem, NC 27013, USA;
| | - Jason D. Rodriguez
- Division of Complex Drug Analysis, Center for Drug Evaluation and Research, US Food and Drug Administration, 645 S. Newstead Ave., St. Louis, MO 63110, USA;
| | - Souvik Banerjee
- Department of Physical Sciences, University of Arkansas-Fort Smith, 5210 Grand Ave, Fort Smith, AR 72913, USA; (C.W.); (S.B.)
| | - Brianda Elzey
- Science, Engineering, and Technology Department, Howard Community College, 10901 Little Patuxent Pkwy, Columbia, MD 21044, USA;
| | - Isiah M. Warner
- Department of Chemistry, Louisiana State University, 232 Choppin Hall, Baton Rouge, LA 70803, USA; (R.L.P.); (C.E.A.); (I.M.W.)
| | - Sayo O. Fakayode
- Department of Physical Sciences, University of Arkansas-Fort Smith, 5210 Grand Ave, Fort Smith, AR 72913, USA; (C.W.); (S.B.)
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Borghi FT, Santos PC, Santos FD, Nascimento MH, Corrêa T, Cesconetto M, Pires AA, Ribeiro AV, Lacerda V, Romão W, Filgueiras PR. Quantification and classification of vegetable oils in extra virgin olive oil samples using a portable near-infrared spectrometer associated with chemometrics. Microchem J 2020. [DOI: 10.1016/j.microc.2020.105544] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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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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50
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Zhang J, Li B, Hu Y, Zhou L, Wang G, Guo G, Zhang Q, Lei S, Zhang A. A parameter-free framework for calibration enhancement of near-infrared spectroscopy based on correlation constraint. Anal Chim Acta 2020; 1142:169-178. [PMID: 33280694 DOI: 10.1016/j.aca.2020.11.006] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 11/03/2020] [Accepted: 11/04/2020] [Indexed: 02/07/2023]
Abstract
A new parameter-free framework for calibration enhancement (PFCE) was proposed for dealing with the near-infrared (NIR) spectral inconsistency and maintaining the prediction ability of the calibration model under different conditions. The calibration issues encountered in the maintenance with or without using standards, and even the enhancement between instruments have been thoroughly addressed. The general calibration maintenance/enhancement cases were formulated into non-supervised PFCE (NS-PFCE), semi-supervised PFCE (SS-PFCE), and full-supervised PFCE (FS-PFCE). The NS-PFCE made use of both the provided master and slave spectra of standard samples to construct a maintained calibration slave model by implementing a correlation constraint on the regression coefficients. The SS-PFCE and FS-PFCE methods integrated the slave spectra and reference information of standard samples at the same time into the slave spectral calibration, and thus a maintenance or enhancement model could be achieved for the slave spectra, in particular measured on different instruments. The use of dataset1 comprised of 655 pharmaceutical tablets measured on two NIR spectrometers and datset2 containing 117 plant leaf samples in two mesh sizes has demonstrated that the PFCE framework had a significant effect on enhancing the predictions of the slave spectra in the models. The root mean square errors of prediction (RMSEPs) of either active pharmaceutical ingredient (API) amount in tablets or reducing sugar content in plant leaf samples from the slave spectra approached to or were lower than those values predicted from the master spectra in the master models established with the partial least-squares (PLS) regression method. The advantage of PFCE was parameter-free and efficient. First, the method could be flexibly employed in scientific or applicative environment with no regard to the parameter specification. Second, the performance of NS-PFCE was comparable to the classical calibration maintenance methods, yet the SS-PFCE and FS-PFCE could enhance the prediction ability to a level widely considered as the upper boundary of classical calibration maintenance methods reached.The source code of the method is available at https://github.com/JinZhangLab/PFCE.
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Affiliation(s)
- Jin Zhang
- Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health/School of Food Science, Guizhou Medical University, Guiyang, 550025, China
| | - Boyan Li
- Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health/School of Food Science, Guizhou Medical University, Guiyang, 550025, China.
| | - Yun Hu
- Technology Centre, China Tobacco Guizhou Industrial Co., Ltd., Guiyang, 550009, China
| | - Luoxiong Zhou
- Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health/School of Food Science, Guizhou Medical University, Guiyang, 550025, China
| | - Guoze Wang
- Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health/School of Food Science, Guizhou Medical University, Guiyang, 550025, China
| | - Guo Guo
- Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health/School of Food Science, Guizhou Medical University, Guiyang, 550025, China
| | - Qinghai Zhang
- Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health/School of Food Science, Guizhou Medical University, Guiyang, 550025, China
| | - Shicheng Lei
- Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health/School of Food Science, Guizhou Medical University, Guiyang, 550025, China.
| | - Aihua Zhang
- Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health/School of Food Science, Guizhou Medical University, Guiyang, 550025, China
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