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Anagaw YK, Ayenew W, Limenh LW, Geremew DT, Worku MC, Tessema TA, Simegn W, Mitku ML. Food adulteration: Causes, risks, and detection techniques-review. SAGE Open Med 2024; 12:20503121241250184. [PMID: 38725924 PMCID: PMC11080768 DOI: 10.1177/20503121241250184] [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: 11/23/2023] [Accepted: 04/11/2024] [Indexed: 05/12/2024] Open
Abstract
Food adulteration is the intentional addition of foreign or inferior substances to original food products for a variety of reasons. It takes place in a variety of forms, like mixing, substitution, hiding poor quality in packaging material, putting decomposed food for sale, misbranding or giving false labels, and adding toxicants. Several analytical methods (such as chromatography, spectroscopy, electronic sensors) are used to detect the quality of foodstuffs. This review provides concise but detailed information to understand the scope and scale of food adulteration as a way to further detect, combat, and prevent future adulterations. The objective of this review was to provide a comprehensive overview of the causes, risks, and detection techniques associated with food adulteration. It also aimed to highlight the potential health risks posed by consuming adulterated food products and the importance of detecting and preventing such practices. During the review, books, regulatory guidelines, articles, and reports on food adulteration were analyzed critically. Furthermore, the review assessed key findings to present a well-rounded analysis of the challenges and opportunities associated with combating food adulteration. This review included different causes and health impacts of food adulteration. The analytical techniques for food adulteration detection have also been documented in brief. In addition, the review emphasized the urgency of addressing food adulteration through a combination of regulatory measures, technological advancements, and consumer awareness. In conclusion, food adulteration causes many diseases such as cancer, liver disease, cardiovascular disease, kidney disease, and nervous system-related diseases. So, ensuring food safety is the backbone of health and customer satisfaction. Strengthening regulations, taking legal enforcement action, enhancing testing, and quality control can prevent and mitigate the adulteration of food products. Moreover, proper law enforcement and regular inspection of food quality can bring about drastic changes.
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Affiliation(s)
- Yeniewa Kerie Anagaw
- Department of Pharmaceutical Chemistry, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Amhara, Ethiopia
| | - Wondim Ayenew
- Department of Social and Administrative Pharmacy, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
| | - Liknaw Workie Limenh
- Department of Pharmaceutics, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
| | - Derso Teju Geremew
- Department of Pharmaceutics, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
| | - Minichil Chanie Worku
- Department of Pharmaceutical Chemistry, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Amhara, Ethiopia
| | - Tewodros Ayalew Tessema
- Department of Pharmaceutics, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
| | - Wudneh Simegn
- Department of Social and Administrative Pharmacy, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
| | - Melese Legesse Mitku
- Department of Pharmaceutical Chemistry, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Amhara, Ethiopia
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Suhandy D, Al Riza DF, Yulia M, Kusumiyati K. Non-Targeted Detection and Quantification of Food Adulteration of High-Quality Stingless Bee Honey (SBH) via a Portable LED-Based Fluorescence Spectroscopy. Foods 2023; 12:3067. [PMID: 37628066 PMCID: PMC10452998 DOI: 10.3390/foods12163067] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Revised: 08/10/2023] [Accepted: 08/11/2023] [Indexed: 08/27/2023] Open
Abstract
Stingless bee honey (SBH) is rich in phenolic compounds and available in limited quantities. Authentication of SBH is important to protect SBH from adulteration and retain the reputation and sustainability of SBH production. In this research, we use portable LED-based fluorescence spectroscopy to generate and measure the fluorescence intensity of pure SBH and adulterated samples. The spectrometer is equipped with four UV-LED lamps (peaking at 365 nm) as an excitation source. Heterotrigona itama, a popular SBH, was used as a sample. 100 samples of pure SBH and 240 samples of adulterated SBH (levels of adulteration ranging from 10 to 60%) were prepared. Fluorescence spectral acquisition was measured for both the pure and adulterated SBH samples. Principal component analysis (PCA) demonstrated that a clear separation between the pure and adulterated SBH samples could be established from the first two principal components (PCs). A supervised classification based on soft independent modeling of class analogy (SIMCA) achieved an excellent classification result with 100% accuracy, sensitivity, specificity, and precision. Principal component regression (PCR) was superior to partial least squares regression (PLSR) and multiple linear regression (MLR) methods, with a coefficient of determination in prediction (R2p) = 0.9627, root mean squared error of prediction (RMSEP) = 4.1579%, ratio prediction to deviation (RPD) = 5.36, and range error ratio (RER) = 14.81. The LOD and LOQ obtained were higher compared to several previous studies. However, most predicted samples were very close to the regression line, which indicates that the developed PLSR, PCR, and MLR models could be used to detect HFCS adulteration of pure SBH samples. These results showed the proposed portable LED-based fluorescence spectroscopy has a high potential to detect and quantify food adulteration in SBH, with the additional advantages of being an accurate, affordable, and fast measurement with minimum sample preparation.
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Affiliation(s)
- Diding Suhandy
- Department of Agricultural Engineering, Faculty of Agriculture, The University of Lampung, Jl. Soemantri Brojonegoro No. 1, Bandar Lampung 35145, Indonesia
| | - Dimas Firmanda Al Riza
- Department of Biosystems Engineering, Faculty of Agricultural Technology, University of Brawijaya, Jl. Veteran, Malang 65145, Indonesia;
| | - Meinilwita Yulia
- Department of Agricultural Technology, Lampung State Polytechnic, Jl. Soekarno Hatta No. 10, Bandar Lampung 35141, Indonesia;
| | - Kusumiyati Kusumiyati
- Department of Agronomy, Faculty of Agriculture, Universitas Padjadjaran, Sumedang 45363, Indonesia;
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3
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Aykas DP, Sinir GO, Borba KR. Determination of quality traits and possible adulteration of molasses using FT-IR spectroscopy: A study from Turkish market. Food Chem 2023; 427:136727. [PMID: 37406447 DOI: 10.1016/j.foodchem.2023.136727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 06/23/2023] [Accepted: 06/24/2023] [Indexed: 07/07/2023]
Abstract
We aimed to develop portable Fourier transform infrared (FT-IR) spectroscopy-based prediction algorithms for the key quality characteristics (soluble solids, water activity, pH, sucrose, glucose, fructose, fructose/glucose, hydroxymethylfurfural) of various types of molasses, establish their legitimacy, and create a model to separate them based on their botanical origin. Samples labeled as carob (n = 27), grape (n = 24), Juniper (n = 13), and mulberry (n = 12) were purchased from different local markets in Turkey. Labeling issues were revealed in five carob and seven grape molasses, and those samples classified as non-authentic by the FT-IR algorithms were corroborated by reference analysis. Partial least squares regression models generated to predict the key quality traits of Turkish molasses demonstrated excellent correlation with reference analysis (R2Val ≥ 0.96) and low standard error of prediction (SEP ≤ 2.88). The FT-IR sensor provided a feasible approach for molasses testing to assess its quality through manufacturing and storage, also provided a powerful tool to -ensure proper product labeling.
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Affiliation(s)
- Didem Peren Aykas
- Department of Food Engineering, Faculty of Engineering, Adnan Menderes University, Aydin 09100, Turkey.
| | - Gulsah Ozcan Sinir
- Department of Food Engineering, Faculty of Agriculture, Bursa Uludağ University, Bursa, Turkey
| | - Karla Rodrigues Borba
- Department of Food and Nutrition, São Paulo State University, Araraquara, SP 01049-10, Brazil
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4
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Aslam R, Sharma SR, Kaur J, Panayampadan AS, Dar OI. A systematic account of food adulteration and recent trends in the non-destructive analysis of food fraud detection. JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION 2023. [DOI: 10.1007/s11694-023-01846-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
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5
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Identifying adulteration of raw bovine milk with urea through electrochemical impedance spectroscopy coupled with chemometric techniques. Food Chem 2022; 385:132678. [PMID: 35290953 DOI: 10.1016/j.foodchem.2022.132678] [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: 10/21/2021] [Revised: 03/07/2022] [Accepted: 03/08/2022] [Indexed: 11/22/2022]
Abstract
This study aimed to evaluate the applicability of electrochemical impedance spectroscopy to identify raw bovine milk adulteration with urea. Three batches of raw milk adulterated with urea were studied. Hierarchical clustering indicated that the samples could be split in three groups corresponding to low adulteration (less than 7 wt%), medium adulteration (between 8 and 16 wt%) and high adulteration (over than 16 wt%). A linear discriminant analysis was performed resulting in 90% of accuracy in classifying between groups. Besides, a partial least squares model containing three directions provided good accuracy in quantitatively predicting the urea mass fraction added to raw bovine milk. Finally, calculations using an approximated electric circuit model suggested the formation of urea aggregates that hinder charge transportation within the milk thus diminishing the solution conductivity. Results indicate that electrochemical impedance spectroscopy can be a useful, low cost and rapid tool to identify milk adulteration with urea.
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7
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The rapid detection of acacia honey adulteration by alternating current impedance spectroscopy combined with 1H NMR profile. Lebensm Wiss Technol 2022. [DOI: 10.1016/j.lwt.2022.113377] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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8
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Stefas D, Gyftokostas N, Kourelias P, Nanou E, Tananaki C, Kanelis D, Liolios V, Kokkinos V, Bouras C, Couris S. Honey discrimination based on the bee feeding by Laser Induced Breakdown Spectroscopy. Food Control 2022. [DOI: 10.1016/j.foodcont.2021.108770] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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9
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Sotiropoulou NS, Xagoraris M, Revelou PK, Kaparakou E, Kanakis C, Pappas C, Tarantilis P. The Use of SPME-GC-MS IR and Raman Techniques for Botanical and Geographical Authentication and Detection of Adulteration of Honey. Foods 2021; 10:foods10071671. [PMID: 34359541 PMCID: PMC8303172 DOI: 10.3390/foods10071671] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 07/14/2021] [Accepted: 07/15/2021] [Indexed: 11/16/2022] Open
Abstract
The aim of this review is to describe the chromatographic, spectrometric, and spectroscopic techniques applied to honey for the determination of botanical and geographical origin and detection of adulteration. Based on the volatile profile of honey and using Solid Phase microextraction-Gas chromatography-Mass spectrometry (SPME-GC-MS) analytical technique, botanical and geographical characterization of honey can be successfully determined. In addition, the use of vibrational spectroscopic techniques, in particular, infrared (IR) and Raman spectroscopy, are discussed as a tool for the detection of honey adulteration and verification of its botanical and geographical origin. Manipulation of the obtained data regarding all the above-mentioned techniques was performed using chemometric analysis. This article reviews the literature between 2007 and 2020.
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10
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Wang L, Yang Q, Zhao H. Sub-regional identification of peanuts from Shandong Province of China based on Fourier transform infrared (FT-IR) spectroscopy. Food Control 2021. [DOI: 10.1016/j.foodcont.2021.107879] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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11
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Skaff W, El Hajj R, Hanna‐Wakim L, Estephan N. Detection of adulteration in honey by infrared spectroscopy and chemometrics: Effect on human health. J FOOD PROCESS PRES 2021. [DOI: 10.1111/jfpp.15438] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- W. Skaff
- ESIAMUniversité Saint‐Joseph Zahle Lebanon
| | - R. El Hajj
- Department of Chemistry and Biochemsitry Faculty of Arts and Sciences Holy Spirit University of Kaslik Jounieh Lebanon
| | - L. Hanna‐Wakim
- Department of Agricultural and Food Engineering School of Engineering Holy Spirit University of Kaslik Jounieh Lebanon
| | - N. Estephan
- Department of Chemistry and Biochemsitry Faculty of Arts and Sciences Holy Spirit University of Kaslik Jounieh Lebanon
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12
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Nonintrusive honey fraud detection and quantification based on differential radiofrequency absorbance analysis. J FOOD ENG 2021. [DOI: 10.1016/j.jfoodeng.2020.110448] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
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13
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Zheng YF, Wu MC, Chien HJ, Wang WC, Kuo CY, Lai CC. Honey proteomic signatures for the identification of honey adulterated with syrup, producing country, and nectar source using SWATH-MS approach. Food Chem 2021; 354:129590. [PMID: 33756333 DOI: 10.1016/j.foodchem.2021.129590] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 02/23/2021] [Accepted: 03/07/2021] [Indexed: 01/18/2023]
Abstract
Honey is widely consumed by humans, due to its multiple applications as a food constituent and its therapeutic effects. This study reports on the discrimination of honey products from different geographical and botanical sources, as well as honey products containing distinct forms of syrup used in honey adulteration. Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS)-based proteomic analysis combined with chemometrics was successfully applied in identifying characteristic proteins that can be used as biomarkers of the original source of honey. Honey samples from different producing regions (Tainan, Changhua, and Taichung), countries (Taiwan and Thailand), and distinct botanical sources (longan and litchi) were clearly distinguished by the developed orthogonal projections to latent structures discriminant analysis (OPLS-DA) model with good fitness and prediction ability. Furthermore, we successfully discriminated the adulteration of honey with syrup in different proportions (even with honey content as low as 20%) with this proteomic SWATH-MS platform.
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Affiliation(s)
- Yi-Feng Zheng
- Institute of Molecular Biology, National Chung Hsing University, Taichung 40227, Taiwan.
| | - Ming-Cheng Wu
- Department of Entomology, National Chung Hsing University, Taichung 40227, Taiwan.
| | - Han-Ju Chien
- Institute of Molecular Biology, National Chung Hsing University, Taichung 40227, Taiwan.
| | - Wei-Chen Wang
- Institute of Molecular Biology, National Chung Hsing University, Taichung 40227, Taiwan.
| | - Cheng-Yu Kuo
- Institute of Molecular Biology, National Chung Hsing University, Taichung 40227, Taiwan.
| | - Chien-Chen Lai
- Institute of Molecular Biology, National Chung Hsing University, Taichung 40227, Taiwan; Graduate Institute of Chinese Medical Science, China Medical University, Taichung 40447, Taiwan; Advanced Plant Biotechnology Center, National Chung Hsing University, Taichung 40227, Taiwan; Ph.D. Program in Translational Medicine, National Chung Hsing University, Taichung 40227, Taiwan; Rong Hsing Research Center For Translational Medicine, National Chung Hsing University, Taichung 40227, Taiwan.
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14
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Das C, Chowdhury BN, Chakraborty S, Sikdar S, Saha R, Mukherjee A, Karmakar A, Chattopadhyay S. A diagrammatic approach of impedimetric phase angle-modulus sensing for identification and quantification of various polar and non-polar/ionic adulterants in milk. Lebensm Wiss Technol 2021. [DOI: 10.1016/j.lwt.2020.110347] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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15
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Pereira JR, da R. Campos AN, de Oliveira FC, Silva VR, David GF, Da Silva JG, Nascimento WW, Silva MH, Denadai ÂM. Physical-chemical characterization of commercial honeys from Minas Gerais, Brazil. FOOD BIOSCI 2020. [DOI: 10.1016/j.fbio.2020.100644] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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16
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He Y, Bai X, Xiao Q, Liu F, Zhou L, Zhang C. Detection of adulteration in food based on nondestructive analysis techniques: a review. Crit Rev Food Sci Nutr 2020; 61:2351-2371. [PMID: 32543218 DOI: 10.1080/10408398.2020.1777526] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
In recent years, people pay more and more attention to food quality and safety, which are significantly relating to human health. Food adulteration is a world-wide concerned issue relating to food quality and safety, and it is difficult to be detected. Modern detection techniques (high performance liquid chromatography, gas chromatography-mass spectrometer, etc.) can accurately identify the types and concentrations of adulterants in different food types. However, the characteristics as expensive, low efficient and complex sample preparation and operation limit the use of these techniques. The rapid, nondestructive and accurate detection techniques of food adulteration is of great and urgent demand. This paper introduced the principles, advantages and disadvantages of the nondestructive analysis techniques and reviewed the applications of these techniques in food adulteration screen in recent years. Differences among these techniques, differences on data interpretation and future prospects were also discussed.
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Affiliation(s)
- Yong He
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, China.,Ministry of Agriculture and Rural Affairs, Key Laboratory of Spectroscopy Sensing, Hangzhou, Zhejiang, China
| | - Xiulin Bai
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, China.,Ministry of Agriculture and Rural Affairs, Key Laboratory of Spectroscopy Sensing, Hangzhou, Zhejiang, China
| | - Qinlin Xiao
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, China.,Ministry of Agriculture and Rural Affairs, Key Laboratory of Spectroscopy Sensing, Hangzhou, Zhejiang, China
| | - Fei Liu
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, China.,Ministry of Agriculture and Rural Affairs, Key Laboratory of Spectroscopy Sensing, Hangzhou, Zhejiang, China
| | - Lei Zhou
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, China.,Ministry of Agriculture and Rural Affairs, Key Laboratory of Spectroscopy Sensing, Hangzhou, Zhejiang, China
| | - Chu Zhang
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, China.,Ministry of Agriculture and Rural Affairs, Key Laboratory of Spectroscopy Sensing, Hangzhou, Zhejiang, China
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Nespeca MG, Vieira AL, Júnior DS, Neto JAG, Ferreira EC. Detection and quantification of adulterants in honey by LIBS. Food Chem 2020; 311:125886. [DOI: 10.1016/j.foodchem.2019.125886] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Revised: 08/09/2019] [Accepted: 11/09/2019] [Indexed: 12/01/2022]
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18
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A Comprehensive Peach Fruit Quality Evaluation Method for Grading and Consumption. APPLIED SCIENCES-BASEL 2020. [DOI: 10.3390/app10041348] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Peaches are a popular fruit appreciated by consumers due to their eating quality. Quality evaluation of peaches is important for their processing, inventory control, and marketing. Eleven quality indicators (shape index, volume, mass, density, firmness, color, impedance, phase angle, soluble solid concentration, titratable acidity, and sugar–acid ratio) of 200 peach fruits (Prunus persica (L.) Batsch “Spring Belle”) were measured within 48 h. Quality indicator data were normalized, outliers were excluded, and correlation analysis showed that the correlation coefficients between dielectric properties and firmness were the highest. A back propagation (BP) neural network was used to predict the firmness of fresh peaches based on their dielectric properties, with an overall fitting ratio of 86.9%. The results of principal component analysis indicated that the cumulative variance of the first five principal components was 85%. Based on k-means clustering analysis, normalized data from eleven quality indicators in 190 peaches were classified into five clusters. The proportion of red surface area was shown to be a poor basis for picking fresh peaches for the consumer market, as it bore little relationship with the comprehensive quality scores calculated using the new grading model.
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20
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Li X, Li J, Li T, Liu H, Wang Y. Species discrimination and total polyphenol prediction of porcini mushrooms by fourier transform mid-infrared (FT-MIR) spectrometry combined with multivariate statistical analysis. Food Sci Nutr 2020; 8:754-766. [PMID: 32148785 PMCID: PMC7020324 DOI: 10.1002/fsn3.1313] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2019] [Revised: 10/27/2019] [Accepted: 11/04/2019] [Indexed: 01/30/2023] Open
Abstract
The plateau specialty agricultural products, wild porcini mushrooms, have great value both as a superb cuisine and as a potential medication. Due to quality different between species added with the fraud behavior in sales process, make poor quality or poisonous sample inflow into the market, which pose a health risk for consumers, but also disrupted the mushroom market. Traditional analysis way is time-consuming and laborious. Therefore, the aim of this study is to develop a way using fourier transform mid-infrared (FT-MIR) spectrometry and data fusion strategies for the fast and accurate species discrimination and predict amount of total polyphenol in four porcini mushrooms. The t-distributed stochastic neighbor embedding based on mid-level data fusion showed two species of Boletus edulis and B. umbriniporus have been identified. The order of correct rate of PLS-DA models was mid-level data fusionq (100%) > mid-level data fusione (97.06%) = mid-level data fusionv (97.06%) = stipes (97.06%) > low-level data fusion (94.12%) > caps (91.18%). The order of correct rate of grid-search support vector machine models was low-level data fusion (100%) > caps (94.12%) > stipes (91.18%), and the order of particle swarm optimization support vector machine was low-level data fusion (100%) > caps (97.06%) > stipes (88.24%). The mid-level data fusionq and low-level data fusion had best discrimination accuracy (100%) allowing each mushroom classed into its real species, which could be used for accurate discrimination of samples. B. edulis mushrooms had highest total polyphenol, with 14.76 mg/g dw and 17.33 in caps and stipes mg/g dw, respectively. The phenols were easier to accumulate in the caps in Leccinum rugosiceps (1.03) and B. tomentipes (1.19), and the opposite phenomenon is observed in B. edulis (0.85) and B. umbriniporus (0.95). The correlation coefficient and residual predictive deviation of best prediction model were 86.76% and 2.40%, respectively, indicating that that there is good relevance between FT-MIR and total polyphenol content, which could be used to predict roughly polyphenols content in mushrooms.
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Affiliation(s)
- Xiu‐Ping Li
- College of Agronomy and BiotechnologyYunnan Agricultural UniversityKunmingChina
- Institute of Medicinal PlantsYunnan Academy of Agricultural SciencesKunmingChina
| | - Jieqing Li
- College of Agronomy and BiotechnologyYunnan Agricultural UniversityKunmingChina
| | - Tao Li
- College of Resources and EnvironmentYuxi Normal UniversityYuxiChina
| | - Honggao Liu
- College of Agronomy and BiotechnologyYunnan Agricultural UniversityKunmingChina
| | - Yuanzhong Wang
- College of Agronomy and BiotechnologyYunnan Agricultural UniversityKunmingChina
- Institute of Medicinal PlantsYunnan Academy of Agricultural SciencesKunmingChina
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Santos GDSD, Santos NRRD, Pereira ICS, Andrade Júnior AJD, Lima EMB, Minguita AP, Rosado LHG, Moreira APD, Middea A, Prudencio ER, Luchese RH, Oliveira RN. Layered cryogels laden with Brazilian honey intended for wound care. POLIMEROS 2020. [DOI: 10.1590/0104-1428.06820] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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22
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Untargeted headspace gas chromatography – Ion mobility spectrometry analysis for detection of adulterated honey. Talanta 2019; 205:120123. [DOI: 10.1016/j.talanta.2019.120123] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 07/03/2019] [Accepted: 07/05/2019] [Indexed: 11/24/2022]
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23
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Anguebes-Franseschi F, Abatal M, Pat L, Flores A, Córdova Quiroz AV, Ramírez-Elias MA, San Pedro L, May Tzuc O, Bassam A. Raman Spectroscopy and Chemometric Modeling to Predict Physical-Chemical Honey Properties from Campeche, Mexico. Molecules 2019; 24:E4091. [PMID: 31766131 PMCID: PMC6891675 DOI: 10.3390/molecules24224091] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Revised: 11/04/2019] [Accepted: 11/05/2019] [Indexed: 11/16/2022] Open
Abstract
In this work, 10 chemometric models based on Raman spectroscopy were constructed to predict the physicochemical properties of honey produced in the state of Campeche, Mexico. The properties of honey studied were pH, moisture, total soluble solids (TSS), free acidity, lactonic acidity, total acidity, electrical conductivity, Redox potential, hydroxymethylfurfural (HMF), and ash content. These proprieties were obtained according to the methods described by the Association of Official Analytical Chemists, Codex Alimentarius, and the International Honey Commission. For the construction of the chemometric models, 189 honey samples were collected and analyzed in triplicate using Raman spectroscopy to generate the matrix data [X], which were correlated with each of the physicochemical properties [Y]. The predictive capacity of each model was determined by cross validation and external validation, using the statistical parameters: standard error of calibration (SEC), standard error of prediction (SEP), coefficient of determination of cross-validation (R2cal), coefficient of determination for external validation (R2val), and Student's t-test. The statistical results indicated that the chemometric models satisfactorily predict the humidity, TSS, free acidity, lactonic acidity, total acidity, and Redox potential. However, the models for electric conductivity and pH presented an acceptable prediction capacity but not adequate to supply the conventional processes, while the models for predicting ash content and HMF were not satisfactory. The developed models represent a low-cost tool to analyze the quality of honey, and contribute significantly to increasing the honey distribution and subsequently the economy of the region.
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Affiliation(s)
- F. Anguebes-Franseschi
- Faculty of Chemistry, Autonomous University of Carmen, Street 56 No. 4 Esq. Av. Concordia, Col. Benito Juárez, Z. C. 24180 Ciudad del Carmen, Campeche, Mexico; (F.A.-F.); (A.V.C.Q.); (M.A.R.-E.)
| | - M. Abatal
- Faculty of Engineering, Autonomous University of Carmen, Campus III, Avenida Central s/n, Esq. Con Fracc. Mundo Maya, C. P. 24115 Ciudad del Carmen, Campeche, Mexico; (M.A.); (A.F.)
| | - Lucio Pat
- South Frontier College, Av. Rancho Polígono 2-A, Ciudad Industrial, 24500 Lerma, Campeche, Mexico;
| | - A. Flores
- Faculty of Engineering, Autonomous University of Carmen, Campus III, Avenida Central s/n, Esq. Con Fracc. Mundo Maya, C. P. 24115 Ciudad del Carmen, Campeche, Mexico; (M.A.); (A.F.)
| | - A. V. Córdova Quiroz
- Faculty of Chemistry, Autonomous University of Carmen, Street 56 No. 4 Esq. Av. Concordia, Col. Benito Juárez, Z. C. 24180 Ciudad del Carmen, Campeche, Mexico; (F.A.-F.); (A.V.C.Q.); (M.A.R.-E.)
| | - M. A. Ramírez-Elias
- Faculty of Chemistry, Autonomous University of Carmen, Street 56 No. 4 Esq. Av. Concordia, Col. Benito Juárez, Z. C. 24180 Ciudad del Carmen, Campeche, Mexico; (F.A.-F.); (A.V.C.Q.); (M.A.R.-E.)
| | - L. San Pedro
- Faculty of Engineering, Autonomous University of Yucatan, Av. Industrias no Contaminantes Periférico Norte, Cordemex, Z.C. 97310 Mérida, Yucatan, Mexico; (L.S.P.); (O.M.T.)
| | - O. May Tzuc
- Faculty of Engineering, Autonomous University of Yucatan, Av. Industrias no Contaminantes Periférico Norte, Cordemex, Z.C. 97310 Mérida, Yucatan, Mexico; (L.S.P.); (O.M.T.)
| | - A. Bassam
- Faculty of Engineering, Autonomous University of Yucatan, Av. Industrias no Contaminantes Periférico Norte, Cordemex, Z.C. 97310 Mérida, Yucatan, Mexico; (L.S.P.); (O.M.T.)
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Su WH, Sun DW. Mid-infrared (MIR) Spectroscopy for Quality Analysis of Liquid Foods. FOOD ENGINEERING REVIEWS 2019. [DOI: 10.1007/s12393-019-09191-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Ren H, Yue J, Wang D, Fan J, An L. HPLC and 1H-NMR combined with chemometrics analysis for rapid discrimination of floral origin of honey. JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION 2019. [DOI: 10.1007/s11694-019-00035-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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Impedimetric Approach for Estimating the Presence of Metanil Yellow in Turmeric Powder from Tunable Capacitance Measurement. FOOD ANAL METHOD 2019. [DOI: 10.1007/s12161-018-01423-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
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Ferreiro-González M, Espada-Bellido E, Guillén-Cueto L, Palma M, Barroso CG, Barbero GF. Rapid quantification of honey adulteration by visible-near infrared spectroscopy combined with chemometrics. Talanta 2018; 188:288-292. [DOI: 10.1016/j.talanta.2018.05.095] [Citation(s) in RCA: 81] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Revised: 05/24/2018] [Accepted: 05/28/2018] [Indexed: 12/01/2022]
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Kędzierska-Matysek M, Matwijczuk A, Florek M, Barłowska J, Wolanciuk A, Matwijczuk A, Chruściel E, Walkowiak R, Karcz D, Gładyszewska B. Application of FTIR spectroscopy for analysis of the quality of honey. BIO WEB OF CONFERENCES 2018. [DOI: 10.1051/bioconf/20181002008] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Every kind of honey is a very precious natural product which is made by Mellifera bees species. The chemical composition of honey depends on its origin or mode of production. Honey consists essentially of different sugars, predominantly fructose and glucose. There are also non – sugar ingredients like proteins and amino acids, as well as some kind of enzymes, such as: invertase, amylase, glucose oxidase, catalase and phosphatase. The fact that honey is one of the oldest medicine known worldwide is remarkable. Scientists all over the world have been trying to improve analytical methods as well as to implement new ones in order to reaffirm the high quality of honey the benefits of which may be distracted or disturbed. There are many methods and popular analytical techniques, including as follows: mass spectroscopy and molecular spectroscopy (especially FTIR spectroscopy). The infrared spectroscopy technique is one of the most common analytical methods which are used to analyse honey nowadays. The main aim of the task was to use ATR-FTIR infrared spectroscopy to compare selected honey samples as well as typical sequences coming out from certain functional groups in the analysed samples.
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