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Magnani G, Giliberti C, Errico D, Stighezza M, Fortunati S, Mattarozzi M, Boni A, Bianchi V, Giannetto M, De Munari I, Cagnoni S, Careri M. Evaluation of a Voltametric E-Tongue Combined with Data Preprocessing for Fast and Effective Machine Learning-Based Classification of Tomato Purées by Cultivar. SENSORS (BASEL, SWITZERLAND) 2024; 24:3586. [PMID: 38894376 PMCID: PMC11175304 DOI: 10.3390/s24113586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Revised: 05/28/2024] [Accepted: 05/31/2024] [Indexed: 06/21/2024]
Abstract
The potential of a voltametric E-tongue coupled with a custom data pre-processing stage to improve the performance of machine learning techniques for rapid discrimination of tomato purées between cultivars of different economic value has been investigated. To this aim, a sensor array with screen-printed carbon electrodes modified with gold nanoparticles (GNP), copper nanoparticles (CNP) and bulk gold subsequently modified with poly(3,4-ethylenedioxythiophene) (PEDOT), was developed to acquire data to be transformed by a custom pre-processing pipeline and then processed by a set of commonly used classifiers. The GNP and CNP-modified electrodes, selected based on their sensitivity to soluble monosaccharides, demonstrated good ability in discriminating samples of different cultivars. Among the different data analysis methods tested, Linear Discriminant Analysis (LDA) proved to be particularly suitable, obtaining an average F1 score of 99.26%. The pre-processing stage was beneficial in reducing the number of input features, decreasing the computational cost, i.e., the number of computing operations to be performed, of the entire method and aiding future cost-efficient hardware implementation. These findings proved that coupling the multi-sensing platform featuring properly modified sensors with the custom pre-processing method developed and LDA provided an optimal tradeoff between analytical problem solving and reliable chemical information, as well as accuracy and computational complexity. These results can be preliminary to the design of hardware solutions that could be embedded into low-cost portable devices.
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Affiliation(s)
- Giulia Magnani
- Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy; (G.M.); (M.S.); (A.B.); (V.B.); (I.D.M.)
| | - Chiara Giliberti
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, 43124 Parma, Italy; (C.G.); (D.E.); (S.F.); (M.M.); (M.C.)
| | - Davide Errico
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, 43124 Parma, Italy; (C.G.); (D.E.); (S.F.); (M.M.); (M.C.)
| | - Mattia Stighezza
- Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy; (G.M.); (M.S.); (A.B.); (V.B.); (I.D.M.)
| | - Simone Fortunati
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, 43124 Parma, Italy; (C.G.); (D.E.); (S.F.); (M.M.); (M.C.)
| | - Monica Mattarozzi
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, 43124 Parma, Italy; (C.G.); (D.E.); (S.F.); (M.M.); (M.C.)
| | - Andrea Boni
- Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy; (G.M.); (M.S.); (A.B.); (V.B.); (I.D.M.)
| | - Valentina Bianchi
- Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy; (G.M.); (M.S.); (A.B.); (V.B.); (I.D.M.)
| | - Marco Giannetto
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, 43124 Parma, Italy; (C.G.); (D.E.); (S.F.); (M.M.); (M.C.)
| | - Ilaria De Munari
- Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy; (G.M.); (M.S.); (A.B.); (V.B.); (I.D.M.)
| | - Stefano Cagnoni
- Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy; (G.M.); (M.S.); (A.B.); (V.B.); (I.D.M.)
| | - Maria Careri
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, 43124 Parma, Italy; (C.G.); (D.E.); (S.F.); (M.M.); (M.C.)
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Egido C, Saurina J, Sentellas S, Núñez O. Honey fraud detection based on sugar syrup adulterations by HPLC-UV fingerprinting and chemometrics. Food Chem 2024; 436:137758. [PMID: 37857208 DOI: 10.1016/j.foodchem.2023.137758] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 10/12/2023] [Accepted: 10/12/2023] [Indexed: 10/21/2023]
Abstract
In recent years, honey-producing sector has faced the increasing presence of adulterated honeys, implying great economic losses and questioning the quality of this highly appreciated product by the society. Due to the high sugar content of honey, sugar syrups are among its most common adulterants, being also the most difficult to detect even with isotope ratio techniques depending on the origin of the sugar syrup plant source. In this work, a honey authentication method based on HPLC-UV fingerprinting was developed, exhibiting a 100% classification rate of honey samples against a great variety of sugar syrups (agave, corn, fiber, maple, rice, sugar cane and glucose) by partial least squares-discriminant analysis (PLS-DA). In addition, the detection and level quantitation of adulteration using syrups as adulterants (down to 15%) was accomplished by partial least squares (PLS) regression with low prediction errors by both internal and external validation (values below 12.8% and 19.7%, respectively).
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Affiliation(s)
- Carla Egido
- Department of Chemical Engineering and Analytical Chemistry, Universitat de Barcelona, Martí i Franquès 1-11, E08028 Barcelona, Spain
| | - Javier Saurina
- Department of Chemical Engineering and Analytical Chemistry, Universitat de Barcelona, Martí i Franquès 1-11, E08028 Barcelona, Spain; Research Institute in Food Nutrition and Food Safety, Universitat de Barcelona, Av. Prat de la Riba 171, Edifici Recerca (Gaudí), E08921 Santa Coloma de Gramenet, Spain
| | - Sònia Sentellas
- Department of Chemical Engineering and Analytical Chemistry, Universitat de Barcelona, Martí i Franquès 1-11, E08028 Barcelona, Spain; Research Institute in Food Nutrition and Food Safety, Universitat de Barcelona, Av. Prat de la Riba 171, Edifici Recerca (Gaudí), E08921 Santa Coloma de Gramenet, Spain; Serra Húnter Fellow Programme, Generalitat de Catalunya, Via Laietana 2, E08003 Barcelona, Spain
| | - Oscar Núñez
- Department of Chemical Engineering and Analytical Chemistry, Universitat de Barcelona, Martí i Franquès 1-11, E08028 Barcelona, Spain; Research Institute in Food Nutrition and Food Safety, Universitat de Barcelona, Av. Prat de la Riba 171, Edifici Recerca (Gaudí), E08921 Santa Coloma de Gramenet, Spain; Serra Húnter Fellow Programme, Generalitat de Catalunya, Via Laietana 2, E08003 Barcelona, Spain.
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3
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Leon-Medina JX, Acosta-Opayome D, Fuenmayor CA, Zuluaga-Domínguez CM, Anaya M, Tibaduiza DA. Intelligent electronic tongue system for the classification of genuine and false honeys. INTERNATIONAL JOURNAL OF FOOD PROPERTIES 2023. [DOI: 10.1080/10942912.2022.2161571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
- Jersson X. Leon-Medina
- Department of Mechanical and Mechatronics Engineering, Universidad Nacional de Colombia – Sede Bogotá, Colombia
- Department of Mechatronics Engineering, Universidad de San Buenaventura Sede Bogotá, Bogotá, Colombia
| | - Diana Acosta-Opayome
- Facultad de Ciencias Agrarias, Posgrado en Ciencia y Tecnología de Alimentos, Universidad Nacional de Colombia – Sede Bogotá, Bogotá, Colombia
| | - Carlos Alberto Fuenmayor
- Instituto de Ciencia y Tecnología de Alimentos, Universidad Nacional de Colombia – Sede Bogotá, Bogotá, Colombia
| | - Carlos Mario Zuluaga-Domínguez
- Facultad de Ciencias Agrarias, Departamento de Desarrollo Rural y Agroalimentario, Universidad Nacional de Colombia – Sede Bogotá, Bogotá, Colombia
| | - Maribel Anaya
- Department of Electrical and Electronic Engineering, Universidad Nacional de Colombia – Sede Bogotá, Colombia
| | - Diego A Tibaduiza
- Department of Electrical and Electronic Engineering, Universidad Nacional de Colombia – Sede Bogotá, Colombia
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Oroian M, Dranca F, Ropciuc S, Pauliuc D. A comparative study regarding the adulteration detection of honey: Physicochemical parameters vs. impedimetric data. Curr Res Food Sci 2023; 7:100642. [PMID: 38115897 PMCID: PMC10728335 DOI: 10.1016/j.crfs.2023.100642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 11/02/2023] [Accepted: 11/13/2023] [Indexed: 12/21/2023] Open
Abstract
Honey adulteration is a major issue for European Union and its members because of an unfair practice of different producers and beekeepers, many adulterations involve the addition of sweet, concentrated syrups which may appear like honey. In our study we analysed the influence of adulteration of tilia honey with different syrups (such as corn, rice, inverted sugar, agave, maple syrups) in different percentages (5%, 10%, and 20% respectively) on physicochemical parameters (moisture content, L*, hab,cab, pH, free acidity, electrical conductivity (EC), 5-hydroxymetilfurfural (HMF), fructose, glucose, sucrose, turanose, trehalose, melesitose and raffinose) and impedimetric properties using electrochemical impedance spectroscopy. The impedimetric sensing was made using an electrochemical cell composed of two gold electrodes, and the frequency ranged between 0.1 kHz and 100 kHz. The impedimetric parameters (Z', Z″ and phase) and Randal circuit parameters can distinguish the authentic honeys from the adulterated ones (based on the adulteration agent and adulteration percentage, respectively). The partial least squares - discriminant analysis (PLS-DA) and support vector machines (SVM) were used in a binary mode to separate the authentic honeys from the adulterated ones, and the SVM proved to separate much better than PLS-DA.
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Affiliation(s)
- Mircea Oroian
- Faculty of Food Engineering, Stefan cel Mare University of Suceava, Romania
| | - Florina Dranca
- Faculty of Food Engineering, Stefan cel Mare University of Suceava, Romania
| | - Sorina Ropciuc
- Faculty of Food Engineering, Stefan cel Mare University of Suceava, Romania
| | - Daniela Pauliuc
- Faculty of Food Engineering, Stefan cel Mare University of Suceava, Romania
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Zhang XH, Gu HW, Liu RJ, Qing XD, Nie JF. A comprehensive review of the current trends and recent advancements on the authenticity of honey. Food Chem X 2023; 19:100850. [PMID: 37780275 PMCID: PMC10534224 DOI: 10.1016/j.fochx.2023.100850] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 08/15/2023] [Accepted: 08/26/2023] [Indexed: 10/03/2023] Open
Abstract
The authenticity of honey currently poses challenges to food quality control, thus requiring continuous modernization and improvement of related analytical methodologies. This review provides a comprehensively overview of honey authenticity challenges and related analytical methods. Firstly, direct and indirect methods of honey adulteration were described in detail, commenting the existing challenges in current detection methods and market supervision approaches. As an important part, the integrated metabolomic workflow involving sample processing procedures, instrumental analysis techniques, and chemometric tools in honey authenticity studies were discussed, with a focus on their advantages, disadvantages, and scopes. Among them, various improved microscale extraction methods, combined with hyphenated instrumental analysis techniques and chemometric data processing tools, have broad application potential in honey authenticity research. The future of honey authenticity determination will involve the use of simplified and portable methods, which will enable on-site rapid detection and transfer detection technologies from the laboratory to the industry.
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Affiliation(s)
- Xiao-Hua Zhang
- Department of Chemistry and Chemical Engineering, Hunan Institute of Science and Technology, Yueyang, China
- Henan Key Laboratory of Biomarker Based Rapid-detection Technology for Food Safety, Food and Pharmacy College, Xuchang University, Xuchang, China
| | - Hui-Wen Gu
- College of Chemistry and Environmental Engineering, Yangtze University, Jingzhou, China
| | - Ren-Jun Liu
- Collaborative Innovation Center for Water Pollution Control and Water Safety in Karst Area, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, China
| | - Xiang-Dong Qing
- Hunan Provincial Key Laboratory of Dark Tea and Jin-hua, College of Materials and Chemical Engineering, Hunan City University, Yiyang, China
| | - Jin-Fang Nie
- Collaborative Innovation Center for Water Pollution Control and Water Safety in Karst Area, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, China
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Abi-Rizk H, Jouan-Rimbaud Bouveresse D, Chamberland J, Cordella CBY. Recent developments of e-sensing devices coupled to data processing techniques in food quality evaluation: a critical review. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2023; 15:5410-5440. [PMID: 37818969 DOI: 10.1039/d3ay01132a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/13/2023]
Abstract
A greater demand for high-quality food is being driven by the growth of economic and technological advancements. In this context, consumers are currently paying special attention to organoleptic characteristics such as smell, taste, and appearance. Motivated to mimic human senses, scientists developed electronic devices such as e-noses, e-tongues, and e-eyes, to spot signals relative to different chemical substances prevalent in food systems. To interpret the information provided by the sensors' responses, multiple chemometric approaches are used depending on the aim of the study. This review based on the Web of Science database, endeavored to scrutinize three e-sensing systems coupled to chemometric approaches for food quality evaluation. A total of 122 eligible articles pertaining to the e-nose, e-tongue and e-eye devices were selected to conduct this review. Most of the performed studies used exploratory analysis based on linear factorial methods, while classification and regression techniques came in the second position. Although their applications have been less common in food science, it is to be noted that nonlinear approaches based on artificial intelligence and machine learning deployed in a big-data context have generally yielded better results for classification and regression purposes, providing new perspectives for future studies.
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Affiliation(s)
- Hala Abi-Rizk
- LAboratoire de Recherche et de Traitement de l'Information Chimiosensorielle - LARTIC, Institute of Nutrition and Functional Foods (INAF), Université Laval, Québec, QC, G1V 0A6, Canada.
| | | | - Julien Chamberland
- Department of Food Sciences, STELA Dairy Research Center, Institute of Nutrition and Functional Foods (INAF), Université Laval, Québec, QC, G1V 0A6, Canada
| | - Christophe B Y Cordella
- LAboratoire de Recherche et de Traitement de l'Information Chimiosensorielle - LARTIC, Institute of Nutrition and Functional Foods (INAF), Université Laval, Québec, QC, G1V 0A6, Canada.
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Biswas A, Naresh KS, Jaygadkar SS, Chaudhari SR. Enabling honey quality and authenticity with NMR and LC-IRMS based platform. Food Chem 2023; 416:135825. [PMID: 36924528 DOI: 10.1016/j.foodchem.2023.135825] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 12/22/2022] [Accepted: 02/27/2023] [Indexed: 03/04/2023]
Abstract
Honey has been known for economically motivated adulteration around the world, because of its high demand and short supply. As consequence increasing honey production using the deliberate addition of sugar syrups while claiming a fictitious origin and diversifying it to increase its value. Generally, honey testing is supervised by a set of guidelines and quality parameters to ensure its quality and authenticity. As per the many regulatory bodies, current honey scams have been challenging to identify with conventional methods, so quality control labs require sophisticated technology. With these paradigm shifts, the aim of the present review is focused on the authenticity of honey through two important cutting-edge methods viz LC-IRMS and NMR. The LC-IRMS aids in the detection of added C3 and C4 sugars. Whereas NMR has provided a potent solution by allowing the classification of botanical varieties and geographical origin along with the quantification of a set of quality parameters in a single experiment.
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Affiliation(s)
- Anisha Biswas
- Department of Plantation Products, Spice and Flavor Technology, CSIR-Central Food Technological Research Institute, Mysore, Karnataka 570020, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - K S Naresh
- Department of Plantation Products, Spice and Flavor Technology, CSIR-Central Food Technological Research Institute, Mysore, Karnataka 570020, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | | | - Sachin R Chaudhari
- Department of Plantation Products, Spice and Flavor Technology, CSIR-Central Food Technological Research Institute, Mysore, Karnataka 570020, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India.
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8
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NADES-modified voltammetric sensors and information fusion for detection of honey heat alteration. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.109144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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9
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Brar DS, Pant K, Krishna R, Kaur S, Rasane P, Nanda V, Saxena S, Gautam S. A comprehensive review on unethical honey: Validation by emerging techniques. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.109482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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10
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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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Rufo M, Jiménez A, Paniagua JM, González-Mohíno A. Ultrasound Assessment of Honey Using Fast Fourier Transform. SENSORS 2021; 21:s21206748. [PMID: 34695961 PMCID: PMC8537696 DOI: 10.3390/s21206748] [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: 09/14/2021] [Revised: 09/28/2021] [Accepted: 10/08/2021] [Indexed: 11/19/2022]
Abstract
Ultrasound inspection permits the characteristics of some foodstuffs to be determined easily and cheaply. This experimental study included the determination of various ultrasound parameters provided by the fast Fourier transform (FFT) which had not previously been considered in testing the physical properties of different varieties of honey. These parameters are practically independent of the criteria adopted for their calculation, unlike other ultrasound variables such as pulse velocity or attenuation whose determination can vary depending on those criteria. The study was carried out on four varieties of honey (Eucalyptus, Heather, Thyme, and Thousand Flowers) using 500-kHz transducers. A simultaneously performed honey texture analysis (Texture Profile Analysis-TPA) showed significant linear correlations between the ultrasound variables provided by FFT and the texture parameters. The FFT parameters distinguished between each of the four honey varieties studied.
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Affiliation(s)
- Montaña Rufo
- Department of Applied Physics, School of Technology, University of Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, Spain; (M.R.); (J.M.P.)
- Research Institute of Meat and Meat Product, University of Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, Spain;
| | - Antonio Jiménez
- Department of Applied Physics, School of Technology, University of Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, Spain; (M.R.); (J.M.P.)
- Research Institute of Meat and Meat Product, University of Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, Spain;
- Correspondence:
| | - Jesús M. Paniagua
- Department of Applied Physics, School of Technology, University of Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, Spain; (M.R.); (J.M.P.)
- Research Institute of Meat and Meat Product, University of Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, Spain;
| | - Alberto González-Mohíno
- Research Institute of Meat and Meat Product, University of Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, Spain;
- Department of Food Technology, Faculty of Veterinary, University of Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, Spain
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