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Meliana C, Liu J, Show PL, Low SS. Biosensor in smart food traceability system for food safety and security. Bioengineered 2024; 15:2310908. [PMID: 38303521 PMCID: PMC10841032 DOI: 10.1080/21655979.2024.2310908] [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: 11/12/2023] [Accepted: 01/23/2024] [Indexed: 02/03/2024] Open
Abstract
The burden of food contamination and food wastage has significantly contributed to the increased prevalence of foodborne disease and food insecurity all over the world. Due to this, there is an urgent need to develop a smarter food traceability system. Recent advancements in biosensors that are easy-to-use, rapid yet selective, sensitive, and cost-effective have shown great promise to meet the critical demand for onsite and immediate diagnosis and treatment of food safety and quality control (i.e. point-of-care technology). This review article focuses on the recent development of different biosensors for food safety and quality monitoring. In general, the application of biosensors in agriculture (i.e. pre-harvest stage) for early detection and routine control of plant infections or stress is discussed. Afterward, a more detailed advancement of biosensors in the past five years within the food supply chain (i.e. post-harvest stage) to detect different types of food contaminants and smart food packaging is highlighted. A section that discusses perspectives for the development of biosensors in the future is also mentioned.
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Affiliation(s)
- Catarina Meliana
- Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, University of Nottingham Ningbo China, Ningbo, Zhejiang Province, China
| | - Jingjing Liu
- College of Automation Engineering, Northeast Electric Power University, Jilin, Jilin Province, China
| | - Pau Loke Show
- Department of Chemical Engineering, Khalifa University, Abu Dhabi, Abu Dhabi Municipality, United Arab Emirates
- Department of Chemical and Environmental Engineering, Faculty of Science and Engineering, University of Nottingham Malaysia, Semenyih, Selangor Darul Ehsan, Malaysia
| | - Sze Shin Low
- Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, University of Nottingham Ningbo China, Ningbo, Zhejiang Province, China
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Kiani H, Beheshti B, Borghei AM, Rahmati MH. Determination of heavy metals in edible oils by a novel voltammetry taste sensor array. JOURNAL OF FOOD SCIENCE AND TECHNOLOGY 2024; 61:1126-1137. [PMID: 38562596 PMCID: PMC10981641 DOI: 10.1007/s13197-024-05933-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Revised: 12/17/2023] [Accepted: 01/09/2024] [Indexed: 04/04/2024]
Abstract
Herein, a novel voltammetry taste sensor array (VTSA) using pencil graphite electrode, screen-printed electrode, and glassy carbon electrode was used to identify heavy metals (HM) including Cad, Pb, Sn and Ni in soybean and rapeseed oils. HMs were added to edible oils at three concentrations of 0.05, 0.1 and 0.25 ppm, and then, the output of the device was classified using a chemometric classification method. According to the principal component analysis results, PG electrode explains 96% and 81% of the variance between the data in rapeseed and soybean edible oils, respectively. Additionally, the SP electrode explains 91% of the variance between the data in rapeseed and soybean oils. Moreover, the GC electrode explains 100% and 99% of the variance between the data in rapeseed and soybean edible oils, respectively. K-nearest neighbor exhibited high capability in classifying HMs in edible oils. In addition, partial least squares in the combine of VTSA shows a predict 99% in rapeseed oil. The best electrode for soybean edible oil was GC.
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Affiliation(s)
- Hasan Kiani
- Department of Biosystem Mechanical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Babak Beheshti
- Department of Biosystem Mechanical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Ali Mohammad Borghei
- Department of Biosystem Mechanical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Mohammad Hashem Rahmati
- Department of Biosystem Mechanical Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgān, Iran
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Nobari Moghaddam H, Tamiji Z, Amini M, Khoshayand MR, Kobarfrad F, Sadeghi N, Hajimahmoodi M. Development of non-destructive methods for the assessment of authenticity of sports whey protein supplements. Food Addit Contam Part A Chem Anal Control Expo Risk Assess 2024; 41:339-351. [PMID: 38319919 DOI: 10.1080/19440049.2024.2311218] [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: 10/11/2023] [Accepted: 01/23/2024] [Indexed: 02/08/2024]
Abstract
In the category of sports supplements, whey protein powder is one of the popular supplements for muscle building applications. Therefore, verification of the sport supplements as authentic products has become a universal concern. This work aimed to propose vibrational spectroscopy including near infrared (NIR) and infrared (IR) as rapid and non-destructive testing tools for the detection and quantification of maltodextrin, milk powder and milk whey powder in whey protein supplements. Initially, principal component analysis was applied to data for pattern recognition and the results displayed a fine pattern of discrimination. Partial least square discrimination analysis (PLS-DA) and K-nearest neighbours (KNN) were exploited as supervised method modelling classification. This process was done in order to respond to two vital questions whether the sample is adulterated or not and what is the kind of adulteration. PLS-DA showed better classification results rather than KNN according to the figure of merits of the model. Partial least square regression (PLSR) was employed on pre-treated spectra to quantify the amount of adulteration in sport whey supplements. Eventually, it seems vibrational spectroscopy could be implemented as a simple, and low-cost analysis method for the detection and quantification of mentioned adulterants in whey protein supplements.
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Affiliation(s)
- Hanieh Nobari Moghaddam
- Department of Drug and Food Control, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
| | - Zahra Tamiji
- Department of Drug and Food Control, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
- Department of Chemometrics, The Institute of Pharmaceutical Sciences, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohsen Amini
- Department of Medicinal Chemistry and Pharmaceutical Sciences Research Center, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Reza Khoshayand
- Department of Drug and Food Control, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
- Department of Chemometrics, The Institute of Pharmaceutical Sciences, Tehran University of Medical Sciences, Tehran, Iran
| | - Farzad Kobarfrad
- Department of Medicinal Chemistry, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Naficeh Sadeghi
- Department of Drug and Food Control, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
| | - Mannan Hajimahmoodi
- Department of Drug and Food Control, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
- Pharmaceutical Quality Assurance Research Center, The Institute of Pharmaceutical Sciences (TIPS), Tehran University of Medical Sciences, Tehran, Iran
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Smaoui S, Tarapoulouzi M, Agriopoulou S, D'Amore T, Varzakas T. Current State of Milk, Dairy Products, Meat and Meat Products, Eggs, Fish and Fishery Products Authentication and Chemometrics. Foods 2023; 12:4254. [PMID: 38231684 DOI: 10.3390/foods12234254] [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: 11/11/2023] [Revised: 11/21/2023] [Accepted: 11/22/2023] [Indexed: 01/19/2024] Open
Abstract
Food fraud is a matter of major concern as many foods and beverages do not follow their labelling. Because of economic interests, as well as consumers' health protection, the related topics, food adulteration, counterfeiting, substitution and inaccurate labelling, have become top issues and priorities in food safety and quality. In addition, globalized and complex food supply chains have increased rapidly and contribute to a growing problem affecting local, regional and global food systems. Animal origin food products such as milk, dairy products, meat and meat products, eggs and fish and fishery products are included in the most commonly adulterated food items. In order to prevent unfair competition and protect the rights of consumers, it is vital to detect any kind of adulteration to them. Geographical origin, production methods and farming systems, species identification, processing treatments and the detection of adulterants are among the important authenticity problems for these foods. The existence of accurate and automated analytical techniques in combination with available chemometric tools provides reliable information about adulteration and fraud. Therefore, the purpose of this review is to present the advances made through recent studies in terms of the analytical techniques and chemometric approaches that have been developed to address the authenticity issues in animal origin food products.
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Affiliation(s)
- Slim Smaoui
- Laboratory of Microbial, Enzymatic Biotechnology, and Biomolecules (LBMEB), Center of Biotechnology of Sfax, University of Sfax-Tunisia, Sfax 3029, Tunisia
| | - Maria Tarapoulouzi
- Department of Chemistry, Faculty of Pure and Applied Science, University of Cyprus, P.O. Box 20537, Nicosia CY-1678, Cyprus
| | - Sofia Agriopoulou
- Department of Food Science and Technology, University of the Peloponnese, Antikalamos, 24100 Kalamata, Greece
| | - Teresa D'Amore
- IRCCS CROB, Centro di Riferimento Oncologico della Basilicata, 85028 Rionero in Vulture, Italy
| | - Theodoros Varzakas
- Department of Food Science and Technology, University of the Peloponnese, Antikalamos, 24100 Kalamata, Greece
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Windarsih A, Bakar NKA, Dachriyanus, Yuliana ND, Riswanto FDO, Rohman A. Analysis of Pork in Beef Sausages Using LC-Orbitrap HRMS Untargeted Metabolomics Combined with Chemometrics for Halal Authentication Study. Molecules 2023; 28:5964. [PMID: 37630216 PMCID: PMC10459517 DOI: 10.3390/molecules28165964] [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: 07/21/2023] [Accepted: 08/07/2023] [Indexed: 08/27/2023] Open
Abstract
Beef sausage (BS) is one of the most favored meat products due to its nutrition and good taste. However, for economic purposes, BS is often adulterated with pork by unethical players. Pork consumption is strictly prohibited for religions including Islam and Judaism. Therefore, advanced detection methods are highly required to warrant the halal authenticity of BS. This research aimed to develop a liquid chromatography-high-resolution mass spectrometry (LC-HRMS) method to determine the halal authenticity of BS using an untargeted metabolomics approach. LC-HRMS was capable of detecting various metabolites in BS and BS containing pork. The presence of pork in BS could be differentiated using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) with high accuracy. PLS-DA perfectly classified authentic BS and BS containing pork in all concentration levels of pork with R2X = (0.821), R2Y(= 0.984), and Q2 = (0.795). The level of pork in BS was successfully predicted through partial least squares (PLS) and orthogonal PLS (OPLS) chemometrics. Both models gave high R2 (>0.99) actual and predicted values as well as few errors, indicating good accuracy and precision. Identification of discriminating metabolites' potential as biomarker candidates through variable importance for projections (VIP) value revealed metabolites of 2-arachidonyl-sn-glycero-3-phosphoethanolamine, 3-hydroxyoctanoylcarnitine, 8Z,11Z,14Z-eicosatrienoic acid, D-(+)-galactose, oleamide, 3-hydroxyhexadecanoylcarnitine, arachidonic acid, and α-eleostearic acid as good indicators to detect pork. It can be concluded that LC-HRMS metabolomics combined with PCA, PLS-DA, PLS, and OPLS was successfully used to detect pork adulteration in beef sausages. The results imply that LC-HRMS untargeted metabolomics in combination with chemometrics is a promising alternative as an analytical technique to detect pork in sausage products. Further analysis of larger samples is required to warrant the reproducibility.
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Affiliation(s)
- Anjar Windarsih
- Department of Chemistry, Faculty of Science, Universiti Malaya, Kuala Lumpur 50603, Malaysia; (A.W.); (N.K.A.B.)
- Research Center for Food Technology and Processing (PRTPP), National Research and Innovation Agency (BRIN), Yogyakarta 55861, Indonesia
| | - Nor Kartini Abu Bakar
- Department of Chemistry, Faculty of Science, Universiti Malaya, Kuala Lumpur 50603, Malaysia; (A.W.); (N.K.A.B.)
| | - Dachriyanus
- Faculty of Pharmacy, Andalas University, Padang 25175, Indonesia;
| | - Nancy Dewi Yuliana
- Department of Food Science and Technology, IPB University, Bogor 16680, Indonesia;
- Halal Science Center, IPB University, Bogor 16129, Indonesia
| | - Florentinus Dika Octa Riswanto
- Division of Pharmaceutical Analysis and Medicinal Chemistry, Faculty of Pharmacy, Campus III Paingan, Universitas Sanata Dharma, Yogyakarta 55282, Indonesia;
| | - Abdul Rohman
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
- Center of Excellence, Institute for Halal Industry and Systems (PUIPT-IHIS), Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
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A comprehensive overview of emerging techniques and chemometrics for authenticity and traceability of animal-derived food. Food Chem 2023; 402:134216. [DOI: 10.1016/j.foodchem.2022.134216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 08/21/2022] [Accepted: 09/09/2022] [Indexed: 11/17/2022]
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Grassi S, Tarapoulouzi M, D’Alessandro A, Agriopoulou S, Strani L, Varzakas T. How Chemometrics Can Fight Milk Adulteration. Foods 2022; 12:foods12010139. [PMID: 36613355 PMCID: PMC9819000 DOI: 10.3390/foods12010139] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Revised: 12/10/2022] [Accepted: 12/22/2022] [Indexed: 12/29/2022] Open
Abstract
Adulteration and fraud are amongst the wrong practices followed nowadays due to the attitude of some people to gain more money or their tendency to mislead consumers. Obviously, the industry follows stringent controls and methodologies in order to protect consumers as well as the origin of the food products, and investment in these technologies is highly critical. In this context, chemometric techniques proved to be very efficient in detecting and even quantifying the number of substances used as adulterants. The extraction of relevant information from different kinds of data is a crucial feature to achieve this aim. However, these techniques are not always used properly. In fact, training is important along with investment in these technologies in order to cope effectively and not only reduce fraud but also advertise the geographical origin of the various food and drink products. The aim of this paper is to present an overview of the different chemometric techniques (from clustering to classification and regression applied to several analytical data) along with spectroscopy, chromatography, electrochemical sensors, and other on-site detection devices in the battle against milk adulteration. Moreover, the steps which should be followed to develop a chemometric model to face adulteration issues are carefully presented with the required critical discussion.
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Affiliation(s)
- Silvia Grassi
- Department of Food, Environmental and Nutritional Sciences (DeFENS), Università degli Studi di Milano, Via Celoria, 2, 20133 Milano, Italy
| | - Maria Tarapoulouzi
- Department of Chemistry, Faculty of Pure and Applied Science, University of Cyprus, P.O. Box 20537, Nicosia CY-1678, Cyprus
| | - Alessandro D’Alessandro
- Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Via Campi 103, 41125 Modena, Italy
| | - Sofia Agriopoulou
- Department of Food Science and Technology, University of the Peloponnese, Antikalamos, 24100 Kalamata, Greece
| | - Lorenzo Strani
- Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Via Campi 103, 41125 Modena, Italy
- Correspondence: (L.S.); (T.V.)
| | - Theodoros Varzakas
- Department of Food Science and Technology, University of the Peloponnese, Antikalamos, 24100 Kalamata, Greece
- Correspondence: (L.S.); (T.V.)
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He Y, Zeng W, Zhao Y, Zhu X, Wan H, Zhang M, Li Z. Rapid detection of adulteration of goat milk and goat infant formulas using near-infrared spectroscopy fingerprints. Int Dairy J 2022. [DOI: 10.1016/j.idairyj.2022.105536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Kang M, Wang H, Shi X, Chen H, Suo R. Goat milk authentication based on amino acid ratio and chemometric analysis. J Food Compost Anal 2022. [DOI: 10.1016/j.jfca.2022.104636] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Tian H, Chen S, Li D, Lou X, Chen C, Yu H. Simultaneous detection for adulterations of maltodextrin, sodium carbonate, and whey in raw milk using Raman spectroscopy and chemometrics. J Dairy Sci 2022; 105:7242-7252. [PMID: 35863924 DOI: 10.3168/jds.2021-21082] [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: 07/29/2021] [Accepted: 04/04/2022] [Indexed: 11/19/2022]
Abstract
To achieve rapid on-site identification of raw milk adulteration and simultaneously quantify the levels of various adulterants, we combined Raman spectroscopy with chemometrics to detect 3 of the most common adulterants. Raw milk was artificially adulterated with maltodextrin (0.5-15.0%; wt/wt), sodium carbonate (10-100 mg/kg), or whey (1.0-20.0%; wt/wt). Partial least square discriminant analysis (PLS-DA) classification and a partial least square (PLS) regression model were established using Raman spectra of 144 samples, among which 108 samples were used for training and 36 were used for validation. A model with excellent performance was obtained by spectral preprocessing with first derivative, and variable selection optimization with variable importance in the projection. The classification accuracy of the PLS-DA model was 95.83% for maltodextrin, 100% for sodium carbonate, 95.84% for whey, and 92.25% for pure raw milk. The PLS model had a detection limit of 1.46% for maltodextrin, 4.38 mg/kg for sodium carbonate, and 2.64% for whey. These results suggested that Raman spectroscopy combined with PLS-DA and PLS model can rapidly and efficiently detect adulterants of maltodextrin, sodium carbonate, and whey in raw milk.
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Affiliation(s)
- Huaixiang Tian
- School of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai 201418, P.R. China
| | - Shuang Chen
- School of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai 201418, P.R. China
| | - Dan Li
- School of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai 201418, P.R. China
| | - Xinman Lou
- School of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai 201418, P.R. China
| | - Chen Chen
- School of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai 201418, P.R. China
| | - Haiyan Yu
- School of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai 201418, P.R. China.
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Lelis CA, Galvan D, Tessaro L, de Andrade JC, Mutz YS, Conte-Junior CA. Fluorescence spectroscopy in tandem with chemometric tools applied to milk quality control. J Food Compost Anal 2022. [DOI: 10.1016/j.jfca.2022.104515] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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Arifah MF, Irnawati, Ruslin, Nisa K, Windarsih A, Rohman A. The Application of FTIR Spectroscopy and Chemometrics for the Authentication Analysis of Horse Milk. INTERNATIONAL JOURNAL OF FOOD SCIENCE 2022; 2022:7643959. [PMID: 35242875 PMCID: PMC8888094 DOI: 10.1155/2022/7643959] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 01/18/2022] [Accepted: 01/25/2022] [Indexed: 12/02/2022]
Abstract
Expensive milk such as horse's milk (HM) may be the target of adulteration by other milk such as goat's milk (GM) and cow's milk (CM). FTIR spectroscopy in combination with chemometrics of linear discriminant analysis (LDA) and multivariate calibrations of partial least square regression (PLSR) and principal component regression (PCR) was used for authentication of HM from GM and CM. Milk was directly subjected to attenuated total reflectance (ATR) spectral measurement at midinfrared regions (4000-650 cm-1). Results showed that LDA could make clear discrimination between HM and HM adulterated with CM and GM without any misclassification observed. PLSR using 2nd derivative spectra at 3200-2800 and 1300-1000 cm-1 provided the best model for the relationship between actual values of GM and FTIR predicted values than PCR. At this condition, R 2 values for calibration and validation models obtained were 0.9995 and 0.9612 with RMSEC and RMSEP values of 0.0093 and 0.0794. PLSR using normal FTIR spectra at 3800-3000 and 1500-1000 cm-1 offered R 2 for the relationship between actual values of CM and FTIR predicted values of >0.99 in calibration and validation models with low errors of RMSEC of 0.0164 and RMSEP of 0.0336 during authentication of HM from CM. Therefore, FTIR spectroscopy in combination with LDA and PLSR is an effective method for authentication of HM from GM and CM.
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Affiliation(s)
- Mitsalina Fildzah Arifah
- Center of Excellence, Institute for Halal Industry and Systems, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
| | - Irnawati
- Faculty of Pharmacy, Halu Oleo University, Kendari 93232, Indonesia
| | - Ruslin
- Faculty of Pharmacy, Halu Oleo University, Kendari 93232, Indonesia
| | - Khoirun Nisa
- Research Division for Natural Product Technology (BPTBA), National Research and Innovation Agency (BRIN), Yogyakarta 55861, Indonesia
| | - Anjar Windarsih
- Research Division for Natural Product Technology (BPTBA), National Research and Innovation Agency (BRIN), Yogyakarta 55861, Indonesia
| | - Abdul Rohman
- Center of Excellence, Institute for Halal Industry and Systems, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
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Sert D, Mercan E. Production and characterisation of goat milk powder made from sonicated whole milk concentrates. Int Dairy J 2022. [DOI: 10.1016/j.idairyj.2022.105333] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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PLS-R Calibration Models for Wine Spirit Volatile Phenols Prediction by Near-Infrared Spectroscopy. SENSORS 2021; 22:s22010286. [PMID: 35009831 PMCID: PMC8749750 DOI: 10.3390/s22010286] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 12/24/2021] [Accepted: 12/29/2021] [Indexed: 11/30/2022]
Abstract
Near-infrared spectroscopic (NIR) technique was used, for the first time, to predict volatile phenols content, namely guaiacol, 4-methyl-guaiacol, eugenol, syringol, 4-methyl-syringol and 4-allyl-syringol, of aged wine spirits (AWS). This study aimed to develop calibration models for the volatile phenol’s quantification in AWS, by NIR, faster and without sample preparation. Partial least square regression (PLS-R) models were developed with NIR spectra in the near-IR region (12,500–4000 cm−1) and those obtained from GC-FID quantification after liquid-liquid extraction. In the PLS-R developed method, cross-validation with 50% of the samples along a validation test set with 50% of the remaining samples. The final calibration was performed with 100% of the data. PLS-R models with a good accuracy were obtained for guaiacol (r2 = 96.34; RPD = 5.23), 4-methyl-guaiacol (r2 = 96.1; RPD = 5.07), eugenol (r2 = 96.06; RPD = 5.04), syringol (r2 = 97.32; RPD = 6.11), 4-methyl-syringol (r2 = 95.79; RPD = 4.88) and 4-allyl-syringol (r2 = 95.97; RPD = 4.98). These results reveal that NIR is a valuable technique for the quality control of wine spirits and to predict the volatile phenols content, which contributes to the sensory quality of the spirit beverages.
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Teixeira JLDP, Caramês ETDS, Baptista DP, Gigante ML, Pallone JAL. Adulteration Detection in Goat Dairy Beverage Through NIR Spectroscopy and DD-SIMCA. FOOD ANAL METHOD 2021. [DOI: 10.1007/s12161-021-02151-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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dos Santos Pereira EV, de Sousa Fernandes DD, de Araújo MCU, Diniz PHGD, Maciel MIS. In-situ authentication of goat milk in terms of its adulteration with cow milk using a low-cost portable NIR spectrophotometer. Microchem J 2021. [DOI: 10.1016/j.microc.2020.105885] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
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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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20
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Yazgan NN, Genis HE, Bulat T, Topcu A, Durna S, Yetisemiyen A, Boyaci IH. Discrimination of milk species using Raman spectroscopy coupled with partial least squares discriminant analysis in raw and pasteurized milk. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2020; 100:4756-4765. [PMID: 32458436 DOI: 10.1002/jsfa.10534] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 04/30/2020] [Accepted: 05/26/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Heat treatment is the most common practice for the microbiological safety of milk; hence, determination of the heat treatment of milk is essential. Also, mislabeling or adulteration of expensive milk samples, like ewe or goat milk, with cow's milk is a growing problem in the dairy market. Thus, the determination of the authenticity of milk samples has crucial importance for both producers and consumers. The aim of this study was to discriminate milk samples using Raman spectroscopy with partial least squares discriminant analysis (PLS-DA), first with regard to whether the milk was heat-treated or not, and second with regard to species (cow, goat, ewe, mixture (adulterated)) in both raw and pasteurized milk. RESULTS First, discrimination of milk samples as raw or pasteurized was achieved using PLS-DA. Both in calibration and prediction models, high sensitivity and specificity values were obtained for raw and pasteurized milk samples. Second, the proposed method also discriminated milk samples according to their species (cow, goat, ewe, and mixture) for both raw and pasteurized milk. In both calibration and prediction models, the sensitivity and specificity values were above 0.857 and 0.897 respectively. Also, the accuracy values were above 0.915. The results obtained denote satisfactory accurate classification of the samples. CONCLUSION The results suggest that Raman spectroscopy coupled with PLS-DA can be successfully used to discriminate milk samples according to heat treatment (raw/pasteurized) and their species within 20 s per sample. It was seen that Raman spectra provide valuable information to be used especially for discrimination of milk samples according to their origin. © 2020 Society of Chemical Industry.
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Affiliation(s)
- Nazife N Yazgan
- Department of Food Engineering, Faculty of Engineering, Hacettepe University, Ankara, Turkey
| | - Huseyin E Genis
- Department of Food Engineering, Faculty of Engineering, Hacettepe University, Ankara, Turkey
| | - Tugba Bulat
- Department of Food Engineering, Faculty of Engineering, Hacettepe University, Ankara, Turkey
| | - Ali Topcu
- Department of Food Engineering, Faculty of Engineering, Hacettepe University, Ankara, Turkey
| | - Sahin Durna
- Department of Dairy Technology, Ankara University, Diskapi, Ankara, Turkey
- Atatürk Forestry Farm, Ankara, Turkey
| | - Atila Yetisemiyen
- Department of Dairy Technology, Ankara University, Diskapi, Ankara, Turkey
| | - Ismail H Boyaci
- Department of Food Engineering, Faculty of Engineering, Hacettepe University, Ankara, Turkey
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21
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Hassoun A, Måge I, Schmidt WF, Temiz HT, Li L, Kim HY, Nilsen H, Biancolillo A, Aït-Kaddour A, Sikorski M, Sikorska E, Grassi S, Cozzolino D. Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years. Foods 2020; 9:E1069. [PMID: 32781687 PMCID: PMC7466239 DOI: 10.3390/foods9081069] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 07/29/2020] [Accepted: 08/01/2020] [Indexed: 12/27/2022] Open
Abstract
Animal origin food products, including fish and seafood, meat and poultry, milk and dairy foods, and other related products play significant roles in human nutrition. However, fraud in this food sector frequently occurs, leading to negative economic impacts on consumers and potential risks to public health and the environment. Therefore, the development of analytical techniques that can rapidly detect fraud and verify the authenticity of such products is of paramount importance. Traditionally, a wide variety of targeted approaches, such as chemical, chromatographic, molecular, and protein-based techniques, among others, have been frequently used to identify animal species, production methods, provenance, and processing of food products. Although these conventional methods are accurate and reliable, they are destructive, time-consuming, and can only be employed at the laboratory scale. On the contrary, alternative methods based mainly on spectroscopy have emerged in recent years as invaluable tools to overcome most of the limitations associated with traditional measurements. The number of scientific studies reporting on various authenticity issues investigated by vibrational spectroscopy, nuclear magnetic resonance, and fluorescence spectroscopy has increased substantially over the past few years, indicating the tremendous potential of these techniques in the fight against food fraud. It is the aim of the present manuscript to review the state-of-the-art research advances since 2015 regarding the use of analytical methods applied to detect fraud in food products of animal origin, with particular attention paid to spectroscopic measurements coupled with chemometric analysis. The opportunities and challenges surrounding the use of spectroscopic techniques and possible future directions will also be discussed.
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Affiliation(s)
- Abdo Hassoun
- Nofima AS, Norwegian Institute of Food, Fisheries, and Aquaculture Research, Muninbakken 9-13, 9291 Tromsø, Norway; (I.M.); (H.N.)
| | - Ingrid Måge
- Nofima AS, Norwegian Institute of Food, Fisheries, and Aquaculture Research, Muninbakken 9-13, 9291 Tromsø, Norway; (I.M.); (H.N.)
| | - Walter F. Schmidt
- United States Department of Agriculture, Agricultural Research Service, 10300 Baltimore Avenue, Beltsville, MD 20705-2325, USA;
| | - Havva Tümay Temiz
- Department of Food Engineering, Bingol University, 12000 Bingol, Turkey;
| | - Li Li
- Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, China;
| | - Hae-Yeong Kim
- Department of Food Science and Biotechnology, Kyung Hee University, Yongin 17104, Korea;
| | - Heidi Nilsen
- Nofima AS, Norwegian Institute of Food, Fisheries, and Aquaculture Research, Muninbakken 9-13, 9291 Tromsø, Norway; (I.M.); (H.N.)
| | - Alessandra Biancolillo
- Department of Physical and Chemical Sciences, University of L’Aquila, 67100 Via Vetoio, Coppito, L’Aquila, Italy;
| | | | - Marek Sikorski
- Faculty of Chemistry, Adam Mickiewicz University in Poznan, Uniwersytetu Poznanskiego 8, 61-614 Poznan, Poland;
| | - Ewa Sikorska
- Institute of Quality Science, Poznań University of Economics and Business, al. Niepodległości 10, 61-875 Poznań, Poland;
| | - Silvia Grassi
- Department of Food, Environmental and Nutritional Sciences (DeFENS), Università degli Studi di Milano, via Celoria, 2, 20133 Milano, Italy;
| | - Daniel Cozzolino
- Centre for Nutrition and Food Sciences, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, 39 Kessels Rd, Coopers Plains, QLD 4108, Australia;
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22
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Caramês ETDS, Piacentini KC, Alves LT, Pallone JAL, Rocha LDO. NIR spectroscopy and chemometric tools to identify high content of deoxynivalenol in barley. Food Addit Contam Part A Chem Anal Control Expo Risk Assess 2020; 37:1542-1552. [PMID: 32717175 DOI: 10.1080/19440049.2020.1778189] [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] [Indexed: 10/23/2022]
Abstract
Deoxynivalenol (DON) is one of the mycotoxins produced mainly by the Fusarium graminearum species complex in small grain cereals, including barley. This toxin can cause alimentary disorders, immune function depression and gastroenteritis. The negative health effects associated with DON coupled to the increasing concern about green and rapid methods of analysis motivated this study. In this context, near infrared (NIR) spectroscopy data were applied for exploratory analysis to distinguish barley with high and low levels of DON contamination (> or <1250 µg/kg according to the European Union threshold), by Partial Least Squares-Discriminant Analysis (PLS-DA), and to verify the performance of Partial Least Squares-Regression (PLS-R) to predict DON concentration in barley samples. Maximum values of specificity and sensitivity were achieved in the calibration set; 90.9% and 81.9% were observed in the cross-validation set for the PLS-DA classification model. PLS-R quantification of DON in barley presented low values of error (RMSEC = 101.94 µg/kg and RMSEP = 160.76 µg/kg). Thus, we found that NIR in combination with adequate chemometric tools could be applied as a green technique to monitor DON contamination in barley.
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Affiliation(s)
| | - Karim C Piacentini
- Department of Food Science, School of Food Engineering, State University of Campinas , Campinas, São Paulo, Brazil
| | - Lucas Teixeira Alves
- Department of Food Science, School of Food Engineering, State University of Campinas , Campinas, São Paulo, Brazil
| | - Juliana Azevedo Lima Pallone
- Department of Food Science, School of Food Engineering, State University of Campinas , Campinas, São Paulo, Brazil
| | - Liliana de Oliveira Rocha
- Department of Food Science, School of Food Engineering, State University of Campinas , Campinas, São Paulo, Brazil
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23
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Screening of Different Ageing Technologies of Wine Spirit by Application of Near-Infrared (NIR) Spectroscopy and Volatile Quantification. Processes (Basel) 2020. [DOI: 10.3390/pr8060736] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
The traditional ageing of wine spirits is done in wooden barrels, however, high costs have led to the search for alternative technologies, such as the use of stainless steel tanks with wooden staves and the application of micro-oxygenation. This work evaluates the changes in the major volatile compounds of wine spirits aged for 6, 12 and 18 months in wooden barrels and stainless steel tanks with micro-oxygenation. For both ageing technologies, two types of wood (Limousin oak and Portuguese chestnut wood) were used. The samples were analysed concerning their alcohol strength (electronic densimetry) and volatile composition, namely of methanol, acetaldehyde, ethyl acetate and other major volatile compounds ((GC-FID) and near-infrared spectroscopy (NIR)). The results show that the ageing technology was more influential than the wood species for the volatile composition of wine spirits, namely acetaldedehyde, methanol, 2-methylpropan-1-ol and 2+3-methylbutan-1-ol. However, the opposite behaviour was found for the spectral data. The ageing process was accelerated by using the alternative ageing technology, especially with chestnut wood staves. The most informative spectral regions to discriminate samples were around 6859 cm−1 and from 5200 cm−1 to 4200 cm−1. NIR is a promising technique to identify different technologies and different wood species used in the ageing process of wine spirits.
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Alamar PD, Caramês ETS, Poppi RJ, Pallone JAL. Detection of Fruit Pulp Adulteration Using Multivariate Analysis: Comparison of NIR, MIR and Data Fusion Performance. FOOD ANAL METHOD 2020. [DOI: 10.1007/s12161-020-01755-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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