1
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Hu L, Zhu Y, Zhang H, Zhang X, Li Y, Yao Q, Cai Q, Hu Y. Differentiation of three commercial tuna species through GC-Q-TOF and UPLC-Q/Orbitrap mass spectrometry-based metabolomics and chemometrics. Food Chem 2024; 452:139603. [PMID: 38754166 DOI: 10.1016/j.foodchem.2024.139603] [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: 10/09/2023] [Revised: 04/22/2024] [Accepted: 05/07/2024] [Indexed: 05/18/2024]
Abstract
Food fraud is common in the tuna industry because of the economic benefits involved. Ensuring the authenticity of tuna species is crucial for protecting both consumers and tuna stocks. In this study, GC-Q-TOF and UPLC-Q/Orbitrap mass spectrometry-based metabolomics were used to investigate the metabolite profiles of three commercial tuna species (skipjack tuna, bigeye tuna and yellowfin tuna). A total of 22 and 77 metabolites were identified with high confidence using GC-Q-TOF and UPLC-Q/Orbitrap mass spectrometry, respectively. Further screening via chemometrics revealed that 38 metabolites could potentially serve as potential biomarkers. Hierarchical cluster analysis showed that the screened metabolite biomarkers successfully distinguished the three tested tuna species. Furthermore, a total of 27 metabolic pathways were identified through enrichment analysis based on the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathways.
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Affiliation(s)
- Lingping Hu
- Yangtze Delta Region Institute of Tsinghua University, Zhejiang 314006, China; College of Food Science and Engineering, Yazhou Bay Innovation Institute, Hainan Tropical Ocean University, Marine Food Engineering Technology Research Center of Hainan Province, Collaborative Innovation Center of Marine Food Deep Processing, Hainan Key Laboratory of Herpetological Research, Sanya 572022, China
| | - Yin Zhu
- Yangtze Delta Region Institute of Tsinghua University, Zhejiang 314006, China
| | - Hongwei Zhang
- Food and Agricultural Products Testing Agency, Technology Center of Qingdao Customs District, Qingdao, Shandong Province 266002, China
| | - Xiaomei Zhang
- Food and Agricultural Products Testing Agency, Technology Center of Qingdao Customs District, Qingdao, Shandong Province 266002, China.
| | - Yujin Li
- College of Food Science and Engineering, Ocean University of China, Qingdao 266003, China; Sanya Ocean Institute, Ocean University of China, Floor 7, Building 1, Yonyou Industrial Park, Yazhou Bay Science & Technology City, Sanya, Hainan, China.
| | - Qian Yao
- Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, Sichuan Industrial Institute of Antibiotics, School of Pharmacy, Chengdu University, Chengdu 610106, China.
| | - Qiang Cai
- Yangtze Delta Region Institute of Tsinghua University, Zhejiang 314006, China.
| | - Yaqin Hu
- College of Food Science and Engineering, Yazhou Bay Innovation Institute, Hainan Tropical Ocean University, Marine Food Engineering Technology Research Center of Hainan Province, Collaborative Innovation Center of Marine Food Deep Processing, Hainan Key Laboratory of Herpetological Research, Sanya 572022, China.
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2
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Kakarelidou M, Christopoulos P, Conides A, Kalogianni DP, Christopoulos TK. Fish DNA Sensors for Authenticity Assessment-Application to Sardine Species Identification. Molecules 2024; 29:677. [PMID: 38338421 PMCID: PMC10856316 DOI: 10.3390/molecules29030677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 01/29/2024] [Accepted: 01/30/2024] [Indexed: 02/12/2024] Open
Abstract
Food and fish adulteration is a major public concern worldwide. Apart from economic fraud, health issues are in the forefront mainly due to severe allergies. Sardines are one of the most vulnerable-to-adulteration fish species due to their high nutritional value. Adulteration comprises the substitution of one fish species with similar species of lower nutritional value and lower cost. The detection of adulteration, especially in processed fish products, is very challenging because the morphological characteristics of the tissues change, making identification by the naked eye very difficult. Therefore, new analytical methods and (bio)sensors that provide fast analysis with high specificity, especially between closely related fish species, are in high demand. DNA-based methods are considered as important analytical tools for food adulteration detection. In this context, we report the first DNA sensors for sardine species identification. The sensing principle involves species recognition, via short hybridization of PCR-amplified sequences with specific probes, capture in the test zone of the sensor, and detection by the naked eye using gold nanoparticles as reporters; thus, avoiding the need for expensive instruments. As low as 5% adulteration of Sardina pilchardus with Sardinella aurita was detected with high reproducibility in the processed mixtures simulating canned fish products.
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Affiliation(s)
- Myrto Kakarelidou
- Analytical/Bioanalytical Chemistry & Nanotechnology Group, Department of Chemistry, University of Patras, Rio, 26504 Patras, Greece; (M.K.); (P.C.)
| | - Panagiotis Christopoulos
- Analytical/Bioanalytical Chemistry & Nanotechnology Group, Department of Chemistry, University of Patras, Rio, 26504 Patras, Greece; (M.K.); (P.C.)
| | - Alexis Conides
- Hellenic Centre for Marine Research, Institute for Marine Biological Resources, 46.7 km Athens-Sounion, Anavyssos, 19013 Attika, Greece;
| | - Despina P. Kalogianni
- Analytical/Bioanalytical Chemistry & Nanotechnology Group, Department of Chemistry, University of Patras, Rio, 26504 Patras, Greece; (M.K.); (P.C.)
| | - Theodore K. Christopoulos
- Analytical/Bioanalytical Chemistry & Nanotechnology Group, Department of Chemistry, University of Patras, Rio, 26504 Patras, Greece; (M.K.); (P.C.)
- Institute of Chemical Engineering Sciences, Foundation for Research and Technology Hellas (FORTH/ICE-HT), Platani, 26504 Patras, Greece
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3
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Yang SM, Kim JS, Kim E, Kim HY. Rapid and Simultaneous Authentication of Six Laver Species Using Capillary Electrophoresis-Based Multiplex PCR. Foods 2024; 13:363. [PMID: 38338499 PMCID: PMC10855616 DOI: 10.3390/foods13030363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2023] [Revised: 01/21/2024] [Accepted: 01/21/2024] [Indexed: 02/12/2024] Open
Abstract
Lavers are typically consumed in dried or seasoned forms. However, commercially processed lavers can lead to seafood fraud because it is impossible to authenticate the original species based on morphological characteristics alone. In this study, we developed a capillary electrophoresis-based multiplex polymerase chain reaction (PCR) to authenticate six different laver species. The species-specific primer sets to target the chloroplast rbcL or rbcS genes were newly designed. We successfully established both singleplex and multiplex conditions, which resulted in specific amplicons for each species (N. dentata, 274 bp; N. yezoensis, 211 bp; N. seriata, 195 bp; N. tenera, 169 bp; N. haitanensis, 127 bp; P. suborbiculata, 117 bp). Moreover, the assays were sensitive enough to detect DNA ranging from 10 to 0.1 pg of DNA. The optimized capillary electrophoresis-based multiplex PCR was successfully applied to 40 commercial laver products. In addition to detecting the laver species as stated on the commercial label, the assay discovered cases where less expensive species were mixed in. With its advantageous properties, such as short amplicon size, high specificity, and superior sensitivity, this assay could be used for the authentication of the six laver species.
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Affiliation(s)
| | | | | | - Hae-Yeong Kim
- Institute of Life Sciences & Resources, Department of Food Science and Biotechnology, Kyung Hee University, Yongin 17104, Republic of Korea; (S.-M.Y.); (J.-S.K.); (E.K.)
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4
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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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5
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Xenidis VA, Martsikalis PV, Kotsanopoulos KV, Palaiokostas C, Gkafas GA, Parlapani FF, Boziaris IS, Exadactylos A. The use of telomeric length as authenticity marker in fish and seafood - a new perspective in the detection of adulteration. Crit Rev Food Sci Nutr 2023; 63:12625-12636. [PMID: 35894643 DOI: 10.1080/10408398.2022.2103643] [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] [Indexed: 11/03/2022]
Abstract
In this review we propose the use of telomeric length (TL) as an authenticity marker that could provide an alternative method for differentiating fish and seafood samples or detecting fraud. Considering the ever-growing number of incidents of economically motivated fish and seafood adulteration using even more sophisticated methods to overcome current authenticity markers, the need to identify novel authenticity markers becomes essential. The TL of fish and seafood depends on individual characteristics (e.g., sex, age) and the environmental stimuli (e.g., temperature, water quality) to which these are exposed. Hence, both wild marine and freshwater populations occupying different geographical origin habitats might differ substantially because of the environmental cues affecting them. Moreover, the implementation of various rearing practices in aquaculture, such as different levels of fish and seafood density and increased ambient noise combined with site-specific environmental cues could affect TL, providing regulatory authorities with valuable information by distinguishing wild from reared populations and organic from conventional ones. In the present review the effects of both the environmental conditions and individual characteristics on the telomeric stability of fish and seafood telomeres are discussed, suggesting TL as a potential prospect authenticity marker that could be used to prevent fish and seafood adulteration.
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Affiliation(s)
- Vasileios A Xenidis
- Department of Food Science and Technology, School of Agriculture, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Petros V Martsikalis
- Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Volos, Greece
| | - Konstantinos V Kotsanopoulos
- Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Volos, Greece
| | - Christos Palaiokostas
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Georgios A Gkafas
- Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Volos, Greece
| | - Foteini F Parlapani
- Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Volos, Greece
| | - Ioannis S Boziaris
- Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Volos, Greece
| | - Athanasios Exadactylos
- Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Volos, Greece
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6
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Giantsis IA, Tokamani M, Triantaphyllidis G, Tzatzani S, Chatzinikolaou E, Toros A, Bouchorikou A, Chatzoglou E, Miliou H, Sarantopoulou J, Gkafas GA, Exadactylos A, Sandaltzopoulos R, Apostolidis AP. Development of Multiplex PCR and Melt-Curve Analysis for the Molecular Identification of Four Species of the Mullidae Family, Available in the Market. Genes (Basel) 2023; 14:genes14050960. [PMID: 37239320 DOI: 10.3390/genes14050960] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 04/13/2023] [Accepted: 04/20/2023] [Indexed: 05/28/2023] Open
Abstract
The authentication of food products and the verification of their identity are of major importance for consumers. Food fraud through mislabeling is an illegal practice consisting of the substitution of an expensive food product by a relatively cheaper one, misleading false labelling of their origin and adulteration in processed or frozen products. This issue is particularly of high importance concerning fish and seafood, which are easily adulterated primarily due to difficult morphological identification. Fish species of the Mullidae family are considered among the most high-valued seafood products traded in Greece and Eastern Mediterranean in general, in terms of the price and demand. Specifically, the red mullet (Mullus barbatus) and the striped red mullet (Mullus surmuletus) are both indigenous in the Aegean (FAO Division 37.3.1) and the Ionian (FAO Division 37.2.2) Seas, with high levels of consumers' preferences. However, they could be easily adulterated or misidentified by the invasive Aegean Sea Lessepsian migrator goldband goatfish (Upeneus moluccensis) as well as by the imported West African goatfish (Pseudupeneus prayensis). Keeping this in mind, we designed two novel, time-saving and easy-to-apply multiplex PCR assays and one multiple Melt-Curve analysis real-time PCR for the identification of these four species. These methodologies are based on species-specific primers targeting single nucleotide polymorphisms (SNPs) detected via sequencing analysis of the mitochondrial cytochrome C oxidase subunit I (CO1) and of the cytochrome b (CYTB) genes in newly collected individuals, with additional comparison with congeneric and conspecific haplotypes obtained from the GenBank database. Both methodologies, targeting CO1 or CYTB, utilize one common and four diagnostic primers, producing amplicons of different length that are easily and reliably separated on agarose gel electrophoresis, yielding a single clear band of diagnostic size for each species or a certain Melt-Curve profile. The applicability of this cost-effective and fast methodology was tested in 328 collected specimens, including 10 cooked samples obtained from restaurants. In the vast majority (327 out of the 328) of the specimens tested, one single band was produced, in agreement with the expected products with a single exception a M. barbatus sample that was identified as M. surmuletus, the identity of which was confirmed using sequencing, indicating erroneous morphological identification. The developed methodologies are expected to contribute to the detection of commercial fraud in fish authentication.
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Affiliation(s)
- Ioannis A Giantsis
- Department of Animal Science, Faculty of Agricultural Sciences, University of Western Macedonia, 53100 Florina, Greece
- Department of Molecular Biology and Genetics, Democritus University of Thrace, 68100 Alexandroupolis, Greece
- Laboratory of Fish & Fisheries, Department of Animal Production, School of Agriculture, Faculty of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Maria Tokamani
- Department of Molecular Biology and Genetics, Democritus University of Thrace, 68100 Alexandroupolis, Greece
| | - George Triantaphyllidis
- Laboratory of Applied Hydrobiology, School of Animal Biosciences, Agricultural University of Athens, 11855 Athens, Greece
| | - Stella Tzatzani
- Laboratory of Fish & Fisheries, Department of Animal Production, School of Agriculture, Faculty of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Emmanuella Chatzinikolaou
- Laboratory of Fish & Fisheries, Department of Animal Production, School of Agriculture, Faculty of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Athanasios Toros
- Department of Molecular Biology and Genetics, Democritus University of Thrace, 68100 Alexandroupolis, Greece
| | - Anastasia Bouchorikou
- Department of Molecular Biology and Genetics, Democritus University of Thrace, 68100 Alexandroupolis, Greece
| | - Evanthia Chatzoglou
- Laboratory of Applied Hydrobiology, School of Animal Biosciences, Agricultural University of Athens, 11855 Athens, Greece
| | - Helen Miliou
- Laboratory of Applied Hydrobiology, School of Animal Biosciences, Agricultural University of Athens, 11855 Athens, Greece
| | - Joanne Sarantopoulou
- Hydrobiology-Ichthyology Lab, Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, 38446 Volos, Greece
| | - Georgios A Gkafas
- Hydrobiology-Ichthyology Lab, Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, 38446 Volos, Greece
| | - Athanasios Exadactylos
- Hydrobiology-Ichthyology Lab, Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, 38446 Volos, Greece
| | - Raphael Sandaltzopoulos
- Department of Molecular Biology and Genetics, Democritus University of Thrace, 68100 Alexandroupolis, Greece
| | - Apostolos P Apostolidis
- Laboratory of Fish & Fisheries, Department of Animal Production, School of Agriculture, Faculty of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
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7
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Dou X, Zhang L, Chen Z, Wang X, Ma F, Yu L, Mao J, Li P. Establishment and evaluation of multiple adulteration detection of camellia oil by mixture design. Food Chem 2023; 406:135050. [PMID: 36462349 DOI: 10.1016/j.foodchem.2022.135050] [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: 08/12/2022] [Revised: 11/01/2022] [Accepted: 11/21/2022] [Indexed: 11/27/2022]
Abstract
Multiple adulteration is a common trick to mask adulteration detection methods. In this study, the representative multiple adulterated camellia oils were prepared according to the mixture design. Then, these representative oils were employed to build two-class classification models and validate one-class classification model combined with fatty acid profiles. The cross-validation results indicated that the recursive SVM model possessed higher classification accuracy (97.9%) than PLS-DA. In OCPLS model, the optimal percentage of RO, SO, CO and SUO was 2.8%, 0%, 7.2%, 0% respectively in adulterated camellia oil, which is the most similar to the authentic camellia oils. Further validation showed that five adulterated oils with the optimal percentage could be correctly identified, indicating that the OCPLS model could identify multiple adulterated oils with these four cheaper oils. Moreover, this study serves as a reference for one class classification model evaluation and a solution for multiple adulteration detection of other foods.
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Affiliation(s)
- Xinjing Dou
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Laboratory of Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Quality Inspection and Test Center for Oilseed Products, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Liangxiao Zhang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Laboratory of Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Quality Inspection and Test Center for Oilseed Products, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China; College of Food Science and Engineering, Nanjing University of Finance and Economics/Collaborative Innovation Center for Modern Grain Circulation and Safety, Nanjing 210023, China; Hubei Hongshan Laboratory, Wuhan 430070, China.
| | - Zhe Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Laboratory of Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Quality Inspection and Test Center for Oilseed Products, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Xuefang Wang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Laboratory of Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Quality Inspection and Test Center for Oilseed Products, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Fei Ma
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Laboratory of Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Quality Inspection and Test Center for Oilseed Products, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Li Yu
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Laboratory of Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Quality Inspection and Test Center for Oilseed Products, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Jin Mao
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Laboratory of Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Quality Inspection and Test Center for Oilseed Products, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China; Hubei Hongshan Laboratory, Wuhan 430070, China
| | - Peiwu Li
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Laboratory of Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Quality Inspection and Test Center for Oilseed Products, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China; Hubei Hongshan Laboratory, Wuhan 430070, China; Xianghu Laboratory, Hangzhou 311231, China
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8
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Rather MA, Agarwal D, Bhat TA, Khan IA, Zafar I, Kumar S, Amin A, Sundaray JK, Qadri T. Bioinformatics approaches and big data analytics opportunities in improving fisheries and aquaculture. Int J Biol Macromol 2023; 233:123549. [PMID: 36740117 DOI: 10.1016/j.ijbiomac.2023.123549] [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: 07/15/2022] [Revised: 01/30/2023] [Accepted: 01/31/2023] [Indexed: 02/05/2023]
Abstract
Aquaculture has witnessed an excellent growth rate during the last two decades and offers huge potential to provide nutritional as well as livelihood security. Genomic research has contributed significantly toward the development of beneficial technologies for aquaculture. The existing high throughput technologies like next-generation technologies generate oceanic data which requires extensive analysis using appropriate tools. Bioinformatics is a rapidly evolving science that involves integrating gene based information and computational technology to produce new knowledge for the benefit of aquaculture. Bioinformatics provides new opportunities as well as challenges for information and data processing in new generation aquaculture. Rapid technical advancements have opened up a world of possibilities for using current genomics to improve aquaculture performance. Understanding the genes that govern economically relevant characteristics, necessitates a significant amount of additional research. The various dimensions of data sources includes next-generation DNA sequencing, protein sequencing, RNA sequencing gene expression profiles, metabolic pathways, molecular markers, and so on. Appropriate bioinformatics tools are developed to mine the biologically relevant and commercially useful results. The purpose of this scoping review is to present various arms of diverse bioinformatics tools with special emphasis on practical translation to the aquaculture industry.
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Affiliation(s)
- Mohd Ashraf Rather
- Division of Fish Genetics and Biotechnology, Faculty of Fisheries Ganderbal, Sher-e- Kashmir University of Agricultural Science and Technology, Kashmir, India.
| | - Deepak Agarwal
- Institute of Fisheries Post Graduation Studies OMR Campus, Vaniyanchavadi, Chennai, India
| | | | - Irfan Ahamd Khan
- Division of Fish Genetics and Biotechnology, Faculty of Fisheries Ganderbal, Sher-e- Kashmir University of Agricultural Science and Technology, Kashmir, India
| | - Imran Zafar
- Department of Bioinformatics and Computational Biology, Virtual University Punjab, Pakistan
| | - Sujit Kumar
- Department of Bioinformatics and Computational Biology, Virtual University Punjab, Pakistan
| | - Adnan Amin
- Postgraduate Institute of Fisheries Education and Research Kamdhenu University, Gandhinagar-India University of Kurasthra, India; Department of Aquatic Environmental Management, Faculty of Fisheries Rangil- Ganderbel -SKUAST-K, India
| | - Jitendra Kumar Sundaray
- ICAR-Central Institute of Freshwater Aquaculture, Kausalyaganga, Bhubaneswar, Odisha 751002, India
| | - Tahiya Qadri
- Division of Food Science and Technology, SKUAST-K, Shalimar, India
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9
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Li Y, Xue H, Fei Y, Yang Y, Huang D, Wang L, Xiong X, Xiong X. A rapid and closed-tube method based on the dual-color fluorescence loop-mediated isothermal amplification for visual detection of Atlantic salmon (Salmo salar). Food Chem 2023; 405:134975. [PMID: 36410220 DOI: 10.1016/j.foodchem.2022.134975] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Revised: 10/16/2022] [Accepted: 11/14/2022] [Indexed: 11/18/2022]
Abstract
Loop-mediated isothermal amplification (LAMP) visual detection based on hydroxyl naphthol blue (HNB) and SYTO 9 is often confounded by the narrow color variation window and the requirement of empirical preset of cutoff intensity value. To improve the suitability for naked-eye inspection, the present work proposed a strategy based on the fluorescence property of SYTO 9 and HNB to enlarge the contrast and a novel dual-color fluorescence LAMP (dfLAMP) assay was developed for visual detection of Atlantic salmon. Specifically, HNB of 26.25 μM, blended with SYTO 9 of 0.75-1.5 μM, was added in the mixture before amplification, producing light green fluorescence for both positive and negative samples. After amplification, green or yellow-green fluorescence was observed for positive samples, while only orange-red fluorescence emitted for negative ones, enabling an easy and rapid distinguish. The optimized dfLAMP assay has proved its specificity and can detect as little as 1 fg Atlantic salmon DNA.
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Affiliation(s)
- Yi Li
- College of Food Science and Light Industry, Nanjing Tech University, Nanjing 211800, China
| | - Hanyue Xue
- College of Food Science and Light Industry, Nanjing Tech University, Nanjing 211800, China
| | - Yanjing Fei
- College of Food Science and Light Industry, Nanjing Tech University, Nanjing 211800, China
| | - Ying Yang
- School of Horticulture, Anhui Agricultural University, Hefei 230036, China.
| | - Danping Huang
- The State Light Industry Food Quality Supervision and Detection Station, Nanjing 210009, China
| | - Libin Wang
- College of Light Industry and Food Engineering, Nanjing Forestry University, Nanjing 210037, China
| | - Xiaohui Xiong
- College of Food Science and Light Industry, Nanjing Tech University, Nanjing 211800, China
| | - Xiong Xiong
- College of Food Science and Light Industry, Nanjing Tech University, Nanjing 211800, China.
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10
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Yanjin F, Hanyue X, Xiong X, Ying Y, Libin W, Xiaohui X. Detection of Salmonidae ingredient using mini-DNA barcoding in conjunction with a rapid visual inspection method. J Food Compost Anal 2023. [DOI: 10.1016/j.jfca.2023.105198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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11
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Silveira T, Moreno Abril SI, Lucas CG, Remião MH. Editorial: Application of fishes as biological models in genetic studies. Front Genet 2023; 13:1092160. [PMID: 36685980 PMCID: PMC9849242 DOI: 10.3389/fgene.2022.1092160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 11/28/2022] [Indexed: 01/06/2023] Open
Affiliation(s)
- Tony Silveira
- Biological Sciences Institute, Federal University of Rio Grande, Rio Grande, Brazil,*Correspondence: Tony Silveira, ; Mariana Härter Remião,
| | - Sandra Isabel Moreno Abril
- Marine Research Centre, University of Vigo, Vigo, Spain,Department of Ecology and Animal Biology, University of Vigo, Vigo, Spain
| | - Caroline Gomes Lucas
- Division of Animal Sciences, Animal Science Research Center, National Swine Resource and Research Center, University of Missouri, Columbia, MO, United States
| | - Mariana Härter Remião
- Structural Genomics Laboratory, Technological Developmental Center, Federal University of Pelotas, Pelotas, Brazil,*Correspondence: Tony Silveira, ; Mariana Härter Remião,
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12
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Identification of Fish Species and Targeted Genetic Modifications Based on DNA Analysis: State of the Art. Foods 2023; 12:foods12010228. [PMID: 36613444 PMCID: PMC9818732 DOI: 10.3390/foods12010228] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 12/22/2022] [Accepted: 12/30/2022] [Indexed: 01/05/2023] Open
Abstract
Food adulteration is one of the most serious problems regarding food safety and quality worldwide. Besides misleading consumers, it poses a considerable health risk associated with the potential non-labeled allergen content. Fish and fish products are one of the most expensive and widely traded commodities, which predisposes them to being adulterated. Among all fraud types, replacing high-quality or rare fish with a less valuable species predominates. Because fish differ in their allergen content, specifically the main one, parvalbumin, their replacement can endanger consumers. This underlines the need for reliable, robust control systems for fish species identification. Various methods may be used for the aforementioned purpose. DNA-based methods are favored due to the characteristics of the target molecule, DNA, which is heat resistant, and the fact that through its sequencing, several other traits, including the recognition of genetic modifications, can be determined. Thus, they are considered to be powerful tools for identifying cases of food fraud. In this review, the major DNA-based methods applicable for fish meat and product authentication and their commercial applications are discussed, the possibilities of detecting genetic modifications in fish are evaluated, and future trends are highlighted, emphasizing the need for comprehensive and regularly updated online database resources.
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13
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Rapid identification of fish species by laser-induced breakdown spectroscopy and Raman spectroscopy coupled with machine learning methods. Food Chem 2023; 400:134043. [DOI: 10.1016/j.foodchem.2022.134043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 08/20/2022] [Accepted: 08/24/2022] [Indexed: 11/23/2022]
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14
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Xu Y, Koidis A, Tian X, Xu S, Xu X, Wei X, Jiang A, Lei H. Bayesian Fusion Model Enhanced Codfish Classification Using Near Infrared and Raman Spectrum. Foods 2022; 11:foods11244100. [PMID: 36553842 PMCID: PMC9777887 DOI: 10.3390/foods11244100] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 12/14/2022] [Accepted: 12/14/2022] [Indexed: 12/24/2022] Open
Abstract
In this study, a Bayesian-based decision fusion technique was developed for the first time to quickly and non-destructively identify codfish using near infrared (NIRS) and Raman spectroscopy (RS). NIRS and RS spectra from 320 codfish samples were collected, and separate partial least squares discriminant analysis (PLS-DA) models were developed to establish the relationship between the raw data and cod identity for each spectral technique. Three decision fusion methods: decision fusion, data layer or feature layer, were tested and compared. The decision fusion model based on the Bayesian algorithm (NIRS-RS-B) was developed on the optimal discrimination features of NIRS and RS data (NIRS-RS) extracted by the PLS-DA method whereas the other fusion models followed conventional, non-Bayesian approaches. The Bayesian model showed enhanced classification metrics (92% sensitivity, 98% specificity, 98% accuracy) that were significantly superior to those demonstrated by any of other two spectroscopic methods (NIRS, RS) and the two data fusion methods (data layer fused, NIRS-RS-D, or feature layer fused, NIRS-RS-F). This novel proposed approach can provide an alternative classification for codfish and potentially other food speciation cases.
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Affiliation(s)
- Yi Xu
- Guangdong Provincial Key Laboratory of Food Quality and Safety/Nation-Local Joint Engineering Research Center for Precision Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou 510642, China
- College of Light Industry and Engineering, Sichuan Technology & Business College, Chengdu 611800, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China
| | - Anastasios Koidis
- Institute for Global Food Security, Queen’s University Belfast, 19 Chlorine Gardens, Belfast BT9 5DJ, UK
| | - Xingguo Tian
- Guangdong Provincial Key Laboratory of Food Quality and Safety/Nation-Local Joint Engineering Research Center for Precision Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou 510642, China
| | - Sai Xu
- Public Monitoring Center of Agricultural Products, Guangdong Academy of Agricultural Sciences, Guangzhou 510642, China
| | - Xiaoyan Xu
- Guangdong Provincial Key Laboratory of Food Quality and Safety/Nation-Local Joint Engineering Research Center for Precision Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou 510642, China
| | - Xiaoqun Wei
- Guangdong Provincial Key Laboratory of Food Quality and Safety/Nation-Local Joint Engineering Research Center for Precision Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou 510642, China
| | - Aimin Jiang
- Guangdong Provincial Key Laboratory of Food Quality and Safety/Nation-Local Joint Engineering Research Center for Precision Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou 510642, China
- Correspondence: (A.J.); (H.L.); Tel.: +86-20-8528-0270 (A.J.); +86-20-8528-3925 (H.L.)
| | - Hongtao Lei
- Guangdong Provincial Key Laboratory of Food Quality and Safety/Nation-Local Joint Engineering Research Center for Precision Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou 510642, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China
- Correspondence: (A.J.); (H.L.); Tel.: +86-20-8528-0270 (A.J.); +86-20-8528-3925 (H.L.)
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15
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Kotsanopoulos K, Martsikalis PV, Gkafas GA, Exadactylos A. The use of various statistical methods for authenticity and detection of adulteration in fish and seafood. Crit Rev Food Sci Nutr 2022; 64:1553-1571. [PMID: 36052815 DOI: 10.1080/10408398.2022.2117786] [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] [Indexed: 11/03/2022]
Abstract
Various methodologies including genetic analyses, morphometrics, proteomics, lipidomics, metabolomics, etc. are now used or being developed to authenticate fish and seafood. Such techniques usually lead to the generation of enormous amounts of data. The analysis and interpretation of this information can be particularly challenging. Statistical techniques are therefore commonly used to assist in analyzing these data, visualizing trends and differences and extracting conclusions. This review article aims at presenting and discussing statistical methods used in studies on fish and seafood authenticity and adulteration, allowing researchers to consider their options based on previous successes/failures but also offering some recommendations about the future of such techniques. Techniques such as PCA, AMOVA and FST statistics, that allow the differentiation of genetic groups, or techniques such as MANOVA that allow large data sets of morphometric characteristics or elemental differences to be analyzed are discussed. Furthermore, methods such as cluster analysis, DFA, CVA, CDA and heatmaps/Circos plots that allow samples to be differentiated based on their geographical origin are also reviewed and their advantages and disadvantages as found in past studies are given. Finally, mathematical simulations and modeling are presented in a detailed review of studies using them, together with their advantages and limitations.
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Affiliation(s)
- Konstantinos Kotsanopoulos
- Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Volos, Greece
| | - Petros V Martsikalis
- Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Volos, Greece
| | - George A Gkafas
- Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Volos, Greece
| | - Athanasios Exadactylos
- Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Volos, Greece
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16
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Li Q, Xue H, Fei Y, Cao M, Xiong X, Xiong X, Yang Y, Wang L. Visual detection of rainbow trout ( Oncorhynchus mykiss) and Atlantic salmon ( Salmo salar) simultaneously by duplex loop-mediated isothermal amplification. FOOD CHEMISTRY. MOLECULAR SCIENCES 2022; 4:100107. [PMID: 35769395 PMCID: PMC9235052 DOI: 10.1016/j.fochms.2022.100107] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 03/25/2022] [Accepted: 03/25/2022] [Indexed: 06/15/2023]
Abstract
Loop-mediated isothermal amplification (LAMP) is often confounded by the non-specific amplification arising from primer dimers, off-target priming, and other artifacts. Precipitation of the DNA produced during LAMP with the use of specific fluorescently labeled probe has proved the effectiveness in specific detection. Herein, two fluorophores (ROX and FAM) were attached to the primers S-LB-6 and R-FIP for Atlantic salmon and rainbow trout, respectively, which are self-quenched in unbound state and become de-quenched after binding to the dumbbell-shaped DNA specifically. The DNA precipitation and appearance of small sediment took 10 s of centrifugation at 1000 g, by adding polyethylenimine (PEI) 600. Each target species was specifically amplified with the predicted color of PEI-DNA sediment, namely red for Atlantic salmon, green for rainbow trout, and pale yellow for mixed species. The optimized duplex LAMP system has proved its specificity and can detect as little as 1 ng DNA in visual detection.
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Affiliation(s)
- Qiuping Li
- College of Food Science and Light Industry, Nanjing Tech University, Nanjing 211800, China
| | - Hanyue Xue
- College of Food Science and Light Industry, Nanjing Tech University, Nanjing 211800, China
| | - Yanjin Fei
- College of Food Science and Light Industry, Nanjing Tech University, Nanjing 211800, China
| | - Min Cao
- College of Food Science and Light Industry, Nanjing Tech University, Nanjing 211800, China
| | - Xiaohui Xiong
- College of Food Science and Light Industry, Nanjing Tech University, Nanjing 211800, China
| | - Xiong Xiong
- College of Food Science and Light Industry, Nanjing Tech University, Nanjing 211800, China
| | - Ying Yang
- School of Horticulture, Anhui Agricultural University, Hefei 230036, China
| | - Libin Wang
- College of Light Industry and Food Engineering, Nanjing Forestry University, Jiangsu Province 210037, China
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17
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Establishment of a rapid method for skipjack tuna (Katsuwonus pelamis) authentication using molecular beacons in loop-mediated isothermal amplification. Food Chem 2022; 382:132365. [DOI: 10.1016/j.foodchem.2022.132365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 01/21/2022] [Accepted: 02/04/2022] [Indexed: 11/20/2022]
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18
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Pappalardo AM, Giuga M, Raffa A, Nania M, Rossitto L, Calogero GS, Ferrito V. COIBar-RFLP Molecular Strategy Discriminates Species and Unveils Commercial Frauds in Fishery Products. Foods 2022; 11:foods11111569. [PMID: 35681319 PMCID: PMC9180250 DOI: 10.3390/foods11111569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 05/20/2022] [Accepted: 05/24/2022] [Indexed: 12/03/2022] Open
Abstract
The DNA analysis is the best approach to authenticate species in seafood products and to unveil frauds based on species substitution. In this study, a molecular strategy coupling Cytochrome Oxidase I (COI) DNA barcoding with the consolidated methodology of Restriction Fragment Length Polymorphisms (RFLPs), named COIBar-RFLP, was applied for searching pattern of restriction enzyme digestion, useful to discriminate seven different fish species (juveniles of Engraulis encrasicolus and Sardina pilchardus sold in Italy as “bianchetto” and Aphia minuta sold as “rossetto”; icefish Neosalanx tangkahkeii; European perch, Perca fluviatilis and the Nile Perch, Lates niloticus; striped catfish, Pangasianodon hypophthalmus). A total of 30 fresh and frozen samples were processed for DNA barcoding, analyzed against a barcode library of COI sequences retrieved from GenBank, and validated for COIBar–RFLP analysis. Cases of misdescription were detected: 3 samples labeled as “bianchetto” were substituted by N. tangkahkeii (2 samples) and A. minuta (1 sample); 3 samples labeled as “persico reale” (P. fluviatilis) were substituted by L. niloticus and P. hypophthalmus. All species were simultaneously discriminated through the restriction pattern obtained with MspI enzyme. The results highlighted that the COIBar-RFLP could be an effective tool to authenticate fish in seafood products by responding to the emerging interest in molecular identification technologies.
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Affiliation(s)
- Anna Maria Pappalardo
- Department of Biological, Geological and Environmental Sciences, Section of Animal Biology “M. La Greca”, University of Catania, Via Androne 81, 95124 Catania, Italy; (A.M.P.); (M.G.); (A.R.); (M.N.); (L.R.); (G.S.C.)
| | - Marta Giuga
- Department of Biological, Geological and Environmental Sciences, Section of Animal Biology “M. La Greca”, University of Catania, Via Androne 81, 95124 Catania, Italy; (A.M.P.); (M.G.); (A.R.); (M.N.); (L.R.); (G.S.C.)
- Institute for the Study of Antropic Impact and Sustainability in the Marine Environment, IAS-CNR, 91021 Trapani, Italy
| | - Alessandra Raffa
- Department of Biological, Geological and Environmental Sciences, Section of Animal Biology “M. La Greca”, University of Catania, Via Androne 81, 95124 Catania, Italy; (A.M.P.); (M.G.); (A.R.); (M.N.); (L.R.); (G.S.C.)
| | - Marco Nania
- Department of Biological, Geological and Environmental Sciences, Section of Animal Biology “M. La Greca”, University of Catania, Via Androne 81, 95124 Catania, Italy; (A.M.P.); (M.G.); (A.R.); (M.N.); (L.R.); (G.S.C.)
| | - Luana Rossitto
- Department of Biological, Geological and Environmental Sciences, Section of Animal Biology “M. La Greca”, University of Catania, Via Androne 81, 95124 Catania, Italy; (A.M.P.); (M.G.); (A.R.); (M.N.); (L.R.); (G.S.C.)
| | - Giada Santa Calogero
- Department of Biological, Geological and Environmental Sciences, Section of Animal Biology “M. La Greca”, University of Catania, Via Androne 81, 95124 Catania, Italy; (A.M.P.); (M.G.); (A.R.); (M.N.); (L.R.); (G.S.C.)
| | - Venera Ferrito
- Department of Biological, Geological and Environmental Sciences, Section of Animal Biology “M. La Greca”, University of Catania, Via Androne 81, 95124 Catania, Italy; (A.M.P.); (M.G.); (A.R.); (M.N.); (L.R.); (G.S.C.)
- Correspondence: ; Tel.: +39-095-730-6030
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19
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20
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Dufflocq P, Larraín MA, Araneda C. Species substitution and mislabeling in the swordfish (Xiphias gladius) market in Santiago, Chile: Implications in shark conservation. Food Control 2022. [DOI: 10.1016/j.foodcont.2021.108607] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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21
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Li Q, Cheng Y, Xu W, Cui X, Cao M, Xiong X, Wang L, Xiong X. Rapid identification of Atlantic salmon (Salmo salar) based on loop-mediated isothermal amplification (LAMP) using self-quenching fluorogenic approach. J Food Compost Anal 2022. [DOI: 10.1016/j.jfca.2021.104224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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22
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Real-time Loop-Mediated Isothermal Amplification (LAMP) Using Self-quenching Fluorogenic Probes: the Application in Skipjack Tuna (Katsuwonus pelamis) Authentication. FOOD ANAL METHOD 2021. [DOI: 10.1007/s12161-021-02159-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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23
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Monteiro CS, Deconinck D, Eljasik P, Sobczak M, Derycke S, Panicz R, Kane N, Mazloomrezaei M, H Devlin R, Faria MA. A fast HRMA tool to authenticate eight salmonid species in commercial food products. Food Chem Toxicol 2021; 156:112440. [PMID: 34311008 DOI: 10.1016/j.fct.2021.112440] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 06/30/2021] [Accepted: 07/22/2021] [Indexed: 10/20/2022]
Abstract
Atlantic and Pacific salmon are frequently consumed species with very different economic values: farmed Atlantic salmon is cheaper than wild-caught Pacific salmons. Species replacements occur with the high valued Pacific species (Oncorhynchus keta, O. gorbuscha, O. kisutch, O. nerka and O. tshawytscha) substituted by cheaper farmed Atlantic salmon (Salmo salar) and Atlantic salmon by rainbow trout (Oncorhynchus mykiss) and brown trout (Salmo trutta). Here we use High-Resolution Melting Analysis (HRMA) to identify eight salmonid species. We designed primers to generate short amplicons of 72 and 116 bp from the fish barcode genes CO1 and CYTB. The time of analysis was under 70 min, after DNA extraction. Food processing of Atlantic salmon (fresh, "Bellevue", "gravadlax", frozen and smoked) did not impact the HRMA profiles allowing reliable identification. A blind test was conducted by three different institutes, showing correct species identifications irrespective of the laboratory conducting the analysis. Finally, a total of 82 retail samples from three European countries were analyzed and a low substitution rate of 1.2% was found. The developed tool provides a quick way to investigate salmon fraud and contributes to safeguard consumers.
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Affiliation(s)
- Carolina Sousa Monteiro
- LAQV-REQUIMTE, Faculty of Pharmacy, University of Porto, R. Jorge de Viterbo Ferreira 228, 4050-313, Porto, Portugal
| | - Dumas Deconinck
- Flanders Research Institute for Agriculture, Fisheries and Food, ILVO, Aquatic Environment and Quality, Ankerstraat 1, B-8400, Oostende, Belgium; Laboratory of Biodiversity and Evolutionary Genomics, KU Leuven, Ch. Deberiotstraat 32, B-3000, Leuven, Belgium
| | - Piotr Eljasik
- Department of Meat Science, Faculty of Food Science and Fisheries, West Pomeranian University of Technology Szczecin, Kazimierza Królewicza 4, 71-550, Szczecin, Poland
| | - Małgorzata Sobczak
- Department of Meat Science, Faculty of Food Science and Fisheries, West Pomeranian University of Technology Szczecin, Kazimierza Królewicza 4, 71-550, Szczecin, Poland
| | - Sofie Derycke
- Flanders Research Institute for Agriculture, Fisheries and Food, ILVO, Aquatic Environment and Quality, Ankerstraat 1, B-8400, Oostende, Belgium; Department of Biology, Ghent University, Krijgslaan 281, Building S8, 9000, Ghent, Belgium
| | - Remigiusz Panicz
- Department of Meat Science, Faculty of Food Science and Fisheries, West Pomeranian University of Technology Szczecin, Kazimierza Królewicza 4, 71-550, Szczecin, Poland
| | - Nicola Kane
- BIOREX Food Diagnostics, 9A the Technology Park, Belfast Road, Antrim, BT41 1QS, UK
| | - Mohsen Mazloomrezaei
- BIOREX Food Diagnostics, 9A the Technology Park, Belfast Road, Antrim, BT41 1QS, UK
| | - Robert H Devlin
- Fisheries and Oceans Canada, 4160 Marine Drive, West Vancouver, BC, V7V 1N6, Canada
| | - Miguel A Faria
- LAQV-REQUIMTE, Faculty of Pharmacy, University of Porto, R. Jorge de Viterbo Ferreira 228, 4050-313, Porto, Portugal.
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24
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Amino Acid Profiling with Chemometric Analysis as a Feasible Tool for the Discrimination of Marine-Derived Peptide Powders. Foods 2021; 10:foods10061294. [PMID: 34199884 PMCID: PMC8229220 DOI: 10.3390/foods10061294] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 05/29/2021] [Accepted: 06/01/2021] [Indexed: 01/28/2023] Open
Abstract
Marine-derived peptide powders have suffered from adulteration via the substitution of lower-price peptides or the addition of adulterants in the market. This study aims to establish an effective approach for the discrimination and detection of adulterants for four representative categories of marine-derived peptide powders, namely, oyster peptides, sea cucumber peptides, Antarctic krill peptides, and fish skin peptides, based on amino acid profiling alongside chemometric analysis. The principal component analysis and orthogonal partial least squares discriminant analysis results indicate that four categories of marine-derived peptides could be distinctly classified into four clusters and aggregated with the respective raw materials. Taurine, glycine, lysine, and protein contents were the major discriminants. A reliable classification model was constructed and validated by the prediction dataset, mixture sample dataset, and unclassified sample dataset with accuracy values of 100%, 100%, and 100%, respectively.
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