Exploring Metabolomics Guided Authentication of Plant-Based Meat Alternatives Supporting Regulatory Standards and Consumer Health Protection


Authors : Felix Donkor; Mavis Nkem Okafor; Joy Onma Enyejo

Volume/Issue : Volume 10 - 2025, Issue 10 - October


Google Scholar : https://tinyurl.com/mtxdruvy

Scribd : https://tinyurl.com/2umc2eux

DOI : https://doi.org/10.38124/ijisrt/25oct1027

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Note : Google Scholar may take 30 to 40 days to display the article.


Abstract : The global demand for plant-based meat alternatives has accelerated in response to rising environmental concerns, shifting dietary preferences, and the pursuit of healthier food systems. However, the authenticity, safety, and quality assurance of these products remain central challenges in meeting consumer expectations and regulatory requirements. Metabolomics, a systems-level analytical approach that profiles the complete set of metabolites in a biological sample, has emerged as a powerful tool for authenticating plant-based meats. Through advanced spectroscopic and chromatographic techniques, coupled with bioinformatics-driven data integration, metabolomics enables the identification of product-specific biomarkers, detection of adulterants, and verification of ingredient sourcing. This review critically examines the application of metabolomics in the authentication of plant-based meat alternatives, focusing on its role in supporting regulatory frameworks, safeguarding consumer health, and enhancing transparency within the food supply chain. Key areas of emphasis include the detection of compositional discrepancies, allergen monitoring, nutritional profiling, and the prevention of fraudulent practices. Furthermore, the paper highlights the challenges of standardizing metabolomics protocols, ensuring reproducibility across laboratories, and integrating omics-based data into international regulatory standards. By situating metabolomics within the broader context of food authenticity and public health, this review underscores its transformative potential in strengthening consumer confidence and advancing sustainable food innovation.

Keywords : Metabolomics; Plant-Based Meat Authentication; Food Safety Regulation; Consumer Health Protection; Omics-Based Food Analysis.

References :

  1. Akindote, O., Enyejo, J. O., Awotiwon, B. O. & Ajayi, A. A. (2024). Integrating Blockchain and Homomorphic Encryption to Enhance Security and Privacy in Project Management and Combat Counterfeit Goods in Global Supply Chain Operations. International Journal of Innovative Science and Research Technology Volume 9, Issue 11, NOV. 2024, ISSN No:-2456-2165. https://doi.org/10.38124/ijisrt/IJISRT24NOV149.
  2. Amebleh, J., Igba, E. & Ijiga, O. M. (2021). Graph-Based Fraud Detection in Open-Loop Gift Cards: Heterogeneous GNNs, Streaming Feature Stores, and Near-Zero-Lag Anomaly Alerts  International Journal of Scientific Research in Science, Engineering and Technology Volume 8, Issue 6  doi : https://doi.org/10.32628/IJSRSET
  3. Aschemann-Witzel, J., & Peschel, A. O. (2019). How circular will you eat? The sustainability challenge in developing consumer trust and interest in plant-based food. Food Quality and Preference, 77, 15–22. https://doi.org/10.1016/j.foodqual.2019.04.011
  4. Atalor, S. I. (2024). Building a geo-analytic public health dashboard for tracking cancer drug deserts in U.S. counties, International Medical Science Research Journal Volume 4, Issue 11, Fair East Publishers DOI: 10.51594/imsrj.v4i11.1932
  5. Atalor, S. I., & Enyejo, J. O. (2025). Mobile Health Platforms for Medication Adherence among Oncology Patients in Rural Populations International Journal of Innovative Science and Research Technology  Volume 10, Issue 5, ISSN No:-2456-2165 https://doi.org/10.38124/ijisrt/25may415
  6. Awotiwon,  B. O.,  Enyejo, J. O., Owolabi, F. R. A., Babalola, I. N. O., & Olola, T. M. (2024). Addressing Supply Chain Inefficiencies to Enhance Competitive Advantage in Low-Cost Carriers (LCCs) through Risk Identification and Benchmarking Applied to Air Australasia’s Operational Model. World Journal of Advanced Research and Reviews, 2024, 23(03), 355–370. https://wjarr.com/content/addressing-supply-chain-inefficiencies-enhance-competitive-advantage-low-cost-carriers-lccs
  7. Babatuyi, P. B., Imoh, P. O., Igwe, E. U., & Enyejo, J. O. (2024). The Role of Public Health Leadership in Strengthening Emergency Response Protocols and Addressing Infrastructure Gaps During Infectious Disease Outbreaks. International Journal of Scientific Research and Modern Technology, 3(10), 109–122. https://doi.org/10.38124/ijsrmt.v3i10.735
  8. Broadhurst, D. I., Kell, D. B., & Takahashi, H. (2020). Guidelines and considerations for the reproducibility of metabolomics studies. Metabolites, 10(11), 462. https://doi.org/10.3390/metabo10110462
  9. Checa, A., & Mayr, M. (2020). Recent advances in metabolomics: Biomarker discovery for nutritional interventions. Current Opinion in Lipidology, 31(5), 279–287. https://doi.org/10.1097/MOL.0000000000000710
  10. Clarke, G., O’Sullivan, O., Ross, R. P., & Stanton, C. (2020). Metabolomics in food research: Identifying the metabolic signatures of food components. Trends in Food Science & Technology, 96, 88–102. https://doi.org/10.1016/j.tifs.2019.12.015
  11. Curtain, F., & Grafenauer, S. (2019). Plant-based meat substitutes in the flexitarian age: An audit of products on supermarket shelves. Nutrients, 11(11), 2603. https://doi.org/10.3390/nu11112603
  12. Dunn, W. B., Erban, A., Weber, R. J., Creek, D. J., Brown, M., Breitling, R., Hankemeier, T., Goodacre, R., Neumann, S., Kopka, J., & Viant, M. R. (2021). Mass appeal: Metabolite identification in mass spectrometry-focused untargeted metabolomics. Metabolomics, 17(11), 108. https://doi.org/10.1007/s11306-021-01872-7
  13. Ellis, D. I., Muhamadali, H., Haughey, S. A., Elliott, C. T., & Goodacre, R. (2022). Point-and-shoot: Metabolomics approaches for food fraud detection. TrAC Trends in Analytical Chemistry, 157, 116790. https://doi.org/10.1016/j.trac.2022.116790
  14. Emwas, A. H., Roy, R., McKay, R. T., Tenori, L., Saccenti, E., Gowda, G. A. N., Raftery, D., Alahmari, F., Jaremko, Ł., Jaremko, M., & Wishart, D. S. (2019). NMR spectroscopy for metabolomics research. Metabolites, 9(7), 123. https://doi.org/10.3390/metabo9070123
  15. Enyejo, J. O., Adeyemi, A. F., Olola, T. M., Igba, E & Obani, O. Q. (2024). Resilience in supply chains: How technology is helping USA companies navigate disruptions. Magna Scientia Advanced Research and Reviews, 2024, 11(02), 261–277. https://doi.org/10.30574/msarr.2024.11.2.0129
  16. Enyejo, J. O., Babalola, I. N. O., Owolabi, F. R. A. Adeyemi, A. F., Osam-Nunoo, G., & Ogwuche, A. O. (2024). Data-driven digital marketing and battery supply chain optimization in the battery powered aircraft industry through case studies of Rolls-Royce’s ACCEL and Airbus's E-Fan X Projects. International Journal of Scholarly Research and Reviews, 2024, 05(02), 001–020.  https://doi.org/10.56781/ijsrr.2024.5.2.0045
  17. Fiehn, O. (2002). Metabolomics—the link between genotypes and phenotypes. Plant Molecular Biology, 48(1-2), 155–171. https://doi.org/10.1023/A:1013713905833
  18. Foo, A. (Nd). Plant based meat vs meat, choose wisely, https://www.linkedin.com/posts/alvinfsc_plant-based-meat-vs-meat-choose-wisely-activity-7338671538201604098-scDx
  19. Foodtank, (2021). Supply Chain Transparency Can Support a Stronger Food System
  20. García-Cañas, V., Simó, C., León, C., & Cifuentes, A. (2020). Advances in food authentication through omics technologies: Metabolomics in the regulatory environment. TrAC Trends in Analytical Chemistry, 131, 115991. https://doi.org/10.1016/j.trac.2020.115991
  21. Haider, A., Iqbal, S. Z., Bhatti, I. A., Alim, M. B., Waseem, M., Iqbal, M., & Mousavi Khaneghah, A. (2024). Food authentication, current issues, analytical techniques, and future challenges: A comprehensive review. Comprehensive reviews in food science and food safety23(3), e13360. https://foodtank.com/news/2021/02/supply-chain-transparency-can-support-a-stronger-food-system/
  22. Idika, C. N. & Ijiga, O. M. (2025). Blockchain-Based Intrusion Detection Techniques for Securing Decentralized Healthcare Information Exchange Networks. Information Management and Computer Science, Zibeline International Publishing 8(2): 25-36. DOI: http://doi.org/10.26480/imcs.02.2025.25.36
  23. Idika, C. N., Salami, E. O., Ijiga, O. M. & Enyejo, L. A. (2021). Deep Learning Driven Malware Classification for Cloud-Native Microservices in Edge Computing Architectures International Journal of Scientific Research in Computer Science, Engineering and Information Technology Volume 7, Issue 4 doi : https://doi.org/10.32628/IJSRCSEIT
  24. Ijiga, O. M., Balogun, S. A., Okika, N., Agbo, O. J. & Enyejo, L. A. (2025). An In-Depth Review of Blockchain-Integrated Logging Mechanisms for Ensuring Integrity and Auditability in Relational Database Transactions International Journal of Social Science and Humanities Research Vol. 13, Issue 3, DOI: https://doi.org/10.5281/zenodo.15834931
  25. James, U. U. (2022). Machine Learning-Driven Anomaly Detection for Supply Chain Integrity in 5G Industrial Automation Systems International Journal of Scientific Research in Science, Engineering and Technology Volume 9, Issue 2 doi : https://doi.org/10.32628/IJSRSET
  26. James, U. U., Ijiga, O. M. & Enyejo, L. A. (2025). Zero Trust Network Access Enforcement for Securing Multi-Slice Architectures in 5G Private Enterprise Deployments International Journal of Scientific Research and Modern Technology, Volume 10, Issue 8,  https://doi.org/10.38124/ijisrt/25aug323
  27. Johnson, C. H., Ivanisevic, J., & Siuzdak, G. (2016). Metabolomics: Beyond biomarkers and towards mechanisms. Nature Reviews Molecular Cell Biology, 17(7), 451–459. https://doi.org/10.1038/nrm.2016.25
  28. Joshi, V. K., & Kumar, S. (2015). Meat analogues: Plant-based alternatives to meat products—A review. International Journal of Food and Fermentation Technology, 5(2), 107–119. https://doi.org/10.5958/2277-9396.2016.00001.5
  29. Khan, M. A., Govindan, K., & Yang, C. (2021). The regulatory landscape of food safety and traceability: Emerging trends and challenges. Food Control, 124, 107877. https://doi.org/10.1016/j.foodcont.2021.107877
  30. Kumar, P., Rani, A., Singh, S., & Kumar, A. (2022). Recent advances on DNA and omics‐based technology in Food testing and authentication: A review. Journal of Food Safety, 42(4), e12986.
  31. Li, S., Tian, Y., Jiang, P., Lin, Y., Liu, X., & Yang, H. (2021). Recent advances in the application of metabolomics for food safety control and food quality analyses. Critical reviews in food science and nutrition61(9), 1448-1469.
  32. Menezes, R. C., Kussmann, M., & Pujos-Guillot, E. (2020). Food traceability: Omics approaches for ensuring transparency in global supply chains. Comprehensive Reviews in Food Science and Food Safety, 19(6), 3454–3476. https://doi.org/10.1111/1541-4337.12642
  33. Misra, B. B., Langefeld, C., Olivier, M., & Cox, L. A. (2021). Integrated omics: Tools for next-generation food authentication research. Metabolites, 11(8), 504. https://doi.org/10.3390/metabo11080504
  34. Nicholson, J. K., Lindon, J. C., & Holmes, E. (1999). ‘Metabonomics’: Understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica, 29(11), 1181–1189. https://doi.org/10.1080/004982599238047
  35. Okpanachi, A. T., Adeniyi, M., Igba, E. & Dzakpasu, N. H. (2025). Enhancing Blood Supply Chain Management with Blockchain Technology to Improve Diagnostic Precision and Strengthen Health Information Security. International Journal of Innovative Science and Research Technology Volume 10, Issue 4, ISSN No:-2456-2165 https://doi.org/10.38124/ijisrt/25apr214
  36. Ononiwu, M., Azonuche, T. I., Okoh, O. F., & Enyejo, J. O. (2023). AI-Driven Predictive Analytics for Customer Retention in E-Commerce Platforms using Real-Time Behavioral Tracking. International Journal of Scientific Research and Modern Technology, 2(8), 17–31. https://doi.org/10.38124/ijsrmt.v2i8.561
  37. Oyekan, M., Igba, E. & Jinadu, S. O.. (2024). Building Resilient Renewable Infrastructure in an Era of Climate and Market Volatility International Journal of Scientific Research in Humanities and Social Sciences Volume 1, Issue 1 doi : https://doi.org/10.32628/IJSRSSH
  38. Patti, G. J., Yanes, O., & Siuzdak, G. (2012). Metabolomics: The apogee of the omics trilogy. Nature Reviews Molecular Cell Biology, 13(4), 263–269. https://doi.org/10.1038/nrm3314
  39. Pedrosa, M. C., Lima, L., Heleno, S., Carocho, M., Ferreira, I. C., & Barros, L. (2021). Food metabolites as tools for authentication, processing, and nutritive value assessment. Foods10(9), 2213.
  40. García-García, G., Stone, J., Rahimifard, S., & Matharu, A. S. (2020). The role of metabolomics in food quality assessment: Nutritional profiling of novel foods. Food Chemistry, 321, 126716. https://doi.org/10.1016/j.foodchem.2020.126716
  41. Rao, R. S. P., & Dixon, R. A. (2020). Metabolomics approaches for allergen detection in complex food systems. Frontiers in Plant Science, 11, 602. https://doi.org/10.3389/fpls.2020.00602
  42. Ribeiro, D. M., Esteves, E., & Fernandes, J. O. (2022). Metabolomics tools for traceability and authenticity of food products in globalized markets. Critical Reviews in Food Science and Nutrition, 62(24), 6780–6795. https://doi.org/10.1080/10408398.2021.1887075
  43. Rinschen, M. M., Ivanisevic, J., Giera, M., & Siuzdak, G. (2019). Identification of bioactive metabolites using activity metabolomics. Nature Reviews Molecular Cell Biology, 20(6), 353–367. https://doi.org/10.1038/s41580-019-0108-4
  44. Roberts, L. D., & Koulman, A. (2020). Practical approaches to metabolomics for food analysis. Annual Review of Food Science and Technology, 11, 45–68. https://doi.org/10.1146/annurev-food-032519-051729
  45. Scalbert, A., Brennan, L., Manach, C., Andres-Lacueva, C., Dragsted, L. O., Draper, J., Rappaport, S. M., van der Hooft, J. J., & Wishart, D. S. (2014). The food metabolome: A window over dietary exposure. The American Journal of Clinical Nutrition, 99(6), 1286–1308. https://doi.org/10.3945/ajcn.113.076133
  46. Shah, S. H., Kraus, W. E., & Newgard, C. B. (2020). Metabolomic profiling for the identification of regulatory policy challenges in nutrition science. Annual Review of Nutrition, 40, 99–122. https://doi.org/10.1146/annurev-nutr-122319-034601
  47. Spink, J., Ortega, D. L., Chen, C., & Wu, F. (2020). Food fraud prevention shifts the food risk focus to vulnerability. Food Control, 112, 107109. https://doi.org/10.1016/j.foodcont.2020.107109
  48. Ulaszewska, M. M., Vázquez-Manjarrez, N., Garcia-Aloy, M., Llorach, R., Mattivi, F., Dragsted, L. O., Praticò, G., Manach, C., & Brennan, L. (2020). Food metabolomics: A new frontier in nutritional research and consumer health protection. Nutrients, 12(10), 3003. https://doi.org/10.3390/nu12103003
  49. van der Weele, C., Feindt, P., Jan van der Goot, A., van Mierlo, B., & van Boekel, M. (2019). Meat alternatives: An integrative comparison. Trends in Food Science & Technology, 88, 505–512. https://doi.org/10.1016/j.tifs.2019.04.018
  50. Wishart, D. S. (2020). Metabolomics for investigating physiological and pathophysiological processes. Physiological Reviews, 100(2), 843–908. https://doi.org/10.1152/physrev.00035.2018
  51. Zhang, J., Sun, M., Elmaidomy, A. H., Youssif, K. A., Zaki, A. M., Kamal, H. H., ... & Abdelmohsen, U. R. (2023). Emerging trends and applications of metabolomics in food science and nutrition. Food & function14(20), 9050-9082.
  52. Zhang, Y., Chen, B., & Li, X. (2021). Application of metabolomics in food safety: Monitoring toxins and contaminants. Food Chemistry, 350, 129202. https://doi.org/10.1016/j.foodchem.2021.129202

The global demand for plant-based meat alternatives has accelerated in response to rising environmental concerns, shifting dietary preferences, and the pursuit of healthier food systems. However, the authenticity, safety, and quality assurance of these products remain central challenges in meeting consumer expectations and regulatory requirements. Metabolomics, a systems-level analytical approach that profiles the complete set of metabolites in a biological sample, has emerged as a powerful tool for authenticating plant-based meats. Through advanced spectroscopic and chromatographic techniques, coupled with bioinformatics-driven data integration, metabolomics enables the identification of product-specific biomarkers, detection of adulterants, and verification of ingredient sourcing. This review critically examines the application of metabolomics in the authentication of plant-based meat alternatives, focusing on its role in supporting regulatory frameworks, safeguarding consumer health, and enhancing transparency within the food supply chain. Key areas of emphasis include the detection of compositional discrepancies, allergen monitoring, nutritional profiling, and the prevention of fraudulent practices. Furthermore, the paper highlights the challenges of standardizing metabolomics protocols, ensuring reproducibility across laboratories, and integrating omics-based data into international regulatory standards. By situating metabolomics within the broader context of food authenticity and public health, this review underscores its transformative potential in strengthening consumer confidence and advancing sustainable food innovation.

Keywords : Metabolomics; Plant-Based Meat Authentication; Food Safety Regulation; Consumer Health Protection; Omics-Based Food Analysis.

CALL FOR PAPERS


Paper Submission Last Date
31 - December - 2025

Video Explanation for Published paper

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.
Subscribe
OR

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.
Subscribe