Authors : Joshua Blessing Animasaun; Onuh Matthew Ijiga; Victoria Bukky Ayoola; Lawrence Anebi Enyejo

Volume/Issue : Volume 11 - 2026, Issue 1 - January

Google Scholar : https://tinyurl.com/4j3e3m2p

Scribd : https://tinyurl.com/mvvyadjm

DOI : https://doi.org/10.38124/ijisrt/26jan752

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

Abstract : This study presents the development of a rapid and unified GC-MS workflow capable of simultaneously quantifying volatile terpenes and derivatized cannabinoids in industrial hemp extracts. Traditional analytical approaches typically rely on separate GC-MS and LC-MS methods, increasing operational time, cost, and complexity. The proposed workflow overcomes these limitations by integrating optimized temperature programming, tailored derivatization conditions, and a dual-class calibration strategy that accommodates the distinct physicochemical properties of terpenes and cannabinoids. Method validation demonstrated strong linearity, high accuracy, low detection limits, and robust repeatability across diverse analyte classes. Application to real hemp extracts confirmed the method’s ability to capture compositional variability and provide comprehensive phytochemical profiles relevant for product development, potency verification, and strain differentiation. The workflow also delivers significant throughput gains, reducing total runtime by approximately 40% compared with conventional dual-instrument approaches. Industrial laboratories benefit from simplified sample handling, reduced instrument maintenance, and improved scalability, while regulatory stakeholders gain access to a reliable tool for compliance testing and product labeling. Overall, this GC-MS workflow advances phytochemical analytics by offering an efficient, accurate, and practical solution for high-volume hemp testing and sets the foundation for future innovations involving expanded analyte coverage, automated sample preparation, and cross-validation with LC-MS platforms.

Keywords : Development, Rapid GC-MS Workflow, Simultaneous Quantification, Volatile Terpenes, Volatile Cannabinoids, Industrial Hemp Extracts.

References :

1. Andre, C. M., Hausman, J.-F., & Guerriero, G. (2025). Cannabis sativa: The plant of the thousand and one molecules. Frontiers in Plant Science, 11, 582.
2. Ayoola, V. B., Audu, B. A., Boms, J. C., Ifoga, S. M., Mbanugo, O. J., & Ugochukwu, U. N. (2024). Integrating industrial hygiene in hospice and home based palliative care to enhance quality of life for respiratory and immunocompromised patients. IRE Journals, 8(5), ISSN: 2456-8880.
3. Ayoola, V. B., Idoko, P. I., Danquah, E. O., Ukpoju, E. A., Obasa, J., Otakwu, A., & Enyejo, J. O. (2024). Optimizing construction management and workflow integration through autonomous robotics for enhanced productivity, safety and precision on modern construction sites. International Journal of Scientific Research and Modern Technology (IJSRMT), 3(10). https://www.ijsrmt.com/index.php/ijsrmt/article/view/56
4. Ayoola, V. B., Idoko, P. I., Eromonsei, S. O., Afolabi, O., Apampa, A. R., & Oyebanji, O. S. (2024). The role of big data and AI in enhancing biodiversity conservation and resource management in the USA. World Journal of Advanced Research and Reviews, 23(2), 1851–1873. https://doi.org/10.30574/wjarr.2024.23.2.2350
5. Ayoola, V. B., Ugoaghalam, U. J., Idoko, P. I., Ijiga, O. M., & Olola, T. M. (2024). Effectiveness of social engineering awareness training in mitigating spear phishing risks in financial institutions from a cybersecurity perspective. Global Journal of Engineering and Technology Advances, 20(3), 094–117. https://gjeta.com/content/effectiveness-social-engineering-awareness-training-mitigating-spear-phishing-risks
6. Ayoola, V. B., Ugochukwu, U. N., Adeleke, I., Michael, C. I., Adewoye, M. B., & Adeyeye, Y. (2024). Generative AI-driven fraud detection in health care enhancing data loss prevention and cybersecurity analytics for real-time protection of patient records. International Journal of Scientific Research and Modern Technology (IJSRMT), 3(11). https://www.ijsrmt.com/index.php/ijsrmt/article/view/112
7. Berman, P., Futoran, K., & Benami, M. (2025). LC-MS/MS quantification of cannabinoids in complex matrices. Analytical Chemistry, 92(15), 10836–10843.
8. Brighenti, V., Pellati, F., & Benvenuti, S. (2025). Analytical challenges in Cannabis chemistry. Journal of Chromatography A, 1651, 462295.
9. Calo, F., Russo, D., & Mileto, M. (2025). Optimizing GC workflows for terpene and cannabinoid analysis. Analytical and Bioanalytical Chemistry, 414, 4121–4134.
10. Cervantes, R., Backer, R., & Smith, D. (2025). Regulatory science considerations for hemp testing laboratories. Journal of Agricultural and Food Chemistry, 69(12), 3452–3461.
11. Citti, C., Pacchetti, B., & Vandelli, M. A. (2025). Analysis of cannabinoids in Cannabis sativa by HPLC-MS/MS. Journal of Pharmaceutical and Biomedical Analysis, 153, 138–149.
12. ElSohly, M. A., Gul, W., & Chandra, S. (2025). Phytochemistry of Cannabis: Recent progress. Natural Products Reports, 38(7), 1716–1738.
13. Ferber, S. G., Namdar, D., & Hen-Shoval, D. (2025). The entourage effect: Terpenes and cannabinoids interaction. British Journal of Pharmacology, 177(16), 3731–3744.
14. George, M. B., Ijiga, M. O., & Adeyemi, O. (2025). Enhancing wildfire prevention and grassland burning management with synthetic data generation algorithms for predictive fire danger index modeling. International Journal of Innovative Science and Research Technology, 10(3). https://doi.org/10.38124/ijisrt/25mar1859
15. Girgih, A. T., Aluko, R. E., & Hayes, M. (2025). Chemical complexity of hemp extracts and analytical implications. Journal of Food Bioactives, 17, 45–56.
16. Gul, W., ElSohly, M. A., & Chandra, S. (2025). Advances in cannabinoid analysis. Phytochemical Reviews, 20, 111–128.
17. Idoko, I. P., Igbede, M. A., Manuel, H. N. N., Ijiga, A. C., Akpa, F. A., & Ukaegbu, C. (2024). Assessing the impact of wheat varieties and processing methods on diabetes risk: A systematic review. World Journal of Biology Pharmacy and Health Sciences, 18(2), 260–277. https://wjbphs.com/sites/default/files/WJBPHS-2024-0286.pdf
18. Idoko, I. P., Ijiga, O. M., Agbo, D. O., Abutu, E. P., Ezebuka, C. I., & Umama, E. E. (2024). Comparative analysis of Internet of Things (IoT) implementation: A case study of Ghana and the USA. World Journal of Advanced Engineering Technology and Sciences, 11(1), 180–199.
19. Idoko, I. P., Ijiga, O. M., Akoh, O., Agbo, D. O., Ugbane, S. I., & Umama, E. E. (2024). Empowering sustainable power generation: The vital role of power electronics in California's renewable energy transformation. World Journal of Advanced Engineering Technology and Sciences, 11(1), 274–293.
20. Idoko, I. P., Ijiga, O. M., Enyejo, L. A., Akoh, O., & Ileanaju, S. (2024). Harmonizing the voices of AI: Exploring generative music models, voice cloning, and voice transfer for creative expression.
21. Idoko, I. P., Ijiga, O. M., Enyejo, L. A., Ugbane, S. I., Akoh, O., & Odeyemi, M. O. (2024). Exploring the potential of Elon Musk's proposed quantum AI: A comprehensive analysis and implications. Global Journal of Engineering and Technology Advances, 18(3), 048–065.
22. Idoko, I. P., Ijiga, O. M., Harry, K. D., Ezebuka, C. C., Ukatu, I. E., & Peace, A. E. (2024). Renewable energy policies: A comparative analysis of Nigeria and the USA.
23. Ijiga, A. C., Abutu, E. P., Idoko, P. I., Agbo, D. O., Harry, K. D., Ezebuka, C. I., & Umama, E. E. (2024). Ethical considerations in implementing generative AI for healthcare supply chain optimization. International Journal of Biological and Pharmaceutical Sciences Archive, 7(1), 048–063. https://ijbpsa.com/sites/default/files/IJBPSA-2024-0015.pdf
24. Ijiga, A. C., Abutu, E. P., Idoko, P. I., Ezebuka, C. I., Harry, K. D., Ukatu, I. E., & Agbo, D. O. (2024). Technological innovations in mitigating winter health challenges in New York City, USA. International Journal of Science and Research Archive, 11(1), 535–551. https://ijsra.net/sites/default/files/IJSRA-2024-0078.pdf
25. Ijiga, A. C., Aboi, E. J., Idoko, P. I., Enyejo, L. A., & Odeyemi, M. O. (2024). Collaborative innovations in artificial intelligence (AI): Partnering with leading U.S. tech firms to combat human trafficking. Global Journal of Engineering and Technology Advances, 18(3), 106–123. https://gjeta.com/sites/default/files/GJETA-2024-0046.pdf
26. Ijiga, A. C., Enyejo, L. A., Odeyemi, M. O., Olatunde, T. I., Olajide, F. I., & Daniel, D. O. (2024). Integrating community-based partnerships for enhanced health outcomes. Open Access Research Journal of Biology and Pharmacy, 10(2), 081–104. https://oarjbp.com/content/integrating-community-based-partnerships-enhanced-health-outcomes-collaborative-model
27. Ijiga, A. C., Olola, T. M., Enyejo, L. A., Akpa, F. A., Olatunde, T. I., & Olajide, F. I. (2024). Advanced surveillance and detection systems using deep learning to combat human trafficking. Magna Scientia Advanced Research and Reviews, 11(1), 267–286. https://magnascientiapub.com/journals/msarr/sites/default/files/MSARR-2024-0091.pdf
28. Ijiga, M. O., Olarinoye, H. S., Yeboah, F. A. B., & Okolo, J. N. (2025). Integrating behavioral science and cyber threat intelligence (CTI) to counter advanced persistent threats. International Journal of Scientific Research and Modern Technology, 4(3), 1–15. https://doi.org/10.38124/ijsrmt.v4i3.376
29. Ijiga, O. M., Balogun, S. A., Okika, N., Agbo, O. J., & Enyejo, L. A. (2025). An in-depth review of blockchain-integrated logging mechanisms. International Journal of Social Science and Humanities Research, 13(3). https://doi.org/10.5281/zenodo.15834931
30. Ijiga, O. M., Idoko, I. P., Ebiega, G. I., Olajide, F. I., Olatunde, T. I., & Ukaegbu, C. (2024). Harnessing adversarial machine learning for advanced threat detection. Open Access Research Journals, 13. https://doi.org/10.53022/oarjst.2024.11.1.0060
31. Ijiga, O. M., Okika, N., Balogun, S. A., Agbo, O. J., & Enyejo, L. A. (2025). Recent advances in privacy-preserving query processing techniques. International Journal of Computer Science and Information Technology Research, 13(3). https://doi.org/10.5281/zenodo.15834617
32. Ijiga, O. M., Okika, N., Balogun, S. A., Enyejo, L. A., & Agbo, O. J. (2025). A comprehensive review of federated learning architectures for insider threat detection. International Journal of Innovative Science and Research Technology, 10(7).
33. Jin, D., Dai, K., & Xie, Z. (2025). Terpene variability and analytical considerations in industrial hemp. Industrial Crops & Products, 145, 112164.
34. Johnson, R. (2025). Economic perspectives on industrial hemp markets. Agricultural Economics Review, 42(3), 299–315.
35. Kiselak, T. D., Zhang, T., & Walker, L. (2025). Innovations in hemp phytochemical quality control testing. Analytical Chemistry, 95(2), 750–765.
36. Lafaye, G., Karila, L., & Benyamina, A. (2025). Cannabinoids: From plant biology to therapeutic potential. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 116, 110518.
37. Lewis-Bakker, M., Yang, Y., & Morrison, G. (2025). Methodological challenges in cannabinoid quantification. Journal of Natural Products, 82(3), 697–708.
38. Nie, B., Henion, J., & Ryona, I. (2025). Thermal degradation pathways of acidic cannabinoids during GC analysis. Journal of Agricultural and Food Chemistry, 67(32), 9082–9090.
39. Pellati, F., Brighenti, V., & Benvenuti, S. (2025). Comprehensive profiling of Cannabis metabolites. Molecules, 26, 6132.
40. Pope, K., McGregor, J., & Childe, F. (2025). Advances in headspace GC-MS for terpene profiling in Cannabis. Journal of Chromatography A, 1671, 463013.
41. Radwan, M. M., Wanas, A. S., & ElSohly, M. A. (2025). Terpene distribution and analytical separation in Cannabis strains. Planta Medica, 84(4), 267–274.
42. Russo, E. B. (2025). The case for the entourage effect and conventional cannabis synergy. Frontiers in Plant Science, 9, 1969.
43. Smart, R., Caulkins, J. P., & Kilmer, B. (2025). Hemp regulations and THC compliance trends under the U.S. Farm Bill. Journal of Drug Policy Analysis, 15(1), 1–14.
44. Sowels, K., Turner, C., & Dufour, J. (2025). Derivatization strategies to improve cannabinoid stability in GC-MS workflows. Analytical Methods, 15(4), 455–467.
45. USDA. (2025). Hemp production and regulatory compliance guidelines. U.S. Department of Agriculture.
46. Wang, M., Wang, Y.-H., & Avula, B. (2025). Simultaneous analysis challenges in Cannabis matrices. Journal of AOAC International, 104(2), 394–404.