Research Article


DOI :10.26650/IstanbulJPharm.2023.1181298   IUP :10.26650/IstanbulJPharm.2023.1181298    Full Text (PDF)

A chemometrics-based approach for the determination of thymoquinone from Nigella sativa L. (Black Cumin) seeds of different geographical regions using the HPLC technique

Selin IşıkAbdullahi Garba UsmanSani Isah Abba

Background and Aims: In this study, thymoquinone (TQ) from black cumin will be quantified from several geographical regions, including India, Syria, Saudi Arabia, Iraq, and Turkey. Additionally, to forecast the chromatographic behavior of the analyte in artificial intelligence (AI)-based models, the study used both ensemble machine learning methodologies and chemometrics-based approaches.

Methods: An Agilent Technologies (1200 series, USA) instrument that includes an autosampler, a binary pump, a diode array detector (DAD), and a vacuum degasser was used for the HPLC analysis. Using five different single models—principal component regression (PCR), least square-support vector machine (LSSVM), least square boost (LSQ-BOOST), adaptive neuro-fuzzy inference system (ANFIS), and step-wise linear regression—the HPLC-DAD technique was used to simulate the qualitative and quantitative properties of TQ (SWLR).

Results: The collected results demonstrated that samples from India and Iraq have the highest concentration of TQ. TQ was present in all samples, but in varying amounts; the amounts of TQ in the samples from Iraq, India, Saudi Arabia, Syria, and Turkey, respectively, were 0.031, 0.030, 0.022, 0.005, and 0.001%. According to a comparison of their performances, the four ensemble machine learning techniques can reproduce the chromatographic properties of TQ, PA, and tR with minimum and maximum NSE-values of 0.842 and 0.999 in the training phase and 0.918 and 0.999 in the testing phase, respectively.

Conclusion: The TQ content of each sample of black cumin, which was collected from various geographical locations, was determined quantitatively. The quantity of thymoquinone fluctuates depending on geographic variances, according to HPLC data. Five different AI-based models, including SWLR, PCR, LSSVM, ANFIS, and LSQ-Boost, were used to simulate the chromatographic behavior of TQ information of retention duration and peak area using various independent factors. Additionally, SAE, WAE, NNE, and ANFIS-E are informed by the application of ensemble machine learning to enhance the performance of AI-based models. Comparing the approaches to the individual models, they both demonstrated lower error values in terms of RMSE and MSE.


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APA

Işık, S., Usman, A., & Abba, S.I. (2023). A chemometrics-based approach for the determination of thymoquinone from Nigella sativa L. (Black Cumin) seeds of different geographical regions using the HPLC technique. İstanbul Journal of Pharmacy, 53(3), 320-328. https://doi.org/10.26650/IstanbulJPharm.2023.1181298


AMA

Işık S, Usman A, Abba S I. A chemometrics-based approach for the determination of thymoquinone from Nigella sativa L. (Black Cumin) seeds of different geographical regions using the HPLC technique. İstanbul Journal of Pharmacy. 2023;53(3):320-328. https://doi.org/10.26650/IstanbulJPharm.2023.1181298


ABNT

Işık, S.; Usman, A.; Abba, S.I. A chemometrics-based approach for the determination of thymoquinone from Nigella sativa L. (Black Cumin) seeds of different geographical regions using the HPLC technique. İstanbul Journal of Pharmacy, [Publisher Location], v. 53, n. 3, p. 320-328, 2023.


Chicago: Author-Date Style

Işık, Selin, and Abdullahi Garba Usman and Sani Isah Abba. 2023. “A chemometrics-based approach for the determination of thymoquinone from Nigella sativa L. (Black Cumin) seeds of different geographical regions using the HPLC technique.” İstanbul Journal of Pharmacy 53, no. 3: 320-328. https://doi.org/10.26650/IstanbulJPharm.2023.1181298


Chicago: Humanities Style

Işık, Selin, and Abdullahi Garba Usman and Sani Isah Abba. A chemometrics-based approach for the determination of thymoquinone from Nigella sativa L. (Black Cumin) seeds of different geographical regions using the HPLC technique.” İstanbul Journal of Pharmacy 53, no. 3 (Apr. 2024): 320-328. https://doi.org/10.26650/IstanbulJPharm.2023.1181298


Harvard: Australian Style

Işık, S & Usman, A & Abba, SI 2023, 'A chemometrics-based approach for the determination of thymoquinone from Nigella sativa L. (Black Cumin) seeds of different geographical regions using the HPLC technique', İstanbul Journal of Pharmacy, vol. 53, no. 3, pp. 320-328, viewed 28 Apr. 2024, https://doi.org/10.26650/IstanbulJPharm.2023.1181298


Harvard: Author-Date Style

Işık, S. and Usman, A. and Abba, S.I. (2023) ‘A chemometrics-based approach for the determination of thymoquinone from Nigella sativa L. (Black Cumin) seeds of different geographical regions using the HPLC technique’, İstanbul Journal of Pharmacy, 53(3), pp. 320-328. https://doi.org/10.26650/IstanbulJPharm.2023.1181298 (28 Apr. 2024).


MLA

Işık, Selin, and Abdullahi Garba Usman and Sani Isah Abba. A chemometrics-based approach for the determination of thymoquinone from Nigella sativa L. (Black Cumin) seeds of different geographical regions using the HPLC technique.” İstanbul Journal of Pharmacy, vol. 53, no. 3, 2023, pp. 320-328. [Database Container], https://doi.org/10.26650/IstanbulJPharm.2023.1181298


Vancouver

Işık S, Usman A, Abba SI. A chemometrics-based approach for the determination of thymoquinone from Nigella sativa L. (Black Cumin) seeds of different geographical regions using the HPLC technique. İstanbul Journal of Pharmacy [Internet]. 28 Apr. 2024 [cited 28 Apr. 2024];53(3):320-328. Available from: https://doi.org/10.26650/IstanbulJPharm.2023.1181298 doi: 10.26650/IstanbulJPharm.2023.1181298


ISNAD

Işık, Selin - Usman, Abdullahi Garba - Abba, SaniIsah. A chemometrics-based approach for the determination of thymoquinone from Nigella sativa L. (Black Cumin) seeds of different geographical regions using the HPLC technique”. İstanbul Journal of Pharmacy 53/3 (Apr. 2024): 320-328. https://doi.org/10.26650/IstanbulJPharm.2023.1181298



TIMELINE


Submitted28.09.2022
Accepted22.09.2023
Published Online28.12.2023

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