Feasibility of UV-Vis spectral fingerprinting combined with chemometrics for rapid detection of Phyllanthus niruri adulteration with Leucaena leucocephala

Phyllanthus niruri is widely used in Indonesia as immunostimulant. The morphology of Leucaena leucocephala leaves is similar to that of P. niruri leaves. L. leucocephala is easy to find and collect because it is widely distributed in the world. Therefore, it is likely P. niruri could be adultera...

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Main Authors: Mohamad Rafi, Nurcahyo, Bayu, Wulan Tri Wahyuni, Arif, Zulhan, Dewi Anggraini Septaningsih, Sastia Prama Putri, Fukusaki, Eiichiro
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2021
Online Access:http://journalarticle.ukm.my/17172/1/10.pdf
http://journalarticle.ukm.my/17172/
https://www.ukm.my/jsm/malay_journals/jilid50bil4_2021/KandunganJilid50Bil4_2021.html
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Institution: Universiti Kebangsaan Malaysia
Language: English
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Summary:Phyllanthus niruri is widely used in Indonesia as immunostimulant. The morphology of Leucaena leucocephala leaves is similar to that of P. niruri leaves. L. leucocephala is easy to find and collect because it is widely distributed in the world. Therefore, it is likely P. niruri could be adulterated with L. leucocephala. Therefore, identification and authentication of P. niruri is important to ensure the raw materials used are original without any substitution or mixture with other similar plants causing inconsistencies in their efficacy. In this paper, we described feasibility used of UV-Vis spectral fingerprinting and chemometrics for rapid method for the identification and detection of P. niruri leaves adulterated with L. leucocephala leaves. UV-Vis spectra of samples measured in the interval of 200-800 nm and signal smoothing followed by standard normal variate were used for pre-processing the spectral data. Principal component analysis (PCA) with the absorbance data from the pre-processed UV-Vis spectra in the range of 250-700 nm as variables could distinguish P. niruri from L. leucocephala. PCA followed by discriminant analysis (DA) could successfully classified P. niruri mixed with 5, 25, and 50% L. luecocephala into their respective groups (96.81%). We also employed soft independent modelling of class analogy (SIMCA) for authentication of P. niruri and found that 88.3% of the samples were also correctly classified into their respective groups. A combination of UV-Vis spectroscopy with chemometrics, such as PCA-DA and SIMCA, were used for the first time for the identification and detection of P. niruri adulterated with L. leucocephala.