Int J App Pharm, Vol 11, Issue 4, 2019, 258-263Original Article


APPLICATION OF 1H-NMR SPECTA AND MULTIVARIATE ANALYSIS FOR THE AUTHENTICATION OF CURCUMA XANTHORRHIZA FROM ZINGIBER CASSUMUNAR

THERESIA WIJAYANTI1, SUGENG RIYANTO1, ENDANG LUKITANINGSIH1, ABDUL ROHMAN1,2*

1Departement of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta, 55281, Indonesia, 2Institute of Halal Industry and Systems, Universitas Gadjah Mada, Yogyakarta, 55281, Indonesia
Email: abdulkimfar@gmail.com

Received: 05 Feb 2019, Revised and Accepted: 10 May 2019

ABSTRACT

Objective: This study was aimed to apply metabolite fingerprinting for the authentication of Curcuma xanthorrhiza adulterated with Zingiber cassumunar using 1H-NMR spectroscopy and multivariate analysis (chemometrics) methods, namely principal component analysis (PCA) and partial least square–discriminant analysis (PLS-DA).

Methods: The pure dried powder samples of C. xanthorrhiza from different regions, Z. cassumunar, and its binary mixtures of C. xanthorrhiza with various concentrations of Z. cassumunar as adulterants were prepared for 1H-NMR measurements. The binary mixtures were prepared by mixing C. xanthorrhiza with various concentrations (10%, 25%, 40%, 50%, and 75%) of Z. cassumunar. 1H-NMR spectra were subjected to multivariate analysis for classification using PCA and PLS-DA.

Results: A diverse group of metabolites could be detected by 1H-NMR spectroscopy. PCA using the chemical shift in 1H-NMR spectra of the plant extracts as variables clearly discriminated pure C. xanthorrhiza extracts from different origins and C. xanthorrhiza extract adulterated with Z. cassumunar. PLS-DA employed to enhance the separation obtained from the PCA model resulted in well separation and good classification of pure C. xanthorrhiza from the adulterated ones.

Conclusion: The developed method could be a useful and powerfull tools to assess adulteration practice and to evaluate the authentication of C. xanthorrhiza extracts.

Keywords: Metabolite fingerprinting, 1H-NMR spectroscopy, C. xanthorrhiza, Authentication, Principal component analysis, Partial least square-discriminant analysis

© 2019 The Authors. Published by Innovare Academic Sciences Pvt Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
DOI: http://dx.doi.org/10.22159/ijap.2019v11i4.32417

INTRODUCTION

In the last decade, the metabolomic approach has been established as a well-known technique in the field of plant science and natural product chemistry with the main objective to identify and quantify all the metabolites contained in an organism under certain condition [1, 2]. One of the metabolomic approaches is metabolite fingerprinting, a method to classify and discriminate samples based on its metabolite pattern or ‘fingerprint’. These metabolite patterns can be provided by various high-throughput analytical methods such as mass spectrometry (MS), nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), or liquid chromatography-nuclear magnetic resonance (LC-NMR) [2, 3]. One of the most popular analytical methods used in metabolite fingerprinting in the last recent years is nuclear magnetic resonance (NMR) spectroscopy. Proton (1H)-NMR spectroscopy gained its popularity because of its capability for simultaneous detection of diverse groups of secondary metabolites, fast, convenient, and effective for discriminating between groups of samples with relatively simple sample preparation [1, 2].

NMR-based metabolite fingerprinting has been applied in many different fields. Some of them were discrimination of wild or transgenic plants and also monitoring the response of plants to stress or wounds. Another important application of NMR-based metabolite fingerprinting is for classification and characterization of different species of medicinal plants, such as Curcuma xanthorrhiza. This approach can be a very powerful tool for quality control and authentication of C. xanthorrhiza used as a raw material in herbal medicine industries [1].

C. xanthorrhiza, also known as temulawak belongs to family Zingiberaceae and is widely cultivated around the world, especially in Southeast Asia due to its variety of pharmacological activities such as anticancer, antimicrobial, anti-inflammatory, antioxidant, anticandidal, antihyperglycemic, and antihypertensive effects [4-6]. This herbal plant was commonly used as food supplements, herbal drink, syrup, and has recently gained popularity as raw material in herbal industries [7, 8]. Most of the potential pharmacological activities of C. xanthorrhiza are believed to be related to various bioactive and phytochemical compounds, which include xanthorrhizol (1.48-1.63%), curcuminoids such as curcumin and demethoxycurcumin (1-2%), phelandren, camphor, tumerol, sineol, borneol, flavonoids, and sesquiterpenes [9].

Because the adulteration practice of herbal plant used as raw material has became a serious problem, the authentication of C. xanthorrhiza needs to be performed in order to ensure its quality, safety, and efficacy [10, 11]. The adulteration practice, either intentionally or unintentionally, usually includes partial or full substitution of original crude drugs with other substances which is cheaper, either free from or inferior in therapeutic properties. The most common rhizome used as an adulterant in C. xanthorrhiza is Zingiber cassumunar which also belongs to family Zingiberaceae, due to the similar color and similar metabolites content of both rhizomes [12]. Proton NMR-based metabolite fingerprinting combined with chemometric methods of principal component analysis (PCA) and partial least square–discriminant analysis (PLS-DA), could be an appropriate method to assess the authentication of C. xanthorrhiza extract.

Proton (1H)-NMR metabolite fingerprinting and chemometrics has been used for the authentication of Curcuma longa adulterated with Curcuma manga [13]. In our best knowledge, there is no publication regarding authentication of C. xanthorrhiza extract which is adulterated with Z. cassumunar. This study proposed the application of metabolite fingerprinting for the authentication of C. xanthorrhiza adulterated with Z. cassumunar using 1H-NMR spectroscopy and chemometric methods of PCA and PLS-DA. With PCA, separation of samples based on the pattern of the signals in the spectra could be accomplished. Meanwhile, by conducting PLS-DA, classification of pure and adulterated samples could be developed. Therefore, this study was aimed to develop sufficient and suitable techniques (combination of 1H-NMR spectra and chemometrics) as very powerful tools for the authentication of C. xanthorrhiza extracts.

MATERIALS AND METHODS

Plant materials

Curcuma xanthorrhiza rhizomes were collected from Sleman (Yogyakarta), Karanganyar, Pati, Wonogiri, and Sukolilo (Central Java), meanwhile, Z. cassumunar rhizomes were obtained from Yogyakarta. The identification of rhizomes used in this study was performed in the Department of Pharmaceutical Biology, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta, Indonesia. These rhizomes were washed and then chopped into small and thin pieces, followed by air drying. The dried thin pieces of rhizomes were then ground into fine powder form and were used as samples for 1H-NMR measurements.

Sample preparation for 1H-NMR measurements

Pure dried powder samples of C. xanthorrhiza from each region, Z. cassumunar, and binary mixtures of C. xanthorrhiza with various concentrations of Z. cassumunar as adulterants were prepared for 1H-NMR measurements. The binary mixtures were prepared by mixing C. xanthorrhiza with various concentrations (10%, 25%, 40%, 50%, and 75%) of Z. cassumunar as adulterants in a total weight of 5 g.

1H-NMR spectra measurements

Twenty-five mg of each dried powder samples (pure and binary mixtures) were weighed and transferred in 2 ml micro-tubes and then added with 500 µl of CD3OD and 500 µl of KH2PO4 buffer (pH 6.0) in D2O containing trimethylsilyl propionic acid (TSP) 0.01%. The mixture was vortexed (Vortex Mixer Maxi MixTM II, Thermo Fisher Scientific, Waltham, MA USA) for 1 min followed by ultrasonication for 20 min and centrifugation (Centrifuge MPW-260, MPW Med. Instruments, Warsaw, Poland) at 13000 rpm for 10 min to obtain a clear supernatant. Approximately of 600 µl of the supernatant was transferred to an NMR tube and was immediately subjected to 1H-NMR measurements using a preset setting for all the samples. The 1H-NMR measurements were implemented using a 500 MHz NMR Spectrometer (JEOL ECZR, JEOL Ltd., Tokyo, Japan).

Bucketing of 1H-NMR spectra and principal component analysis

The 1H-NMR spectra were automatically reduced to ASCII files using MestreNova software (v. 12.0, Mestrelab Research, Santiago de Compostela, Spain). Spectra intensities were reduced to buckets with the spectral width δ 0.04 forming a region of 0.08-10.04 ppm and the total variables of 250 chemical shifts bin were generated for each 1H-NMR spectrum. The generated ASCII files were subjected to PCA and PLS-DA using XLSTAT add-ins (v. 2018.2.50198) integrated with Microsoft Excel.

Statistical analysis

Multivariate analysis of principal component analysis (PCA) and partial least square-discriminant was carried with the software of XL-STAT and Microsoft Excel (Microsoft Inc.), respectively.

RESULTS AND DISCUSSION

1H-NMR measurements and principal component analysis (PCA)

Representative one-dimensional 1H-NMR spectra of C. xanthorrhiza extracts from different origins, Z. cassumunar extract, and C. xanthorrhiza adulterated with Z. cassumunar were shown in fig. 1. where a diverse range of metabolites of C. xanthorrhiza and Z. cassumunar could be observed. Proton signals in the regions of 3.90, 7.22, 7.28, and 6.80 ppm corresponds to curcumin, whereas proton signals in the regions of 3.94, 5.89, and 6.92 ppm is correlated to demethoxycurcumin. Besides of that, signals in the regions of 1.52, 1.66, 7.02, and 6.64 ppm is characterized to be the signals of xanthorrhizol. Proton signals correspond to glucose and sucrose are observed in the regions of 4.58–5.38 ppm [14].

Fig. 1: 1H-NMR spectra of (a): Curcuma xanthorrhiza from different regions; (b): Curcuma xanthorrhiza and Zingiber cassumunar; (C): Curcuma xanthorrhiza, Zingiber cassumunar, and Curcuma xanthorrhiza adulterated with 40% Zingiber cassumunar

After the 1H-NMR spectra were reduced to buckets and converted to ASCII files, principal component analysis (PCA) was carried out to observe the differences between the spectra of each sample. PCA is an unsupervised pattern recognition method used to decrease the dimensionality of the multivariate data set while conserving most of the variance within it [15, 16]. Fig. 2 showed PCA score plot of the 1H-NMR spectra of C. xanthorrhiza extract from different origins. C. xanthorrhiza from various regions were mapped in three well-separated clusters that took place in the first two factors (Fs) which cumulatively account for 95.43% of the variation. The first factor (F1) unfold the differences of C. xanthorrhiza from various regions for 68.50% variance. C. xanthorrhiza from Sukolilo, Sleman, and Pati were located in negative side of F1 and F2, and were clearly separated from either C. xanthorrhiza from Karanganyar or Wonogiri.

Fig. 2: Principal component analysis (PCA) score plot of Curcuma xanthorrhiza from different regions

Fig. 3: PCA score plot of Curcuma xanthorrhiza and Curcuma xanthorrhiza adulterated with various concentrations of Zingiber cassumunar

PCA was also implemented to 1H-NMR spectra obtained from C. xanthorrhiza and C. xanthorrhiza adulterated with various concentration of Z. cassumunar to discriminate the pure C. xanthorrhiza extracts from adulterated ones. Fig. 3 displayed the score plot and loadings plot of C. xanthorrhiza and C. xanthorrhiza adulterated with various concentration of adulterants. The PCA score plot exhibits three clearly separated clusters (fig. 3a.), with the most variance, was displayed by F1 at 68.2%. Pure C. xanthorrhiza and C. xanthorrhiza adulterated with 10% of Z. cassumunar were located in the negative side of F1 and F2, which were well separated from pure Z. cassumunar and C. xanthorrhiza adulterated with 75% of Z. cassumunar. Meanwhile, C. xanthorrhiza adulterated with 25, 40, and 50% of Z. cassumunar was clustered separately from other samples in the positive side of F1. The adulterated C. xanthorrhiza extracts were clustered between pure C. xanthorrhiza and pure Z. cassumunar according to F2 score plot.

Classification using partial least square–discriminant analysis (PLS-DA)

In order to improve the separation obtained from PCA model of C. xanthorrhiza and C. xanthorrhiza adulterated with various concentrations of Z. cassumunar as adulterants, the supervised pattern recognition method PLS-DA was carried out. PLS-DA belongs to supervised pattern recognition method because of its ability to classifying objects to certain class or group if the required passing grade of the group is achieved [17]. In this study, PLS-DA was engaged to discriminate pure C. xanthorrhiza and adulterated C. xanthorrhiza. Table 1 compiled the classification process of each observation into the class or group for which the function value is the highest. The results of this classfication process could be seen in fig. 4 that displayed the observations on the axes.

Table 1: Pre-and post-classification and scores of Curcuma xanthorrhiza and Curcuma xanthorrhiza adulterated with Zingiber cassumunar using partial least square–discriminant analysis (PLS-DA)

Observation Weight Y1 Pred (Y1)

F

(Adulterated)

 F (C. xantho-rrhiza) F (Z. cassu-munar)

P

(Adulterated)

 P (C. xantho-rrhiza)

P

(Z. cassu-munar)
Zingeber cassumunar (Zs)10% 1 Adulterated Adulte-rated 1.108 -0.009 -0.100 0.615 0.201 0.184
Zs 25% 1 Adulterated Adulte-rated 1.026 -0.013 -0.013 0.586 0.207 0.207
Zs 40% 1 Adulterated Adulte-rated 1.067 -0.010 -0.057 0.600 0.204 0.195
Zs 50% 1 Adulterated Adulte-rated 0.872 0.048 0.080 0.529 0.232 0.239
Zs 75% 1 Adulterated Adulte-rated 0.875 -0.009 0.134 0.529 0.219 0.252
Zs 100% 1 Z. cassu-munar Z. cassu-munar 0.044 -0.004 0.961 0.224 0.214 0.562
C. xanthorrhiza 100% 1 C. xantho-rrhiza C. xantho-rrhiza 0.007 0.997 -0.004 0.214 0.575 0.211

F = scores during Partial Least Square–Discriminant Analysis (PLS-DA).

Fig. 4: PLS-DA score plot of Curcuma xanthorrhiza and Curcuma xanthorrhiza adulterated with various concentrations of Zingiber cassumunar as adulterants

PLS-DA model provided better class separation of pure C. xanthorrhiza from the adulterated C. xanthorrhiza than that provided by PCA model. The efficiency of PLS-DA in classifying and discriminating the samples can be assessed through the confusion matrix as shown in table 2. The confusion matrix presented the percentage of the observations that have been well classified. This is equal to the ratio of the number of well-classified observations over the total number of observations. In this study, the percentage of well-classified observation is equal to 100%.

Table 2: Confusion matrix of Curcuma xanthorrhiza and adulterated Curcuma xanthorrhiza with Zingiber cassumunar obtained during analysis with partial least square–discriminant analysis (PLS-DA)

from \ to Adulterated C. xanthorrhiza Z. cassumunar Total % correct
Adulterated 5 0 0 5 100.00%
C. xanthorrhiza 0 1 0 1 100.00%
Z. cassumunar 0 0 1 1 100.00%
Total 5 1 1 7 100.00%

C. xanthorrhiza = Curcuma xanthorrhiza; Z. cassumunar = Zingiber cassumunar

CONCLUSION

Metabolite fingerprinting using 1H-NMR spectroscopy and chemometrics proposed in this study could be applied for the authentication of C. xanthorrhiza adulterated with Z. cassumunar. The combination of chemometrics of PCA and PLS-DA allowed the consistent discrimination and classification of pure C. xanthorrhiza and C. xanthorrhiza adulterated with Z. cassumunar.

ACKNOWLEDGMENT

The authors would like to thank Faculty of Pharmacy, Universitas Gadjah Mada (UGM) and the Ministry of Research and Higher Education, Republic Indonesia for the financial support through Directorate of Research UGM via scheme “World Class research” awarded to Prof. Dr. Abdul Rohman with contract number 1973/UN.1. DITLIT/DIT-LIT/lT/2019.

AUTHORS CONTRIBUTIONS

TW performed research activities and analyzed data. AR, SR and EL designed research, prepared manuscript and made critical thinking on the manuscript.

CONFLICT OF INTERESTS

Declared none

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