classification of chili powders by high performance liquid chromatography‐diode array detection

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This article was downloaded by: [University of Sydney] On: 27 August 2014, At: 06:59 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Analytical Letters Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/lanl20 Classification of Chili Powders by High Performance Liquid ChromatographyDiode Array Detection Esther Forgács a & Tibor Cserháti a a Institute of Materials and Environmental Chemistry, Chemical Research Centre , Hungarian Academy of Sciences , Budapest, Hungary Published online: 04 Jan 2007. To cite this article: Esther Forgács & Tibor Cserháti (2006) Classification of Chili Powders by High Performance Liquid ChromatographyDiode Array Detection, Analytical Letters, 39:15, 2775-2785, DOI: 10.1080/00032710600824771 To link to this article: http://dx.doi.org/10.1080/00032710600824771 PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions

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Page 1: Classification of Chili Powders by High Performance Liquid Chromatography‐Diode Array Detection

This article was downloaded by: [University of Sydney]On: 27 August 2014, At: 06:59Publisher: Taylor & FrancisInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office:Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

Analytical LettersPublication details, including instructions for authors and subscriptioninformation:http://www.tandfonline.com/loi/lanl20

Classification of Chili Powders by HighPerformance Liquid Chromatography‐DiodeArray DetectionEsther Forgács a & Tibor Cserháti aa Institute of Materials and Environmental Chemistry, Chemical ResearchCentre , Hungarian Academy of Sciences , Budapest, HungaryPublished online: 04 Jan 2007.

To cite this article: Esther Forgács & Tibor Cserháti (2006) Classification of Chili Powders by HighPerformance Liquid Chromatography‐Diode Array Detection, Analytical Letters, 39:15, 2775-2785, DOI:10.1080/00032710600824771

To link to this article: http://dx.doi.org/10.1080/00032710600824771

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”)contained in the publications on our platform. However, Taylor & Francis, our agents, and ourlicensors make no representations or warranties whatsoever as to the accuracy, completeness, orsuitability for any purpose of the Content. Any opinions and views expressed in this publicationare the opinions and views of the authors, and are not the views of or endorsed by Taylor &Francis. The accuracy of the Content should not be relied upon and should be independentlyverified with primary sources of information. Taylor and Francis shall not be liable for anylosses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilitieswhatsoever or howsoever caused arising directly or indirectly in connection with, in relation to orarising out of the use of the Content.

This article may be used for research, teaching, and private study purposes. Any substantialor systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, ordistribution in any form to anyone is expressly forbidden. Terms & Conditions of access and usecan be found at http://www.tandfonline.com/page/terms-and-conditions

Page 2: Classification of Chili Powders by High Performance Liquid Chromatography‐Diode Array Detection

HPLC

Classification of Chili Powdersby High Performance Liquid

Chromatography-Diode Array Detection

Esther Forgacs and Tibor Cserhati

Institute of Materials and Environmental Chemistry, Chemical Research

Centre, Hungarian Academy of Sciences, Budapest, Hungary

Abstract: The color pigments of six chili powders of different origins (China, Bali,

Pakistan, Malaysia, India, and Thailand) were separated and quantified by reversed-

phase high-performance liquid chromatography (RP-HPLC) using a narrow-bore octa-

decylsilica column (Purospher, 125 � 3 mm I.D., Merck, Darmstadt, Germany),

gradient elution, and diode array detector (DAD). The similarities and dissimilarities

among the pigment composition of chili powders have been elucidated by principal

component analysis (PCA). The RP-HPLC separated 71–111 pigment fractions

depending on the detection wavelength and on the origin of chili powder. The

pigment composition of chili powders from Malayia and China showed marked simi-

larities while the composition of pigments of other chili powders was different. It was

concluded that RP-HPLC–DAD can be successfully employed for the separation and

quantitative determination of pigments of chili powders of various origins and may

help the classification of chili powders and facilitate the authenticity test of such

food products.

Keywords: Chili, HPLC, authenticity

INTRODUCTION

The quantity and composition of pigments in foods and food products exert a

marked influence on the consumer acceptance and, consequently, on the

Received 19 January 2005; accepted 28 April 2006

Address correspondence to Esther Forgacs, Institute of Materials and Environ-

mental Chemistry, Chemical Research Centre, Hungarian Academy of Sciences,

Budapest, Hungary. E-mail: [email protected]

Analytical Letters, 39: 2775–2785, 2006

Copyright # Taylor & Francis Group, LLC

ISSN 0003-2719 print/1532-236X online

DOI: 10.1080/00032710600824771

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commercial value of the products. It has been established many times that one

of the main properties employed for the evaluation of the product quality is the

color, that is, an adequate pigment composition considerably enhances the

marketability of the products. A desirable color is due to the complex

mixture of various constituents mixed in proper proportions. The exact

knowledge of the stability of pigments against hydrolysis, oxidation, and

other environmental and technological conditions is also of paramount import-

ance, because it may help the prediction of the product shelf-life and the

assessment of the influence of technological steps on the pigments resulting

in more consumer friendly processing methods (Morais et al. 2002; Cserhati

et al. 2002). Furthermore, the qualitative determination and identification of

pigments may contribute to the establishment of the provenance of the

product and to its exact qualification (Revilla et al. 2001). Unfortunately,

traditional analytical methods are generally unsuitable for the separation

and accurate determination of the particular fractions of complex pigment

mixtures. Moreover, they do not contain any useful information on the

concentration of the individual pigments and they are not suitable for their

identification. The high separation capacity of various chromatographic

techniques makes them a method of preference for the analysis of pigments

(Airs et al. 2001). The successful separation of anthocyanins in red wines

(Berente et al. 2001), color pigments in paprika (Hayashi et al. 2001), theafla-

vins of black tea (Du et al. 2001), and color pigments of chili powder

(Capsicum frutescens) (Cserhati et al. 2000) has been recently reported.

Principal component analysis (PCA), a versatile and easy-to-use multi-

variate mathemathical-statistical method was developed to contribute to the

extraction of maximal information from large data matrices containing

numerous columns and rows (Mardia et al. 1979). Use of PCA makes

possible the elucidation of the relationship between the columns and rows

of any data matrix without being the dependent variable. It is a so-called

projection method representing the original data in smaller dimensions. It

calculates the correlations (similarities and dissimilarities) between the

columns of the data matrix and classifies the variables according to the coeffi-

cients of correlations taking into considerations simultaneously the magnitude

and sign of the coefficients of correlation. PCA frequently is used in many

fields of up-to date research. Thus, it has been employed in quantitative

structure-activity relationship (QSAR) studies (Drew et al. 1998), for the

exploration of molecular structure-property relationships (Seybold 1999),

for the evaluation of molecular lipophilicity (Sarbu and Todor 1998;

Mannhold et al. 1998), for theoretical organic chemistry (Heberger and

Lopata 1998), for quantitative structure-retention studies in chromatography

(Heberger and Gorgenyi 1999), for the elucidation of structure-biodegradation

relationships (Damborsky et al. 1998), for the clustering of amino acids

(Zaliani, and Gancia 1999), for the assessment of solvent properties

(Katritzky et al 1999), and polarity indicators in gas chromatography

(Heberger 1999), etc. As the resulting matrices of PC loadings and variables

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are generally multidimensional they cannot be evaluated by visual methods.

Nonlinear mapping technique (NLMAP) has been developed for the

reduction of the dimensionality of such matrices (Sammon 1969).

The aims of this work were the separation and quantitation of the color

pigments of assorted chili (Capsicum frutescenc) powders by RP-HPLC/DAD

Table 1. Steps of gradient elution employed

for the RP-HPLC separation of color pigments

of chili (Capsicum frutescenc) powders.

Solvent A ¼ methanol-acetonitrile (80 : 20,

v/v); solvent B ¼ bidistilled water

Time (min) Solvent A Solvent B

0 15 85

25 80 20

35 80 20

45 90 10

55 90 10

58 97 3

90 97 3

Figure 1. Separation of color pigments of chili powder (origin:Pakistan) at 340 nm.

For conditions see Materials and Methods.

Classifying Chili Powders by HPLC-DAD 2777

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and the employment of PCA and nonlinear mapping technique for the classifi-

cation of the chili powders according to the chromatographic profile of pigments.

EXPERIMENTAL

Chili powders of different origin (sample I: China; sample II: Bali; sample III:

Pakistan; sample IV: Malaysia; sample V: India; sample VI: Thailand) were

purchased in a local market in Budapest (Hungary). Pigments were

extracted from samples of 2 g weight with 15 mL of acetone. The mixtures

were homogenized, then centrifuged. The procedure was repeated until the

extracts were colorless (normally 3 extraction steps were enough). The

combined extracts were dried over anhydrous sodium sulfate and then dried

in a rotary evaporator at 358C. The residue was dissolved in 10 mL of

acetone, filtered through a 0.45 mm membrane filter, and used for RP-HPLC

analysis. Solvents of HPLC quality used for extraction and HPLC develop-

ment were purchased from Merck (Darmstadt, Germany). The HPLC separ-

ation of pigments was performed with a Waters LC Module I HPLC

instrument with an injection device of variable volume and a Waters 746

Data Module integrator (Waters-Millipore Inc., Milford, Massaschuttes,

Figure 2. Separation of color pigments of chili powder (origin: Pakistan) at 440 nm.

For conditions see Materials and Methods.

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USA). Separation and quantitative determination of pigments were carried out

on a narrow-bore octadecylsilica column (Purospher RP-18, 125 � 3 mm I.D.;

particle size, 5 mm; carbon loading, 4.9%; Merck, Darmstadt, Germany). The

column was not thermostated. Analyses were carried out at ambient tempera-

ture (21 + 18C). The ratio of yellow and red pigments was assessed by eval-

uating the chromatograms at 340 (yellow) and 440 nm (red). The flow rate was

0.50 mL/min. The gradient steps employed for the RP-HPLC separation of

pigments are compiled in Table 1.

Gradient steps were linear. Three parallel measurements were carried out

for each sample, and the relative standard deviation (RSD%) of the retention

times and peak areas were computed (intraday reproducibility). The interday

reproduccibility was calculated from the three parallel determinations carried

out for 4 consecutive working days. The intraday and interday reproducibil-

ities were compared with the “F” probe.

Principal component analysis was applied to assess the similarities

and differences among the pigment compositions of chili powders. The six

chili powders were the variables. As the retention time of pigment fractions

showed high variations among the samples the retention times and,

Figure 3. Separation of color pigments of chili powder (origin: Bali) at 340 nm. For

conditions see Materisls and Methods.

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consequently, the relative peak areas of the individual peaks cannot be

employed as observations for PCA. Therefore, the peak areas were summar-

ized between the retention time intervals of 0–15, 15–30, 30–45, 45–60,

60–75, and 75–90 min at both 340 and 440 nm and were included in PCA

as observations (altogether 12 variables). The limit of the total variance

explained by the principal components was set to 99%. In order to facilitate

the evaluation of the multidimensional matrices of PC loadings and

Figure 4. Separation of color pigments of chili powder (origin: Bali) at 440 nm. For

conditions see Materials and Methods.

Table 2. Amount of pigments (%) in various sections of the chromatograms of chili

powders of various origin determined at 440 and 340 nm

Retention

time

interval

(min)

Wavelength

(nm) China Bali Pakistan Malaysia India Thailand

0–15 440 2.97 1.06 5.75 2.92 2.93 3.23

340 2.88 1.26 7.15 3.98 1.18 1.59

15–30 440 8.25 4.70 12.17 6.68 12.37 7.90

340 13.75 14.37 34.67 12.08 12.07 5.07

30–45 440 20.86 17.72 27.23 18.84 36.80 21.21

340 11.55 20.31 13.56 17.01 62.22 12.56

45–60 440 18.35 15.85 17.74 22.67 13.69 19.64

340 8.26 11.10 7.10 12.38 4.53 14.22

60–75 440 23.23 14.87 18.79 23.79 16.19 24.70

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variables their dimensionality has been reduced to two by the nonlinear

mapping technique. The iteration of the nonlinear maps was carried out

to the point when the difference between the two last iterations was lower

than 1028.

Table 3. Similarities and dissimilarities between the

pigment composition of chili powders. Results of principal

component analysis

No of PC

explained % Eigenvalue

Variance

explained %

Total

variance

1 3.91 65.17 65.17

2 1.02 16.93 82.21

3 0.70 11.70 93.81

4 0.29 4.79 98.60

Figure 5. Similarities and dissimilarities of chili powders according to the compo-

sition of color pigments. Two-dimensional nonlinear map of principal component

loadings. No. of iterations: 97; maximal error: 1.05 . 1022.

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Software for PCA and nonlinear mapping was developed by Dr. Barna

Bordas (Plant Protection Institute, Hungarian Academy of Sciences,

Budapest, Hungary).

RESULTS AND DISCUSSION

Color pigments of each chili powder were effectively separated into many

fractions under the RP-HPLC conditions applied as demonstrated in Figs. 1–4.

The chromatographic profiles of pigments are different at 340 and 440

nms suggesting that both red and yellow pigments occur equally in each

chili powder (compare Figs. 1 and 2 and 3 and 4). This finding indicates

that the determination of the pigment composition at minimally two

different wavelengths is a prerequisite of the accurate evaluation of the

pigment composition. The chromatographic profiles of pigments also show

considerable deviations according to the type of the sample (compare Figs.

1 through 3 and 2 through 4) demonstrating that the RP-HPLC analysis of

chili pigments may help the identification of the origin of chili powders.

Similar results were reported previously (Cserhati et al. 2000, 2001; Kosa

et al. 2001).

The relative peak areas of pigment fractions quantified at 340 and 440 nm

are collected in Table 2.

The data in Table 2 prove again that the amount of pigment in a time

interval considerably depends on both the origin of the sample and the

detection wavelength, consequently, the chromatographic profiles character-

ize the individual chili powder well.

The results of PCA using are compiled in Table 3.

Three principal components explain the overwhelming majority of total

variance suggesting that the six original variables can be replaced by three

background (abstract) variables with only 6.19% loss of information.

However, PCA does not confirm the reality of such theoretical variables

only indicates their mathematical possibility. The fact that the majority of

Table 4. Principal component loadings

Chili powder

No. of principal components

1 2 3

China 0.97 20.17 20.09

Bali 0.86 0.01 0.23

Pakistan 0.64 0.34 2 0.69

Malaysia 0.97 20.06 0.02

India 0.32 0.88 0.33

Thailand 0.88 20.32 0.23

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chili powder has high loadings in the first PC suggests the fundamental simi-

larity of pigment composition of chili powders. Chili originating from China

and Malaysia has the highest, those of Pakistan and India have the lowest

loadings in the first principal component.

The two-dimensional nonlinear map of PC loadings is shown in Fig. 5.

The scattering of chili powders on the map wholly supports the results

compiled in Table 4: the points representing chili powders originating from

Malaysia and China are the nearest to each other while points of chili

powders from India and Pakistan are far away from the other points, indicating

that the composition of pigment is markedly different.

The two-dimensional nonlinear map of PC variables (relative peak areas

determined at different time intervals and detection wavelengths) is shown

in Fig. 6.

The points do not form clear-cut clusters. Only the retention time intervals

0–15 min are very near to each other, indicating that the first part of chroma-

togram is not characteristic for the pigment composition of chili powders,

therefore, it cannot be employed for the identification of the samples. The

relative peak areas measured at 340 and 440 nms are well separated indicating

that both of them can be employed for the classification of chili powders.

No significant differences were found between the intraday and interday

repoducibilities of retention times and peak areas proving the good stability

Figure 6. Similarities and dissimilarities between the pigment fractions. Two-dimen-

sional nonlinear map of principal component variables. No. of iterations: 70; maximal

error: 1.51 . 1022. Numbers refer to pigment fractions in Table 2.

Classifying Chili Powders by HPLC-DAD 2783

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and reproducibility of the RP-HPLC system. The RSD values for both intraday

and interday reproducibilities were 0.9%–1.8% for retention times and 3.7%–

5.3% for peak areas. The relatively high RSD values for peak areas may be

due to the fact that some pigment fractions were not entirely separated

during the chromatographic process.

It can be concluded from the results that the color pigments of chili

powders can be readily separated and quantitated by RP-LC. The profile

and ratio of yellow and red pigments measured at 440 and 340 nm is charac-

teristic for the chili powders of different origin. Principal component analysis

is a valuable tool for the assessment of the similarities and differences among

the chili powders according to the composition of the pigments. The method

may facilitate the authenticity test of chili powders. By comparing the present

method with the other one previously published (Kosa et al. 2001) it can be

established that the analysis time of this method is shorter and the capacity

to differentiate among chili powders of different origin is the same.

REFERENCES

Airs, R.L., Atkinson, J.E., and Keely, B.J. 2001. J. Chromatogr. A, 917: 167.Berente, B., Reichenbacher, M., and Danzer, K. 2001. Fresenius J. Anal. Chem.,

371: 68.Cserhati, T., Forgacs, E., Darwish, Y., Morais, H., Mota, T., and Ramos, A.C. 2002.

J. Chromatogr. A, 949: 269.Cserhati, T., Forgacs, E., Morais, M.H., Mota, T., and Ramos, A. 2001. J. Liq.

Chromat. Relat. Technol., 24: 425.Cserhati, T., Forgacs, E., Morais, M.H., Mota, T., and Ramos, A. 2000. J. Chromatogr.

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Simmie, J.M. 1998. J. Agr. Food Chem., 46: 3016.Du, Q., Jiang, H., and Itu, Y. 2001. J. Liq. Chromat. Relat. Technol., 24: 2363.Hayashi, T., Hayashi, K., Fujita, J., Ono, M., Oka, H., Ito, Y., Matsumoto, H.,

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Heberger, K. 1999. Chemometer Intell. Lab., 47: 41.Heberger, K. and Gorgenyi, M. 1999. J. Chromatogr. A, 845: 21.Heberger, K. and Lopata, A. 1998. J. Org. Chem., 63: 8646.Katritzky, A.R., Tamm, T., Wang, Y., and Karelson, M. 1999. J. Chem. Inf. Comput.

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J. Chromatogr. A, 915: 149.Mannhold, R., Cruciani, G., Dross, K., and Rekker, R. 1998. J. Comp.-Aid. Mol. Des.,

12: 573.Mardia, K.V., Kent, J.T., and Bibby, J.M. 1979. Multivariate Analysis; Acad. Press:

London, 213.Morais, H., Rodrigues, P., Ramos, C., Almeida, V., Forgacs, E., Cserhati, T., and

Oliveira, J.S. 2002. Food Sci. Tech. Int., 8: 55.

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