Extraction optimization and characterization of water soluble red purple pigment from floral bracts of Bougainvillea glabra

Shiv Narayan Amit Kumar; Sunil Kumar Ritesh; Govindasamy Sharmila; Chandrasekaran Muthukumaran

doi:10.1016/j.arabjc.2013.07.047

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Original Article

10 (

2_suppl

); S2145-S2150

doi:

10.1016/j.arabjc.2013.07.047

Extraction optimization and characterization of water soluble red purple pigment from floral bracts of Bougainvillea glabra

Shiv Narayan Amit Kumar, Sunil Kumar Ritesh, Govindasamy Sharmila, Chandrasekaran Muthukumaran^⁎

Department of Biotechnology, School of Bioengineering, SRM University, Kattankulathur 603203, Tamilnadu, India

⁎Corresponding author. Tel.: +91 44 27452270; fax: +91 44 27453903. biopearl1981@gmail.com (Chandrasekaran Muthukumaran)

Received: 2012-10-29, Accepted: 2013-7-21, Published: 2013-05-01

Disclaimer:
This article was originally published by Elsevier and was migrated to Scientific Scholar after the change of Publisher.

Peer review under responsibility of King Saud University.

Abstract

Recently, natural dyes and pigments gain more importance in food and textile industries because of their non toxic and eco friendly characteristics. Bougainvillea glabra floral bracts are rich in betalain pigments which can be used as a dye in sensitized solar cells, medicinal and food applications. The aim of this study was to optimize the natural pigment extraction from the floral bracts by response surface methodology. Central composite design (CCD) of response surface methodology (RSM) was applied to evaluate the optimal conditions of three process variables namely mass of floral bracts (g), extraction time (h) and temperature (°C) studied at five levels. Mass of bracts and extraction time were found statistically significant in the process and correlation coefficient (R²) value of 0.96 showed that model was well fitted with the experimental values. The optimum process conditions were found to be mass of floral bracts: 3 g, contact time: 6 h and extraction temperature: 22.5 °C with maximum absorbance of 9.18. Response surface methodology was performed well to identify the optimal levels of extraction process variables and the validation of predicted model was fitted 99.76% with the experimental results conducted at the optimum conditions. Fourier Transform Infrared Spectroscopy was also confirmed the presence of betalain pigment by identifying the major functional groups.

Keywords

Natural pigment

Bougainvillea glabra

Floral bracts

Central composite design

Response surface methodology

Fourier Transform Infrared Spectroscopy

Show Related Articles from PubMed

ANOVA: analysis of variance
CCD: central composite design
FTIR: Fourier Transform Infrared Spectroscopy
OD: optical density
OFAT: one factor at a time
RSM: response surface methodology

1 Introduction

Color of the commercial products plays a vital role to attract the consumers and also represent the quality of the products (Azeredo, 2009; Downham and Collins, 2000). Synthetic dyes and pigments are widely used as coloring agents in industries for the production of commercial products. These coloring agents are a major pollutant that affects the soil and water sources (Eichlerova et al., 2007). Waste water generated from textile industries containing synthetic dyes was found toxic to the aquatic eco-system (Michaels and Lewis, 1985; Vaidya and Datye, 1982). Difficulty in treatment of textile waste water was the major issue in present days (Eichlerova et al., 2007). To overcome this problem, researchers were involved in the development of natural dyes and pigments. Various studies were reported for natural pigments derived from plant (Strack et al., 2003; Heuer et al., 1994) and microbial sources (Chiu and Poon, 1993; Cho et al., 2002; Mukherjee and Singh, 2011 ).Several plants in nature can yield pigments which can be used for many useful purposes (Feugang et al., 2006; Wu et al., 2006; Vaillant et al., 2005 ). Bougainvillea is a genus of bright flowering plants belonging to the Nyctaginaceae family. Bougainvillea is a popular ornamental plant in most areas with warm climatic conditions. Bougainvillea glabra also called as paper flower having shiny green and magenta or purple colored bracts. Betalain pigments are mainly responsible for color of the bract, particularly betacyanins (Moreno et al., 2008; Piattelli, 1981). Betacyanins are water soluble red- violet color pigment containing nitrogen in its structure (Table.1) (Moreno et al., 2008). The major advantages of betalain pigments are they are independent on pH and are more stable than anthocyanin pigments (Tanaka et al., 2008). Betalain pigments are having high potential as dye sensitizer and utilized for the photo-electrochemical studies (Hernandez-Martinez et al., 2011; Zhang et al., 2008).

Table 1 Structure of betalain pigments.

Pigment name	structure
Betanidin
Betanin

Statistical optimization methods are successfully used to identify the optimal level of various parameters involved in the process. Optimization by changing one factor at a time (OFAT) was a common and well studied method but it has many disadvantages like time consuming, expensive etc. and it does not provide details about the interaction effect of the variables involved in the process (Haaland, 1989). Response surface methodology (RSM) is a collection of statistical tool used to analyze and determine the optimal conditions within the design space of the experimental study (Myers and Montgomery, 1995). The main advantage of using RSM is to understand the interaction among the process variables with less number of experimental runs and it is utilized well for various optimization studies (Sharmila et al., 2013; Ramandi et al., 2017; Baboukani et al., 2012 ).

The main objective of the study was to determine the optimal conditions of water soluble pigment extraction process from B. glabra floral bracts using central composite design (CCD) of RSM. Mass of floral bract, contact time and temperature were chosen for the optimization study. Structural analysis of extracted pigment was also examined by FTIR.

2 Materials and methods

2.1

2.1 Collection of floral bracts

Fresh floral bracts were collected from B. glabra plant grown in SRM University campus. Floral bracts were cut approximately into 10 mm in size and used for extraction process.

2.2

2.2 Pigment extraction

Methanol and water in 0.5:1.5 ratio were used as solvent system for extraction process. 50 mL of the solvent was added to 250 mL Erlenmeyer flak containing known amount of the bracts according to the design (Table.2). Flask was tightly covered by the polyethylene cover to avoid evaporation of the solvent. Flask was kept in a temperature controlled orbital shaker for appropriate time to completely extract the pigment.

Table 2 Central composite design matrix represented in actual and coded values (in brackets) with observed and predicted response.

Run	Variables			Pigment OD
Run	(A) mass of bracts (g)	(B) time (h)	(C) temperature (°C)	Experimental	Predicted
1	1.0 (−1)	2.0 (−1)	20.0 (−1)	1.423	1.227
2	3.0 (+1)	2.0 (−1)	20.0 (−1)	2.571	2.412
3	1.0 (−1)	6.0 (+1)	20.0 (−1)	3.387	2.532
4	3.0 (+1)	6.0 (+1)	20.0 (−1)	9.514	9.132
5	1.0 (−1)	2.0 (−1)	40.0 (+1)	2.351	2.283
6	3.0 (+1)	2.0 (−1)	40.0 (+1)	1.793	2.198
7	1.0 (−1)	6.0 (+1)	40.0 (+1)	1.846	1.555
8	3.0 (+1)	6.0 (+1)	40.0 (+1)	7.140	6.886
9	0.3 (−2)	4.0 (0)	30.0 (0)	1.148	1.726
10	3.7 (+2)	4.0 (0)	30.0 (0)	7.232	7.264
11	2.0 (0)	0.6 (−2)	30.0 (0)	1.046	0.774
12	2.0 (0)	7.4 (+2)	30.0 (0)	5.036	5.868
13	2.0 (0)	4.0 (0)	13.2 (−2)	2.764	3.496
14	2.0 (0)	4.0 (0)	46.8 (+2)	2.582	2.496
15	2.0 (0)	4.0 (0)	30.0 (0)	5.382	5.127
16	2.0 (0)	4.0 (0)	30.0 (0)	4.842	5.127
17	2.0 (0)	4.0 (0)	30.0 (0)	4.656	5.127
18	2.0 (0)	4.0 (0)	30.0 (0)	4.938	5.127
19	2.0 (0)	4.0 (0)	30.0 (0)	5.924	5.127

2.3

2.3 Analytical method

After the extraction process, 10 mL of the solvent (contain soluble pigment) was taken in a falcon tube and centrifuged at 5000 rpm for 10 min. The supernatant was suitably diluted and absorbance was measured at 538 nm by using UV–Vis spectrophotometer.

2.4

2.4 Statistical optimization

Central composite design was used to evaluate the optimum conditions for extraction process. Statistical analysis was done by using Design Expert software 8.0.5.2. The three parameters selected were mass of petals (g), extraction time (h) and temperature (°C) and were studied at five levels (+2,+1,0,−1,−2). Nineteen experiments were carried out according to the design table given in Table.2 and response pigment optical density (OD) was tabulated. A second order polynomial model given in (Eq. (1)) was used to fit the observed data in CCD. All the experiments were performed in triplicate to reduce the experimental errors.

(1)

Y = α_{0} + \sum α_{i} X_{i} + \sum α_{ii} X_{i}^{2} + \sum α_{ij} X_{i} X_{j}

where α_i, α_ii, and α_ij are linear, quadratic and interaction effect coefficients respectively.

3 Results and discussion

3.1

3.1 Optimization by response surface methodology

Central composite design (CCD) of RSM was used to design the experiment and nineteen experiments were carried out according to the combination of the variables given in the design table and the observed results are given in (Table.2).

3.1.1

3.1.1 Regression analysis and model fitting

The response, pigment OD was varied from 1.041 to 9.514 in the experimental runs. The observed experimental results in each run were subjected to multiple regression analysis to calculate the regression coefficients of the model (Eq. (1)). Calculated regression coefficients were substituted in (Eq. (1)) to obtain a model (Eq. (2)) for the extraction of water soluble pigment from bracts.

(2)

Y_{Pigment OD} = 5.13 + 1.63 A + 1.50 B - 0.30 C + 1.35 AB - 0.38 AC - 0.51 BC - 0.22 A^{2} - 0.63 B^{2} - 0.76 C^{2}

Results of the regression analysis tabulated in Table.3, explained that linear effect of temperature (C), interaction effect of temperature with mass of bracts (AC) and time (BC), and square effect of mass of bracts (A²) were found to be statistically insignificant in extract process (p > 0.05). The model for pigment extraction process was modified and represented in (Eq. (3)) by neglecting the insignificant model terms.

(3)

Y_{Pigment OD} = 5.13 + 1.63 A + 1.50 B + 1.35 AB - 0.63 B^{2} - 0.76 C^{2}

The linear effect of floral bract mass and time (p < 0.05), quadratic effect of extraction time (B²), temperature (C²) (p < 0.05), and combined effect of bract mass with time (AB) (p < 0.05) showed significance on pigment extraction. High F-test value of floral bract mass (82.04) and time (69.41) of linear effect explained that these variables contribute more on extraction than other effects. Determination coefficient (R²) value near to unity denotes the quality of the good fit (Weisberg, 1985). Determination coefficient (R²) value of 0.96 revealed that the regression model was statistically significant and 0.04% of variation was not explained by the model.

Table 3 ANOVA table for pigment OD.

Source	Pigment OD
Source	Coefficient	Sum of squares	DF	Mean square	F value	p-Value prob > F
Model	5.13	97.13	9	10.79	24.44	<0.0001^a
(A) mass of bracts	1.63	36.23	1	36.23	82.04	<0.0001 ^a
(B) time	1.50	30.66	1	30.66	69.41	<0.0001 ^a
(C) temperature	−0.30	1.21	1	1.21	2.75	0.1318
AB	1.35	14.66	1	14.66	33.20	0.0003 ^a
AC	−0.38	0.81	1	0.81	1.82	0.2098
BC	−0.51	2.07	1	2.07	4.68	0.0588
A²	−0.22	0.65	1	0.65	1.48	0.2551
B²	−0.63	5.33	1	5.33	12.07	0.0070 ^a
C²	−0.76	7.78	1	7.78	17.62	0.0023 ^a
Residual		3.97	9	0.44
Lack of fit		2.94	5	0.59	2.27	0.2239
Pure error		1.04	4	0.26
Cor total		101.10	18
R²	0.960

a Significant model parameters (p < 0.05).

3.1.2

3.1.2 Surface plots

The 3D surface plots represented in Figs. 1–3 were used to study the interaction among the variables in the process (Bas and Boyaci, 2007). Combined effect of floral bract mass and time represented in Fig. 1 explained that the pigment absorbance was increased as the time increases and remains constant with mass of floral bracts. Similar trend was reported by Sinha et al. (2012) on natural dye extraction from petals of Flame of forest flower. Maximum absorbance of pigment (8.74) was observed at a high level of time (6 h) and bract mass (2.99 g).Fig. 2 shows the mutual effect of mass of floral bract and temperature. Pigment OD was gradually increased from low to high level of floral bract mass whereas it remain constant with the temperature. The optimal OD value of 6.658 was expected at 25.5 °C and 3 h of contact time. Interaction between contact time and temperature was explained by Fig. 3, where the high OD value (6.214) was observed when time and temperature were maintained at 6 h and 24.4 °C respectively.

3D surface plots showing the mutual effect between pair of variables, mass of floral bracts (A) and time (B) by keeping the third variable constant at middle level.

3D surface plots representing the interaction effect between pair of variables, mass of floral bract (A) and temperature (C) by keeping the third variable constant at middle level.

3D surface plots showing the combined effect between pair of variables, time (B) and temperature (C) by keeping the third variable constant at middle level.

The point prediction tool of the Design Expert software was used to identify the optimal value of the chosen process variables. Optimal values of floral bract mass (A), contact time (B) and extraction temperature (C) were found to be 3 g, 6 h and 22.5 °C respectively with maximum predicted response of 9.18.

3.1.3

3.1.3 Model validation

The validation experiment for the predicted optimum conditions was performed in triplicate to check the accuracy of the model. Three grams of bract was taken in the 250 mL flask containing 50 mL of the selected solvent (methanol:water: 0.5:1.5). The flask was kept at 22.5 °C for 6 h and the optical density of the extracted pigment was taken at 538 nm. The obtained optical density was found to be 9.16 which proved the model to be 99.76% accurate when compared with the predicted optical density of 9.18. This result explained that the predicted model had a good agreement with the experimental results.

3.2

3.2 FTIR analysis

The Fourier Transform Infrared (FTIR) spectral analysis was done to indentify the major functional groups present in the extracted pigment (DeSouza et al., 2003). FTIR spectrum represented in Fig. 4 shows distinct peaks at 3394, 2953, 2842, 2527, 2148, 1651, 1451, 1412, 1115, 1018 and 718 cm⁻¹ respectively. The broad and strong band at 3394 cm⁻¹ suggests (O-H) bond in stretching vibration mode and band at 2953 and 2842 cm⁻¹ indicates (C–H) symmetry in stretching mode. The wave numbers 2527 and 2148 cm⁻¹ showed the presence of (O–H) and (C≡C) in stretching vibration mode respectively. The wave number 1651 cm⁻¹ confirmed the presence of the carbonyl group (C⚌O) in stretching mode associated with amide bond. The weak peak at 1451 and 1412 cm⁻¹ suggested the presence of bending aromatic (C⚌C) bond. The peaks at 1115 and 1018 cm⁻¹ represented the (C–O) bond and the presence of the amine group (N–H) was confirmed by the wave number 718 cm⁻¹ in the spectrum. The presence of amine (N–H) and carbonyl (C⚌O) and other functional groups confirmed that the extracted red–purple pigment from B. glabra belongs to the betacyanin group of betalains.

FTIR analysis spectrum for the red–purple pigment extracted from floral bracts of B. glabra.

4 Conclusion

This study explained the utilization of B. glabra floral bracts for successful extraction of natural pigment. Mass of the floral bracts and extraction time play an important role to increase the efficiency of pigment extraction at higher levels. Experimental results revealed that the extraction of pigment was highly favored at low temperatures than at elevated levels. The optimum process conditions were found to be mass of floral bracts: 3 g, contact time: 6 h and extraction temperature: 22.5 °C with maximum optical density of 9.18. Validation of the predicted model was fitted 99.76% with the experimental results conducted at the optimum conditions. FTIR analysis of pigment showed the presence of the nitrogen (N–H) amine group and confirmed that the extracted pigment belongs to betacyanin of betalains.

Acknowledgments

Authors wish to thank the Management, Director (E&T) and Department of Biotechnology for providing necessary facilities to carry out this study and also acknowledges The Sophisticated Analytical Instrument Facility (SAIF) at IIT, Madras for FTIR analysis.

References

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Mukherjee G., Singh S.K., . Purification and characterization of a new red pigment from Monascus purpureus in submerged fermentation. Process Biochem.. 2011;46:188-192.
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Myers R.H., Montgomery D.C., . Response Surface Methodology, Process and Product Optimization Using Design Experiments. New York: John Wiley & Sons; 1995.
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[Google Scholar]
Strack D., Vogt T., Schliemann W., . Recent advances in betalain research. Phytochemistry. 2003;62:247-269.
[Google Scholar]
Tanaka Y., Sasaki N., Ohmiya A., . Biosynthesis of plant pigments: anthocyanins, betalains and carotenoids. Plant J.. 2008;54:733-749.
[Google Scholar]
Vaidya A.A., Datye K.V., . Environmental pollution during chemical processing of synthetic fibres. Colourage. 1982;14:3-10.
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Vaillant F., Perez A., Davila I., Dornier M., Reynes M., . Colourant and antioxidant properties of red-purple pitahaya (Hylocereus sp.) Fruits. 2005;60:1-10.
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Weisberg S., . Applied Linear Regression. New York: Wiley; 1985.
Wu L., Hsu H.W., Chen Y.C., Chiu C.C., Lin Y.I., Ho J.A., . Antioxidant and antiproliferative activities of red pitaya. Food Chem.. 2006;95:319-327.
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Zhang D., Lanier S.M., Downing J.A., Avent J.L., Lum J., McHale J.L., . Betalain pigments for dye-sensitized solar cells. J. Photochem. Photobiol. A: Chem.. 2008;195:72-80.
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Introduction

Materials and methods

Collection of floral bracts
Pigment extraction
Analytical method
Statistical optimization

Results and discussion

Optimization by response surface methodology
FTIR analysis

Conclusion

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[1] Azeredo H.M.C., . Betalains: properties, sources, applications, and stability–a review. Int. J. Food Sci. Technol.. 2009;44:2365-2376.
[Google Scholar]

[2] Baboukani B.S., Vossoughi M., Alemzadeh I., . Optimisation of dilute-acid pretreatment conditions for enhancement sugar recovery and enzymatic hydrolysis of wheat straw. Biosys. Eng.. 2012;111:166-174.
[Google Scholar]

[3] Bas D., Boyaci I.H., . Modeling and optimization I: usability of response surface methodology. J. Food Eng.. 2007;78:836-845.
[Google Scholar]

[4] Chiu S.W., Poon Y.K., . Submerged production of Monascus pigments. Mycologia. 1993;85:214-218.
[Google Scholar]

[5] Cho Y.J., Park J.P., Hwang H.J., Kim S.W., Choi J.W., Yun J.W., . Production of red pigment by submerged culture of Paecilomyces sinclairii. Lett. Appl. Microbiol.. 2002;35:195-202.
[Google Scholar]

[6] DeSouza R.F.V., Sussuchi E.M., De Giovani W.F., . Synthesis, electrochemical, spectral, and antioxidant properties of complexes of flavonoids with metal ions. Synth. React. Inorg. Met. Org. Chem.. 2003;33:1125-1144.
[Google Scholar]

[7] Downham A., Collins P., . Colouring our foods in the last and next millennium. Int. J. Food Sci. Technol.. 2000;35:5-22.
[Google Scholar]

[8] Eichlerova I., Homolka L., Nerud F., . Decolorization of high concentrations of synthetic dyes by the white rot fungus Bjerkandera adusta strain CCBAS 232. Dyes Pigm.. 2007;75:38-44.
[Google Scholar]

[9] Feugang J.M., Konarski P., Zou D., Stintzing F.C., Zou C., . Nutritional and medicinal use of cactus pear (Opuntia spp.) cladodes and fruits. Front. Biosci.. 2006;11:2574-2589.
[Google Scholar]

[10] Haaland P.D., . Experimental Design in Biotechnology. New York: Dekker; 1989.

[11] Hernandez-Martinez A.R., Estevez M., Vargas S., Quintanilla F., Rodriguez R., . New dye-sensitized solar cells obtained from extracted bracts of Bougainvillea glabra and Spectabilis betalain pigments by different purification processes. Int. J. Mol. Sci.. 2011;12:5565-5576.
[Google Scholar]

[12] Heuer S., Richter S., Metzger J.W., Wray V., Nimtz M., Strack D., . Betacyanins from bracts of Bougainvillea glabra. Phytochemistry. 1994;37:761-767.
[Google Scholar]

[13] Michaels G.B., Lewis D.L., . Sorption and toxicity of azo and triphenylmethane dyes to aquatic microbial populations. Environ. Toxicol. Chem.. 1985;4:45-50.
[Google Scholar]

[14] Moreno D.A., García-Viguera C., Gil J.I., Gil-Izquierdo A., . Betalains in the era of global agri-food science, technology and nutritional health. Phytochem. Rev.. 2008;7:261-280.
[Google Scholar]

[15] Mukherjee G., Singh S.K., . Purification and characterization of a new red pigment from Monascus purpureus in submerged fermentation. Process Biochem.. 2011;46:188-192.
[Google Scholar]

[16] Myers R.H., Montgomery D.C., . Response Surface Methodology, Process and Product Optimization Using Design Experiments. New York: John Wiley & Sons; 1995.

[17] Piattelli M., . The betalains: structure, biosynthesis, and chemical taxonomy. In: Conn E.E., ed. The Biochemistry of Plants. New York: Academic Press; 1981. p. :557-575.
[Google Scholar]

[18] Ramandi, N.F., Ghassempour, A., Najafi, N.M., Ghasemi, E., 2017. Optimization of ultrasonic assisted extraction of fatty acids from Borago officinalis L. flower by central composite design. Arabian J. Chem. 10, S23–S27.

[19] Sharmila G., Nidhi B., Muthukumaran C., . Sequential statistical optimization of red pigment production by Monascus purpureus (MTCC 369) using potato powder. Ind. Crop. Prod.. 2013;44:158-164.
[Google Scholar]

[20] Sinha K., Saha P.D., Datta S., . Extraction of natural dye from petals of Flame of forest Butea monosperma flower: process optimization using response surface methodology RSM. Dyes Pigm.. 2012;94:212-216.
[Google Scholar]

[21] Strack D., Vogt T., Schliemann W., . Recent advances in betalain research. Phytochemistry. 2003;62:247-269.
[Google Scholar]

[22] Tanaka Y., Sasaki N., Ohmiya A., . Biosynthesis of plant pigments: anthocyanins, betalains and carotenoids. Plant J.. 2008;54:733-749.
[Google Scholar]

[23] Vaidya A.A., Datye K.V., . Environmental pollution during chemical processing of synthetic fibres. Colourage. 1982;14:3-10.
[Google Scholar]

[24] Vaillant F., Perez A., Davila I., Dornier M., Reynes M., . Colourant and antioxidant properties of red-purple pitahaya (Hylocereus sp.) Fruits. 2005;60:1-10.
[Google Scholar]

[25] Weisberg S., . Applied Linear Regression. New York: Wiley; 1985.

[26] Wu L., Hsu H.W., Chen Y.C., Chiu C.C., Lin Y.I., Ho J.A., . Antioxidant and antiproliferative activities of red pitaya. Food Chem.. 2006;95:319-327.
[Google Scholar]

[27] Zhang D., Lanier S.M., Downing J.A., Avent J.L., Lum J., McHale J.L., . Betalain pigments for dye-sensitized solar cells. J. Photochem. Photobiol. A: Chem.. 2008;195:72-80.
[Google Scholar]

Extraction optimization and characterization of water soluble red purple pigment from floral bracts of Bougainvillea glabra

Abstract

Keywords

Natural pigment

Bougainvillea glabra

Floral bracts

Central composite design

Response surface methodology

Fourier Transform Infrared Spectroscopy

Abbreviations

1 Introduction

2 Materials and methods

2.1 Collection of floral bracts

2.2 Pigment extraction

2.3 Analytical method

2.4 Statistical optimization

3 Results and discussion

3.1 Optimization by response surface methodology

3.1.1 Regression analysis and model fitting

3.1.2 Surface plots

3.1.3 Model validation

3.2 FTIR analysis

4 Conclusion

Acknowledgments

References

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