2009 - Extraction and Identification of Anthocyanin From Purple Corn

5/26/2018 2009 - Extraction and Identification of Anthocyanin From Purple Corn - sli...

http:///reader/full/2009-extraction-and-identification-of-anthocyanin-from-

Original article

Extraction and identification of anthocyanin from purple corn

(Zea maysL.)

Zhendong Yang,1 Zhijie Chen,1 Shulin Yuan,1 Weiwei Zhai,1* Xiangshu Piao2 & Xianglan Piao3

1 Food Engineering Department of Jiangsu Food Science College, Huaian, Jiangsu, China, 223003

2 State Key Laboratory of Animal Nutrition, China Agricultural University, Beijing, China, 100094

3 Institute of Chinese Minority Traditional Medicine, Minzu University of China, Beijing, China, 100081

(Received: 13 November 2008; Accepted in revised from 7 July 2009 )

Summary An efficient extraction of anthocyanin from purple corn (Zea mays L.) was investigated in this paper.

Tristimulus colourimetry was used to evaluate the process quantitatively and qualitatively. Purple corn

anthocyanin was extracted with 1 nHCl95% ethanol (15:85, vv) at different extraction temperatures (30

70 C), times (60120 min) and solidliquid ratio (1:201:40). The combined effects of extraction conditions

on anthocyanin yield and colour attributes were studied using a three-level three-factor BoxBehnken design.

The results showed that the highest yield of anthocyanin from purple corn (6.02 mg g)1) were obtained at70 C, extraction time 73 min, and solidliquid ratio 1:25. Three kinds of non-acylated anthocyanins were

detected and characterised as cyanidin-3-glucoside, pelargonidin-3-glucoside and peonidin-3-glucoside by

HPLC-MS.

Keywords Anthocyanin, extraction, HPLC-MS, optimisation, purple corn.

Introduction

There are various breeds of corn in the world showingvarious colours such as white, yellow, red, purple,brown, green and blue. Purple corn is a pigmentedvariety ofZea maysL., originally cultivated in Andes ofSouth America and was introduced to China long timeago. This corn variety is mainly grown in Shanxi andAnhui Province, China.

Purple corn was rich in anthocyanin. Purple cornanthocyanin was characterised as cyanidin-3-glucoside,pelargonidin-3-glucoside, peonidin-3-glucoside and theirrespective malonated counterparts (Aoki et al., 2001;Pascual-Teresa et al., 2002). Currently, it is interestingto note the relevance of some under utilised cereals as apotential source of anthocyanin for food-colourantpurposes. Several patens exist that describe variouspreparations and application processes for their use as

colourants (Mazza & Miniati, 1993). Recently, antho-cyanin has been reported to have various biologicalactivities, such as antioxidant, anti-mutagenic andanticancer activities (Yoshimotoet al., 2001; Ka hko nen& Heinoner, 2003; Katsube et al., 2003). Especially,most of the properties attributed to purple corn extracts

were related to anthocyanin, including colouringattributes (Duhard et al., 1997; Cevallos-Casals &Cisneros-Zevallos, 2004), antioxidant (Cevallos-Casals& Cisneros-Zevallos, 2003a), antimicrobial (Cevallos-Casals & Cisneros-Zevallos, 200b), anti-obesity activityand amelioration of hyperglycaemia (Tsudaet al., 2003)and anticarcinogenic properties (Hagiwara et al., 2001).Thus, there is a need to develop an efficient extractiontechnique of anthoycanins from purple corn.

Anthocyanin extraction is commonly carried out withethanol containing a small amount of hydrochloric acidor formic acid with the purpose of obtaining theflavylium cation, which is red and stable in the acidmedium and recommended to prevent the degradationof the non-acylated compounds (Gonnet & Fenet, 2000;Lapornik et al., 2005; Longo & Vasapollo, 2006).Current studies on anthocyanin from purple corn arefocused on their stability, structure and physiological

functionality (Aoki et al., 2001; Hagiwara et al., 2001;Pascual-Teresaet al., 2002; Tsudaet al., 2003; Cevallos-Casals & Cisneros-Zevallos, 2004). However, littleinformation on the detailed extraction process param-eters of purple corn anthocyanin is available in openliteratures.

Colour is one of the most important attributes ofnatural colourants. The application of colourimetricsystems, based on uniform colour spaces (CIELUV and

*Correspondent: Fax: +86 0517 87088039,

e-mail: [email protected]

International Journal of Food Science and Technology 2009, 44, 24852492

doi:10.1111/j.1365-2621.2009.02045.x

2009 The Authors. Journal compilation 2009 Institute of Food Science and Technology



CIELAB) and non-uniform colour spaces (CIEXYZ), isof great value in the quantification and characterisationof the colour properties of pigments and foods. Thecorrelation between some colour parameters and pig-ments content in food has been evaluated in manystudies (Arias et al., 2000; Lee, 2001; Sinnecher et al.,

2002; Mele ndez-Martnez et al., 2003; Kammerer et al.,2004; Montes et al., 2005), although the relationshipsbetween the total anthocyanin content and colourparameters of purple corn extracts have not beenstudied during extraction process.

In this study, the main processing conditions (extrac-tion temperature, time and solidliquid ratio) on theextraction of purple corn anthocyanin, was investigated.The colour properties of anthocyanin extracts wereestimated by Tritimulus Colourimetry. The aim was todetermine the optimal condition for efficient quantitativeand qualitative (related to colour properties) extraction ofanthocyanin from purple corn in order to be used as foodcolourant. In addition, we identified the anthocyaninconstituents of extracts from purple corn by HPLC-MS.

Materials and methods

Sample preparation

Purple corn (Zea mays L. cv. ZiRuo1) was generouslysupplied from National Sweet Potato Research Insti-tute, Xuzhou, China. These corns were pulverised withthe grinder (FSD-100A, Taizhou city, Zhejiang prov-ince, China) and sifted through a 100 mesh sieve.Samples were kept at 4 C.

Extraction of purple corn anthocyanin

Purple corn anthocyanins were extracted as described byFan et al. (2008a). One gram of sample was used fordetermination. The powder of purple corn was put intoa 50 mL conical tube and then 1.5 nHCl95% ethanol(15:85, vv) with different solidliquid ratio (1:151:40)was added. The mixture was put in thermostatic waterbath at selected temperatures of 2070 C for time of30180 min, and centrifuged at 4000 g for 15 min.The supernatant was collected and transferred into50 mL volumetric flask for the determination of antho-cyanin yield.

Experimental design

Firstly, the single factor experiment for extraction wasperformed with the analysis of the effect of three factors(temperature, solvent-solid ratio and time) on extractionof anthocyanin from purple corn. Secondly, the optimi-sation of anthocyanin extraction parameters throughthree parameters was performed using BoxBehnkendesign (Table 3) and a model was developed. Thirdly,

the model validation and the effect of extraction timeson anthocyanin yield were carried out (Table 6). Finally,the anthocyanin constituents of extracts were identifiedby HPLC-MS.

Response surface methodology (RSM) is an affectivestatistical technique for optimising complex processes. It

is widely used in finding optimal condition of processvariables. The basic theoretical and fundamental aspectsof RSM have been reviewed (Farooq et al., 1997;Chandrika & Fereidoom, 2005). The experimental designand statistical analysis were performed using Stat-Easesoftware (Design-Expert 6.0.10 Trial, Delaware, USAEchip, 1993). A three-level three-factor BoxBehnkendesign was chosen to evaluate the combined effect of threeindependent variables, extraction temperature, time andsolidliquid ratio, coded asA,BandC, respectively. Theminimum and maximum values for extraction tempera-ture were set at 30 and 70 C, extraction time between60 and 120 min and solidliquid ratio 1:20 and 1:40(Table 1). Theresponse values were anthocyanin pigmentyield, L*, C* and h. The complete design consisted ofseventeen combinations including five replicates of thecentre point (Table 2) (Myers & Montgomery, 2002). Theresponses function (Y) was partitioned into linear, qua-dratic and interactive components,

Y b0 Xk

i1

BiXiXk

i1

BiiX2iXk

i>j

BijXiXj 1

where Ystands for total anthocyanin yield. b0 denotesthe model intercept, Bi, Bii and Bij represent the

coefficients of the linear, quadratic and interactive effect,respectively, and Xi, and Xj are the coded independentvariables; k equals to the number of the tested factors(k = 3). The analysis of variance (anova) tables weregenerated and the effect and regression coefficients ofindividual linear, quadratic and interaction terms weredetermined. The significances of all terms in the poly-nomial were judged statistically by computing theF-value at a probability (P) of 0.001, 0.01 or 0.05. Theregression coefficients were then used to make statisticalcalculations to generate contour maps from the regres-sion models.

Table 1 Independent variables and their coded and actual values usedfor optimisation

Independents

variables Units Symbol

Code levels

)1 0 1

Temperature C A 30 50 70

Time min B 60 90 120

Solidliquid ratio 1:X C 20 30 40

Extraction of anthocyanin from purple corn Z. Yanget al.2486

International Journal of Food Science and Technology 2009 2009 The Authors. Journal compilation 2009 Institute of Food Science and Technology



Determination of total anthocyanin content of purple cornextract

Purple corn anthocyanins were quantified following thespectrophotometric method proposed by Francis (1989).The concentration of anthocyanin was determined usingthe LambertBeer law. The factor 98.2 is the molarabsorption value of cyanidin-3-glucoside for the acidethanol solvent and it refers to the absorption of amixture of cranberry anthocyanin in acidethanol,

measured in a 1-cm cell at 535 nm, at a concentrationof 1% (wv).

The spectra recorded in a diode array spectropho-tometer (UV-2802, UNICO, FL, USA) were measuredat 25 C and 530 nm, against the solvent. For thatpurpose 1-cm quartz cells were used. The anthocyaninyield (mg g)1) was calculated using the followingequation:

Total anthocyanin (TA) A530 dilution factor=98:2

2

Colour coordinates

Tristimulus parameters (L*, C* andh) were calculatedusing CR-S4w software (CR400, Konica Minolta,Japan), based on CIELAB colour space, and withreference to standard observation angle of ten visualfield and a standard illuminator D65 at Dkof 5 nm (Fanet al., 2008b).

Purification of anthocyanin from purple corn extracts

Anthocyanin extracts of purple corn were purifiedaccording to the procedure described by Fuleki &Francis (1968). The Amberlite CG-50 resins (50 g eachtime) were hydrated by placing in a beaker with repeateddecantation and removed the fine particles with distilledwater. Water slurry of the hydrated resin was pouredinto a 26 400 mm column, and the excess water wasallowed to drain out without letting the column dry.

Approximately 15 mL of aqueous extract was pouredon the top of the column until the entire resin bedbecame red due to the absorbed anthocyanin. Anthocy-anin were absorbed onto the resin column while sugars,acids and other water-soluble compounds were removedby washing the column with 100 mL of distilled water asjudged by the refractive index of the liquid coming offthe column. The pigments were eluted by adding ethanolcontaining 0.01% HCl (approximately 50 mL) until theresin returned to its original colour. The eluate wasconcentrated with a rotary evaporator at 45 C undervacuum until the ethanol was evaporated, and theresidue was dissolved in 0.5% HCl solvent. The solutionwas stored at )20 C until further analysis.

Identification of anthocyanin from purple corn extractsby HPLC-MS

High-performance liquid chromatography (HPLC) sys-tem consisted of a Waters 2690 pump coupled with aWaters 2996 photodiode array detector. Data analysiswas performed with Waters HPLC chem-station soft-ware. Solvents and samples were filtered through a

Table 2 BoxBehnken design and experiment data for anthocyanin extraction from purple corn

No

Independent variables Dependent variables

Temperature

(C)

Time

(min)

Solidsolvent

ratio

Anthocyanin

yield (mg g)1) L* C* h

1 30()1) 60()1) 30(0) 4.13 0.05 20.55 0.08 4.28 0.05 24.31 0.12

2 70(1) 60()1) 30(0) 5.99 0.05 19.52 0.10 5.46 0.07 23.15 0.07

3 30()1) 120(1) 30(0) 3.82 0.04 20.67 0.09 4.11 0.07 24.22 0.13

4 70(1) 120(1) 30(0) 5.27 0.07 19.94 0.07 4.62 0.03 23.52 0.03

5 30()1) 90(0) 20()1) 3.43 0.10 20.78 0.14 4.28 0.11 24.34 0.09

6 70(1) 90(0) 20()1) 5.60 0.04 19.72 0.04 5.04 0.09 24.16 0.01

7 30()1) 90(0) 40(1) 4.64 0.08 20.29 0.09 4.49 0.07 25.20 0.18

8 70(1) 90(0) 40(1) 5.60 0.07 19.74 0.11 4.88 0.05 24.22 0.07

9 50(0) 60()1) 20()1) 4.47 0.07 20.47 0.06 4.54 0.06 24.90 0.06

10 50(0) 120(1) 20()1) 4.15 0.09 20.54 0.04 4.47 0.18 24.46 0.05

11 50(0) 60()1) 40(1) 4.73 0.04 20.15 0.07 4.65 0.07 24.99 0.09

12 50(0) 120(1) 40(1) 4.46 0.01 20.49 0.09 4.66 0.01 24.50 0.14

13 50(0) 90(0) 30(0) 5.10 0.06 20.34 0.07 4.71 0.09 24.80 0.07

14 50(0) 90(0) 30(0) 5.30 0.08 19.80 0.06 4.87 0.15 24.81 0.08

15 50(0) 90(0) 30(0) 5.26 0.07 19.91 0.15 4.56 0.03 24.49 0.11

16 50(0) 90(0) 30(0) 5.21 0.14 20.00 0.07 4.73 0.04 24.38 0.0817 50(0) 90(0) 30(0) 5.47 0.07 19.74 0.01 4.92 0.02 24.20 0.02

Extraction of anthocyanin from purple corn Z. Yanget al.

2009 The Authors. Journal compilation 2009 Institute of Food Science and Technology International Journal of Food Science and Technology 2009



0.45lm filter. Separations were carried out on aLichrospher C18 column (5lm, 2.1 250 mm i.d.).Simultaneous monitoring was performed at 520 nm at aflow rate 0.3 mL min)1. The running temperature was at35 C and the injection volume was 10 lL. A gradientelution system of solvent A [0.05% (vv) trifluoroacetic

acid (TFA)] and B (acetonitrile) was used [5% solvent B(0 min); 20% solvent B (20 min); 4% solvent B(50 min)]. The flow rate was 0.8 mL min)1. The antho-cyanin were checked using electrospray MS with aWaters Platform ZMD 4000 mass spectrometerequipped with an ion spray interface (ISV = 4400).Spectra were recorded in positive ion mode between mz200 and 1300.

Statistics

All trials were carried out in triplicate and all the datawere reported as means standard deviation (SD).The statistics significance was evaluated using Studentst-test and P < 0.05 was taken as significant.

Results and discussion

Preliminary experiments for setting up BoxBehnkendesign

The effect of temperature on anthocyain yield wasshown in Table 3. The anthocyanin yield increasedsignificantly (P < 0.05) with the temperature from 10 to50 C, but it did not increase any further above 50 C.This suggested that the optimal temperature for antho-cyanin extraction was 50 C. Tu rker & Erdog du (2006)

also suggested that as the temperature raised (2550 C),the anthocyanin yield increased. However, higher tem-perature may also result in degradation of anthocyaninas reported by Cacace & Mazza (2003).

The results showed in Table 3 indicated that theanthocyanin yield increased significantly (P < 0.05)when the extraction time was extended from 30 to90 min. The yield of anthocyanin slight decreased butnot significantly in statistical analysis (P > 0.05) when

the time was extended from 90 to 120 min. It decreasedsignificantly (P < 0.05) when the extraction time werebetween 120 and 180 min. This indicated that theoptimal time for anthocyanin extraction was 60120 min.

Table 3 showed the effect of different solidliquid

ratios on anthocyanin yield. The anthocyanin yieldincreased (P < 0.05) when the solidliquid ratio wasfrom fifteen to thirty, but it did not increased when theratio was higher than 30. This suggested that thesolventsolid ratio of thirty was the optimal ratio foranthocyanin extraction.

Analysis of BoxBehnken experiment

The results of each dependent variable with theircoefficients of determination (R2) were summarised inTable 4. The statistical analysis indicates that theproposed model was adequate, possessing no significantlack of fit and with very satisfactory values of the R2 forall the responses. The R2 values for anthocyanin yield,L*, C* and h were 0.981, 0.905, 0.854 and 0.852,respectively. Coefficient of variances (Table 4) foranthocyanin yield, L*, C* and h were within theacceptable range. In general, a high coefficient ofvariances indicates that variation in the mean value ishigh and does not satisfactorily develop an adequateresponse model (Chandrika & Shahidi, 2005). Theprobability (P) values of all regression models were lessthan 0.05.

The effects of extraction temperature, time and solidliquid ratio on anthocyanin yields, L*, C* and h arereported (Table 4) by the coefficient of the second order

polynomials. Response surface and contour plots wereused to illustrate the effect of extraction temperature,extraction time and solidliquid ratio on the responses.Response surfaces and contour plots for anthocyaninyield were shown in Figs S1S3.

Figure S1 showed the contour map for the effect ofextraction temperature and time on the yield of antho-cyanin from purple corn. As shown in Table 4, antho-cyanin yield depends on the extraction temperature as

Table 3 Effect of different extraction conditions on anthocyanin yield

Index

Temperature (C) (60 min, 1:30)

20 30 40 50 60 70

Anthocyanin

yield (mg g)1)

2.22 0.09d 2.87 0.12c 3.28 0.04b 3.95 0.02a 3.99 0.04a 4.05 0.11a

Time (min) (50 C, 1:30)

30 60 90 120 150 180

3.95 0.04d 4.37 0.08c 4.88 0.10a 4.72 0.12ab 4.60 0.07bc 4.48 0.11cd

Solidliquid ratio (50 C, 90 min)

1:15 1:20 1:25 1:30 1:35 1:40

2.81 0.05c 2.98 0.14c 3.57 0.10b 3.88 0.05a 3.95 0.08a 4.01 0.05a

Values with different superscripts (a, b, c, etc.) differ significantly ( P< 0.05).





its negative linear effect (P < 0.01) was significant,whereas its quadratic effect were not significant(P > 0.05), which resulted in a curvilinear increase inanthocyanin yield for all the extraction times. It can beseen that the extraction temperature was the main effecton the anthocyanin yield. In this case, the extractiontime had only a slight influence, especially when the

extraction temperature is low. When the extraction timewas longer than 90 min, the anthocyanin yield decreasedsignificantly (P < 0.01).

The contour map for effect of temperature and solidliquid ratio on anthocyanin yield was shown in Fig. S2.Anthocyanin yield depends on the solidliquid ratio asits linear (P < 0.01) and quadratic effects (P < 0.001)were significant (Table 4). The linear effect (P < 0.01)was positive, whereas the quadratic effect (P < 0.001)was negative, which resulted in an overall curvilinearincrease in anthocyanin yield for all extraction temper-ature. When the solidliquid ratio increased up to aboutthirty, temperature became the critical factor forimproving anthocyanin yield.

Figure S3 showed the contour map for the effect ofthe time and solidliquid ratio on anthocyanin yield.The solidliquid ratio where its linear (P < 0.01) andquadratic effects (P < 0.001) were significantly influ-enced the anthocyanin yield (Table 4). The anthocyaninyield increased when the solventsolid ratio increasedfrom twenty to thirty but it did not continue to increasesignificantly when the ratio was higher than thirty. Atthe lowest level of time, anthocyanin yield of purple corn

increased rapidly at the beginning but with a decreasingtowards the end. It can be seen that the positive linearand negative quadratic effects of solidliquid ratio andtemperature explained the observed nature of the curveshown in Fig. S3.

The contour plots showed the optimum conditions of

the extraction process to anthocyanin yield. There are anumber of combinations of variables that could givemaximum levels of anthocyanin yield. Since the opti-mum response for each dependent variable did not fallexactly in the same region, the superimposition of all thecontour plots obtained was done. During the anthocy-anin extraction, the extraction temperature, time andsolidliquid ratio are important. Therefore, the bestcombination of process variables for response functionswas found. The process variables for the best combina-tion of response function are extraction temperature70 C, time 73 min and solidliquid ratio 1:25. Theresponse functions were calculated from the final poly-nomial, and the response were 6.02 mg g)1 for antho-cyanin yield, 19.52 for L*, 5.23 for C*and h for 23.69,respectively. Cevallos-Casals & Cisneros-Zevallos(2003a) reported that the anthocyanin content is16.42 mg g)1 (fresh weight) in whole purle corn. Forpurple corn cob, the anthocyanin content is 5.90 mg g)1

(dry weight) (Yang et al., 2008). Compared with otherfruits, such as grape (0.252.60 mg g)1, fresh weight)(Arozarena et al., 2002), blackberry (0.672.30 mg g)1,fresh weight) (Wang & Xu, 2007) and Jaboticaba(0.0440.163 mg g)1, fresh weight) (Montes et al.,2005), the yield of anthocyanin was relatively high inpurple corn, which made this cereal a good source foranthocyanin.

The effects of temperature, time and solidliquid onthe yield of anthocyanins from purple corn wereinvestigated in this paper. However, the other importantfactor, such as diffusion coefficients, particle size,characteristics of biological material, co-pigmentationreactions and complexation etc., were not taken intoaccount and could play a crucial role in the extractionyield. So, these factors need thus further research.

Correlations between anthocyanin yield and the colourparameters

Correlations between the yield of anthocyanin and thecolour parameters were explored in this study (Fig. S4).A negative correlation (r =

)0.9263) was found with

L*, indicating that higher L* values were related tolower yield of anthocyanin. The positive correlationwere found between the yield of anthocyanins and C*(r = 0.7808). This positive correlation indicated thathigh C* values were related to high yield of anthocy-anins. These results were in agreement with Monteset al. (2005) who evaluated the correlations between theanthocyanin yield and C* and L* in Juboticaba fruit.

Table 4 Regression coefficients,R2, and CV values for four dependents

variables for the extraction of purple corn

Coefficient

Anthocyanin

yield L* C* h

b0 (intercept) 5.270 19.960 4.760 24.540

LinerB1 0.810*** )0 .420*** 0.360 )0.380**

B2 )0.200** 0.120 )0.130 )0.081

B3 0.220** )0.110 0.044 0.130

Quadratic

B11 )0.050 )0.034 )0.024 )0.480**

B22 )0.420*** 0.250* )0.120 )0.250

B33 )0.400*** 0.210* )0.061 0.430**

Cross product

B12 )0.100 0.075 )0.170 0.110

B13 )0.300** 0.130 )0.093 )0.200

B23 0.012 0.067 0.020 )0.013

R2 0.981 0.905 0.854 0.852

CV 3.040 0.900 3.960 1.210

Probability (P)



However, the correlations between yield of anthocya-nins and h was too low (r =)0.367).

Verification of model

Within the scopes of the variables investigated inBoxBehnken design, additional experiments withdifferent conditions for anthocyanin extraction werecarried out in order to assess the validity of the model(eqn 1). The arrangement and result of the confirma-tory trials were shown in Table 5. It was demon-strated that there was a high fit degree between thevalues observed in experiment and the values pre-dicted by eqn 1.

Effect of repeated extraction on the anthocyanin

yield

Four times of repeated extraction of anthocyanin frompurple corn under the optimal conditions (70 C,73 min, 1:25) were performed in order to obtain themaximum anthocyanin yield (Table 6). In fact, the firsttwo extractions (6.63 mg g)1) produced as much as

94.31% of the entire anthocyanin content (7.03 mg g)1

)in purple corn, implying that two times of extractionwould be enough to get a desired anthocyanin yieldfrom purple corn.

Identifications of anthocyanin from purple corn extracts byHPLC-MS analysis

Reverse phase HPLC and MS analysis were used torapidly identify the anthocyanin from purple cornextracts. The identification was carried out by compar-

ison of their retention time and by confirming themolecular weight with ESI-MS (Aoki et al., 2001;Pascual-Teresaet al., 2002).

Figure S4 shows the chromatograms of anthocya-nins from purple corn, which were detected at 520 nm.Three peaks were identified in the chromatograms,indicating the existence of three types of anthocya-nin. Their contents were 73.3%, 9.3% and 17.4%,respectively.

Three types of anthocyanin were identified shown inFigs S5 and S6. They were identified as cyanidin-3-glucoside, pelargonidin-3-glucoside and peonidin-3-glu-coside, respectively (Fig. S5). Peak 1 showed [M]+ atmz449 and fragment ion of loss of a glucose [M-162]+

at mz 287. It was identified as cyanidin-3-glucoside.Peak 2, with [M]+ atmz433, fragment ion [M-162]+ atmz 271, was identified as pelargonidin-3-glucoside.Peak 3 appeared a [M]+ at mz 463 and the fragmention of less of glucose [M-162]+ at mz 301. It wasidentified as peonidin-3-glucoside (Fig. S5).

In this study, some anthocyanin components ofpurple corn extracts were identified similar with theprevious reports (Aoki et al., 2001; Pascual-Teresa

et al., 2002). However, cyanidin-3-(6-malon-glucoside),pelargonidin-3-(6-malon-glucoside) and peonidin-3-(6-malon-glucoside) were not detected, which have beenidentified by Aoki et al. (2001).

Conclusions

The different conditions for anthocyanin extractionrecealed that extraction temperature, time and solidliquid ratio markedly affect the anthocyanin yield.These can be related to the anthocyanin extractionconditions by second-order polynomials. Using thecontour plots, the optimum set of the operatingvariables are obtained graphically in order to obtain

the desired levels of these properties of the purple cornanthocyanin, which is suitable for the subsequentanalysis based clarification processes. The best combi-nation of response function are extraction temperature70 C, time 73 min, and solidliquid ratio 1:25. Threetypes of anthocyanin from purple corn extracts wereseparated and identified them as cyanidin-3-glucoside,pelargonidin-3-glucoside and peonidin-3-glucosideusing HPLC-MS analysis.

Table 5 Arrangement and result of confirmatory trials

Trials Temperature (C)

Time

(min)

Solventsolid

ratio

Anthocyanin yield (mg g )

Observed v alue Predicte d value

Optimum condition 70 73 25 5.98 0.15 6.02

Random condition 1 50 100 40 5.05 0.11 4.98

Random condition 2 70 60 30 5.90 0.18 5.91

Table 6 Effect of extraction times on anthocyanin yield and extraction

rate of purple corn anthocyanins (70 C, 90 min, 1:30)

Index

Extraction stage

First Second Third Fourth

Anthocyanin

yield (mg g)1)

4.79 0.24 1.84 0.13 0.29 0.09 0.11 0.02

Extraction

ratio (%)

68.14 26.17 4.12 1.57





References

Aoki, H., Kuze, N. & Kato, Y. (2001). Anthocyanin isolated frompurple corn (Zea mays L). Available-from-http://www.ffcer.or.jp/zaudan/FFCRHOME.nsf/7bd44c20b0dc562649256502001b65e9/c6698773361b42b249256ba60018e581/$FILE/anthocyanin-FFIJ199.pdf.

Arias, R., Lee, T-C., Logendra, L. & Janes, H. (2000). Correlation oflycopene measured by HPLC with the L*,a*,b* colour readings ofa hydroponics tomato and the relationship of maturity with andlycopene content. Journal of Agricultural and Food Chemistry, 48,16971702.

Arozarena, I., Ayestara n, B., Cantalejo, M.J. et al. (2002).Anthocyanin composition of Tempranillo, Garnacha and Caber-net Sauvignon grapes from high- and low quality vineyards over twoyears. European Food Research and Technology, 214, 303309.

Cacace, J.E. & Mazza, G. (2003). Mass transfer process duringextraction of phenolic compounds from milled berries. Journal ofFood Engineering, 59, 379389.

Cevallos-Casals, B.A. & Cisneros-Zevallos, L. (2003a). Stoichiometricand kinetic studies of phenolic antioxidants from andean purplecorn and red-fleshed sweet potato. Journal of Agricultural and FoodChemistry, 51, 33133319.

Cevallos-Casals, B.A. & Cisneros-Zevallos, L.A. (2003b).A compar-ative study of antimicrobial, antimutagenic and antioxidant

activity of phenolic compounds from purple corn and bilberrycolourant extracts. In: Book of Abstracts of the Institute of FoodTechnologists Technical Program Abstracts, Poster 14E-1. Pp. 29.Chicago, IL.

Cevallos-Casals, B.A. & Cisneros-Zevallos, L. (2004). Stability ofanthocyanin-based aqueous extracts of andean purple corn andredfleshed sweet potato compared to synthetic and natural colou-rants. Food Chemistry, 86, 6977.

Chandrika, L.P. & Fereidoom, S. (2005). Optimization of extraction ofphenolic compounds from wheat using response surface methodol-ogy. Food Chemistry, 93, 4756.

Duhard, V., Garner, J. & Megard, D. (1997). Comparison of thestability of selected anthocyanin colourants in drink model systems.Agro Food Industry High Technology, 8, 2834.

Fan, G.J., Han, Y.B., Gu, Z.X. & Chen, D.M. (2008a). Optimizingconditions for anthocyanin extraction from purple sweet potatousing response surface methodology (RSM).LWT-Food Science andTechnology, 41, 155160.

Fan, G.J., Han, Y.B., Gu, Z.X. & Gu, F.R. (2008b). Composition andcolour stabilityof anthocyanin extracted fromfermented purple sweetpotato culture.LWT-Food Science and Technology,41, 14121416.

Farooq, A.M., Imran, T. & Khaled, A.S. (1997). Response surfacemethodology: a neural network approach. European Journal ofOperational Research, 101, 6573.

Francis, F. (1989). Food colourants: anthocyanin. Critical Reviews inFood Science and Nutrition, 28, 273314.

Fuleki, T. & Francis, F.J. (1968). Quantitative methods for anthocya-nins 1. Extraction and determination of total anthocyanin incranberries. Journal of Food Science, 33, 7277.

Gonnet, J.F. & Fenet, B. (2000). Cyclamen red colours based on amacrocyclic anthocyanin in carnation flowers. Journal of Agricul-tural and Food Chemistry, 48, 2226.

Hagiwara, A., Miyashita, K., Nakanishi, T. et al. (2001). Pronounced

inhibition by a natural anthocyanin, purple corn colour, of 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP)-associated colorec-tal carcinogenesis in male F344 rats pretreated with 1,2-dimethyl-hydrazine. Cancer Letters, 171, 1725.

Ka hko nen, M.P. & Heinoner, M. (2003). Antioxidant activity ofanthocyanin and their aglycons. Journal of Agricultural and FoodChemistry, 51, 628633.

Kammerer, D., Carle, R. & Schieber, A. (2004). Quantification ofanthocyanin in black carrot extracts (Daucus carotassp.sativusvar.atrorubens Alef.) and evaluation of their properties. European FoodResearch and Technology, 219, 479486.

Katsube, N., Iwashita, K., Tsushida, T., Yamaki, K. & Kobori, M.(2003). Induction of apoptosis in cancer cells by bilberry (Vacciniummyrtillus) and the anthocyanin. Journal of Agricultural and FoodChemistry, 51, 6875.

Lapornik, B., Prosek, M. & Wondra, A.G. (2005). Comparison ofextracts prepared from plant by-products using different solventsand extraction time. Journal of Food Engineering, 71, 214222.

Lee, H.S. (2001). Characterization of carotenoids in juice or red navelorange (Cara Cara).Journal of Agricultural and Food Chemistry, 49,25632568.

Longo, L. & Vasapollo, G. (2006). Extraction and identification ofanthocyanin from Smilax aspera L. berries. Food Chemistry, 94,226231.

Mazza, G. & Miniati, E. (1993). Anthocyanin in Fruits, Vegetables andGrains. 362 p. Boca Raton, Florida (USA): CRC Press.

Mele ndez-Martnez, A.J., Vicario, I.M. & Heredia, F.J. (2003).Application of tristimulus colourimetry to estimate the carotenoidscontent in ultrafrozen orange juices. Journal of Agricultural andFood Chemistry, 51, 72667270.

Montes, C., Vicario, I.M., Raymundo, M., Fett, R. & Heredia, F.J.(2005). Application of tristimulus colourimetry to optimize theextraction of anthocyanin from Jaboticaba (Myricia JaboticabaBerg.).Food Research International, 38, 983988.

Myers, R.H. & Montgomery, D.C. (2002). Response surface methodo-

logy: process and product optimization using designed experiments(2nd edn). New York: Wiley.

Pascual-Teresa, S., Santos-Buelga, C. & Rivas-Gonzalo, J.C. (2002).LC-MS analysis of anthocyanin from purple corn cob.Journal of theScience of Food and Agriculture, 82, 10031006.

Sinnecher, P., Gomes, M.S., Areas, J.A.G. & Lanfer-Marquez, U.M.(2002). Relationship between colour (instrumental and visual) andchlorophyll contents in soybean seeds during ripening. Journal ofAgricultural and Food Chemistry, 50, 39613966.

Tsuda, T., Horio, F., Uchida, K., Aoki, H. & Osawa, T. (2003).Dietary cyanidin 3-O-b-D-glucoside-rich purple corn colour pre-vents obesity and ameliorates hyperglycemia in mice. Journal ofNutrition, 133, 21252130.

Tu rker, N. & Erdog du, F. (2006). Effect of pH and temperature ofextraction medium on effective diffusion coefficient of anthocyaninpigments of black carrot (Daucus carota Var. L.). Journal of FoodEngineering, 76, 579583.

Wang, W.D. & Xu, S.Y. (2007). Degradation kinetics of anthocyaninsin blackberry juice and concentration. Journal of Food Engineering,82, 271275.

Yang, Z.D., Fan, G.J., Gu, Z.X., Han, Y.B. & Chen, Z.G. (2008).Optimization extraction of anthocyanin from purple corn (Zea maysL.) cob using tristimulus colorimetry. European Food ResearchTechnology, 227, 409415.

Yoshimoto, M., Okuno, S., Yamaguchi, M. & Yamakawa, O. (2001).Antimutagenicity of deacylated anthocyanin in purple-fleshed sweetpotato.Bioscience Biotechnology and Biochemistry, 65, 16521655.

Supporting Information

Additional Supporting Information may be found in theonline version of this article:

Figure S1. Contour plots for the effects of temperatureand time at a constants solid-liquid ratio of 1:30 on theyield of anthocyanin from purple corn.Figure S2. Contour plots for the effects of temperatureand solid liquid ratio at a constants time of 90 min onthe yield of anthocyanin from purple corn.Figure S3. Contour plots for the effects of time andsolid-liquid ratio at a constants of 50 C on the yield ofanthocyanin from purple corn.

Extraction of anthocyanin from purple corn Z. Yanget al.

2009 The Authors. Journal compilation 2009 Institute of Food Science and Technology International Journal of Food Science and Technology 2009



Figure S4. The calibration curve of corrections betweenanthocyanin yeild and the colour parameters (L* andC*).Figure S5.HPLC chromatogram at 520 nm correspond-ing to purple corn extract.Figure S6. Positive ion mass spectra of anthocyanin

constituents in purple corn extract: (1) cyanin-3-gluco-

side; (2) pelargonidin-3-glucoside; (3) peonidin-3-gluco-side; Glu = glucoside.Please note: Wiley-Blackwell are not responsible for thecontent or functionality of any supporting materialssupplied by the authors. Any queries (other than missingmaterial) should be directed to the corresponding author

for the article.



Documents

2009 - Extraction and Identification of Anthocyanin From Purple Corn