Preparation and Evaluation of Antioxidant Loaded Candy using Microwave Prepared Capsicum powder with Optimization of Time and Temperature

 

Madhumita Saha1, Dibya Das2, Sushmita Saha1, Pinaki Saha1, Sudipta Saha3,

Runu Chakraborty1*

1Department of Food Technology and Biochemical Engineering, Jadavpur University, Kolkata, India.

2Department of Pharmaceutical Technology, JIS University, Kolkata, India.

3UCD School of Public Health, Physiotherapy and Sports Sciences, Ireland.

*Corresponding Author E-mail: crunu@hotmail.com

 

ABSTRACT:

Capsicum belongs to the Solanaceae family. These are used as vegetables, spices, or drugs. Capsicum contains capsaicin, Vitamins A, C and phenolic compounds, which are essential antioxidant components that may reduce the risk of diseases. This study aimed to prepare candy using Capsicum powder and evaluate their moisture content, colour measurement, and antioxidant activity under various cooking times and temperatures using the microwave. Response Surface Methodology (RMS) was used for the optimization of cooking time and tempareture of this process. Here a small piece of healthy sweet candy made from sugar with Capsicum powder with other ingredients. This antioxidant-loaded candy's study showed that the varying microwave power and time combination during cooking leads to a significant change in Capsicum fortified candy's physicochemical properties. Increase the combination of time-microwave power burn the batter and due to liquid condition of solution is found a combination of low power and low time. 300 W - 10 min is a good combination for made candy. It gives the best colour (L* =13.1±0.019, a* =4.4±0.0128, b*=4.4±0.0312), antioxidant (2.4±0.012) mg/ml and texture (hardness 4±0.5) properties.

 

KEYWORDS: Capsicum, antioxidant, candy, Response Surface Methodology.

 

 


INTRODUCTION:

Candy is a sweet confectionery product prepared with sugar (sucrose), corn syrup, water, maltodextrin, liquid glucose, and spices. Candy should not be a significant nutrient source, but different fruits and vegetable incorporation improved antioxidant characteristics. Dihydrocapsaicin causes the pungent flavour in caspicum1. Candies are usually divided into two basic classes that are crystalline and non-crystalline hard candies2,3. During cooking, inversion of sucrose occurs. Corn syrup prevents large sugar crystals formation4.

 

The cooking step is to reduce candy moisture and directly influence the degree of inversion of sucrose. Citric acid is commonly added to the final product to decry the inversion5. The crystallization in hard candies minimized by adjusting formulation and cooking time and cooking power6,7. Capsicum is a perishable vegetable, but it contains many antioxidant components such as capsaicin, dihydrocapsaicin, carotenoids, etc8. Fortification of capsicum powder into candy improves their physicochemical characteristics, mainly antioxidant properties. RSM (response surface methodology) is a proper statistical technique for analyzing complex processes9. It is a less time-consuming and less expensive method for research. RSM has successfully been applied for the development and optimization of confectionary products10.

 

MATERIALS AND METHODS:

Raw materials:

Capsicum powder, Sugar (Sakthi Sugar, India), lemon, salt (Tata Salt, India), spices (cinnamon, green cardamom, cloves, and fennel seed) were purchased from the local grocery.

 

Reagents:

Ethanol, Sodium Hydroxide (NaOH), Aluminum chloride (AlCl3), sodium nitrite (NaNo2), Folin reagent, Sodium carbonate (Na2CO3), Acetonitrile, NaK Tartarate, catechin, Gallic acid, Capsaicin, baking powder, Maltodextrin.

 

Preparation of capsicum powder:

Capsicums were washed with water. The whole Capsicum was blanched using hot water at 90oC for 3 min and then cooled and drained on a perforated tray before drying. The Capsicum was cut into approximately 2cm × 2cm in size. It was then dried using a different microwave power. All the dried capsicum samples were taken when the moisture content obtained was approximately 3-5%, and constant weight was obtained. Dried samples were made into the fine powder by kitchen mixture and store in the freezer for further analysis.

 

Preparation of candy:

In the preparation of Capsicum, incorporated candy, sugar 55g, maltodextrin 1g, salt 2g, baking powder 2g, water 20ml, spices 2g, capsicum powder 3g, lemon juice, and glucose syrup 15g were constant while cooking power and cooking time were changed according to response surface methodology. The candy syrup was prepared with 55g of sucrose/100g and 15g of glucose syrup/100g. Sugar 14g, water, lemon juice, salt 1g, and baking soda 2g are mixed thoroughly to make glucose syrup. This solution was kept in a micro oven drier for different cooking power and different cooking time. When the solution was boiled, and the colour of the solution was changed (transparent white to light reddish), it is kept out from the microwave oven, and spices and capsicum powder were mixed. After mixing the solution, a small mold was placed to forget a proper shape and size at room temperature 25ºC.

 

Evaluation for candy:

Moisture content:

5g of the sample was weighted in a metal dish using a digital weighing balance. The metal dish sample was then kept for 3 hours in the hot air oven at 105°C until the constant weight of the sample was achieved. Then, the sample was placed inside desiccators for 10 minutes to cool down the sample temperature. The final sample weight was measured.

 

Moisture content = [(initial weight - final weight)/ initial weight)] * 100.

 

Colour measurement:

The Hunter Lab colour measurement system determined the colour profile analysis. A 3.5cm white standard plate (L*=93.49; a* =-1.07; b*=10.6) was used for instrument calibration. In optical glass cells, samples were taken, which have 3.5cm in length and 6cm in diameter. In L* lightness (0; black to 100; white), a* redness (−; green to +; red), and b* yellowness (−; blue to +; yellow) values, the results were expressed.11

 

Texture analysis:

Instron analyzed the texture of the food samples, and a texture profile analysis curve is obtained. An aluminum cylindrical probe was poured into the food samples' center, which has an average thickness of 10mm/s speed. From the TPA graphic, Hardness, gumminess, cohesiveness, chewiness was calculated.12

 

Extraction of samples:

Extraction of the sample was prepared by weighing 1g sample taken in 100mL beaker which contains 20mL of 80% ethanol and then sonicated for reducing the particle size for 10minutes to determine antioxidant activity and antioxidant content. Then it was centrifuged at 8944×g for 10min at 4ºC. The extracts were ready for use after transferred into glass tubes.

 

Antioxidant content and antioxidant activity:

Total phenolic content13:

To the 0.2mL extracted sample, 1.8ml distilled water was added. Then, 0.2mL Folin Ciocalteu Reagent was applied, and the mixture was manually mixed for 5 minutes. After that, 2mL of Folin ciocalteu reagent solution (7%) was applied. After that, 0.8milliliters of distilled water were added. The absorbance of the mixture was measured in a spectrophotometer at 750nm after 90minutes of incubation in the dark. Gallic acid was used to create a standard curve for total phenolic content, expressed as mg of gallic acid per g equivalents of the sample's dry weight.

 

Total flavonoid content14:

One milliliter of the extracted sample, 4 milliliters of distilled water, and 0.3 milliliters of NaNO2 were mixed. Then 2mL 1(M) NaOH and 0.3ml AlCl3 were added. In the spectrophotometer, the mixture's absorbance was measured at 510nm after 25 minutes of light incubation. Catechins were used to create a typical standard curve for total flavonoid material. The result was calculated as mg of catechin equivalents per g of the dry sample weight.

 

 

Capsaicin:

1g powder was sonicated with a 35 kHz frequency for 20 minutes at 65oC with 10ml of acetonitrile. The extract was dried at 60OC, resuspended in 0.5ml ACN, filtered through a 0.45m membrane filter, and deposited at -20OC. The concentration was expressed as mg of capsaicin equivalent per g of the sample's dry weight. Absorbance was measured at a wavelength of 280nm. Fisher's least significant difference test was used to compare and group the mean values.

 

Experimental Design:

Response surface model:

A face-centered central composite design was employed to study and optimize the effect of process parameters15 such as cooking time (X1), cooking power (X2) on the dependent variables (responses) such as the effect on the colour parameter L* (Y1), a* (Y2),b* value (Y3), moisture content (Y4), Capsaicin (Y5), Phenol (Y6) and Flavonoid (Y7). A different range of process variables was selected, and independent variables were taken at three levels (between 1 and +1. ) based on single-factor analysis. By the following equation the coding of the variables was done16:

 

xi = (Xi Xz)/Yi i=1, 2, 3, k

 

xi, Xi, and Xz detonated as an independent variable; Yi, step change of the variable's actual value; i. it is six centre points have taken in a central composite rotatable design with three factors. Calculated by the following equation:

 

N=2K +2K+Cp

 

K is the number of the process variable; the axial points were 2K on each designed factor's axis distance, from the central point, the replicate number is Cp and N is the total number of experiments.

 

The central composite rotatable design consists of 4 factorial points, 4 axial points, and 5 center points. The most accurate model was chosen from this quadratic model.

 

The second-order response functions for the experiments were fitted in this quadratic regression equation:

 

Y = b0 + b1X1 + b2X2 + b11X12 + b12X1X2+b22X22

 

X1 is the cooking time; X2 is the cooking power; b0 is the fitted response at the center point (0, 0) of the given design; b1 and b2 are the linear regression expressions; b11 and b22 are the quadratic expressions, and b12 is the interaction expressions.

 

RESULTS AND DISCUSSION:

Response surface models:

Total observations are taken for Face cantered central composite design, which performed for optimization of the process parameter, i.e., cooking time (X1) and cooking power (X2), and studies the effect on the colour parameter L* (Y1), a* (Y2),b* value (Y3), moisture content(Y4), Capsaicin (Y5), Phenol(Y6), Flavonoid (Y7) and texture (Y8) of the product. The experimental data were fitted to the model to get regression equations and sums of squares. A lack of fit test was done to check the models are significant or not.

 

The following response surface models equations were given below:

L* value of the product (Y1) =13.5369-6.87832X1+2.040862X12+1.665X2+7.150862X22-6.325X1X2,

 a* value of the product (Y2) =4.71-1.64X1-0.032X2+2.74X12+2.81X22+2.33X1X2,

b* value of the product (Y3) = 4.59-4.52X1+4.44 X12-2.75 X2 +13.29 X22-0.33 X1X2,

Moisture of the product (Y4) = 2.15-0.42X1-0.037X12 -1.16X2-0.29X22+0.0075X1X2

Capsaicin of the product (Y5) = 2.169+0.643X1+0.246X12+0.508X2-0.088X22+0.455X1X2,

Phenol of the product (Y6) = 11.065 +4.1X1+0.3744X12+13.54X2+11.5X22-0.6X1X2, Flavonoid of the product (Y7) =0.293-0.196X1-0.04X12-0.123X2+0.041X22+0.073X1X2.

 

Table 1. Independent variables and their levels in the central composite design

Independent variables

Unit

Symbol

Coded levels

 

 

-1

0

+1

Cooking power

W

X2

180

300

420

Cooking time

Minutes

X1

6

10

14


 

Table 2. The central composite design with actual values of independent variables and responses.

Independent variables

Responses

Run

Cooking Time

Cooking Power

Moisture (%)

Colour

Capsaicin

Phenols

Flavonoids

L*

a*

b*

1

10

300

2.25

13.57

4.7

4.7

2.13

11.50

0.27

2

10

300

2.20

13.30

5

4.1

2.20

10.60

0.28

3

6

300

2.70

21.67

8.73

13

2.06

8.56

0.44

4

10

420

0.70

22.34

6.73

14.55

2.39

37.20

0.26

5

10

300

2.10

13.1

4.40

4.40

2.40

11.80

0.31

6

6

180

3.36

22

14.08

29.25

1.55

4.62

0.70

7

10

180

2.9

19.05

8.25

21.25

1.84

8.02

0.47

8

14

300

1.4

9.50

6.12

5.10

3.20

14.4

0.12

9

10

300

2

13.65

4.40

4.90

1.70

10.30

0.31

10

6

420

0.96

38

10.09

25

1.89

31.85

0.29

11

14

180

2.73

20.10

5.80

20.30

1.82

15.20

0.13

12

10

300

2.30

14.05

5.10

4.85

2.0

11.05

0.25

13

14

420

0.36

10.80

11.12

14.75

3.98

40.03

0.009

 

Table 3. Analysis of variance table showing the effect of treatment variables on colour parameter L* value (Y1), a* value (Y2), b* value (Y3), moisture content (Y4), capsaicin content (Y5), phenolic content (Y6), flavonoid content (Y7) and Hardness (Y8).

Model Y1

 

X1

X2

X12

X22

X1X2

Lack of fit

Some of square

283.87

18.63

11.50

141.23

160.02

1.89

Degree of Freedom

1

1

1

1

1

3

Mean square

283.86

16.63

11.50

141.22

160.02

0.63

F value

823.23

48.24

33.36

409.57

464.07

4.81

P value prob>F

<0.0001

0.0002

0.0007

<0.0001

<0.0001

0.0817

 

Model Y2

Some of square

16.20

6.017E-003

20.77

21.77

21.67

1.94

Degree of Freedom

1

1

1

1

1

3

Mean square

16.21

0.017E-003

20.77

21.77

21.67

0.65

F value

47.92

0.012

61.43

64.38

64.08

6.04

P value prob>F

0.8976

0.0002

0.0001

<0.0001

<0.0001

0.0575

Model Y3

 

Some of square

122.40

45.38

54.52

488.05

0.42

2.04

Degree of Freedom

1

1

1

1

1

3

Mean square

122.40

45.38

54.52

488.05

0.42

0.68

F value

343.25

127.24

152.90

1368.62

1.18

6.03

P value prob>F

<0.0001

<0.0001

<0.0001

<0.0001

03124

0.0575

Model Y4

 

Some of square

1.07

8.10

3.725E-003

0.23

2.250E-004

0.19

Degree of Freedom

1

1

1

1

1

3

Mean square

1.07

8.10

3.725E-003

0.23

2.250E-004

0.063

F value

30.31

230.08

0.11

6.45

6.394E-003

4.33

P value prob>F

0.0009

<0.0001

0.7544

0.0387

0.9385

0.0954

Model Y5

 

Some of square

2.48

1.55

0.17

0.02

0.82

0.20

Degree of Freedom

1

1

1

1

1

3

Mean square

2.48

1.55

0.17

0.02

0.82

0.06

F value

57.57

35.94

3.88

0.50

19.20

2.79

P value prob>F

0.0001

0.0005

0.0895

0.5004

0.0032

0.1737

Model Y6

 

Some of square

100.86

1099.99

0.39

365.55

1.44

7.49

Degree of Freedom

1

1

1

1

1

3

Mean square

100.86

1099.99

0.39

365.55

1.44

2.40

F value

78.24

853.29

0.30

0.30

1.12

4.33

P-value prob>F

<0.0001

<0.0001

0.6006

<0.0001

0.3257

0.0508

Model Y7

 

Some of square

0.23

0.09

0.004

0.004

0.02

0.008

Degree of Freedom

1

1

1

1

1

3

Mean square

0.23

0.09

0.004

0.004

0.02

0.003

F value

138.68

55.11

2.67

2.84

12.89

4.20

P value prob>F

<0.0001

0.0001

0.146

0.1361

0.0089

0.0996

 


For all colour parameters (L value, a* and b* value), the model F and p-value were 391.5693 and <0.0001, 63.05 and <0.0001, 531.84 and <0.0001, which are statistically significant in this model was high. The model's fitness was determined by the lack of fit test where F-value and p-value were 4.807137 and 0.0817, 6.04 and 0.0575, 6.03 and 0.0576 indicated the model's suitability. The lower P-value is comparatively significant cause the model terms—the P-value is less than 0.05, which has shown that the model was significant. The goodness of model fit was evaluated by the determination regression coefficient (R2). The CV value was 3.302819, 8.00, and 4.67 indicated the deviations between experimental and predicted values are low, high degree of precision (72.43, 24.180 and 61.011) revealed a good sign of the experiments.

 

For antioxidant content, the model F and p-value of capsaicin were 23.318 and 0.0003, phenol was 254.58 and <0.0001, flavonoid was 42.135 and <0.0001, which have indicated that the model was highly statistically significant. The lack of fit F-value and p-value for capsaicin was 2.786 and 0.173, phenol was 6.530, and the 0.0508 flavonoid was 4.202 and 0.0996 suitability model for predicting variations. The R2 value of capsaicin, phenol, and flavonoids were 0.943363, 0.994531, and 0.967842. C.V= 9.262333, 6.861018, and 13.86411 revealed that the deviations between experimental and predicted values are low, proving the experiment's excellent reliability.

 

The model F and p-value of moisture content were 53.76 and <0.0001, indicating that the model is significant. The lack of fit F-value and p-value for moisture was 4.33, and 0.0954 indicated the model's suitability. The R2 value of moisture content was 0.9746, and C.V= 9.39 revealed that the deviations between experimental and predicted values are low, proving the experiments' good reliability.

 

Table 4. Determination coefficient on process variables in ANOVA

Regression coefficient

Y1

Y2

Y3

Y4

Y5

Y6

Y7

R2

0.99

0.97

0.99

0.97

0.94

0.99

0.96

Adjusted R2

0.99

0.96

0.99

0.95

0.90

0.99

0.94

Predicted R2

0.97

0.81

0.97

0.95

0.58

0.95

0.78

CV %

3.30

8.00

4.67

9.39

9.26

6.86

13.86

 

Effect of cooking time and temperature on capsicum powder incorporated candy:

The response surface determines the effects of cooking time and temperature to determine the colour value (L*, a*, b*) in figure 1 (a), (b) (c) to better visualize for significant (p <0.0001) effect, interaction effects is variables on the colour value of candy. The interaction between cooking time and temperature and their effect on L*, a*,b* value, figures 1 (a) and (c) show respectively. The moderate redness (a value) and lightness (L value) score varied from 4.44 to 14.08 and 9.5 to 22.34. It was found that cooking time and temperature were significantly affected the redness and lightness colour of candy in quadratic manners. The interactive effects between cooking time and temperature showed a positive and significant effect on colour quality.

A

B

C

Fig.1.Response surface plot for the effect of microwave power and time on the colour quality of Capsicum fortified candy.

 

Effects of cooking time and temperature to determine antioxidant value in figure 2 (a), (b) (c) to better visualize for significant (p <0.0001) effect, interaction effects vary on the antioxidant value of candy. The average antioxidant compound values were varied from 1.55 to 3.99 for capsaicin, 8.02 to 40.03 for phenol, and 0.009 to 0.444 for flavonoid. Increased cooking power and time capsaicin values will be increased because capsaicin is a thermo stable compound.

 

A

B

C

Fig.2 Response surface plot for the effect of microwave power and time on the antioxidant content of Capsicum fortified candy.

 

Figure 3 shows the effects of cooking time and temperature on the moisture content of candy to visualize better the significant (p<0.0001) effect of interaction effects on the moisture content of candy. The average moisture content values were varied from 0.36 to 3.36. Due to high power and more exposure time, the moisture content will be less. High power 420 W and 14 min less moisture content 0.36 will be found.

 

Fig. 3 Response surface plot for the effect of microwave power and time on the moisture content of Capsicum fortified candy.

 

Texture:

The texture profile analysis of the optimum sample of candy was observed that Hardness was 4±0.5 N/mm², Chewiness was 2.45±0.09, Springiness was 0.7±0.1 and Fracture ability was 3.1±0.3.

 

CONCLUSION:

This study showed that the varying microwave power and time combination during cooking leads to a significant change in Capsicum fortified candy's physicochemical properties. Increase the combination of time-microwave power burn the batter, and due to the liquid condition of batter, the combination of low power and low time (300W - 10minutes) is gives good combination for made candy. It gives best colour (L* =13.1±0.019, a* =4.4±0.0128, b*=4.4±0.0312), antioxidant (2.4±0.012)mg/ml and texture (hardness 4±0.5) properties. Daily Consumption of Antioxidants, Prevention of disease is better than cure.

 

ACKNOWLEDGEMENT:

The authors want to acknowledge Jadavpur University, Kolkata-700032, India, for providing samples and the necessary instrumental facilities to complete the work.

 

CONFLICT OF INTEREST:

There is no conflict of interest as a result of this declared by its authors.

 

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Received on 15.04.2021           Modified on 04.06.2021

Accepted on 02.07.2021         © RJPT All right reserved

Research J. Pharm. and Tech. 2022; 15(7):2962-2968.

DOI: 10.52711/0974-360X.2022.00494