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 incaspicum¹. Candies are usually divided into two basic classes that are crystalline and non-crystalline hard candies^2,3. 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 producttodecrytheinversion⁵. The crystallization in hard candies minimized by adjusting formulation and cooking time and cooking power^6,7. 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 90^oC 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 65^oC with 10ml of acetonitrile. The extract was dried at 60^OC, resuspended in 0.5ml ACN, filtered through a 0.45m membrane filter, and deposited at -20^OC. 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:

x_i = (X_i –X_z)/Y_i i=1, 2, 3, k

x_i, X_i, and X_z detonated as an independent variable; Y_i, 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=2^K +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 b₂₂are 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 X₁X_2,

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+0.073X₁X_2.

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
Run	Cooking Time	Cooking Power	Moisture (%)	L*	a*	b*	Capsaicin	Phenols	Flavonoids
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.

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.

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

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

DOI: 10.52711/0974-360X.2022.00494