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Optimization The Effect of Roasting Conditions by Central Composite Design (CCD) Method on The Antioxidant Compounds of Opuntia Ficus Indica Seeds From Morocco
Chakir El Guezzane, Hamza El Moudden, Hicham Harhar, Abdelkader Zarrouk, Mohamed Tabyaoui
Chakir El Guezzane
Laboratory of Materials, Nanotechnology and Environment, Faculty of Sciences, Mohammed V University, P.O. Box 1014 Agdal-Rabat, Morocco
Hamza El Moudden
Laboratory of Materials, Nanotechnology and Environment, Faculty of Sciences, Mohammed V University, P.O. Box 1014 Agdal-Rabat, Morocco
Hicham Harhar
Laboratory of Materials, Nanotechnology and Environment, Faculty of Sciences, Mohammed V University, P.O. Box 1014 Agdal-Rabat, Morocco
Abdelkader Zarrouk
Universite Mohammed V de Rabat
Corresponding Author
Mohamed Tabyaoui
Laboratory of Materials, Nanotechnology and Environment, Faculty of Sciences, Mohammed V University, P.O. Box 1014 Agdal-Rabat, Morocco
This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License
The effect of roasting conditions on antioxidant activity Opuntia Ficus Indica seeds from Morocco and their phenolic compounds were optimized by the Central Composite Design (CDD) method. The CCD was used to optimize the roasting conditions: temperature (X1: 60–200 °C) and roasting time (X2: 10–50 min). The best roasting conditions were used in order to optimize the optimal value of the response : TPC (Total Phenolic Content): X1: 200°C, X2: 50min with 104.86±1.94GAE/g extract predicted response, TFC (Total Flavonoids Content) : X1: 200 °C, X2: 50 min with 81.23±0.90 mg QE/g extract predicted responses, TTC (Total Condensed Tannins Content): X1: 128.9°C, X2: 34.92min with 6.12±0.95 mg QAE/g extract) predicted response. Moreover, the optimal potential antioxidant activity by ABTS assay and DPPH assay was found in extracts of Opuntia Ficus Indica seeds roasted: at a high temperature of the roasting. Furthermore, the positive significant correlations were determined by the principal component analysis (PCA) on the one hand, between the antioxidant capacity of the extracts and their antioxidants compounds (TPC and TFC), and on the other hand, between the two assays ABTS and DPPH. Consequently, the results of this work indicated that roasted Opuntia Ficus Indica seeds from Morocco can be considered as an essential ingredient for human foods.
The Opuntia cactus is specie originally from Mexico (Mulas, 1992) and considered an important food for the indigenous populations (Barbera, Inglese, & Pimienta-Barrios, 1995). It is a specie of the Cactaceae family, the it is distributed in all continents as well as cultivated especially in the arid and semi-arid regions such as Africa and the Mediterranean region, South and Central America (Benayad et al., 2014). Moreover, the prickly pear fruit are rich in sugar, vitamin C, minerals, antioxidant compounds, and pigments, consequently, it was recommended in the human diet (Di Cagno et al., 2016). Furthermore, the seeds from Opuntia sp are considered rich in nutritional value, such as polyphenol, tannins, flavonoids, and fatty acids, in addition to that, the doses of these compounds are higher than in the pulp of the fruit, these fruits are eaten fresh with their seeds (Al Juhaimi et al., 2018). Also, the nutritional value and the chemical compounds of the oils of the seeds can be modified by roasting, this method is considered as a pretreatment which is done before extraction (Gao et al., 2019), and it can render the color, texture, and acceptability of grilled products (Khan & Saini, 2016). In addition to that, various studies showed that roasting pretreatment modifies the phenolic profile of the seeds; it can improve the health benefit effects (Carciochi, Galván D′ Alessandro, Manrique, & technology, 2016). Consequently, the roasting can influence the antioxidant power of the seeds, this influence can depend on the formation of Maillard reaction products (MRP) and the thermal degradation of natural antioxidant molecules (Açar, Gökmen, Pellegrini, Fogliano, & Technology, 2009; Zhang, He, Hu, & technologies, 2011). Also, the study done by Sharma et (Sharma et al., 2015) showed that an increase in phenolic compounds and potential antioxidant capacity of six varieties of onions at 80° C,100°C,and 120°C. In this work, we are interested in the response surface methodology (RMS), it is a statistical technique useful for optimization. It is based on the most important variables and their effects of an experiment to build an empirical model, among the advantages of this technique; it makes to reduce the number of experimental tests necessary to evaluate several factors and their interactions (Zhang et al., 2011). In the present work, we want to apply the Central Composite Design (CDD) approach, in order to investigate the effect of roasting treatment: roasting temperature, roasting time to maximize the contents of antioxidants compounds, and the antioxidant activity of opuntia ficus idica seeds. The main objective of this paper, we applied the CDD approach, in order to assess the effect of roasting treatment : roasting temperature and roasting time for to maximize the TPC(Total Phenolic Content),TFC (Total Flavonoids Content ),TTC(Total Condensed Tannins Content), and the antioxidant properties by ABTS and DPPH assays for opuntia ficus indica from Morocco, Significant correlations between the antioxidant compounds and the antioxidant activities of Opuntia ficus-Indica seeds were evaluated by principal component analysis (PCA).
Plant materials
The plant material (Opuntia ficus-indica seeds) studied, were collected in the period between June and July 2019, in the region of Taza located in the East-North of Morocco.
Preparations of extracts
After the harvested of the fruits, the seeds were isolated, and then dried in the dark at room temperature for 72 hours, and they have been placed in an aluminum Petri dish (7 cm diameter) and roasted in a forced hot-air convection oven at 60, 130 and 200 °C for 10, 30 and 50 min. After that, the seeds will be crushed using a grinder, this fine powder will then be used for the preparation of the various extracts. Moreover, 40 grams of fine powder was macerated with the ethanol solvent for 48 hours. After that, the solvent was evaporated using a rotary evaporator. The extracts obtained are preserved at a temperature of about -4 ° C until the subsequent analyzes.
Chemicals and reagents
the chemical reagents that are used in these studies are categorized as follows : 2,2-diphenyl-1-pycridazil (DPPH. 90%) ,2,2’-azino-bis(3-ethylbenzthiazoline–6-sulphonic acid) (ABTS), Ascorbic acid, 2-thiobarbituric acid (TBA), aluminium chloride (AlCl3), K2HPO4, KH2PO4, ethylene-diaminetetraacetic acid (EDTA), Sulfuric acid and phenol and potassium persulphate,Folin–Ciocalteu’s phenol reagent, aluminum chloride, , sodium acetate, sodium carbonate, sodium hydroxide , methanol, ethanol,ferrous sulfate, ferric chloride, ) and 2,4,6-Tris(1-pyridyl)-5-triazine (TPTZ).
Determination of Total Phenolic Content (TPC)
The TPC of these extracts seeds was quantified by the method of singleton (Singleton, Orthofer, & Lamuela-Raventós, 1999). 200 μl of OFI seed extracts, add a volume of 1.5 ml of Folin Ciocalteu reagent (diluted 10 times). After 4 minutes, a volume of 1.5 ml of 5% sodium carbonate (Na2 CO3) was added on to the solution. The tubes were placed in darkness. After two hours, Gallic acid was used as a standard for the calibration curve. The results were read on a spectrophotometer at 750 nm. The concentration of total polyphenols is deduced according to a calibration interval established with Gallic acid (0-100 μg / ml), as well as are presented in milligrams equivalent of a Gallic acid gram of extract (mg EGA / g extract).
Determination of Total Flavonoids Content (TFC)
The TFC was determined according to the method discussed by yeddes et al (Yeddes, Chérif, Guyot, Sotin, & Ayadi, 2013). 1 ml of extract is added to 1 ml of a solution of AlCl3 (2% in methanol). After ten minutes of reaction, the absorbance is read at 430 nm. The flavonoid content is determined using a linear regression equation deduced from the calibration curve and expressed in milligrams equivalent of Quercetin per gram of extract (mg EQ / g extract). The flavonoid concentration is deduced from a calibration range established with Quercetin (0-100 μg / ml).
Determination of Total Condensed Tannins Content (TTC)
The TTC was done by the method described by the method described by sun et al (Sun, Ricardo-da-Silva, Spranger, & chemistry, 1998).50 mL of extracts seeds (50-600 mg / mL) was added to 3 mL of 4% methanolic vanillin solution and 1.5 mL of H2SO4. The absorbance was read at 430 nm after 15 minutes. The Catechin calibration curve was in the range of 50-600 mg / mL. TTC was presented as mg Catechin equivalent (CE) per gram of extract
Radical scavenging activity of DPPH1(1-diphenyl picrylhydrazyl)
The free radical removal capacity of the extracts was evaluated by the method of Grzegorczyk et al (Grzegorczyk, Matkowski, & Wysokińska, 2007). One ml for each extract at different concentrations (50 to 1000µg / ml) was mixed with one ml of a methanolic solution of DPPH at 0.1 mM and let sit for 30 min at 27 ° C. Methanol and DPPH were used as controls. After incubation at 37 ° C in the dark for 20 min, the absorbance was read at 517 nm. The antiradical capacity was quantified according to the following equation: % Radical scavenging activity DPPH = 1-[Asample / Acontrol] × 100, where A sample and A control were the absorbance of the sample and control. The results obtained for each extract tested are compared with those obtained for ascorbic acid taken as standard antioxidant.
Radical cation inhibition activity (ABTS)
The radical cation capacity of OFI seed extracts was determined by the method described by Yim el al (Yim et al., 2013). 88µL of 140mM of potassium persulfate (K2S2O8) was added to 5ml of 7mM ABTS.+ solution. After that, the whole was stored in the dark at room temperature for 16h.Then,the absorbance of the ABTS.+ mixture was adjusted by ethanol to 0.70 ±0.05 at 734nm.10µ of OFI seed extracts at different concentration was mixed with 1 ml of ABTS reagent (100 to 1000µg / ml).The absorbance was read against the blank reagent at 734nm.The inhibition capacity was quantified uation according to the following equation:: % Radical inhibition activity ABTS= 1- [Aextract / Acontrol] × 100, where A extract and Acontrol were the absorbance of the extract and control
Experimental design
In this study we used the CDD method, this method consists of 11 experimental assays (Table2) was employed for the optimization of roasting variables. The independent variables include roasting temperature and roasting time. These variable had a three levels (-1.0.+1) which are lower, medium, and higher (Table 1). TPC, TFC and TTC and antioxidant activity by ABTS assay and DPPH assay were selected such as the response of model design(Y) in this study; they are presented in Table 2. The regression coefficients (β) were obtained by the adjustment the experimental results to a second order polynomial model; this model was used to response analysis surface as below.
Where, Y is the response variable, Xi and Xj are the independent variables. β0, βi,, βii ,and βij are the regression coefficients of the model which are the constant, linear, quadratic ;and interactive effect respectively. These coefficients were obtained by analysis of variance ANOVA using JMP11 (SW) software. The p-value of the model, coefficient of determination (R2), coefficient of adjustment (R2adj), and the p-value of lack of fit were used to the estimation of the adequacy of the polynomial equation to the responses. The desirability function was employed for multi-response optimization (Los, Zielinski, Wojeicchowski, Nogueira, & Demiate, 2019). All terms of the model were significant when their p-value is less than 0.05.3D response surface graphs were generated by JMP11(SW) software (Tomšik et al., 2016).
Table 1
Levels of variables of the roasting condition by CDD
Extraction process
Independent variables
Level
(-1)
(0)
(+ 1)
Maceration process
X1 roasting temperature(°C)
60
130
200
X2 roasting time(min)
10
30
50
Data Analysis of principal component analysis (PCA) and matrix correlation
The correlations between all responses studied (TPC, TFC, TTC, ABTS, and DPPH) were determined by PCA. Also, PCA has represented the eleven extracts studied with the responses in a graph for facilitate comprehension the variation of the results of values photochemical responses according to the nature of the roasting condition.
Data Analysis
Central Composite Design (CCD) was done to the optimization of roasting conditions for Opuntia Ficus Indica seeds using, it was analyzed by JMP 11(SW) software. Moreover, the XLSTAT 2014 software (Zielinski et al., 2014) was used to determine the Pearson correlation between all data responses and for a graphical representation (PCA). Software IBM SPSS Statistics 21 was used to express the data in means ± standard error of the mean. The signification of data was done by the Tukey test at alpha = 0.05.
Table 2 present the results of the responses TPC, TFC, and TTC, DPPH, and ABTS of extracts from opuntia ficus indica seeds .This optimization of the roasting conditions was achieved in eleven randomized trials in order to evaluate the effects of different roasting factures on the studied responses.
Table 2
Experimental design and results of TPC, TFC, TTC, and antioxidant activity by DPPH assay, ABTS assay from opunitia ficus indica seeds extracts
Run
X1
X2
TPC
TFC
TTC
DPPH IC50
ABTS IC50
1
130
30
23.43 ± 1.23a
53.71 ± 0.90ah
6.8 ± 0.20a
217.34 ± 2.96a
410.62 ± 4.70a
2
200
10
46 ± 0.56b
49.14 ± 1.04h
1.2 ± 0.30b
149.72 ± 2.89b
287.76 ± 2.09b
3
130
50
41.85 ± 1.05b
70.21 ± 0.79b
4.6 ± 0.70ae
144.10 ± 3.03b
320.83 ± 4.93c
4
130
30
2427 ± 1.20a
57.21 ± 1.20a
6.4 ± 0.95a
212.93 ± 4.03a
402.92 ± 3.98a
5
200
30
59.86 ± 0.94d
56.34 ± 0.96a
1 ± 0.17b
120.30 ± 2.18d
240.013 ± 3.997d
6
200
50
104.86 ± 1.94e
81.23 ± 0.90c
1.4 ± 0.23b
90.663 ± 2.093e
124.9 ± 4e
7
60
10
21.57 ± 1.07af
28.86 ± 1.10d
0.4 ± 0.05b
458.69 ± 3.70f
624.736 ± 3.11f
8
60
30
15.57 ± 1.10f
30.43 ± 0.43de
1.8 ± 0.33be
375.92 ± 4.98 g
471.67 ± 2.90 g
9
130
10
20.71 ± 0.71af
34.43 ± 1.03e
2.1 ± 0.30be
290.47 ± 3.79h
546.48 ± 3.21i
10
60
50
15.42 ± 1.02f
63.29 ± 0.90 g
2.2 ± 0.60be
265.94 ± 4.02i
367.54 ± 2.10j
11
130
30
26.23 ± 1.20a
57.89 ± 1.09a
6.1 ± 0.90a
215.92 ± 3.02a
413.97 ± 4.02a
The data are presented in the form of the average of two individual repetitions (n = 2e ± SEM), the means followed by similar letters exposing in the same colum are not different (P < 0.05). TPC (mgGAE/gextract ) : TFC(mgQE/gextract) : TTC(mgQAE/gextract) : DPPH IC50 (µg/ml) : ABTS IC50 (µg/ml), X1 roasting temperature(°C) : X2 roasting time(min)
Interpretation of the response surface model of TPC
Second-order polynomial model
In this study, the TPC of extracts from opuntia ficus indica seeds varied from 15.42 ± 1.02 to 104.86 ± 1.94 mg GAE / g extract. According to the results of ANOVA for TPC (Table 3),the model was significant (p-value < 0.0001).The lack of fit was not significant (P-value = 0.0862),which showed that the model equation was adequate to predicting the value values of the response. Additionally, the R2 value was 0.990054 and the adjusted determination coefficient (Radj2 = 0. 980107), showing that the model adequately showed the true combination between all factors studied. According to Li et al (LI et al., 2019), when the determination coefficient was more than 0.75, the model is adequate. The equation Eq. 2 was represented according to a reduced regression model, it can predicate to the effects of factor variables on the content of TPC.
Anova data of the regression coefficient and the terms of the model
Source
Coef
Sum of square
Degree of freedom
Mean square
F-value
p-value
TPC
Model
7047.1123
5
1409.42
99.5379
< 0.0001*
Constant
24.093684
< 0.0001*
X1
26.36
4169 .0976
1
4169 .0976
294.4350
< 0.0001*
X2
12.308333
908.9704
1
908.9704
64.1944
0.0005*
X1 *X2
16.2525
1056.5750
1
1056.5750
74.6187
0.0003*
X1 *X1
14.445789
528.6581
1
528.6581
37.3355
0.0017*
X2 *X2
8.0107895
162.5710
1
162.5710
11.4813
0.0195*
Residual
70.7983
5
14.16
Lack of fit
66.669210
3
22.2231
10.7642
0.0862
Pure Error
4.129067
2
2.0645
Total Error
70.798277
5
R2
0.990054
Radj2
0.980107
* Significant at p-value < 0.05
X1 had a significant positive linear effect (p-value < 0.0001), as well as, it’s the quadratic X1* X1 had a significant positive effect (p-value < 0.05) on TPC. Moreover, the linear effect of the roasting time X2 and its quadratics effects X2* X2 were shown to have a significant positive effect respectively (p-value < 0.05).Furthermore, the interaction effect between the two parameters studied X1* X2 had significant (p-value < 0.05) on TPC.
Response Surface Methodology (RSM) analysis
The effects of both the roasting temperature and the roasting time and their reciprocal interactions on TPC can be visualized on the generating 3D response surface plots shown in Fig. 1. According to Fig. 1, the TPC content increased when X1 roasting temperature (°C) increased at a roasting time fixed, also it increased rapidly when the X2 roasting time (min)exceeds 30 min. Thus, the maximal extraction of TPC was found at the strong levels of both the roasting temperature (X1) and roasting time (X2). However, to get optimization overall of all variables studied. Optimization of the response was used by desirability function (d) in order to obtain the maximum response in TPC of the opuntia ficus indica seeds, thereby the maximum response precision is obtained when the desirability close to 1 (Figure.6) (Gullian Klanian & Terrats Preciat, 2017; Laib & Barkat, 2018; Los et al., 2019). Therefore, the optimal conditions were determined by using the JMP prediction profiler. The results regarding the optimized conditions of roasting by maceration extraction were when the desirability values (d = 0.89) close to 1 (Fig. 6.a): 200 °C, 50 min and predicted response is 101.4711 mg GAE/g extract). The experimental value was 104.86 ± 1.94 mg GAE/g extract, Therefore, the experimental and predicted responses were close. Hence, these results suggest that the model may be valid for the prevision of phenolic content by extraction maceration of the OFI seeds roasted. These results confirm the results found by several studies. Chandrasekara et al (Chandrasekara, Shahidi, & Chemistry, 2011) showed that the roasting at high temperature (130 °C) for 33 min had increased the phenolic content relative to raw seed (testa, cashew nuts).Yu et al (Yu, Ahmedna, & Goktepe, 2005) have also found that the TPC (in both water and ethanol) from peanut skin was increased about 35.9% by roasting at 175 °C for 5 min relative to the raw sample. Also, Locatelli et al (Locatelli et al., 2010) and Yin el al (Yin et al., 2019) respectively indicated that the TPC from extract soluble of hazelnut skin increased at 180 °C for 20 min more than 10 min,and the TPC increased about 3.4 times at temperature between 120 °C and 140 °C for 180 min, as well as, it increases more at 140 °C. Moreover, Kim et al (Kim et al., 2006) showed that, the TPC significantly increased (p-value < 0.05) at heat treatment. Accordingly, the increase in the content of phenolic compounds can be explained by the following causes:
During the roasting ,the molecules phenolic can be degraded/polymerized, which indicated the training of the new compounds, these compounds can be more soluble in ethanol and water, as well as, they can reagent with the Folin-Ciocalteu in alkaline middle(Yu et al., 2005).
It could be due processed by roasting, because the bound molecules bioactive can be released (Jeong et al., 2004).
Interpretation of the response surface model of TFC
Second-order polynomial model
Our results showed that, the TFC of extracts from opuntia ficus indica seeds varied from 28.86 ± 1.10 to 81.23 ± 0.90 mg QE / g extract. Moreover, ANOVA was used to verify the adequacy and the significance of the model. Table 4 showed that, the F-value is large (12. 9938) and the p-value is small (0.0069), which confirms that the model has been validated. Additionally, the lack of fit was not significant (p-value: 0. 0771) which indicates the was significant for TFC prediction of the opuntia ficus indica seeds roasted, the lack of fit cheks the inability of the model (LotfizadehDehkordi, Ghadimi, & Metselaar, 2013). The coefficients of determination R2 and of adjusted had high values R2 = 0.92854 and Radj2 = 0.85708 respectively. These values indicated that the quality of the model is valid. The equation which combines the relationship between the variables and prediction TFC was described below.
ANOVA data of the regression coefficient and the terms of the model.
Source
Coef
Sum of square
Degree of freedom
Mean square
F-value
p-value
TFC
Model
2510.9388
5
502.188
12.9938
0.0069*
Constant
52.860526
< 0.0001*
X1
10.688333
685.4428
1
685.4428
17.7354
0.0084*
X2
17.05
1744.2150
1
1744.2150
45.1306
0.0011*
X1 *X2
-0.585
1.3689
1
1.3689
0.0354
0.8581
X1 *X1
-4.361316
48.1867
1
48.1867
1.2468
0.3149
X2 *X2
4.5736842
52.9938
1
52.9938
1.3712
0.2944
Residual
193.2410
5
38.648
Lack of fit
183.17941
3
61.0598
12.1372
0.0771
Pure Error
10.06160
2
5.0308
Total Error
193.24101
5
R2
0.92854
Radj2
0.85708
* Significant at p < 0.05
Roasting time(X2) had a positive significant linear effect (p-value = 0.0011 < 0.05) on TFC, and it doesn’t have a significant quadratic effect (p-value = 0.2944).As well as, the Roasting temperature X1 had significant positive linear (p-value = 0.0084), but its quadratic effect is not significant (p-value = 0.2944). Moreover, the not significant interaction effect between the two parameters studied was observed (Table 4).
Response Surface Methodology (RSM) analysis
Figure 2 shows the response surface plot of roasting temperature and roasting time on total flavonoid content. The TFC increased with the increased both the roasting time and the roasting temperature. Accordingly, the higher TFC yield was detected in regions of high roasting temperature and hard roasting time. Consequently, the optimum extraction of TFC was at: roasting temperature 200°Cand roasting time 50 min, and it was assigned for the predicted response is 80.22623 (mg QE/g extract) with the desirability is d=0.84(Figure.6.b.). Our results are similar with various studies as, Lin et al (Lin et al., 2016) reported that the TFC increased significantly after 5min of the roasting, as well as, the flavonoid aglycones and acids are increased according to roasting temperature and time. Furthermore, Kumar et al (Kumar & Pandey, 2013) mentioned that, the fractions of sugar in flavonoids glycosides have an important role in antioxidants capacity, as well as, the aglcycones had a high effect on the antioxidant capacity more than the glycosides.
Interpretation of the response surface model of TTC
Second-order polynomial model
Table 5 shows the coefficients of regression and their significance for the TTC yield. The regression model was significant (p-value = 0.0231). Also, the determination coefficients (R2) for the TTC response variable (0.881256) and the lack-of-fit values (0.0537) were not significant (P > 0.05), which indicates that the model can explain all data. So the response variable was included in roasting optimization. Besides, the R2adjs was 0.762512,it indicated that 76.25% of the variability was estimated by the model. Therefore, the second-order polynomial model was applied (Eq. 4).
ANOVA data of the regression coefficient and the terms of the model.
Source
Coef
Sum of square
Degree of freedom
Mean square
F-value
p-value
TTC
Model
50.697863
5
10.1396
7.4215
0.0231*
Constant
5.8052632
0.0002*
X1
-0.133333
0.106667
1
0.106667
0.0781
0.7911
X2
0.75
3.375000
1
3.375000
2.4703
0.1768
X1 *X2
-0.4
0.640000
1
0.640000
0.4684
0.5241
X1 *X1
-3.463158
30.383439
1
30.383439
22.2386
0.0053*
X2 *X2
-1.513158
5.800439
1
5.800439
4.2455
0.0944
Residual
6.831228
5
1.3662
Lack of fit
6.5845614
3
2.19485
17.7961
0.0537
Pure Error
0.2466667
2
0.12333
Total Error
6.8312281
5
R2
0.881256
Radj2
0.762512
* Significant at p < 0.05
According to p-value < 0.05, the X1 * X1 is the quadratic effect of roasting temperature was positive significant for TTC, on the contrary, its linear effect did not have significant because of the p-value = 0.791. As well as, the X2 and X2 * X2 of roasting time were not had significant in TTC because, their p-value was respectively: 0.1768, 0.0944. The X1 *X2 had also not significant according to its p-value was 0.5241.
Response Surface Methodology (RSM) analysis
The 3D of response surface of regression Eq. (3) were constructed using RSM to illustrate the effects of the roasting temperature and roasting time and their interaction on the TTC (Fig. 3). Accordingly, the TTC content increased before the roasting temperature increased at 130 °C, after that it decreased quickly. Also, the TTC increased with the roasting time in the range of 10 to 35 min and then decreased.. The optimum extraction of TTC was roasting temperature 128.9 °C, roasting time 34.92 min with 5.901 (mg QAE/g extract) predicted responses and the desirability is d = 0.82(Figure.6.c.).These results are similar to these reported by Lin et al (Lin et al., 2016), they showed that, during the roasting at 200 °C for 20 min the content of condensed tannins from ethanol extracts had a high levels in TTC.
Interpretation of the response surface model of DPPH assay
Second-order polynomial model
The ANOVA results from DPPH assay content based on the RSM design are reported in Table 6.The p-value of the model was (< 0.0001),which indicated that the model was significant. Moreover, the R2 and R2adj were 0.997921 and 0.995841 respectively, that confirms the adequacy of the model because R2 > 0.75 (LI et al., 2019). Additionally, the lack of fit (p-value > 0.05) confirms also the adequacy the model for prediction of the antioxidant power for opuntia ficus indica seeds roasted. Therefore, the second-order polynomial model was applied (Eq. 5).
ANOVA data of the regression coefficient and the terms of the model.
Source
Coef
Sum of square
Degree of freedom
Mean of square
F-value
p-value
DPPH
Model
124190.70
5
24838.1
479.9081
< 0.0001*
Constant
217.23774
< 0.0001*
X1
-123.3112
91233.863
1
91233.863
1762.768
< 0.0001*
X2
-66.36283
26424.154
1
26424.154
510.5521
< 0.0001*
X1 *X2
33.42325
4468.455
1
4468.455
86.3369
0.0002*
X1 *X1
28.110658
2001.863
1
2001.863
38.6788
0.0016*
X2 *X2
-2.714342
18.665
1
18.665
0.3606
0.5743
Residual
258.78
5
51.8
Lack of fit
248.64531
3
82.8818
16.3558
0.0582
Pure Error
10.13487
2
5.0674
Total Error
258.78018
5
R2
0.997921
Radj2
0.995841
* Significant at p < 0.05
Based on statistical analyses of ANOVA for DPPH, the roasting temperature (X1) and roasting time (X2) had a negative significant linear effect on the IC50 of DPPH assay, because their P-value is equal respectively a <0.0001*and <0.0001*.As well as, their interaction had significant for DPPH because the p-value was 0.0002*.On the contrary, their quadratic effects were not had significant due to their p-value was >0.005.
Response Surface Methodology (RSM) analysis
The response surface (3D) of regression Eq. (5) were constructed using RSM to illustrate the effects of X1 and X2 and their interactionX1*X2 on the IC50 of DPPH assay (Fig. 4.). We know that the antioxidant power is inversely proportional with the value of the IC50. We observed that the increase in the antioxidant power was made thanks to the increasing of the X2 roasting time and the increasing of the roasting temperature (X1). The optimum of the antioxidant power by DPPH assay observed at roasting temperature 200 °C and roasting time 50 min with 96.60% of inhibition, which matches 86.3845 µg/ml predicted responses, and also the desirability is d = 0.93(Figure.6.d.).Our results confirm those founded by Lin et al (Lin et al., 2016), they reported that, the higher antioxidants capacity was observed at strong roasting temperature for ethanol extracts from almond(Prnus duclis)kernel, and during the roasting at 200 °C for 20 min the power for scavenging DPPH radical was strong than the raw sample. Moreover, Chandrasekra et al (Chandrasekara et al., 2011), reported that in their study, the scavenging capacity of DPPH radical increased significantly with the increase of the roasting temperature for soluble phenolic extract from testa, as well as, they justified that increase due to Maillard reaction products MRPs. Indeed, during at roasting, a reaction between the reducing sugars and amino acids can be done, this reaction can produce the new compounds, which are Maillard reaction products MRPs, these formed products can contribute to TPC, flavour, antioxidant activity and color of food (Chandrasekara et al., 2011). Furthermore, the resultant melanoidin and the intermediate Maillard reaction products (MRPs) had strong antioxidant pwer,which are according to the presence of reductone-type structures (Hayase, Hirashima, Okamoto, Kato, & Chemistry, 1989).
Interpretation of the response surface model of ABTS assay
Second-order polynomial model
Experimental modeling results for antioxidant power by ABTS assay were shown in Table 7. From the model analysis, the R2 and R2adj of the model were 0.99075, 0.9815 respectively, also did not present lack of fit (p-value = 0. 0528). Moreover, the model was significant because its p-value was < 0.0001,which showed that the model equation was acceptable to predict the antioxidant power by ABTS assay. this model equation is shown in Eq. 6 as follows:
ANOVA data of the regression coefficient and the terms of the model.
Source
Coef
Sum of square
Degree of freedom
Mean square
F-value
p-value
ABTS
Model
193571.35
5
38714.3
107.1061
< 0.0001*
Constant
415.29474
< 0.0001*
X1
-135.2122
109693.98
1
109693.98
303.4772
< 0.0001*
X2
-107.6177
69489.37
1
69489.37
192.2479
< 0.0001*
X1 *X2
23.584
2224.82
1
2224.82
6.1551
0.0558
X1 *X1
-68.64034
11935.79
1
11935.79
33.0213
0.0022*
X2 *X2
9.1731579
213.17
1
213.17
0.5898
0.4772
Residual
1807.29
5
361.5
Lack of fit
1743.0803
3
581.027
18.0991
0.0528
Pure Error
64.2050
2
31.103
Total Error
1807.2853
5
R2
0.99075
Radj2
0.9815
* Significant at p < 0.05
Roasting time (X1) and roasting temperature (X2) had a negative significant linear effect (p < 0.05). Also, the quadratic effect of the roasting temperature X1 * X1 had significant effect (p-value = 0.0022), and the interaction effect between the two parameters roasting was not significant (Table 7).
Response Surface Methodology (RSM) analysis
Figure 5 shows the IC50 of ABTS assay, we observed that the antioxidant power increase significantly when the roasting temperature X1 and roasting time X2 increased, because the IC50 decreased. According to, the more IC50 decreases the more the antioxidant power increases. The optimum of the antioxidant power by ABTS assay was at: roasting temperature 200°C and roasting time 50 min with 96.75% of inhibition, which matches 130.581 µg/ml predicted responses, and also the desirability is d=0.89 (Figure.6.e.). These results are similar to several works as Gao et al (Gao et al., 2019) mentioned that, the ABTS capacity was increased significantly during the roasting at 160°C for 10min compared to raw sample. Also Yin et al (Yin et al., 2019) reported that the ABTS scavenging increased during the heating between 130°C-140°C after 60min.Moreover, these results can depend on several conditions such as, the plants have a bound antioxidant phenol and bound polymeric compounds, during the thermal treatment these molecules can be degraded and released which leads to an increase in the antioxidants activity (Lee, Kim, Kim, Jang, & chemistry, 2002). Furthermore, after the antioxidants characteristics can be improved thanks to the degradation of the heat-labile antioxidants compounds or training the new compounds by Maillard reaction (Nicoli, Anese, Parpinel, & Technology, 1999). Also, the solubility of non-phenolic molecules was improved by roasting (Dewanto, Wu, Adom, Liu, & chemistry, 2002).
Comparisons of predict (models) and experimental results.
The verification experiments for five responses such as antioxidants activity by DPPH IC50 (µg/ml), ABTS•+ inhibition activityIC50 (µg/ml), Total phenolic Contents (mg GAE/g extract, Total flavonoids (mg QE/g extract), and Total Tannins Content (mg QAE/g extract) were reported in Table 8. These experiments were done at the conditions of responses optimal and in the experimental range. these results showed that the values of responses experimental are close to those predicted.
Table 8: predicted and experimental results at conditions optimal
Total phenolic Contents (mg GAE/g extract)
X1 roasting temperature (°C)
X2 roasting time (min)
Predicted value
Experimental value
Total flavonoids content (mg QE/g extract)
200°C
50min
80.22623
81.23±0.90
Total Tannins Content (mg QAE/g extract)
128.9°C
34.92min
5.901
6.12±0.95
Total phenolic Contents (mg GAE/g extract )
200°C
50min
101.4711
104.86±1.94
DPPH IC50 (µg/ml)
200°C
50min
86.3845
90.663±2.093
ABTS IC50 (µg/ml)
200°C
50min
130.581
124.9±4
The data are presented in the form of the average of two individual repetitions (n = 2e ± SEM),
Correlation Matrix
Table 9 showed the correlations coefficients data between all responses studied. Moreover, Table 10 presents the p-value of these correlation coefficients. Additionally, the DPPH (1/DPPH IC50) and ABTS (1/ABTS IC50) represent the power to inhibit DPPH free radical and ABTS.+ radical respectively.
Table 9
Pearson’s correlation matrix coefficient between antioxidant capacity and antioxidants compounds in the extracts from Opuntia Ficus Indica
Variables
TPC
TFC
TTC
DPPH
(1/DPPH IC50 )
ABTS
(1/ABTS IC50 )
TPC
1
TFC
0.652
1
TTC
-0.301
0.287
1
DPPH
(1/DPPH IC50)
0.949
0.784
-0.121
1
ABTS
(1/ABTS IC50)
0.966
0.727
-0.255
0.920
1
The values is bold are different from 0 at a significance level alpha = 0.05.TPC (Total Phenolic Content), TTC :Total Condensed Tannins Content, TFC : Total Flavonoïdes Content, DPPH(1/DPPH IC50 ): 1,1-diphenyl-2-picrylhydrazyl radical scavenging activity;ABTS(1/ABTS IC50)
Table 10
p-values of the correlation matrix coefficient between all variables
Variables
TPC
TFC
TTC
DPPH
(1/DPPH IC50 )
ABTS
(1/ABTS IC50 )
TPC
0
TFC
0.030
0
TTC
0.369
0.392
0
DPPH
(1/DPPH IC50)
< 0.0001
0.004
0.723
0
ABTS
(1/ABTS IC50)
< 0.0001
0.011
0.449
< 0.0001
0
The values is bold are different from 0 at a significance level alpha = 0.05.
According to Table 9 and Table 10, we observed that, the TPC had high positive correlations significant (p-value < 0.05) between the antioxidants power. The correlation coefficients of TPC were 0.949 and 0.966 with free radical scavenging effect DPPH and ABTS.+ respectively. These positive correlations are justified that the antioxidants capacity depends on the presence of phenolic compounds in opuntia ficus indica seeds extracts,these results are similar with those reported by several study (Amri et al., 2015; Cheniany et al., 2013; Guettaf, Abidli, Kariche, Bellebcir, & Bouriche, 2016). It found that, the TFC had also the positive correlations significant between DPPH (1/DPPH IC50) and ABTS (1/ABTS IC50) , these correlation coefficients were 0.784 and 0.727 respectively. Therefore, these results are confirmed by the strong positive correlation significant (p-value < 0.05) between TFC and TFC (r2 = 0.652). We observed that, the p-values of TTC with the antioxidants power were not significant (p-value > 0.05), which indicates that Tannin contribute slightly in this bioactivity. Furthermore, the strong positive correlation significant between tow antioxidant capacity (r2 = 0.920),indicates that the same bioactive molecules in our extracts are responsible to the scavenging power of two free radicals DPPH and ABTS.+ ..
Principal Component Analysis (PCA).
According to Fig. 8, the projections of the responses studied and the experiment assays (extracts) were done by the factorial plan reported in Fig. 8.The cumulative percentage was 95.14%, which indicates that it was is representative of the variables because it was more the 50%. Moreover, the two axe are suitable for explains the all information, with the frits (F1) and second (F2) main components have explained 70.63% and 24.51 the information respectively. The correlations between all variables studied were explained by a plan formed by F1 and F2 axes. Besides, the F1 axe was formed by the positive correlation between TPC,TFC,ABTS(1/IC50),DPPH(1/IC50)),on the contrary the F2 axe was constructed by TTC (Fig. 7).Ours 11 extracts studied from opuntia ficus indica seeds, were distributed in three groups according the responses (Fig. 8).
Group I:this group was formed by four extracts(2,3,5,6) ,these extracts had a strong values of the TPC and TFC, as well as, they had also a high power antioxidants by DPPH and ABTS assays.
Group II: it contains four extracts (1, 4, 10, and 11), these extracts are characterized by a strong value of TTC, and by lower values of TPC and TTC. Therefore, their antioxidants activity is lower compared to group I.
Group III is formed by a three extract (7, 8 and 9), these extracts are characterized by the low values of TPC and TFC, and its antioxidant activity is low compared to extracts of the other groups.
The extracts from Group I are characterized by a high roasting temperature varies between 130 °C and 200 °C, and a high time of roasting (50 min) for the extracts roasted at 130 °C, which shows that their a strong antioxidants capacity more than the extracts from the Group II and III obtained by low roasting temperature. Therefore, the roasting makes it possible to increases the extraction of bioactive compounds responsible for antioxidants power.
Dry thermal processing of seeds from the Opuntia ficus indica increased the amounts of active compounds. As well as, antioxidant activity power was significantly improved in extracts roasted especially at stronger temperature. Furthermore, the results indicated that the temperature and time of roasting had significant effects.PCA showed that on one hand the positive correlation between the photochemical compounds (polyphenol, flavonoids) and the antioxidant capacity (ABTS, DPPH),Consequently, this study showed thermal processing can be used as a pre-treatment to increase the antioxidants capacity of Opuntia ficus Indica seeds.
CDD : Central Composite Design; X1: roasting temperature; X2 : roasting time(min); TPC : Total Phenolic Content; TFC: Total Flavonoids Content; TTC : Total Condensed Tannins Content; PCA: Principal Component Analysis; MRP: Maillard Reaction Products; RMS: Response Surface Methodology; DPPH: 2,2-diphenyl-1-pycridazil;ABTS: 2,2’-azino-bis(3-ethylbenzthiazoline–6-sulphonic acid; IC50: half-maximal inhibitory concentration; ANOVA: Analysis of Variance; Eq: equation; R2 : coefficient of determination; R2adj: Coefficient of Adjustment; d: desirability function; r2 : coefficient of correlation; F1:Frist main component; F2 :Second main component; GI: Group I; GII: Group II; GIIi : Group III.
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Availability of data and materials
Not applicable
Competing interests
The authors declare that they have no competing interests.
Funding
Not applicable
Authors’ contributions
C-EG, H-H, A-Z, and M-T conceived and designed the experiments. C-EG and H-EM have carried out experiments. All authors discussed the results and co-wrote the manuscript. All authors read and approved the final paper.
Acknowledgement
The authors would thank Dr I. Nounah for helpful discussion along the realization of this work.
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Optimization The Effect of Roasting Conditions by Central Composite Design (CCD) Method on The Antioxidant Compounds of Opuntia Ficus Indica Seeds From Morocco
Chakir El Guezzane, Hamza El Moudden, Hicham Harhar, Abdelkader Zarrouk, Mohamed Tabyaoui
Chakir El Guezzane
Laboratory of Materials, Nanotechnology and Environment, Faculty of Sciences, Mohammed V University, P.O. Box 1014 Agdal-Rabat, Morocco
Hamza El Moudden
Laboratory of Materials, Nanotechnology and Environment, Faculty of Sciences, Mohammed V University, P.O. Box 1014 Agdal-Rabat, Morocco
Hicham Harhar
Laboratory of Materials, Nanotechnology and Environment, Faculty of Sciences, Mohammed V University, P.O. Box 1014 Agdal-Rabat, Morocco
Abdelkader Zarrouk
Universite Mohammed V de Rabat
Corresponding Author
Mohamed Tabyaoui
Laboratory of Materials, Nanotechnology and Environment, Faculty of Sciences, Mohammed V University, P.O. Box 1014 Agdal-Rabat, Morocco
This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License
The effect of roasting conditions on antioxidant activity Opuntia Ficus Indica seeds from Morocco and their phenolic compounds were optimized by the Central Composite Design (CDD) method. The CCD was used to optimize the roasting conditions: temperature (X1: 60–200 °C) and roasting time (X2: 10–50 min). The best roasting conditions were used in order to optimize the optimal value of the response : TPC (Total Phenolic Content): X1: 200°C, X2: 50min with 104.86±1.94GAE/g extract predicted response, TFC (Total Flavonoids Content) : X1: 200 °C, X2: 50 min with 81.23±0.90 mg QE/g extract predicted responses, TTC (Total Condensed Tannins Content): X1: 128.9°C, X2: 34.92min with 6.12±0.95 mg QAE/g extract) predicted response. Moreover, the optimal potential antioxidant activity by ABTS assay and DPPH assay was found in extracts of Opuntia Ficus Indica seeds roasted: at a high temperature of the roasting. Furthermore, the positive significant correlations were determined by the principal component analysis (PCA) on the one hand, between the antioxidant capacity of the extracts and their antioxidants compounds (TPC and TFC), and on the other hand, between the two assays ABTS and DPPH. Consequently, the results of this work indicated that roasted Opuntia Ficus Indica seeds from Morocco can be considered as an essential ingredient for human foods.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
The Opuntia cactus is specie originally from Mexico (Mulas, 1992) and considered an important food for the indigenous populations (Barbera, Inglese, & Pimienta-Barrios, 1995). It is a specie of the Cactaceae family, the it is distributed in all continents as well as cultivated especially in the arid and semi-arid regions such as Africa and the Mediterranean region, South and Central America (Benayad et al., 2014). Moreover, the prickly pear fruit are rich in sugar, vitamin C, minerals, antioxidant compounds, and pigments, consequently, it was recommended in the human diet (Di Cagno et al., 2016). Furthermore, the seeds from Opuntia sp are considered rich in nutritional value, such as polyphenol, tannins, flavonoids, and fatty acids, in addition to that, the doses of these compounds are higher than in the pulp of the fruit, these fruits are eaten fresh with their seeds (Al Juhaimi et al., 2018). Also, the nutritional value and the chemical compounds of the oils of the seeds can be modified by roasting, this method is considered as a pretreatment which is done before extraction (Gao et al., 2019), and it can render the color, texture, and acceptability of grilled products (Khan & Saini, 2016). In addition to that, various studies showed that roasting pretreatment modifies the phenolic profile of the seeds; it can improve the health benefit effects (Carciochi, Galván D′ Alessandro, Manrique, & technology, 2016). Consequently, the roasting can influence the antioxidant power of the seeds, this influence can depend on the formation of Maillard reaction products (MRP) and the thermal degradation of natural antioxidant molecules (Açar, Gökmen, Pellegrini, Fogliano, & Technology, 2009; Zhang, He, Hu, & technologies, 2011). Also, the study done by Sharma et (Sharma et al., 2015) showed that an increase in phenolic compounds and potential antioxidant capacity of six varieties of onions at 80° C,100°C,and 120°C. In this work, we are interested in the response surface methodology (RMS), it is a statistical technique useful for optimization. It is based on the most important variables and their effects of an experiment to build an empirical model, among the advantages of this technique; it makes to reduce the number of experimental tests necessary to evaluate several factors and their interactions (Zhang et al., 2011). In the present work, we want to apply the Central Composite Design (CDD) approach, in order to investigate the effect of roasting treatment: roasting temperature, roasting time to maximize the contents of antioxidants compounds, and the antioxidant activity of opuntia ficus idica seeds. The main objective of this paper, we applied the CDD approach, in order to assess the effect of roasting treatment : roasting temperature and roasting time for to maximize the TPC(Total Phenolic Content),TFC (Total Flavonoids Content ),TTC(Total Condensed Tannins Content), and the antioxidant properties by ABTS and DPPH assays for opuntia ficus indica from Morocco, Significant correlations between the antioxidant compounds and the antioxidant activities of Opuntia ficus-Indica seeds were evaluated by principal component analysis (PCA).
Plant materials
The plant material (Opuntia ficus-indica seeds) studied, were collected in the period between June and July 2019, in the region of Taza located in the East-North of Morocco.
Preparations of extracts
After the harvested of the fruits, the seeds were isolated, and then dried in the dark at room temperature for 72 hours, and they have been placed in an aluminum Petri dish (7 cm diameter) and roasted in a forced hot-air convection oven at 60, 130 and 200 °C for 10, 30 and 50 min. After that, the seeds will be crushed using a grinder, this fine powder will then be used for the preparation of the various extracts. Moreover, 40 grams of fine powder was macerated with the ethanol solvent for 48 hours. After that, the solvent was evaporated using a rotary evaporator. The extracts obtained are preserved at a temperature of about -4 ° C until the subsequent analyzes.
Chemicals and reagents
the chemical reagents that are used in these studies are categorized as follows : 2,2-diphenyl-1-pycridazil (DPPH. 90%) ,2,2’-azino-bis(3-ethylbenzthiazoline–6-sulphonic acid) (ABTS), Ascorbic acid, 2-thiobarbituric acid (TBA), aluminium chloride (AlCl3), K2HPO4, KH2PO4, ethylene-diaminetetraacetic acid (EDTA), Sulfuric acid and phenol and potassium persulphate,Folin–Ciocalteu’s phenol reagent, aluminum chloride, , sodium acetate, sodium carbonate, sodium hydroxide , methanol, ethanol,ferrous sulfate, ferric chloride, ) and 2,4,6-Tris(1-pyridyl)-5-triazine (TPTZ).
Determination of Total Phenolic Content (TPC)
The TPC of these extracts seeds was quantified by the method of singleton (Singleton, Orthofer, & Lamuela-Raventós, 1999). 200 μl of OFI seed extracts, add a volume of 1.5 ml of Folin Ciocalteu reagent (diluted 10 times). After 4 minutes, a volume of 1.5 ml of 5% sodium carbonate (Na2 CO3) was added on to the solution. The tubes were placed in darkness. After two hours, Gallic acid was used as a standard for the calibration curve. The results were read on a spectrophotometer at 750 nm. The concentration of total polyphenols is deduced according to a calibration interval established with Gallic acid (0-100 μg / ml), as well as are presented in milligrams equivalent of a Gallic acid gram of extract (mg EGA / g extract).
Determination of Total Flavonoids Content (TFC)
The TFC was determined according to the method discussed by yeddes et al (Yeddes, Chérif, Guyot, Sotin, & Ayadi, 2013). 1 ml of extract is added to 1 ml of a solution of AlCl3 (2% in methanol). After ten minutes of reaction, the absorbance is read at 430 nm. The flavonoid content is determined using a linear regression equation deduced from the calibration curve and expressed in milligrams equivalent of Quercetin per gram of extract (mg EQ / g extract). The flavonoid concentration is deduced from a calibration range established with Quercetin (0-100 μg / ml).
Determination of Total Condensed Tannins Content (TTC)
The TTC was done by the method described by the method described by sun et al (Sun, Ricardo-da-Silva, Spranger, & chemistry, 1998).50 mL of extracts seeds (50-600 mg / mL) was added to 3 mL of 4% methanolic vanillin solution and 1.5 mL of H2SO4. The absorbance was read at 430 nm after 15 minutes. The Catechin calibration curve was in the range of 50-600 mg / mL. TTC was presented as mg Catechin equivalent (CE) per gram of extract
Radical scavenging activity of DPPH1(1-diphenyl picrylhydrazyl)
The free radical removal capacity of the extracts was evaluated by the method of Grzegorczyk et al (Grzegorczyk, Matkowski, & Wysokińska, 2007). One ml for each extract at different concentrations (50 to 1000µg / ml) was mixed with one ml of a methanolic solution of DPPH at 0.1 mM and let sit for 30 min at 27 ° C. Methanol and DPPH were used as controls. After incubation at 37 ° C in the dark for 20 min, the absorbance was read at 517 nm. The antiradical capacity was quantified according to the following equation: % Radical scavenging activity DPPH = 1-[Asample / Acontrol] × 100, where A sample and A control were the absorbance of the sample and control. The results obtained for each extract tested are compared with those obtained for ascorbic acid taken as standard antioxidant.
Radical cation inhibition activity (ABTS)
The radical cation capacity of OFI seed extracts was determined by the method described by Yim el al (Yim et al., 2013). 88µL of 140mM of potassium persulfate (K2S2O8) was added to 5ml of 7mM ABTS.+ solution. After that, the whole was stored in the dark at room temperature for 16h.Then,the absorbance of the ABTS.+ mixture was adjusted by ethanol to 0.70 ±0.05 at 734nm.10µ of OFI seed extracts at different concentration was mixed with 1 ml of ABTS reagent (100 to 1000µg / ml).The absorbance was read against the blank reagent at 734nm.The inhibition capacity was quantified uation according to the following equation:: % Radical inhibition activity ABTS= 1- [Aextract / Acontrol] × 100, where A extract and Acontrol were the absorbance of the extract and control
Experimental design
In this study we used the CDD method, this method consists of 11 experimental assays (Table2) was employed for the optimization of roasting variables. The independent variables include roasting temperature and roasting time. These variable had a three levels (-1.0.+1) which are lower, medium, and higher (Table 1). TPC, TFC and TTC and antioxidant activity by ABTS assay and DPPH assay were selected such as the response of model design(Y) in this study; they are presented in Table 2. The regression coefficients (β) were obtained by the adjustment the experimental results to a second order polynomial model; this model was used to response analysis surface as below.
Where, Y is the response variable, Xi and Xj are the independent variables. β0, βi,, βii ,and βij are the regression coefficients of the model which are the constant, linear, quadratic ;and interactive effect respectively. These coefficients were obtained by analysis of variance ANOVA using JMP11 (SW) software. The p-value of the model, coefficient of determination (R2), coefficient of adjustment (R2adj), and the p-value of lack of fit were used to the estimation of the adequacy of the polynomial equation to the responses. The desirability function was employed for multi-response optimization (Los, Zielinski, Wojeicchowski, Nogueira, & Demiate, 2019). All terms of the model were significant when their p-value is less than 0.05.3D response surface graphs were generated by JMP11(SW) software (Tomšik et al., 2016).
Table 1
Levels of variables of the roasting condition by CDD
Extraction process
Independent variables
Level
(-1)
(0)
(+ 1)
Maceration process
X1 roasting temperature(°C)
60
130
200
X2 roasting time(min)
10
30
50
Data Analysis of principal component analysis (PCA) and matrix correlation
The correlations between all responses studied (TPC, TFC, TTC, ABTS, and DPPH) were determined by PCA. Also, PCA has represented the eleven extracts studied with the responses in a graph for facilitate comprehension the variation of the results of values photochemical responses according to the nature of the roasting condition.
Data Analysis
Central Composite Design (CCD) was done to the optimization of roasting conditions for Opuntia Ficus Indica seeds using, it was analyzed by JMP 11(SW) software. Moreover, the XLSTAT 2014 software (Zielinski et al., 2014) was used to determine the Pearson correlation between all data responses and for a graphical representation (PCA). Software IBM SPSS Statistics 21 was used to express the data in means ± standard error of the mean. The signification of data was done by the Tukey test at alpha = 0.05.
Table 2 present the results of the responses TPC, TFC, and TTC, DPPH, and ABTS of extracts from opuntia ficus indica seeds .This optimization of the roasting conditions was achieved in eleven randomized trials in order to evaluate the effects of different roasting factures on the studied responses.
Table 2
Experimental design and results of TPC, TFC, TTC, and antioxidant activity by DPPH assay, ABTS assay from opunitia ficus indica seeds extracts
Run
X1
X2
TPC
TFC
TTC
DPPH IC50
ABTS IC50
1
130
30
23.43 ± 1.23a
53.71 ± 0.90ah
6.8 ± 0.20a
217.34 ± 2.96a
410.62 ± 4.70a
2
200
10
46 ± 0.56b
49.14 ± 1.04h
1.2 ± 0.30b
149.72 ± 2.89b
287.76 ± 2.09b
3
130
50
41.85 ± 1.05b
70.21 ± 0.79b
4.6 ± 0.70ae
144.10 ± 3.03b
320.83 ± 4.93c
4
130
30
2427 ± 1.20a
57.21 ± 1.20a
6.4 ± 0.95a
212.93 ± 4.03a
402.92 ± 3.98a
5
200
30
59.86 ± 0.94d
56.34 ± 0.96a
1 ± 0.17b
120.30 ± 2.18d
240.013 ± 3.997d
6
200
50
104.86 ± 1.94e
81.23 ± 0.90c
1.4 ± 0.23b
90.663 ± 2.093e
124.9 ± 4e
7
60
10
21.57 ± 1.07af
28.86 ± 1.10d
0.4 ± 0.05b
458.69 ± 3.70f
624.736 ± 3.11f
8
60
30
15.57 ± 1.10f
30.43 ± 0.43de
1.8 ± 0.33be
375.92 ± 4.98 g
471.67 ± 2.90 g
9
130
10
20.71 ± 0.71af
34.43 ± 1.03e
2.1 ± 0.30be
290.47 ± 3.79h
546.48 ± 3.21i
10
60
50
15.42 ± 1.02f
63.29 ± 0.90 g
2.2 ± 0.60be
265.94 ± 4.02i
367.54 ± 2.10j
11
130
30
26.23 ± 1.20a
57.89 ± 1.09a
6.1 ± 0.90a
215.92 ± 3.02a
413.97 ± 4.02a
The data are presented in the form of the average of two individual repetitions (n = 2e ± SEM), the means followed by similar letters exposing in the same colum are not different (P < 0.05). TPC (mgGAE/gextract ) : TFC(mgQE/gextract) : TTC(mgQAE/gextract) : DPPH IC50 (µg/ml) : ABTS IC50 (µg/ml), X1 roasting temperature(°C) : X2 roasting time(min)
Interpretation of the response surface model of TPC
Second-order polynomial model
In this study, the TPC of extracts from opuntia ficus indica seeds varied from 15.42 ± 1.02 to 104.86 ± 1.94 mg GAE / g extract. According to the results of ANOVA for TPC (Table 3),the model was significant (p-value < 0.0001).The lack of fit was not significant (P-value = 0.0862),which showed that the model equation was adequate to predicting the value values of the response. Additionally, the R2 value was 0.990054 and the adjusted determination coefficient (Radj2 = 0. 980107), showing that the model adequately showed the true combination between all factors studied. According to Li et al (LI et al., 2019), when the determination coefficient was more than 0.75, the model is adequate. The equation Eq. 2 was represented according to a reduced regression model, it can predicate to the effects of factor variables on the content of TPC.
Anova data of the regression coefficient and the terms of the model
Source
Coef
Sum of square
Degree of freedom
Mean square
F-value
p-value
TPC
Model
7047.1123
5
1409.42
99.5379
< 0.0001*
Constant
24.093684
< 0.0001*
X1
26.36
4169 .0976
1
4169 .0976
294.4350
< 0.0001*
X2
12.308333
908.9704
1
908.9704
64.1944
0.0005*
X1 *X2
16.2525
1056.5750
1
1056.5750
74.6187
0.0003*
X1 *X1
14.445789
528.6581
1
528.6581
37.3355
0.0017*
X2 *X2
8.0107895
162.5710
1
162.5710
11.4813
0.0195*
Residual
70.7983
5
14.16
Lack of fit
66.669210
3
22.2231
10.7642
0.0862
Pure Error
4.129067
2
2.0645
Total Error
70.798277
5
R2
0.990054
Radj2
0.980107
* Significant at p-value < 0.05
X1 had a significant positive linear effect (p-value < 0.0001), as well as, it’s the quadratic X1* X1 had a significant positive effect (p-value < 0.05) on TPC. Moreover, the linear effect of the roasting time X2 and its quadratics effects X2* X2 were shown to have a significant positive effect respectively (p-value < 0.05).Furthermore, the interaction effect between the two parameters studied X1* X2 had significant (p-value < 0.05) on TPC.
Response Surface Methodology (RSM) analysis
The effects of both the roasting temperature and the roasting time and their reciprocal interactions on TPC can be visualized on the generating 3D response surface plots shown in Fig. 1. According to Fig. 1, the TPC content increased when X1 roasting temperature (°C) increased at a roasting time fixed, also it increased rapidly when the X2 roasting time (min)exceeds 30 min. Thus, the maximal extraction of TPC was found at the strong levels of both the roasting temperature (X1) and roasting time (X2). However, to get optimization overall of all variables studied. Optimization of the response was used by desirability function (d) in order to obtain the maximum response in TPC of the opuntia ficus indica seeds, thereby the maximum response precision is obtained when the desirability close to 1 (Figure.6) (Gullian Klanian & Terrats Preciat, 2017; Laib & Barkat, 2018; Los et al., 2019). Therefore, the optimal conditions were determined by using the JMP prediction profiler. The results regarding the optimized conditions of roasting by maceration extraction were when the desirability values (d = 0.89) close to 1 (Fig. 6.a): 200 °C, 50 min and predicted response is 101.4711 mg GAE/g extract). The experimental value was 104.86 ± 1.94 mg GAE/g extract, Therefore, the experimental and predicted responses were close. Hence, these results suggest that the model may be valid for the prevision of phenolic content by extraction maceration of the OFI seeds roasted. These results confirm the results found by several studies. Chandrasekara et al (Chandrasekara, Shahidi, & Chemistry, 2011) showed that the roasting at high temperature (130 °C) for 33 min had increased the phenolic content relative to raw seed (testa, cashew nuts).Yu et al (Yu, Ahmedna, & Goktepe, 2005) have also found that the TPC (in both water and ethanol) from peanut skin was increased about 35.9% by roasting at 175 °C for 5 min relative to the raw sample. Also, Locatelli et al (Locatelli et al., 2010) and Yin el al (Yin et al., 2019) respectively indicated that the TPC from extract soluble of hazelnut skin increased at 180 °C for 20 min more than 10 min,and the TPC increased about 3.4 times at temperature between 120 °C and 140 °C for 180 min, as well as, it increases more at 140 °C. Moreover, Kim et al (Kim et al., 2006) showed that, the TPC significantly increased (p-value < 0.05) at heat treatment. Accordingly, the increase in the content of phenolic compounds can be explained by the following causes:
During the roasting ,the molecules phenolic can be degraded/polymerized, which indicated the training of the new compounds, these compounds can be more soluble in ethanol and water, as well as, they can reagent with the Folin-Ciocalteu in alkaline middle(Yu et al., 2005).
It could be due processed by roasting, because the bound molecules bioactive can be released (Jeong et al., 2004).
Interpretation of the response surface model of TFC
Second-order polynomial model
Our results showed that, the TFC of extracts from opuntia ficus indica seeds varied from 28.86 ± 1.10 to 81.23 ± 0.90 mg QE / g extract. Moreover, ANOVA was used to verify the adequacy and the significance of the model. Table 4 showed that, the F-value is large (12. 9938) and the p-value is small (0.0069), which confirms that the model has been validated. Additionally, the lack of fit was not significant (p-value: 0. 0771) which indicates the was significant for TFC prediction of the opuntia ficus indica seeds roasted, the lack of fit cheks the inability of the model (LotfizadehDehkordi, Ghadimi, & Metselaar, 2013). The coefficients of determination R2 and of adjusted had high values R2 = 0.92854 and Radj2 = 0.85708 respectively. These values indicated that the quality of the model is valid. The equation which combines the relationship between the variables and prediction TFC was described below.
ANOVA data of the regression coefficient and the terms of the model.
Source
Coef
Sum of square
Degree of freedom
Mean square
F-value
p-value
TFC
Model
2510.9388
5
502.188
12.9938
0.0069*
Constant
52.860526
< 0.0001*
X1
10.688333
685.4428
1
685.4428
17.7354
0.0084*
X2
17.05
1744.2150
1
1744.2150
45.1306
0.0011*
X1 *X2
-0.585
1.3689
1
1.3689
0.0354
0.8581
X1 *X1
-4.361316
48.1867
1
48.1867
1.2468
0.3149
X2 *X2
4.5736842
52.9938
1
52.9938
1.3712
0.2944
Residual
193.2410
5
38.648
Lack of fit
183.17941
3
61.0598
12.1372
0.0771
Pure Error
10.06160
2
5.0308
Total Error
193.24101
5
R2
0.92854
Radj2
0.85708
* Significant at p < 0.05
Roasting time(X2) had a positive significant linear effect (p-value = 0.0011 < 0.05) on TFC, and it doesn’t have a significant quadratic effect (p-value = 0.2944).As well as, the Roasting temperature X1 had significant positive linear (p-value = 0.0084), but its quadratic effect is not significant (p-value = 0.2944). Moreover, the not significant interaction effect between the two parameters studied was observed (Table 4).
Response Surface Methodology (RSM) analysis
Figure 2 shows the response surface plot of roasting temperature and roasting time on total flavonoid content. The TFC increased with the increased both the roasting time and the roasting temperature. Accordingly, the higher TFC yield was detected in regions of high roasting temperature and hard roasting time. Consequently, the optimum extraction of TFC was at: roasting temperature 200°Cand roasting time 50 min, and it was assigned for the predicted response is 80.22623 (mg QE/g extract) with the desirability is d=0.84(Figure.6.b.). Our results are similar with various studies as, Lin et al (Lin et al., 2016) reported that the TFC increased significantly after 5min of the roasting, as well as, the flavonoid aglycones and acids are increased according to roasting temperature and time. Furthermore, Kumar et al (Kumar & Pandey, 2013) mentioned that, the fractions of sugar in flavonoids glycosides have an important role in antioxidants capacity, as well as, the aglcycones had a high effect on the antioxidant capacity more than the glycosides.
Interpretation of the response surface model of TTC
Second-order polynomial model
Table 5 shows the coefficients of regression and their significance for the TTC yield. The regression model was significant (p-value = 0.0231). Also, the determination coefficients (R2) for the TTC response variable (0.881256) and the lack-of-fit values (0.0537) were not significant (P > 0.05), which indicates that the model can explain all data. So the response variable was included in roasting optimization. Besides, the R2adjs was 0.762512,it indicated that 76.25% of the variability was estimated by the model. Therefore, the second-order polynomial model was applied (Eq. 4).
ANOVA data of the regression coefficient and the terms of the model.
Source
Coef
Sum of square
Degree of freedom
Mean square
F-value
p-value
TTC
Model
50.697863
5
10.1396
7.4215
0.0231*
Constant
5.8052632
0.0002*
X1
-0.133333
0.106667
1
0.106667
0.0781
0.7911
X2
0.75
3.375000
1
3.375000
2.4703
0.1768
X1 *X2
-0.4
0.640000
1
0.640000
0.4684
0.5241
X1 *X1
-3.463158
30.383439
1
30.383439
22.2386
0.0053*
X2 *X2
-1.513158
5.800439
1
5.800439
4.2455
0.0944
Residual
6.831228
5
1.3662
Lack of fit
6.5845614
3
2.19485
17.7961
0.0537
Pure Error
0.2466667
2
0.12333
Total Error
6.8312281
5
R2
0.881256
Radj2
0.762512
* Significant at p < 0.05
According to p-value < 0.05, the X1 * X1 is the quadratic effect of roasting temperature was positive significant for TTC, on the contrary, its linear effect did not have significant because of the p-value = 0.791. As well as, the X2 and X2 * X2 of roasting time were not had significant in TTC because, their p-value was respectively: 0.1768, 0.0944. The X1 *X2 had also not significant according to its p-value was 0.5241.
Response Surface Methodology (RSM) analysis
The 3D of response surface of regression Eq. (3) were constructed using RSM to illustrate the effects of the roasting temperature and roasting time and their interaction on the TTC (Fig. 3). Accordingly, the TTC content increased before the roasting temperature increased at 130 °C, after that it decreased quickly. Also, the TTC increased with the roasting time in the range of 10 to 35 min and then decreased.. The optimum extraction of TTC was roasting temperature 128.9 °C, roasting time 34.92 min with 5.901 (mg QAE/g extract) predicted responses and the desirability is d = 0.82(Figure.6.c.).These results are similar to these reported by Lin et al (Lin et al., 2016), they showed that, during the roasting at 200 °C for 20 min the content of condensed tannins from ethanol extracts had a high levels in TTC.
Interpretation of the response surface model of DPPH assay
Second-order polynomial model
The ANOVA results from DPPH assay content based on the RSM design are reported in Table 6.The p-value of the model was (< 0.0001),which indicated that the model was significant. Moreover, the R2 and R2adj were 0.997921 and 0.995841 respectively, that confirms the adequacy of the model because R2 > 0.75 (LI et al., 2019). Additionally, the lack of fit (p-value > 0.05) confirms also the adequacy the model for prediction of the antioxidant power for opuntia ficus indica seeds roasted. Therefore, the second-order polynomial model was applied (Eq. 5).
ANOVA data of the regression coefficient and the terms of the model.
Source
Coef
Sum of square
Degree of freedom
Mean of square
F-value
p-value
DPPH
Model
124190.70
5
24838.1
479.9081
< 0.0001*
Constant
217.23774
< 0.0001*
X1
-123.3112
91233.863
1
91233.863
1762.768
< 0.0001*
X2
-66.36283
26424.154
1
26424.154
510.5521
< 0.0001*
X1 *X2
33.42325
4468.455
1
4468.455
86.3369
0.0002*
X1 *X1
28.110658
2001.863
1
2001.863
38.6788
0.0016*
X2 *X2
-2.714342
18.665
1
18.665
0.3606
0.5743
Residual
258.78
5
51.8
Lack of fit
248.64531
3
82.8818
16.3558
0.0582
Pure Error
10.13487
2
5.0674
Total Error
258.78018
5
R2
0.997921
Radj2
0.995841
* Significant at p < 0.05
Based on statistical analyses of ANOVA for DPPH, the roasting temperature (X1) and roasting time (X2) had a negative significant linear effect on the IC50 of DPPH assay, because their P-value is equal respectively a <0.0001*and <0.0001*.As well as, their interaction had significant for DPPH because the p-value was 0.0002*.On the contrary, their quadratic effects were not had significant due to their p-value was >0.005.
Response Surface Methodology (RSM) analysis
The response surface (3D) of regression Eq. (5) were constructed using RSM to illustrate the effects of X1 and X2 and their interactionX1*X2 on the IC50 of DPPH assay (Fig. 4.). We know that the antioxidant power is inversely proportional with the value of the IC50. We observed that the increase in the antioxidant power was made thanks to the increasing of the X2 roasting time and the increasing of the roasting temperature (X1). The optimum of the antioxidant power by DPPH assay observed at roasting temperature 200 °C and roasting time 50 min with 96.60% of inhibition, which matches 86.3845 µg/ml predicted responses, and also the desirability is d = 0.93(Figure.6.d.).Our results confirm those founded by Lin et al (Lin et al., 2016), they reported that, the higher antioxidants capacity was observed at strong roasting temperature for ethanol extracts from almond(Prnus duclis)kernel, and during the roasting at 200 °C for 20 min the power for scavenging DPPH radical was strong than the raw sample. Moreover, Chandrasekra et al (Chandrasekara et al., 2011), reported that in their study, the scavenging capacity of DPPH radical increased significantly with the increase of the roasting temperature for soluble phenolic extract from testa, as well as, they justified that increase due to Maillard reaction products MRPs. Indeed, during at roasting, a reaction between the reducing sugars and amino acids can be done, this reaction can produce the new compounds, which are Maillard reaction products MRPs, these formed products can contribute to TPC, flavour, antioxidant activity and color of food (Chandrasekara et al., 2011). Furthermore, the resultant melanoidin and the intermediate Maillard reaction products (MRPs) had strong antioxidant pwer,which are according to the presence of reductone-type structures (Hayase, Hirashima, Okamoto, Kato, & Chemistry, 1989).
Interpretation of the response surface model of ABTS assay
Second-order polynomial model
Experimental modeling results for antioxidant power by ABTS assay were shown in Table 7. From the model analysis, the R2 and R2adj of the model were 0.99075, 0.9815 respectively, also did not present lack of fit (p-value = 0. 0528). Moreover, the model was significant because its p-value was < 0.0001,which showed that the model equation was acceptable to predict the antioxidant power by ABTS assay. this model equation is shown in Eq. 6 as follows:
ANOVA data of the regression coefficient and the terms of the model.
Source
Coef
Sum of square
Degree of freedom
Mean square
F-value
p-value
ABTS
Model
193571.35
5
38714.3
107.1061
< 0.0001*
Constant
415.29474
< 0.0001*
X1
-135.2122
109693.98
1
109693.98
303.4772
< 0.0001*
X2
-107.6177
69489.37
1
69489.37
192.2479
< 0.0001*
X1 *X2
23.584
2224.82
1
2224.82
6.1551
0.0558
X1 *X1
-68.64034
11935.79
1
11935.79
33.0213
0.0022*
X2 *X2
9.1731579
213.17
1
213.17
0.5898
0.4772
Residual
1807.29
5
361.5
Lack of fit
1743.0803
3
581.027
18.0991
0.0528
Pure Error
64.2050
2
31.103
Total Error
1807.2853
5
R2
0.99075
Radj2
0.9815
* Significant at p < 0.05
Roasting time (X1) and roasting temperature (X2) had a negative significant linear effect (p < 0.05). Also, the quadratic effect of the roasting temperature X1 * X1 had significant effect (p-value = 0.0022), and the interaction effect between the two parameters roasting was not significant (Table 7).
Response Surface Methodology (RSM) analysis
Figure 5 shows the IC50 of ABTS assay, we observed that the antioxidant power increase significantly when the roasting temperature X1 and roasting time X2 increased, because the IC50 decreased. According to, the more IC50 decreases the more the antioxidant power increases. The optimum of the antioxidant power by ABTS assay was at: roasting temperature 200°C and roasting time 50 min with 96.75% of inhibition, which matches 130.581 µg/ml predicted responses, and also the desirability is d=0.89 (Figure.6.e.). These results are similar to several works as Gao et al (Gao et al., 2019) mentioned that, the ABTS capacity was increased significantly during the roasting at 160°C for 10min compared to raw sample. Also Yin et al (Yin et al., 2019) reported that the ABTS scavenging increased during the heating between 130°C-140°C after 60min.Moreover, these results can depend on several conditions such as, the plants have a bound antioxidant phenol and bound polymeric compounds, during the thermal treatment these molecules can be degraded and released which leads to an increase in the antioxidants activity (Lee, Kim, Kim, Jang, & chemistry, 2002). Furthermore, after the antioxidants characteristics can be improved thanks to the degradation of the heat-labile antioxidants compounds or training the new compounds by Maillard reaction (Nicoli, Anese, Parpinel, & Technology, 1999). Also, the solubility of non-phenolic molecules was improved by roasting (Dewanto, Wu, Adom, Liu, & chemistry, 2002).
Comparisons of predict (models) and experimental results.
The verification experiments for five responses such as antioxidants activity by DPPH IC50 (µg/ml), ABTS•+ inhibition activityIC50 (µg/ml), Total phenolic Contents (mg GAE/g extract, Total flavonoids (mg QE/g extract), and Total Tannins Content (mg QAE/g extract) were reported in Table 8. These experiments were done at the conditions of responses optimal and in the experimental range. these results showed that the values of responses experimental are close to those predicted.
Table 8: predicted and experimental results at conditions optimal
Total phenolic Contents (mg GAE/g extract)
X1 roasting temperature (°C)
X2 roasting time (min)
Predicted value
Experimental value
Total flavonoids content (mg QE/g extract)
200°C
50min
80.22623
81.23±0.90
Total Tannins Content (mg QAE/g extract)
128.9°C
34.92min
5.901
6.12±0.95
Total phenolic Contents (mg GAE/g extract )
200°C
50min
101.4711
104.86±1.94
DPPH IC50 (µg/ml)
200°C
50min
86.3845
90.663±2.093
ABTS IC50 (µg/ml)
200°C
50min
130.581
124.9±4
The data are presented in the form of the average of two individual repetitions (n = 2e ± SEM),
Correlation Matrix
Table 9 showed the correlations coefficients data between all responses studied. Moreover, Table 10 presents the p-value of these correlation coefficients. Additionally, the DPPH (1/DPPH IC50) and ABTS (1/ABTS IC50) represent the power to inhibit DPPH free radical and ABTS.+ radical respectively.
Table 9
Pearson’s correlation matrix coefficient between antioxidant capacity and antioxidants compounds in the extracts from Opuntia Ficus Indica
Variables
TPC
TFC
TTC
DPPH
(1/DPPH IC50 )
ABTS
(1/ABTS IC50 )
TPC
1
TFC
0.652
1
TTC
-0.301
0.287
1
DPPH
(1/DPPH IC50)
0.949
0.784
-0.121
1
ABTS
(1/ABTS IC50)
0.966
0.727
-0.255
0.920
1
The values is bold are different from 0 at a significance level alpha = 0.05.TPC (Total Phenolic Content), TTC :Total Condensed Tannins Content, TFC : Total Flavonoïdes Content, DPPH(1/DPPH IC50 ): 1,1-diphenyl-2-picrylhydrazyl radical scavenging activity;ABTS(1/ABTS IC50)
Table 10
p-values of the correlation matrix coefficient between all variables
Variables
TPC
TFC
TTC
DPPH
(1/DPPH IC50 )
ABTS
(1/ABTS IC50 )
TPC
0
TFC
0.030
0
TTC
0.369
0.392
0
DPPH
(1/DPPH IC50)
< 0.0001
0.004
0.723
0
ABTS
(1/ABTS IC50)
< 0.0001
0.011
0.449
< 0.0001
0
The values is bold are different from 0 at a significance level alpha = 0.05.
According to Table 9 and Table 10, we observed that, the TPC had high positive correlations significant (p-value < 0.05) between the antioxidants power. The correlation coefficients of TPC were 0.949 and 0.966 with free radical scavenging effect DPPH and ABTS.+ respectively. These positive correlations are justified that the antioxidants capacity depends on the presence of phenolic compounds in opuntia ficus indica seeds extracts,these results are similar with those reported by several study (Amri et al., 2015; Cheniany et al., 2013; Guettaf, Abidli, Kariche, Bellebcir, & Bouriche, 2016). It found that, the TFC had also the positive correlations significant between DPPH (1/DPPH IC50) and ABTS (1/ABTS IC50) , these correlation coefficients were 0.784 and 0.727 respectively. Therefore, these results are confirmed by the strong positive correlation significant (p-value < 0.05) between TFC and TFC (r2 = 0.652). We observed that, the p-values of TTC with the antioxidants power were not significant (p-value > 0.05), which indicates that Tannin contribute slightly in this bioactivity. Furthermore, the strong positive correlation significant between tow antioxidant capacity (r2 = 0.920),indicates that the same bioactive molecules in our extracts are responsible to the scavenging power of two free radicals DPPH and ABTS.+ ..
Principal Component Analysis (PCA).
According to Fig. 8, the projections of the responses studied and the experiment assays (extracts) were done by the factorial plan reported in Fig. 8.The cumulative percentage was 95.14%, which indicates that it was is representative of the variables because it was more the 50%. Moreover, the two axe are suitable for explains the all information, with the frits (F1) and second (F2) main components have explained 70.63% and 24.51 the information respectively. The correlations between all variables studied were explained by a plan formed by F1 and F2 axes. Besides, the F1 axe was formed by the positive correlation between TPC,TFC,ABTS(1/IC50),DPPH(1/IC50)),on the contrary the F2 axe was constructed by TTC (Fig. 7).Ours 11 extracts studied from opuntia ficus indica seeds, were distributed in three groups according the responses (Fig. 8).
Group I:this group was formed by four extracts(2,3,5,6) ,these extracts had a strong values of the TPC and TFC, as well as, they had also a high power antioxidants by DPPH and ABTS assays.
Group II: it contains four extracts (1, 4, 10, and 11), these extracts are characterized by a strong value of TTC, and by lower values of TPC and TTC. Therefore, their antioxidants activity is lower compared to group I.
Group III is formed by a three extract (7, 8 and 9), these extracts are characterized by the low values of TPC and TFC, and its antioxidant activity is low compared to extracts of the other groups.
The extracts from Group I are characterized by a high roasting temperature varies between 130 °C and 200 °C, and a high time of roasting (50 min) for the extracts roasted at 130 °C, which shows that their a strong antioxidants capacity more than the extracts from the Group II and III obtained by low roasting temperature. Therefore, the roasting makes it possible to increases the extraction of bioactive compounds responsible for antioxidants power.
Dry thermal processing of seeds from the Opuntia ficus indica increased the amounts of active compounds. As well as, antioxidant activity power was significantly improved in extracts roasted especially at stronger temperature. Furthermore, the results indicated that the temperature and time of roasting had significant effects.PCA showed that on one hand the positive correlation between the photochemical compounds (polyphenol, flavonoids) and the antioxidant capacity (ABTS, DPPH),Consequently, this study showed thermal processing can be used as a pre-treatment to increase the antioxidants capacity of Opuntia ficus Indica seeds.
CDD : Central Composite Design; X1: roasting temperature; X2 : roasting time(min); TPC : Total Phenolic Content; TFC: Total Flavonoids Content; TTC : Total Condensed Tannins Content; PCA: Principal Component Analysis; MRP: Maillard Reaction Products; RMS: Response Surface Methodology; DPPH: 2,2-diphenyl-1-pycridazil;ABTS: 2,2’-azino-bis(3-ethylbenzthiazoline–6-sulphonic acid; IC50: half-maximal inhibitory concentration; ANOVA: Analysis of Variance; Eq: equation; R2 : coefficient of determination; R2adj: Coefficient of Adjustment; d: desirability function; r2 : coefficient of correlation; F1:Frist main component; F2 :Second main component; GI: Group I; GII: Group II; GIIi : Group III.
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Availability of data and materials
Not applicable
Competing interests
The authors declare that they have no competing interests.
Funding
Not applicable
Authors’ contributions
C-EG, H-H, A-Z, and M-T conceived and designed the experiments. C-EG and H-EM have carried out experiments. All authors discussed the results and co-wrote the manuscript. All authors read and approved the final paper.
Acknowledgement
The authors would thank Dr I. Nounah for helpful discussion along the realization of this work.
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