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.
TPC = 24.093684 + 26.36X1 + 12.308333X2 + 16.2525X1*X2 + 14.445789X1*X1 + 8.0107895X2*X2 (Eq. 2)
Table 3
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.
TFC = 52.860526 + 10.688333X1 + 17.05X2-0.585X1*X2-4.361316X1*X1 + 4.5736842X2*X2(Eq. 3)
Table 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 |
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).
TTC = 5.8052632-0.133333X10,75X2-0,4X1*X2-3.463158X1*X1-1.513158X2*X2(Eq. 4)
Table 5
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).
DPPH (IC50) = 217.23774-123.3112X1-66.36283X2+33.42325X1*X2 + 28.110658X1*X1-2.714342 X2*X2 (Eq. 5)
Table 6
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:
ABTS (IC50) =415.29474-135,2122X1-107.6177X2+23.584X1*X2-68.64034X1*X1+9.1731579X2*X2(Eq 6)
Table 7
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.