3.2. Setting Ranges for Model Parameters
Previous tests were carried out in order to select the Box–Behnken factor ranges. According to literature [37
], HCl was not taken into account because compared to H2
a low yield of hydrolysis was obtained. Thus, higher amounts of HCl and/or higher time of treatment would be required in order to obtain results similar to those with the used acids in order to hydrolyze the complex carbohydrates as fiber. In fact, as reported by Khawla and co-workers [38
], that compared the yield of reducing sugars after an acid hydrolysis using HCl and H2
(both at a concentration of 5% and at 90 °C), the highest amounts were obtained using sulfuric acid and in lees time (90 vs. 120 min). On the other hand, the final application of the hydrolysate is to be the culture medium of microalgae and they need phosphorus (around 3% of the total weight of the culture medium) and sulfur (around 1% of the total weight of the culture medium), that could proceed as residues of the chemical hydrolysis pretreatment; contrary, their need chlorine is only in trace, thus additional processes should be applied to eliminate the chlorine [5
]. Based on a study on potato peel [38
], 1.8 N sulfuric acid, with a ratio of 15, 120 min at 90 °C was used to hydrolyze starch and cellulose standard compounds. The results obtained were not entirely satisfactory because 94.54% of starch and 0% of cellulose were hydrolyzed. These first assays confirmed that starch can be hydrolyzed by this H2
1.8 N, however, cellulose remains intact. Therefore, according to Englyst and co-workers [40
] that hydrolyzed the chemical fiber, a 12 N sulfuric acid solution was used to evaluate the cellulose hydrolysis. The result obtained showed that 28.94% of cellulose can be hydrolyzed. Thus, a range between 2 and 12 N of H2
was adopted for the Box–Behnken model design. A similar work was carried out for H3
and a range of concentration from 6 to 36 N of H3
To evaluate the influence of static and dynamic hydrolysis, chemical hydrolysis was tested in test tubes with a screw cap in a static oven system at 90 °C for 150 min and in 250 mL Erlenmeyer flasks capped and covered with aluminum foil was tested in a thermostatic bath at 90 °C for 120 min and 100 min−1 revolutions of shaking. The dynamic hydrolysis reported highest amount of reducing sugars than static hydrolysis carried out in tube.
Subsequently, different ratios samples/acid solutions were tested, allowing adequate agitation and an optimum surface of reaction for hydrolysis. In fact, one of the problems that arises is that the tiger nut byproduct has a low weight/volume ratio, which, although the ratio conditions proposed by other studies used in other byproducts were imitated, were not satisfactory. The lowest ratio to reach a satisfactory hydrolysis was ratio 30. Therefore, the creation of the prediction model was proposed as a low limit of a ratio 30 and the high one 60.
The maximum temperature was set at 90 °C because higher temperatures provide unreproducible data due to the fast evaporation of the water in the thermostatic and consequently to a dishomogeneus distribution of the temperature. The lower limit of the established model was 40 °C.
Finally, according to previous experiments, the upper time limit for the model was established at 150 min.
3.3. Model Fit of Sulfuric and Phosphoric Acid Hydrolyzes
The Box–Behnken model, coupled to response surface methodology, was used to optimize the hydrolysis to obtain reducing sugars and determine the combined effect of acid concentration (X1
), temperature (X2
), time (X3
) and acid/sample ratio (X4
). The experimental conditions of the model and the respective responses obtained after acid hydrolyzes developed are presented in Table 2
and Table 3
. The observed values for the sulfuric acid ranged between 0.54 and 37.62 g of sugars per 100 g of dry tiger nut byproduct, which corresponded to the following extraction conditions: H2
2 N, 40 °C, 105 min and 45 ratio and H2
7 N, 90 °C, 105 min and 60 ratio, respectively.
The values obtained for the phosphoric acid ranged between 0.38 and 38.34 g of sugar per 100 g of dry tiger nut byproduct with the extraction conditions: H3PO4 36 N, 40 °C, 105 min and 45 ratio and H3PO4 21 N, 90 °C, 150 min and 45 ratio, respectively. The hydrolysis conditions obtained for phosphoric acid are harshest than those reported for sulfuric acid due to the low acidity of phosphoric acid compared to sulfuric.
The experimental data were analyzed by RSM using the least squares method (LSM), a regression model that provides the lowest residual value and was adjusted to a second order polynomial equation (Equation (1)) using for this, the regression coefficients listed in Table 4
for the model with sulfuric acid and Table 5
for the model with phosphoric acid.
Only few significant terms were noticed when the model was analyzed with a significance level (α) of 0.05; because of that, according to Diaz de Cerio and co-workers [41
] level of significance was increased to (α) 0.1. According the p
-value, both models showed significant effects for the individual linear factors of concentration of acid (β1
), temperature (β2
) and ratio (β4
Concerning crossed interactions, the (β12
) was significant for both models; moreover, β24
showed significant interaction in phosphoric acid model. Furthermore, quadratic of acid concentration and temperature (β11
) were also found in both models. Finally, the quadratic of time (β33
) was reported only in sulfuric acid model. Time (β3
), the rest of interactions and any quadratic product did not have effect with the meanings chosen. The predicted models were recalculated only with significant terms and tested by ANOVA after discarding non-significant terms at p
< 0.1 (Table 6
and Table 7
As can be seen, the present models revealed a high correlation between the factors and the response variable (R2 = 0.9929 and 0.9822 for sulfuric and phosphoric model, respectively) in both models. The validity of the models is statistically accepted due to its p value < 0.05 and a non-significant lack of fit.
3.4. Optimization of Reducing Sugar Extraction Conditions
Taking into account the validity of the predicted models, the optimization of the conditions for the obtention of reducing sugars (RS) was performed. Three-dimensional response surfaces of independent factors were plotted in order to be studied and to obtain the optimal conditions to maximize the value of reducing sugars. This is an essential step because the critical values for the model were not provided by the software. Therefore, to maximize the response, a compromise was established between the minimum possible values of each independent factor.
shows the surface responses obtained for the sulfuric acid model. Figure 1
a represents the combined effect between H2
) and the bath temperature (X2
), which shows that the RS decrease when the H2
concentration increases, while increasing the temperature at low H2
concentration achieves an increase in RS. In addition, the positive influence of the quadratic term of X1
and the negative interaction between X1
produces a maximum range at temperatures in the range 80–90 °C and H2
concentration below 4 N.
According to the study of response surfaces for the concentration of H2
) (Figure 1
c) and the concentration of H2
) (Figure 1
b), the same conclusion could be reached since it is seen that both the time as the ratio seems to have no effect according to the shapes of the graphs. This is confirmed by the low effect shown in Table 4
of the terms X3
compared to the values obtained for X1
, since some of them were not significant. Thus, in these cases a high RS recovery was achieved with shorter times and higher ratios.
With respect to the combined effect of bath temperature (X2
) with time (X3
) (Figure 1
e) and ratio (X4
) (Figure 1
d), it was observed that, on the one hand, higher amounts of RS could be obtained in the highest values of X2
as a result of the positive influence of the regression coefficient (Table 4
) and on the other hand, in the lowest values of X3
, since the interaction effects are negative. As a consequence, higher RS values are obtained at the level lower than X3
and the highest for X4
, concluding that time must be kept to a minimum in order to make the process as fast as possible.
These observations made it possible to adjust the best conditions as follows: Concentration of H2SO4 2 N, 85 °C, 60 min and 60 mL/g ratio.
reports all the combined effects between factors in the model of phosphoric acid. First of all is shown the combined effect between H3
) and the bath temperature (X2
) (Figure 2
a), which have major effect according with Table 4
. As shown in the Figure 2
a,c,e the highest values of RS are at the highest temperature, which is corroborated by the graphics ratio (X4
) (Figure 2
c) and time (X3
) (Figure 2
e). Following the temperature, the second factor with major influence is H3
) and the graphs show clearly that the highest amounts of RS are obtained with intermediate values, because the highest and lowest show negative effect (Table 5
). In third term ratio has shown a subtle influence (Table 5
) as shown in graphs ratio (X4
) (Figure 2
c) and ratio (X4
) (Figure 2
b); it can be deduced that with higher ratios higher amount of RS was obtained. Finally, time has not shown significant effect (Table 5
); moreover, studying the graphs 2d and 2e, reducing sugars yield is totally independent from the time of treatment, because of that, trying to develop a fast process, the time must be kept to a minimum.
Concluding, the optimal conditions are: H3PO4 21 N, 90 °C, 60 min and 60 mL/g ratio.
However, in the case of phosphoric acid hydrolysis it is important to underline that the maximum RS production was reached at the maximum temperature of the model; probably higher temperatures are needed to improve the carbohydrates hydrolysis. However, they could be reached only using a more expensive process such as the autoclave reactor.
3.5. Confirmation of Optimal Conditions
The predicted models were verified using the predicted conditions (Table 8
In the first model (made with sulfuric acid), the value obtained with the optimal conditions were 45.39 ± 0.41 of sugar per 100 g. This value did not report significant differences (p < 0.05) compared to the predicted value.
In the second model (made with phosphoric acid), the values of sugar shown with the optimal conditions were 41.1 ± 0.5 g/100 g of dry tiger nut byproduct; neither this value reported significant differences (p < 0.05) compared to the predicted value.
Hydrolysis optimum conditions were also carried out on n-PDO tiger nut byproducts; the total reducing sugar content was 41.45 ± 0.47 and 39.06 ± 0.71 g/100 g of dry tiger nut byproduct for sulfuric and phosphoric model, respectively.
Comparing to the raw byproducts, the hydrolysis with sulfuric acid increased 60 times the reducing sugar in PDO tiger nut byproduct and 20 times in the case of n-PDO tiger nut byproduct. On the other hand, the optimized conditions of hydrolysis with phosphoric acid allowed significant lower reducing sugar content (p < 0.05) than sulfuric acid model. This is probably due to the low acid power of phosphoric acid compared with sulfuric acid.