3.2. Optimization of Tween-80-Assisted Potassium Hydroxide Pretreatment of Corn Cob
In this work, sugar production from CC was used as a response for the optimization, as the objective of the optimization was to improve the utilization efficiency of the substrates and enhance the sugar yields. In fact, the level of sugar production was also used as a response for the pretreatment optimization of corn stalk [
31] and corn cob [
32]. The results in
Table 1 show that the sugar yields could be influenced significantly by the potassium hydroxide concentration, temperature and time during the pretreatment. Similar results were observed during the pretreatment of deoiled
Jatropha curcas seeds [
33] and switchgrass [
34]. Furthermore, the sugar yields from corn cob [
35] and sugarcane bagasse [
36] can be influenced significantly by the time and temperature during pretreatment. The sugar yields were positively influenced by the potassium hydroxide concentration in this work, as the level of delignification could be enhanced by a high concentration of potassium hydroxide. Similar results have also been observed during the pretreatment of wheat straw [
4] and kallar grass and cotton stalks [
37]. The level of delignification could also be enhanced by increasing the temperature, as the bonds between the lignin and carbohydrate could be disrupted more effectively at higher temperatures, and the reaction rate constant could also be enhanced at relatively high temperatures [
38]. The solid dose amount during the pretreatment was related to the heat and mass transfer efficiency and the adjustment of the chemical concentration [
4]. In this research, the sugar yields were positively influenced by the solid dose amount, as a lower level could trigger relatively higher levels of potassium hydroxide and higher levels of holocellulose degradation. In addition, the sugar yields could be positively influenced by the amount of Tween 80, which was perhaps related to the higher level of delignification caused by higher Tween 80 concentrations. Similar results were also observed in the delignification of corn cob [
26] and bamboo [
39] with the addition of Tween 80. Based on the above results, 3.0 g·L
−1 Tween 80 and a solid dose of 200 g·L
−1 were adopted in the next experimental steps.
The results shown in
Table S8 indicate that the level of sugar production reached the maximum while adopting a concentration of 48 g·L
−1 of potassium hydroxide, a temperature of 80 °C and a pretreatment time of 50 min. However, too severe pretreatment conditions after the plateau were not beneficial to the level of sugar production. As shown in
Table 2, the level of sugar production could be influenced significantly by the primary terms (
x1,
x2 and
x3) and secondary terms (
x12,
x22, and
x32). The level of glucose production was influenced insignificantly by all the interaction terms (
x1x2,
x1x3 and
x2x3). The level of xylose production was influenced insignificantly by the interaction of
x1 and
x2 and that of
x2 and
x3, whereas it was influenced significantly by the interaction of
x1 and
x3. For the model for predicting the level of glucose production, the
p values of the lack of fit (0.118) and model (0.000) along with an
R2 value of 99.6% and an adjusted
R2 value of 98.8%showed the high accuracy of the model. For the model predicting the level of xylose production, the
p values of the lack of fit (0.120) and model (0.000), along with the
R2 value of 99.6% and the adjusted
R2 value of 98.8% showed that the model could also predict the optimal levels of the variables and response.
The effects of the interaction terms on the level of sugar production are shown in contour plots in
Figure 2. As shown in
Figure 2a,b, the optimal potassium hydroxide concentration for sugar production ranged from 44 g·L
−1 to 48 g·L
−1. The suitable temperature range for glucose production was from 78 °C to 81 °C, and that for xylose production was from 75 °C to 78 °C. Based on
Figure 2c,d, the suitable potassium hydroxide concentration range for sugar production was 44 g·L
−1–48 g·L
−1. The suitable time range for glucose production was from 50 min to 52.5 min, and that for xylose production was from 47.5 min to 50 min.
Figure 2e,f indicate that the optimal temperature region for glucose production was 78 °C–81 °C, and that for xylose production was from 75 °C to 78 °C. The optimal time range for glucose production was from 50 min to 52.5 min, and that for xylose production was from 47.5 min to 50 min.
After the canonical analysis, the optimal pretreatment conditions for attaining the maximal glucose yield (230.89 mg·g
ds−1) were as follows: potassium hydroxide concentration, 46.4 g·L
−1 (
x1 = 0.13424); temperature, 78.2 °C (
x2 = −0.17903) and time, 51.2 min (
x3 = 0.14878). The optimal pretreatment conditions for attaining the maximal xylose yield (125.89 mg·g
ds−1) were as follows: potassium hydroxide concentration, 45.7 g·L
−1 (
x1 = −0.18947); temperature, 77.3 °C (
x2 = −0.27117) and time, 47.9 min (
x3 = −0.26113). The corresponding models for the optimization were as follows:
where
Y1 is the glucose yield,
Y2 is the xylose yield,
x1 is the potassium hydroxide concentration,
x2 is the temperature and
x3 is the time.
After modification, the optimal conditions were set as follows: potassium hydroxide concentration, 46 g·L
−1; temperature, 78 °C; time, 50 min; Tween 80 concentration, 3.0 g·L
−1 and solid dose, 200 g·L
−1. The average yields of glucose and xylose from three replicates were 230.36 mg·g
ds−1 and 124.30 mg·g
ds−1, respectively, which were similar to the predicted values (230.89 mg·g
ds−1 and 125.89 mg·g
ds−1) of the models. To investigate the changes in the contents of cellulosic components and lignin before and after the pretreatment, raw CC (20.0 g) was pretreated under the optimal conditions, and 14.65 g of CC was obtained. The results showed that cellulose content of 35.98% and 48.03%, hemicellulose contents of 40.15% and 37.25% and lignin contents of 14.98% and 2.11% for the raw CC and the pretreated CC were obtained, respectively. After the calculation, the SDR, CER, HCER and LGR values were 73.25%, 97.8%, 68.0% and 89.7%, respectively. Comparisons of related results from different studies are illustrated in
Table 3. The levels of lignin reduction (89.7%) and cellulose recovery (97.8%) in this work were the highest among the studies shown in
Table 3, which made it possible to enhance the glucose yield from the CC. However, the hemicellulose recovery value of 68.0% obtained in this research was less than 81.47% [
38] and 81.1% [
40]. The relatively low hemicellulose recovery obtained in this work was related to the higher level of delignification during the pretreatment. However, the hemicellulose recovery value of 68.0% obtained in this work was also higher than the previously reported values of 47.77% [
41], 9.9% [
42] and 61.3% [
43].
As shown in
Table 3, compared with other reports, the relatively higher solid dose of 200 g·L
−1 used in this work indicated that the optimal conditions in this research could pretreat more CC at once, enhancing the utilization efficiency of vessels. Among the different reports, the temperature and time ranged from 50 °C to 170 °C and from 50 min to 360 min, respectively. The relatively short time (50 min) used during the pretreatment in this research could lead to an enhancement in the pretreatment efficiency. Although the temperature (50 °C) [
38,
43] was below 78 °C in this research, the 360 min of time used in the two previous reports indicate a lower pretreatment efficiency. Compared with the temperatures of 170 °C [
40], 121 °C [
41] and 80 °C [
42,
44], the temperature of 78 °C used in this research could lead to a reduction in the energy expenditure of the pretreatment.
3.4. Optimization of Enzymatic Hydrolysis of Corn Cob
As shown in
Table 4, the sugar yields were influenced significantly by the biomass loading, enzyme loading and reaction time. In some previous reports, sugar yields from sweet sorghum bagasse [
13] and rice straw [
51] were also influenced significantly by these three factors. In addition, the sugar yields could be enhanced by relatively high levels of these three factors in this work. An insufficiently low biomass loading could reduce the pretreatment efficiency, and an excessively high a biomass loading could influence the stirring and result in enzymatic feedback inhibition. Enzyme loading was also related to the enzymolysis input costs and enzymolysis efficiency. An insufficient enzyme loading was not enough to produce sugar on a large scale. However, an excess level could result in instability of the fluid kinetics and an unsuitable suspension of slurry, which could influence the sugar yields. The reaction time was also related to the efficiency and input costs for enzymolysis. It is noteworthy that the sugar yield efficiency could be influenced by the recrystallization of cellulose and adhesion on amorphous regions by cellulases in the later period of hydrolysis [
52].
The level of sugar production from the CC was not influenced significantly by the pH, temperature and Tween 80 concentration in this research, whereas the level of sugar production from cotton stalk was influenced significantly by the temperature and pH [
53], and the level of sugar production from pine foliage was influenced significantly by the Tween 80 concentration [
9]. The different effects of the variables on the level of sugar production were probably related to the source diversity of the enzymes and substrates.
Table S5 illustrates that the level of sugar production could be maximized under the following conditions: biomass loading, 200 g·L
−1; Tween 80 concentration, 3.0 g·L
−1; enzyme loading, 8.5 FPU·g
ds−1; pH, 4.8; temperature, 50 °C and time, 30 h.
Table 5 illustrates that the level of sugar production was influenced significantly by the primary terms (
X1,
X2 and
X3) and secondary terms (
X12,
X22 and
X32). The glucose yield was influenced insignificantly by three interaction terms (
X1X2,
X1X3 and
X2X3). The xylose yield was influenced insignificantly by two interaction terms,
X1X2 and
X2X3; however, it was significantly influenced by
X1X3. For the model of optimizing the glucose yield, the
p values of the lack of fit (0.105) and the model (0.000) along with the
R2 value of 99.4% and te adjusted
R2 value of 98.9% evidenced that the glucose yield could be predicted and optimized using the model. For the model for predicting the xylose yield, the
p values of the lack of fit (0.103) and the model (0.000) along with the
R2 value of 99.5% and the adjusted
R2 value of 99.1% also illustrated the accuracy of the model.
As shown in
Figure 4a,b, the maximal level of sugar production could be obtained when the biomass loading region was from 190 g·L
−1 to 200 g·L
−1, and the enzyme loading region was from 8.0 FPU·g
ds−1 to 10.0 FPU·g
ds−1 after 30 h of hydrolysis.
Figure 4c,d illustrate that the maximal level of sugar production could be obtained in the biomass loading region of 190 g·L
−1–200 g·L
−1 with the use of 8.5 FPU·g
ds−1. In addition, the maximal glucose yield and xylose yield could be obtained when the reaction time ranged from 30 h to 33 h and from 27 h to 30 h, respectively.
Figure 4e,f illustrate that the suitable enzyme loading range for sugar production was 8.0 FPU·g
ds−1–10.0 FPU·g
ds−1 with the use of 200 g·L
−1 biomass loading. Furthermore, the suitable range of the reaction time for the glucose yield was from 30 h to 33 h, and that for the xylose yield was from 27 h to 30 h.
After the canonical analysis, the optimal conditions for obtaining the maximal glucose yield (518.76 mg·g
ds−1) were as follows: biomass loading, 195.1 g·L
−1 (
X1 = −0.24656); enzyme loading, 8.93 FPU·g
ds−1 (
X2 = 0.14154) and reaction time, 31.7 h (
X3 = 0.28508). The optimal conditions for obtaining the maximal xylose yield (351.08 mg·g
ds−1) were as follows: biomass loading, 195.6 g·L
−1 (
X1 = −0.21828); enzyme loading, 8.9 FPU·g
ds−1 (
X2 = 0.13858) and reaction time, 29.1 h (
X3 = 0.15778). The corresponding regression models were obtained as follows:
where
Y3,
Y4,
X1,
X2 and
X3 are the glucose yield, xylose yield, biomass loading, enzyme loading and reaction time, respectively.
After adjustment, verification of the models was performed three times, where the biomass loading was 195 g·L−1, the enzyme loading was 8.9 FPU·gds−1 and the reaction time was 30.4 h. The level of glucose production was 518.48 mg·gds−1, and that of xylose production was 351.14 mg·gds−1. The experimental data were similar to the predicted data (518.76 mg·gds−1 and 351.08 mg·gds−1).
To explore the competitiveness of the results in this research, comparisons of sugar production in various studies were performed (
Table 6). This illustrated that the levels of sugar production in this study (518.48 mg·g
ds−1 351.14 mg·g
ds−1) were the highest among the values reported in
Table 6, which indicated that the method of sugar production from CC conducted in this research has established a foundation for enhancing bioethanol production. Based on the 97.2% cellulose conversion and 82.9% hemicellulose conversion, the utilization efficiency of holocellulose in the CC was more competitive.
Table 6 also illustrates that the expression levels of enzyme loading were FPU·g
ds−1 [
41,
44,
54,
55,
56,
57], CBU·g
ds−1 [
44] and EU·g
ds−1 [
58]. The levels of enzyme loading among the various studies could not be compared directly due to differences in the determination of the enzyme activities and enzyme loading expression. However, the 8.9 FPU·g
ds−1 enzyme loading in this research was less than 10.0 FPU·g
ds−1 [
41,
55], 61.27 FPU·g
ds−1 [
44], 75.15 FPU·g
ds−1 [
54] and 31.1 FPU·g
ds−1 [
56,
57], which indicated that the cellulase input costs could be reduced in this research.
As shown in
Table 6, the 200 g·L
−1 biomass loading in [
54] was the highest. However, the simultaneous adoption of 72 h and 75.15 FPU·g
ds−1 could result in a lower hydrolysis efficiency and higher cellulase input cost. Although the biomass loading (195 g·L
−1) used in this research was slightly below 200 g·L
−1, the application of a 30.4 h duration and an 8.9 FPU·g
ds−1 enzyme loading could enhance the hydrolysis efficiency and reduce the cellulase input costs. In addition, the reaction time range was 24.0 h–96.0 h among the various reports (
Table 6). Although the shorter time (24.0 h) used in [
56] was more advantageous than the 30.4 h used in this research, an insufficient biomass loading (50 g·L
−1) and excess enzyme loading (31.1 FPU·g
ds−1) were also used, which could improve the reaction vessel requirements and reduce the hydrolysis efficiency. Compared with six other previous reports [
41,
44,
54,
55,
57,
58], the 30.4 h reaction time in this work was shorter, which could improve the sugar yield efficiency. On the other hand, compared with the six reports [
41,
44,
54,
55,
56,
57], using an in-house cellulase preparation in this research could also reduce the enzyme input costs. In brief, a higher level of sugar production could be obtained by using a smaller amount of enzyme and a shorter time to hydrolyze more substrates in this research.