2.1. Lipid Profile of Oils
The three oils selected (sunflower, hempseed, and linseed) were analyzed by gas chromatography. The FA composition of each oil is shown in
Table 1.
Sunflower oil contains linoleic acid (55.3%), oleic acid (33.3%), and saturated FA (9.5%). Hempseed oil has the particularity of having a high content of PUFAs, such as 56.6% linoleic acid and 19.0% linolenic acid, and low contents of oleic acid (4.4%) and saturated FA (12.7%) [
13,
23]. Selected linseed oil is rich in linolenic acid (53.0%), oleic acid (20.6%), linoleic acid (15.5%), and saturated FA (9.5%). In a biocatalytic process, hexanal or (3
Z)-nonenal (responsible for the smell of cut grass, apples, or cucumber-like scents) are obtained from linoleic acid, while (3
Z)-hexenal or (3
Z,6
Z)-nonadienal (responsible for the odor of green leaves, grass, and melon) are obtained from linolenic acid.
The saponification value of the sunflower, hempseed, and linseed oils measured is, respectively, 195.8 mgKOH.g−1, 193.4 mgKOH.g−1, and 186.6 mgKOH.g−1. The total amount of FAs for each of the oils is therefore 3.49 mmol FAs.g−1 for sunflower oil, 3.45 mmol FAs.g−1 for hempseed oil, and 3.33 mmol FAs.g−1 for linseed oil.
2.3. Optimization of the Hydrolysis Rate Using a Central Composite Design
The optimization of the hydrolysis reaction of the selected vegetable oils by lipases was performed using an RSM. A central composite design was used to evaluate the effect of the pH (H) and the temperature (T) on the hydrolysis rate over several hours. The results obtained from 39 experimental runs carried out according to the central composite design are summarized in the
Supplementary Materials, Table S1. The hydrolysis rate varies from 1.4% to 93.7% for sunflower oil, from 0% to 100% for hempseed oil, and from 1.9% to 100% for linseed oil.
A regression analysis was performed on the experimental data. Then, a second-order polynomial equation was fitted to the measured values of the hydrolysis rate. Thus, the equations shown in
Table 2. model the relationship between the factors (pH and temperature) and the hydrolysis rate.
R
2 coefficients of the models are, respectively, for CRL, RML, and PFL 96.21%, 88.43%, and 89.83% for sunflower oil; 93.88%, 89.94%, and 91.99% for hempseed oil; and 92.90%, 91.20%, and 92.42% for linseed oil. The adjusted R
2 shown in
Table 2 indicates that more than 86.68% of the variability in the hydrolysis rate could be explained by the model. These values of R
2 reveal a satisfactory adjustment of the models to the experimental data, so these models can be used for the analysis and prediction of the hydrolysis rate.
An analysis of variance (ANOVA) was carried out to assess the significance of the fit of the response surface model for the hydrolysis rate. A
p-value <0.05 was considered to be significant. The models are shown in
Table 3.
The RSM analysis for the sunflower oil lipolysis with CRL, RML, and PFL showed a
p-value lower than 0.05 for each of the linear terms H and T and the quadratic terms H
2 and T
2, meaning both factors have a significant influence on the hydrolysis rate. The interaction term H × T is significant only with CRL action ((a) in
Table 3).
Concerning the hempseed oil lipolysis with CRL, RML, and PFL, the linear terms H and T and the quadratic terms H
2 and T
2 exhibit a significant influence on the hydrolysis rate. The interaction term H × T is only significant for the RML and PFL action ((b) in
Table 3).
Regarding the RSM analysis of linseed oil, the linear term H and the quadratic term H
2 are significant for the action of the three lipases, while the linear term T and the quadratic term T
2 have a significant influence on the hydrolysis rate with CRL and PFL action. The interaction term H × T reveals a statistically significant influence only with the RML and PFL action ((c) in
Table 3).
The effects of cross-term product factors on the rate of hydrolysis can be examined using contour plots. Only significant interactions are retained in
Figure 3. Other contour plots, in addition to three-dimensional (3D) response surface plots, are shown in the
Supplementary Data, Figures S1 and S2, respectively.
The lipase that achieves the best lipolysis seems to be CRL, with a hydrolysis rate over 90% (
Figure 3a) for sunflower oil, while hydrolysis rates over 50% and 30% are barely reached, respectively, with the action of PFL (
Figure 3c) and RML (
Figure 3b) for linseed and hempseed oils.
For sunflower and hempseed oils, high hydrolysis rates are measured when the pH is around 7 and for temperatures around 30 °C. Concerning the temperature, when the temperature is low (<25 °C), lower hydrolysis rates are measured, whereas the highest hydrolysis rates are measured between 30 and 40 °C (
Figure 3a,b). This is explained by the fact that the probability of collision between the substrate and the enzyme increases with the temperature [
27,
28]. The range of temperatures for which high rates are obtained is wider for linseed oil than for sunflower and hempseed oils, especially concerning the action of RML, where only the pH showed a significant influence on the hydrolysis reaction (
Table 3). Concerning the pH, for linseed oil, the maximum hydrolysis rates are measured when the pH is more acidic, regardless of the temperature tested (
Figure 3c). Globally, the data show that regardless of the oil or the lipase, an alkaline pH leads to low hydrolysis rates (
Figure 3). The parameter with the greatest impact on the reaction seems to be pH, which needs to be close to neutral or acidic in order to obtain a high hydrolysis rate. Interface quality is essential to obtain a high hydrolysis rate. Given the essential role of the interface, the optimum pH and the optimum temperature of the enzymes could differ over several hours and also from one oil to another [
29,
30,
31].
The RSM approach provides optimal pH and temperature values to maximize the hydrolysis rate and predicts the maximum value of the hydrolysis rate with these optimal conditions. Then, the predicted hydrolysis rate is subject to experimental validation. The results are shown in
Table 4.
For sunflower oil, the maximum hydrolysis rate is reached at 35 °C and at a pH of 7 with the action of CRL (96.4 ± 1.8%) and RML (38.4 ± 2.3%) and at 34 °C and at a pH of 5.2 with PFL action (20.2 ± 1.5%). The hydrolysis rates have a standard deviation of 0.2%, 3.7%, and 2.5%, respectively, with the predicted hydrolysis rates (
Table 4, sunflower oil).
For hempseed oil, the highest hydrolysis rates are reached at 35 °C and at a pH of 7.5 with CRL action (87.9 ± 3.6%), at 36 °C and at a pH of 7.6 with RML action (40.3 ± 3.2%), and at 35 °C and at a pH of 7.5 with PFL action (48.7 ± 1.9%). The standard deviation is 1.4%, 27.9%, and 8.4% with the predicted values, respectively (
Table 4, hempseed oil).
The lipolysis of linseed oil is maximal at 30 °C and at a pH of 6 with CRL action (93.0 ± 3.8%), at 43 °C and at a pH of 6 with the action of RML (39.0 ± 1.5%), and at 21 °C and at a pH of 5.2 with PFL action (56.1 ± 2.7%). The standard deviation is 2.7%, 7.4%, and 1.3% with the predicted values, respectively (
Table 4, linseed oil).
Under optimal conditions of pH and temperature, the best yield is obtained with CRL for the three selected oils. CRL is described as a lipase acting on all three positions of triacylglycerol, unlike the other two lipases, which would explain its ability to release more FAs over the same period. For RML and PFL, a hydrolysis rate of over 50% has rarely been described, regardless of the medium used (heterogeneous solvent-free medium or heterogeneous medium with organic solvent) [
28,
32].
Finally, our results show that CRL is the most efficient lipase on the three oils considering their hydrolysis rates. Thus, this lipase was selected for the next experiments.
2.4. Optimization of the Hydrolysis Reaction Using a Box–Behnken Design
The optimization of the hydrolysis reaction of the three different vegetable oils with the CRL is carried out using an RSM at the optimum pH and temperature previously determined. A Box–Behnken design is used to investigate the influence of the duration time (D), the enzyme load (E), and the oil/aqueous ratio of the mixture (O) on the hydrolysis rate. The results obtained from 45 experimental runs performed according to the Box-Behnken design are summarized in the
Supplementary Materials, Table S2. Hydrolysis rates ranged from 32.4% to 96% for sunflower oil, 22.6% to 100% for hempseed oil, and 47.8% to 100% for linseed oil.
A regression analysis was performed on the experimental data. The second-order polynomial equation was fitted to the measured values of the hydrolysis rate. Thus, the equations shown in
Table 5 model the relationship between the factors (duration time, enzyme load, and oil/aqueous ratio of the mixture) and the hydrolysis rate.
R
2 coefficients of the models are, respectively, 85.22%, 85.72%, and 82.36% for sunflower oil, hempseed oil, and linseed oil with CRL (
Table 5).
The adjusted R
2 shown in
Table 5 indicates that more than 76.48% of the variability in the response could be explained by the model. These values of R
2 reveal a satisfactory adjustment of the models to the experimental data, so these models can be used for the RSM analysis and the prediction of the hydrolysis rate.
An analysis of variance (ANOVA) was carried out to assess the significance of the fit of the response surface model for the hydrolysis rate. A
p-value <0.05 is considered to be significant. The models are shown in
Table 6.
The RSM analysis shows that, for sunflower oil, linear terms D and E, quadratic terms D
2 and E
2, and the interaction term D × E are significant ((a) in
Table 6). For hempseed oil, linear terms D and E, quadratic terms D
2 and E
2, and the interaction terms D × E and D × O show a significant influence on the hydrolysis rate ((b) in
Table 6). For linseed oil, linear terms D, E, and O and the quadratic term O
2 are statistically significant ((c) in
Table 6).
The effects of cross-term product factors on the rate of hydrolysis can be examined using three-dimensional (3D) response surface plots by maintaining a variable at its middle value. Only significant interactions are retained (
Figure 4). The other 3D response surface plots are shown in the
Supplementary Data, Figure S3.
On each plot, the third factor is maintained at its middle level. The holding values are 5 h for the duration reaction, 1900 U for the enzyme load, and 35% for the oil/aqueous ratio of the mixture.
Concerning the interaction term D × E, for a duration of 2 h, the larger the amount of enzyme, the higher the hydrolysis rate increases, rising from 40% with 1000 U of enzyme to over 80% with 3000 U, regardless of the oil selected (
Figure 4I). For sunflower oil, a decrease of the hydrolysis rate can be observed after 4 h, regardless of the enzyme load. Although less pronounced, this decrease is still present for hempseed oil at a duration of 8 h for a high enzyme load (>2000 U). During the hydrolysis process, NaOH is continuously added to the medium, which could lead to the formation of soap when hydrolysis times are long. In this case, when FAs are saponified, they will not be quantified by the FTIR method, which would explain the lower hydrolysis rates measured.
The only variable between the two reactions being the lipid substrate, this would suggest that saponified FAs are formed more rapidly during the hydrolysis of sunflower oil than during the hydrolysis of hempseed oil. Indeed, sunflower oil contains high levels of PUFAs (over 55% linoleic acid) and also contains a high amount of monounsaturated and saturated FAs (around 43%), while hempseed oil contains more PUFAs (75%) and only 17% monounsaturated and saturated FAs (
Table 1). Thus, the fatty acid composition would influence soap formation in the medium.
Concerning the interaction term D × O for hempseed oil, increasing the duration maximizes the hydrolysis rate, while the influence of the oil/aqueous ratio of the mixture remains low (
Figure 4II). Indeed, the data previously show that D had a significant influence on the reaction, unlike O (
Table 6).
The RSM approach provides optimal values of factors (duration reaction, enzyme load, and oil/aqueous ratio of the mixture) to optimize the reaction while maintaining a high hydrolysis rate. By maintaining a high hydrolysis rate, this optimization consisted of maximizing the amount of oil hydrolyzed in a single reaction while minimizing the reaction time and the amount of enzyme load. The RSM predicts the hydrolysis rates that could be reached in these optimal conditions. The predicted hydrolysis rate is then subject to experimental validation. The results are shown in
Table 7.
For sunflower oil, a hydrolysis rate of 96.0 ± 1.7% is measured, i.e., with 1798 U of CRL at a pH of 7 and 35 °C over 4 h, 19.6 g of oil is hydrolyzed. The standard deviation is 0.2% with the predicted hydrolysis rate. This optimization allows 1.9-fold more oil to be hydrolyzed with 1.2-fold more enzyme over 4 h while maintaining a hydrolysis rate of 96% (
Table 7, sunflower oil).
For hempseed oil, the maximum hydrolysis rate measured is 97.2 ± 3.8%, and the standard deviation with the predicted hydrolysis rate is 0.4%. With 2592 U of enzyme, 21.04 g of hempseed oil can be hydrolyzed in 4.5 h, which represents 2.1-fold more oil hydrolyzed with 1.9-fold more enzyme over 4.5 h compared with non-optimized reaction conditions (
Table 7, hempseed oil).
Finally, a hydrolysis rate of linseed oil of 91.8 ± 3.2%% is found when the reaction is carried out under optimized conditions, i.e., in 4.5 h, with 1431 U of enzyme and an oil/water ratio of 38%, representing 15.34 g of oil hydrolyzed in one reaction. Under these conditions, 1.5-fold more oil can be hydrolyzed with 1.02-fold more enzyme over a period of 4.5 h, maintaining a high hydrolysis rate (91.8%). The standard deviation is 5.5% with the predicted hydrolysis rates (
Table 7, linseed oil).