Factors and their levels for Box-Behnken design.
Abstract
This chapter investigates the effect of some selected nitrogen sources (corn steep liquor—CSL, yeast extract, and beef extract) on the bioproduction of a selected flavor—acetoin (AC) from glucose—with a view to optimize its production. The results revealed that by using a cheap nitrogen source, corn steep liquor, the yield of acetoin is similar to those of the extracts of yeast and beef. Furthermore, it was shown that by using the Box-Behnken design, the optimum parameters such as glucose concentration, corn steep liquor, and inoculum size to maximize the concentration of acetoin produced are 78.40 g/L, 15% w/v, and 2.70% v/v, respectively. The validated concentration of acetoin produced in a triplicate analysis, 10.70 g/L, was 0.06% less than the predicted value. The results of this study may encourage the development of cost-effective nutritional use of corn steep liquor for bioproduction of acetoin on an industrial scale.
Keywords
- acetoin
- bioproduction
- corn steep liquor
- statistical optimization
- Box-Behnken design
- response surface methodology
1. Introduction
The increasing trend in the consumption of healthy food and the growing demand of natural products by consumers coupled with the price margin between the synthetic and natural flavors have motivated the bioconversion of natural flavors like vanillin, acetoin (AC), etc. that is cost-effective and commercialized. Likewise, the new sustainable development goals of the united nation, goal 3 and 12 stated the need for the good health and well-being of the consumer and to ensure the sustainable production and consumption patterns of food product. Acetoin (3-hydroxy-2-butanone or acetylmethylcarbinol) is widely used in the food industry as a flavor enhancer, giving a buttery taste [1]. It can also be used as a building block for various chemicals such as alkyl pyrazines, diacetyl, and acetyl butanediol [1, 2]. Currently, most of the commercial acetoin is produced by chemical synthesis from 2,3-butanedione and 2,3-butanediol. However, the use of such chemically derived acetoin is restricted to food and cosmetic industries because of safety concerns [3]. The production of acetoin by microbial fermentation has been reported to gain increasing interest due to its safety and environmental friendliness [3, 4]. Intensive efforts have been taken to enhance microbial production of acetoin, including screening of high-yield acetoin-producing strains [5, 6], metabolic engineering breeding [7, 8, 9], and fermentation optimization [9, 10, 11]. The price of chemically generated acetoin (racemic) is over $ 16.2/kg, and biologically generated dietary acetoin can be two times more expensive [12]. One of the chemicals that can use acetoin as a building block is 1,3-butadiene (BD), which has a worldwide market of 11 Mt./year [13]. However, acetoin is only a minor by-product of 2,3-butanediol production, and its accumulation usually needs complex and expensive growth factors. Apart from carbon, which acts as feedstock for most fermentations, nitrogen is another significant nutrition compositional element needed for the active microbial growth for the fermentation of most targeted bioactive compounds [14].
Studies have shown the potential of low-cost media and complex nitrogen sources like urea, peptone, yeast extract, beef extract, soya bean [14, 15, 16] for acetoin production but yet to ascertain effectively the optimized condition. Nitrogen source is one of the main contributors in the total material cost of commercial acetoin production. Hence, replacing a costly nitrogen source with less expensive ones for acetoin production may improve the economics of the process. Corn steep liquor (CSL) has been identified as a potential nitrogen source in biochemical industries and a good substitute for other expensive complex media. It is a major by-product found during cornstarch processing. it is a low-cost source of proteins (Figure 1), amino acids, minerals, vitamins, and trace elements and can be used as a rich and effective nutritional substitute for expensive complex media like yeast extract, beef extract, and peptone in fermentations [17, 18, 19, 20].
Studies have shown that CSL can be used as a nutrition supplement and a cheap nitrogen source for cellular growth in the production of some fermentation products [18, 20, 21]. Yang et al. [15] reported that when a high concentration of CSL was used in acetoin production, cell growth improved with a 3.69-fold increase in acetoin and an improved acetoin productivity [15]. Another author reported that a lower concentration of corn steep liquor had negative effects in the screening of medium components for acetoin production using a newly isolated
2. Materials and methods
2.1. Microorganism and inoculum preparation
2.2. Medium composition for acetoin production
The fermentation medium used for this work was the significant optimized medium of Xiao et al. [16], which was then modified. The nutrients used comprised the following (g/L): glucose 150, K2HP04 0.5 g, CH3COONa 0.5 g, NaCl 5 g, and MgSO4.7H2O 0.5 g, while 1 g/L of three different nitrogen sources were used in the preliminary experiment (corn steep liquor, yeast extract, and beef extract). The medium was adjusted to pH 7.0 and autoclaved at 121°C for 15 min. The flasks were incubated at 37°C with an orbital shaker at 150 rpm for 7 days.
2.3. Batch fermentation study
The preliminary experimental study of acetoin production was performed with 50 mL of glucose solution (100 g/L) measured into 250-mL Duran flask, and the growth effect of three complex nitrogen sources (yeast extract, beef extract, and corn steep liquor) were tested for acetoin fermentation nutrients. The pH of the medium was adjusted with 120 g/L of NaOH and 36.5 g/L of HCl buffer solutions. Subsequently, 5% volume fraction of inoculum size was added aseptically to the flask. The flasks were transferred into the environment-controlled incubator shaker (platform shaker, model: FSIM SP016) at 30°C and 150 rpm. Fermentation was performed for 168 h with 12-h sampling interval.
2.4. Experimental design by Box-Behnken Design
A three-level factor was employed to generate 17 experimental runs by considering the effect of glucose concentration (g/L), inoculum size (% v/v), and corn steep liquor (% w/v). The range and the levels of the independent variables investigated using the Box-Behnken experimental design (Table 1) were chosen based on variables previously reported to influence acetoin [11, 26]. The minimum, center point, and maximum levels of each variable were coded as −1, 0, and +1, respectively.
Factor | Unit | Symbols | Coded factors | ||
---|---|---|---|---|---|
0 | −1 | 1 | |||
Glucose | (g/L) | X1 | 50 | 100 | 150 |
CSL | (% w/v) | X2 | 5 | 10 | 15 |
Inoculum size | (% v/v) | X3 | 2 | 3.5 | 5 |
A second-order mathematical equation, including all interaction terms, was used to calculate the predicted response:
where Y is response variable (acetoin concentration), b0 is the intercept value, bi (i = 1, 2…k) is the first-order model coefficient, bij is the interaction effect, and bii represents the quadratic coefficients of Xi. Xi and Xj are the input variables that influence the response variable and
2.5. Statistical analysis
The observed data were subjected to multiple regression analysis using Design-Expert versions 10.0 (Stat Ease Inc., Minneapolis, USA) to obtain the coefficients of the quadratic equation. The
2.6. Analytical methods
2.6.1. Reducing sugar analysis
Reducing sugar concentration was analyzed using the dinitrosalicylic acid (DNS) method [27] and the results were expressed as glucose equivalent. To 1 mL of the supernatant, 3 mL of the DNS solution was added in the test tube and boiled for 15 min, cooled, and diluted appropriately after which the absorbance was measured at a wavelength of 540 nm using a UV–Visible Spectrometer (GBC Cintra 2020).
2.6.2. Biomass concentration determination
Dry cell weight (DCW) was obtained by centrifuging an aliquot of the sample followed by drying the cell pellet to a constant weight using an electric oven (Scientific, series 2000), in a pre-weighed centrifuge tube, at 105°C for approximately 24 h. It was later cooled in a desiccator. The biomass concentration was calculated on the basis of the volume of the fresh sample as the difference between the weight of the empty tube and the final weight of the tube plus the dried biomass after drying and cooling [28, 29].
2.6.3. Acetoin concentration determination
Acetoin was determined by the modified Voges-Proskauer (VP) reaction of Westerfield [30]. An aliquot of the sample solution was pipetted into a 25 cm3 calibrated flask. A total of 2.5 cm3 of 1-naphthol solution and 1.0 cm3 of creatine solution were added. After adjusting the mixture to volume and shaking vigorously, the solution was kept at 30°C. The color intensity of the complex was determined by measuring the absorbance after 40 min at 530 nm using a UV–Visible Spectrometer of 2020 GBC Cintra model [31].
3. Results and discussion
3.1. Preliminary evaluation of complex nitrogen sources on AC production
The study in Figure 2 shows that CSL supports rapid utilization of the reducing sugar (from 150 to 84 g/L) within the first 60 h of fermentation [32], the resultant acetoin and biomass growth being maximum during this period. The maximum biomass growth is found to be fairly constant at ~ 8 g/L until the 144 h when it starts to decline. Likewise, the maximum acetoin concentration is found to be ~ 7 g/L after 60 h of fermentation and then declines. The decline in the acetoin concentration could be attributed to the complete metabolism of glucose in the fermentation medium. Although the biomass concentration remained constant after the 60 h of fermentation, it can be assumed that the energy derived from reducing sugar metabolism was channeled toward cell maintenance since biomass growth remained constant and acetoin was still produced till the fermentation lapse. It has been shown previously that CSL is a rich source of proteins, amino acids, minerals, vitamins, and trace elements and can be used as nutritional supplement [32]. The addition of CSL reduced the fermentation time and promoted the growth and fermentation of the strain.
On the other hand, when yeast extract was used as the nitrogen source in the fermentation media, as depicted in Figure 2b, after reducing 150 g/L of sugar, the results showed a rapid consumption of the reducing sugar when compared to Figure 2a. More than 97% of the reducing sugar was converted (during the first 84 h of fermentation), the acetoin concentration approached a maximum, and the biomass growth was constant at 8.6 and 7.7 g/L, respectively. The wide range of amino acids, peptides, vitamins, inorganic salts, and carbon in growth media of yeast extract supports the biomass growth and rapid sugar utilization [33].
In Figure 2c, the extract was used in place of CSL and yeast extract as earlier discussed (Figure 2a and b). The beef extract is a mixture of peptides and amino acids, nucleotide fractions, organic acids, minerals, and some vitamins. Its function can, therefore, be described as complementing the nutritive properties of peptone by contributing minerals, phosphates, energy sources, and those essential factors missing from peptone [34]. The glucose was almost depleted after 96 h till the end of the fermentation lapse. It can be deduced from the study that the beef extract supports the utilization of glucose consumption as more than 98% of the glucose has been consumed within 96 h of fermentation.
To see the clear difference of the complex media earlier considered, the acetoin fermentation was done without the nitrogen sources (Figure 2d) but with the simple salts in the fermentation media. A maximum acetoin of about 5.2 g/L was obtained during the first 12 h of the fermentation, after which there was no significant change in the biomass growth from that period until the lapse time of fermentation. About 50% (72.53 g/L) of sugar concentration was not consumed until the fermentation time lapse of 168 h, and the sluggish consumption of glucose could be traceable to the lack of rich nitrogen sources, which was needed as a nutritional supplement [28].
3.2. Metabolism of corn steep liquor on AC production
It was observed in the preliminary evaluation of nitrogen sources discussed earlier (Figure 2a–d) that corn steep liquor produces acetoin at a short time interval when compared to other nitrogen sources. Therefore, the fermentation time interval of acetoin was reduced from the initial 168 h (Figure 2a–d) to 48 h (Figure 3) and sample taken at every 2-h interval, to investigate the biomass growth, utilization of glucose, and the acetoin accumulation when corn steep liquor was used as nitrogen source. The results show that the accumulated acetoin and the biomass growth were already at the peak of 7.03 and 7.83 g/L, respectively, in the first 36 h of fermentation (Figure 3). The rapid utilization of reducing sugar (from 150 to 66 g/L) within 36 h of fermentation was due to high amino acids and polypeptides, which are excellent sources of nitrogen in corn steep liquor and has been reported to support the growth of most microorganism [35]. CSL comprises a mixture of reducing sugars that contribute to the nutritional growth of the bacteria with a steady increase in biomass growth (7.7–7.8 g/L) from 18 to 46 h when it starts to decline [36]. It can be affirmed from the findings that corn steep liquor hastens fermentation of acetoin at short time interval and this makes large-scale production of acetoin cost-effective.
3.3. Optimization of AC production using response surface method
After the preliminary studies, RSM coupled with Box-Behnken design (BBD) was used for the optimization of the fermentation process with respect to glucose concentration, CSL concentration, and inoculum size with a view to maximize the AC production. Table 2 shows the experimental conditions investigated together with the observed and predicted values. The data were fitted using the following second-order mathematical equation:
where Y is the acetoin (AC) produced in g/L and X1 is glucose concentration, X2 is corn steep liquor, X3 is Inoculum size. The residuals between the observed and predicted (Table 2) values in this work revealed good fit of the equation as shown by the parity graph which is a measure of agreement between the observed and predicted values (Figure 4). These observations implied that the model developed for the fermentation process adequately described the actual relationship among the selected factors.
Run | X1 (g/L) | X2 (% w/v) | X3 (%v/v) | Observed AC (g/L) | Predicted AC (g/L) | Residuals |
---|---|---|---|---|---|---|
1 | 100 (0) | 10 (0) | 3.5 (0) | 7.68 | 7.81 | −0.13 |
2 | 150 (1) | 10 (0) | 2 (−1) | 4.32 | 5.28 | −0.96 |
3 | 150 (1) | 5 (−1) | 3.5 (0) | 2.47 | 2.29 | 0.18 |
4 | 100 (0) | 10 (0) | 3.5 (0) | 7.68 | 7.81 | −0.13 |
5 | 100 (0) | 5 (−1) | 2 (−1) | 3.66 | 3.24 | 0.42 |
6 | 100 (0) | 15 (1) | 2 (−1) | 10.69 | 10.41 | 0.28 |
7 | 50 (−1) | 10 (0) | 2 (−1) | 7.14 | 6.88 | 0.26 |
8 | 100 (0) | 15 (1) | 5 (1) | 6.49 | 7.15 | −0.66 |
9 | 50 (−1) | 10 (0) | 5 (1) | 8.00 | 6.8 | 1.20 |
10 | 150 (1) | 10 (0) | 5 (1) | 2.91 | 2.92 | −0.01 |
11 | 100 (0) | 10 (0) | 3.5 (0) | 7.68 | 7.81 | −0.13 |
12 | 100 (0) | 5 (−1) | 5 (−1) | 3.53 | 4.06 | −0.53 |
13 | 150 (1) | 15 (1) | 3.5 (0) | 7.88 | 7.08 | 0.80 |
14 | 50 (−1) | 15 (1) | 3.5 (0) | 9.74 | 10.16 | −0.42 |
15 | 100 (0) | 10 (0) | 3.5 (0) | 7.70 | 7.80 | −0.11 |
16 | 100 (0) | 5 (−1) | 3.5 (0) | 5.72 | 4.74 | 0.98 |
17 | 50 (−1) | 5 (−1) | 3.5 (0) | 3.65 | 4.69 | −1.04 |
The three-dimensional graph and contour plot, which is depicted in Figure 5(a) and (b) shows the relationship between corn steep liquor and glucose concentration when acetoin production is at the maximum (10.70 g/L). Also, the
Factor | Sum of squares | df | Mean square | ||
---|---|---|---|---|---|
X1 (Glucose) | 14.99 | 1 | 14.99 | 16.51 | 0.0048 |
X12 | 6.52 | 1 | 6.52 | 7.18 | 0.0315 |
X2 (CSL) | 57.85 | 1 | 57.85 | 63.73 | 0.0001 |
X22 | 1.06 | 1 | 1.06 | 1.17 | 0.3160 |
X3 (Inoculum size) | 2.98 | 1 | 2.98 | 3.28 | 0.1131 |
X32 | 4.98 | 1 | 4.98 | 5.48 | 0.0517 |
X1X2 | 0.12 | 1 | 0.12 | 0.13 | 0.7317 |
X1X3 | 1.29 | 1 | 1.29 | 1.42 | 0.2724 |
X2X3 | 4.14 | 1 | 4.14 | 4.56 | 0.0701 |
ANOVA | |||||
Model | 90.63 | 9 | 10.07 | 11.09 | 0.0022 |
Error | 3.000E-004 | 3 | 1.000E-004 | ||
Total sum of squares | 96.99 | 16 | |||
3.4. Model validation
The optimum values of the three factors selected for the fermentation process were obtained by solving Eq. (2) using the Design-Expert software package (version 10.0). The optimal condition was statistically predicted as glucose concentration of 78.40 g/L, CSL of 15.00% w/v, and inoculum size of 2.70% v/v. Under this condition, the AC concentration predicted was 10.73 g/L. In order to validate the model, the optimal condition values were applied to three independent experimental replicates and the average value of AC produced was 10.70 ± 0.1 g/L. The correlations between predicted and experimental values after optimization infer the validity of the response model and the existence of an optimum point [40]. The bar chart (Figure 6) is a graphical view for each optimal solution showing the desirability of every dependent and independent factor with combined value. Independent factors are shown with red bars, while the dependent response and combined values are displayed in blue. The desirability result is accurate as it falls within the acceptable value ranging between 0.8 and 1 [41]. In Table 4, variance inflation factor (VIF) obtained showed that the center points are orthogonal to all other factors in the model. The 95% confidence interval (CI) bounds showing high and low help to hypothesize that there is 95% probability of including the right predicted responses by the model, and there is only 5% chance that the observed value lies either below or above the level of confidence limits. The coefficient estimate shows the confidence interval around the model coefficient and the standard error less than 1 shows the statistical accuracy of the predicted responses (Table 4).
Factor | Coefficient estimate | df | Standard error | 95% CI low | 95% CI high | VIF |
---|---|---|---|---|---|---|
Intercept | 7.81 | 1 | 0.47 | 6.71 | 8.91 | |
X1 (Glucose) | −1.37 | 1 | 0.34 | −2.17 | −0.57 | 1.00 |
X2 (Corn steep liquor) | 2.56 | 1 | 0.32 | 1.80 | 3.32 | 1.02 |
X3 (Inoculum size) | −0.61 | 1 | 0.34 | −1.41 | 0.19 | 1.00 |
X1X2 | −0.17 | 1 | 0.48 | −1.30 | 0.96 | 1.00 |
X1X3 | −0.57 | 1 | 0.48 | −1.69 | 0.56 | 1.00 |
X2X3 | −1.02 | 1 | 0.48 | −2.14 | 0.11 | 1.00 |
X12 | −1.25 | 1 | 0.47 | −2.35 | −0.15 | 1.01 |
X22 | −0.50 | 1 | 0.47 | −1.60 | 0.60 | 1.01 |
X32 | −1.09 | 1 | 0.47 | −2.19 | 0.011 | 1.01 |
4. Conclusion
The feasibility of corn steep liquor to replace yeast extract and beef extract, which is an expensive nutrient source in acetoin fermentation, was investigated. Corn steep liquor—a low-cost nitrogen source—competes with other complex nutrients (yeast extract and beef extract) for acetoin production and statistical optimization was carried out in batch fermentation. The model that best described the AC fermentation process was a quadratic model with
Acknowledgments
The authors wish to thank the National Research Foundation (NRF) and Cape Peninsula University of Technology (CPUT) for providing the running cost of this research. AE Taiwo acknowledges NRF in partnership with the World Academy of Sciences (TWAS)—NRF-TWAS—for the award of his doctoral scholarship and Landmark University Nigeria for the staff development program.
Conflict of interest
The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; and in the decision to publish the results.
References
- 1.
Bae S-J, Kim S, Hahn J-S. Efficient production of acetoin in Saccharomyces cerevisiae by disruption of 2, 3-butanediol dehydrogenase and expression of NADH oxidase. Scientific Reports. 2016;6 :27667. DOI: 10.1038/srep27667 - 2.
Zhang L, Chen S, Xie H, Tian Y, Hu K. Efficient acetoin production by optimization of medium components and oxygen supply control using a newly isolated Paenibacillus polymyxa CS107. Journal of Chemical Technology and Biotechnology. 2012;87 :1551-1557. DOI: 10.1002/jctb.3791 - 3.
Li L, Wei X, Yu W, Wen Z, Chen S. Enhancement of acetoin production from Bacillus licheniformis by 2, 3-butanediol conversion strategy: Metabolic engineering and fermentation control. Process Biochemistry. 2017;57 :35-42. DOI: 10.1016/j.procbio.2017.03.027 - 4.
Luo Q, Wu J, Wu M. Enhanced acetoin production by Bacillus amyloliquefaciens through improved acetoin tolerance. Process Biochemistry. 2014;49 :1223-1230. DOI: 10.1016/j.procbio.2014.05.005 - 5.
Zhang X, T-w Y, Lin Q, M-j X, H-f X, Xu Z-h, et al. Isolation and identification of an acetoin high production bacterium that can reverse transform 2, 3-butanediol to acetoin at the decline phase of fermentation. World Journal of Microbiology and Biotechnology. 2011; 27 :2785-2790. DOI: 10.1007/s11274-011-0754-y - 6.
Xiao Z, Wang X, Huang Y, Huo F, Zhu X, Xi L, et al. Thermophilic fermentation of acetoin and 2, 3-butanediol by a novel Geobacillus strain. Biotechnology for Biofuels. 2012; 5 :88. DOI: 10.1186/1754-6834-5-88 - 7.
Nielsen DR, Yoon SH, Yuan CJ, Prather KL. Metabolic engineering of acetoin and meso-2, 3-butanediol biosynthesis in E. coli . Biotechnology Journal. 2010;5 :274-284. DOI: 10.1002/biot.200900279 - 8.
Xu Q, Xie L, Li Y, Lin H, Sun S, Guan X, et al. Metabolic engineering of Escherichia coli for efficient production of (3R)-acetoin. Journal of Chemical Technology and Biotechnology. 2015;90 :93-100. DOI: 10.1002/jctb.4293 - 9.
Sun J, Zhang L, Rao B, Han Y, Chu J, Zhu J, et al. Enhanced acetoin production by Serratia marcescens H32 using statistical optimization and a two-stage agitation speed control strategy. Biotechnology and Bioprocess Engineering. 2012;17 :598-605. DOI: 10.1007/s12257-011-0587-4 - 10.
Teixeira RM, Cavalheiro D, Ninow J, Furigo A Jr. Optimization of acetoin production by Hanseniaspora guilliermondii using experimental design. Brazilian Journal of Chemical Engineering. 2002;19 :181-186. DOI: 10.1590/S0104-66322002000200014 - 11.
Tian Y, Fan Y, Zhao X, Zhang J, Yang L, Liu J. Optimization of fermentation medium for acetoin production by Bacillus subtilis SF4-3 using statistical methods. Preparative Biochemistry and Biotechnology. 2014;44 :529-543. DOI: 10.1080/10826068.2013.835731 - 12.
Liu D, Chen Y, Ding F, Guo T, Xie J, Zhuang W, et al. Simultaneous production of butanol and acetoin by metabolically engineered Clostridium acetobutylicum . Metabolic Engineering. 2015;27 :107-114. DOI: 10.1016/j.ymben.2014.11.002 - 13.
Roncal T, Caballero S, de Guereñu MMD, Rincón I, Prieto-Fernández S, Ochoa-Gómez JR. Efficient production of acetoin by fermentation using the newly isolated mutant strain Lactococcus lactis subsp.lactis CML B4. Process Biochemistry. 2017;58 :35-41. DOI: 10.1016/j.procbio.2017.04.007 - 14.
Tian Y, Fan Y, Liu J, Zhao X, Chen W. Effect of nitrogen, carbon sources and agitation speed on acetoin production of Bacillus subtilis SF4-3. Electronic Journal of Biotechnology. 2016;19 :41-49. DOI: 10.1016/j.ejbt.2015.11.005 - 15.
Yang T-W, Rao Z-M, Zhang X, Xu M-J, Xu Z-H, Yang S-T. Effects of corn steep liquor on production of 2, 3-butanediol and acetoin by Bacillus subtilis . Process Biochemistry. 2013;48 :1610-1617. DOI: 10.1016/j.procbio.2013.07.027 - 16.
Xiao Z, Liu P, Qin JY, Xu P. Statistical optimization of medium components for enhanced acetoin production from molasses and soybean meal hydrolysate. Applied Microbiology and Biotechnology. 2007; 74 :61-68. DOI: 10.1007/s00253-006-0646-5 - 17.
Tang Y, An M, Liu K, Nagai S, Shigematsu T, Morimura S, et al. Ethanol production from acid hydrolysate of wood biomass using the flocculating yeast Saccharomyces cerevisiae strain KF-7. Process Biochemistry. 2006; 41 :909-914. DOI: 10.1016/j.procbio.2005.09.008 - 18.
Edwinoliver N, Thirunavukarasu K, Purushothaman S, Rose C, Gowthaman M, Kamini N. Corn steep liquor as a nutrition adjunct for the production of Aspergillus niger lipase and hydrolysis of oils thereof. Journal of Agricultural and Food Chemistry. 2009;57 :10658-10663. DOI: 10.1021/jf902726p - 19.
Seo H-B, Kim SS, Lee H-Y, Jung K-H. High-level production of ethanol during fed-batch ethanol fermentation with a controlled aeration rate and non-sterile glucose powder feeding of Saccharomyces cerevisiae . Biotechnology and Bioprocess Engineering. 2009;14 :591. DOI: 10.1007/s12257-008-0274-2 - 20.
Lawford HG, Rousseau JD. Corn steep liquor as a cost-effective nutrition adjunct in high-performance Zymomonas ethanol fermentations. Applied Biochemistry and Biotechnology. 1997; 63 :287. DOI: 10.1007/BF02920431 - 21.
Souza AF, Rodriguez DM, Ribeaux DR, Luna MA, Lima e Silva TA, Andrade RFS, et al. Waste soybean oil and corn steep liquor as economic substrates for bioemulsifier and biodiesel production by Candida lipolytica UCP 0998. International Journal of Molecular Sciences. 2016;17 :1608. DOI: 10.3390/ijms17101608 - 22.
Xu H, Jia S, Liu J. Production of acetoin by Bacillus subtilis TH-49. Consumer Electronics, Communications and Networks (CECNet), 2011 International Conference on; 2011; 16-18 April. IEEE - 23.
Osunkanmibi OB, Owolabi TO, Betiku E. Comparison of artificial neural network and response surface methodology performance on fermentation parameters optimization of bioconversion of cashew apple juice to gluconic acid. International Journal of Food Engineering. 2015; 11 :393-403. DOI: 10.1515/ijfe-2015-0072 - 24.
Oyeniran O, Taiwo A, Betiku E. A modeling study by response surface methodology on the culture parameters optimization of citric acid bioproduction from sweet potato peel. Ife Journal of Technology. 2013; 22 :21-25 - 25.
Pereira FB, Guimarães PM, Teixeira JA, Domingues L. Optimization of low-cost medium for very high gravity ethanol fermentations by Saccharomyces cerevisiae using statistical experimental designs. Bioresource Technology. 2010;101 :7856-7863. DOI: 10.1016/j.biortech.2010.04.082 - 26.
Sharma P, Noronha S. Comparative assessment of factors involved in acetoin synthesis by Bacillus subtilis 168. ISRN Microbiology. 2014;2014 :1-7. DOI: 10.1155/2014/578682 - 27.
Miller GL. Use of dinitrosalicylic acid reagent for determination of reducing sugar. Analytical Chemistry. 1959; 31 :426-428. DOI: 10.1021/ac60147a030 - 28.
Betiku E, Taiwo AE. Modeling and optimization of bioethanol production from breadfruit starch hydrolyzate vis-à-vis response surface methodology and artificial neural network. Renewable Energy. 2015; 74 :87-94. DOI: 10.1016/j.renene.2014.07.054 - 29.
Betiku E, Alade O. Media evaluation of bioethanol production from cassava starch hydrolysate using Saccharomyces cerevisiae . Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. 2014;36 :1990-1998. DOI: 10.1080/15567036.2011.557690 - 30.
Speckman R, Collins E. Specificity of the Westerfeld adaptation of the Voges-Proskauer test. Applied and Environmental Microbiology. 1982; 44 :40-43. DOI: aem00176-0048 - 31.
Campo G, CarmenáLajo M. Spectrophotometric determination of biacetyl in distillates of wine by flow injection. The Analyst. 1992; 117 :1343-1346. DOI: 10.1039/AN9921701343 - 32.
Sreenath HK, Jeffries TW. Effect of corn steep liquor on fermentation of mixed sugars by Candida shehatae FPL-702. Applied Biochemistry and Biotechnology. 1996;57 :551-561. DOI: 10.1007/BF02941735 - 33.
Costa E, Teixidó N, Usall J, Atarés E, Viñas I. The effect of nitrogen and carbon sources on growth of the biocontrol agent Pantoea agglomerans strain CPA-2. Letters in Applied Microbiology. 2002;35 :117-120. DOI: 10.1046/j.1472-765X.2002.01133.x - 34.
Prokofeva M, Miroshnichenko M, Kostrikina N, Chernyh N, Kuznetsov B, Tourova T, et al. Acidilobus aceticus gen. nov., sp. nov., a novel anaerobic thermoacidophilic archaeon from continental hot vents in Kamchatka. International Journal of Systematic and Evolutionary Microbiology. 2000;50 :2001-2008. DOI: 10.1099/00207713-50-6-2001 - 35.
Liggett RW, Koffler H. Corn steep liquor in microbiology. Bacteriological Reviews. 1948; 12 :297-311. DOI: bactrev00003-0030 - 36.
Xiao X, Hou Y, Liu Y, Liu Y, Zhao H, Dong L, et al. Classification and analysis of corn steep liquor by UPLC/Q-TOF MS and HPLC. Talanta. 2013; 107 :344-348. DOI: 10.1016/j.talanta.2013.01.044 - 37.
Dhillon GS, Kaur S, Brar SK, Verma M. Potential of apple pomace as a solid substrate for fungal cellulase and hemicellulase bioproduction through solid-state fermentation. Industrial Crops and Products. 2012; 38 :6-13. DOI: 10.1016/j.indcrop.2011.12.036 - 38.
Betiku E, Omilakin OR, Ajala SO, Okeleye AA, Taiwo AE, Solomon BO. Mathematical modeling and process parameters optimization studies by artificial neural network and response surface methodology: A case of non-edible neem ( Azadirachta indica ) seed oil biodiesel synthesis. Energy. 2014;72 :266-273. DOI: 10.1016/j.energy.2014.05.033 - 39.
Joglekar A, May A. Product excellence through design of experiments. Cereal Foods World. 1987; 32 :857-868 - 40.
Ashengroph M, Nahvi I, Amini J. Application of Taguchi design and response surface methodology for improving conversion of isoeugenol into vanillin by resting cells of Psychrobacter sp. CSW4. Iranian Journal of Pharmaceutical Research. 2013; 12 :411-421. DOI: 10.1016/j.lwt.2014.05.014 - 41.
Sarteshnizi RA, Hosseini H, Bondarianzadeh D, Colmenero FJ. Optimization of prebiotic sausage formulation: Effect of using β-glucan and resistant starch by D-optimal mixture design approach. LWT-Food Science and Technology. 2015; 62 :704-710. DOI: 10.1016/j.lwt.2014.05.014