INTRODUCTION
The growing global population and rapid technological advancements have led to a surge in energy demand, primarily met by fossil fuels. However, their continued use poses severe environmental challenges, such as increased greenhouse gas emissions contributing to global warming and ocean acidification (Chew et al., 2018). Therefore, exploring alternative renewable energy sources is essential.
Bioethanol, a renewable biofuel, offers a sustainable solution for reducing dependence on fossil fuels. Bioethanol sources are classified into three generations: first-generation (food crops), second-generation (lignocellulosic non-edible materials), and third-generation (microalgae). Among these, microalgae-based bioethanol stands out due to its fast growth, minimal land requirements, lack of competition with food resources, and absence of lignin, which simplifies cell disruption and lowers processing costs (Chew et al., 2018; Chia et al., 2018).
This research focused on quantifying bioethanol production from Zygnema microalgae biomass under different fermentation conditions, assessing its suitability for fuel applications.
MATERIALS AND METHODS
Ethanol Concentration Determination:
Five milliliters of each sample were mixed with 2 ml of prepared potassium dichromate solution, shaken, and left for 20 minutes. Samples were then analyzed in a UV-Visible spectrophotometer to determine ethanol concentration by comparison with a standard curve (Sirajo et al., 2019).
Reactivation of Baker’s Yeast (Saccharomyces cerevisiae):
Commercial baker’s yeast was reactivated by suspending it in warm water at 36°C, following Rabah et al. (2011). Yeast dextrose agar was prepared and incubated to cultivate active yeast, which was later inoculated into yeast dextrose broth.
Fermentation Process:
The hydrolysate was adjusted to pH values of 6.5, 7.0, and 7.5 and supplemented with nutrients (per L): 5 g MgSO₄·7H₂O, 5 g S. cerevisiae extract, 5 g KH₂PO₄, and 2 g (NH₄)₂SO₄. Fermentations were carried out in triplicate at temperatures of 20°C, 25°C, and 30°C, with retention times of 3, 6, and 9 days. Samples were collected at 6-hour intervals, and results were recorded as mean ± standard deviation.
Fractional Distillation:
Fermented broth was distilled at 78.3°C, and bioethanol was collected in a conical flask connected to a distillation column.
Density Determination:
Density was calculated by measuring the volume of distillate relative to the original sample mass using the method described by Emtron (2015).
Quantity Determination:
The quantity of bioethanol produced was determined by multiplying the volume of collected distillate by the density of ethanol (0.8033 g/ml) and expressed in g/L (Humphrey et al., 2007).
Viscosity Determination:
Samples were equilibrated to the test temperature for 30 minutes before measuring flow time using a capillary viscometer. Kinematic viscosity was calculated as the product of flow time and instrument constant (ASTM D445, 1984).
RESULTS AND DISCUSSION
Table 1: Bioethanol Concentration Over Different Retention Times
| Retention Time (Days) | pH | Temp (°C) | Bioethanol Concentration (g/dm³) |
|---|---|---|---|
| 3 | 6.5 | 20 | 0.11 ± 0.21 |
| 6 | 7.0 | 25 | 0.078 ± 0.13 |
| 9 | 7.5 | 30 | 0.048 ± 0.14 |
The highest concentration was observed at Day 6 (0.078 ± 0.13 g/dm³) at 25°C, decreasing by Day 9. Variations in bioethanol concentration are influenced by yeast performance, where Saccharomyces cerevisiae remains the most robust and widely used organism for ethanol fermentation due to its ability to tolerate stress and high ethanol concentrations (Walker & Basso, 2020).
Table 2: Quantity of Bioethanol Produced
| Retention Time (Days) | pH | Temp (°C) | Quantity (g/ml) |
|---|---|---|---|
| 3 | 6.5 | 20 | 0.54 ± 0.056 |
| 6 | 7.0 | 25 | 0.85 ± 0.078 |
| 9 | 7.5 | 30 | 0.94 ± 0.15 |
The highest yield occurred at Day 9 (0.94 ± 0.15 g/ml) at pH 7.5 and 30°C, consistent with other studies showing optimal ethanol production at higher temperatures and neutral pH levels (Kemka et al., 2013).
Table 3: Density of Produced Bioethanol
| Retention Time (Days) | pH | Temp (°C) | Density (g/cm³) |
|---|---|---|---|
| 3 | 6.5 | 20 | 0.54 ± 0.58 |
| 6 | 7.0 | 25 | 0.85 ± 0.08 |
| 9 | 7.5 | 30 | 0.94 ± 0.15 |
Measured densities exceeded the ASTM standard density of 0.789 g/cm³ for ethanol, indicating potential issues such as engine knocking if used at high temperatures and pressures, aligning with findings by Anonymous (2006) and Raj (2019).
able 4: Viscosity of Produced Bioethanol
| Retention Time (Days) | pH | Temp (°C) | Viscosity (cSt) |
|---|---|---|---|
| 3 | 6.5 | 20 | 1.89 ± 0.35 |
| 6 | 7.0 | 25 | 2.23 ± 0.65 |
| 9 | 7.5 | 30 | 1.83 ± 0.22 |
The highest viscosity was recorded at Day 6 (2.23 ± 0.65 cSt), while viscosity decreased at higher temperatures (Day 9), which is consistent with the expected behavior of fluids where viscosity inversely relates to temperature (IOP Conference, 2019). Viscosity values above 1.5 cSt may affect engine performance by hindering fuel atomization.
CONCLUSION
Bioethanol production from Zygnema microalgae demonstrated promising results, with optimal yields achieved at pH 7–7.5 and higher temperatures over extended fermentation periods. The measured quantities, densities, and viscosities were within or close to acceptable standards, indicating Zygnema microalgae as a viable alternative feedstock for sustainable bioethanol production, potentially outperforming first- and second-generation sources.
References
Abee, T. (1995).Pore-forming bacteriocins of Gram-positive bacteria and self-protection mechanisms of producer organisms. FEMS Microbiology Letters, 129 (1): 1-9.
Anonymous (2006).A Bet on Ethanol, with a Convert at the Helm. New York, pp:8.
André, L., Hemming, A., and Adler, L. (1991). Osmoregulation in Saccharomyces cerevisiae studies on the osmotic induction of glycerol production and glycerol 3-phosphate dehydrogenase (NAD+). FEBS letters, 286(1-2): 13-17.
Ansell, R., Granath, K., Hohmann, S., Thevelein, J. M., and Adler, L. (1997). The two isoenzymes for yeast NAD+-dependent glycerol 3-phosphate dehydrogenase encoded by GPD1 and GPD2 have distinct roles in osmoadaptation and redox regulation. The EMBO journal, 16(9): 2179-2187.
Berthel, D., Neumaier, M., Schüler, D., Kaulisch, T., Lanz, T., and Stiller, D. (2014).Optimization of a four channel phased array coil for rat lung imaging at 7 T. In Processing International Social Management Revised Medicine. 22: 2310.
Blieck, L., Toye, G., Dumortier, F., Verstrepen, K. J., Delvaux, F. R., Thevelein, J. M., and Van Dijck, P. (2007).Isolation and characterization of brewer’s yeast variants with improved fermentation performance under high-gravity conditions. Applied and Environmental Microbiology, 73(3), 815- 824.
Chew, K.W., Chia, S.R., Show, P.L, Yap, Y.J., Ling, T.C., and Chang, J.S. (2018) Effects of Water
Culture Medium, cultivation systems and growth modes for microalgae cultivation: A Review. J Taiwan Inst. Chem. Eng.; 91:332–44.
Chia, S.R., Chew, K.W., Show, P.L., Yap, Y.J., Ong, H.C., Ling, T.C., Chang, J.S. (2018). Analysis
of Economic and environmental aspects of microalgae bio-refinery for biofuels Production: a review. Biotechnology. J. 2018;13(6):1700618.
Claassen, P.A.M.; van Lier, J.B.; Lopez Contreras, A.M.; van Niel, E.W.J.; Sijtsma, L.; Stams, A.J.M.; de Vries, S.S.; and Weusthuis, R.A. (1999).Utilization of biomass for the supply of energy carriers. Applied Microbioliology Biotechnology. 52, Pp. 741–755.
Cray, J.A.; Stevenson, A.; Ball, P.; Bankar, S.B.; Eleutherio, E.C.; Ezeji, T.C.; Singhal, R.S.; Thevelein, J.M.; Timson, D.J.; and Hallsworth, J.E. (2015).Chaotropicity: A key factor in product tolerance of biofuel-producing microorganisms. Current. Open. Biotechnology. 33, Pp. 228–259.
Deparis, Q.; Claes, A.; Foulquié-Moreno, M.R.; and Thevelein, K.M. (2017). Engineering tolerance to industrially relevant stress factors in yeast cell factories. FEMS Yeast Research. 17, 4.
Humphrey, C. N., and Caritas, U. O. (2007). Optimization of ethanol production from
GarciniaKola (bitter kola) pulp agrowaste. African Journal of Biotechnology, 6 (17): 2033-2037.
Dragone, G., Silva, D. P., de Almeida e Silva, J. B., and de Almeida Lima, U. (2003).Improvement of the ethanol productivity in a high gravity brewing at pilot plant scale. Biotechnology Letters, 25, 1171-1174.
Emtron, A. (2015). Calculating fuel density.Available on www.emtronaustralia.com.au. Retrived on 22nd November, 2018.
Erten, H.; Tanguler, H.; and Cakiroz, H. (2007). The effect of pitching rate on fermentation and Flavour compounds in high gravity brewing. Journal of the Institute of Brewing. 113, 75–79.
IOP Conference Series, Earth and Environmental Science 2019.
Sirajo, I. Muhammad, I., and Mominur, R. (2019). Comparative study on production of bioethanol from banana and yam peel. Journal of Pharmacology online1:100-106.
Ojewumi, M.E., Job, A.I., Taiwo, O.S., Obanla, O.M., Ayoola, A.A., Ojewumi, E.O., and Oyeniyi, E.A (2018). Bio-Conversion of Sweet Potato Peel Waste to Bio-Ethanol Using Saccharomyces Cerevisiae. International Journal of Pharmaceutical and Phytopharmacological Research. 8(3):46-54.
Oyeleke, S. B., and Jibril, N.M. (2009). Production of bioethanol from guinea corn husk and millet husk. African Journal of Microbiology Reseach3 (4): 147-152.
Larsson, K., Ohlsen, P., Larsson, L., Malmberg, P., Rydström, P. O., and Ulriksen, H. (1993).High prevalence of asthma in cross country skiers. British Medical Journal, 307(6915), 1326-1329.
Nissen, T. L., Kielland-Brandt, M. C., Nielsen, J., and Villadsen, J. (2000).Optimization of ethanol production in Saccharomyces cerevisiae by metabolic engineering of the ammonium assimilation.Metabolic engineering, 2(1): 69-77.
Norton, A. J., Matthews, J., Pappa, V., Shamash, J., Love, S., Rohatiner, A. Z. S., and Lister, T. A. (1995). Mantle cell lymphoma: natural history defined in a serially biopsied population over a 20-year period. Annals of Oncology, 6(3), 249-256.
Nguyen, T.H.; and Le, V.V.M. (2009).Using high pitching rate for improvement of yeast fermentation performance in high gravity brewing. International Food Revised Journal. 16: 547–554.
Pagliardini, J., Hubmann, G., Alfenore, S., Nevoigt, E., Bideaux, C., and Guillouet, S. E. (2013). The metabolic costs of improving ethanol yield by reducing glycerol formation capacity under anaerobic conditions in Saccharomyces cerevisiae. Microbial cell factories, 12: 1-14.
Pham, M. X., Teuteberg, J. J., Kfoury, A. G., Starling, R. C., Deng, M. C., Cappola, T. P., … and Valantine, H. A. (2010). Gene-expression profiling for rejection surveillance after cardiac transplantation. New England Journal of Medicine, 362(20): 1890-1900.
Walker, G.M.; and Basso, T.O.( 2020). Mitigating stress in industrial yeasts. Fungal Biology. 124: 387–397.