Abstract
This paper proposes a method to determine bioethanol concentration that uses a pycnometer verified with a high performance liquid chromatography (HPLC) technique; it is a simple tool to determine the density of liquids for getting information about the ethanol concentration. The results showed that the sugar concentration affected the bioethanol concentration. A lower initial sugar concentration of 26.5 g/L generated higher yield of 45.3% sugar to bioethanol and a fractional or relative yield of 88.74%. Significance tests were used to compare the two experimental means, revealing that the pycnometer method and HPLC provide the same bioethanol concentration with joint variances of 2.269, 0.242, and 0.112 for 3 different tests with initial sugar concentrations of 26.486 g/L, 49.043 g/L, and 68.535 g/L, respectively. This study established and developed a methodology to determine bioethanol concentration from coffee mucilage by the proposed method.
Download PDF
Full Article
A Simple Method to Determine Bioethanol Production from Coffee Mucilage, Verified by HPLC
Bianca Yadira Pérez-Sariñana,a,* Sergio Saldaña-Trinidad,b Carlos Alberto Guerrero-Fajardo,c Luis Fernando Santis-Espinosa,a and Sebastian P. J. a,*
This paper proposes a method to determine bioethanol concentration that uses a pycnometer verified with a high performance liquid chromatography (HPLC) technique; it is a simple tool to determine the density of liquids for getting information about the ethanol concentration. The results showed that the sugar concentration affected the bioethanol concentration. A lower initial sugar concentration of 26.5 g/L generated higher yield of 45.3% sugar to bioethanol and a fractional or relative yield of 88.74%. Significance tests were used to compare the two experimental means, revealing that the pycnometer method and HPLC provide the same bioethanol concentration with joint variances of 2.269, 0.242, and 0.112 for 3 different tests with initial sugar concentrations of 26.486 g/L, 49.043 g/L, and 68.535 g/L, respectively. This study established and developed a methodology to determine bioethanol concentration from coffee mucilage by the proposed method.
Keywords: Pycnometer; HPLC; Fermentation; Bioethanol concentration
Contact information: a: Instituto de Energías Renovables-UNAM, Temixco, Morelos, 62580, México; b: Universidad Politécnica de Chiapas, Tuxtla Gutiérrez, Chiapas, 29010, México; c: Departamento de Química, Universidad Nacional de Colombia, Bogotá 11001, Colombia;
* Corresponding authors: bipes@ier.unam.mx; sjp@ier.unam.mx
INTRODUCTION
Using renewable resources derived from biomass is beneficial when trying to develop sustainable energy systems from different substrates (Cortright et al. 2002). The conversion of biomass into biofuels can reduce the strategic vulnerability of petroleum-based transportation systems. Bioethanol has received considerable attention over the last few years as a fuel extender or even as a neat liquid fuel (Vučurović and Razmovski 2012). Previous studies reference the determination of ethanol or bioethanol content by HPLC (Liebmann et al. 2009) from polysaccharides (Huang et al. 2013), from steam-flaked sorghum and maize (Chuck-Hernandez et al. 2009), rapeseed straw (Karagöz et al.2013), forestry residue (Ferreira et al. 2010), and others. Coffee mucilage is a waste product that is thrown directly into waterways without treatment. This is because it has no alternative use, which causes serious pollution problems.
Ethanol determination can be realized in several ways: densimetric methods (Lachenmeier et al. 2010), potassium dichromate (Breisha 2010), biosensor potentiometry (Rotariu et al. 2004), gas chromatography (GC) (Wang et al. 2003), capillary electrophoresis (Oliver et al. 2014), high performance liquid chromatography (HPLC) (Huang et al. 2013), Raman spectrometry (Shih and Smith 2009), near-infrared spectroscopy (NIR) (Liemann et al. 2009), beer analyzer, and flow injection analysis (Rangel and Tóth 2000).
For the dichromate oxidation spectrophotometry, the reagents used are highly toxic and harmful. Low stability, reproducibility, and accuracy are the disadvantages for enzymatic method, biosensor, and potentiometry. Raman spectrometry, capillary electrophoresis, GC method, and HPLC require expensive equipment. The HPLC method has a comparatively low sensitivity. NIR spectroscopy and analyzer have low accuracy.
A method proposed to determine bioethanol concentration in this paper using a pycnometer method verified with the high-performance liquid chromatography (HPLC) technique is like a simple tool to determine the density of liquids as a means for getting information about ethanol concentration. This method helps to compare the densities of two liquids, weighing the pycnometer with each liquid separately and comparing their masses (Pratten 1981; Piccolo and Bezzo 2009). The entire process should be conducted at a constant temperature to avoid errors due to slight variations in volume due to the temperature. The pycnometer is very sensitive to changes in concentration of salts in the water, so it is used to determine the salinity of the water and the density of biological liquids in laboratories, among other applications. The pycnometer method is an alternative way to quantify ethanol concentration in a fermentation medium when there is a lack of sophisticated equipment.
EXPERIMENTAL
Materials
Substrate
The coffee mucilage was extracted mechanically and supplemented with salts: 0.02 g/L of magnesium sulfate (MgSO47H2O) and 0.2 g/L of ammonium sulphate ((NH4)2SO4) (Mishima et al. 2008).
Microorganisms
The yeast Saccharomyces cerevisiae Y-2034 (Wang et al. 2012) was maintained in a YPD medium (yeast extract 1%, peptone 2%, and dextrose 2%). The cells were incubated to 30 °C over 48 h (Mishima et al. 2008; Mussato et al. 2011). The strain was cultured in flasks of 250 mL under anaerobic conditions and stirred at 150 rpm at 30 °C over 24 h to allow cell growth to the exponential phase, and the cells were suspended in the fermentation medium.
Methods
Fermentation process
The fermentation process was carried out with three different reducing sugar concentrations of 26.486 g/L, 49.043 g/L, and 68.535 g/L, according to one factor design (Design Expert Software Version 7.0.0, Stat-Ease, Inc. Minneapolis), by triplicate in a flask of 250 mL, pH 5, and temperature of 30 ºC (Reddy and Reddy 2011) with constant stirring at 150 rpm over 16 h. The volume used for the fermentations was 150 mL, with an initial cell concentration of 1.0 x 106 ufc/mL (Pratten 1981). Culture samples of 1 mL were taken at the end of the fermentation process and centrifuged at 10,000 rpm for 10 min at 5 ºC. The supernatant was filtered through a 0.22 m filter (Millipore, Bedford, MA, USA). After it was filtered, it was stored at -20 ºC for later analysis by HPLC.
Analytic methods
During the fermentation, the reducing sugar concentration was determined by the Miller method (Miller 1959). Viable cell counts were measured with a Neubauer chamber adapted with optical microscopy (Pereira et al. 2010), and trypan blue dye was used on the vital cells (Tolnai 1975). Bioethanol concentration was determined with a pycnometer method through densities verified with HPLC, using a column (Phenomenex, Inc. USA) eluted at 60 °C with 0.0025 M H2SO4 at a flow rate of 0.5 mL/min and having a refractive-index detector.
Pycnometer method
A clean dry pycnometer was used for the next step with a capacity of 50 mL and a constant weight for each of the measurements. To prepare the medium used as a blank, it was necessary to obtain a flask fermented with the features described above (fermentation process). After the fermentation process, the alcohol formed in the fermentation medium from coffee mucilage was evaporated at 78 °C, cooled to 20 °C, and centrifuged at 10,000 rpm for 15 min at 5 °C. The supernatant was used as blank. For the calibration curve (Fig. 1), ethyl alcohol (99.9%) was added in the blank to have concentrations of ethanol from 0 to 50 g/L; the weights and densities determined by an analytical balance and a pycnometer were calculated at 20 °C.
To determine the concentration of ethanol in the fermentation, a sample of medium was taken, and centrifuged at 10,000 rpm for 15 min at 5 °C. The supernatant was changed to a new tube, and the precipitate was discarded. Each of the densities was determined at 20 °C, and the ethanol concentration was calculated from the calibration curve (AOAC 1990).
Density was calculated using the following equation:
where is a density, m1 pycnometer + sample mass, m0 is pycnometer mass, and v is pycnometer volume.
Comparison of two experimental means
The results from a new analytical method can be contrasted by comparison with those obtained using a second method. In this case we have two sample means. The null hypothesis defines that the two methods provide the same result. In other words H0: 1 = 2. It is necessary to test whether (y1 – y2) values differ significantly from zero. If the two samples have standard deviations that are not significantly different, then a joint estimation of the individual standard deviations s1 and s2 is carried out (Miller and Miller 2002).
For one to decide if the differences between two samples means, y is significantly different i.e., for it to contrast the null hypothesis, H0: 1 = 2, one has to calculate the t statistic:
where n is remarks and s calculated from:
And t has n1+ n2 – 2 degrees of freedom.
RESULTS AND DISCUSSION
Determination of Bioethanol Concentration
In Fig. 1 the curve calibration is given with a coefficient of determination of 0.997. This was used to determine the bioethanol concentration in the fermentation step.
Fig. 1. Calibration curve using coffee mucilage as medium
Table 1 shows the values for initial and consumed sugar amounts, bioethanol concentrations determined by the pycnometer method and HPLC technique, and their respective standard deviations.
Table 1. Bioethanol Production from Coffee Mucilage
The sugar consumption was higher than 90%, and the yields of sugar in bioethanol were 45.345%, 37.198%, and 37.677% grams of bioethanol per grams of initial sugar. The fractional or relative yields were 88.740%, 72.794%, and 73.731% with initial sugar concentrations of 26.486 g/L, 49.043 g/L, and 68.535 g/L respectively. So a lower initial sugar concentration resulted in a higher yield (Fig. 2).
Fig. 2. Initial sugar concentrations (○), yields (△), and fractional yields (□), Pycnometer method
The results from the study of a new analytical method can be contrasted by comparison with those obtained using a second method as a reference. There are 4 degrees of freedom for all cases, so that the critical value is t4 = 3.36 (P=0.05). The observed values were t (= 1.130, 1.532, and 1.418) which were less than the critical value, thereby accepting the null hypothesis. The two methods provided the same result. It was also shown that P (t>1.130) = 0.322, P (t>1.532) = 0.200, and P (t>1.418) = 0.229. Since these probabilities are greater than 0.05, the result was not significant at the 5% level; in other words, (x1 – x2) was not different from zero.
The F contrast for comparison of standard deviations was used to determine whether the methods differed in their precision, resulting in F2,2= 19. The calculated value was less than this (Table 2), so there was no significant difference between the two variances at a level of 5%.
Table 2. F Contrast: Two Samples Supposing Same Variances
The equation describing the relationship shown in Fig. 3 is as follows:
Fig. 3. Function describing equation 1 for the sugar concentration against the bioethanol concentration (Design Expert 7.0.0)
The analysis model to one factor design was significant. There was only a 0.01% chance that a model F-value this large could occur due to noise. Values of P > F less than 0.0500 indicate that the model terms are significant. In this case, x12 and x1 were significant model terms. The adequacy of the models was expressed by the coefficient of determination (R2), which was very close to 1.0 for determination of bioethanol concentration.
CONCLUSIONS
1. This study established and developed a methodology to determine bioethanol concentration from coffee mucilage by a pycnometer method that was verified with HPLC.
2. Initial sugar concentrations of 26.486 g/L, 49.043 g/L, and 68.535 g/L generated yields of 0.453, 0.371, and 0.376 grams of bioethanol per gram of initial sugar and fractional or relative yields of 88.740%, 72.794%, and 73.731%, respectively.
3. According to significance tests comparing the two experimental means, the pycnometer method and HPLC provided the same bioethanol concentration (pycnometer method: 12.010 g/L, 18.242 g/L, and 25.821 g/L; HPLC: 11.146 g/L, 17.570 g/L, and 24.776 g/L) with joint variances of 2.269, 0.242, and 0.112 to three different tests with initial sugar concentrations of 26.486 g/L, 49.043 g/L, and 68.535 g/L, respectively.
4. The pycnometer method proposed here is an alternative way to quantify bioethanol concentration in a fermentation medium when there is a lack of sophisticated equipment, such as is needed for HPLC.
ACKNOWLEDGMENTS
The authors are grateful for the support of the Consejo Nacional de Ciencia y Tecnología (CONACYT project INF224765) and the Agroindustrial and Energy Engineering Laboratory at the Universidad Politécnica de Chiapas.
REFERENCES CITED
AOAC. (1990). “Official Methods, 945.06,” Official Methods of Analysis of the Association of Official Analytical Chemists. Fifteenth edition.
Breisha, G. Z. (2010). “Production of 16% ethanol from 35% sucrose,” Biomass and Bioenergy 34, 1243-1249. DOI: 10.1016/j.biombioe.2010.03.017
Chuck-Hernandez, C., Perez-Carrillo, E., and Serna-Saldivar, S. O. (2009). “Production of bioethanol from steam-flaked sorghum and maize,” Journal of Cereal Science 50, 131-137. DOI: 10.1016/j.jcs.2009.04.004
Cortright, R. D., Davda, R. R., and Dumesic, J. A. (2002). “Hydrogen from catalytic reforming of biomass-derived hydrocarbons in liquid water,” Letters to Nature 418, 964-967. DOI: 10.1038/nature11891
Ferreira, S., Gil, N., Queiroz, J., Duarte, P., and Domingues, F. C. (2010). “Bioethanol from the Portuguese forest residue Pterospartum tridentatuman – An evaluation of pretreatment strategy for enzymatic saccharification and sugars fermentation,” Bioresource Technology 101(20), 7797-7803. DOI: 10.1016/j.biortech.2010.05.038
Huang, Y., Jin, Y., Fang, Y., Li, Y., and Zhao, H. (2013). “Simultaneous utilization of non-starch polysaccharides and starch and viscosity reduction for bioethanol fermentation from fresh Canna edulis Ker. tubers,” Bioresource Technology 128, 560-564. DOI: 10.1016/j.biortech.2012.09.134
Karagöz, P., Rocha, I.V., Özkan, M., and Angelidaki, I. (2013). “Alkaline peroxide pretreatment of rapeseed straw for enhancing bioethanol production by Same Vessel Saccharification and Co-Fermentation,” Bioresource Technology 104, 349-357. DOI: 10.1016/j.biortech.2011.10.075
Lachenmeier, D. W., Godelmann, R., Steiner, M., Ansay, B., Weigel, J., Krieg, G. (2010). “Rapid and mobile determination of alcoholic strength in wine, beer and spirits using a flow-through infrared sensor,” Chemistry Central Journal 4, 1-10. DOI: 10.1186/1752-153X-4-5
Liebmann, B., Friedl, A., and Varmuza, K. (2008). “Determination of glucose and ethanol in bioethanol production by near infrared spectroscopy and chemometrics,” Analytica Chimica Acta642(1), 171-178. DOI: 10.1016/j.aca.2008.10.069
Miller, G. (1959). “Use of dinitrosalicylic acid reagent for determination of reducing sugar,” Analytic Chemistry 31(1), 426-428. DOI: 10.1021/ac60147a030
Miller, J. N., and Miller, J. C. (2002). Estadística y Quimiometría para Química Analítica, 4th Ed., Trans. C. M. Jimenez and R.I. Hornillos, Prentice Hall, Madrid, pp. 286.
Mishima, D., Kuniki, M., Sei, K., Soda, S., Ike, M., and Fujita, M. (2008). “Ethanol production from candidate energy crops: Water hyacith (Eichhornia crassipes) and water lettuce (Pistia stratiotes),” Bioresource Technology 99(7), 2495-2500. DOI: 10.1016/j.biortech.2007.04.056
Mussato, S. I., Machado, E. M., Carneiro, L. M., and Teixeira, J. A. (2011). “Sugars metabolism and ethanol production by different yeast strains,” Applied Energy 92, 763-768. DOI: 10.1016/j.apenergy.2011.08.020
Oliver, J. D., Gaborieau, M., Castignolles, P. (2014). “Ethanol determination using pressure mobilization and free solution capillary electrophoresis by photo-oxidation assisted ultraviolet detection,” Journal of Chromatography 1348, 150-157. DOI: 10.1016/j.chroma.2014.04.076
Pereira, F. B., Guimarães, P. M., Teixeira, J. A., and Domingues, L. (2010). “Optimization of low-cost medium for very high gravity ethanol fermentations by Saccharomyces cerevisiae using statistical experimental designs,” Bioresource Technology 101(20), 7856-7863. DOI: 10.1016/j.biortech.2010.04.082
Piccolo, C. and Bezzo, F. (2009). “A techno-economic comparison between two technologies for bioethanol production from lignocellulose,” Biomass and Bioenergy 33(3), 478-491. DOI: 10.1016/j.biombioe.2008.08.008
Pratten, N.A. (1981) “Review, The precise measurement of the density of small samples,” Journal of Materials Science 16(7), 1737-1747. DOI: 10.1007/BF00540619
Rangel, A. O. S. S., and Tóth, I. V. (2000). “Enzymatic determination of ethanol and glycerol by flow injection parallel multi-site detection,” Analytica Chimica Acta 416, 205-210.
Reddy, L. V. A., and Reddy, O. V. S. (2011). “Effect of fermentation conditions on yeast growth and volatile composition of wine produced from mango (Mangifera indica L.) fruit juice,” Food and Bioproducts Processing 89, 487-491. DOI: 10.1016/j.fbp.2010.11.007
Rotariu, L., Bala, C., and Magearu, V. (2004). “New potentiometric microbial biosensor for ethanol determination in alcoholic beverages,” Analytica Chimica Acta 513, 119-123. DOI: 10.1016/j.aca.2003.12.048
Shih, C. J., and Smith, E. A. (2009). “Determination of glucose and ethanol after enzymatic hydrolysis and fermentation of biomass using Raman spectroscopy,” Analytica Chimica Acta 653, 200–6. DOI: 10.1016/j.aca.2009.09.012
Tolnai, S. (1975). “A method for viable cell count,” Methods in Cell Science 1(1), 37-38. DOI: 10.1007/BF00914435
Vučurović, V. M., and Razmovski, R. N. (2012). “Sugar beet pulp as support for Saccharomyces cerivisiae immobilization in bioethanol production,” Industrial Crops and Products 39, 128-134. DOI: 10.1016/j.indcrop.2012.02.002
Wang, M., Choong, Y., Su, N., and Lee, M. (2003). “A rapid method for determination of ethanol in alcoholic beverages using capillary gas chromatography,” 11, 133-140.
Wang, W., Zhuang, X., Yuan, Z., Yu, Q., Qi, W., Wang, Q., and Tan, X. (2012). “High consistency enzymatic saccharification of sweet sorghum bagasse pretreated with liquid hot water,” Bioresource Technology 108, 252-257. DOI: 10.1016/j.biortech.2011.12.092
Article submitted: December 2, 2014; Peer review completed: March 1, 2015; Revisions accepted: March 10, 2015; Published: March 16, 2015.
DOI: 10.15376/biores.10.2.2691-2698