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In this study, kinetics of bioethanol production by fermentation of three different substrates, which were artificial substrate and the juice of two sweet sorghum varieties FS and KCS using Saccharomyces steineri, were examined using two proposed models by assuming that simultaneous hydrolysis and fermentation occured. As the consequence, sucrose hydrolysis seems very dominant in the FS and KCS juices fermentation during the lag phase.
Fermentation of the substrate of FS and KCS juices showed better data fitting by using the modified version of the kinetics model while the fermentation of artificial substrate which was free of any other components followed Philippidis’s kinetics model. The change of behavior of the yeast was estimated being caused by the existence of “impurities” such as acetic acid, glycerol, nitrogen, phosphor, and potassium in the FS and KCS juices. From statistical analysis using correlation coefficient between kinetics parameters and “impurities”acetic acid was the most influential component to change the behavior.
Introduction Fluctuation of the world crude oil price  and environmental concern of greenhouse gas emission have promoted the attraction over biofuel as the alternative renewable energy resources. However, a complete substitution of petroleum-derived fuels by biofuel recently is still impossible from the production capacity and engine compatibility point of views. Yet, marginal replacement by biofuel can remarkably reduce the dependency on the petroleum resources and abate the radical climate change caused by automotive pollutants .
Incremental vehicle technology options, such as bioethanol-supported vehicle with 85 percent bioethanol mixed with 15 percent gasolinecan reduce the greenhouse gas GHG emissions to to grams per mile or to about 65 to 74 percent of the emission levels expected from future gasoline-supported vehicles .
This signifies the importance of bioethanol to reduce carbon footprint in energy fulfillment distribution throughout dlaam world, which could be seen from Fig. World primary energy demand by fuel in sek Biofuel is undergoing a revolution in terms of technological aspect. As the development of technology continues to rise, the demand of bioethanol-powered fuel keeps proliferating . With all current government programs for renewable energy development in America, Asia, glikolisie Europe, the total demand of bioethanol for fuel could exceed billion liters by .
Bioethanol can be produced from either various biomasses or various natural resources. A number of agricultural crops, such as wheat, corn, sweet sorghum, sugarcane molasses, sugar beet, and sweet potatoes  not only provide foods , feeds , and fibers  but also produce sugars which can be converted to alcohol that can subsequently be used as energy sources.
Utilization of sweet sorghum as the source for bioethanol production offered more advantages compared to other resources: Sorghum production also boosted the utilization ralam dry lands which is unsuitable for corn or cane production. These make sorghum is highly suitable to be developed in the region se the dry and hot climates such as Southeast Asia, Middle East, and Africa. To create an effective method to produce bioethanol from sweet sorghum, both good and comprehensive understanding about reaction mechanism and kinetics model are required.
Kinetics modeling of sucrose hydrolysis is an important tool in estimating the rate of hydrolysis by the microorganism’s enzymes and the rate of fermentation by the sek itself .
Consequently, kinetics modeling of simultaneous hydrolysis and fermentation SHF process is a powerful step toward industrialization of bioethanol production from sweet sorghum due to the fact that concepts establishment of production process totally DOI: Moreover, decent kinetics model and reliable model parameters are necessary to optimize the performance of SHF process.
Several kinetics models had been developed since the past years but it was to explain the production mechanism of bioethanol from lignocellulose through simultaneous saccharification and fermentation SSF process [15,16,17].
In this study, sl model of a batch SHF process was developed to incorporate the g,ikolisis of substrate composition of the juice of different sweet sorghum varieties. Evaluation of kinetics models and kinetics parameters correlation to the various substrate composition helps to obtain a comprehensive understanding of which model can be applied to a wide range of substrate compositions.
The comprehensive understanding was made due to the possibility of sweet sorghum juice to contain minerals which can be the group of required macronutrients or micronutrients by the yeast or the inhibiting component to the yeast growth.
The effect of mineral existence in the juice to the growth of the yeast and to the bioethanol production was studied by comparing the hydrolysis and fermentation process of sweet sorghum juice of two varieties FS and KCS to glikolisiz artificial substrate which was comprised of sucrose, glucose, and fructose of certain concentration.
Therefore, in this study, the best kinetics model and its parameters were estimated by fitting the models to experimental data using numerical completion method. Afterward, the correlation of the obtained kinetics parameters with the mineral content of ssel substrate was verified through statistical methods named correlation coefficient . Kinetics modelling of SHF Simultaneous hydrolysis and fermentation SHF of sweet sorghum juice is a multi-step process and interactions between enzymes inside the yeast and the sophisticated substrate.
In addition, SHF also undergoes mechanisms by the product and other components inside the substrate. glikolisos
dalsm The process, interactions, and as well as inhibition mechanism of SHF are not fully understood. A modified kinetics model based on those reported by Philippidis  and Shadbahr . However, the original version of kinetics model by Philippidis  was also used for the comparison. The kinetics model assumes that the yeast both consume and hydrolyze the sucrose into glucose and fructose. The rate of sucrose hydrolysis is shown on Eq.
The reaction pathway for the biochemical conversion of sucrose is supposed to follow the pathway shown by Fig. Pathway of simultaneous hydrolysis and fermentation of sweet sorghum juice The microbial growth is a very sophisticated phenomenon, nonetheless, the overall microbial growth can often be considered as one single chemical reaction with a simple rate expression.
The dlam idea is that the growth accumulation is the subtraction of bacteria growth and bacteria death. There are two different kinetics models proposed to explain the growth mechanism of the yeast as shown by Eq. Growth rate equation of yeast adopted from Philippidis : Growth rate equation of yeast adopted from Philippidis  with modification: In this wel, the concentration change over the time of both substrates and products were described using specific yield coefficient and maintenance constant for each component gliko,isis shown in Eq.
The equation for SSE was formulated using weighting factor as shown by Eq. The weighting factor for each component aims to equalize the order of the experimental data by dividing the average of experimental data of the component whose order is the highest by the average of experimental data of the related component . Materials and Methods 3. The two sweet sorghums were obtained from municipal government plantation area in Kricak Village, Yogyakarta, Indonesia. The estimated influencing mineral rwgi in the sweet sorghum juices were nitrogen, phosphor, and potassium Dakam.
All of the chemicals for NPK analysis were supplied from Merck. Inoculum were prepared by culturing each strain in a medium containing 2. Fermentation media were prepared by mixing the materials with the composition of 2. While for the others, the fermentation media consisted of the sweet sorghum juice, 0. Fermentation was begun by adding a certain volume of inoculum to the one liter sterilized fermentation jars to achieve the cell density of 3.
Afterward, mL of fermentation media were also added and were mixed aseptically. During SHF experiment, solution pH and temperature were monitored. The pH level was adjusted by NaOH solution. For analytical routines, samples taken at a certain time were refrigerated in the refrigerator with a temperature of oC before being analyzed. The nitrogen content in the sweet sorghum juice was determined using Kjeldahl method as explained by AOCA .
This method was adapted according to the original works of Hoft  and Kirkbright . It can be applied for determination of phosphates, phosphoric acid or total phosphorus in water samples, biological materials or food and beverages.
The potassium analytical method using atomic absorption spectroscopy was adapted from the literature  Analysis of sugars and ethanol was performed using an HPLC system Knauer smart line RI detectorGermany with a column of Aminex HPXC x 7.
Injection volume is 20 L and mobile phase was deionized water at flow rate of 0. The recorded concentration of sugars and ethanol over the time would be fitted by the proposed kinetics models.
Bmd – Glikolisis & Siklus Krebs
Yeast cell concentration was determined indirectly by measuring the optical density absorbance of a culture sample . A sample of the culture medium from the fermenter was taken and read its absorbance using spectrophotometer.
Up to a certain cell density, the concentration of yeast cells in the sample is proportional to the absorbance reading on the spectrophotometer. The calibration curve correlating cell concentration with absorbance deviates from a linear correlation at high cell densities. Thus, the high optical density OD samples that may be on the non-linear portion of the curve are usually diluted by a known dilution factor to confirm that the measured OD values fall on the linear portion.
Results and Discussion 4. From two sweet sorghum juices of two different varieties, there were similarities of other component’s peaks detected. The components were glycerol and acetic acid. The presence of acetic acid and glycerol was estimated to be a potential inhibitor for the yeast during its growth and during bioethanol production.
The trend was also similar of which the K2 O content was the highest followed by P2 O5 content and N content. The existence of NPK in the fermentation media was useful to fulfill the nutrient need of the yeast during the growth phase.
The previous work by Batista  explained that the increasing nitrogen supply using extruded bean could improve the S.
However, the increase of nitrogen supply had its limit since the P. Therefore, it is suggested that there was a maximum nitrogen concentration to enhance the yeast growth.
The increase of nitrogen supply to the fermentation media was also usually limited by the phosphor concentration. The previous work by Camenzind  showed that high concentration of both nitrogen and phosphor did not give the good effect to the microbial growth of fungi.
It was preferred that the concentration of phosphor was much lower than nitrogen in the fermentation media. Potassium is an important ion that affects the growth and survival of living cells [30,31].
NPK content in the sweet sorghum juices 0. As previously explained, the difference between the two models proposed was at the growth rate equation of the yeast.
It was surprisingly followed by the consistently decreasing trend of glucose and fructose concentration change over time see Fig.
Fermentasi Aaerob by bgs ard on Prezi
By referring the reaction pathway as shown by Fig. Another interpretation could be made from the experimental data was the characteristic of the yeast. From the slope of the peak shown by Fig. This indicated that Saccharomyces steineri has glucophilic characteristic, which is similar to the previous glikolsiis of Tronchoni  which mentioned that in general, the strain of yeast was glucophilic.
From the bioethanol productivity aspect, the ethanol production profile over the time followed the profile of the yeast growth. The productive period was certainly during the log phase of the yeast growth period. Experimental data fitting using two proposed kinetics models of artificial substrate fermentation for: However, the quantitative approach using SSE showed that kinetics models used by Philippidis  in the previous work could fit the experimental data better in the fermentation of artificial substrate into bioethanol using Saccharomyces steineri.
This is glikolisiw by lower SSE value for each component see Table 2. The fermentation of KCS juice showed different result from the fermentation of artificial substrate. The difference existed on the profile of fructose concentration over the time which was firstly increasing before it decreased glikolisiw see Fig.
This indicated that the sum of the rate of fructose consumption and the rate of fructose conversion into bioethanol was slower than that of glucose. Therefore, the yeast behaved differently when it grew in a different substrate but nevertheless, the result of KCS juice fermentation proved that Saccharomyces steineri was glucophilic.
The interesting result of the KCS juice fermentation was the productivity of the bioethanol see Fig. The ethanol concentration reached