The oscillatory behavior that has been demonstrated numerically and experimentally by several workers ad- versely affects the fermentation process and the ethanol production. Hence one must develop strategies to avoid or eliminate the oscillations. Reference  recently compu- tationally demonstrated some techniques for eliminat- ing oscillations in fermentation processes involving both Zymomonas mobilis and Saccharomyces cerevisiae. Spe- cifically, it was shown that in the case of the Saccharo- myces cerevisiae fermentation that a small increase in the input oxygen concentration would eliminate the oscilla- tion causing Hopf bifurcation. This increase in oxygen mass transfer can also be observed if the mass transfer coefficient for the oxygen mass transfer can be enhanced. Recently, [2,3] investigated the use of functionalized magnetic nanoparticles with flourinated polymer coating to enhance oxygen mass transfer in bioreactors. The
Abstract: There are several types of experiments which require statistical investigation. These are characterized by the nature of treatments under investigation and also the nature of comparison required among them so as to meet the objectives of the experiment. To achieve this, cassava peels was collected from Kasuwa Gwari market Minna, Niger state dried and taken for hydrolysis and fermentation processes. Temperature, acid concentration, cassava biomass ratio, ph and time were varied to get the optimum yield of reducing sugar. Curve fitting and a two-way analysis of variance were used in analyzing the data. Most of the results from the experiment follows quadratic model. Furthermore, time and temperature were very significant in both hydrolysis and fermentation processes. We therefore concluded that for hydrolysis process yield is optimum at 110°C and 30mins, while for fermentation process yield is optimum at 35°C and at 6 days and 7 days respectively.
The model-based feed-rate optimization task is solved by applying the parametric optimization approach  and the evolutionary programming algorithm . Referring to investigation results of different shape feed-rate time-profiles used for model- based optimization of various fermentation processes , we applied in the parametric optimization procedure the exponential-type feed-rate time profile, which requires a modest number of parameters to be optimized and provides with good approximation of optimal feed-rate. The structure of the feed-rate control algorithm is as follows:
When whole cells are used as template source, another issue associated with PCN quantification in fermentation processes, is the proper determination of the quantifica- tion range in order to avoid inhibition and stochastic var- iation. Clearly, these two effects are more pronounced when whole cells are used instead of pure DNA, as a result of the complexity of the samples and the size of bacteria. We found that at least 100-fold dilution of samples was enough to prevent inhibition. The possibility of inhibi- tion should be checked in all experiments which employ different media. The stochastic effect does not appear if more than 100 cells are used per reaction. Furthermore, the method has to be adapted to a broad range of optical density of bacterial culture and broad range of PCN in order to be applied for monitoring a real fermentation process. The fermentation process starts at a low PCN (e.g., around 5–10 in the inoculum) and low OD in the early lag phase and ends up with a high PCN (e.g., 50–150 in the log phase) and high OD. This actually means that different sample dilutions have to be used for various parts of the bacterial growth curve, i.e. for low PCN sam- ples one set of dilutions can be used and for high PCN samples another level of dilution has to be employed. The calculation used in the presented study is only possi- ble using SYBR Green detection chemistry since fluores- cence generated by amplicons of about the same size is equal. There are some advantages in using SYBR Green detection chemistry as it can reveal the presence of primer dimers and non-specific products. Furthermore, SYBR Green is less expensive than alternatives and the costs are further lowered by adapting the assay to a 10 μL reaction.
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The MBP was observed to be 551.02, 506.57,451.50 (g/kg DM) and 397.15 at 0,0.5,1 and 2 µl/ml level of EO respectively. The three treatments of EO showed a significant decrease (p < 0.01) in MBP with control and each other. In respect to various levels of EO viz.,0,0.5, 1 and 2 (µl/ ml) in CF-1, TDDM was recorded 630.25,567.35,508.70 and 449.75(g/kg DM); TDOM to be 607.12, 545.17, 477.47 and 417.50 (g/kg DM); and TDNDF to be 384.8,280.12, 182.52 and 84.70 (g/kg DM) respectively. A significant decrease (p < 0.01) in TDDM, TDOM and TDNDF was shown by three treatments of EO when compared with control.The OMD percentage was observed to be 43.67, 36.60, 31.47 and 29.22 at 0,0.5,1 and 2 (µl/ml) levels of EO respectively. While comparing the effect of three different levels of EO on OMD percent with control,the OMD percent was found to decrease significantly (p < 0.01). A nonsignificant decrease in OMD percent was found after 1 µl/ml of EO, when the three treatments were compared with each other. The effects of adding various levels of EO on CF-1 related to fermentation are given in table 4. The effect of adding various levels EO(EO) in CF-1 on concentration of NH 3 - N and total N are shown
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Succinic acid, which is also known as butanedioic acid, 1,2-ethanedicarboxylic acid and amber acid, occurs in nature as such or in various forms of its esters. Before the development of fermentation processes for its production, succinic acid was manufactured by catalytic hydrogenation of maleic anhydride, which is a fossil-based chemical. Traditional applications of succinic acid include food additives, detergents, cosmetics, pigments, toners, cement additives, soldering fluxes, and pharmaceutical intermediates. In the past, succinic acid had a relatively small market size. It was estimated that the annual total world production in 1990 was between 16,000 and 18,000 metric tons (MT) . Production of succinic acid from renewable feedstocks started to gain attention due to the increasing oil prices, dwindling oil supplies, and most importantly, the potential of converting succinic acid to a range of industrial chemicals with very large markets, such as 1,4-butanediol and other organic solvents. As an intermediate of several biochemical pathways, succinic acid is produced by many microorganisms. In fact, it is one of the metabolic co-products of ethanol fermentation by the yeast Saccharomyces cerevisiae in addition to glycerol, lactic acid, and acetic acid. The challenge of producing succinic acid biologically at commercial scale and potentially for the commodity chemical market
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The liquid product stream of dark fermentation processes consists of a mixture of VFA with different compositions. In the vast majority, the dominant acid in these mixtures is acetic acid, followed by propionic acid (Table 1). Acetic acid seems to have a higher value as a product, since it is more easily consumed by several microorganisms . However, since it is classified as a hazardous pollutant for the environment, its production through dark fermentation needs to be justified by its utilization as a raw material for the production of high added-value products. The composition of the acid fraction of the liquid product depends on various variables, like the type of waste stream used and the fermentation conditions (pH, fermentation time, etc.) [1,28]. The pH value for example plays an important role in the synthesis of different VFA. It has been reported in the literature that, during the fermentation of a synthetic gelatin wastewater, pH values between 4.0–5.0 favors the production of propionic acid, while a pH around 6.0–7.0 favors the production of acetic and butyric acid, instead . Chen et al. also noticed that, during the fermentation of a mixture of primary and waste activated sludge, the proportion of acetate increased when the pH increased from 7.9 to 8.9 .
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The change of aflatoxin B1 (AFB1) content during must fermentation processes in different white, rosé and red musts was investigated, using selected yeast strains of Saccharomyces cerevisiae as starter cultures. Levels of AFB1 in must and lees were determined by high-performance liquid chromatography (HPLC) combined with diode array detection (DAD). Reductions of the AFB1 content between 77% - 97% were recorded after 90 days must fermentations in the model sys- tems, while the relative adsorption level of AFB1 in lees was around ~0.63 in case of white wines, ~0.41 in case of rosé wines and ~0.23 in case of red wines. The results show that even extremely high AFB1 levels do not affect the fermentation process and the life-circle of yeast strains. The concentration of AFB1 in wine can be controlled by using appropriate yeast strains during the al- coholic fermentation.
The performance of the PEM-based robust optimization framework is also demonstrated with a fermentation process as illustrated in Fig. 11. Fermentation processes have received great interest in the pharmaceutical industry, and in this study, we try to optimize the penicillin fermentation . To this end, we design a feeding substrate profile that ensures the optimal performance and robustness of the bioreactor. A fed-batch reactor model is used based on the following assumptions: 1) ideal mixing of all components in the bioreactor, 2) isothermal condition in the reactor, and 3) the effect of the oxygen transfer can be neglected by considering an upper limitation on the biomass and substrate concentrations. The mathematical model for the fermentation process reads as:
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However, the chemical structure of diluent may also have various effects on the formation of acid-amine complexes. The literature related to the fermentation processes for the production of carboxylic acids and the reactive extraction for recovery of the carboxylic acids (lactic acid, citric acid, tartaric acid, acetic acid, and propionic acid, etc.) from fermentation broth and aqueous waste stream is extensively reviewed. These studies focus on various aspects such as solvent (extractant and diluent) selection, effects of temperature, pH, aqueous and organic phase compositions on extraction, in-situ product recovery, and chemical interactions involved in the complexation of acid with the extractant, kinetics of extraction, etc.
Among all the Evolutionary Algorithms (EAs), Genetic Algorithms (GAs) have placed a much stronger emphasis than their counterparts on global, as opposed to local, search and optimization. Since its emergence, GAs have been successfully applied in various fields and have been used to solve many control engineering problems such as optimal controller tuning, robust stability analysis, system identification and fuzzy control. In all the applications of EAs to the optimization of fed-batch fermentation processes, it is found that GAs have attracted the most interest . While many applications have only considered using a single manipulated variable, i.e. the feed rate, to optimize a single objective – the production, multi-objective optimization and multivariable problems have also been addressed . All the successful applications of GAs to the optimization of fed-batch fermentation processes have demonstrated GAs can successfully be used within an optimal online control scheme. However, in doing so, customized genetic operators and encoding methods should be designed to fit for any particular application.
The influence of benzoic acid and formic acid (positive control) of ensilaged maize and pressed sugar beet pulp on quality fermentation processes was studied in a laboratory experiment. The effect of addi- tive on the quality of fermentation process during maize ensiling was studied in a first model experi- ment. Preservatives such as formic acid and benzoic acid were added to ensiled maize at the concen- tration of 1L/t and 1 kg/t, respectively. when benzoic acid was used as a preservative, the pH and the N-NH 3 / N total ratio decreased statistically (P<0.05) significantly while the titration acidity increased (P<0.05) in comparison with the control values. The addition of HCOOH to the maize silage reduced the level of acetic acid in dry matter by 11.3% while the overall level of acids decreased by 1.8%. The minimum loss of dry matter (2%) was found in the silage treated with formic acid in comparison with that of the control (11.0%).
Saccharomyces genus, as reported by other authors (Martini, 1993; Pretorius, 2000), was observed at low frequency, only 6.25% (Table 3). According to Barata et al. (2012), this yeast, despite being very utilized in fermentation processes of wine production, is isolated in a smaller number when a direct isolation technique is used, suggesting that it is less frequent in grape carposphere. According to Fleet (1999), the number of fermentative yeasts such as Saccharomyces spp is greater when the grape skin is damaged, releasing its content to the grape carposphere, resulting in a population increase of 10 6 to 10 8 CFU/g when compared to undamaged grapes.
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In brewing yeast may be reused for fermenta- tion several times. However, after a certain time deterioration of cropped yeast is observed and a newly propagated yeast culture has to be applied. Lower yeast slurry quality is directly related to poorer fermentation performance and consequently to lower quality of final beer. Alterations in fer- mentation performance can already be assessed by the measurement of attenuation, which provides information on the extent to which wort sugars can be used. It describes yeast ability to reach a certain attenuation limit.
3) Influence of Initial pH: The initial pH factor has significant influence on bioethanol fermentation. To observe the influence of pH on the quantity of ethanol, the experiments were carried out fermentation period of 24 hour at 37oC. The pH value of mango peel samples was varied 4.0-6.0 with an increment of 0.5. Fig.4 shows the variation of ethanol content (%) produced with PH. The ethanol content was least of at pH~4.5 and increased to reach the highest value at pH~4.5. At this pH, the pH different is lowest (ΔPH=0.5). However, keep increasing pH to 6.0, the ethanol content significant decreased. The important reason is the optimum initial pH for the growth of yeast is about 4.5-6.0, and the most appropriated pH for cellulose activity is about 4.5-5.5. The lower activities of yeast towards bioethanol fermentation are shown at a pH of 4 because these pH values are too low to activate the of yeast to run their functions.
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Preparation and monitoring of windrows. The study was performed in a semi-industrial pilot plant and using two types of windrow W1 and W2. The process of com- posting proceeds in two successive separately steps: pre-fermentation (uncontrolled fermentation) and matu- ration (controlled fermentation), and with two different raw composting materials: municipal solid waste from the Erriadh city of Beja were pre-selected at source (household pre-selection with average physical-chemical characteristics, humidity = 60%, organic matter = 30% dry weight, and C/N = 32) and dry sewage sludge (stabi- lized from anaerobic digestion of the urban wastewater treatment plant of Beja was integrated in the process at the dry state (with average physical-chemical character- istics, humidity = 30%, organic matter = 65% dry weight,
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Five microorganisms were identified from the spontaneous (traditional) fermentation of ogi from maize raw material. They include: Lactobacillus plantarum, L. brevis, Candida sp., Aspergillus niger and Penicillium notatum. Their frequency of occurrence is shown in Table 1. The lactic acid bacterial groups were prevalent through out the spontaneous fermentation of ogi while Candida yeast was detected at the later stage of the fermentation (72h) and then remained till the end of the fermentation. The fermentation decreased the number of moulds after their initial increase with in the first 24h of steeping.
DOI: 10.4236/jbm.2018.66008 109 Journal of Biosciences and Medicines company, we urgently need to know the optimum fermentation time of flue-cured tobacco. But so far, no one or any studies have shown how to determine the op- timal fermentation time for flue-cured tobacco. Most companies still rely on sensory quality reviews. This is obviously not very scientific. The best fermenta- tion period of tobacco is the best period for tobacco to enter into formula utili- zation. The industrial judgment method on the best fermentation period of to- bacco still gives priority to sensory evaluation   . Sensory evaluation is easy to be affected by artificial subjective influences. The accuracy and repro- ducibility are weaknesses. It is urgent to use a chemical detection means to do auxiliary judgment on the best fermentation period of tobacco.
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In general, the SPORL pretreated whole slurry C-t60 was quite sterile. However the pretreated FS-10 sample has been stored in a cold room for quite a few months. It is worth studying whether or not sterilization help ethanol productivity. The SSF results clearly showed a lagging phase within the first 12 h for the fermentation run without sterilization (Figure 3c). Glucose consumption was much faster when the sample was autoclaved at 121 °C for 15 min. This perhaps due to the fact that growth of Saccharomyces cerevisiae YRH400 was suppressed by other microorganisms that existed in the sample. After 48 h, these microorganisms may not be able to survive due to elevated ethanol concentrations. The inoculated strain YRH400 became the dominant strain. As a result, terminal ethanol concentration at 96 h was not affected due to the lack of sterilization.
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The 14 processes (six for persimmon and eight for strawberry) were conducted under laboratory conditions in 8 L glass containers with a broad top hole of 10 cm in diameter. During alcoholic fermentation and acetification, this top hole was covered by a cloth to keep out insects, dust, etc. The glass containers were filled with 6 L of the initial pulp or liquid, leaving an air chamber of 2 L. To fill the containers in triplicate, a total of 50 kg of persimmon and 65 kg of strawberry was required. When strawberry was pressed, we required 9 L of crushed strawberry pulp to obtain 6 L of liquid. As a general criterion, alcoholic fermentation was considered to have finished when the sugar had been consumed (,2 g/L) and acetification finished when the ethanol concentration had fallen below 1% (v/v). All fermentations were done at room temperature (23 ± 3 ° C).