Browsing by Author "Tai, Siew L"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Open Access
    Enhanced bioethanol fermentation from mixed xylose and glucose using free and immobilized cultures: mathematical model and experimental observation
    (2019) Ghods, Nosaibeh Nosrati; Tai, Siew L; Harrison, Susan TL; Isafiade, Adeniyi J
    Bioethanol plays a significant role in the world of liquid biofuel. However, majority of bioethanol is produced from edible food crops such as corn and sugarcane that causes an increase in demand for vacant lands for food production and, subsequently, increase in the cost of food manufacturing. Therefore, alternative raw materials for bioethanol production are sought after, such as sugarcane bagasse which is a waste material from the sugar industry. South Africa, a net sugar exporter, has a large potential to produce bioethanol from sugarcane bagasse. This research focuses on the study of the production of bioethanol from glucose and xylose which are the two most abundant sugars in hydrolysed sugarcane bagasse. To date, no suitable wild type organisms can concomitantly ferment both glucose and xylose to ethanol efficiently. Options to address the co-fermentation of glucose and xylose include genetic modification of the selected microorganism to include both pathways - limitation in the understanding of the metabolic pathways regulations - or utilization of two microorganisms in co-culture or sequential culture e.g. Zymomonas mobilis and Pichia stipitis for efficient fermentation of glucose and xylose respectively. In this study, the dual micro-organism route is explored. There are numerous problems associated with co-culturing. Xylose, a non-preferred carbon source is only converted if the glucose concentration is adequately low due to catabolite repression. In order to increase xylose conversion, a low glucose concentration is required. Therefore, two stage sequential fermentation either in one or two reactors was tested. A high inoculum of suspended or immobilized Z. mobilis was inoculated in the first stage to convert the glucose rapidly. Varying reactor configuration, including the continuous fluidized bed, continuous stirred tank reactor (CSTR) and stirred batch reactor were considered. The products and residual substrate from this fermentation was then directed to a second stage, using either a CSTR or stirred batch configuration, with a high inoculum of P. stipitis in suspension culture for conversion of xylose. When immobilized, Z. mobilis was entrapped in calcium alginate beads. On the issue of ethanol tolerance, P. stipitis is generally more easily inhibited by ethanol (threshold ethanol concentration of 35 g L-1) compared to other ethanol producing strains such as Z. mobilis (threshold ethanol concentration of 127 g L-1) and Saccharomyces cerevisiae (threshold ethanol concentration of 118.2 g L-1). In order to overcome this, a continuous bioprocess was investigated to keep ethanol concentrations in Stage II below 35 g L-1 to prevent inhibition of metabolic reactions in P. stipitis. Further, ethanol fermentation by Z. mobilis requires obligate anaerobic conditions while xylose conversion by P. stipitis is optimum under microaerobic conditions. Therefore, oxygen was sparged into the second P. stipitis stage only. The following components were carried out in this project to improve the kinetic model and to find accurate kinetic data in the selected process of the two stage sequential fermentation. Firstly, where kinetic parameters were not available in literature, the kinetic parameter relationships of glucose and xylose utilization between different constructs of the same species were examined, for example, a wild type and engineered strain. This approach was used for glucose conversion using wild type Z. mobilis, owing to the ill-fit of available kinetic parameters with experimental results. In this study, the correction factors on estimated kinetic parameters from linear and non-linear regression when a xylose fermentation route was inserted recombinantly (S. cerevisiae RWB 217) into the native culture (S. cerevisiae CEN.PK 113-7D) were determined. From kinetic parameters of an engineered strain with the xylose-fermenting pathway (Z. mobilis ZM4 (pZB5)) and the correction factors, kinetic parameters of the wild-type Z. mobilis ZM4 were determined. Predicted rates of Z. mobilis ZM4 were then validated with experimental data generated in this study. Then, the optimum initial biomass concentration required to provide a faster volumetric rate of sugar utilisation and ethanol production, as well as the optimum oxygenation level for xylose conversion using P. stipitis achieved through appropriate aeration were investigated through experimental observation and using a MATLAB mathematical model developed through combination of the Andrews and Levenspiel's models, with oxygen, substrate, cell and product terms. Experiments were carried out to validate the kinetic model and data under anaerobic and microaerobic growth conditions in a batch process. The results showed that both increasing the initial biomass concentration (3 g L-1) and operating under optimum oxygenation levels (0.1 vvm) benefitted the ethanol production and yield by P. stipitis from xylose. It was also concluded that the addition of the oxygen effective factors in the developed model allowed for optimization of aeration in the fermentation system. Next, the custom kinetic model for fermentation process of bioethanol production was developed in Aspen Custom Modeller (ACM) and embedded in Aspen Plus. The model includes equations of vapour-liquid equilibrium (VLE), mass balance, and energy balance (e.g. molecular weight, thermodynamic phase equilibria, kinetic equation). The obtained results showed better agreement between industrial data and kinetic model (1% differences) than a stoichiometric model (9% differences). The simulation showed that ACM integrated into Aspen Plus allowed for complex biological processes to be accurately predicted for biomass growth, ethanol production and sugar consumption. Finding suitable microorganisms and process conditions for efficient glucose and xylose conversion is still currently a challenge and requires optimization. Therefore, this research focusses on improving the conversion of glucose and xylose to bioethanol, with specific emphasis on the fermentation systems used to maximize biomass efficiency, and ethanol yields and productivities. Manipulation of process conditions ranging from operation conditions (e.g. batch, fed-batch, continuous), process parameters (aeration, temperature, pH), immobilization technique and type of microorganism initially using kinetic models and thereafter validating with experimental data, therefore, offers a quick and strong foundation in improving bioethanol yields and productivities.
  • Thumbnail Image
    Item
    Open Access
    Process simulation as a decision support tool for biopharmaceutical process development in a South African context
    (2020) Collair, Wesley; Tai, Siew L
    In 2010 the incidence of neo-natal Group B Streptococcus (GBS) disease in South Africa was 3 per 1000 live births, more than twice the global average of 1.21 per 1000 live births. A recent life cycle impact assessment showed that a new vaccine against GBS disease in South Africa could have a potential value of $ 2 million - $ 4 million /kg (R 25 million - R 50 million /kg), as an attractive investment opportunity if a novel process can be successfully synthesised and licensed commercially. In the current global market new biopharmaceutical products require innovative and expedited development pathways. To achieve this, low-cost analytical tools with short turnaround times are needed to assist with process development decision making. Process simulation is one such tool which has been shown to be useful for evaluating process development decisions without the typically expensive investment required for experimental development of a new process. Three technology platforms (stainless steel, single-use, and a hybrid of both) were identified for use in a novel process to manufacture a GBS serotype III polysaccharide-protein conjugate antigen, for formulation into a vaccine against GBS disease. The three technology choices were compared and evaluated for the novel process at two fermentation scales of 20 L and 200 L, with cost of goods (COG) used as a comparison of economic performance for the six different scenarios. It was hypothesised that single use technology would yield the lower COG at both scales compared to stainless steel. Based on a literature survey, single use technology should require lower capital costs for pilot scale processes and should also have lower operating costs due to single use equipment not requiring sterilisation in place (SIP) and cleaning in place (CIP). It was further hypothesised that hybrid technology would yield the lowest COG by combining the best properties of stainless steel and single use technologies. A 3 x 2 factorial experiment design was used to structure the simulation exercise with three technologies at each of the two scales. A GBS serotype III process model was synthesised from literature sources, with fermentation stoichiometry based on an empirical material balance and fermentation kinetics fitted to a two-parameter Monod kinetic model. Equipment, consumables, and raw materials specifications were made using literature and empirical models. A base case simulation model, built for 20 L scale using stainless steel technology, was developed into the five additional scenarios. The best performing scenario in terms COG was then selected for sensitivity analysis using three parameters: fermentation titer, solid-liquid separation efficiency, and electricity dependence on diesel generation. At 20 L scale there was little difference in COG between the three technology options, with COG range across the three platforms of $ 9.7 million - $ 9.8 million /kg. At 200 L scale the best performing technology was stainless steel with a COG of $ 3.7 million /kg, which was $ 600 000 /kg less than the COG for single use of $ 4.3 million/kg. The difference was due to a higher cost of consumables for single use technology, and negligible differences in capital costs for single use over stainless steel. The effect of SIP and CIP costs on operating cost for stainless steel technology was found to be small compared to the greater consumables cost for single use. The 200 L stainless steel process was found to be sensitive to fermentation titer, with an increase in titer to 600 mg/L resulting in the lowest COG of $ 2.2 million /kg. The process was found to be least sensitive to electricity dependence on diesel, with only a $ 60 000 /kg increase in COG when 75% of electricity was derived by diesel generator. The hypothesis was disproved, with single use technology having the higher COG at both 20 L and 200 L scales compared to stainless steel technology. Hybrid technology did not yield the lowest COG either, instead resulting in a COG somewhere between stainless steel and single use. Stainless steel technology outperformed single use and hybrid technologies in COG at both scales, contrary to both parts of the hypothesis. A process to make a GBS vaccine could be profitable at scales of 200 L and above using stainless steel technology. Process simulation modelling was effective for evaluating process technology options without performing costly physical experiments. The simulation exercise provided valuable information on the economic impact of process development decisions as well as context specific information for the South African context. This methodology is therefore recommended for commercial biopharmaceutical process development, particularly for evaluating techno-economic scenarios in different decision pathways during the development process.
  • Thumbnail Image
    Item
    Open Access
    Value chain diversification in the sugar industry using quantitative economic forecasting models
    (2021) Ghafeer, Amna; Tai, Siew L; Harrison, Susan T L
    The South African sugar industry is facing increasing pressure from global sugar markets where the price of sugar is significantly lower than in domestic markets, as well as from the implementation of the health levy which has resulted in beverage manufacturers replacing sugar with non-taxable sweeteners. To maintain the industry infrastructure and to increase the demand for sugar, a diversification route for sucrose is needed. Most of the studies focused on identifying a diversification solution for bioproducts are survey or experienced based and so, one of the main aims of this study was to use mathematical modelling of industrial manufacturing data to identify one single industry to explore sucrosebased chemicals. Datasets published by Statistics South Africa, The World Bank, Trading Economics and by the Organization for Economic Cooperation and Development were considered, from which the monthly manufacturing industries' sales data published by Statistics South Africa was selected for model building. Seven different types of models were considered, including the Naïve method, simple and weighted moving averages, simple exponential smoothing, Holt's method, Holt-Winters' method and Auto-Regressive Integrated Moving Average (ARIMA) models. Each type of model was analysed in the context of the eight industries' data, from which ARIMA models were identified as those which were broad enough to cater for the varying degrees of trends and seasonality in the data without oversimplifying the data's behaviour. The other seven were not suitable either because their narrow applicability was not suitable to most of the datasets at hand or because they would provide an oversimplified model which would not be robust for future datapoints. The models were then built using training and test data splits with the auto.arima function in R Studio. From these, selection matrices were constructed to evaluate the industries' forecasts on sales growth and revenue generating potential, the results of which identified the beverages' industry to the best option for investment. One of the objectives of the study was to identify a sucrose-based chemical for investment that is not highly commercialized in order to widen the range of investment options available. To this end, only four of the less commercialized chemicals explored showed significant advancement based on published research and patents, namely caprolactam, dodecanedioic acid, adipic acid and muconic acid. However, all four chemicals would feature mainly in the textiles industry, which the model identifies as not being a high growth industry and thus would limit the revenue generating potential. The main beverage constituents of common drinks were then explored, from which nonnutritive sweeteners were chosen based on their wide applicability. From the six sweeteners considered, sucralose is the most widely used sweetener with the least number of reported serious health risks; this is thought to compensate for sucralose being a mid-price range product. Sucralose would also allow the sugar industry to leverage beverage manufacturers' replacement of sugar with sweeteners to comply with the Health Protection Levy. The techno-economic analysis performed for the selected synthetic sucralose production process proved profitable in the first year of operation, as did a refined configuration using a lower ethyl acetate flow rate. This is largely due to the retail price of sucralose being close to 8 times the purchase cost of the most expensive raw material used. Although this profitability analysis is promising, further investigation into the fixed capital costs involved should be done prior to the sugar industry investing in sucralose. Recommendations for further work to improve the profitability of this scenario include the consideration of forming a strategic partnership with key players in the beverages' industry, exploring alternative production routes, and using other time series models to validate the results achieved here.