No description available.

No description available.

No description available.

Overfishing of natural fisheries is a global issue that is becoming more urgent as the human population increases exponentially. According to the Food and Agriculture Organization of the United Nations, over 70% of the world's seafood species are fully exploited or depleted. This high demand for seafood protein is not going away; and, in fact, an astonishing one out of five people in this world depend on this source of protein. Traditional aquaculture practices use pond and flow-through systems which are often responsible for discharging pollutants into the environment. Furthermore, aquacultural feeds often contain high levels of fish protein, so the demand on wild fisheries is not completely eased. Even though traditional aquaculture has these drawbacks, there is a significant movement towards more sustainable practices. For example, implementing recirculating aquaculture systems (RAS) maximizes the reuse of culture water which decreases water demand and minimizes the levels of pollutants being discharged to the environment. And, alternative proteins (e.g., soy bean) are replacing the fish and seafood proteins in aquaculture diets. Accordingly, the research described in this dissertation focused on maximizing the reuse of freshwater fish effluent to culture marine shrimp. More specifically, by using suspended-growth biological reactors to treat a tilapia effluent waste stream and to generate microbial flocs that could be used to support shrimp culture. This RAS technology will decrease water consumption by increasing the amount of recycled water and will also improve effluent water quality. The biomass generated in the bioreactors could be used to feed shrimp with an alternative source of protein. Treating fish effluent to be reused to culture shrimp while producing this alternative feed, could significantly decrease operational costs and make these operations more sustainable. Understanding which ions are critical for the survival and normal growth of marine shrimp in freshwater effluents is essential. It is also very important to understand how to convert an effluent's organic matter into food for shrimp. Results from studies revealed that the marine shrimp, Litopenaeus vannamei, can be raised in freshwater effluent when supplemented with specific ions and wet microbial flocs fed directly to shrimp can enhance growth in shrimp fed a restricted ration of commercial feed. The treatability of the tilapia effluent using suspended-growth, biological reactors and nutritional analysis of the generated biomass were also reported. Carbon supplementation enhanced reactor performance and microbial floc generation. These microbial flocs also proved to be a superior feed ingredient when dried and incorporated into a pellet feed. / Ph. D.

No description available.

No description available.

<p> A novel mathematical model has been developed for biofilms and bioflocs. The model is based on the use of the effectiveness factor and the effect of cell density is included. The key assumption in the model is that cell density decreases in proportion to the substrate concentration within the biofilm or biofloc, reflecting lower rates of cellular metabolism. The equations given by the model were solved numerically for three types of reaction kinetics: Monod, Andrews (substrate inhibition), and multiple-Monod (twolimiting substrates), as well as for two geometries: a slab, as a representation of a biofilm and a sphere, as a representation of a biofloc. The simulations indicate that a decrease of the cell density in the biofilm and biofloc results in a decline of the effectiveness factor. Furthermore, the analytical solutions and approximate analytical versions of the effectiveness factor for the biofilm in two cell growth models: Monod and Andrews, have been derived. The effectiveness factors derived analytically are in agreement with those calculated numerically, and the approximate analytical versions are valid for the Thiele modulus greater than five. This new model was tested using operational data available in the literature, by including the effectiveness factor as a part of the design equations for an upflow anaerobic sludge blanket (UASB) reactor. </p> <p> For any biologically mediated transformation, it is critical to uniquely identify the parameters associated with microbial growth models. In this study, it is proved that the parameters of the integrated Andrews model are identifiable if the experimental data does not contain any random noise based on a criterion proposed by Beck and Arnold [1977]. When noise is present, the parameters may or may not be identifiable, depending on noise levels. A new approach has been developed based on the calculation of dimensionless sensitivity coefficients. Plotting these coefficients provides straightforward visualization of parameter identification. This method was used for quantitative evaluation of the noise level that can be associated with measurements, while still allowing parameter identification. It was demonstrated that an indirect cause of the parameter nonidentification of the integrated Andrews model is the linearization of the Andrews model at a low or high substrate concentration. Robinson [1985] obtained a similar result with the Monod model. </p> / Thesis / Master of Science (MSc)

Articular cartilage on weight-bearing joints experiences three main forces: fluid-induced shear across the surface, perfusion through the cartilage from the surrounding fluid, and compression during motion of the joint. A new bioreactor that employs two of these forces was developed in this lab to study their effect on tissue-engineered cartilage development. The focus of this research and overall hypothesis is that bioreactors that employ both perfusion and shear will improve chondrogenesis and preservation to produce functionally relevant cartilage by modulating shear stress and introducing exogenous preservation factors. Applying both a low shear stress across the surface of cell-seeded scaffolds and perfusion through them in a perfusion concentric cylinder (PCC) bioreactor may stimulate chondrocytes to undergo chondrogenesis. Experimental data showed that the PCC bioreactor stimulated cartilage growth over the course of four weeks, supported by the appearance of glycosaminoglycan (GAG) and collagen type II, which are markers for articular cartilage. Computational fluid dynamics modeling showed that shear stress across the face of the construct was heterogeneous, and that only the center experienced a relatively uniform shear stress of 0.4 dynes/cm^2 when the outer cup of the bioreactor rotated at 38 rpm. When compared to a concentric cylinder (CC) bioreactor that employed only shear stress, the PCC bioreactor caused a significant increase in cellular proliferation, which resulted in a 12-fold increase in cell number per construct compared to 7-fold increase within the CC bioreactor. However, the PCC bioreactor had a less pronounced effect on glycosaminoglycan and collagen content with 1.3 mg of GAG and 1.8 mg of collagen per construct within the CC bioreactor and 0.7 mg of GAG and 0.8 mg of collagen per construct within the PCC bioreactor after 28 days in culture (p < 0.05). Our results led to an important observation that the PCC bioreactor affected cellular proliferation significantly but not extracellular matrix synthesis. The next objective of this study focused on the PCC bioreactor to evaluate the direct role of perfusion and shear on chondrogenesis in vitro and in vivo.

The word cybernetics has its roots in the Greek word \kybernetes" or \steers-man" and was coined by Norbert Wiener in 1948 to describe \the science of control and communication, in the animal and the machine". The discipline focuses on the way various complex systems (animals/machines) steer towards/maintain their goals utilizing information, models and control actions in the face of various disturbances. For a given animal/machine, cybernetics considers all the possible behaviors that the animal/machine can exhibit and then enquires about the constraints that result in a particular behavior. The thesis focuses on the application of principles of cybernetics to the modeling and optimization of bioreactors and lies at the interface of systems engineering and biology. Specifically, it lies at the interface of control theory and the growth behavior exhibited by microorganisms. The hypothesis of the present work is that the principles and tools of control theory can give novel insights into the growth behavior of microorganisms and that the growth behavior exhibited by microorganisms can in turn provide insights for the development of principles and tools of control theory. Mathematical models for the growth of microorganisms such as stoichiometric, optimal and cybernetic assume that microorganisms have evolved to become optimal with respect to certain cellular goals or objectives. Typical cellular goals used in the literature are the maximization of instantaneous/short term objectives such biomass yield, instantaneous growth rate, instantaneous ATP production rate etc. Since microorganisms live in a dynamic world, it is expected that the microorganisms have evolved towards maximizing long term goals. In the literature, it is often assumed that the maximization of a short term cellular goal results in the maximization of the long term cellular goal. However, in the systems engineering literature, it has long been recognized that the maximization of a short term goal does not necessarily result in the maximization of the long term goal. For example, maximization of product production in a fed-batch bioreactor involves two separate phases: a first phase in which the growth of microorganisms is maximized and a second phase in which the production of product is maximized. An analogous situation arises when the bacterium E. coli passes through the digestive tract of mammals wherein it first encounters the sugar lactose in the proximal portions and the sugar maltose in the distal portions. Mitchell et al. (2009) have experimentally shown that when E. coli encounters the sugar lactose, it expresses the genes of maltose operons anticipatorily which reduces its growth rate on lactose. This regulatory strategy of E. coli has been termed asymmetric anticipatory regulation (AAR) and is shown to be beneficial for long term cellular fitness by Mitchell et al. (2009). The cybernetic modeling framework for the growth of microorganisms, developed by Ramakrishna and co-workers, is extended in the present thesis for modeling the AAR strategy of E. coli. The developed model accurately captures the experimental observations of the AAR phenomenon, reveals the inherent advantages of the cybernetic modeling framework over other frameworks in explaining the AAR phenomenon, while at the same time suggesting a scope for the generalization of the cybernetic framework. As cybernetics is interested in all the possible behaviors that a machine (which is, in the present case, microorganism) can exhibit, a rigorous analysis of the optimal dynamic growth behavior of microorganisms under various constraints is carried out next using the methods of optimal control theory. An optimal control problem is formulated using a generalized version of the unstructured Monod model with the objective of maximization of cellular concentration at a fixed final time. Optimal control analysis of the above problem reveals that the long term objective of maximization of cellular concentration at a final time is equivalent to maximization of instantaneous growth rate for the growth of microorganisms under various constraints in a two substrate batch environment. In addition, reformulation of the above optimal control problem together with its necessary conditions of optimality reveals the existence of generalized governing dynamic equations of the structured cybernetic modeling framework. The dynamic behavior of the generalized equations of the cybernetic modeling framework is analyzed further to gain insights into the growth of microorganisms. For growth of microorganisms on a single growth limiting carbon substrate, the analysis reveals that the cybernetic model exhibits linear growth behavior, similar to that of the unstructured Contois model at high cellular concentrations, under appropriate constraints. During the growth of microorganisms on multiple substitutable substrates, the analysis reveals the existence of simple correlations that quantitatively predict the mixed substrate maximum specific growth rate from single substrate maximum specific growth rates during simultaneous consumption of the substrates in several cases. Further analysis of the cybernetic model of the growth of S. cerevisiae on the mixture of glucose and galactose reveals that S. cerevisiae exhibits sub-optimal dynamic growth with a long diauxic lag phase and suggests the possibility for S. cerevisiae to grow optimally with a significantly reduced diauxic lag period. Since cybernetics is interested in understanding the constraints under which a particular machine (microorganism) exhibits a particular behavior, a methodology is then developed for inferring the internal constraints experienced by the microorganisms from experimental data. The methodology is used for inferring the internal constraints experienced by E. coli during its growth on the mixture of glycerol and lactose. An interesting question in the study of the growth behavior of microorganisms concerns the objective that the microorganisms optimize. Several studies aim to determine these cellular objectives experimentally. A similar question that is relevant to the optimization of fed-batch bioreactors is \what are the objectives that are to be optimized by the feed flow rate in various time intervals for the optimization of a final objective?" It was mentioned previously that the maximization of product production in a fed-batch bioreactor involves maximization of growth of microorganisms first and the maximization of product production later. However, such guidelines can only be stated for relatively simple bioreactor optimization problems and no such guidelines exist for sufficiently complex problems. For complex problems, the answer to the above question requires the formulation and solution of a genetic programming problem which can be quite challenging. An alternative numerical solution methodology is developed in the present thesis to address the above question. The solution methodology involves the specification of bioreactor objectives in terms of the bioreactor trajectory in the state space of substrate concentration-volume. The equivalent control law of the sliding mode control technique is used for finding the inlet feed ow rate that tracks the bioreactor trajectory accurately. The search for the best bioreactor trajectory is carried out using the stochastic search technique genetic algorithm. The effectiveness of the developed solution methodology in determining the optimal bioreactor trajectory is demonstrated using three challenging bioreactor optimization problems.

Submitted in fulfilment of the requirements of the Degree of Master of Technology: Biotechnology, Durban University of Technology, 2011. / Due to greenhouse gas emissions from fossil fuel usage, the impending threat of global climate change has increased. The need for an alternative energy feedstock that is not in direct competition to food production has drawn the focus to microalgae. Research suggests that future advances in microalgal mass culture will require closed systems as most microalgal species of interest thrive in highly selective environments. A high lipid producing microalga, identified as Chlorella vulgaris was isolated from a freshwater pond. To appraise the biofuel potential of the isolated strain, the growth kinetics, pyroletic characteristics and photosynthetic efficiency of the Chlorella sp was evaluated in vitro. The optimised preliminary conditions for higher biomass yield of the selected strain were at 4% CO2, 0.5 g l-1 NaNO3 and 0.04 g l-1 PO4, respectively. Pulse amplitude modulation results indicated that C. vulgaris could withstand a light intensity ranging from 150-350 μmol photons m-2s-1. The pyrolitic studies under inert atmosphere at different heating rates of 15, 30, 40 and 50 ºC min-1 from ambient temperature to 800 oC showed that the overall final weight loss recorded for the four different heating rates was in the range of 78.9 to 81%. A tubular photobioreactor was then designed and utilised for biomass and lipid optimisation. The suspension of microalgae was circulated by a pump and propelled to give a sufficiently turbulent flow periodically through the illuminated part and the dark part of the photobioreactor. Microalgal density was determined daily using a Spectrophotometer. Spectrophotometric determinations of biomass were periodically verified by dry cell weight measurements. Results suggest that the optimal NaNO3 concentration for cell growth in the reactor was around 7.5 g l-1, yielding maximum biomass of 2.09 g l-1 on day 16. This was a significant 2.2 fold increase in biomass (p < 0.005) when compared to results achieved at the lowest NaNO3 cycle (of 3.8 g l-1), which yielded a biomass value of 0.95 g l-1 at an OD of 1.178. Lipid accumulation experiments revealed that the microalga did not accumulate significant amounts of lipids when NaNO3 concentrations in the reactor were beyond 1.5 g l-1 (p > 0.005). The largest lipid fraction occurred when the NaNO3 concentration in the medium was 0.5 g l-1. Results suggest that the optimal trade-off between maximising biomass and lipid content occurs at 0.9 g l-1 NaNO3 among the tested conditions within the photobioreactor. Gas chromatograms showed that even though a greater number of known lipids were produced in Run 8, the total lipid percentage was much lower when compared to Runs 9-13. For maximal biomass and lipid from C. vulgaris, it is therefore crucial to optimise nutritional parameters such as NaNO3. However, suitable growth conditions for C. vulgaris in a tubular photobioreactor calls for innovative technological breakthroughs and therefore work is ongoing globally to address this.