Bioreactor Implementation in the Agro-Food Industries E-Book
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- Herausgeber: John Wiley & Sons
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- Sprache: Englisch
The use of bioreactors in food ingredient production has expanded rapidly in recent years. These processes create a controlled environment that is tailored to the specific needs of each microorganism, while also minimizing their environmental impact.
However, to optimize the implementation of these processes, it is necessary to master a number of scientific concepts relating to material and heat balances, thermodynamics, microbial kinetics, extrapolation and agitation techniques, as well as the techno-economic analysis of processes.
This book aims to provide an exhaustive and precise presentation of all of these concepts, making them accessible to students, researchers and professionals alike.
Bioreactor Implementation in the Agro-Food Industries is structured in two complementary parts. The first part outlines the essential principles of bioreactor engineering. This knowledge is essential if we are to master the biological and physico-chemical processes that take place in bioreactors.
The second part presents practical examples of the use of bioreactors for the production of several ingredients and metabolites of interest.
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Table of Contents
Cover
Table of Contents
Title Page
Copyright Page
Preface
Introduction
PART 1: The Fundamentals of Fermentation and Photobioreactor Engineering
Introduction to Part 1
1 Principles of Fermentation Engineering
1.1. Mass balances
1.2. Heat balances
1.3. Microbial kinetics
1.4. Oxygen consumption, solubility and transfer in fermenters
1.5. CO
2
production, solubility and transfer in fermenters
1.6. References
2 Fermenter Implementation: Principle and Optimization
2.1. Optimal fermenter implementation
2.2. Batch fermentation
2.3. Continuous fermentations
2.4. Optimal implementation of fed-batch fermentations
2.5. References
3 Photobioreactor Engineering
3.1. Overview of different photobioreactor configurations
3.2. Conclusion
3.3. References
4 Bioreactor Hydrodynamics and Mixing
4.1. Introduction
4.2. Hydrodynamics and macroscopic mixing in bioreactors
4.3. From macromix to micromix
4.4. Bioreactor mixture characterization method
4.5. Hydrodynamics–kinetics coupling
4.6. Conclusion
4.7. References
5 Bioreactor Extrapolation
5.1. Introduction
5.2. Introducing the bioreactor extrapolation concept
5.3. Extrapolation methods
5.4. Conclusion
5.5. References
PART 2: Examples of Bioreactor Applications in the Food Industry
Introduction to Part 2
6 Production of Fermented Beverages: Beer
6.1. Introduction
6.2. Introduction to the brewing process
6.3. Substrate degradation pathways
6.4. Metabolite synthesis pathways
6.5. Effects of physicochemical factors on the beer production process
6.6. New trends in the beer fermentation process
6.7. References
7 Production of Biomass and Bioactives by Microalgae
7.1. Introduction
7.2. Biomass production from microalgae
7.3. The main bioactives derived from microalgae
7.4. Other microalgae potential
7.5. Conclusion
7.6. References
8 Economic and Environmental Optimization of Fermentation Processes: Ethanol and Glutamic Acid Production
8.1. Economic assessment and optimization of fermentation processes
8.2. Environmental assessment and optimization of fermentation processes
8.3. Optimization of the ethanol fermentation process
8.4. Optimization of the glutamic acid fermentation process
8.5. References
Conclusion
List of Authors
Index
End User License Agreement
List of Tables
Chapter 1
Table 1.1. Oxygen solubility according to Henry’s law
Chapter 3
Table 3.1. Main types of photobioreactor used for microalgae cultivation
Chapter 4
Table 4.1. Parameters characterizing mixing and hydrodynamics in a stirred rea...
Chapter 5
Table 5.1. Main dimensionless numbers and parameters used in bioreactor extrap...
Table 5.2. Orders of magnitude of the impact of scaling on process parameters ...
Table 5.3. kLa prediction correlations as a function of bioreactor configurati...
Chapter 6
Table 6.1. Average major element composition of malt
Table 6.2. Perception thresholds for different beer compounds
Table 6.3. Classification of amino acids according to their wort absorption ra...
Chapter 7
Table 7.1. Main bioactives marketed from microalgae
Chapter 8
Table 8.1. Kinetic parameters of the ethanol fermentation simulation model
Table 8.2. Technical and economic characteristics of optimized ethanol ferment...
Table 8.3. Technical characteristics of ethanol production in a multi-stage co...
Table 8.4. Kinetic parameters of the glutamic acid fermentation simulation mod...
Table 8.5. Technical and economic characteristics of optimized batch and fed-b...
Table 8.6. Technical and economic characteristics of glutamate fed-batch ferme...
List of Illustrations
Chapter 1
Figure 1.1. Initial–final balance terms for total material
Figure 1.2. Initial–final balance terms for component A
Figure 1.3. Instantaneous balance terms for the total mass
Figure 1.4. Instantaneous balance terms for component A
Figure 1.5. Instantaneous heat balance terms on a fermenter.
Figure 1.6. Fermenter cooling characteristics through its cooling jacket.
Figure 1.7. (a) Fermenter agitation, aeration and cooling characteristics
Figure 1.7. (b) Values of the instantaneous heat balance terms for the ferment...
Figure 1.8. (a) Variation in substrate S and biomass X concentrations during C...
Figure 1.9. Overall, volumetric and specific cell rates in a fermenter
Figure 1.10. Defining the rates of growth, cell death, substrate consumption a...
Figure 1.11. (a) Corynebacteria X biomass variation over time. (b) Substrate S...
Figure 1.11. (c) Variation in the volumetric growth rate over time. (d) Variat...
Figure 1.11. (e) Variation in the volumetric rate of substrate consumption ove...
Figure 1.12. Variation in substrate S and biomass X concentrations during cont...
Figure 1.13. Factors influencing cell rates in a fermenter
Figure 1.14. Relation between specific cell rates and composition of the mediu...
Figure 1.15. (a) Illustration of Monod’s kinetic law for specific growth rate ...
Figure 1.16. (a) Specific growth rate of Corynebacteria μ as a function of sug...
Figure 1.17. (a) Illustration of the growth kinetic law with substrate inhibit...
Figure 1.18. (a) Influence of the maximum concentration of metabolite Mm on μ ...
Figure 1.19. (a) variation over time of the concentrations of biomass X and me...
Figure 1.19. (c) Influence of the kinetic constant KM on the variation of the ...
Figure 1.20. (a) Variation in biomass X and metabolite M concentrations over t...
Figure 1.21. Representation of the specific sugar consumption rate as a functi...
Figure 1.22. Kinetic model with three physiological states of latency, growth ...
Figure 1.23. Instantaneous oxygen balance terms for an aerated fermenter.
Figure 1.24. (a) Variation in the concentrations of biomass X and metabolite M...
Figure 1.24. (c) Variation of the volume rate of oxygen consumption rO2‴ over ...
Figure 1.25. Diagram of a dissolved oxygen probe and its response to dissolved...
Figure 1.26. Influence of probe response time on the variation in dissolved ox...
Figure 1.27. Influence of glucose concentration on oxygen solubility O2* norma...
Figure 1.28. (a) Stages of oxygen transfer between the air and fermentation me...
Figure 1.28. (b) Oxygen concentration profile at the air-liquid interface.
Figure 1.29. Influence of agitation power density Pag/V and surface air veloci...
Figure 1.30. (a) Influence of probe response time on the variation in dissolve...
Figure 1.30. (b) Influence of probe response time on the representation used t...
Figure 1.31. (a) Influence of probe response time on the variation in dissolve...
Figure 1.32. (a) Variation of the volumetric rate of oxygen consumption rO2‴ o...
Figure 1.33. Factors influencing the concentration of dissolved CO2 in a ferme...
Figure 1.34. (a) Variation in biomass X and metabolite M concentrations over t...
Figure 1.34. (c) Variation of the volumetric rate rCO2‴ of CO2 production over...
Figure 1.35. Stages of CO2 transfer between fermentation medium and air, and p...
Figure 1.36. Variation in CO2* solubility and CO2l concentration of dissolved ...
Chapter 2
Figure 2.1. Balance–thermodynamics–kinetics methodological triangle for modeli...
Figure 2.2. Instantaneous biomass, substrate and metabolite balances for batch...
Figure 2.3. Instantaneous oxygen balances to determine mole fraction of oxygen...
Figure 2.4. (a) Variation during anaerobic batch fermentation in metabolite M ...
Figure 2.4. (c) Influence of initial substrate concentration S0 on the ferment...
Figure 2.5. Variation of the volumetric rate of oxygen consumption and the m...
Figure 2.6. Influence of specific growth rate μ and oxygen transfer coefficien...
Figure 2.7. (a) Variation of oxygen consumption volumetric rate and maximum ...
Figure 2.7. (c) For batch fermentation, influence of initial substrate concent...
Figure 2.8. (a) Variation of non-growth-associated metabolite in the concentra...
Figure 2.8. (c) Variation in metabolite M concentration and ProdM metabolite p...
Figure 2.8. (e) Influence of initial substrate concentration S0 on aeration-in...
Figure 2.9. Operating variables for continuous fermentation and variation over...
Figure 2.10. (a) Influence of dilution rate D on the variation of substrate co...
Figure 2.11. (a) At steady state, influence of dilution rate D on substrate S ...
Figure 2.12. (a) At steady state, influence of dilution rate D on fermenter bi...
Figure 2.13. (a) For anaerobic fermentation of growth-associated metabolite, i...
Figure 2.13. (c) Influence of substrate concentration in the feed Sfeed on the...
Figure 2.13. (e) Under optimal operating conditions, variation of substrate S,...
Figure 2.14. For aerobic cell production in continuous fermentation, influence...
Figure 2.15. (a) For aerobic fermentation for cell production, influence of di...
Figure 2.15. (c) Influence of substrate concentration in feed Sfeed on station...
Figure 2.15. (e) Under optimal conditions for continuous fermentation, variati...
Figure 2.16. Operating variables in fed-batch fermentation and variation over ...
Figure 2.17. (a) For a production of cells, variation in specific growth rate ...
Figure 2.18. (a) Variation, as a function of the stationary substrate concentr...
Figure 2.18. (c) Influence of substrate concentration in feed Sfeed on ferment...
Figure 2.18. (d) Influence of initial medium volume fraction V0/Vt on fermente...
Figure 2.19. (a) Under optimal fed-batch fermentation conditions, variation ov...
Figure 2.19. (c) Under optimal fed-batch fermentation conditions, variation ov...
Figure 2.20. (a) For aerobic production of a non-growth associated metabolite,...
Figure 2.20. (c) Variation of specific substrate consumption rates qs and oxyg...
Figure 2.21. (a) Influence of initial substrate concentration S0 on biomass co...
Figure 2.21. (b) Influence of stationary substrate concentration Sss on final ...
Figure 2.21. (c) Influence of substrate concentration in Sfeed feed on final m...
Figure 2.21. (d) Influence of initial medium volume fraction V0/Vt on final me...
Figure 2.22. (a) Under optimal fed-batch fermentation conditions, variation ov...
Chapter 3
Figure 3.1. Circular Chlorella cultivation basins in Japan. Unit area 500 m
2
Figure 3.2. Greenhouse raceways. Unit area of 100 m2. Spirulina cultivation at...
Figure 3.3. Algal channel under a thermo-regulated, illuminated system. Volume...
Figure 3.4. Bubble columns connected in series. Unit volume: 12 L. Institut Na...
Figure 3.5. Thin-layer cultivation. Total area 90 m2. Campus of Institute of M...
Figure 3.6. Tubular photobioreactors. (A) Vertical coil. Volume: 4,000 L (sour...
Figure 3.7. Flat photoreactors. (A) plastic. Volume: 500 L (source: IGV Biotec...
Chapter 4
Figure 4.1. Diagram of operating parameters affecting mixing in a mechanically...
Figure 4.2. Diagram of circulation loops according to the type of agitator: (a...
Figure 4.3. Examples of radial-flow impellers: (a) Rushton turbine and (b) str...
Figure 4.4. Examples of axial-flow impellers: (a) marine propeller, (b) inclin...
Figure 4.5. Examples of tangential-flow impellers: (a) anchor and (b) paddle i...
Figure 4.6. Characteristic geometric parameters for agitation sizing.
Figure 4.7. Flow regime and turbulence evolution according to the Reynolds num...
Figure 4.8. Changes in local tracer concentration after a single addition.
Figure 4.9. Degree of suspension of a liquid–solid mixture: (a) partial suspen...
Figure 4.10. Gas dispersion regimes as a function of gas flow Qg and stirring ...
Figure 4.11. Energy transfer from large eddies to small eddies according to tu...
Figure 4.12. Typical RTD profiles in an open reactor.
Figure 4.13. Representation of the different types of biological models.
Chapter 6
Figure 6.1. Description of the different stages in beer production.
Chapter 8
Figure 8.1. Methodology for the economic assessment of processes
Figure 8.2. Lifecycle assessment of processes and products
Figure 8.3. Methodology for assessing environmental impact indicators for proc...
Figure 8.4. Processes for producing ethanol from agro-resources
Figure 8.5. (a) Variation in sugar S, biomass X and Ethanol Eth concentrations...
Figure 8.5. (b) Variation in sugar S, biomass X and Ethanol Eth concentrations...
Figure 8.6. Batch and continuous fermenter ethanol production cost analysis by...
Figure 8.7. Multi-stage continuous fermenter with cell recycling for ethanol p...
Figure 8.8. Water and heat recycling strategies for the ethanol production pro...
Figure 8.9. Industrial glutamic acid production process
Figure 8.10. (a) Variation in sugar S, biomass X, glutamate Glu and trehalose ...
Figure 8.11. Analysis of glutamic acid production costs in batch and fed-batch...
Figure 8.12. (a) Operational variables of glutamate fed-batch fermentation. (b...
Figure 8.13. (a) Variation in the concentrations of sugar S, biomass X, glutam...
Figure 8.14. (a) Variation in dissolved oxygen concentration O2l during fed-ba...
Figure 8.15. Water and heat recycling strategies for the glutamic acid product...
Guide
Cover Page
Table of Contents
Title Page
Copyright Page
Preface
Begin Reading
Conclusion
List of Authors
Index
WILEY END USER LICENSE AGREEMENT
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SCIENCES
Agronomy and Food Science,Field Directors – Jack Legrand and Gilles Trystram
Food Bioprocesses, Subject Head – Mohamed Ghoul
Bioreactor Implementation in the Agro-Food Industries
Technology, Kinetics and Modelization
Coordinated by
Mohamed Ghoul
First published 2024 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.
Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:
ISTE Ltd27-37 St George’s RoadLondon SW19 4EUUK
www.iste.co.uk
John Wiley & Sons, Inc.111 River StreetHoboken, NJ 07030USA
www.wiley.com
© ISTE Ltd 2024The rights of Mohamed Ghoul to be identified as the author of this work have been asserted by him in accordance with the Copyright, Designs and Patents Act 1988.
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s), contributor(s) or editor(s) and do not necessarily reflect the views of ISTE Group.
Library of Congress Control Number: 2024943819
British Library Cataloguing-in-Publication DataA CIP record for this book is available from the British LibraryISBN 978-1-78945-155-9
ERC code:LS9 Biotechnology and Biosystems Engineering LS9_5 Food biotechnology and bioengineeringSH1 Individuals, Markets and Organisations SH1_12 Environmental economics; resource and energy economics; agricultural economics
Preface
Mohamed GHOUL
Laboratoire Réaction et Génie des Procédés (LRGP), CNRS, Université de Lorraine, Nancy, France
The use of bioreactors for the production of food ingredients has been burgeoning in recent years. These processes enable the creation of a controlled environment adapted to the specific needs of each microorganism, while minimizing the environmental impact of these processes. However, the implementation of bioreactors on an industrial scale often remains empirical based on the experience and expertise of individual companies.
A rational approach to optimal bioreactor implementation is possible, but requires a mastery of a number of scientific concepts relating to material and heat balances, microbial kinetics and their implementation. Indeed, depending on the kinetics of the microorganism used, the composition of the reaction medium and the nature of the ingredients sought, several configurations and modes of bioreactor operation are possible.
The aim of this book is to provide an exhaustive and accurate presentation of all of these concepts, making them accessible to students, researchers and professionals wishing to exploit the potential of bioreactors in order to produce food ingredients and develop innovative processes.
The first part of this book therefore develops the fundamentals of bioreactor engineering, including material and heat balances, microbial kinetics, bioreactor implementation, as well as agitation and mixing techniques. This knowledge is essential for controlling the biological and physicochemical processes that take place in bioreactors. These processes can have contradictory effects, and the search for compromises is often necessary to achieve optimal operation of these processes. Criteria for optimizing bioreactor operation (batch, fed-batch or continuous) and choosing the most suitable agitation technology for the biological system used (bacteria, yeast, fungi, microalgae), as well as the rheology of the culture medium, will be presented and discussed.
The second part illustrates the use of bioreactors for the production of several ingredients and metabolites of interest. In this way, we discover how to integrate all of the knowledge developed in the first part of this book in an original and innovative way, so as to produce (i) biomass and food bioactives by cultivating different species of microalgae, (ii) glutamic acid by exploiting the potential of bacteria in this field, (iii) beverages such as beer thanks to the fermentative power of yeast and (iv) ethanol from renewable bioresources by yeast fermentation.
This book is aimed at professionals, researchers and students alike, and is therefore a basic reference in the field of bioreactors applied to food bioprocesses.
Mohamed GHOUL
October 2024
Introduction
Jean-Marc ENGASSER and Mohamed GHOUL
Laboratoire Réaction et Génie des Procédés (LRGP), CNRS, Université de Lorraine, Nancy, France
Processes for the production of biomass and metabolites by different species of microorganisms are key techniques in many industries, including food processing. Microorganisms such as bacteria, yeasts, fungi and microalgae are widely used in these processes. They act as “cellular factories”, performing numerous enzymatic reactions to transform various substrates into the desired products.
In most cases, specific strains of microorganisms are selected for their production performance. These strains are often genetically modified to improve their ability to produce specific metabolites. Indeed, genetic engineering and metabolic engineering techniques make it possible to create new industrial microorganisms that are capable of synthesizing specific metabolites. These new strains can significantly increase productivity levels. In some cases, mixed cultures are used to optimize processing activities and yields. This approach can be particularly useful when different strains have complementary roles.
Processes using microorganisms are used in the food industry for a variety of applications, including the production of proteins, foods, beverages, colorants, acids and other food-related bioactives.
The products resulting from these transformations fall into four distinct categories:
small molecules
resulting from cellular metabolism, such as organic acids, amino acids, nucleotides, alcohols, esters, dyes and vitamins;
macromolecules
such as polysaccharides, peptides and proteins;
whole cells
such as baker’s yeast, microalgae, lactic ferments and probiotics;
fermented food products
such as beer and yogurt.
In addition to their use in food production, these processes also have numerous environmental applications in waste decontamination. Common examples include activated sludge processes, denitrification and anaerobic digestion for methane production. These processes can also contribute to environmental sustainability, as they can use renewable substrates and produce less waste than other chemical methods.
Bioreactors are essential equipment in these processes in order to enable precise control of microorganism growth conditions such as temperature, pH, agitation and nutrient concentration.
In addition to the central operation involving the bioreactor, biotransformation processes often involve a number of upstream and downstream unit operations to efficiently transform raw materials into high-quality end products.
Upstream, raw materials may require pretreatment. This may include grinding, cutting, washing or other steps to prepare the raw materials. To avoid contamination by undesirable microorganisms, the culture media used in the bioreactor must be sterilized. This can be achieved by autoclaving, sterilizing filtration or through other sterilization methods.
In the downstream step, after bioconversion, the final products are often mixed with the culture medium and microbial cells. The first step usually involves separation operations to isolate the desired products. This may include centrifugation, filtration, decantation or other separation methods, depending on the characteristics of the products and the medium. Isolated products may contain impurities such as undesirable compounds, residual cells or contaminants. Purification aims to remove these impurities to obtain a pure and high-quality product. Common purification techniques include chromatography, precipitation, ion exchange and other product-specific methods. Once products are purified, they may require formulation to achieve the desired final composition. This may include steps such as adding stabilizers, preservatives, colorants or other additives to meet final product specifications.
These upstream and downstream operations are essential to guarantee the quality, purity and conformity of the final products to food industry standards. The exact sequence of operations may vary according to product, process and specific application requirements, but they are all crucial to the overall success of the biotransformation process.
For optimal implementation of processes involving bioreactors with different species of microorganisms to produce metabolites of interest, it is therefore necessary to not only master the biotransformation stage, but also the upstream and downstream stages of the process. This calls for a multidisciplinary approach, with a mastery of a number of engineering and life science concepts. All of these bioreactor engineering tools will be presented and illustrated by practical examples from the food industry.
PART 1The Fundamentals of Fermentation and Photobioreactor Engineering
Introduction to Part 1
Jean-Marc ENGASSER and Mohamed GHOUL
Laboratoire Réaction et Génie des Procédés (LRGP), CNRS, Université de Lorraine, Nancy, France
In order to ensure proper and optimal extrapolation of a bioreactor process, the engineer must consider a number of technological choices. These choices include the sequence of upstream and downstream unit operations, the selection of the necessary equipment and the operating modes associated with this equipment. In terms of the biotransformation operation itself under the effect of different microorganisms, technological extrapolation decisions involve the composition of the medium, which varies according to the microorganism used, the bioreactor technology and its implementation.
With regard to the composition of the medium, which must meet the nutritional requirements of the strain used, the choice involves selecting the nutrients and determining their appropriate concentrations. Indeed, the composition of the medium has a significant influence on the course of the process, as well as on the final concentrations of the obtained products. Moreover, it can also have an impact on other process steps, including sterilization, extraction and purification. The composition of the medium can also have a significant impact on the cost of the process. In the case of large-scale metabolite production, for example, the cost of the medium can account for more than half the total cost of production.
The elements to be optimized in bioreactor culture media are the carbon source, typically sugars or mineral carbon for microalgae, the nitrogen source, which can be ammonia, nitrates, amino acids and peptides, the phosphorus source, usually phosphates, growth factors or micronutrients such as vitamins, iron, zinc, copper and manganese, as well as the source and brightness in the case of microalgae cultivation.
For bacterial, yeast and fungal cultures, most industrial fermentation media are complex media containing elements such as yeast extract, corn steep or peptones, the composition of which is not precisely known. However, media in which the concentrations of all of the elements are specified are also used. Although these media are generally more expensive, they have the advantage of facilitating product purification and ensuring reproducibility.
Microalgae can be grown under autotrophic conditions, using sunlight or artificial light as an energy source and CO2 or bicarbonate as a carbon source. In heterotrophic cultures, microalgae use simple sugars as a carbon and energy source. The culture medium must also provide sufficient quantities of mineral ions, and possibly growth factors or vitamins.
With regard to bioreactor technology, there is a wide range of bioreactors available for microbial fermentations or microalgae cultivation. The most common technology revolves around using cells in suspension in mixed tanks. In the laboratory, microorganisms are cultivated in containers that are agitated and in small mixed bioreactors, with capacities ranging from a few liters to several tens of liters. These cultures are then extrapolated to tanks with volumes of up to several thousand cubic meters. Other, less frequently used technologies include membrane bioreactors, in which the cells are retained by microfiltration membranes, and fixed-bed or fluidized-bed bioreactors, in which the cultured cells are located on the surface or inside solid supports.
An essential feature of a bioreactor is its agitation and/or aeration system. For anaerobic microbial fermentations, tanks may be equipped with moderate agitation systems, or may not require agitation at all. In such cases, agitation of the medium can be achieved by the release of CO2, like in the cylindrical-conical tanks used in the brewing industry. For aerobic fermentations, bioreactors are equipped with more powerful agitation and aeration systems. The mechanically aerated and agitated bioreactor, fitted with various types of agitator, is the most commonly chosen option for bacterial and yeast culture. Other, less shearing systems are used for microalgae and fungi. Other aeration configurations include bubble columns, air lifts and external loop bioreactors, where the medium is continuously stirred by rising air bubbles. The choice of agitation and aeration technology depends on the oxygen demand of the process under study, the rheological properties of the medium and the sensitivity of the cells to shear forces.
In terms of the bioreactor operating mode, aerobic or anaerobic bioreactors with suspension cells can be operated in three different modes: batch, fed-batch and continuous. In batch mode, the entire culture medium is initially introduced into the reactor. Fed-batch mode involves the initial introduction of part of the culture medium, followed by the continuous addition of the rest of the medium over time. The continuous mode is characterized by the continuous supply of fresh medium and the simultaneous removal of used medium. Continuous culture can also be implemented using several bioreactors that are arranged in a series.
The continuous bioreactor can also be combined with cell recovery and recycling. This operation can be carried out using a centrifuge, a microfiltration membrane module or simply by decantation in the case of flocculating cells.
For a specified operating mode, the bioprocess engineer must also optimize its operational variables. The predominant operational variable is the composition of the medium, which is characterized by the concentrations of substrates and nutrients added, notably sugar concentration for bacteria and minerals, and CO2 for microalgae. Concentrations of other nutrients, such as sources of nitrogen or phosphorus, are also adjusted. The substrate concentrations to be optimized are the concentrations in the initially added medium and, in the case of continuous or fed-batch operation, the substrate concentrations in the supply medium.
The second category of operational variables concerns bioreactor aeration. It includes air flow rate and agitation power of the medium in the case of mechanically agitated biotransformation. For yeast and bacterial cultures, it is also possible to increase the mole fraction of oxygen in the inlet air in order to overcome any oxygen limitations.
Temperature and pH are other operational parameters to consider. In most cases, temperature and pH are kept constant. However, they can also be modified over time, for example, to promote metabolite excretion.
The choice of technology and operating mode for a bioreactor depends on a number of criteria. First, it is influenced by the nature of the transformation, depending on the microorganism used, whether cell or metabolite production is involved, as well as its aerobic or anaerobic nature. Second, the kinetics of the microorganism used play a crucial role, particularly with regard to inhibitions of cell growth at high concentrations of substrates and metabolites. It is also important to consider whether or not metabolite production is linked to cell growth, as well as the morphology of cultured cells and their sensitivity to shear stress in bioreactors. Additional criteria to be considered include the quality of the products obtained, the sterility requirements of the process and the economic aspects related to the cultivation process, which depend on the species of microorganism used.
Given the wide range of possible transformations and the different types of cells used (bacteria, yeast, fungi and microalgae), there is no global optimal bioreactor process design. Bioreactor technology and implementation must be specifically adapted to the biotransformation reaction, the characteristics of the cells and the industrial context in which they are used. However, to speed up the implementation and optimization of bioreactors, regardless of the strain used, the engineer can benefit from the methodology of bioprocess engineering, which favors the use of simulation models. The aim of these simulators is to predict and compare the progress of a bioprocess under different batch, continuous or fed-batch operating conditions, and with different operational variables, such as substrate concentrations or the intensity and quality of light for microalgae.
This approach to digital extrapolation and optimization of biotransformation in a bioreactor uses a “digital twin”, enabling virtual biotransformations to be carried out, in order to determine the optimal operating mode and associated variables. The use of bioreactor simulators reduces the need for experimentation during the R&D phase. It also speeds up process extrapolation and reduces R&D costs.
The most effective simulators are those that rely on knowledge-based models, which are themselves based on a thorough understanding of the phenomena and factors that influence or control bioreactor operation under various operational conditions.
Thus, the first step in the methodology for building mechanistic or knowledge-based simulation models involves identifying the phenomena that influence bioreactor behavior or limit its operation. These phenomena include the transformation reaction by the microorganism used, material and heat transfers, as well as flows inside the bioreactor.
For a given microorganism culture operation in a bioreactor, it is the transformation reaction, that is specific to the microorganism used, that largely controls variations in substrate, cell and metabolite concentrations. It is therefore essential to understand the factors related to the composition of the medium that influence the rates of cell growth, substrate consumption and metabolite production.
During aerobic fermentation of yeast or bacteria, the maximum achievable cell concentration is often limited by the transfer of oxygen between the air and the medium. The speed of this oxygen transfer depends on two key factors: the solubility of oxygen in the liquid medium and the intensity of matter transfer. In the case of reactions involving microorganisms that are sensitive to carbon dioxide concentration or requiring CO2, the solubility and transfer of CO2 in the medium can also exert a significant influence on biotransformation kinetics.
A third potentially limiting phenomenon is the heat transfer between the medium and the cooling system used to regulate temperature. At high cell concentrations, the rates of heat production by the metabolism of the biological system used can reach very high levels, approaching the maximum rate of heat removal, which is controlled by heat transfer from the medium to the cooling fluid.
The fourth phenomenon to consider is the flow of the medium inside the bioreactor, which is closely linked to the rheological properties of the medium, as well as to the shape and agitation system of the bioreactor. The internal flows of the medium have a direct impact on the transfer rates of oxygen, carbon dioxide and heat within the bioreactor. In addition, the shear stresses generated by the flows can also affect cell viability.
This analysis of the fundamental processes influencing or limiting the operation of the bioreactor is particularly appropriate for its extrapolation. As part of the extrapolation process, it is important to identify the scale factors that may modify the flow, transfer and reaction processes between the laboratory bioreactor and the industrial bioreactor. Situations may arise where the microorganism’s reaction plays a predominant role in the process at the laboratory scale, while oxygen and/or carbon dioxide and heat transfer become limiting factors for productivity at the industrial scale.
The second stage of the simulation model-building methodology involves mathematical modeling of the bioreactor. This phase consists of establishing the equations that describe the changes in substrate, cell biomass and metabolite concentrations during biotransformation. This methodology is based on the concept of the “modeling triangle”, which combines the material and heat balances with the thermodynamic and kinetic laws defining the influencing phenomena.
Variations in concentrations of components during biotransformation are governed by instantaneous matter balance, which expresses the principle of conservation of matter at each instant. Similarly, temperature variations are determined by instantaneous heat balance, which expresses the principle of energy conservation.
In addition to the balances, the simulation models incorporate the thermodynamic and kinetic laws that define the influence of the fundamental processes identified above. The thermodynamic laws used include those describing the solubilities of oxygen and carbon dioxide in the media, and the enthalpies of the liquid and gas phases in bioreactors. The kinetic laws of biotransformation models involve those characterizing transformation reactions by the microorganism used, material and heat transfers, and fluid flows. Ultimately, modeling involves incorporating these thermodynamic and kinetic laws into the balance equations, so as to create a system of algebraic or differential equations that simulate the process involved.
Chapter 1 describes the fundamentals of bioprocess engineering, which details material and heat balance relationships, thermodynamic laws governing oxygen and carbon dioxide solubility, and oxygen and CO2 transfer kinetics. Chapter 2 presents the bioreactor implementation methodology, which involves the development of simulation models for bioreactors operating in batch, continuous and fed-batch modes.
1Principles of Fermentation Engineering
Jean-Marc ENGASSER and Mohamed GHOUL
Laboratoire Réaction et Génie des Procédés (LRGP), CNRS, Université de Lorraine, Nancy, France
To optimize the use of fermenters and bioreactors in general, it is necessary to master a number of concepts related to mass and energy balances, the kinetics of microorganisms, and the transfer and dissolution of oxygen and carbon dioxide. In this chapter, all of these concepts will be presented and discussed.
1.1. Mass balances
Mass balances are the most commonly used relationships in bioprocess engineering for modeling, simulating and the sizing of unit operation equipment. Mass balances are relations that express the conservation of the principle of matter (Felder and Rousseau 2005; Doran 2013; Geankoplis et al. 2018).
There are two types of mass balance. The first is the initial–final mass balance. It expresses the conservation of the quantity of matter between the beginning and the end of an operation or process. The unit of the initial–final mass balance is the kilogram. The second is the instantaneous mass balance. It expresses the conservation of the quantity of matter at any instant during an operation or process. The unit of instantaneous mass balance is the kilogram per second.
1.1.1. Initial–final mass balances
A distinction is made between the initial–final total mass balance and the initial–final component balance.
1.1.1.1. Initial–final total mass balance
As illustrated in Figure 1.1, the initial–final mass balance first applies to the total mass in a system. Conservation of total mass implies that, during an operation or process, the total mass of material inputs is equal to the total mass of material outputs. The mass of inputs includes the initial quantity of material introduced and the quantity of material added over time. The mass of outputs includes the total quantity of the material removed over time and the quantity of the material remaining at the end of the operation or process.
Expressed in kilograms, the principle of conservation of the total quantity of material, from the beginning to the end of an operation, is represented by the equality between the quantities of inputs and outputs:
The total mass balance can be expressed in a different way by introducing the variation in the internal quantity of material, which represents the difference between the final quantity and the initial quantity:
Figure 1.1.Initial–final balance terms for total material
1.1.1.2. Initial–final component assessment
The initial–final mass balance (Figure 1.2) also applies to the mass of the individual material components that are present in the system. When considering a component A, the initial–final mass balance includes the same terms of initial quantity, input quantity, output quantity and final quantity of A. If component A is involved in a chemical or biochemical reaction, where it is either produced or transformed, the mass balance includes an additional term representing the quantity produced or transformed. In the case where A is produced by the reaction, the mass balance relation for A (in kg A) is written as follows:
If component A is transformed during the operation, the consumption of A can be considered as negative production. In this case, the initial–final balance relation is:
As with the total mass balance, it is possible to introduce the variation of the component’s internal mass between the start and finish of the process. The component’s mass balance can thus be expressed as follows:
The initial–final mass balance is used to estimate the final mass of material at the end of an operation or process, taking into account the initial content and the quantities that have been added or removed over time. The balance is also used to calculate the amount of material that needs to be added or removed during an operation in order to obtain a desired final quantity. Furthermore, the initial–final component balance can be used to estimate the component mass that is either produced or transformed during a reaction based on measurements of the other terms in the balance.
Figure 1.2.Initial–final balance terms for component A
1.1.2. Instantaneous mass balances
A distinction is made between the instantaneous total material balance and the instantaneous component balance.
1.1.2.1. Instantaneous total mass balance
The instantaneous mass balance (Figure 1.3) first applies to the total mass. It expresses the principle of conservation of total mass in a system at all times. At any given moment, the instantaneous total mass balance involves the three terms of rate or material flow, represented by arrows: (i) the input rate arrow indicates the material flow from the outside to the inside of the system; (ii) the output rate arrow represents the material flow from the inside to the outside of the system and (iii) the arrow indicates the rate of change of the internal quantity of material.
Figure 1.3.Instantaneous balance terms for the total mass
The instantaneous total mass balance in kg/s is as follows:
The first two terms, input rate and outlet rate, generally represent the material flow across the system boundary. The third term of the internal rate of change is equal to dm/dt, the time derivative of the total mass m inside the system. If input and output rates are equal during an operation, the rate of internal variation becomes zero. This implies that the total internal mass remains constant.
Note that the instantaneous total mass balance is equivalent to the initial–final mass balance over a very short time interval, expressed as: input = output + internal variation.
1.1.2.2. Instantaneous component balance
The principle of instantaneous mass balance (Figure 1.4) also applies to the various material components within the system. When there is no chemical reaction involved, the conservation of material for component A is governed by three rate or flow terms, represented by the arrows for the input rate of A into the system, the output rate of A from the system and the rate of change of the quantity of A within the system. In the presence of a chemical reaction producing or transforming component A, the instantaneous balance involves an additional arrow representing the rate at which A is produced or transformed by the reaction.
Figure 1.4.Instantaneous balance terms for component A
The instantaneous balance of component A, expressed in kg A/s, is as follows:
In the case of the production of component A:
In the case of the transformation of component A:
In these balances, the input and output rate terms represent the flow rates of component A across the system boundaries. The reaction rate term, shown as rA, is determined by the kinetic law of the reaction. The fourth internal rate of change term is equal to dmA/dt, the time derivative of the mass mA of A within the system. According to the principle of conservation of matter, the internal mass of A can increase or decrease according to the relative values of the input, output and reaction rates. In a steady-state system, there is no internal variation in the mass of A, and the instantaneous balance is simplified by specifying that dmA/dt is equal to zero.
It is worth noting that the instantaneous component mass balance is equivalent to the initial–final balance expressed over a very short period of time in the following form: input + production = output + internal variation.
Instantaneous mass balance is the most common relationship in bioprocess engineering. One of the main applications of instantaneous mass balance is the modeling and simulation of operations. Using total mass balance, it is possible to determine the temporal variations in the mass of material in a system. Similarly, the instantaneous component balance is used to model variations over time in the concentration of a component in a system. Another application of the instantaneous component balance is in the kinetic analysis of chemical or biochemical reactions. In a continuous or discontinuous system, the instantaneous balance of a component A enables the reaction rate of A to be determined from the measurement of the variation over time in the concentration of the component.
1.1.2.3. Example of mass balances on a garder tank
A mixed tank initially contains a volume V0 of 100 L of a sugar solution with a sugar concentration S0 of 100 g/L and a density ρ0 of 1.04 kg/L. A feed solution, with a Sfeed sugar concentration of 250 g/L and a density ρfeed of 1.1 kg/L, is added continuously to the tank at a constant flow rate Q of 2 L/min.
Calculate the terms of the following balances:
total mass and sugar balances on the tank, from the start to the end of a 10 min t
feed
feeding period;
instantaneous total material and sugar balances during tank feeding.
Initial–final total mass balance
Initial–final sugar balance
Instantaneous total mass balance
Instantaneous sugar balance
1.2. Heat balances
Heat is a co-product of microbial transformations. Microorganisms generate significant amounts of heat through their metabolic reactions, when converting organic substrates into biomass or metabolites.
Controlling the temperature of the fermentation medium is essential for optimal operation of a fermenter. In most cases, the temperature is kept constant throughout fermentation. However, it is also possible to have different optimal temperature ranges during the growth and metabolite production phases.
Temperature control in a fermenter is achieved by removing the heat that is generated through a cooling system, such as a cooling jacket or internal coils. To maintain a constant temperature, heat must be removed at a rate equivalent to that of its production in the medium. Removing heat from the fermentation process can be one of the difficulties in scaling up fermenters. As tank size increases, the ratio of lateral heat exchange surface area to media volume decreases, affecting the efficiency of cooling through the cooling jacket.
Modeling temperature control in a fermenter is based on the instantaneous heat balance in the plant (Figure 1.5). This balance comprises several terms: the rate of heat input into the air (qa,input), the rate of heat generation by both agitation energy (rag) and microbial metabolism (rf), the rate of heat output into the air (qa,output) and by the cooling system (qr).
Figure 1.5.Instantaneous heat balance terms on a fermenter.
In this section, we will take a detailed look at the terms of the heat balance rate in a fermenter, with the aim of better understanding how to regulate temperature during fermentation (Cooney et al 1968; Luong and Volesky 2005; Doran 2013).
1.2.1. Heat generation rate in fermenters
Heat is generated in the fermenter by the dissipation of mechanical agitation energy and by microbial metabolism. The heat generation rate in the fermenter, rc (kJ/s), is the sum of the agitation and fermentation heat generation rates:
The agitation heat generation rate, rc,ag (kJ/s), is equal to the following mechanical agitation power:
The agitation power Pag depends on the geometry and rate of rotation of the stirrers, as well as on the rheological properties of the medium.
For aerobic fermentation, the rate of microbial heat generation rc,f is generally considered to be proportional to the rate of oxygen consumption in the fermentation medium:
where Yc/O2 represents the microbial heat generated in Joules per gram of oxygen consumed. This heat depends on the microbial strain and the substrate converted. An average value is 14 kJ/g of O2 consumed.
For anaerobic fermentations, the rate of heat generation is generally assumed to be proportional to the rate of carbon substrate consumption.
where Yc/S represents the microbial heat generated in J/g of substrate consumed. This heat depends on the microbial strain and the carbon substrate. For example, for anaerobic sugar fermentation by the yeast Saccharomyces cerevisiae, Yc/S is around 0.6 kJ/gS.
1.2.2. Air heat input and output rates
The heat input rate, qa,input (kJ/s), is equal to the air mass flow Ma,input, multiplied by the specific enthalpy of air Ha,input/kg (kJ/kg):
The specific enthalpy of air comprises two inputs: the enthalpy of dry air, which is the product of the heat capacity Cpa of air by the input temperature Ta,input air, and the enthalpy of water vapor in air, which is the product of the mass fraction of water vapor xv,input in the air by the specific enthalpy of water vapor. The latter depends on the heat capacity Cpv of the water vapor and the temperature of the input air. Thus:
The water vapor mass fraction xv,input is calculated from the relative humidity of the air at the input temperature.
Similarly, the heat output rate qa,output in the air flow is:
At the output temperature Toutput and water vapor mass fraction xv,output, the heat output rate is calculated by the following relation:
The output water mass fraction takes into account water evaporation inside the fermenter. Its value is highest when the output air is saturated with moisture.
1.2.3. Cooling rate of a fermenter
Heat is removed from the fermentation medium by a cooling jacket or internal coils through which cold water circulates (Figure 1.6).
Figure 1.6.Fermenter cooling characteristics through its cooling jacket.
If the cooling exchange surface is Sc and the average temperature of the circulating cooling water is Tc, the heat transfer rate qc in J/s of the medium at temperature T is given by the kinetic law of heat transfer:
where h is the heat transfer coefficient between the medium and the cooling water.
For a cylindrical fermenter with diameter df and medium height hm, the cooling jacket exchange surface is:
and the ratio between the exchange surface and the volume of the medium is equal to:
This relation shows that the surface-to-volume ratio decreases with increasing fermenter diameter.
The heat transfer coefficient h (J/m2.s.°C) is assessed from the individual thermal characteristics of the three stages involved in the heat transfer process between the medium and the cooling water, namely, hm is the heat transfer coefficient in the fermentation medium, hc is the heat transfer coefficient in the cooling water, l is the thickness of the fermenter wall and λ is the thermal conductivity of the steel wall.
The total resistance to heat transfer, which is the inverse of the transfer coefficient h, is determined by adding up the individual resistances of the three stages:
Thus, the overall heat transfer coefficient h is calculated by the following relation:
1.2.4. Heat balance of a fermenter
The instantaneous heat balance, which expresses the principle of heat conservation at each instant, is written as a four-term balance relation, similar to the instantaneous mass balance relation. The four terms of the balance are the input rate, the output rate, the rate of production by energy conversion and the rate of change of internal enthalpy Hf. The heat balance is written as:
This heat balance can initially be used to determine the rate of temperature increase in the absence of cooling of the medium. The change in internal enthalpy is then given by the following relation:
The enthalpy, which represents the heat contained inside the fermenter, is essentially the enthalpy of the liquid medium. Consequently, the rate of temperature rise T in the medium is given by equation:
where mm is the mass of the medium and Cpm is the heat capacity of the medium.
The instantaneous heat balance is also used to assess the cooling rate required for temperature control. At a constant controlled temperature, the term for the rate of change is zero, and the cooling rate is given by the relation:
Once we know the cooling surface Sr and the heat transfer coefficient h, we can use the kinetic law expressing this cooling rate to estimate the required cooling water temperature:
1.2.5. Example: instantaneous heat balance of an aerated fermenter
A cylindrical fermenter that is 4 m in diameter contains 100 m3 of medium (Figure 1.7). It is mixed at an agitation power of 1 kW/m3
