“…Different ML techniques have been employed to manage fermentation parameters such as temperature, pH, dissolved oxygen, aeration rate, feeding rate, and agitation speed. For instance, Gaussian process regression (GPR) was implemented to forecast the biomass concentration of S. cerevisiae based solely on substrate flow rate, given that certain variables could not be measured in real-time (Masampally et al, 2018). Similarly, the challenge of optimum growth temperature (OGT) detection in non-conventional microorganisms has been solved using the amino acid composition as input for employing six different ML models since amino acid composition is strongly related to the OGT (Li et al, 2019).…”
Section: Innovative Fermentation and Bioprocess Engineeringmentioning
Omega-3 fatty acids, including alpha-linolenic acids (ALA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA), have shown major health benefits, but the human body’s inability to synthesize them has led to the necessity of dietary intake of the products. The omega-3 fatty acid market has grown significantly, with a global market from an estimated USD 2.10 billion in 2020 to a predicted nearly USD 3.61 billion in 2028. However, obtaining a sufficient supply of high-quality and stable omega-3 fatty acids can be challenging. Currently, fish oil serves as the primary source of omega-3 fatty acids in the market, but it has several drawbacks, including high cost, inconsistent product quality, and major uncertainties in its sustainability and ecological impact. Other significant sources of omega-3 fatty acids include plants and microalgae fermentation, but they face similar challenges in reducing manufacturing costs and improving product quality and sustainability. With the advances in synthetic biology, biotechnological production of omega-3 fatty acids via engineered microbial cell factories still offers the best solution to provide a more stable, sustainable, and affordable source of omega-3 fatty acids by overcoming the major issues associated with conventional sources. This review summarizes the current status, key challenges, and future perspectives for the biotechnological production of major omega-3 fatty acids.
“…Different ML techniques have been employed to manage fermentation parameters such as temperature, pH, dissolved oxygen, aeration rate, feeding rate, and agitation speed. For instance, Gaussian process regression (GPR) was implemented to forecast the biomass concentration of S. cerevisiae based solely on substrate flow rate, given that certain variables could not be measured in real-time (Masampally et al, 2018). Similarly, the challenge of optimum growth temperature (OGT) detection in non-conventional microorganisms has been solved using the amino acid composition as input for employing six different ML models since amino acid composition is strongly related to the OGT (Li et al, 2019).…”
Section: Innovative Fermentation and Bioprocess Engineeringmentioning
Omega-3 fatty acids, including alpha-linolenic acids (ALA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA), have shown major health benefits, but the human body’s inability to synthesize them has led to the necessity of dietary intake of the products. The omega-3 fatty acid market has grown significantly, with a global market from an estimated USD 2.10 billion in 2020 to a predicted nearly USD 3.61 billion in 2028. However, obtaining a sufficient supply of high-quality and stable omega-3 fatty acids can be challenging. Currently, fish oil serves as the primary source of omega-3 fatty acids in the market, but it has several drawbacks, including high cost, inconsistent product quality, and major uncertainties in its sustainability and ecological impact. Other significant sources of omega-3 fatty acids include plants and microalgae fermentation, but they face similar challenges in reducing manufacturing costs and improving product quality and sustainability. With the advances in synthetic biology, biotechnological production of omega-3 fatty acids via engineered microbial cell factories still offers the best solution to provide a more stable, sustainable, and affordable source of omega-3 fatty acids by overcoming the major issues associated with conventional sources. This review summarizes the current status, key challenges, and future perspectives for the biotechnological production of major omega-3 fatty acids.
“…ANN was further used in conjunction with a genetic algorithm to determine the best nutrient composition for producing potential anti-cancer compounds in S. cerevisiae ( Zheng et al, 2017 ). In a different study, the focus is on predicting the required concentration of S. cerevisiae in a bioreactor, by simply using substrate flow rate as input ( Masampally et al, 2018 ). To be able to do so, three sequential models, using Gaussian process regression based on Bayes’ rules, were applied to infer important intermediate variables, such as the gas hold-up, and the concentrations of biomass and dissolved oxygen, which could not be measured in real time.…”
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