Optimization strategies for enhanced production of single cell protein: recent advances and perspectives

Abstract

The increasing demand for protein supplementation in both animal and human nutrition, coupled with the limitations of conventional protein sources, necessitates research into sustainable alternatives. Single-cell proteins (SCPs) are the dried biomass of microorganisms such as algae, yeast, and bacteria that are cultured under controlled conditions. Production of SCP has emerged as a promising solution, offering advantages such as rapid production, minimal land requirement, and adaptability to diverse climatic conditions; however, their large-scale production requires meticulous optimization of entire process of production. Efficient optimization enhances productivity, product quality, and cost-efficiency, making SCP production economically viable, safer and sustainable. Optimization involves standardization of various regulating factors such as temperature, pH, nutrient availability and type, oxygen level, agitation, etc., which requires a large number of experimental trials and a high consumption of resources. To overcome these challenges, optimization of SCP production is increasingly using multivariate statistical techniques, including response surface methodology (RSM), and factorial design. Computer modelling and simulation techniques offer insights into the complex dynamics of production systems. This review discusses popularly followed strategies for optimization of SCP production, beginning with an overview of the fundamentals and significance of SCP. Methods of optimization, including classical methods and RSM, along with integration of mathematical modelling into the Design of Experiment (DoE), are then examined. Case studies have also been discussed to illustrate successful optimization approaches while addressing applications of SCP and, challenges and future directions in SCP optimization/ production.

Graphical abstract