Mixed cultures are prevalent in nature, which are biological systems with more than one type of organism sharing or competing for available nutrients. Compared to single cultures, mixed culture present many advantages. For example, when organisms in mixed cultures work symbiotically, the cells’ metabolic pathways complement each other and can result in efficient utilization of substrates and increased product yield. Other advantages include the use of mixed or cheaper substrates, reduction in sterilization and increased robustness to environmental changes. The application of mixed cultures in biotechnology has expanded rapidly in the last a few years, with applications ranging from wastewater treatment, biogas production, soil remediation, to chemical production such as solvent, antibiotics, acids and other valued commodities.

At the same time, many challenges remain for effective mixed culture applications. One of them is how to efficiently and accurately monitor the individual cell populations in a mixed culture. The current approaches on individual cell mass quantification are suitable for off-line, infrequent characterization of mixed cultures. In this work, we propose a fast and accurate ‘soft sensor’ approach for estimating individual cell concentrations in mixed cultures. The proposed approach utilizes absorption spectrum of a mixed culture sample measured by a spectrophotometer over a range of wavelengths. A multivariate linear regression method, partial least squares or PLS, is applied to correlate individual cell concentrations to the spectrum.

The proposed soft sensor is demonstrated using a methanotroph microalgae coculture. Recent findings published in Nature and Nature Geoscience suggest that the coupling of methane oxidation and oxygenic photosynthesis are prevalent in nature and reduce CH₄ emissions and reuse CO₂. These findings suggest that the coculture of methanotrophs and microalgae represents not only a feasible, but also a highly promising strategy for agriculture waste and wastewater treatment: the biogas and wastewater produced from anaerobic digestion of agriculture waste can be converted by the coculture of methanotroph and microalgae to cell biomass for animal food or biodiesel production, which not only significantly reduces the greenhouse gases emission, but also captures the valuable nutrients contained in digester effluent. Several case studies are presented to demonstrate the effectiveness and robustness of the soft sensor approach.