Software sensors in the monitoring of microalgae cultivations

Author:

Porras Reyes Luis,Havlik Ivo,Beutel SaschaORCID

Abstract

AbstractMicroalgae are well-known photosynthetic microorganisms used as cell factories for the production of relevant biotechnological compounds. Despite the outstanding characteristics attributed to microalgae, their industrial-scale production still struggles with scale-up problems and economic feasibility. One important bottleneck is the lack of suitable online sensors for the reliable monitoring of biological parameters, mostly concentrations of intracellular components, in microalgae bioprocesses. Software sensors provide an approach to improving the monitoring of those process parameters that are difficult to quantify directly and are therefore only indirectly accessible. Their use aims to improve the productivity of microalgal bioprocesses through better monitoring, control and automation, according to the current demands of Industry 4.0. In this review, a description of the microalgae components of interest as candidates for monitoring in a cultivation, an overview of software sensors, some of the available approaches and tools, and the current state-of-the-art of the design and use of software sensors in microalgae cultivation are presented. The latter is grouped on the basis of measurement methods used as software sensor inputs, employing either optical or non-optical techniques, or a combination of both. Some examples of software sensor design using simulated process data are also given, grouped according to their design, either as model-driven or data-driven estimators.

Funder

H2020 Marie Skłodowska-Curie Actions

Gottfried Wilhelm Leibniz Universität Hannover

Publisher

Springer Science and Business Media LLC

Reference156 articles.

1. Humana Press;H Abdi,2013

2. Aguilar-Garnica E, García-Sandoval JP (2015) Software sensors design and selection for the production of biodiesel from grease trap wastes. In: Gernaey KV, Huusom JK, Gani R (eds) Computer aided chemical engineering. Elsevier, Great Britain, pp 1589–1594

3. Andersen R (2005) Algal culturing techniques. Elsevier Academic Press, New York, p 578

4. Andersen RA (2013) The microalgal cell. In: Handbook of Microalgal Culture, Second edition. Wiley, pp 1–20

5. Appl C, Moser A, Baganz F, Hass VC (2021) Digital Twins for bioprocess control strategy development and realisation. In: Herwig C, Pörtner R, Möller J (eds) Digital Twins: applications to the design and optimization of bioprocesses. Springer International Publishing, Cham, pp 63–94

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