PRODIGIO is a three-year Research and Innovation Action funded by the EU H2020 Framework Programme under the topic Developing the next generation of renewable energy technologies.

PRODIGIO will boost the efficiency of solar energy conversion into biogas by increasing the performance of i) microalgae production systems and ii) anaerobic digestion systems, thanks to the development of early-warning signals for improved systems monitoring and control.

Microalgae Production Systems

Microalgae are some of nature’s finest examples of solar energy conversion systems, transforming carbon dioxide into complex organic molecules through photosynthesis. They are capable of achieving solar energy to biomass conversion efficiencies up to one order of magnitude higher than oleaginous crops, and there is biotechnology potential to further increase conversion efficiency. Due to their outstanding photosynthetic yields and ability to grow in non-arable lands, non-potable water sources (e.g. wastewater, seawater), and a wide range of environmental conditions, there is much interest in the use of microalgae biomass as a source of truly sustainable bioenergy feedstock.

Anaerobic Digestion Systems

Anaerobic digestion (AD) is probably the most economically attractive process for the production of biofuel from microalgae since it does not require drying of biomass and it is a relatively simple procedure from an infrastructure and engineering perspective. AD is a natural biomass degradation process carried out by microorganisms, which very efficiently transform the organic matter firstly into intermediate bioproducts and finally into biogas under anaerobic conditions.

Early-warning Signal

Early warning signals are simple properties of a system that change in characteristic ways prior to a critical transition. Progress in bio-analytical chemistry has resulted in a vast array of chemical probes and biosensors, which enable the process engineer to monitor a wide variety of parameters. However, the advancement of system failure prediction technologies requires knowing the most effective process parameters with which to guarantee failure prediction as far in advance as possible. Currently, the availability of early warning signals for critical transitions in microalgae biomass production and anaerobic digestion systems is very low, critically limiting our ability to implement effective process monitoring and control systems.


Scaling-up biological processes from laboratory-scale experimental trials to industrial-scale applications leads to a systematic loss of efficiency, which impairs the economic viability and the potential environmental benefits of the technology. Process instability is critical in nonlinear dynamical systems, such as bio-based production systems, where the functioning of complex microbial communities largely controls their performance stability. These dynamical systems can undergo transitions where the system shifts from one stable state to another at a critical threshold or tipping point. Because critical state transitions alter the efficiency of microbial communities for the provision of services, anticipating the failure of the system is crucial for the timely implementation of prevention and/or mitigation countermeasures that ensure process stability and technology profitability in the long-term.

Conceptual diagram showing hypothetical interactions among the components (X1, X2, X3, …..Xn) of the system, such as the target product (green), the core members of the microbiomes (blue) and relevant environmental variables (red) in an idealised bioreactor transiting from the normal state to the failure state through the pre-failure state. Interactions among components are denoted by arrows and can be causal (black arrows) or spurious (grey dot arrows). Causal interactions can be stabilizing (e.g. fermenting bacteria adjusting pH in AD systems) or destabilizing (e.g. deleterious species infecting microalgae in PBRs). The strength of causal interactions, which is denoted by the thickness of the arrows, influences the dynamics of the system through the enhancement of either stabilizing or destabilizing effects.

PRODIGIO will develop an innovative and versatile methodology for the identification of early warning signals that combines causal detection methods with the analysis of interaction networks. The method sequentially calculates the interaction network over time (its topology and strength of the interactions) and, at each time step, it calculates a measure of the stability of the network. When stability approaches a critical value (or tipping point), the method evaluates the dominant eigenvalue of the interaction network, providing the best warning/s for system failure. By combining ‘big data’ acquisition from thoroughly designed perturbation experiments in bioreactor systems, advanced metaOmics and chemical fingerprint technologies, state-of-the-art bioinformatic tools, and novel methods for the analysis of causal interaction networks, PRODIGIO will decode triggers, identify early warnings, define threshold values, and calculate warning times for critical state transitions in bioreactor systems.


All the project activities are separated into 7 clearly defined activities or work packages (WPs) plus an additional WP-8 for ethics requirements related to all other WPs. The following Pert chart shows the links between the different activity streams and work-packages making up the backbone of the PRODIGIO project.


The EU’s energy policy has set ambitious objectives for 2030 including a 30% share of energy from renewables and a 40% cut in CO2 emissions compared to 1990.

If managed sustainably, biofuels are renewable energy resources for heat, power and transportation that can contribute to reducing CO2 emissions. However, as of 2020, the adoption of biofuels falls short of the predicted expectations to align with the sustainable development scenario (SDS). To increase the adoption of biofuels and meet the SDS targets, it is mandatory to achieve performance breakthroughs and cost reductions for large-scale production of advanced biofuels.

Microalgae biomethanisation represents an exciting new avenue of biotechnology leading to the realization of a truly sustainable renewable fuel technology and a circular bio-economy strongly advocated in the EU recently. The project PRODIGIO will contribute to efficiency-enhancing technologies and feedstock diversification, boosting the economic, environmental and social benefits of this renewable energy technology, while contributing to strengthening EU leadership in bioenergy.

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