Biosystem & Bioprocesses Engineering
From mathematical modeling and computer-aided simulation to design, control and optimization of bioprocesses and biological systems.
The world around us can be explained to a great extent by understanding the systems that compose it and the processes that connect them.
The IIM-CSIC's Biosystem & Bioprocess Engineering group seeks to develop new methods and tools (mainly software) for process systems engineering, which enable the simulation, optimization and control of bioprocesses, such as those involved in food processing and preservation and in industrial biotechnology.
The group applies process systems engineering methods to improve the efficiency of key industrial processes, reducing their environmental impact and improving the quality and safety of their products.
Its focus is model identification, optimization, monitoring and robust control of non-linear dynamic systems, including distributed parameter systems (convection-diffusion-reaction). The group considers a broad spectrum of applications, namely fisheries management, food processing, quality and safety—including antimicrobial resistance—and industrial biotechnology.
- DigitAlg -
<p>Programa Ciencias Mariñas: Xemelgo dixital do cultivo de algas na acuicultura multitrófica integrada</p>
Principal investigator:BalsaCantoEvaFunding body:El Programa de Ciencias Mariñas de Galicia es 1 de los 5 programas de Ciencias Marinas de los Planes Complementarios de I+D+I del Plan de Recuperación Transformación y Resilencia. Financiado por FEMP/FEMPA.Funding for IIM-CSIC:122667€Go to project pageFromto - ATOPES -
<p>Programa Ciencias Mariñas: Aplicación de Tecnoloxías Innovadoras para a Obtención de Datos Pesqueiros</p>
Principal investigator:TaboadaAnteloLuisFunding body:El Programa de Ciencias Mariñas de Galicia es 1 de los 5 programas de Ciencias Marinas de los Planes Complementarios de I+D+I con las CCAA del Plan de Recuperación Transformación y Resilencia (NextGenerationEU).Funding for IIM-CSIC:137391€Go to project pageFromto - DATAMARE -
<p>Programa Ciencias Mariñas: Plataforma integrada de datos mariños</p>
Principal investigator:VeloLanchasAntónFunding body:El Programa de Ciencias Mariñas de Galicia es 1 de los 5 programas de Ciencias Marinas de los Planes Complementarios de I+D+I con las CCAA del Plan de Recuperación Transformación y Resilencia (NextGenerationEU).Funding for IIM-CSIC:112585€Go to project pageFromto - PreCalA -
<p>Programa Ciencias Mariñas: Ferramentas para a predición da calidade en productos da acuicultura</p>
Principal investigator:VilasFernándezCarlosFunding body:El Programa de Ciencias Mariñas de Galicia es 1 de los 5 programas de Ciencias Marinas de los Planes Complementarios de I+D+I del Plan de Recuperación Transformación y Resilencia. Financiado por FEMP/FEMPA.Funding for IIM-CSIC:100281€Go to project pageFromto - aCIDit -
<p>a-CIDiT - Modelos basados en datos y actualización de modelos para gemelos digitales</p>
Principal investigator:TaboadaAnteloLuisVilasFernándezCarlosFunding body:Ayuda PID2021-123654OB-C32 financiada por MCIN/AEI/10.13039/501100011033 y por la Unión Europea NextGenerationEU/PRTRFunding for IIM-CSIC:94200€Go to project pageFromto
- Pedreira, A.; Vázquez, J.A.; García, M.R. (2022) Kinetics of Bacterial Adaptation, Growth, and Death at Didecyldimethylammonium Chloride sub-MIC Concentrations Frontiers in Microbiology DOI:10.3389/fmicb.2022.758237
- Ovalle, J.C.; Vilas, C.; Antelo, L.T. (2022) On the use of deep learning for fish species recognition and quantification on board fishing vessels Marine Policy DOI:10.1016/j.marpol.2022.105015
- González, P.; Osorio, R.R.; Pardo, X.C.; Banga, J.R.; Doallo, R. (2022) An efficient ant colony optimization framework for HPC environments Applied Soft Computing Journal DOI:10.1016/j.asoc.2021.108058
- Otero-Muras I; Banga JR (2021) Synthetic Gene Circuit Analysis and Optimization " Computational Methods in Synthetic Biology" Humana Press / Springer ISBN:978-1-0716-0822-7
- Otero-Muras I; Banga JR (2021) Automated Biocircuit Design with SYNBADm " Synthetic Gene Circuits" Springer ISBN:978-1-0716-1031-2
- TFM - Andrea Arribas Jimeno (26/09/2022) Aplicabilidad de la tecnología de imágenes hiperespectrales (HSI) como método no invasivo para la evaluación de la calidad del pescado UNIVERSIDAD DE SANTIAGO DE COMPOSTELA
- TFM - Artai Rodríguez Moimenta (19/07/2020) Desarrollo de un modelo de corte mecanístico que permita describir un proceso de fermentación mixta Universidad de Vigo (UVigo)
- TFG - Laura Honrubia Baamonde (11/07/2019) Optimization of Benzalkonium Chloride treatment in the disinfection of L. Monocytogenes in the Food Industry UNIVERSIDAD DE LLEIDA
- TFM - Pablo de la Torre Fernández (20/09/2018) Modelado del proceso de fermenatición vínica: co-cultivo de especies no convencionales Universidade da Coruña
- PhD - Alejandro López Núñez (18/07/2018) CONTRIBUTIONS TO MATHEMATICAL MODELLING AND NUMERICAL SIMULATION OF BIOFILMS UdC
- WASHTOP -
<p>Water Associated Safety Hazards in the Treatment of Produce</p>
Principal investigator:RodríguezGarcíaMíriamFunding body:European Food Safety Authority (EFSA)Funding for IIM-CSIC:80000€Go to project pageFromto
- Capabilities | Development of Artificial Intelligence applications for fisheries management
Development of Deep Learning algorithms that allow automating fisheries monitoring processes and reducing time and costs compared with processing by human observers. The applications developed range from innovative systems for real-time remote electronic monitoring, which identify and quantify total catches of fishing vessels (e.g., iObserver), to new image recognition techniques that allow individually identifying fish and estimating population parameters.
- Capabilities | Development of intelligent and active food labels
Development of smart food labels based on models for oxidation, microbial growth, etc. that let consumers know when food is no longer fit to eat, helping to prevent food waste, and give information on freshness, package temperature, etc.
- Capacidades | Deseño de procedementos de desinfección e modelaxe para a prevención da resistencia a axentes antimicrobianos
Desenvolvemento de estratexias químicas (combinacións de desinfectantes, aceites esenciais) e biolóxicas (encimas, fagos) que sexan efectivas na eliminación de biopelículas monoespecíficas e mixtas en superficies usadas na industria alimentaria. Proba de biocidas e desenvolvemento de mellores estratexias de dosificación de biocidas para a industria alimentaria, garantindo a seguridade alimentaria ao tempo que se evita a adquisición de resistencia a axentes antimicrobianos.
- Capacidades | Desarrollo de aplicaciones de Inteligencia Artificial para la gestión de pesquerías
Desarrollo de algoritmos de Deep Learning que permiten automatizar los procesos de monitorización de las pesquerías y reducir el tiempo y los costes en comparación con el procesado mediante observación humana. Las aplicaciones desarrolladas van desde sistemas innovadores de monitorización electrónica remota en tiempo real, que identifican y cuantifican las capturas totales de los barcos de pesca (p. ej., iObserver), hasta nuevas técnicas de reconocimiento de imagen que permiten identificar los peces a nivel individual y estimar parámetros poblacionales.
- Capacidades | Desarrollo de etiquetado inteligente y activo de los alimentos
Desarrollo de etiquetas inteligentes para los alimentos basadas en modelos de oxidación, crecimiento microbiano, etc. que permitan a quienes los consumen saber cuándo los alimentos ya no son aptos para su consumo, ayudando a evitar el desperdicio de alimentos, y que informen sobre su frescura, temperatura del paquete, etc
- Prototype | Morbidostat: Unraveling Antimicrobial Resistance
Morbidostat is a computer-controlled continuous culture device that automatically adjusts drug concentration to maintain constant growth inhibition in microbial cultures. As bacteria acquire mutations that give them resistance against drugs, they are able to tolerate higher drug concentrations and grow faster, thus removing selective pressure, the driving force of evolution. To compensate for this, morbidostat increases drug concentration sufficiently to keep bacteria at their original growth rate, therefore maintaining selective pressure over time. This system allows for data acquisition to model microbial evolution under antimicrobial stress, optimize biocide dosage strategies and develop highly antimicrobial-resistant strains used to test the performance of new biocides, among other applications.
- Software | Model-based design of smart active packaging systems with antimicrobial activity
Matlab code to perform simulations and optimize packaging design using natural antimicrobials (carvacrol) for hake (Merluccius merluccius). In addition, different polymers are considered as possible active packaging materials.
More information here.
- Software | DOTcvpSB: Matlab toolbox for Dynamic Optimization in Systems Biology
DOTcvpSB is a toolbox written in MATLAB that uses the control vector parameterization (CVP) method to handle continuous and mixed integer dynamic optimization problems. DOTcvpSB has been successfully applied to several problems in systems biology and bioprocess engineering.
More information here.
- Software | Fish-T-TaB Simulator: Temperature simulator for fish stored in tubs and boxes
This model was developed and applied by members of the EFSA Working Group on the transport/storage of fresh fishery products during the preparatory work on the BIOHAZ Scientific Opinion on the use of "tubs" for transporting and storing fresh fishery products (EFSA-Q-2019-00053). Heat transfer modeling was applied to estimate surface temperature of fish during the temperature-related processes of cooling and subsequently maintaining the chill temperature of the fish (‘cooling’ process) and/or maintaining the chill temperature (‘keeping’ process) for fish kept in ice (in boxes) versus in water and ice (in tubs) under similar transport/storage conditions.
More information here.
- Software | CRNreals: distinguishability analysis of biochemical reaction networks
A software toolbox that supports the distinguishability analysis of chemical reaction network (CRN) models.
More information here.
