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Baroukh C, Mairet F, Bernard O. The paradoxes hidden behind the Droop model highlighted by a metabolic approach. FRONTIERS IN PLANT SCIENCE 2022; 13:941230. [PMID: 36072315 PMCID: PMC9442053 DOI: 10.3389/fpls.2022.941230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 08/02/2022] [Indexed: 06/15/2023]
Abstract
We propose metabolic models for the haptophyte microalgae Tisochrysis lutea with different possible organic carbon excretion mechanisms. These models-based on the DRUM (Dynamic Reduction of Unbalanced Metabolism) methodology-are calibrated with an experiment of nitrogen starvation under day/night cycles, and then validated with nitrogen-limited chemostat culture under continuous light. We show that models including exopolysaccharide excretion offer a better prediction capability. It also gives an alternative mechanistic interpretation to the Droop model for nitrogen limitation, which can be understood as an accumulation of carbon storage during nitrogen stress, rather than the common belief of a nitrogen pool driving growth. Excretion of organic carbon limits its accumulation, which leads to a maximal C/N ratio (corresponding to the minimum Droop N/C quota). Although others phenomena-including metabolic regulations and dissipation of energy-are possibly at stake, excretion appears as a key component in our metabolic model, that we propose to include in the Droop model.
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Affiliation(s)
- Caroline Baroukh
- LIPME, Université de Toulouse, INRAE, CNRS, Castanet-Tolosan, France
| | | | - Olivier Bernard
- Biocore, INRIA, Université Côte d'Azur, Sophia Antipolis, France
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2
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Rodríguez-Miranda E, Sánchez-Zurano A, Guzmán JL, Acién G, Visioli A. A seasonal simulation approach for culture depth influence on the temperature for different characterized microalgae strains. Biotechnol J 2022; 17:e2100489. [PMID: 35567392 DOI: 10.1002/biot.202100489] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Revised: 04/29/2022] [Accepted: 05/07/2022] [Indexed: 11/07/2022]
Abstract
Irradiance and temperature are among the most important variables that affect microalgae growth, being both difficult to control in outdoor raceway reactors utilized for large-scale production of microalgae biomass. They are mainly a function of the location of the reactors, thus, producing certain strains of microalgae in inappropriate places conduces to the failure of the systems. To be able to determine important parameters of any microalgae strains on the performance of the culture, such as the influence of irradiance and temperature, is a powerful tool in decision-making processes. In addition, whatever the strain and location, operation strategies must be defined for each specific case, such as the imposed dilution rate and culture depth, both influencing the light availability and temperature of the culture as major variables determining the biomass productivity. In this paper, a simulation-based methodology is proposed to establish the influence of season and culture depth on the 1-year age irradiance and temperature of the culture, and thus on the biomass productivity of different microalgae strains. Up to five of the most frequently produced strains, such as Spirulina platensis, Chlorella vulgaris, Nannochloropsis gaditana, Isochrysis galbana and Scenedesmus almeriensis have been considered. The challenge is to develop an easy-to-manage decision-making tool for the optimal design and operation of large-scale microalgae facilities. Especially, dates for microalgae production and culture depth at which the reactors must be operated will be provided, being valid for any microalgae strain. The proposed methodology will largely contribute to the risk of investment in this field, then to enlarge the relevance of the microalgae production industry. This article is protected by copyright. All rights reserved.
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Affiliation(s)
| | - Ana Sánchez-Zurano
- Departamento de Ingeniería Química, CIESOL ceiA3, Universidad de Almería, Almería, Spain
| | - José Luis Guzmán
- Departamento de Informática, CIESOL ceiA3, Universidad de Almería, Almería, Spain
| | - Gabriel Acién
- Departamento de Ingeniería Química, CIESOL ceiA3, Universidad de Almería, Almería, Spain
| | - Antonio Visioli
- Department of Mechanical and Industrial Engineering, University of Brescia, Brescia, Italy
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3
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Bekirogullari M, Figueroa-Torres GM, Pittman JK, Theodoropoulos C. Models of microalgal cultivation for added-value products - A review. Biotechnol Adv 2020; 44:107609. [PMID: 32781245 DOI: 10.1016/j.biotechadv.2020.107609] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 07/07/2020] [Accepted: 08/04/2020] [Indexed: 12/23/2022]
Abstract
Microalgae are considered a promising feedstock for biorefineries given that their chemical composition - rich in carbohydrate and lipid - can be directed towards the co-production of various value-added fuels and chemicals. Production of microalgal biomass for biorefinery purposes requires the identification and establishment of optimal cultivation systems, a crucial yet complicated task due to the numerous factors (e.g. media composition, light, temperature) that simultaneously regulate biomass growth and intracellular composition. Modelling these biological processes, taking into account a single or multiple growth-limiting factors, offers a valuable tool to simulate, design and optimise the dynamics of microalgae cultivation. This review provides an overview of existing models developed to describe microalgal growth processes at the macroscopic scale (also termed black-box models) and discusses their formulation in detail. The black-box kinetic modelling frameworks are compiled into single-factor (6 formulations) and multiple-factor (32 formulations - further divided into non-interactive, additive, and interactive) growth kinetic models, as reported in more than 80 studies, for the prediction of biomass growth as a function of major operational factors such as media composition (e.g. nutrient concentration) and environmental factors (e.g. transient light and temperature). In addition, the review focuses on those models that further account for the production dynamics of two microalgal intracellular products with renowned potential as biorefinery substrates: carbohydrate and lipid molecules. Models of microalgal cultivation dynamics offer a robust engineering tool to understand the natural yet complex responses of microalgae to their growing environment and can help - if used appropriately - to optimise microalgae cultivation and increase the economic viability and sustainability of microalgal systems.
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Affiliation(s)
- Mesut Bekirogullari
- Department of Chemical Engineering and Analytical Science, Biochemical and Bioprocess Engineering Group, The University of Manchester, Manchester M13 9PL, UK
| | - Gonzalo M Figueroa-Torres
- Department of Chemical Engineering and Analytical Science, Biochemical and Bioprocess Engineering Group, The University of Manchester, Manchester M13 9PL, UK
| | - Jon K Pittman
- Department of Earth and Environmental Sciences, The University of Manchester, Manchester M13 9PL, UK
| | - Constantinos Theodoropoulos
- Department of Chemical Engineering and Analytical Science, Biochemical and Bioprocess Engineering Group, The University of Manchester, Manchester M13 9PL, UK.
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4
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Robles Á, Capson-Tojo G, Galès A, Ruano MV, Sialve B, Ferrer J, Steyer JP. Microalgae-bacteria consortia in high-rate ponds for treating urban wastewater: Elucidating the key state indicators under dynamic conditions. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2020; 261:110244. [PMID: 32148311 DOI: 10.1016/j.jenvman.2020.110244] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Revised: 01/18/2020] [Accepted: 02/04/2020] [Indexed: 06/10/2023]
Abstract
On-line performance indicators of a microalgae-bacteria consortium were screened out from different variables based on pH and dissolved oxygen on-line measurements via multivariate projection analysis, aiming at finding on-line key state indicators to easily monitor the process. To fulfil this objective, a pilot-scale high-rate pond for urban wastewater treatment was evaluated under highly variable conditions, i.e. during the start-up period. The system was started-up without seed of either bacterial or microalgal biomass. It took around 19 days to fully develop a microalgal community assimilating nutrients significantly. Slight increases in the biomass productivities in days 26-30 suggest that the minimum time for establishing a performant bacteria-microalgae consortium could be of around one month for non-inoculated systems. At this point, the process was fully functional, meeting the European discharge limits for protected areas. The results of the statistical analyses show that both the pH and the dissolved oxygen concentration represent accurately the biochemical processes taking place under the start-up of the process. Both pH and dissolved oxygen represented accurately also the performance of the high-rate algal pond, being affordable, easily-implemented, options for monitoring, control and optimization of industrial-scale processes.
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Affiliation(s)
- Ángel Robles
- Departament d'Enginyeria Química, Escola Tècnica Superior D'Enginyeria, Universitat de València, Avinguda de la Universitat s/n, 46100, Burjassot, Valencia, Spain.
| | - Gabriel Capson-Tojo
- CRETUS Institute, Department of Chemical Engineering, School of Engineering, Universidade de Santiago de Compostela, 15782, Santiago de Compostela, Spain
| | - Amandine Galès
- LBE, Univ. Montpellier, INRA, 102 avenue des Etangs, 11100, Narbonne, France
| | - María Victoria Ruano
- Departament d'Enginyeria Química, Escola Tècnica Superior D'Enginyeria, Universitat de València, Avinguda de la Universitat s/n, 46100, Burjassot, Valencia, Spain
| | - Bruno Sialve
- LBE, Univ. Montpellier, INRA, 102 avenue des Etangs, 11100, Narbonne, France
| | - José Ferrer
- Institut Universitari d'Investigació d'Enginyeria de l'Aigua i Medi Ambient (IIAMA), Universitat Politècnica de València, Camí de Vera s/n, 46022, Valencia, Spain
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5
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Cea‐Barcia G, López‐Caamal F, Torres‐Zúñiga I, Hernández‐Escoto H. Biogas purification via optimal microalgae growth: A literature review. Biotechnol Prog 2018; 34:1513-1532. [DOI: 10.1002/btpr.2686] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2017] [Revised: 05/08/2018] [Indexed: 01/02/2023]
Affiliation(s)
- Glenda Cea‐Barcia
- Departamento de Ciencias Ambientales., División de Ciencias de la Vida del campus Irapuato‐SalamancaUniversidad de Guanajuato Irapuato Mexico
| | - Fernando López‐Caamal
- Departamento de Ingeniería Química, División de Ciencias Naturales y Exactas del campus Guanajuato.Universidad de Guanajuato Guanajuato Mexico
| | - Ixbalank Torres‐Zúñiga
- C. A. Telemática, Departamento de Ingeniería Electrónica., División de Ingenierías del campus Irapuato‐SalamancaUniversidad de Guanajuato Salamanca Mexico
| | - Héctor Hernández‐Escoto
- Departamento de Ingeniería Química, División de Ciencias Naturales y Exactas del campus Guanajuato.Universidad de Guanajuato Guanajuato Mexico
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De-Luca R, Trabuio M, Barolo M, Bezzo F. Microalgae growth optimization in open ponds with uncertain weather data. Comput Chem Eng 2018. [DOI: 10.1016/j.compchemeng.2018.07.005] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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7
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López-Pérez PA, Cuervo-Parra JA, Robles-Olvera VJ, Del C Rodriguez Jimenes G, Pérez España VH, Romero-Cortes T. Development of a Novel Kinetic Model for Cocoa Fermentation Applying the Evolutionary Optimization Approach. INTERNATIONAL JOURNAL OF FOOD ENGINEERING 2018. [DOI: 10.1515/ijfe-2017-0206] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
AbstractTraditional Mexican cocoa fermentation performed in batch was studied by applying kinetic modelling with experimental validation. Similar microbiological behaviour was observed up to 60 h, with a temperature increase at 72 h that remained constant (50 °C) until 156 h. Metabolite-production kinetics (ethanol and acetic acid) from degradable mucilage (glucose) was explored. Exploration involved applying different combinations of unstructured growth models, in order to consider the effect of temperature when predicting the concentration of metabolites in these microorganisms. Two methods were used to optimize model parameters: the Levenberg–Marquardt optimization approach and Genetic Algorithms (GAs). GAs which could be used to scale up the fermentation process indicated the applicability of this model for predicting fermentation quality. The maximum specific rate average for μmax and saturation constant (Ks) were 0.0961 h−1 and 1.4 mg/g m.s., respectively. The results obtained indicate the expediency of this technique for future application in the design and control of batch fermentation.
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Affiliation(s)
- Pablo A. López-Pérez
- Escuela Superior de Apan, Universidad Autónoma del Estado de Hidalgo, Carretera Apan-Calpulalpan, Km 8, Chimalpa Tlalayote s/n, Colonia Chimalpa, Apan, HgoC.P. 43900, Mexico
| | - Jaime A. Cuervo-Parra
- Escuela Superior de Apan, Universidad Autónoma del Estado de Hidalgo, Carretera Apan-Calpulalpan, Km 8, Chimalpa Tlalayote s/n, Colonia Chimalpa, Apan, HgoC.P. 43900, Mexico
| | - Víctor José Robles-Olvera
- Unidad de Investigación y Desarrollo en Alimentos.Instituto Tecnológico de Veracruz. Av. M.A. de Quevedo No. 2779. Col. Formando Hogar, Veracruz, VerC.P. 91897. Mexico
| | - Guadalupe Del C Rodriguez Jimenes
- Unidad de Investigación y Desarrollo en Alimentos.Instituto Tecnológico de Veracruz. Av. M.A. de Quevedo No. 2779. Col. Formando Hogar, Veracruz, VerC.P. 91897. Mexico
| | - Victor H. Pérez España
- Escuela Superior de Apan, Universidad Autónoma del Estado de Hidalgo, Carretera Apan-Calpulalpan, Km 8, Chimalpa Tlalayote s/n, Colonia Chimalpa, Apan, HgoC.P. 43900, Mexico
| | - Teresa Romero-Cortes
- Escuela Superior de Apan, Universidad Autónoma del Estado de Hidalgo, Carretera Apan-Calpulalpan, Km 8, Chimalpa Tlalayote s/n, Colonia Chimalpa, Apan, HgoC.P. 43900, Mexico
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8
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Béchet Q, Coulombier N, Vasseur C, Lasserre T, Le Dean L, Bernard O. Full-scale validation of an algal productivity model including nitrogen limitation. ALGAL RES 2018. [DOI: 10.1016/j.algal.2018.02.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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9
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Hurst T, Rehbock V. Optimal control for micro-algae on a raceway model. Biotechnol Prog 2017; 34:107-119. [PMID: 28734039 DOI: 10.1002/btpr.2532] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2016] [Revised: 07/18/2017] [Indexed: 11/06/2022]
Abstract
We apply numerical optimal control methods to an existing algae growth model with the aim to determine the best performance of the model under known conditions using a variety of decision variables. We transform the system of differential algebraic equations in the existing model to a system of ordinary differential equations which introduces dynamics for average light intensity and chlorophyll. In addition, we allow for variable nitrogen concentration of the inflow as well as variable initial nitrogen concentration of the raceway. Our main focus is on optimizing of the production of lipids. We calculate both open and closed loop optimal controllers and test their robustness. Finally, we also consider raceway depth as a decision variable. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 34:107-119, 2018.
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Affiliation(s)
- Todd Hurst
- Dept. of Mathematics and Statistics, Curtin University, Kent Street, Bentley, Perth, 6102, Western Australia
| | - Volker Rehbock
- Dept. of Mathematics and Statistics, Curtin University, Kent Street, Bentley, Perth, 6102, Western Australia
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10
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Béchet Q, Shilton A, Guieysse B. Maximizing Productivity and Reducing Environmental Impacts of Full-Scale Algal Production through Optimization of Open Pond Depth and Hydraulic Retention Time. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2016; 50:4102-4110. [PMID: 26928398 DOI: 10.1021/acs.est.5b05412] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
The ability to dynamically control algal raceway ponds to maximize biomass productivity and reduce environmental impacts (e.g., land and water use) with consideration of local constraints (e.g., water availability and climatic conditions) is an important consideration in algal biotechnology. This paper presents a novel optimization strategy that seeks to maximize growth (i.e., optimize land use), minimize respiration losses, and minimize water demand through regular adjustment of pond depth and hydraulic retention time (HRT) in response to seasonal changes. To evaluate the efficiency of this strategy, algal productivity and water demand were simulated in five different climatic regions. In comparison to the standard approach (constant and location-independent depth and HRT), dynamic control of depth and HRT was shown to increase productivity by 0.6-9.9% while decreasing water demand by 10-61% depending upon the location considered (corresponding to a decrease in the water footprint of 19-62%). Interestingly, when the fact that the water demand was limited to twice the local annual rainfall was added as a constraint, higher net productivities were predicted in temperate and tropical climates (15.7 and 16.7 g m(-2) day(-1), respectively) than in Mediterranean and subtropical climates (13.0 and 9.7 g m(-2) day(-1), respectively), while algal cultivation was not economically feasible in arid climates. Using dynamic control for a full-scale operation by adjusting for local climatic conditions and water constraints can notably affect algal productivity. It is clear that future assessments of algal cultivation feasibility should implement locally optimized dynamic process control.
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Affiliation(s)
- Quentin Béchet
- School of Engineering and Advanced Technology, Massey University , Private Bag 11 222, Palmerston North 4442, New Zealand
- INRIA BIOCORE , BP 93, 06902 Sophia Antipolis Cedex, France
| | - Andy Shilton
- School of Engineering and Advanced Technology, Massey University , Private Bag 11 222, Palmerston North 4442, New Zealand
| | - Benoit Guieysse
- School of Engineering and Advanced Technology, Massey University , Private Bag 11 222, Palmerston North 4442, New Zealand
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11
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Barbera E, Sforza E, Bertucco A. Maximizing the production of Scenedesmus obliquus in photobioreactors under different irradiation regimes: experiments and modeling. Bioprocess Biosyst Eng 2015; 38:2177-88. [DOI: 10.1007/s00449-015-1457-9] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2015] [Accepted: 08/07/2015] [Indexed: 11/29/2022]
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12
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Combe C, Hartmann P, Rabouille S, Talec A, Bernard O, Sciandra A. Long-term adaptive response to high-frequency light signals in the unicellular photosynthetic eukaryoteDunaliella salina. Biotechnol Bioeng 2015; 112:1111-21. [DOI: 10.1002/bit.25526] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Charlotte Combe
- Sorbonne Universites; UPMC Univ Paris 06; UMR 7093, LOV, Observatoire océanologique; F-06230 Villefranche/mer France
- CNRS, UMR 7093, LOV; Observatoire océanologique; F-06230 Villefranche/mer France
| | - Philipp Hartmann
- Sorbonne Universites; UPMC Univ Paris 06; UMR 7093, LOV, Observatoire océanologique; F-06230 Villefranche/mer France
- CNRS, UMR 7093, LOV; Observatoire océanologique; F-06230 Villefranche/mer France
- BIOCORE-INRIA, BP93; 06902 Sophia-Antipolis Cedex; France
| | - Sophie Rabouille
- Sorbonne Universites; UPMC Univ Paris 06; UMR 7093, LOV, Observatoire océanologique; F-06230 Villefranche/mer France
- CNRS, UMR 7093, LOV; Observatoire océanologique; F-06230 Villefranche/mer France
| | - Amelie Talec
- Sorbonne Universites; UPMC Univ Paris 06; UMR 7093, LOV, Observatoire océanologique; F-06230 Villefranche/mer France
- CNRS, UMR 7093, LOV; Observatoire océanologique; F-06230 Villefranche/mer France
| | - Olivier Bernard
- Sorbonne Universites; UPMC Univ Paris 06; UMR 7093, LOV, Observatoire océanologique; F-06230 Villefranche/mer France
- CNRS, UMR 7093, LOV; Observatoire océanologique; F-06230 Villefranche/mer France
- BIOCORE-INRIA, BP93; 06902 Sophia-Antipolis Cedex; France
| | - Antoine Sciandra
- Sorbonne Universites; UPMC Univ Paris 06; UMR 7093, LOV, Observatoire océanologique; F-06230 Villefranche/mer France
- CNRS, UMR 7093, LOV; Observatoire océanologique; F-06230 Villefranche/mer France
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Park S, Li Y. Integration of biological kinetics and computational fluid dynamics to model the growth ofNannochloropsis salinain an open channel raceway. Biotechnol Bioeng 2015; 112:923-33. [DOI: 10.1002/bit.25509] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2014] [Revised: 11/11/2014] [Accepted: 11/18/2014] [Indexed: 11/08/2022]
Affiliation(s)
- Stephen Park
- Department of Food, Agricultural and Biological Engineering; The Ohio State University/Ohio Agricultural Research and Development Center; 1680 Madison Ave. Wooster Ohio 44691-4096
| | - Yebo Li
- Department of Food, Agricultural and Biological Engineering; The Ohio State University/Ohio Agricultural Research and Development Center; 1680 Madison Ave. Wooster Ohio 44691-4096
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14
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Béchet Q, Shilton A, Guieysse B. Full-scale validation of a model of algal productivity. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2014; 48:13826-33. [PMID: 25369326 DOI: 10.1021/es503204e] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
While modeling algal productivity outdoors is crucial to assess the economic and environmental performance of full-scale cultivation, most of the models hitherto developed for this purpose have not been validated under fully relevant conditions, especially with regard to temperature variations. The objective of this study was to independently validate a model of algal biomass productivity accounting for both light and temperature and constructed using parameters experimentally derived using short-term indoor experiments. To do this, the accuracy of a model developed for Chlorella vulgaris was assessed against data collected from photobioreactors operated outdoor (New Zealand) over different seasons, years, and operating conditions (temperature-control/no temperature-control, batch, and fed-batch regimes). The model accurately predicted experimental productivities under all conditions tested, yielding an overall accuracy of ±8.4% over 148 days of cultivation. For the purpose of assessing the feasibility of full-scale algal cultivation, the use of the productivity model was therefore shown to markedly reduce uncertainty in cost of biofuel production while also eliminating uncertainties in water demand, a critical element of environmental impact assessments. Simulations at five climatic locations demonstrated that temperature-control in outdoor photobioreactors would require tremendous amounts of energy without considerable increase of algal biomass. Prior assessments neglecting the impact of temperature variations on algal productivity in photobioreactors may therefore be erroneous.
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Affiliation(s)
- Quentin Béchet
- School of Engineering and Advanced Technology, Massey University, Private Bag 11 222, Palmerston North 4442, New Zealand
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15
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Mairet F, Muñoz-Tamayo R, Bernard O. Adaptive control for optimizing microalgae production. ACTA ACUST UNITED AC 2013. [DOI: 10.3182/20131216-3-in-2044.00027] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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