On-line optimization of biotechnological processes: I. Application to open algal pond
Abstract
A new on-line optimization and control procedure applicable to biotechnological systems for which a precise mathematical model is unavailable has been developed and tested. The proposed approach is based on an online search for optimum operating conditions by an automatic system using a modified simplex algorithm to which several features have been added to permit real time operation. The simplex algorithm is the upper level of a hierarchical software package in which the other levels are cost evaluation, control, data acquisition, and signal processing. The optimization method was tested in a laboratory minipond for the cultivation of Spirulina platensis. The controlled parameters were light intensity, optical density, pH, and temperature. The proposed optimization method can be applied to other biological processes provided that the pertinent variables can be measured and controlled and the cost function can be defined mathematically.
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Open ponds for Spirulina cultivation have low biomass productivity due to frequent evaporation of water and pollution.
“Along with these advantages, however, there are also a number of disadvantages such as low biomass productivity [8,9] due to the frequent evaporation of water from the reservoir [10] and pollution.”
From Application of Arthrospira platensis for Medicinal Purposes and the Food Industry: A Review of the Literature (2023) · cites this paper as [10]
Cites
A Simplex Method for Function Minimization
Nelder, J. A., & Mead, R. (1965) · The Computer Journal · doi:10.1093/comjnl/7.4.308 · Cited by 28,905 · see citing works
Linear Optimal Control Systems
Kwakernaak, H., Sivan, R., & Tyreus, B. N. D. (1974) · Journal of Dynamic Systems Measurement and Control · doi:10.1115/1.3426828 · Cited by 5,010 · see citing works
Sequential Application of Simplex Designs in Optimisation and Evolutionary Operation
Spendley, W., Hext, G. R., & Himsworth, F. R. (1962) · Technometrics · doi:10.1080/00401706.1962.10490033 · Cited by 1,310 · see citing works
Hadley, G. F., & Kemp, M. C. (1971) · Elsevier eBooks · doi:10.1016/b978-0-7204-3601-3.50008-8 · Cited by 497 · see citing works
Handbook of Microalgal Mass Culture (1986)
(2017) · CRC Press eBooks · doi:10.1201/9780203712405 · Cited by 420 · see citing works
Simplex optimization of analytical chemical methods
Morgan, S. L., & Deming, S. N. (1974) · Analytical Chemistry · doi:10.1021/ac60345a035 · Cited by 335 · see citing works
Božić, S. (1979) · Cited by 243 · see citing works
Perdikaris, G. A. (1991) · Springer eBooks · doi:10.1007/978-94-015-7929-2_7 · Cited by 241 · see citing works
Adaptive identification and control algorithms for nonlinear bacterial growth systems
Dochain, D., & Bastin, G. L. (1984) · Automatica · doi:10.1016/0005-1098(84)90012-8 · Cited by 159 · see citing works
Computer control of bakers' yeast production
Wang, H. Y., Cooney, C. L., & Wang, D. I. C. (1979) · Biotechnology and Bioengineering · doi:10.1002/bit.260210605 · Cited by 157 · see citing works
Simplex techniques for nonlinear optimization
Ryan, P. B., Barr, R. L., & Todd, H. D. (1980) · Analytical Chemistry · doi:10.1021/ac50059a019 · Cited by 110 · see citing works
Techniques in bioproductivity and photosynthesis
Boardman, N. K. (1983) · Trends in Biochemical Sciences · doi:10.1016/0968-0004(83)90172-x · Cited by 78 · see citing works
Reflections on the modified simplex—II1
Betteridge, D., Wade, A. P., & Howard, A. G. (1985) · Talanta · doi:10.1016/0039-9140(85)80175-2 · Cited by 75 · see citing works
Optimal control of bacterial growth
D'Ans, G., Gottlieb, D. J., & Kokotović, P. V. (1972) · Automatica · doi:10.1016/0005-1098(72)90083-0 · Cited by 71 · see citing works
Mou, D., & Cooney, C. L. (1983) · Biotechnology and Bioengineering · doi:10.1002/bit.260250119 · Cited by 50 · see citing works
Optimal substrate profile for antibiotic fermentations
Guthke, R., & Knorre, W. A. (1981) · Biotechnology and Bioengineering · doi:10.1002/bit.260231211 · Cited by 45 · see citing works
Optimal quality control of bakers' yeast fed‐batch culture using population dynamics
Dairaku, K., Izumoto, E., Morikawa, H., Shioya, S., & Takamatsu, T. (1982) · Biotechnology and Bioengineering · doi:10.1002/bit.260241205 · Cited by 43 · see citing works
Automatic on‐line growth estimation method for outdoor algal biomass production
Guterman, H., Ben‐Yaakov, S., & Vonshak, A. (1989) · Biotechnology and Bioengineering · doi:10.1002/bit.260340202 · Cited by 38 · see citing works
Self-citationOptimization of operating temperature for continuous glucose isomerase reactor system
Park, S. H., Lee, S. B., & Ryu, D. D. Y. (1981) · Biotechnology and Bioengineering · doi:10.1002/bit.260230606 · Cited by 26 · see citing works
Optimizing alcohol production from whey using computer technology
Zertuche, L., & Zall, R. R. (1985) · Biotechnology and Bioengineering · doi:10.1002/bit.260270423 · Cited by 25 · see citing works
The symmetry-controlled simplex optimization procedure
van der Wiel, P. F. A., Maassen, R., & Kateman, G. (1983) · Analytica Chimica Acta · doi:10.1016/s0003-2670(00)85490-2 · Cited by 23 · see citing works
Modelling, Identification and Control of the Alcohol Fermentation in a Cascade Reactor
Sevely, Y., Pourciel, J., Rauzy, G., & Bovee, J. P. (1981) · IFAC Proceedings Volumes · doi:10.1016/s1474-6670(17)63891-6 · Cited by 23 · see citing works
Comparison of Optimization Techniques for Application to Food Product and Process Development
Nakai, S. (1982) · Journal of Food Science · doi:10.1111/j.1365-2621.1982.tb11046.x · Cited by 21 · see citing works
An automatic method for on‐line estimation of the photosynthetic rate in open algal ponds
Ben‐Yaakov, S., Guterman, H., Vonshak, A., & RICHMOND, A. E. (1985) · Biotechnology and Bioengineering · doi:10.1002/bit.260270808 · Cited by 19 · see citing works
Self-citationCordenunsi, B. R., Silva, R. S. F. D., Srivastava, K. C., Sanches, S. F., & Perre, M. A. (1985) · Journal of Biotechnology · doi:10.1016/0168-1656(85)90051-3 · Cited by 19 · see citing works
Automated fermentation equipment II. Computer–fermentor system
Nyeste, L., Szigeti, L., Veres, A., Pungor, E., Kurucz, I., & Holló, J. (1981) · Biotechnology and Bioengineering · doi:10.1002/bit.260230214 · Cited by 17 · see citing works
Marty, J. (1985) · Applied Microbiology and Biotechnology · doi:10.1007/bf00250025 · Cited by 16 · see citing works
Application of a statistical procedure for the control of yeast production
Kishimoto, M., Sawano, T., Yoshida, T., & Taguchi, H. (1984) · Biotechnology and Bioengineering · doi:10.1002/bit.260260809 · Cited by 11 · see citing works
Exchange rates of O2 and CO2 between an algal culture and atmosphere
Guterman, H., & Ben‐Yaakov, S. (1987) · Water Research · doi:10.1016/0043-1354(87)90095-9 · Cited by 11 · see citing works
Self-citationUtilization of the “complex method” to optimize a fermentation process
Saguy, I. S. (1982) · Biotechnology and Bioengineering · doi:10.1002/bit.260240706 · Cited by 9 · see citing works
JERMFERM : A fermentation process development game
MATELES, R. I. (1978) · Biotechnology and Bioengineering · doi:10.1002/bit.260201214 · Cited by 8 · see citing works
A simple algorithm for on‐line prediction of BOD5 by a microprocessor‐based system
Raviv, R., & Ben‐Yaakov, S. (1984) · Biotechnology and Bioengineering · doi:10.1002/bit.260261014 · Cited by 6 · see citing works
Self-citationStrategies for Optimizing Microbial Growth and Product Formation
Cooney, C. L. (1983) · ACS symposium series · doi:10.1021/bk-1983-0207.ch008 · Cited by 6 · see citing works
Iterative Methods for Nonlinear Problems
Engl, H. W., Hanke, M., & Neubauer, A. (2000) · Springer eBooks · doi:10.1007/978-94-009-1740-8_11 · Cited by 5 · see citing works
On-line Monitoring and Biochemical Reaction Control of Processes
Takamatsu, T., Shioya, S., Yokoyama, K., Kurome, Y., & Morisaki, K. (1981) · IFAC Proceedings Volumes · doi:10.1016/s1474-6670(17)64022-9 · Cited by 4 · see citing works
Ben‐Yaakov, S., & Guterman, H. (1985) · Microprocessing and Microprogramming · doi:10.1016/0165-6074(85)90022-5 · Cited by 3 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Carbon Dioxide Mitigation by Microalgal Photosynthesis
Jeong, M.-J. G. L. (2003) · Bulletin of the Korean Chemical Society · doi:10.5012/bkcs.2003.24.12.1763 · Cited by 112 · see citing works
Gentscheva, G., Nikolova, K., Panayotova, V., Peycheva, K., Makedonski, L., Slavov, P., Radusheva, P., Petrova, P., & Yotkovska, I. (2023) · Life · doi:10.3390/life13030845 · Cited by 106 · see citing works
“Along with these advantages, however, there are also a number of disadvantages such as low biomass productivity [8,9] due to the frequent evaporation of water from the reservoir [10] and pollution.”
BackgroundTechno-economic case study: Bio-fixation of industrial emissions at an Indian oil and gas plant
Choudhary, P., & Srivastava, R. K. (2020) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2020.121820 · Cited by 15 · see citing works
Beste, H., Fackeldey, M., Willems, M., Stockmann, L., & Weuster‐Botz, D. (1997) · Chemical Engineering & Technology · doi:10.1002/ceat.270200608 · Cited by 9 · see citing works
Senko, O. V., & Efremenko, E. N. (2017) · Catalysis in Industry · doi:10.1134/s2070050417040079 · Cited by 7 · see citing works
Carbon Sequestration Through Solar Bioreactors: Industrial Strategies
Sudhakar, K., & Soni, R. A. (2017) · Green energy and technology · doi:10.1007/978-981-10-3352-0_10 · Cited by 5 · see citing works
A Bilevel Programming Approach to Optimize C-phycocyanin Bio-production under Uncertainty
del Rio‐Chanona, E. A., & Zhang, D. (2018) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2018.09.301 · Cited by 3 · see citing works
“…and design with the embedding of model uncertainty (Pollock et al. 2013; Biwer et al. 2005; Rosengart et al. 2017), and different methods such as ensemble modeling has been adopted to optimize the performance of traditional fermentation processes (Guterman & Ben-Yaakov 1990; Liu & Gunawan 2017).”
MethodLustigman, B. K., & Lee, L. H. (2003) · Encyclopedia of Environmental Microbiology · doi:10.1002/0471263397.env046
Tebbani, S., Lopes, F., Filali, R., Dumur, D., & Pareau, D. (2014) · doi:10.1002/9781118984475.biblio
- Authors
- Guterman, H., & Ben‐Yaakov, S.
- Affiliations
- Ben-Gurion University of the Negev (IL)
- Venue
- Biotechnology and Bioengineering
- Publisher
- Wiley
- Published
- 1990-02-20
- Volume
- 35
- Issue
- 4
- Pages
- 417-426
- ISSN
- 0006-3592 (ISSN-L)
- 1097-0290
- OpenAlex
- W2166899855
- Cited by
- 9
- References
- 36
- Citations by year
- 2023: 1 · 2020: 1 · 2018: 1 · 2017: 2 · 2014: 1
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biotechnology and Bioengineering (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Advanced Control Systems Optimization
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Algal biology and biofuel production
- Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
- Keywords
- online optimization, bioprocess control, model-free optimization, Spirulina platensis, microalgae cultivation, light intensity control, pH control, temperature control, optical density, real-time optimization
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