A turbidity sensor development based on NL-PI observers: Experimental application to the control of a Sinaloa’s River Spirulina maxima cultivation

Flores, Gerardo; Rodríguez-Mata, Abraham Efraim; Amábilis-Sosa, Leonel Ernesto; Gonzalez-Huitron, Victor; Hernández-González, Omar; López‐Pérez, Pablo A.

doi:10.1515/chem-2020-0119

Cited by 9 publications

(3 citation statements)

References 51 publications

(95 reference statements)

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“…Flores et al [17] use a sensor like that of Nguyen and Rittmann [16] which is employed for measuring the OD 560 of a suspension of mixotrophically cultivated Spirulina flowing inside a borosilicate tube, calibrated with biomass DWC. A flat-panel closed PBR was used for cultivation.…”

Section: Methods Based On Optical Density Measurementmentioning

confidence: 99%

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On-Line Monitoring of Biological Parameters in Microalgal Bioprocesses Using Optical Methods

et al. 2022

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Microalgae are promising sources of fuels and other chemicals. To operate microalgal cultivations efficiently, process control based on monitoring of process variables is needed. On-line sensing has important advantages over off-line and other analytical and sensing methods in minimizing the measurement delay. Consequently, on-line, in-situ sensors are preferred. In this respect, optical sensors occupy a central position since they are versatile and readily implemented in an on-line format. In biotechnological processes, measurements are performed in three phases (gaseous, liquid and solid (biomass)), and monitored process variables can be classified as physical, chemical and biological. On-line sensing technologies that rely on standard industrial sensors employed in chemical processes are already well-established for monitoring the physical and chemical environment of an algal cultivation. In contrast, on-line sensors for the process variables of the biological phase, whether biomass, intracellular or extracellular products, or the physiological state of living cells, are at an earlier developmental stage and are the focus of this review. On-line monitoring of biological process variables is much more difficult and sometimes impossible and must rely on indirect measurement and extensive data processing. In contrast to other recent reviews, this review concentrates on current methods and technologies for monitoring of biological parameters in microalgal cultivations that are suitable for the on-line and in-situ implementation. These parameters include cell concentration, chlorophyll content, irradiance, and lipid and pigment concentration and are measured using NMR, IR spectrophotometry, dielectric scattering, and multispectral methods. An important part of the review is the computer-aided monitoring of microalgal cultivations in the form of software sensors, the use of multi-parameter measurements in mathematical process models, fuzzy logic and artificial neural networks. In the future, software sensors will play an increasing role in the real-time estimation of biological variables because of their flexibility and extendibility.

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Section: Methods Based On Optical Density Measurementmentioning

confidence: 99%

“…As described in Section 2.3.1 in more detail, a robust nonlinear observer processing a turbidity signal was used to estimate the microalgal biomass and glucose concentration [17].…”

Section: Observersmentioning

confidence: 99%

On-Line Monitoring of Biological Parameters in Microalgal Bioprocesses Using Optical Methods

et al. 2022

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“…In addition to the determination of alga biomass, the measurement of Chl a content is also useful during the evaluation of the effectiveness and productivity of C. vulgaris in WWT systems [ 97 ]. The algal biomass and Chl a concentration can be measured using various techniques, such as turbidimetry [ 98 , 99 , 100 ], spectrophotometry [ 101 , 102 , 103 ], fluorescence-based methods [ 104 , 105 ], and laser-based analytical methods [ 106 ]. The qualitative and quantitative determination of phytoplankton biomass is generally performed by time-consuming methods, like direct cell counts under a microscope or the measurements of cellular mass or volume.…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Laboratory-Based and Spectroscopic Methods Used to Estimate the Algal Density of Chlorella vulgaris

Fekete,

Sebők,

Klátyik

et al. 2024

Microorganisms

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Chlorella vulgaris is of great importance in numerous exploratory or industrial applications (e.g., medicals, food, and feed additives). Rapid quantification of algal biomass is crucial in photobioreactors for the optimization of nutrient management and the estimation of production. The main goal of this study is to provide a simple, rapid, and not-resource-intensive estimation method for determining the algal density of C. vulgaris according to the measured parameters using UV–Vis spectrophotometry. Comparative assessment measurements were conducted with seven different methods (e.g., filtration, evaporation, chlorophyll a extraction, and detection of optical density and fluorescence) to determine algal biomass. By analyzing the entire spectra of diluted algae samples, optimal wavelengths were determined through a stepwise series of linear regression analyses by a novel correlation scanning method, facilitating accurate parameter estimation. Nonlinear formulas for spectrometry-based estimation processes were derived for each parameter. As a result, a general formula for biomass concentration estimation was developed, with recommendations for suitable measuring devices based on algae concentration levels. New values for magnesium content and the average single-cell weight of C. vulgaris were established, in addition to the development of a rapid, semiautomated cell counting method, improving efficiency and accuracy in algae quantification for cultivation and biotechnology applications.

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Software sensors in the monitoring of microalgae cultivations

Porras Reyes,

Havlik,

Beutel

2024

Rev Environ Sci Biotechnol

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Microalgae 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.

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A turbidity sensor development based on NL-PI observers: Experimental application to the control of a Sinaloa’s River Spirulina maxima cultivation

Cited by 9 publications

References 51 publications

On-Line Monitoring of Biological Parameters in Microalgal Bioprocesses Using Optical Methods

On-Line Monitoring of Biological Parameters in Microalgal Bioprocesses Using Optical Methods

Comparative Analysis of Laboratory-Based and Spectroscopic Methods Used to Estimate the Algal Density of Chlorella vulgaris

Software sensors in the monitoring of microalgae cultivations

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