Spectroradiometric detection of competitor diatoms and the grazer Poteriochromonas in algal cultures

Reichardt, Thomas A.; Maes, Danae; Jensen, Travis J; Dempster, Thomas A.; McGowen, John; Poorey, Kunal; Curtis, Deanna Joy; Lane, Todd W.; Timlin, Jerilyn A.

doi:10.1016/j.algal.2020.102020

Cited by 11 publications

(10 citation statements)

References 56 publications

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“…Other estimated variables are the pigment and lipid content, and for their estimation, physical measurements of cell count, nitrate and glucose concentration are employed, complemented by process signals obtained by various methods as measurement of turbidity, IR spectrum and fluorescence, RGB imaging and transmission spectra, NMR spectroscopy, fluorescence, hyperspectral or RGB imaging, and dielectrophoresis. [22] (2) (a) [23,24] (2) (b) [25] Color analysis (RGB) Biomass On Off…”

Section: Measurement Methods Used For On-line Monitoring Of Biological Variablesmentioning

confidence: 99%

“…Reflectivity spectral data were collected on-line by Reichardt et al [22] in four open raceway ponds cultivating N. oceanica and C. vulgaris using multi-channel spectrometers, equipped with downward-looking fibers angled at 30 • from normal, one at each pond, for monitoring the reflected light, and one upward-looking fiber equipped with a diffusing optics (180 • ) for monitoring the downwelling light. Reflectance spectra were analyzed by a model described in [66].…”

Section: Culture Health Monitoring Contaminationmentioning

confidence: 99%

“…Most microalgal biomass is produced in open photobioreactors where contamination by various pathogens, e.g., grazers, poses a grave danger. Here, an early detection of contaminating organisms is very important and the in-situ microscopy with automatic image evaluation, reflectance, multispectral absorbance, color measurement or FTIR spectroscopy could be employed [22,33,67,90]. Microfluidics is another technology finding its place in microalgal research and industrial applications in monitoring and optimizing both upstream and downstream processes, performing functions in cell sorting, screening and characterization, cultivation and lipid and pigment identification using measurement methods as intrinsic fluorescence and fluorescence after staining, Raman spectroscopy, dielectrophoresis or magnetophoresis [91].…”

Section: Perspectives and Outlook For On-line Sensing In Microalgal Cultivationsmentioning

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: Measurement Methods Used For On-line Monitoring Of Biological Variablesmentioning

confidence: 99%

Section: Culture Health Monitoring Contaminationmentioning

confidence: 99%

Section: Perspectives and Outlook For On-line Sensing In Microalgal Cultivationsmentioning

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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“…Several methods are commonly used to identify and quantify microorganisms (such as microscopy, fluorescence and PCR/qPCR). In recent years, alternative methods have been proposed for rapid in vivo assessment of microalgae communities (and their competitors/predators), such as spectroradiometric monitoring (Reichardt et al, 2020). These emerging techniques should allow biofilm structure and characteristics to be more carefully monitored and controlled, allowing wastewater treatment processes to be further optimised.…”

Section: Biofilm Community Structuresmentioning

confidence: 99%

Innovative Wastewater Treatment Technologies — The INNOQUA Project

2021

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“…used with artificial neural network (ANN) to differentiate microalgal species in suspension (Franco et al 2019)), reflectance (e.g. for the detection of diatoms in open ponds, (Reichardt et al 2020)), chlorophyll fluorescence (e.g. NPQ measured by PAM to detect grazing (Deore et al 2020)), or Fourier Transform Infrared (FTIR) spectroscopy (e.g.…”

Section: Introductionmentioning

confidence: 99%

Image-Based Analysis and Quantification of Biofouling in Cultures of the Red Alga Asparagopsis taxiformis

Dishon

Resetarits

Tsai

et al. 2022

Preprint

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Methane is an extremely potent yet short-lived greenhouse gas and is thus recognized as a promising target for rapid climate change mitigation. About 35% of anthropogenic methane emissions are associated with livestock production, and most of these emissions are the outcome of enteric fermentation in ruminant animals. The red seaweed Asparagopsis is currently considered the most efficient feed additive to suppress methane emissions from enteric fermentation but is not currently available on commercial scale. The ongoing effort to successfully commercialize Asparagopsis requires the development of pest control frameworks which rely on the quantitative assessment of biological contamination in cultures. Here we present a low-cost readily available approach for quantifying biofouling in Asparagopsis taxiformis cultures based on microscopic examination and automated image analysis. The proposed methodology is demonstrated to estimate contamination associated with Asparagopsis biomass with error rates lower than 2% over a wide range of contamination levels and contaminating organisms, while significantly cutting down image processing time and allowing for frequent contamination quantification.

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Spectroradiometric detection of competitor diatoms and the grazer Poteriochromonas in algal cultures

Cited by 11 publications

References 56 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

Innovative Wastewater Treatment Technologies — The INNOQUA Project

Image-Based Analysis and Quantification of Biofouling in Cultures of the Red Alga Asparagopsis taxiformis

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