Method and system for characterization of microalgal lipid content

Patent metadata

Field	Value
Publication number	US-10416093-B2
Application number	US-201515121647-A
Country	US
Kind code	B2
Filing date	May 25, 2015
Priority date	May 25, 2014
Publication date	Sep 17, 2019
Grant date	Sep 17, 2019

Abstract

Method and system (100) for characterizing lipid content in microalgae are disclosed. An input signal is transmitted to a resonator cavity (102) containing a sample microalgal suspension and a frequency response curve is obtained. Subsequently, a set of sample parameters is determined based on a Gaussian distribution modelling of the frequency response curve. An amount of lipid content in the sample microalgal suspension is determined based on correlation between the sample parameters and a set of reference parameters, wherein the reference parameters correspond to specific amounts of lipid content.

First claim

What is claimed is:

1. A method for characterizing lipid content in microalgae, said method comprising:
providing a sample microalgal suspension in a resonator cavity;
transmitting an input signal to said resonator cavity, wherein said input signal sweeps over a frequency range;
determining a frequency response curve corresponding to said frequency range based on an output signal reflected from said resonator cavity;
determining a set of sample parameters based on a Gaussian distribution modelling of said frequency response curve; and
determining an amount of lipid content in said sample microalgal suspension based on correlation between said sample parameters and a set of reference parameters, wherein said reference parameters correspond to specific amounts of lipid content.

2. The method according to claim 1 , wherein said frequency response curve corresponds to variation of a scattering parameter.

3. The method according to claim 1 , wherein said sample parameters and said reference parameters correspond to magnitude, center frequency, bandwidth, and offset obtained from said output signal reflected from said resonator cavity under test and calibration conditions respectively.

4. The method according to claim 1 , wherein said reference parameters are determined from a set of reference microalgal suspensions with predetermined microalgal strain, cultivation medium, and amount of lipid content.

5. The method according to claim 1 further comprising generating a reference library of said reference parameters.

6. The method according to claim 5 , wherein said reference library comprises tuples of said reference parameters and wherein each tuple corresponds to a specific amount of lipid content.

7. The method according to claim 6 , wherein correlation between said sample parameters and said reference parameters is performed on a tuple basis, and said amount of lipid content is determined based on best match between tuples corresponding to said sample parameters and said reference parameters.

8. The method according to claim 5 , wherein said reference library comprises correlations between individual reference parameters and amount of lipid content.

9. The method according to claim 8 , wherein correlation between said sample parameters and said reference parameters is performed on an individual basis, and said amount of lipid content is determined based on triangulation of a set of amounts of lipid content derived from individual reference parameters.

10. The method according to claim 5 , wherein said reference library is indexed based on at least one or more of microalgal strains, cultivation media, and cell concentrations.

11. A system for characterizing lipid content in microalgae, said system comprising:
a resonator cavity, said resonator cavity configured for holding a sample microalgal suspension;
a vector network analyzer, said vector network analyzer operationally coupled to said resonator cavity for transmitting an input signal thereto, wherein said input signal sweeps over a frequency range, and further configured for determining, using a processing module, a frequency response curve corresponding to said frequency range based on an output signal reflected from said resonator cavity; and
a computational module accessible by the processing module, said computational module configured for determining a set of sample parameters based on a Gaussian distribution modelling of said frequency response curve, and determining an amount of lipid content in said sample microalgal suspension based on correlation between said sample parameters and a set of reference parameters, wherein said reference parameters correspond to specific amounts of lipid content.

12. The system according to claim 11 , wherein said frequency response curve corresponds to variation of a scattering parameter.

13. The system according to claim 11 , wherein said sample parameters and said reference parameters correspond to magnitude, center frequency, bandwidth, and offset obtained from said output signal under test and calibration conditions respectively.

14. The system according to claim 11 , wherein said reference parameters are determined from a set of reference microalgal suspensions with predetermined microalgal strain, cultivation medium, and amount of lipid content.

15. The system according to claim 11 further comprising a storage module accessible by the processing module and configured for storing a reference library of said reference parameters.

16. The system according to claim 15 , wherein said reference library comprises tuples of said reference parameters and wherein each tuple corresponds to a specific amount of lipid content.

17. The system according to claim 16 , wherein said computational module performs correlation between said sample parameters and said reference parameters on a tuple basis, and determines said amount of lipid content based on best match between tuples corresponding to said sample parameters and said reference parameters.

18. The system according to claim 15 , wherein said reference library comprises correlations between individual reference parameters and amount of lipid content.

19. The system according to claim 18 , wherein said computational module performs correlation between said sample parameters and said reference parameters on an individual basis, and determines said amount of lipid content based on triangulation of a set of amounts of lipid content derived from individual reference parameters.

20. The system according to claim 15 , wherein said reference library is indexed based on at least one or more of microalgal strains, cultivation media, and cell concentrations.

Assignees

• Univ United Arab Emirates

Inventors

• Al Ahmad Mahmoud F Y

Classifications

• C12N1/12

  Unicellular algae; Culture media therefor (as new plants A01H13/00) · CPC title

• G01N29/00

  Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object (G01N3/00 - G01N27/00 take precedence) · CPC title

• G01N29/4418

  with a model, e.g. best-fit, regression analysis · CPC title

• G01N29/36

  Detecting the response signal {, e.g. electronic circuits specially adapted therefor} · CPC title

• C12N1/26

  Processes using, or culture media containing, hydrocarbons (refining of hydrocarbon oils by using microorganisms C10G32/00) · CPC title