Quantification of cell concentration in biofuel-important microalgae using hyperspectral reflectance and hyperspectral extinction coefficient. Issue 23 (2nd December 2019)
- Record Type:
- Journal Article
- Title:
- Quantification of cell concentration in biofuel-important microalgae using hyperspectral reflectance and hyperspectral extinction coefficient. Issue 23 (2nd December 2019)
- Main Title:
- Quantification of cell concentration in biofuel-important microalgae using hyperspectral reflectance and hyperspectral extinction coefficient
- Authors:
- Zhou, Zhaoming
Zhou, Xiaobing
Apple, Martha E.
Miao, Jiaqing
Wyss, Gary
Spangler, Lee - Abstract:
- ABSTRACT: Monitoring of microalgae cell concentration during their growing phase is imperative to ensure efficiency in biomass production and to study the cell division kinetics since it impacts the penetration depth of the active light radiation and thus determines the thickness of the active growing layer. Conventionally, the cell concentration (number of cells per unit volume) of microalgal solutions is estimated by microscopic enumeration method that is laborious and time consuming and can be performed only in the laboratory. In this study, we developed algorithms that relate cell concentration to hyperspectral reflectance and extinction coefficient (EC) for quick estimates of cell concentration. A multi-layer radiative transfer model was developed to correct the effect of the bottom of the microalgal solution container and table surface to obtain the hyperspectral reflectance and EC of only microalgal solution. Regression results show that the reflectance-based Band Ratio (BR) algorithm and the EC-based Spectral Shape (SS) index in the near-infrared (NIR) band gave the best results for all three microalgae species with the coefficient of determination R 2 > 0 .990, mean relative errors MRE < 5% and root mean squared error RMSE < 5%, and especially for A. cylindrica and N. gaditana, with R 2 > 0.999, MRE < 2% and RMSE < 1%, respectively. These relationships can be used to quickly estimate microalgal cell concentration from hyperspectral measurements that can be carriedABSTRACT: Monitoring of microalgae cell concentration during their growing phase is imperative to ensure efficiency in biomass production and to study the cell division kinetics since it impacts the penetration depth of the active light radiation and thus determines the thickness of the active growing layer. Conventionally, the cell concentration (number of cells per unit volume) of microalgal solutions is estimated by microscopic enumeration method that is laborious and time consuming and can be performed only in the laboratory. In this study, we developed algorithms that relate cell concentration to hyperspectral reflectance and extinction coefficient (EC) for quick estimates of cell concentration. A multi-layer radiative transfer model was developed to correct the effect of the bottom of the microalgal solution container and table surface to obtain the hyperspectral reflectance and EC of only microalgal solution. Regression results show that the reflectance-based Band Ratio (BR) algorithm and the EC-based Spectral Shape (SS) index in the near-infrared (NIR) band gave the best results for all three microalgae species with the coefficient of determination R 2 > 0 .990, mean relative errors MRE < 5% and root mean squared error RMSE < 5%, and especially for A. cylindrica and N. gaditana, with R 2 > 0.999, MRE < 2% and RMSE < 1%, respectively. These relationships can be used to quickly estimate microalgal cell concentration from hyperspectral measurements that can be carried out quickly and easily either in laboratory or in field. … (more)
- Is Part Of:
- International journal of remote sensing. Volume 40:Issue 23(2019)
- Journal:
- International journal of remote sensing
- Issue:
- Volume 40:Issue 23(2019)
- Issue Display:
- Volume 40, Issue 23 (2019)
- Year:
- 2019
- Volume:
- 40
- Issue:
- 23
- Issue Sort Value:
- 2019-0040-0023-0000
- Page Start:
- 8764
- Page End:
- 8792
- Publication Date:
- 2019-12-02
- Subjects:
- Remote sensing -- Periodicals
Télédétection -- Périodiques
621.3678 - Journal URLs:
- http://www.tandfonline.com/toc/tres20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/01431161.2019.1620378 ↗
- Languages:
- English
- ISSNs:
- 0143-1161
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.528000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 11252.xml