Qualitative and quantitative evaluation of microalgal biomass using portable attenuated total reflectance-Fourier transform infrared spectroscopy and machine learning analytics

Mais Sweiss, Sulaf Assi, Lina Barhoumi, Dhiya Al-Jumeily, Megan Watson, Megan Wilson, Tom Arnot, Rod Scott

Research output: Contribution to journalArticlepeer-review

1 Citation (SciVal)


BACKGROUND: Using microalgae for wastewater treatment offers an environmentally friendly method to produce microalgal biomass that can be used for many applications. However, the biochemical characteristics of microalgal biomass vary from species to species, from strain to strain, and between different growth stages within the same species/strain. This study utilized portable attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy to determine the composition of freeze-dried microalgal biomass corresponding to eight different locally isolated microalgae and a reference strain that were grown in wastewater and then harvested at the log and stationary phases, respectively. 

RESULTS: The results showed that the portable ATR-FTIR spectroscopy offered a rapid, non-destructive, and accurate technique for monitoring changes in the biochemical composition of algal biomass at stationary and log phases, as well as quantifying their main constituents. For qualitative analysis of species, two machine learning analytics (MLAs; correlation in wavenumber space and principal component analysis) were able to differentiate between microalgae isolates in both their stationary and log phases. For quantification, univariate or multivariate regression offered accuracy in quantifying key microalgal constituents related to proteins, lipids, and carbohydrates. In this sense, multivariate methods showed more accuracy for quantifying carbohydrates, yet proteins and lipids were more accurately quantified with univariate regression. Based on quantification, the highest relative content of carbohydrates in the log phase was for Jordan-23 (Jo-23; Desmodesmus sp.), whereas the highest content in the stationary phase was that for Jordan-29 (Jo-29; Desmodesmus sp). Regarding the relative lipid content in the log phase, Jo-23 had the highest lipid content, while the highest content in the stationary phase was for Jo-29. 

CONCLUSION: ATR-FTIR spectroscopy offered a rapid and sustainable method for monitoring the microalgal biomass produced during wastewater treatment processes.

Original languageEnglish
Pages (from-to)92-108
Number of pages17
JournalJournal of Chemical Technology and Biotechnology
Issue number1
Early online date7 Sept 2023
Publication statusPublished - 31 Jan 2024

Bibliographical note

Funding Information:
The authors would like to thank the University of Bath (UK) for offering the equipment, consumables, and algal growing facility, as well as the Al‐Balqa Applied University (Jordan) and the Ministry of Higher Education and Scientific Research (Jordan) for providing the PhD studentship. ESystem Engineering Society (eSES) is acknowledged for support with machine learning analytics. The authors would also like to pay tribute to the late Professor Rod Scott, who passed away before publishing this work, for his major contributions in developing and supporting the idea of this research.


  • attenuated total reflectance Fourier transform infrared
  • biomass
  • microalgae
  • principal component analysis
  • spectroscopy
  • wastewater

ASJC Scopus subject areas

  • Biotechnology
  • General Chemical Engineering
  • Renewable Energy, Sustainability and the Environment
  • Fuel Technology
  • Waste Management and Disposal
  • Pollution
  • Organic Chemistry
  • Inorganic Chemistry


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