Identification, quantification, and growth profiling of eight different microalgae species using image analysis

S. Sunoj, Ademola Hammed, C. Igathinathane, Sulaymon Eshkabilov, Halis Simsek

Research output: Contribution to journalArticlepeer-review


Algal blooms and associated oxygen depletion have devastating consequences for freshwater ecosystems. Identifying and quantifying microalgae species require highly expensive equipment that is unaffordable to many research units, mostly those in developing countries. The development of a low-cost technique to quantify the microalgae species could reduce the research expenses and boost microalgae research in developing nations. Therefore, a cost-effective and straightforward microalgae quantification method using an image analysis methodology was developed in this study. Eight different microalgae strains include Oocystis minuta, Synechococcus sp., Acrochaetium sp., Rhodosorus marinus, Chaetoceros gracilis, Isochrysis galbana, Phormidium inundatum, and Phormidium fragile were cultured, and their images were captured during the growth periods (0–28 days). A user-coded plugin known as MAIJA – Microalgae ImageJ Analyzer was developed and used for analyzing the images. The principle involved in microalgae quantification relied on the color intensity increase along with the growth of algae. Seven different color vegetation indices were employed to determine a suitable index for algae quantification. Results indicated that the algae species can be differentiated between homogenously and non-homogeneously dissolving species using the developed approach. Linear models were developed to estimate dry cell mass from culture volume (0.86 ≥ R2 ≤ 0.99) as well as from different vegetation indices (R2 up to 0.99). Among five color kinetic models tested, results showed that the first-order kinetic model with vegetative index was the most suitable indicator to obtain the trend of algae growth (RMSE = 0.2–0.4). Further, the vegetative index was also found to be suitable for differentiating similar colored algae species (Oocystis minuta vs. Synechococcus sp., and Phormidium fragile vs. Rhodosorus marinus). The developed method has the potential to improve the quantification of mixed microalgae culture compared to the traditional solid dried mass method.

Original languageEnglish (US)
Article number102487
JournalAlgal Research
StatePublished - Dec 2021
Externally publishedYes


  • Algae
  • Biomass
  • Bioproducts
  • Growth kinetics
  • Image processing
  • ImageJ
  • Renewable energy

ASJC Scopus subject areas

  • Agronomy and Crop Science


Dive into the research topics of 'Identification, quantification, and growth profiling of eight different microalgae species using image analysis'. Together they form a unique fingerprint.

Cite this