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Research article - Peer-reviewed, 2023

Application of regression and artificial neural network analysis of Red-Green-Blue image components in prediction of chlorophyll content in microalgae

Tang, Doris Ying Ying; Chew, Kit Wayne; Ting, Huong-Yong; Sia, Yuk-Heng; Gentili, Francesco G.; Park, Young-Kwon; Banat, Fawzi; Culaba, Alvin B.; Ma, Zengling; Show, Pau Loke


This study presented a novel methodology to predict microalgae chlorophyll content from colour models using linear regression and artificial neural network. The analysis was performed using SPSS software. Type of extractant solvents and image indexes were used as the input data for the artificial neural network calculation. The findings revealed that the regression model was highly significant, with high R2 of 0.58 and RSME of 3.16, making it a useful tool for predicting the chlorophyll concentration. Simultaneously, artificial neural network model with R2 of 0.66 and low RMSE of 2.36 proved to be more accurate than regression model. The model which fitted to the experimental data indicated that acetone was a suitable extraction solvent. In comparison to the cyan-magenta-yellow-black model in image analysis, the red-greenblue model offered a better correlation. In short, the estimation of chlorophyll concentration using prediction models are rapid, more efficient, and less expensive.


Chlorophyll; Microalgae; Prediction; Multilayer perceptron; Regression

Published in

Bioresource Technology
2023, volume: 370, article number: 128503

Authors' information

Tang, Doris Ying Ying
University of Nottingham Malaysia
Tang, Doris Ying Ying
Wenzhou University
Chew, Kit Wayne
Nanyang Technological University
Ting, Huong-Yong
Swinburne University of Technology Sarawak
Sia, Yuk-Heng
University of Technology Sarawak
Swedish University of Agricultural Sciences, Department of Forest Biomaterials and Technology
Park, Young-Kwon
University of Seoul
Banat, Fawzi
Khalifa University of Science and Technology
Culaba, Alvin B.
De La Salle University
Ma, Zengling
Wenzhou University
Show, Pau Loke
Wenzhou University
Show, Pau Loke
University of Nottingham Malaysia
Show, Pau Loke
Saveetha Institute of Medical and Technical Science

UKÄ Subject classification

Bioinformatics (Computational Biology)
Other Industrial Biotechnology

Publication Identifiers


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