Artificial intelligence-based approaches for modeling the effects of spirulina growth mediums on total phenolic compounds.

Journal: Saudi journal of biological sciences
Published Date: Sep 22, 2021

Abstract

Spirulina is a microalga and its phenolic compound is affected by growth mediums. In this study, Artificial intelligence (AI) based models, namely the Adaptive-Neuro Fuzzy Inference System (ANFIS) and Multilayer perceptron (MLP) models, and Step-Wise-Linear Regression (SWLR) were used to predict total phenolic compounds (TPC) of the spirulina algae. Spirulina productivity (P), extraction yield (EY), total flavonoids (TF), percent of flavonoid (%F) and percent of phenols (%P) are considered as input variables with the corresponding TPC as an output variable. From the result, TPC has a high positive correlation with the input variables with R = 0.99999. Also, the models showed that the ANFIS and SWLR gives superior result in the testing phase and increased its accuracy by 2% compared to MLP model in the prediction of TPC.

Authors

  • Wubshet Asnake Metekia
    Near East University, Faculty of Veterinary Medicine, Food Hygiene and Technology Department, Near East Boulevard, ZIP: 99138 Nicosia, Cyprus.
  • Abdullahi Garba Usman
    Near East University, Faculty of Pharmacy, Department of Analytical Chemistry, Nicosia, Cyprus.
  • Beyza Hatice Ulusoy
    Near East University, Faculty of Veterinary Medicine, Food Hygiene and Technology Department, Near East Boulevard, ZIP: 99138 Nicosia, Cyprus.
  • Sani Isah Abba
    Baze University, Civil Engineering, Abuja, Nigeria.
  • Kefyalew Chirkena Bali
    Near East University, Faculty of Veterinary Medicine, Food Hygiene and Technology Department, Near East Boulevard, ZIP: 99138 Nicosia, Cyprus.

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