Optimization of diosgenin extraction from Dioscorea deltoidea tubers using response surface methodology and artificial neural network modelling.

Journal: PloS one
PMID: 34288904

Abstract

INTRODUCTION: Dioscorea deltoidea var. deltoidea (Dioscoreaceae) is a valuable endangered plant of great medicinal and economic importance due to the presence of the bioactive compound diosgenin. In the present study, response surface methodology (RSM) and artificial neural network (ANN) modelling have been implemented to evaluate the diosgenin content from D. deltoidea. In addition, different extraction parameters have been also optimized and developed.

Authors

  • Romaan Nazir
    Department of Biotechnology, Lovely Faculty of Technology and Sciences, Lovely Professional University, Phagwara, Punjab, India.
  • Devendra Kumar Pandey
    Department of Biotechnology, Lovely Faculty of Technology and Sciences, Lovely Professional University, Phagwara, Punjab, India.
  • Babita Pandey
    School of Computer Applications, Lovely Professional University, Chaheru, Punjab, India.
  • Vijay Kumar
    Computer Science and Engineering Department, National Institute of Technology, Hamirpur, Himachal Pradesh, India.
  • Padmanabh Dwivedi
    Department of Plant Physiology, Banaras Hindu University, Varanasi, Uttar Pradesh, India.
  • Aditya Khampariya
    School of Computer Science and Engineering, Lovely Professional University, Phagwara, Punjab, India.
  • Abhijit Dey
    Department of Life Sciences, Presidency University, Kolkata, India.
  • Tabarak Malik
    Department of Biochemistry, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.

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