Your browser doesn't support javascript.
loading
Kinetic modeling of growth and lipid body induction in Chlorella pyrenoidosa under heterotrophic conditions.
Sachdeva, Neha; Kumar, G Dinesh; Gupta, Ravi Prakash; Mathur, Anshu Shankar; Manikandan, B; Basu, Biswajit; Tuli, Deepak Kumar.
Afiliação
  • Sachdeva N; DBT-IOC Centre for Advanced Bioenergy Research, Research & Development Centre, Indian Oil Corporation Limited, Sector-13, Faridabad 121007, India.
  • Kumar GD; Department of Chemical Engineering, University of Petroleum & Energy Studies, Dehradun 248007, India.
  • Gupta RP; Indian Oil Corporation Limited, Sector-13, Faridabad 121007, India. Electronic address: guptarp1@indianoil.in.
  • Mathur AS; Indian Oil Corporation Limited, Sector-13, Faridabad 121007, India.
  • Manikandan B; Department of Chemical Engineering, University of Petroleum & Energy Studies, Dehradun 248007, India.
  • Basu B; DBT-IOC Centre for Advanced Bioenergy Research, Research & Development Centre, Indian Oil Corporation Limited, Sector-13, Faridabad 121007, India.
  • Tuli DK; DBT-IOC Centre for Advanced Bioenergy Research, Research & Development Centre, Indian Oil Corporation Limited, Sector-13, Faridabad 121007, India.
Bioresour Technol ; 218: 934-43, 2016 Oct.
Article em En | MEDLINE | ID: mdl-27450124
ABSTRACT
The aim of the present work was to develop a mathematical model to describe the biomass and (total) lipid productivity of Chlorella pyrenoidosa NCIM 2738 under heterotrophic conditions. Biomass growth rate was predicted by Droop's cell quota model, while changes observed in cell quota (utilization) under carbon excess conditions were used for the modeling and predicting the lipid accumulation rate. The model was simulated under non-limiting (excess) carbon and limiting nitrate concentration and validated with experimental data for the culture grown in batch (flask) mode under different nitrate concentrations. The present model incorporated two modes (growth and stressed) for the prediction of endogenous lipid synthesis/induction and aimed to predict the effect and response of the microalgae under nutrient starvation (stressed) conditions. MATLAB and Genetic Algorithm were employed for the prediction and validation of the model parameters.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Chlorella / Biomassa / Modelos Teóricos Tipo de estudo: Prognostic_studies Idioma: En Revista: Bioresour Technol Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Chlorella / Biomassa / Modelos Teóricos Tipo de estudo: Prognostic_studies Idioma: En Revista: Bioresour Technol Ano de publicação: 2016 Tipo de documento: Article