Literature DB >> 25304731

The use of Design of Experiments and Response Surface Methodology to optimize biomass and lipid production by the oleaginous marine green alga, Nannochloropsis gaditana in response to light intensity, inoculum size and CO2.

Patrick C Hallenbeck1, Melanie Grogger2, Megan Mraz2, Donald Veverka2.   

Abstract

Biodiesel produced from microalgal lipids is being considered as a potential source of renewable energy. However, a number of hurdles will have to be overcome if such a process is to become practical. One important factor is the volumetric production of biomass and lipid that can be achieved. The marine alga Nannochloropsis gaditana is under study since it is known to be highly oleaginous and has a number of other attractive properties. Factors that might be important in biomass and lipid production by this alga are light intensity, inoculum size and CO2. Here we have carried out for the first time a RSM-DOE study of the influence of these important culture variables and define conditions that maximize biomass production, lipid content (BODIPY® fluorescence) and total lipid production. Moreover, flow cytometry allowed the examination on a cellular level of changes that occur in cellular populations as they age and accumulate lipids.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Algae; Biofuels; Lipid production; Medium optimization; Response Surface Methodology

Mesh:

Substances:

Year:  2014        PMID: 25304731     DOI: 10.1016/j.biortech.2014.09.022

Source DB:  PubMed          Journal:  Bioresour Technol        ISSN: 0960-8524            Impact factor:   9.642


  9 in total

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Authors:  Su-Bin Park; Jin-Ho Yun; Ae Jin Ryu; Joohyun Yun; Ji Won Kim; Sujin Lee; Saehae Choi; Dae-Hyun Cho; Dong-Yun Choi; Yong Jae Lee; Hee-Sik Kim
Journal:  Microb Cell Fact       Date:  2021-02-15       Impact factor: 5.328

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Authors:  Meiyang Yang; Tingyuan Yang; Jilei Jia; Ting Lu; Hailin Wang; Xueying Yan; Lianyan Wang; Lian Yu; Yue Zhao
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9.  Optimization of multiplex quantitative polymerase chain reaction based on response surface methodology and an artificial neural network-genetic algorithm approach.

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Journal:  PLoS One       Date:  2018-07-25       Impact factor: 3.240

  9 in total

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