Optimization of pH and nitrogen for enhanced hydrogen production by Synechocystis sp. PCC 6803 via statistical and machine learning methods

Biotechnology Progress

Volumn 25, Issue 4, 2009, Pages 1009-1017

  Burrows, Elizabeth H ^a   Wong, Weng Keen ^b   Fern, Xiaoli ^b   Chaplen, Frank W R ^a   Ely, Roger L ^a  

^a OREGON STATE UNIVERSITY   (United States)

^b Oregon State University   (United States)

Author keywords

Cyanobacteria; Fermentative hydrogen production; Nitrogen; Optimization algorithm; PH; Response surface methodology; Synechocystis sp. PCC 6803

Indexed keywords

CYANOBACTERIA; FERMENTATIVE HYDROGEN PRODUCTION; OPTIMIZATION ALGORITHM; RESPONSE SURFACE METHODOLOGY; SYNECHOCYSTIS SP. PCC 6803;

CHLOROPHYLL; CONCENTRATION (PROCESS); DENSITY (OPTICAL); DENSITY MEASUREMENT (OPTICAL); GAS PRODUCERS; LEARNING ALGORITHMS; LIGHT TRANSMISSION; NITROGEN; OPTIMIZATION; PORPHYRINS; ROBOT LEARNING; SURFACE PROPERTIES;

HYDROGEN PRODUCTION;

HYDROGEN; NITROGEN;

CHEMISTRY; CONFERENCE PAPER; EVALUATION; FERMENTATION; METABOLISM; METHODOLOGY; PH; STATISTICAL MODEL; SYNECHOCYSTIS; SYSTEMS BIOLOGY;

FERMENTATION; HYDROGEN; HYDROGEN-ION CONCENTRATION; MODELS, STATISTICAL; NITROGEN; SYNECHOCYSTIS; SYSTEMS BIOLOGY;

CYANOBACTERIA; SYNECHOCYSTIS; SYNECHOCYSTIS SP.; SYNECHOCYSTIS SP. PCC 6803;

EID: 69149092509     PISSN: 87567938     EISSN: None     Source Type: Journal    
DOI: 10.1002/btpr.213     Document Type: Conference Paper

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