Predicting microalgae growth

W.M. Blanken; P.R. Postma; L. de Winter; R.H. Wijffels; M.G.J. Janssen

doi:10.1016/j.algal.2015.12.020

Predicting microalgae growth

W.M. Blanken^*, P.R. Postma, L. de Winter, R.H. Wijffels, M.G.J. Janssen^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

83 Citations (Scopus)

Abstract

A generally applicable kineticmodel is presented to predict light limitedmicroalgal growth. Thismodel combines a mathematical description for photoautotrophic sugar productionwith a description for aerobic chemoheterotrophic biomass growth. The model is based on five parameters which are directly measurable but were obtained from literature for the purpose of this study. The modelwas validated for Chlorella sorokinianawith 52 experiments derived from eight publications and for Chlamydomonas reinhardtii with 32 experiments derived from seven publications. The specific growth rate was initially predicted with a mean absolute percent error (MAPE) of 34–36%.
The lowaccuracy ismost likely caused by simplifications in the lightmodel and inaccurate parameter estimations. When optimizing the light model per experimental dataset, a 1–2%MAPE was obtained.When optimizing input
parameters separately from the light model, a 2–18% MAPE was realized. After validating this model on batch data, we conclude that this model is a reliable engineering tool to predict growth in photobioreactors provided the light field is accurately measured or calculated.

Original language	English
Pages (from-to)	28-38
Journal	Algal Research
Volume	14
DOIs	https://doi.org/10.1016/j.algal.2015.12.020
Publication status	Published - 2016

Keywords

Growth model
Light limited
Microalgae
Photosynthesis
Productivity prediction

Access to Document

10.1016/j.algal.2015.12.020Licence: CC BY

ALGADISK: Novel algae-based solution for CO2 capture and biomass production
1/01/12 → 31/12/14
Project: EU research project

Cite this

@article{f2904b77cfb441c3a5d9a0b3fa33f27b,

title = "Predicting microalgae growth",

abstract = "A generally applicable kineticmodel is presented to predict light limitedmicroalgal growth. Thismodel combines a mathematical description for photoautotrophic sugar productionwith a description for aerobic chemoheterotrophic biomass growth. The model is based on five parameters which are directly measurable but were obtained from literature for the purpose of this study. The modelwas validated for Chlorella sorokinianawith 52 experiments derived from eight publications and for Chlamydomonas reinhardtii with 32 experiments derived from seven publications. The specific growth rate was initially predicted with a mean absolute percent error (MAPE) of 34–36%.The lowaccuracy ismost likely caused by simplifications in the lightmodel and inaccurate parameter estimations. When optimizing the light model per experimental dataset, a 1–2%MAPE was obtained.When optimizing inputparameters separately from the light model, a 2–18% MAPE was realized. After validating this model on batch data, we conclude that this model is a reliable engineering tool to predict growth in photobioreactors provided the light field is accurately measured or calculated.",

keywords = "Growth model, Light limited, Microalgae, Photosynthesis, Productivity prediction",

author = "W.M. Blanken and P.R. Postma and {de Winter}, L. and R.H. Wijffels and M.G.J. Janssen",

year = "2016",

doi = "10.1016/j.algal.2015.12.020",

language = "English",

volume = "14",

pages = "28--38",

journal = "Algal Research",

issn = "2211-9264",

publisher = "Elsevier",

}

TY - JOUR

T1 - Predicting microalgae growth

AU - Blanken, W.M.

AU - Postma, P.R.

AU - de Winter, L.

AU - Wijffels, R.H.

AU - Janssen, M.G.J.

PY - 2016

Y1 - 2016

N2 - A generally applicable kineticmodel is presented to predict light limitedmicroalgal growth. Thismodel combines a mathematical description for photoautotrophic sugar productionwith a description for aerobic chemoheterotrophic biomass growth. The model is based on five parameters which are directly measurable but were obtained from literature for the purpose of this study. The modelwas validated for Chlorella sorokinianawith 52 experiments derived from eight publications and for Chlamydomonas reinhardtii with 32 experiments derived from seven publications. The specific growth rate was initially predicted with a mean absolute percent error (MAPE) of 34–36%.The lowaccuracy ismost likely caused by simplifications in the lightmodel and inaccurate parameter estimations. When optimizing the light model per experimental dataset, a 1–2%MAPE was obtained.When optimizing inputparameters separately from the light model, a 2–18% MAPE was realized. After validating this model on batch data, we conclude that this model is a reliable engineering tool to predict growth in photobioreactors provided the light field is accurately measured or calculated.

AB - A generally applicable kineticmodel is presented to predict light limitedmicroalgal growth. Thismodel combines a mathematical description for photoautotrophic sugar productionwith a description for aerobic chemoheterotrophic biomass growth. The model is based on five parameters which are directly measurable but were obtained from literature for the purpose of this study. The modelwas validated for Chlorella sorokinianawith 52 experiments derived from eight publications and for Chlamydomonas reinhardtii with 32 experiments derived from seven publications. The specific growth rate was initially predicted with a mean absolute percent error (MAPE) of 34–36%.The lowaccuracy ismost likely caused by simplifications in the lightmodel and inaccurate parameter estimations. When optimizing the light model per experimental dataset, a 1–2%MAPE was obtained.When optimizing inputparameters separately from the light model, a 2–18% MAPE was realized. After validating this model on batch data, we conclude that this model is a reliable engineering tool to predict growth in photobioreactors provided the light field is accurately measured or calculated.

KW - Growth model

KW - Light limited

KW - Microalgae

KW - Photosynthesis

KW - Productivity prediction

U2 - 10.1016/j.algal.2015.12.020

DO - 10.1016/j.algal.2015.12.020

M3 - Article

SN - 2211-9264

VL - 14

SP - 28

EP - 38

JO - Algal Research

JF - Algal Research

ER -

Predicting microalgae growth

Abstract

Keywords

Access to Document

Fingerprint

Projects

ALGADISK: Novel algae-based solution for CO2 capture and biomass production

Cite this