Determination by response surface methodology of optimal protein and phycocyanin productivity conditions in Arthrospira (Spirulina) platensis under different combinations of photoperiod variation and lighting intensity - Université du Littoral Côte d'Opale Access content directly
Journal Articles Bioresource Technology Reports Year : 2021

Determination by response surface methodology of optimal protein and phycocyanin productivity conditions in Arthrospira (Spirulina) platensis under different combinations of photoperiod variation and lighting intensity

Laura Junique
  • Function : Author
Lucie Watier
  • Function : Author
  • PersonId : 1242281
Hortense Lejeune
  • Function : Author
Florence Viudes
  • Function : Author
Marie Deblieck
  • Function : Author

Abstract

The objective of this study is to determine the lighting conditions for an optimal production of Arthrospira (Spirulina) platensis quantitatively and qualitatively for the process most commonly used by producers. A design of experiments made it possible to obtain surface modelling of responses which were validated under pilot conditions. Spirulina growth, protein and pigment content were modelled as a function of light intensity and duration of illumination. For each of them, the optima have been determined: 14 h (hours light exposure)/10 Klux (light intensity) for the growth rate; 11.8 h/7.2 Klux for phycocyanin rate; 6.2Klux/12.6 h for chlorophyll rate; 6.6Klux/12.6 h for carotene rate. The protein rate is the lowest when lighting conditions are of 10.6 Klux and 14.4 h. It is then possible for the producer to partially obscure the ponds and/or increase the light intensity using additional lighting.

Dates and versions

hal-04049494 , version 1 (12-04-2023)

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Laura Junique, Lucie Watier, Hortense Lejeune, Florence Viudes, Marie Deblieck, et al.. Determination by response surface methodology of optimal protein and phycocyanin productivity conditions in Arthrospira (Spirulina) platensis under different combinations of photoperiod variation and lighting intensity. Bioresource Technology Reports, 2021, 15, pp.100763. ⟨10.1016/j.biteb.2021.100763⟩. ⟨hal-04049494⟩
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