DOI : https://doi.org/10.18517/ijaseit.3.2.307

Pre-Optimization Conditions for Haematococcus pluvialis Growth

Nurul Asmidar Hanan (1), Najeeb Kaid Al-Shorgani (2), Hafiza Shukor (3), Norliza Abd. Rahman (4), Mohd Sahaid Kalil (5)
(1) Department of Chemical and Process Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
(2) Department of Chemical and Process Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
(3) Department of Chemical and Process Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
(4) Department of Chemical and Process Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
(5) Department of Chemical and Process Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
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How to cite (IJASEIT) :
Hanan, Nurul Asmidar, et al. “Pre-Optimization Conditions for Haematococcus Pluvialis Growth”. International Journal on Advanced Science, Engineering and Information Technology, vol. 3, no. 2, Apr. 2013, pp. 168-71, doi:10.18517/ijaseit.3.2.307.
Citation Format :
The green microalgae Haematococcus pluvialis is one of the most beneficial microalgae due to its production of astaxanthin that has great commercial interest because of its antioxidant properties. A two level factorial design (2LFD) was used to pre-optimize conditions to grow H. pluvialis. The variables involved were pH, inoculum size, temperature and presence or absence of light. The results were analyzed by analysis of variance (ANOVA). ANOVA analysis showed that inoculum size of 40%, temperature of 30oC and presence of light had significant effects on H. pluvialis growth whereas production pH had insignificant effect. The established model from the ANOVA analysis had a significant value with Pmodel > F = 0.0074 and the R² value of 0.9989. The expected growth was 1.08879 (Table 5) and the optimized growth was 1.178 (Table 5).

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