Mathematical Modeling of the Optimal Light Wavelength for Increasing Biomass and Cell Size of Chlorella Vulgaris as a Basis for Enhancing Biofuel Production
Session Number
Project ID: RISE 02 (poster only)
Advisor(s)
Mrs. Allison Hennings, Illinois Mathematics and Science Academy;
Dr. Srikanth Ammu (Ph.D), STERIS; Dr. Sri Sankar Chinta (Ph.D), Medical College of Wisconsin;
Dr. Jun Du Wahl (Ph.D), Clipper Corporation; Mr. Drew Mitchell, Wahl Clipper Corporation;
Mrs. Elizabeth Bruker, Naperville North H.S.
Discipline
Environmental Science
Start Date
17-4-2024 9:40 AM
End Date
17-4-2024 9:55 AM
Abstract
The pressing need for eco-friendly fuel sources due to limited fossil fuels and rising population elucidates microalgae including Chlorella vulgaris (C. vulgaris) as a sustainable biofuel. Yet, high production costs hinder their commercial viability, which can be addressed by optimized lighting. However, a gap exists concerning the optimal wavelength of light to enhance biomass growth and cell size in C. vulgaris. This experiment investigated the impact of varying light wavelengths (400-650 nm) on biomass growth and cell size to develop a predictive mathematical model aimed at increasing productivity of commercial units. Separate containers were established for four groups that were each exposed to different light wavelengths: blue (400-490 nm), green (510-530 nm), red (630-650 nm), and control (no light), and a12hr:12 hr light- dark cycle was used. Biomass concentration was measured using a spectrophotometer over 10 days and the data for each condition was regression fitted to a logistic growth curve. Cell size was measured on the last day using a light microscope. C. vulgaris exposed to blue light (400-490 nm) had the largest positive change in biomass, followed by red (630-650 nm) and green (510-530 nm). C. vulgaris exposed to red light had significantly smaller cell sizes, while other groups had comparably larger cell sizes. The derived mathematical model can be extrapolated to large-scale plants. Overall, the null hypothesis can be rejected, as One Way ANOVA p < 0.001. This has implications for reducing the cultivating and harvesting costs of C. vulgaris.
Mathematical Modeling of the Optimal Light Wavelength for Increasing Biomass and Cell Size of Chlorella Vulgaris as a Basis for Enhancing Biofuel Production
The pressing need for eco-friendly fuel sources due to limited fossil fuels and rising population elucidates microalgae including Chlorella vulgaris (C. vulgaris) as a sustainable biofuel. Yet, high production costs hinder their commercial viability, which can be addressed by optimized lighting. However, a gap exists concerning the optimal wavelength of light to enhance biomass growth and cell size in C. vulgaris. This experiment investigated the impact of varying light wavelengths (400-650 nm) on biomass growth and cell size to develop a predictive mathematical model aimed at increasing productivity of commercial units. Separate containers were established for four groups that were each exposed to different light wavelengths: blue (400-490 nm), green (510-530 nm), red (630-650 nm), and control (no light), and a12hr:12 hr light- dark cycle was used. Biomass concentration was measured using a spectrophotometer over 10 days and the data for each condition was regression fitted to a logistic growth curve. Cell size was measured on the last day using a light microscope. C. vulgaris exposed to blue light (400-490 nm) had the largest positive change in biomass, followed by red (630-650 nm) and green (510-530 nm). C. vulgaris exposed to red light had significantly smaller cell sizes, while other groups had comparably larger cell sizes. The derived mathematical model can be extrapolated to large-scale plants. Overall, the null hypothesis can be rejected, as One Way ANOVA p < 0.001. This has implications for reducing the cultivating and harvesting costs of C. vulgaris.