Artificial intelligence model for monitoring biomass growth in semi-batch Chlorella vulgaris cultivation
There is a great demand for a clean, economical, and long-term energy source, due to the depletion of fossil fuels. Large-scale production of microalgae biomass for biofuel production is likely attributable to several challenges, including the high cost of photobioreactors, the need for a sustainabl...
| Main Authors: | , , , , , , , , |
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| Format: | Journal Article |
| Language: | English |
| Published: |
2022
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| Online Access: | https://hdl.handle.net/10356/163734 |
| _version_ | 1824457087934005248 |
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| author | Peter, Angela Paul Chew, Kit Wayne Pandey, Ashok Lau, Sie Yon Rajendran, Saravanan Ting, Huong Yong Munawaroh, Heli Siti Halimatul Phuong, Nguyen Van Show, Pau Loke |
| author2 | School of Chemical and Biomedical Engineering |
| author_facet | School of Chemical and Biomedical Engineering Peter, Angela Paul Chew, Kit Wayne Pandey, Ashok Lau, Sie Yon Rajendran, Saravanan Ting, Huong Yong Munawaroh, Heli Siti Halimatul Phuong, Nguyen Van Show, Pau Loke |
| author_sort | Peter, Angela Paul |
| collection | NTU |
| description | There is a great demand for a clean, economical, and long-term energy source, due to the depletion of fossil fuels. Large-scale production of microalgae biomass for biofuel production is likely attributable to several challenges, including the high cost of photobioreactors, the need for a sustainable medium for optimum development, and time-consuming algal growth monitoring techniques. Firstly, the research novelty aims at improving the strategy of recycling culture media for semi-batch cultivation of Chlorella vulgaris. Two cycles were performed with varying amounts of recycled medium replacement to evaluate algal growth and biochemical content. As compared to all other culture ratio combinations, the mixing ratio of recycled medium to fresh medium is at 40 % (40RB) combination yielded the greatest biomass growth (4.52 g/L), lipid (317.40 mg/g), protein (280.57 mg/g), and carbohydrate (451.37 mg/g) content. Next, custom vision was applied to Chlorella vulgaris maturing stages, and a unique digital architecture framework was developed. The iteration model delivers result interpretation with an accuracy of more than 92 % of every data set based on the trained Model Performance. |
| first_indexed | 2025-02-19T04:04:26Z |
| format | Journal Article |
| id | ntu-10356/163734 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T04:04:26Z |
| publishDate | 2022 |
| record_format | dspace |
| spelling | ntu-10356/1637342022-12-19T07:23:02Z Artificial intelligence model for monitoring biomass growth in semi-batch Chlorella vulgaris cultivation Peter, Angela Paul Chew, Kit Wayne Pandey, Ashok Lau, Sie Yon Rajendran, Saravanan Ting, Huong Yong Munawaroh, Heli Siti Halimatul Phuong, Nguyen Van Show, Pau Loke School of Chemical and Biomedical Engineering Engineering::Chemical engineering Semi Batch Culture Medium Recycling There is a great demand for a clean, economical, and long-term energy source, due to the depletion of fossil fuels. Large-scale production of microalgae biomass for biofuel production is likely attributable to several challenges, including the high cost of photobioreactors, the need for a sustainable medium for optimum development, and time-consuming algal growth monitoring techniques. Firstly, the research novelty aims at improving the strategy of recycling culture media for semi-batch cultivation of Chlorella vulgaris. Two cycles were performed with varying amounts of recycled medium replacement to evaluate algal growth and biochemical content. As compared to all other culture ratio combinations, the mixing ratio of recycled medium to fresh medium is at 40 % (40RB) combination yielded the greatest biomass growth (4.52 g/L), lipid (317.40 mg/g), protein (280.57 mg/g), and carbohydrate (451.37 mg/g) content. Next, custom vision was applied to Chlorella vulgaris maturing stages, and a unique digital architecture framework was developed. The iteration model delivers result interpretation with an accuracy of more than 92 % of every data set based on the trained Model Performance. This work was supported by the Fundamental Research Grant Scheme, Malaysia [FRGS/1/2019/STG05/UNIM/02/2] and MyPAIRPHC-Hibiscus Grant [MyPAIR/1/2020/STG05/UNIM/1], Indonesian Research Collaboration (RKI) scheme C and Universitas Pendidikan Indonesia (Nomor: 1167/UN40.LP/PT01.03/2022). 2022-12-15T05:40:29Z 2022-12-15T05:40:29Z 2023 Journal Article Peter, A. P., Chew, K. W., Pandey, A., Lau, S. Y., Rajendran, S., Ting, H. Y., Munawaroh, H. S. H., Phuong, N. V. & Show, P. L. (2023). Artificial intelligence model for monitoring biomass growth in semi-batch Chlorella vulgaris cultivation. Fuel, 333(Part 2), 126438-. https://dx.doi.org/10.1016/j.fuel.2022.126438 0016-2361 https://hdl.handle.net/10356/163734 10.1016/j.fuel.2022.126438 2-s2.0-85141249438 Part 2 333 126438 en Fuel © 2022 Elsevier Ltd. All rights reserved. |
| spellingShingle | Engineering::Chemical engineering Semi Batch Culture Medium Recycling Peter, Angela Paul Chew, Kit Wayne Pandey, Ashok Lau, Sie Yon Rajendran, Saravanan Ting, Huong Yong Munawaroh, Heli Siti Halimatul Phuong, Nguyen Van Show, Pau Loke Artificial intelligence model for monitoring biomass growth in semi-batch Chlorella vulgaris cultivation |
| title | Artificial intelligence model for monitoring biomass growth in semi-batch Chlorella vulgaris cultivation |
| title_full | Artificial intelligence model for monitoring biomass growth in semi-batch Chlorella vulgaris cultivation |
| title_fullStr | Artificial intelligence model for monitoring biomass growth in semi-batch Chlorella vulgaris cultivation |
| title_full_unstemmed | Artificial intelligence model for monitoring biomass growth in semi-batch Chlorella vulgaris cultivation |
| title_short | Artificial intelligence model for monitoring biomass growth in semi-batch Chlorella vulgaris cultivation |
| title_sort | artificial intelligence model for monitoring biomass growth in semi batch chlorella vulgaris cultivation |
| topic | Engineering::Chemical engineering Semi Batch Culture Medium Recycling |
| url | https://hdl.handle.net/10356/163734 |
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