Multi-objective model optimisation using genetic algorithms for pleurotus sp. cultivation
Malaysia is the largest exporter of Elaeis Guineensis (Palm oil) in the international market. Oil palm cultivation generates a significant amount of lignocellulosic biomass derived from empty fruit bunches (EFB) as waste product. This research focused on optimizing the mycelium growth in Pleurotus s...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
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IOP Publishing
2020
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| Online Access: | https://umpir.ump.edu.my/id/eprint/29452/ |
| _version_ | 1848827280071065600 |
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| author | Norazwina, Zainol Abdul Sahli, Fakharudin Noor Athirah, Dzulkefli M. F., A. Bakar |
| author_facet | Norazwina, Zainol Abdul Sahli, Fakharudin Noor Athirah, Dzulkefli M. F., A. Bakar |
| author_sort | Norazwina, Zainol |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Malaysia is the largest exporter of Elaeis Guineensis (Palm oil) in the international market. Oil palm cultivation generates a significant amount of lignocellulosic biomass derived from empty fruit bunches (EFB) as waste product. This research focused on optimizing the mycelium growth in Pleurotus sp. cultivation by using EFB as a culture medium. The EFB was cut into the range of size of substrate (S) from 1.5 cm to 3.0 cm, soaked in water for overnight, applied steam treatment and incubated at the selected range of temperature (T) from 29 °C to 32 °C. The responses were mycelium extension rate (M) and nitrogen concentration in mycelium (N). The multi-objective optimisation of M and N requires the objective functions which represent both processes. For this type of problem, multi-objective genetic algorithm was chosen as the methodology, specifically using NSGA-II algorithm. Through the implementation of selected multi-objective genetic algorithm, it was able to produce the pareto front for optimising both nitrogen concentration and the extension rate of the mycelium. The highest nitrogen concentration and mycelium extension rate was from the result with crossover and mutation probability of 0.5 and 0.2. It produced 388.45 mg/L of nitrogen concentration and 0.370 cm/day of mycelium growth |
| first_indexed | 2025-11-15T03:58:12Z |
| format | Conference or Workshop Item |
| id | ump-29452 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:58:12Z |
| publishDate | 2020 |
| publisher | IOP Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-294522025-10-06T03:52:13Z https://umpir.ump.edu.my/id/eprint/29452/ Multi-objective model optimisation using genetic algorithms for pleurotus sp. cultivation Norazwina, Zainol Abdul Sahli, Fakharudin Noor Athirah, Dzulkefli M. F., A. Bakar QA76 Computer software TP Chemical technology Malaysia is the largest exporter of Elaeis Guineensis (Palm oil) in the international market. Oil palm cultivation generates a significant amount of lignocellulosic biomass derived from empty fruit bunches (EFB) as waste product. This research focused on optimizing the mycelium growth in Pleurotus sp. cultivation by using EFB as a culture medium. The EFB was cut into the range of size of substrate (S) from 1.5 cm to 3.0 cm, soaked in water for overnight, applied steam treatment and incubated at the selected range of temperature (T) from 29 °C to 32 °C. The responses were mycelium extension rate (M) and nitrogen concentration in mycelium (N). The multi-objective optimisation of M and N requires the objective functions which represent both processes. For this type of problem, multi-objective genetic algorithm was chosen as the methodology, specifically using NSGA-II algorithm. Through the implementation of selected multi-objective genetic algorithm, it was able to produce the pareto front for optimising both nitrogen concentration and the extension rate of the mycelium. The highest nitrogen concentration and mycelium extension rate was from the result with crossover and mutation probability of 0.5 and 0.2. It produced 388.45 mg/L of nitrogen concentration and 0.370 cm/day of mycelium growth IOP Publishing 2020 Conference or Workshop Item PeerReviewed pdf en cc_by https://umpir.ump.edu.my/id/eprint/29452/1/3.%20Multi-objective%20model%20optimisation%20using%20genetic%20algorithms.pdf Norazwina, Zainol and Abdul Sahli, Fakharudin and Noor Athirah, Dzulkefli and M. F., A. Bakar (2020) Multi-objective model optimisation using genetic algorithms for pleurotus sp. cultivation. In: IOP Conference Series: Materials Science and Engineering. 5th UTP-UMP-UAF Symposium on Energy Systems 2019, SES 2019 , 1 - 2 October 2019 , Kuantan; Malaysia. pp. 1-9., 863 (012027). ISSN 1757-8981 (Print), 1757-899X (Online) (Published) https://doi.org/10.1088/1757-899X/863/1/012027 |
| spellingShingle | QA76 Computer software TP Chemical technology Norazwina, Zainol Abdul Sahli, Fakharudin Noor Athirah, Dzulkefli M. F., A. Bakar Multi-objective model optimisation using genetic algorithms for pleurotus sp. cultivation |
| title | Multi-objective model optimisation using genetic algorithms for pleurotus sp. cultivation |
| title_full | Multi-objective model optimisation using genetic algorithms for pleurotus sp. cultivation |
| title_fullStr | Multi-objective model optimisation using genetic algorithms for pleurotus sp. cultivation |
| title_full_unstemmed | Multi-objective model optimisation using genetic algorithms for pleurotus sp. cultivation |
| title_short | Multi-objective model optimisation using genetic algorithms for pleurotus sp. cultivation |
| title_sort | multi-objective model optimisation using genetic algorithms for pleurotus sp. cultivation |
| topic | QA76 Computer software TP Chemical technology |
| url | https://umpir.ump.edu.my/id/eprint/29452/ https://umpir.ump.edu.my/id/eprint/29452/ |