Proceedings of the 2nd International Conference on Neural Networks and Machine Learning 2023 (ICNNML 2023)

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Kinetic Model of Ulva sp Protein Extraction using Ultrasound-Assisted Osmotic Shock Method

Authors
Boy Arief Fachri1, *, Bekti Palupi1, Istiqomah Rahmawati1, Meta Fitri Rizkiana1, Helda Wika Amini1, Nurul Hidayati1
1Chemical Engineering Department, Universitas Jember, Jalan Kalimantan 37, 68121, Jember, Indonesia
*Corresponding author. Email: fachri.teknik@unej.ac.id
Corresponding Author
Boy Arief Fachri
Available Online 29 June 2024.
DOI
10.2991/978-94-6463-445-7_27How to use a DOI?
Keywords
Ultrasound-assisted extraction; protein yield optimization; diffusion coefficient analysis
Abstract

Ulva Sp is a type of macroalgae that contains 13-26% protein. This works is to study kinetic of Ulva sp protein extraction using Ultrasound-Assisted Osmotic Shock Method. The ulva sp powder and Na-Sulfate-ethanol solution in a ratio of 1:10 (g/mL) were fed into a set of extractor unit in a presence of ultrasound wave for 30 minutes. The variables extraction was particle size (60, 80, 100 mesh) and extraction time (10, 15, 30 minutes). Supernatants thus was separated and purified from precipitates to analyze protein content using Bradford method. The maximum protein yield obtained is 61.98 % with an operating condition of particle size of 100 mesh and extraction time of 15 minutes. The diffusion coefficient empirically was formulated as De = 3 × 10−15 × (particle size) 0.6.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2nd International Conference on Neural Networks and Machine Learning 2023 (ICNNML 2023)
Series
Advances in Intelligent Systems Research
Publication Date
29 June 2024
ISBN
10.2991/978-94-6463-445-7_27
ISSN
1951-6851
DOI
10.2991/978-94-6463-445-7_27How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Boy Arief Fachri
AU  - Bekti Palupi
AU  - Istiqomah Rahmawati
AU  - Meta Fitri Rizkiana
AU  - Helda Wika Amini
AU  - Nurul Hidayati
PY  - 2024
DA  - 2024/06/29
TI  - Kinetic Model of Ulva sp Protein Extraction using Ultrasound-Assisted Osmotic Shock Method
BT  - Proceedings of the 2nd International Conference on Neural Networks and Machine Learning 2023 (ICNNML 2023)
PB  - Atlantis Press
SP  - 244
EP  - 248
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-445-7_27
DO  - 10.2991/978-94-6463-445-7_27
ID  - Fachri2024
ER  -