Cover Image

Predictive growth model of microalgae in agricultural wastewater / Nur I'ffah Abdul Hanan...[et al.]

Agricultural wastewater is a dark brown viscous liquid with a high concentration of degradable organic matter and mineral constituents. The incorporation of microalgae in agricultural wastewater to utilizes organic substances creates a potentially unprecedented valuation. However, provided that the...

Full description

Saved in:
Bibliographic Details
Main Authors: Abdul Hanan, Nur I'ffah, Azmi, Nur Faqihah, Yusof, Nurul Asyikin, Mohd Nazril, Akif
Format: Student Project
Language:English
Subjects:
Study and teaching
Laboratories. General works
Microscopy
Microorganisms
Online Access:https://ir.uitm.edu.my/id/eprint/55025/1/55025.pdf
https://ir.uitm.edu.my/id/eprint/55025/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uitm.ir.55025
record_format eprints
spelling my.uitm.ir.550252024-04-05T06:47:10Z https://ir.uitm.edu.my/id/eprint/55025/ Predictive growth model of microalgae in agricultural wastewater / Nur I'ffah Abdul Hanan...[et al.] Abdul Hanan, Nur I'ffah Azmi, Nur Faqihah Yusof, Nurul Asyikin Mohd Nazril, Akif Study and teaching Laboratories. General works Microscopy Microorganisms Agricultural wastewater is a dark brown viscous liquid with a high concentration of degradable organic matter and mineral constituents. The incorporation of microalgae in agricultural wastewater to utilizes organic substances creates a potentially unprecedented valuation. However, provided that the descriptive growth model of microalgae in agricultural wastewater is rarely addressed. In this study, an assessment was performed on four mathematical models (Logistic, Modified Logistic, Modified Gompertz, and Baranyi-Roberts) on the growth of Coellastrela sp. UKM4, Chlamydomonas sp. UKM6 and Scenedesmus sp. UKM9 based on the available published works in the literature. Statistical analyses, including R2, adjusted R2, rootmean-square error (RMSE), bias factor (BF), accuracy factor (AF), and percent of standard error prediction (%SEP) were applied to verify the accuracy of each model. The findings showed, based on the visual analysis and residual plots, modified logistic model and Baranyi- Robets model had produced good fitting curve between experimental data and model predictive data. For statistical analysis, both models produced R2 (>95%), adjusted R2 (>93%), RMSE (0.048-0.08), BF (0.9-1.01), AF (<1.1) and %SEP (7.7%-15%). The findings therefore revealed that the most appropriate model for predicting the growth of Coellastrela sp. UKM4, Chlamydomonas sp. UKM6 and Scenedesmus sp. UKM9 in agricultural wastewater were modified logistic and Baranyi-Roberts models. Student Project NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/55025/1/55025.pdf Predictive growth model of microalgae in agricultural wastewater / Nur I'ffah Abdul Hanan...[et al.]. [Student Project] <http://terminalib.uitm.edu.my/55025.pdf> (Unpublished)
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Study and teaching
Laboratories. General works
Microscopy
Microorganisms
spellingShingle Study and teaching
Laboratories. General works
Microscopy
Microorganisms
Abdul Hanan, Nur I'ffah
Azmi, Nur Faqihah
Yusof, Nurul Asyikin
Mohd Nazril, Akif
Predictive growth model of microalgae in agricultural wastewater / Nur I'ffah Abdul Hanan...[et al.]
description Agricultural wastewater is a dark brown viscous liquid with a high concentration of degradable organic matter and mineral constituents. The incorporation of microalgae in agricultural wastewater to utilizes organic substances creates a potentially unprecedented valuation. However, provided that the descriptive growth model of microalgae in agricultural wastewater is rarely addressed. In this study, an assessment was performed on four mathematical models (Logistic, Modified Logistic, Modified Gompertz, and Baranyi-Roberts) on the growth of Coellastrela sp. UKM4, Chlamydomonas sp. UKM6 and Scenedesmus sp. UKM9 based on the available published works in the literature. Statistical analyses, including R2, adjusted R2, rootmean-square error (RMSE), bias factor (BF), accuracy factor (AF), and percent of standard error prediction (%SEP) were applied to verify the accuracy of each model. The findings showed, based on the visual analysis and residual plots, modified logistic model and Baranyi- Robets model had produced good fitting curve between experimental data and model predictive data. For statistical analysis, both models produced R2 (>95%), adjusted R2 (>93%), RMSE (0.048-0.08), BF (0.9-1.01), AF (<1.1) and %SEP (7.7%-15%). The findings therefore revealed that the most appropriate model for predicting the growth of Coellastrela sp. UKM4, Chlamydomonas sp. UKM6 and Scenedesmus sp. UKM9 in agricultural wastewater were modified logistic and Baranyi-Roberts models.
format Student Project
author Abdul Hanan, Nur I'ffah
Azmi, Nur Faqihah
Yusof, Nurul Asyikin
Mohd Nazril, Akif
author_facet Abdul Hanan, Nur I'ffah
Azmi, Nur Faqihah
Yusof, Nurul Asyikin
Mohd Nazril, Akif
author_sort Abdul Hanan, Nur I'ffah
title Predictive growth model of microalgae in agricultural wastewater / Nur I'ffah Abdul Hanan...[et al.]
title_short Predictive growth model of microalgae in agricultural wastewater / Nur I'ffah Abdul Hanan...[et al.]
title_full Predictive growth model of microalgae in agricultural wastewater / Nur I'ffah Abdul Hanan...[et al.]
title_fullStr Predictive growth model of microalgae in agricultural wastewater / Nur I'ffah Abdul Hanan...[et al.]
title_full_unstemmed Predictive growth model of microalgae in agricultural wastewater / Nur I'ffah Abdul Hanan...[et al.]
title_sort predictive growth model of microalgae in agricultural wastewater / nur i'ffah abdul hanan...[et al.]
url https://ir.uitm.edu.my/id/eprint/55025/1/55025.pdf
https://ir.uitm.edu.my/id/eprint/55025/
_version_ 1797924678382125056
score 13.211869

Similar Items