Modelling of Biphasic Biogas Production Process from Mixtures of Livestock Manure Using Bi-logistic Function and Modified Gompertz Equation

Opurum, Christian C. and Nweke, Christian O. and Nwanyanwu, Christopher E. and Nwogu, Nkemakolam A. (2021) Modelling of Biphasic Biogas Production Process from Mixtures of Livestock Manure Using Bi-logistic Function and Modified Gompertz Equation. Annual Research & Review in Biology, 36 (3). pp. 116-129. ISSN 2347-565X

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Abstract

In this study, anaerobic digestion (AD) of three livestock manure: (poultry manure (PM), pig dung (PD), and cow dung (CD) was conducted at different mixed ratios under mesophilic (25-35°C) conditions. Two kinetic models, the modified Gompertz and bi-logistic function model were used to simulate the cumulative biogas yield from the experiments, and model parameters simultaneously obtained. The biogas production profile appeared diauxic-like or biphasic with multiple peaks, revealing the complexity and multi-component nature of the substrates. There was an increase in biogas yield from the treatments, PD/CD 1:1; 37.25 dm3 (3.47%), PD/CD 3:1; 38.41 dm3 (6.96%), CD/PM 1:1; 26.76 dm3 (16.80%) and CD/PM 3:1 24.31 dm3 (6.11%), whereas PD/CD 2:1 (15.41 dm3) and CD/PM 2:1 (22.57 dm3) exhibited inhibitory effect. However, statistical analysis (ANOVA) indicated a significant difference in biogas yield from PD alone (36 dm3) compared to CD alone (22.91 dm3). The two models showed good performance in the simulation of the AD process, with high correlation coefficients, an indication of a very strong relationship between experimental data and model parameters. However, the bi-logistic function model showed a better fit in the simulation of the experimental values, as it was able to capture the curves in the plots, with a higher correlation coefficient R2 (0.9920 - 0.9985) than the modified Gompertz model (0.9797 - 0.9968). This work has shown that the phenomenon of diauxic growth in the anaerobic digestion of complex organic substrates could be captured quantitatively in the kinetic model using bi-logistic function model.

Item Type: Article
Subjects: STM Library > Biological Science
Depositing User: Managing Editor
Date Deposited: 04 Feb 2023 05:27
Last Modified: 23 Apr 2024 12:30
URI: http://open.journal4submit.com/id/eprint/378

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