Prediction of Microbial Population in Sorghum Fermentation through Mathematical Models

*Umi Laila  -  Research Unit for Natural Product Technology, Indonesian Institute of Sciences, Indonesia
Rifa Nurhayati  -  Research Divison for Natural Product Technology, Indonesian Institute of Sciences, Indonesia
Tyas Utami  -  Department of Food and Agricultural Product Technology, Faculty of Agricultural Technology, Gadjah Mada University, Indonesia
Endang Sutriswati Rahayu  -  Department of Food and Agricultural Product Technology, Faculty of Agricultural Technology, Gadjah Mada University, Indonesia
Received: 7 Aug 2019; Published: 31 Dec 2019.
DOI: https://doi.org/10.14710/reaktor.19.4.152-161 View
Coli spontan _Baranyi
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lAB spontan _ Baranyi
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Coli spontan_Fujikawa
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LAB spontan_Fujikawa
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Coli spontan _Gompertz modified Gibson
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LAB spontan _ Gompertz modified by Gibson
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Coli spontan _Gompertz Zwietering
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LAB spontan _Gompertz Zwietering
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LAB spontan _Richard
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LAB spontan _Schnute
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Coli spontan _RIchard
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Coli spontan _ Schnute
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model fermentasi sorgum dengan penambahan inokulum
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Open Access Copyright (c) 2019 Reaktor
License URL: http://creativecommons.org/licenses/by-nc-sa/4.0

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Section: Research Article
Language: EN
Statistics: 106 92
Abstract

The mathematical models can be used as a tool in predicting microbial population in sorghum fermentation, either spontaneous fermentation or fermentation with the addition of lactic acid bacteria (LAB) inoculum. Gompertz model modified by Gibson, Gompertz model modified by Zwietering, Baranyi-Robert model, Fujikawa model, Richards model, Schnute model were used in predicting the growth of lactic acid bacteria (LAB) and coliform bacteria during spontaneous fermentation, and also the growth of LAB during fermentation with the addition of inoculum. Meanwhile, there was death (inactivation) of coliform bacteria during sorghum fermentation with the addition of LAB inoculum. The Geeraerd model and the Gompertz model modified by Gil et al. were used to predict the inactivation. The accuracy and precision of models were evaluated based on the Root Mean of Sum Square Error (RMSE), coefficient of determination (R2), and curve fitting. Gompertz model modified by Gibson had the highest accuracy and precision, which was followed by the accuracy of the Fujikawa model and Baranyi-Robert model in predicting the growth of LAB and the growth of coliform bacteria during spontaneous fermentation. Meanwhile, in predicting LAB growth during fermentation with the addition of inoculum, high accuracy and precision was obtained from Richards and Schnute models. In predicting the inactivation of coliform bacteria, Geeraerd model provided higher accuracy and precision compared to Gompertz model modified by Gil et al.

 

Keywords: fermentation; inoculum; mathematical; model; sorghum; spontaneous

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