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Subject: search.filters.subject.Acetification rate

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    Acetification of rice wine by Acetobacter aceti using loofa sponge in a low-cost reciprocating shaker
    (2014-11-01)
    Krusong, W.
    ;
    Tantratian, S.
    Aims: To maximize acetification rate (ETA) by adsorption of acetic acid bacteria (AAB) on loofa sponge matrices (LSM). Methods and Results: AAB were adsorbed on LSM, and the optimal shaking rate was determined for maximized AAB growth and oxygen availability. Results confirm that the 1 Hz reciprocating shaking rate with 40% working volume (liquid volume 24 l, tank volume 60 l) achieved a high oxygen transfer coefficient (k<inf>L</inf>a). The highest ETA was obtained at 50% (w:v) LSM-AAB:culture medium at 30 ± 2°C (P ≤ 0·05). To test process consistency, nine sequential acetification cycles were run using LSM-AAB and comparing it with no LSM. The highest ETA (1·701-2·401 g l<sup>-1</sup> d<sup>-1</sup>) was with LSM-AAB and was associated with the highest biomass of AAB, confirmed by SEM images. Conclusions: Results confirm that LSM-AAB works well as an inert substrate for AAB. High oxygenation was maintained by a reciprocating shaker. Both shaking and LSM were important in increasing ETA. Significance and Impact of the Study: High cell biomass in LSM-AAB provides good conditions for higher ETAs of quick acetification under adequate oxygen transfer by reciprocating shaker. It is a sustainable process for small-scale vinegar production system requiring minimal set-up cost.
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    Prediction of influence of stepwise increment of initial acetic acid concentration in charging medium on acetification rate of semi-continuous process by artificial neural network
    (2014-01-01)
    Krusong, Warawut
    ;
    Pornpukdeewatana, Soisuda
    ;
    Kerdpiboon, Soraya
    ;
    Tantratian, Sumate
    Based on industrial vinegar production, ethanol concentration in charging medium is normally considered as a strong variable influencing the acetification for a given initial acetic acid concentration. Moreover, high initial acetic acid concentration is considered when higher than 100 g L<sup>-1</sup> of acetic acid as finished product is obtained. This study assessed the effect of a stepwise increment of initial acetic acid concentration in fermentation medium of 45, 55, and 65 g L<sup>-1</sup> after charging at constant ethanol concentration of 35 g L<sup>-1</sup> on acetification rate (ETA) by high acid-tolerant strain of Acetobacter aceti WK. Average ETA was 8.144 + 0.09 g L<sup>-1</sup> d<sup>-1</sup> at 45 g L<sup>-1</sup> and 8.655 + 0.09 g L<sup>-1</sup> d<sup>-1</sup> at 55 g L<sup>-1</sup>, and significant decreased to 6.819 + 0.23 g L<sup>-1</sup> d<sup>-1</sup> at 65 g L<sup>-1</sup>. An artificial neural network (ANN) model was applied to predict the ETA in semi-continuous acetification under the conditions of the study. The optimized ANN structure was revealed to contain two hidden layers and seven neurons per layer. The experimental acetification correlated to the predicted data with R<sup>2</sup> of training and testing data set of 0.858 and validation data set of 0.831, respectively. Results indicated that the inputs as acetic acid and ethanol concentrations successfully predicted the ETA of semi-continuous acetification process. © 2013 Elsevier Ltd.