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Author: search.filters.author.Krusong, WarawutSubject: search.filters.subject.acetic acid

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    Defining Paenibacillus azoreducens (P8) and Acetobacter pasteurianus (UMCC 2951) strains performances in producing acetic acid
    (2022-11-17)
    Krusong, Warawut
    ;
    La China, Salvatore
    ;
    Pothimon, Ruttipron
    ;
    Gullo, Maria
    In this study, spore-forming bacteria isolated from saccharified rice were selected for producing acetic acid. From the screening of 15 strains, P8 strain was chosen as a candidate. The strain was identified as Paenibacillus azoreducens by 16S rRNA analysis (99.85% similarity with P. azoreducens CM1<sup>T</sup>). Acetic acid is the main component of vinegar but also an industrial commodity produced by chemical synthesis. Sustainable routes for obtaining acetic acid are of great interest for decreasing the environmental impact generated by chemical syntheses. Biological acetic acid production is effective for vinegar production by acetic acid bacteria, but it cannot economically compete with the chemical synthesis for producing it as a pure commodity. Considering the need to improve the yield of pure acetic acid produced by microbial conversions, in this study, P8 strain was chosen for designing processes in different fermentation conditions. Tests were conducted in single and semi-continuous systems, using rice wine as substrate. Acetic acid produced by P8 strain was compared with that of Acetobacter pasteurianus (UMCC 2951), a strain known for producing acetic acid from rice wine. Even though the fermentation performances of P. azoreducens P8 were slightly lower than those of acetic acid bacteria usually used for vinegar production, results highlight its suitability for producing acetic acid. The final acetic acid produced by P. azoreducens P8 was 73 g/L, in a single stage fermentation, without losses. In nine cycles of semi-continuous regime the average of acetification rate was 0.814 (g/L/days). Two main attributes of P. azoreducens P8 are of relevance for producing acetic acid, namely the ability to grow at temperature higher (+ 37°C), than mesophilic acetic acid bacteria, and the absence of cytoplasmic assimilation of acetic acid. These features allow to design multiple strains cultures, in which P. azoreducens can acts as a helper strain. Based on our results, the new isolate P. azoreducens P8 can be propagated in fermenting broths for boosting acetic acid production, under the selected conditions, and used in combination with acetic acid bacteria to produce biological acetic acid, as a non-food grade commodity.
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    Evaluation of acetic acid and ethanol concentration in a rice vinegar internal venturi injector bioreactor using Fourier transform near infrared spectroscopy
    (2019-12-01)
    Phanomsophon, Thitima
    ;
    Sirisomboon, Panmanas
    ;
    Lapcharoensuk, Ravipat
    ;
    Shrestha, Bim
    ;
    Krusong, Warawut
    In the process of fermenting rice vinegar, the concentration of acetic acid and ethanol concentration must be measured for monitoring of the total concentration. Near infrared spectroscopy has been used to rapidly monitor the concentration of acetic acid and ethanol concentration daily during 10 cycles of the fermentation process. The model was developed using partial least squares regression. For predicting concentration of acetic acid with near infrared spectroscopy, the coefficient of determination (R<sup>2</sup>), root mean square error of calibration, root mean square error of cross validation, ratio of standard error of validation to standard deviation, and bias was 0.96, 2.30 g L<sup>−1</sup>, 2.44 g L<sup>−1</sup>, 1.11 g L<sup>−1</sup>, and 5.56, respectively. For ethanol concentration, the value of R<sup>2</sup>, root mean square error of calibration, root mean square error of cross validation, bias and ratio of prediction to deviation were predicted to be 0.94, 3.15 g L<sup>−1</sup>, 2.73 g L<sup>−1</sup>, −0.40 g L<sup>−1</sup>, and 4.04, respectively. However, both models provided fair performance when tested with an external set of samples, indicating that the models could be applied for rough screening.