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  • 标题:Optimization of the Effects of Different Temperatures and Compositions of Filmogenic Solution on Lactobacillus salivarius Using Predictive Mathematical Models
  • 本地全文:下载
  • 作者:Shênia Santos Monteiro ; Wilton Pereira da Silva ; Shirley Santos Monteiro
  • 期刊名称:Foods
  • 电子版ISSN:2304-8158
  • 出版年度:2021
  • 卷号:10
  • 期号:1
  • 页码:25
  • DOI:10.3390/foods10010025
  • 出版社:MDPI Publishing
  • 摘要:It is well known that intake of probiotic brings health benefits. Lactic bacteria with probiotic potential have aroused the interest of the industry in developing food products that incorporate such benefits. However, incorporating probiotic bacteria into food is a challenge for the industry, given the sensitivity of probiotic cultures to process conditions. Therefore, the objective of this study is to evaluate gelatin- and inulin-based filmogenic solutions as a potential vehicle for incorporating probiotics into food products and to model the fermentation kinetics. L. salivarius (Lactobacillus salivarius) growth in filmogenic solutions was analyzed under the influence of a variety gelatin concentrations (1.0–3.0%) and inulin concentrations (4.0–6.0%) and fermented under the effect of different temperatures (25–45 °C). A full 23 factorial plan with three replicates at the central point was used to optimize the process. The impacts of process conditions on cell development are fundamental to optimize the process and make it applicable by the industry. The present study showed that the optimal conditions for the development of probiotic cells in filmogenic solutions are a combination of 1.0% gelatin with 4.0% inulin and fermentation temperature of 45 °C. It was observed that the maximum cell growth occurred in an estimated time of about 4 h of fermentation. L. salivarius cell production and substrate consumption during the fermentation of the filmogenic solution were well simulated by a model proposed in this article, with coefficients of determination of 0.981 (cell growth) and 0.991 (substrate consumption).
  • 关键词:fermentation; inulin; predictive modelling; probiotic fermentation ; inulin ; predictive modelling ; probiotic
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