Food Technology and Biotechnology (Jan 2010)

Modelling the Effect of Different Substrates and Temperature on the Growth and Lactic Acid Production by Lactobacillus amylovorus DSM 20531T in Batch Process

  • Antonija Trontel,
  • Vanda Baršić,
  • Anita Slavica,
  • Božidar Šantek,
  • Srđan Novak

Journal volume & issue
Vol. 48, no. 3
pp. 352 – 361

Abstract

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Amylolytic lactic acid bacterium Lactobacillus amylovorus DSM 20531T utilised glucose, sucrose and starch as a sole carbon and energy source. The three substrates were completely depleted from MRS medium during batch cultivations carried out in a laboratory scale stirred tank bioreactor at constant temperature (40 °C) and pH value (5.5). Under the tested conditions, the bacterium was capable of conducting simultaneously starch hydrolysis and fermentation. A mixture of two stereoisomers, D-(–)- and L-(+)-lactic acid, was produced in all cases by highly efficient homofermentative bioprocess with 0.93 to 1 g of lactate produced per g of total (consumed) substrate. The effect of temperature on the kinetics of cell growth and lactic acid production by the amylolytic strain in the starch-containing medium was also investigated. Efficient simultaneous saccharification and fermentation (SSF) was obtained at 35, 40 and 45 °C with completely degraded complex carbohydrate in 8 to 12 h and the product yield coefficient in the range from 0.91 to 0.93 g/g. Maximum values for substrate consumption rate (0.89 h^–1), maximum specific growth rate (0.87 h^–1), product formation rate (2.01 h^–1), and productivity of lactic acid (1.45 g/(L·h)) were obtained at 45 °C, while maximum biomass concentration (4.38 g/L) was attained at 40 °C. The ratio of the two stereoisomeric forms of produced lactic acid was strongly affected by the temperature. Unstructured kinetic model was used to describe the consumption of the three substrates, bacterial biomass formation and lactic acid production by L. amylovorus DSM 20531T. The dependence of biokinetic parameters on temperature was described by cardinal temperature model. The applied models successfully predicted all experimental data.

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