Mathematical modelling of the effects of prebiotic concentration on lactobacillus casei growth

作者
V.S. Shankar Kumar,U.J. Anantharaj,M. Sakthioli,R. Vinnakota,Kamalanand Krishnamurthy
出处
期刊:International Journal of Infectious Diseases [Elsevier BV]
卷期号:45: 205-205 被引量:1
标识
DOI:10.1016/j.ijid.2016.02.470
摘要

Background: Probiotics are microorganisms that are beneficial to the human digestive system. Lactobacillus Casei is a beneficial probiotic bacterium present naturally in the human digestive system. Also, Lactobacillus Casei helps in treatment of several gastric disorders and in inhibiting the growth of Helicobacter Pyroli that causes gastro-intestinal ulcers. Prebiotics, in general, refers to substances that help in stimulating the growth of the beneficial probiotic bacteria. Further, the growth of probiotics is sustained by the optimized concentration of prebiotics. Methods & Materials: In this work, the growth of Lactobacillus Casei, in response to the prebiotic concentration is obtained experimentally. The growth curves of Lactobacillus Casei, in response to a 10% nutrient solution (10grams of milk powder in 100ml) was obtained using UV spectrophotometer (Model: UV 1800) under sterile laboratory conditions. The absorbance was measured at a wavelength of 600nm for a time period of 150 minutes. Further, using the measured data, the growth of Lactobacillus Casei in response to the nutrients was modeled using a mathematical modeling approach namely the transfer function model. Results: Results demonstrate that the developed model is efficient in capturing the dynamics of Lactobacillus Casei growth, with an accuracy of 88.81%. Further, by analyzing the model, it was found that the growth of Lactobacillus Casei is stable. Hence, the model can be efficiently used to develop suitable control systems for sustaining the growth of Lactobacillus Casei. Conclusion: This work appears to be of high clinical and industrial importance since Lactobacillus Casei helps in treatment of several gastric disorders and the development of mathematical models of probiotic growth is highly useful for mass production of probiotics.

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