Optimization of a cryoprotective medium for infant formula probiotic applications using response surface methodology

Abstract

The paper focuses on the development of a cryoprotective drying medium suitable for the application of probiotics in infant formulae. Response surface methodology was used to optimize the concentrations of skim milk and prebiotics for maximizing the survival of the probiotic Bifidobacterium lactis DSM 10140 during freeze-drying. The optimal combination was found to be 15.0% skim milk blended with 3.4% prebiotics, which protected viability in 62.16% of cells. There was no significant difference (p>0.05) between the experimental and predicted values, thereby verifying the model adequacy. The stability of the freezedried cells in the optimal combination of drying medium was examined under different conditions of rehydration and storage and in a simulated gastrointestinal tract model. The results showed that optimized drying medium could increase the viability of freeze-dried stationary phase cells by 1.34 log (CFU/ml) as compared to phosphate buffer after 120 days of storage at 4°C. However, with increasing temperature to 25°C, the protective effect of the optimized medium was more obvious. The optimized drying medium was also able to reduce the mortality rate of cells after sequential incubation under simulated infantile gastrointestinal conditions, including gastric conditions (pH 3.0 and 4.0, 90 min) and intestinal conditions (pH 7.5, 5 h) by 1.24 and 0.57 log (CFU/ml), respectively, compared to the control.

Effects of Persian gum and gum Arabic on the survival of Lactobacillus plantarum PTCC 1896, Escherichia coli, Xanthomonas axonopodis, and Saccharomyces cerevisiae during freeze drying

“…The plates were then incubated. Survival percent was expressed as N/N i ×100, in which N was defined as log 10 CFU ml −1 after freeze drying and N i was defined as log 10 CFU ml −1 before freeze drying (Peighambardoust et al, 2011;Shamekhi et al, 2011).…”

Encapsulación de Alimentos Probióticos mediante Liofilización en Presencia de Prebióticos

“…La tecnología de liofilización permite la encapsulación de materiales biológicos al reducir la velocidad de las reacciones químicas y la degradación por calor (Strasser et al, 2009;Semyonov et al, 2010). Se han reportado muchos factores como responsables de la supervivencia microbiana durante y después del liofilizado, entre ellos, la especie bacteriana, el estado fisiológico, la densidad celular, efecto de protectores (Shamekhi et al, 2012), tasas de congelación y otros parámetros de proceso, así como la rehidratación (Kearney et al, 2009;Shamekhi et al, 2012). El efecto de estos parámetros puede causar daño celular, reducción de la viabilidad y actividad microbiana en varios grados, induciendo a cambios en el estado físico de la membrana lipídica y la estructura de las proteínas (Strasser et al, 2009) Resultados de investigaciones muestran que además de la técnica de encapsulación, el efecto de protección depende en gran medida de las propiedades funcionales del material pared.…”

“…Adicionalmente, para incrementar la viabilidad de los probióticos durante la encapsulación por liofilización, el almacenamiento y subsecuentemente el paso a través del tracto gastrointestinal, se adicionan agentes crioprotectoctores (sacáridos y polioles) y otros solutos compatibles como el adonitol, la betaina, el glicerol y la leche en polvo (Shamekhi et al, 2012). La presente investigación contribuye al estudio y aplicación de la tecnología de liofilización en la encapsulación de las cepas probióticas con agentes prebióticos como material pared para su aplicación posterior en matrices alimenticias con características funcionales.…”

Optimization of Protective Agents for The Freeze-Drying of Paenibacillus polymyxa Kp10 as a Potential Biofungicide

“…There was a 9.68% chance that lack of fit value could happen because of noise. In determining the fitness of the model, the model must have the significance of the model (p < 0.05) and the insignificance of the lack of fit (p > 0.05) [34]. Fitness between the development model and experimental data can be determined based on the coefficient value (R 2 ).…”