Artículo

Optimization of fermentation parameters to study the behavior of selected lactic cultures on soy solid state fermentation

Rodríguez de Olmos, Antonieta Icon; Bru Chauve, Elena Magdalena Icon; Garro, Marisa Selva Icon

Otros responsables

Fecha

2015-03-02

Editorial

Elsevier

Revista

International Journal of Food Microbiology

Título del libro

Nombre del evento

Fecha del evento

Institución organizadora

ISSN

0168-1605

eISSN

1879-3460

ISBN

Idioma

Inglés

Tipo del evento

Clasificación temática

Resumen

The use of solid fermentation substrate (SSF) has been appreciated by the demand for natural and healthy products. Lactic acid bacteria and bifidobacteria play a leading role in the production of novel functional foods and their behavior is practically unknown in these systems. Soy is an excellent substrate for the production of functional foods for their low cost and nutritional value. The aim of this work was to optimize different parameters involved in solid state fermentation (SSF) using selected lactic cultures to improve soybean substrate as a possible strategy for the elaboration of new soy food with enhanced functional and nutritional properties. Soy flour and selected lactic cultures were used under different conditions to optimize the soy SSF. The measured responses were bacterial growth, free amino acids and β-glucosidase activity, which were analyzed by applying response surface methodology. Based on the proposed statistical model, different fermentation conditions were raised by varying the moisture content (50?80%) of the soy substrate and temperature of incubation (31?43 °C). The effect of inoculum amount was also investigated. These studies demonstrated the ability of selected strains (Lactobacillus paracasei subsp. paracasei and Bifidobacterium longum) to grow with strain-dependent behavior on the SSF system. β-Glucosidase activity was evident in both strains and L. paracasei subsp. paracasei was able to increase the free amino acids at the end of fermentation under assayed conditions. The used statistical model has allowed the optimization of fermentation parameters on soy SSF by selected lactic strains. Besides, the possibility to work with lower initial bacterial amounts to obtain results with significant technological impact was demonstrated.

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