TITLE:
Development of acidophilus milk via selected probiotics & prebiotics using artificial neural network
AUTHORS:
Zeynab Raftaniamiri, Pratima Khandelwal, B. R. Aruna
KEYWORDS:
Synbiotic Acidophilus Milk; Artificial Neural Network; Sensory Evaluation
JOURNAL NAME:
Advances in Bioscience and Biotechnology,
Vol.1 No.3,
August
16,
2010
ABSTRACT: Commercial interest in functional foods containing probiotic strains has consistently increased due to the awareness of gut health. Recent advancements are leading to development of synbiotic foods, containing prebiotics and probiotics bearing synergistic effects of the two. Thus, in present study, synbiotic acido- philus milk was developed satisfying functional dairy food properties. Different sets of milk were fermented with probiotic cultures (Lactobacillus acidophilus, Bifidobacterium bifidum, Lactobacillus casei, bioyoghurt culture) singly or in combination, and prebiotics namely inulin (I), oat fibre (O) and honey (H). Obtained 20 synbiotic samples were organoleptically tested, physico-chemically (titrable acidity percentage (TA) & pH) and microbiologically (total viable count (TVC), coliform count and yeast & mold count) analyzed. The incorporation of honey and inulin led to development of sweetened and low calorie sweetened synbiotic acidophilus milk, respectively. Incorporation of B. bifidum increased the flavour of synbiotic acidophilus milk when compared to L. acidophilus as control, where as L. casei culture showed thinner consistency in the product. Addition of prebiotic affected only the sensory scores, whereas the probiotics addition resulted in a marginal variation of pH and TA. TVC of all synbiotic acidophilus milk samples obtained were more than desirable limits for harvesting probiotic effects (>10^10 cfu/ml). Finally, a two layer feed-forward artificial neural network (ANN) was established to predict the sensory evaluation based on inputs of probiotic and prebiotic.