Search

Abstract An antioxidant-rich mushroom noodles (gluten-free) rich in L-tryptophan-serotonin-melatonin (TSM) was developed under minimal processing condition(s) without perturbing the natural antioxidant synergy. In vitro release kinetics studies in a standard dissolution apparatus confirmed substantial releases of the target biomolecules from the designer noodles in simulated salivary buffer (SSB), simulated gastric buffer (SGB), simulated intestinal buffer (SIB) and simulated rectal buffer (SRB). Post model fitting, it was evident that L-tryptophan and serotonin followed zero order release kinetics in SSB; while melatonin followed first order release kinetics in SSB and SRB, respectively. However, all the three biomolecules followed Korsmeyer’s- Peppas model kinetics in SGB and SIB; L-tryptophan and serotonin also followed the same release kinetics model in SRB. The in vivo bioavailabilities of these molecules were ascertained through feeding trials (of mushroom noodles) in male Sprague Dawley rats. An enhancement of ~ 95%, 20% and 44% of L-tryptophan, serotonin and melatonin, respectively, occurred in rat blood serum after 30 min of consumption of the designer noodles and decreased 50 min onwards. However, the natural trends of increase and decrease in serum serotonin and melatonin concentrations during different time of the day remained unaltered. These bioavailable molecules also increased insulin sensitivity in the liver and glucose uptake in the brain, as revealed by iHOMA2 prediction modelling. The findings of these investigations have the potential to inform this designer noodles to be a truly antioxidant-rich functional food product which holds promise in providing molecular nutrition, especially for populations with serotonin-melatonin deficiency.

Freshness-aroma or sweet “popcorn”- like aroma of white bread was enhanced by increasing the formation of 2-acetyl-1-pyrroline (2-AP), a key food odorant by addition of its precursor molecule, viz. L-proline (1.2% w/w) to the bread-dough. Overall sensorial acceptability scores, physico-chemical properties, aroma and freshness-stability were all significantly (p < 0.05) enhanced in bread; while the acrylamide content was concomitantly reduced consequent to this amino acid enrichment. Employment of hurdle technology resulted in a 4-fold enhanced freshness-stability of bread (E-7 with 1.2% L-proline added) vis-à-vis the experimental control and commercially available bread samples. In this investigation, electronic nose along with artificial neural network (ANN) was employed to effectively discriminate the test sample (E-7) from the experimental control ones with respect to freshness-stability, for a large number of sample sets. The optimum topology (ANN network) of 8-15-5 rapidly and accurately predicted the shelf-life of E-7, with high correlation (R2 = 0.9785) between the predicted and experimental values. Mahalanobis distance method was adopted to determine ‘freshness index’ of bread by correlating it with its 2-AP content (quantified by gas chromatography) which allowed unambiguous-cum-rapid prediction of this freshness molecular marker in the bread samples during storage. We envisage that ANN coupled with e-nose technology would allow rapid-cum-accurate detection of freshness status of bread for bakery industries forgoing invasive, time-intensive, conventional biochemical analysis.