L-proline enrichment of bread enhances its KFO: Assessment of freshness by electronic nose technology and an ANN prediction model

Abstract

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.

Keywords

• Freshness-enhanced bread
• 2-Acetyl-1-pyrroline
• Fuzzy logic
• Electronic nose
• Mahalanobis distance
• ANN