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  • Volatile profile of elderberry juice: Effect of lactic acid fermentation using L. plantarum, L. rhamnosus and L. casei strains
  • Add time:09/08/2019         Source:sciencedirect.com

    In this study we explored, for the first time, the lactic acid fermentation of elderberry juice (EJ). A total of 15 strains isolated from dairy and plant matrices, belonging to L. plantarum, L. rhamnosus and L. casei, were used for fermentations. The volatile profile of started and unstarted EJ was characterized by HS-SPME/GC-MS technique after 48 h of fermentation and 12 days of storage at 4 °C. All L. plantarum and L. rhamnosus strains exhibited a good capacity of growth while not all L. casei strains showed the same ability. The aromatic profile of fermented juices was characterized by the presence of 82 volatile compounds pertaining to different classes: alcohols, terpenes and norisoprenoids, organic acids, ketones and esters. Elderberry juice fermented with L. plantarum strains showed an increase of total volatile compounds after 48 h while the juices fermented with L. rhamnosus and L. casei exhibited a larger increase after the storage. The highest concentration of total volatile compounds were observed in EJ fermented with L. plantarum 285 isolated from dairy product. Ketones increased in all fermented juices both after fermentation and storage and the most concentrated were acetoin and diacetyl. The organic acids were also affected by lactic acid fermentation and the most abundant acids detected in fermented juices were acetic acid and isovaleric acid. Hexanol, 3-hexen-1-ol (Z) and 2-hexen-1-ol (E) were positively influenced during dairy lactic acid bacteria strains fermentation. The most represented esters were ethyl acetate, methyl isovalerate, isoamyl isovalerate and methyl salicylate, all correlated with fruit notes. Among terpenes and norisoprenoids, β-damascenone resulted the main representative with its typical note of elderberry. Furthermore, coupling obtained data with multivariate statistical analyses, as Principal Component Analysis (PCA) and Classification Trees (CT), it was possible to relate the characteristic volatile profile of samples with the different species and strains applied in this study.

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