Characterizing the Flavor Precursors and Liberation Mechanisms of Various Dry-Aging Methods in Cull Beef Loins Using Metabolomics and Microbiome Approaches

Derico Setyabrata, Kelly Vierck, Tessa R. Sheets, Jerrad F. Legako, Bruce R. Cooper, Timothy A. Johnson, Yuan H. Brad Kim

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

The objective of this study was to characterize and compare the dry-aging flavor precursors and their liberation mechanisms in beef aged with different methods. Thirteen paired loins were collected at 5 days postmortem, divided into four sections, and randomly assigned into four aging methods (wet-aging (WA), conventional dry-aging (DA), dry-aging in a water-permeable bag (DWA), and UV-light dry-aging (UDA)). All sections were aged for 28 days at 2 C, 65% RH, and a 0.8 m/s airflow before trimming and sample collection for chemical, metabolomics, and microbiome analyses. Higher concentrations of free amino acids and reducing sugars were observed in all dry-aging samples (p < 0.05). Similarly, metabolomics revealed greater short-chain peptides in the dry-aged beef (p < 0.05). The DWA samples had an increase in polyunsaturated free fatty acids (C18:2trans, C18:3n3, C20:2, and C20:5; p < 0.05) along with higher volatile compound concentrations compared to other aging methods (aldehyde, nonanal, octanal, octanol, and carbon disulfide; p < 0.05). Microbiome profiling identified a clear separation in beta diversity between dry and wet aging methods. The Pseudomonas spp. are the most prominent bacterial species in dry-aged meat, potentially contributing to the greater accumulation of flavor precursor concentrations in addition to the dehydration process during the dry-aging. Minor microbial species involvement, such as Bacillus spp., could potentially liberate unique and potent flavor precursors.

Original languageEnglish
Article number472
JournalMetabolites
Volume12
Issue number6
DOIs
StatePublished - Jun 2022

Keywords

  • amino acids
  • cull cow
  • dry-aging
  • metabolomics
  • microbiome
  • reducing sugars
  • volatile compounds

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