Abstract
Abstract Postmortem aging is one of the most extensively adopted post-harvest processing practices. Aging is a natural process to ensure the establishment of palatability through the action of endogenous proteolytic systems in fresh muscle. Over the years, Dr. Kim’s group have identified key factors that affect the rate and extent of postmortem aging impacts on meat quality and proposed a novel “Smart-aging” system. Smart-aging is a conceptual system for the development of readily applicable template aging strategies to improve meat quality and value. Dr. Kim’s laboratory has determined that aging can be further optimized through identifying specific post-harvest aging parameters. Coupled with using novel metabolomics techniques, Dr. Kim’s group has elucidated the biochemical mechanism underpinning muscle-specific aging responses to color and oxidative stability as well as tenderness and flavor developments of fresh meats. For example, dry-aging is a traditional century-old process, where carcass side or subprimals with no protective packaging materials are stored in a cold environment for several weeks to months. Through dry-aging, unique dry-aging flavor is generated, but specific flavor compounds and liberation mechanisms associated with dry-aged flavor have not been fully understood. Dr. Kim’s laboratory identified key metabolites associated with dry-aged flavor of beef loins. They further demonstrated that dry-aging under an optimized condition results in significant improvements of flavor and consumer acceptability of beef through the generation of flavor-related metabolites. Concurrently, Dr. Kim’s laboratory works on identifying key molecules in fresh meat samples that can be used for the future development of simple marker-based detection systems for establishing optimal Smart-aging practices. While having its own set of limitations, metabolomics is a tool that has a great deal of potential in the future of muscle food research. This presentation will give a brief overview of metabolomics technologies, highlighting novel areas of research and seeking to identify research gaps and future directions for metabolomics applications in meat science.
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