Seasonal variation of metabolites in Kimchi cabbage: utilizing metabolomics based machine learning for cultivation season and taste discrimination
WooChul Ju,
Sung Jin Park,
Min Jung Lee
et al.
Abstract:Kimchi cabbage, a staple in South Korean cuisine, exhibits taste variations depending on the season of cultivation, with significant implications for kimchi production quality. In this study, we conducted comprehensive metabolomic analyses of kimchi cabbage grown in diverse environments throughout the year. We identified 15 primary metabolites, 10 glucosinolates, and 12 hydrolysates, providing valuable insights into the metabolic composition of kimchi cabbage. Using this data, we developed predictive models fo… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.