Seasonal variation of metabolites in Kimchi cabbage: utilizing metabolomics based machine learning for cultivation season and taste discrimination

초록

"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 for taste and quality differentiation in kimchi cabbage based on the season of cultivation. Three regression models, including Orthogonal Partial Least Squares regression (OPLS), Partial Least Squares (PLS) regression, and Random Forest regression, were employed to predict seasonal variation. The models exhibited high accuracy, with R2 values ranging from 0.77 to 0.95, indicating their potential for distinguishing seasonal differences. Notably, hydroxyglucobrassicin, 5-oxoproline, and inositol consistently emerged as significant metabolites across all models. Additionally, we developed regression models for predicting sweetness and bitterness in kimchi cabbage. Metabolites such as malic acid, fructose, and glucose were positively correlated with sweetness, while neoglucobrassicin and glucobrassicin were negatively correlated. Conversely, metabolites like glucoerucin and glucobrassicin were positively correlated with bitterness, while malic acid and sucrose were negatively correlated. These findings provide a valuable foundation for understanding the metabolic basis of taste variation in kimchi cabbage and offer practical applications for improving kimchi production quality. By incorporating more varieties and multi-year data, future research aims to develop even more accurate predictive models for kimchi cabbage taste and quality, ultimately contributing to the consistency of kimchi production. Graphical Abstract: (Figure presented.) © The Author(s) 2024.

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