|LIU, ZHIHAO - University Of Maryland|
|SUN, JIANGHAO - Ohio University|
|TENG, ZI - University Of Maryland|
|Luo, Yaguang - Sunny|
|YU, LIANGLI - University Of Maryland|
Submitted to: Postharvest Biology and Technology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/9/2021
Publication Date: 6/19/2021
Citation: Liu, Z., Sun, J., Teng, Z., Luo, Y., Yu, L., Simko, I., Chen, P. 2021. Identification of Marker Compounds for Predicting Browning of Fresh-cut Lettuce Using Untargeted UHPLC-HRMS. Postharvest Biology and Technology. https://doi.org/10.1016/j.postharvbio.2021.111626.
Interpretive Summary: Lettuce (Lactuca sativa) is one of the most cultivated and consumed leafy crops around the world. After cutting, enzymatic browning that occurs on the lettuce cut edges reduces the shelf- life and consumer acceptance. Metabolite composition of lettuce could be affected by the browning process. Metabolomics offers a powerful tool to study global changes in the entire metabolite set using LC-MS combined with multivariate statistical analysis. In this project untargeted metabolomics study has been investigated to identify metabolites which could be used as marker compounds of the tissue browning susceptibility after cutting in different lettuce accessions. The identified metabolites would be applied to select the most desirable accessions both for industrial commercial production and breeding programs.
Technical Abstract: Enzymatic browning negatively impacts product quality and shelf-life of packaged fresh-cut lettuce. Metabolite profiles of lettuce are affected by the browning process. The purpose of this study was to identify metabolomic marker compounds to predict lettuce browning, which could be applied to discern accessions suited for commercial production and industrial breeding programs. Romaine lettuce with different browning susceptibilities were evaluated in two independent trials and growing seasons. Metabolites were analyzed using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS). Principal component analysis (PCA) was performed to visualize clusters, trends, and discriminative ion features. Seven metabolites, including quinic acid, caffeoylquinic acid, 3-hydroxytetradecanedioic, cichorioside B, 8-deacetylmatricarin-8-sulfate, dicaffeoylquinic acid and 9S,12S,13S-trihydroxy-10Z-octadecenoic acid, were positively correlated with browning. Three metabolites, including lactucopicrin-15-oxalate, tri-4-hydroxyphenylacetyl glucoside and 15-deoxylactucin-8-sulfate, were negatively correlated with browning. Two additional phenolic metabolites, dicaffeoyltartaric and caffeoyltartaric acids, were identified as potential marker compounds, whose presence on day 0 samples immediately after cutting was negatively correlated with browning development (represented by 'Hue). The identified metabolites help to elucidate the biochemical metabolism and pathways during enzymatic browning and have the potential to serve as marker compounds for predicting browning resistant accessions.