Skip to main content
Log in

Lipidomic Profiling to Assess the Freshness of Stored Cabbage

  • Published:
Food Analytical Methods Aims and scope Submit manuscript

Abstract

The quantitative freshness assessment method for vegetables is desired to upgrade the quality management system in agricultural distribution chain. Since lipid has broad diversity in species and plays an important role in the biological metabolism of plants, there is a possibility that lipid profile indicates the freshness of harvested vegetables. The aims of this study were to clarify the lipidomic alteration of stored cabbage and identify lipid molecules indicative of freshness. Cabbage leaves stored at 5 °C, 10 °C, and 20 °C were sampled periodically for lipidomic analysis by liquid chromatography-tandem mass spectrometry. The cumulative respiratory CO2 production was determined using a flow-through method via gas chromatography. A total of 74 lipid species had a significant correlation with cumulative CO2 production. Hierarchical cluster analysis (HCA) clustered them into three main groups. A partial least squares regression (PLSR) model established the relationship between the abundance of lipid species and the cumulative CO2 production. Four lipid molecules were selected as potential freshness markers. The PLSR model with the selected markers had a better performance in predicting the cumulative CO2 production than that by ascorbic acid which is conventionally used as a quality indicator of fresh produce. Our results show that lipidomic profiling could be viable for assessing the freshness of whole cabbage.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

Download references

Funding

This work was supported by Cabinet Office, Government of Japan, Cross-ministerial Strategic Innovation Promotion Program (SIP), “Technologies for Smart Bio-industry and Agriculture” (funding agency: Bio-oriented Technology Research Advancement Institution, NARO), and JSPS KAKENHI Grant Number 16H02581 and 22H0389.

Author information

Authors and Affiliations

Authors

Contributions

Putri Wulandari Zainal: Investigation, Formal analysis, Software, Writing—original draft. Daimon Syukri: Methodology, Investigation. Khandra Fahmy: Writing—review & editing. Teppei Imaizumi: Formal analysis. Manasikan Thammawong: Formal analysis. Mizuki Tsuta: Software, Writing—review & editing. Masayasu Nagata: Writing—review & editing. Kohei Nakano: Conceptualization, Methodology, Supervision, Writing—review & editing, Funding acquisition.

Corresponding author

Correspondence to Kohei Nakano.

Ethics declarations

Ethics Approval

This study does not involve usage of sample related to human participants or animals.

Consent to Participate

Not applicable.

Conflict of Interest

Putri Wulandari Zainal declares that she has no conflict of interest. Daimon Syukri declares that he has no conflict of interest. Khandra Fahmy declares that he has no conflict of interest. Teppei Imaizumi declares that he has no conflict of interest. Manasikan Thammawong declares that she has no conflict of interest. Mizuki Tsuta declares that he has no conflict of interest. Masayasu Nagata declares that he has no conflict of interest. Kohei Nakano declares that he has no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 247 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zainal, P.W., Syukri, D., Fahmy, K. et al. Lipidomic Profiling to Assess the Freshness of Stored Cabbage. Food Anal. Methods 16, 304–317 (2023). https://doi.org/10.1007/s12161-022-02422-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12161-022-02422-z

Keywords

Navigation