Issue 56, 2021

Use of metabolomics data analysis to identify fruit quality markers enhanced by the application of an aminopolysaccharide

Abstract

Chitosan is a biostimulator that has a great effect either on plant physiology, productivity, or fruit quality. However, the metabolic mechanism regulated by chitosan still remains unknown. Untargeted metabolomics analysis, using LC-MS/MS mass spectrometry, was used to investigate fruit quality markers. Thus, this study was focused on the identification of untargeted metabolites of tomato fruits produced under the application of five doses of chitosan at different concentrations (0, 0.25, 0.50, 0.75, and 1 mg ml−1) that was extracted from Parapenaeus longirostris shrimp shells. The identification was carried out using two ion modes (ESI/ESI+), a web application “Metfamily” to analyze signals, and reference libraries. The analysis of data using partial least squares discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA) showed that chitosan application, especially 0.75 mg ml−1, had a clear and remarkable effect regarding the number of metabolite families identified in both ion modes. This treatment has increased the relative abundance of many metabolites that belong to anthocyanins decorated with sugars, terpenoids, phenylpropanoids, acylsugars, glucosinolates, folates, galactolipids, fatty acids, and phospholipids. Thus, these results showed that chitosan application increased the quality of tomato fruits due to its involvement in the regulation of many metabolic pathways that might be responsible for enhancing the nutritional characteristics as well as the defense of fruits.

Graphical abstract: Use of metabolomics data analysis to identify fruit quality markers enhanced by the application of an aminopolysaccharide

Supplementary files

Article information

Article type
Paper
Submitted
02 Aug 2021
Accepted
25 Oct 2021
First published
03 Nov 2021
This article is Open Access
Creative Commons BY license

RSC Adv., 2021,11, 35514-35524

Use of metabolomics data analysis to identify fruit quality markers enhanced by the application of an aminopolysaccharide

E. A. Fatima, T. Moha, W. Said, M. Abdelilah and R. Mohammed, RSC Adv., 2021, 11, 35514 DOI: 10.1039/D1RA05865G

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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