Literature DB >> 30745065

Gas chromatography-mass spectrometry metabolomics-based prediction of potato tuber sprouting during long-term storage.

Tomohiko Fukuda1, Kiyofumi Takamatsu2, Takeshi Bamba3, Eiichiro Fukusaki4.   

Abstract

In order to supply potato (Solanum tuberosum L.) tubers for the processed food industry throughout the year, suppliers should provide consistent quality potatoes even after long-term storage. Despite being one of the most important foods, there is no simple way to control tuber quality and, in particular, controlling sprouting. Chemical suppression such as chlorpropham is used to inhibit sprouting, however, the regulatory status of such chemical inhibition differs in each country. Gas chromatography-mass spectrometry-based metabolomics was applied to identify the applicable biomarkers for prediction of potato sprouting during long-term storage. Sprouting was measured in chipping potatoes, and these were also subjected to metabolite profiling to develop a predictive model. The model was based on projections to latent structures (PLS) regression calculated from a metabolome data set obtained before storage and was consistent with actual measured sprouting values. Sucrose, phosphate, and amino acids were selected as valid contributing biomarkers for prediction in a validation field experiment. These biomarkers will contribute to the development of a successful novel method for prediction and control of potato tuber quality during long-term storage.
Copyright © 2019 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Gas chromatography–mass spectrometry; Metabolomics; Potato; Prediction; Sprouting; Storage

Mesh:

Substances:

Year:  2019        PMID: 30745065     DOI: 10.1016/j.jbiosc.2019.01.016

Source DB:  PubMed          Journal:  J Biosci Bioeng        ISSN: 1347-4421            Impact factor:   2.894


  2 in total

1.  Cold storage reveals distinct metabolic perturbations in processing and non-processing cultivars of potato (Solanum tuberosum L.).

Authors:  Sagar S Datir; Saleem Yousf; Shilpy Sharma; Mohit Kochle; Ameeta Ravikumar; Jeetender Chugh
Journal:  Sci Rep       Date:  2020-04-14       Impact factor: 4.379

2.  Metabolomic analysis of fibrotic mice combined with public RNA-Seq human lung data reveal potential diagnostic biomarker candidates for lung fibrosis.

Authors:  Yosui Nojima; Yoshito Takeda; Yohei Maeda; Takeshi Bamba; Eiichiro Fukusaki; Mari N Itoh; Kenji Mizuguchi; Atsushi Kumanogoh
Journal:  FEBS Open Bio       Date:  2020-10-05       Impact factor: 2.792

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.