Tingting Zhang
Evaluation of volatile metabolites as potential markers to predict naturally-aged seed vigour by coupling rapid analytical profiling techniques with chemometrics
Zhang, Tingting; Ayed, Charfedinne; Fisk, Ian D.; Pan, Tong; Wang, Jianhua; Yang, Ni; Sun, Qun
Authors
Charfedinne Ayed
Professor IAN FISK IAN.FISK@NOTTINGHAM.AC.UK
PROFESSOR OF FLAVOUR SCIENCE
Tong Pan
Jianhua Wang
Dr NI YANG NI.YANG@NOTTINGHAM.AC.UK
ASSOCIATE PROFESSOR
Qun Sun
Abstract
Rapid volatile detection methods for seed vigour rely heavily on artificial ageing (AA), however the comparability of volatile organic compounds (VOCs) to natural ageing (NA) and practicability of the detection models were not well known. In this study, VOCs between AA and NA sweet corn seeds were compared and Partial Least Squares Regression (PLS-R) models were constructed based on AA to predict the seed vigour of NA. A total of 33 VOCs were identified, among which aldehydes showed the highest consistency between NA and AA. Furthermore, a AS-PLS-R model with variable importance in projection (VIP > 1) and Pearson Correlation Coefficient (r > 0.9) algorithms, which was built on 3 volatile markers: benzaldehyde monomer, n-nonanal, 1-butanol monomer, achieved the best performance (R2p of 0.901 and RMSEP of 0.050). Therefore, coupling Gas Chromatography- Ion Mobility Spectrometry (GC-IMS) with chemometrics can be an effective way to monitor and predict stored seeds vigour.
Citation
Zhang, T., Ayed, C., Fisk, I. D., Pan, T., Wang, J., Yang, N., & Sun, Q. (2022). Evaluation of volatile metabolites as potential markers to predict naturally-aged seed vigour by coupling rapid analytical profiling techniques with chemometrics. Food Chemistry, 367, Article 130760. https://doi.org/10.1016/j.foodchem.2021.130760
Journal Article Type | Article |
---|---|
Acceptance Date | Aug 1, 2021 |
Online Publication Date | Aug 3, 2021 |
Publication Date | Jan 15, 2022 |
Deposit Date | Aug 9, 2021 |
Publicly Available Date | Aug 12, 2021 |
Journal | Food Chemistry |
Print ISSN | 0308-8146 |
Electronic ISSN | 1873-7072 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 367 |
Article Number | 130760 |
DOI | https://doi.org/10.1016/j.foodchem.2021.130760 |
Keywords | General Medicine; Food Science; Analytical Chemistry |
Public URL | https://nottingham-repository.worktribe.com/output/6009051 |
Publisher URL | https://www.sciencedirect.com/science/article/pii/S0308814621017660?via%3Dihub |
Files
1-s2.0-S0308814621017660-main
(2.2 Mb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by-nc-nd/4.0/
You might also like
Oyster Mushroom Growth Stage Identification: An Exploration of Computer Vision Technologies
(2023)
Presentation / Conference Contribution
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search