Evaluation of volatile metabolites as potential markers to predict naturally-aged seed vigour by coupling rapid analytical profiling techniques with chemometrics

Tingting Zhang; Charfedinne Ayed; Ian D Fisk; Tong Pan; Jianhua Wang; Ni Yang; Qun Sun

doi:10.1016/j.foodchem.2021.130760

Evaluation of volatile metabolites as potential markers to predict naturally-aged seed vigour by coupling rapid analytical profiling techniques with chemometrics

Food Chem. 2022 Jan 15:367:130760. doi: 10.1016/j.foodchem.2021.130760. Epub 2021 Aug 3.

Authors

Tingting Zhang¹, Charfedinne Ayed², Ian D Fisk³, Tong Pan¹, Jianhua Wang¹, Ni Yang⁴, Qun Sun⁵

Affiliations

¹ Department of Plant Genetics &Breeding and Seed Science, College of Agronomy and Biotechnology, China Agricultural University/Beijing Key Laboratory of Crop Genetic Improvement/The Innovation Center (Beijing) of Crop Seed Sciences Ministry of Agriculture, Beijing 100193, PR China.
² Division of Food, Nutrition and Dietetics, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough LE12 5RD, United Kingdom.
³ Division of Food, Nutrition and Dietetics, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough LE12 5RD, United Kingdom; The University of Adelaide, North Terrace, Adelaide, South Australia, Australia.
⁴ Division of Food, Nutrition and Dietetics, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough LE12 5RD, United Kingdom. Electronic address: Ni.Yang@nottingham.ac.uk.
⁵ Department of Plant Genetics &Breeding and Seed Science, College of Agronomy and Biotechnology, China Agricultural University/Beijing Key Laboratory of Crop Genetic Improvement/The Innovation Center (Beijing) of Crop Seed Sciences Ministry of Agriculture, Beijing 100193, PR China. Electronic address: sunqun@cau.edu.cn.

PMID: 34390911
DOI: 10.1016/j.foodchem.2021.130760

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) modelswere 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.

Keywords: Artificial ageing; Chemometrics; Gas chromatography – ion mobility spectrometry; Natural ageing; Seed vigour.

MeSH terms

Gas Chromatography-Mass Spectrometry
Ion Mobility Spectrometry
Least-Squares Analysis
Seeds / chemistry
Volatile Organic Compounds* / analysis

Substances

Volatile Organic Compounds