Evaluation of volatile metabolites as potential markers to predict naturally-aged seed vigour by coupling rapid analytical profiling techniques with chemometrics. (15th January 2022)

• Record Type: Journal Article
• Authors: Zhang, Tingting; Ayed, Charfedinne; Fisk, Ian D.; Pan, Tong; Wang, Jianhua; Yang, Ni; Sun, Qun
• Is Part Of: Food chemistry. Volume 367(2022)
• Publication Date: 2022-01-15
• Subjects: Seed vigour -- Natural ageing -- Artificial ageing -- Gas chromatography – ion mobility spectrometry -- Chemometrics; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2021.130760
• Languages: English
• ISSNs: 0308-8146

Abstract

Highlights: Practical ability of AA-based models was tested by NA data for the first time. Differences between the VOCs of seeds during NA and AA were revealed. GC-IMS provided better data to couple with chemometrics to predict seed vigour than E-nose. Benzaldehyde M, n -nonanal and 1-butanol M were key GC-IMS markers of seed vigour. An optimal model (GC-IMS-AS-PCC-VIP-PLS-R) was developed. 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 (R 2 p 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.