Estimating the sensory qualities of tomatoes using visible and near-infrared spectroscopy and interpretation based on gas chromatography-mass spectrometry metabolomics.
Informative wavelengths
Intercorrelations
Metabolites
Partial least squares regression
Principal component analysis
Selectivity ratio
Sensory attributes
Journal
Food chemistry
ISSN: 1873-7072
Titre abrégé: Food Chem
Pays: England
ID NLM: 7702639
Informations de publication
Date de publication:
01 May 2021
01 May 2021
Historique:
received:
15
07
2020
revised:
30
09
2020
accepted:
20
10
2020
pubmed:
3
11
2020
medline:
24
2
2021
entrez:
2
11
2020
Statut:
ppublish
Résumé
The ability to estimate the sensory quality of intact tomatoes rapidly and non-destructively using visible and near-infrared spectroscopy (Vis-NIRS) is important for the tomato industry. In this study, a combination of partial least squares regression (PLSR) analysis and the stepwise selectivity ratio (SWSR) method was used to study the ability of Vis-NIRS to predict 19 sensory attributes in intact tomatoes. The PLSR models constructed based on the informative wavelengths selected by the SWSR method predicted 8 sensory attributes well, particularly the sweetness attribute (correlation coefficient of validation of 0.92). Moreover, based on the tomato metabolites determined by GC-MS analysis, high intercorrelations between sensory attributes, metabolites, and the selected informative wavelengths were found through principal component analysis, as well as the high correlation coefficients between them. The results confirm the feasibility and reliability of Vis-NIRS and the informative wavelengths selected by SWSR to predict the sensory quality of whole tomatoes.
Identifiants
pubmed: 33131961
pii: S0308-8146(20)32332-3
doi: 10.1016/j.foodchem.2020.128470
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
128470Informations de copyright
Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.