Analysis of volatile compound changes in fried shallot (Allium cepa L. var. aggregatum) oil at different frying temperatures by GC–MS, OAV, and multivariate analysis. (30th May 2021)

• Record Type: Journal Article
• Authors: Tian, Peng; Zhan, Ping; Tian, Honglei; Wang, Peng; Lu, Cong; Zhao, Yu; Ni, Ruijie; Zhang, Yuyu
• Is Part Of: Food chemistry. Volume 345(2021)
• Publication Date: 2021-05-30
• Subjects: FSO fried shallot-flavored oil -- FSO1-5 represent shallot oil at 90 °C 110 °C 130 °C 150 °C and 170 °C respectively -- GC–MS gas chromatography-mass spectrometry -- PCA principal component analysis -- OPLS-DA orthogonal partial least-square analysis -- MR Maillard reaction -- SDE simultaneous distillation extraction -- OAVs Odor Activity Values -- RI retention indices -- GC-O gas chromatography–olfactometry -- DF detection frequency; Fried shallot oil (FSO) -- GC–MS -- Odor Activity Values (OAVs) -- Principal Component Analysis (PCA) -- Orthogonal partial least squares analysis (OPLS-DA) -- Classification; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2020.128748
• Languages: English
• ISSNs: 0308-8146

Abstract

Graphical abstract: Highlights: Aroma profiles of fried shallot oil (FSO) at different temperatures were studied. GC–MS, multivariate analysis and aroma recombination were used in the study. Omission test indicated that 5 volatiles had significant effects on FSO aroma. Abstract: Flavor is a key attribute of fried oil that shows a critical correlation with temperature. Therefore, selecting the appropriate temperature is important in preparing fried shallot oil (FSO). Volatile compounds from five different FSOs were identified and comparatively studied using gas chromatography-mass spectrometry (GC–MS) coupled with multivariate data analysis, including principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). GC–MS results identified a total of 93 volatiles, among which aldehydes, alcohols, pyrazines, and sulfur-containing compounds were the major compounds. Eighteen compounds had odor active values (OAV) >1. Among the compounds, hexanal, (E)-2-heptenal, (E)-2-octenal, dipropyl disulfide, 2-ethyl-3, 5-dimethylpyrazine, and 1-octen-3-ol were important to the overall aroma profile of FSOs. In the PCA model, all the detected FSOs were divided into three clusters, which were assigned as cluster A (FSO5), B (FSO4), and C (the rest FSOs). Multivariate data analyses revealed that nonanal, 2-ethyl-5-methylpyrazine, (E, E)-2, 4-decadienal, (E)-2-heptenal, and hexanal contributed positively to the classification of different FSOs. GC–MS coupled with multivariate data analysis could be used as a convenient and efficient analytical method to classify raw materials.