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. 2025 May 22:28:102577.
doi: 10.1016/j.fochx.2025.102577. eCollection 2025 May.

Integrative flavoromics-GC-MS/IMS approach to study the formation mechanism of fishy flavor in skipjack tuna oil induced by oxidation and heat

Affiliations

Integrative flavoromics-GC-MS/IMS approach to study the formation mechanism of fishy flavor in skipjack tuna oil induced by oxidation and heat

Xianling Lan et al. Food Chem X. .

Abstract

Skipjack tuna oil that is rich in polyunsaturated fatty acids, is prone to developing fishy odors under high-temperature or oxidative conditions. This study investigated the effects of four treatments-low-temperature thermal, low-concentration oxidation, high-concentration oxidation, and high-temperature thermal-on oxidation degree, volatile compounds, fatty acids, and sensory characteristics. GC-MS identified five key volatile compounds: hexadecanoic acid, ethyl ester; octadecanoic acid, ethyl ester; ethyl oleate; ethyl 9-hexadecenoate; and ethyl 6,9,12,15-octadecatetraenoate. Oxidation induction significantly increased peroxide value and acid value, primarily by generating aldehydes (e.g., hexanal, heptanal), which intensified fishy odors. In contrast, by GC-IMS analysis, higher concentrations of fishy odor markers, 1-octen-3-ol (0.48 ± 0.05 %), 2-ethylfuran-D (0.75 ± 0.01 %), and (E)-2-heptenal-D (0.08 ± 0 %) were found in the high temperature thermal group, showing a more pronounced impact of thermal induction on flavor dynamics than oxidative pathways. These findings elucidate the dual roles of oxidation and thermal degradation in fishy odor formation.

Keywords: Flavor deterioration; Oxidation induction; Skipjack tuna oil; Thermal induction.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
(A) Peroxide value, (B) acid price, (C) DPPH free radical scavenging capacity of skipjack tuna fish oil under four different treatment conditions, (D) DHA content, (E) EPA content, and (F) total unsaturated fatty acid content.
Fig. 2
Fig. 2
GC–MS variability analysis (A) wayne diagram, (B) principal component analysis plot, (C) clustering heat map, and (D) VIP score plot in PLS-DA.
Fig. 3
Fig. 3
GC-IMS variability analysis (A) gallery Plot fingerprint, (B) Distribution of different kinds of volatile substances in the samples, (C) 2D spectrogram, (D) 2D contrast spectrogram, and (E): Principal component analysis.
Fig. 4
Fig. 4
Visualization of correlation network based on very significant correlation between characteristic volatile aromatic compounds and sensory evaluation (p<0.01). (A) sensory score plot, (B) correlation analysis between sensory evaluation and GC-IMS, and (C) correlation analysis between sensory evaluation and GC–MS (Note: Blue nodes represent the six flavor characteristics for sensory evaluation, and red nodes represent the characteristic volatile aromatic compounds. Red and blue solid lines indicate positive and negative correlations, respectively. The line width is proportional to the correlation strength. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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