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脂肪酸,多和挥发性物质作为冷压油稳定性的预测生物标志物
Tobias Pointner1,2, Philipp Steinlechner1, Marc Pignitter1
1Department of Physiological Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria.
Food chemistry: X
|February 23, 2026
概括
冷压油的氧化恶化最好使用多个生物标志物进行跟踪. 关键指标包括脂肪酸降解和特定的挥发性化物,多也表明了早期的变化.
科学领域:
- 食品化学 食品化学
- 分析化学 分析化学
- 生物化学 生物化学
背景情况:
- 冷压油富含多不和脂肪酸 (PUFA) 和多.
- 这些油容易氧化降解,影响质量和保质期.
研究的目的:
- 为了确定冷压油中氧化恶化的油类特定生物标志物.
- 评估基于机器学习的多标记方法的有效性,以评估氧化稳定性.
主要方法:
- 对6种冷压油 (黑,焦油,向日,高油脂向日,亚麻,大麻) 的分析,储存了6个月.
- 使用气体染色学-火焰电离检测 (GC-FID),液体染色学-双重质谱学 (LC-MS/MS) 和固相微提取气体染色学-质谱学 (SPME-GC-MS).
- 采用机器学习技术 (LASSO,RFR) 和相关性分析来识别生物标志物.
主要成果:
- 脂肪酸 (烯酸和α-烯酸) 的降解是氧化的主要驱动因素.
- 挥发性化物 (六,2,4-十, (E) 2-非) 被确定为关键的二次标记物.
- 聚醇 (酸,黄酸,酸) 显示油类型依赖的耗尽,酸作为早期阶段标记物.
结论:
- 冷压油的氧化稳定性最好通过多标志物方法来描述.
- 该研究提供了一种系统的方法来识别特定于石油的恶化生物标志物.
- 机器学习集成增强了全面氧化稳定性指标的识别.
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