Revealing oxidative degradation of lipids and screening potential markers of four vegetable oils during thermal processing by pseudotargeted oxidative lipidomics

油菜籽 脂类学 食品科学 化学 植物油 大豆油 多不饱和脂肪酸 氧化磷酸化 棕榈油 降级(电信) 加热油 脂肪酸 生物化学 有机化学 计算机科学 电信
作者
Qian Hu,Jiukai Zhang,Lei He,Liyang Wei,Ranran Xing,Ning Yu,Wensheng Huang,Ying Chen
出处
期刊:Food Research International [Elsevier BV]
卷期号:175: 113725-113725 被引量:20
标识
DOI:10.1016/j.foodres.2023.113725
摘要

The oxidative degradation of lipids in vegetable oils during thermal processing may present a risk to human health. However, not much is known about the evolution of lipids and their non-volatile derivatives in vegetable oils under different thermal processing conditions. In the present study, a pseudotargeted oxidative lipidomics approach was developed and the evolution of lipids and their non-volatile derivatives in palm oil, rapeseed oil, soybean oil, and flaxseed oil under different thermal processing conditions was investigated. The results showed that thermal processing resulted in the oxidative degradation of TGs in vegetable oils, which generated oxTGs, DGs, and FFAs, as well as TGs with smaller molecular weights. The lower the fatty acid saturation, the more severe the oxidative degradation of vegetable oils and thermal processing at high temperatures should be avoided if possible. From the accumulation of oxTGs concentrations, the hazards during thermal processing at high temperatures were, in descending order, soybean oil, rapeseed oil, flaxseed oil, and palm oil. The non-volatile potential markers were screened in palm oil, rapeseed oil, soybean oil, and flaxseed oil for 1, 7, 5, and 2 markers related to thermal processing time, respectively. The study provided suggestions for the consumption of vegetable oils from multiple perspectives and identified markers for monitored oxidative degradation of vegetable oils.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
隐形曼青应助两张采纳,获得10
2秒前
王洪超发布了新的文献求助10
3秒前
老子就是杀猪的完成签到,获得积分10
5秒前
wudi发布了新的文献求助10
6秒前
qing完成签到,获得积分10
7秒前
8秒前
9秒前
提前退休完成签到,获得积分10
10秒前
ding应助草上飞采纳,获得10
12秒前
张欢馨应助王洪超采纳,获得10
12秒前
本尼脸上褶子完成签到 ,获得积分10
13秒前
小叶轻舟发布了新的文献求助10
14秒前
14秒前
14秒前
阿格雷完成签到,获得积分10
17秒前
wanci应助xuan采纳,获得10
18秒前
myway完成签到,获得积分10
18秒前
陈智涵发布了新的文献求助10
20秒前
初景应助科研通管家采纳,获得20
20秒前
pengyingni完成签到,获得积分10
20秒前
20秒前
molihuakai应助科研通管家采纳,获得10
21秒前
21秒前
pluto应助科研通管家采纳,获得10
21秒前
NCEPUHIT应助科研通管家采纳,获得10
21秒前
21秒前
今后应助科研通管家采纳,获得10
22秒前
今后应助科研通管家采纳,获得10
22秒前
molihuakai应助科研通管家采纳,获得10
22秒前
baitou完成签到,获得积分10
28秒前
11222完成签到,获得积分10
28秒前
29秒前
29秒前
myway发布了新的文献求助10
29秒前
ding应助成功的院士采纳,获得10
30秒前
30秒前
洁白的白白完成签到,获得积分10
32秒前
ljy完成签到 ,获得积分10
32秒前
Lin完成签到,获得积分10
33秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
How to Use Machine Learning in Chemistry: An Introduction 1000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7583651
求助须知:如何正确求助?哪些是违规求助? 9162345
关于积分的说明 19606805
捐赠科研通 7165660
什么是DOI,文献DOI怎么找? 3266302
关于科研通互助平台的介绍 2431200
邀请新用户注册赠送积分活动 2257779