The interaction between lipid oxidation and the Maillard reaction model of lysine-glucose on aroma formation in fragrant sesame oil

美拉德反应 化学 芳香 脂质氧化 芝麻油 褐变 风味 食品科学 自动氧化 抗氧化剂 气味 芝麻酚 己醛 有机化学 园艺 生物 芝麻
作者
Beibei Hu,Wenting Yin,Heng-bo Zhang,Zhuo-qing Zhai,Hua‐Min Liu,Xue‐De Wang
出处
期刊:Food Research International [Elsevier BV]
卷期号:186: 114397-114397 被引量:44
标识
DOI:10.1016/j.foodres.2024.114397
摘要

The formation mechanism behind the sophisticated aromas of sesame oil (SO) has not been elucidated. The interaction effects of the Maillard reaction (MR) and lipid oxidation on the aroma formation of fragrant sesame oil were investigated in model reaction systems made of l-lysine (Lys) and d-glucose (Glc) with or without fresh SO (FSO) or oxidized SO (OSO). The addition of OSO to the Lys-Glc model increased the MR browning at 294 nm and 420 nm and enhanced the DPPH radical scavenging activity greater than the addition of FSO (p < 0.05). The presence of lysine and glucose inhibited the oxidation of sesame oil, reduced the loss of γ-tocopherol, and facilitated the formation of sesamol (p < 0.05). The Maillard-lipid interaction led to the increased concentrations of some of the alkylpyrazines, alkylfurans, and MR-derived ketones and acids (p < 0.05) while reducing the concentrations of other pyrazines, lipid-derived furans, aliphatic aldehydes, ketones, alcohols, and acids (p < 0.05). The addition of FSO to the MR model enhanced the characteristic roasted, nutty, sweet, and fatty aromas in sesame oil (p < 0.05), while excessive lipid oxidation (OSO) brought about an unpleasant oxidized odor and reduced the characteristic aromas. This study helps to understand the sophisticated aroma formation mechanism in sesame oil and provides scientific instruction for precise flavor control in the production of sesame oil.
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
lili发布了新的文献求助10
刚刚
Jasen发布了新的文献求助10
1秒前
领导范儿应助科研通管家采纳,获得10
1秒前
1秒前
追寻天菱应助科研通管家采纳,获得10
1秒前
Kao应助科研通管家采纳,获得10
1秒前
亚蛋求学完成签到,获得积分10
1秒前
1秒前
Kao应助科研通管家采纳,获得10
1秒前
gxy完成签到,获得积分10
2秒前
无花果应助科研通管家采纳,获得10
2秒前
顺利的紫槐完成签到,获得积分10
2秒前
hh完成签到,获得积分10
2秒前
Menand发布了新的文献求助30
2秒前
传奇3应助科研通管家采纳,获得10
2秒前
缓慢的夜山完成签到 ,获得积分10
2秒前
4秒前
传奇3应助bc采纳,获得10
5秒前
NN应助无心的可仁采纳,获得10
6秒前
Jxw完成签到,获得积分10
6秒前
季思锐发布了新的文献求助10
6秒前
cheesejiang完成签到,获得积分10
7秒前
汪青青发布了新的文献求助10
7秒前
Ava应助az采纳,获得10
8秒前
Charlene发布了新的文献求助10
9秒前
9秒前
9秒前
11秒前
moonli完成签到,获得积分10
11秒前
虚心的乘云完成签到,获得积分10
11秒前
汉堡包应助ohooo采纳,获得10
12秒前
WeirLiu发布了新的文献求助10
13秒前
LittleTT发布了新的文献求助10
13秒前
酷波er应助伶俐春天采纳,获得10
13秒前
充电宝应助幽默毛衣采纳,获得10
16秒前
田文文完成签到,获得积分10
16秒前
16秒前
英俊的铭应助季思锐采纳,获得10
17秒前
迷人雁蓉完成签到,获得积分10
17秒前
18秒前
高分求助中
(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
The anomeric effect 1314
Principles of town planning: translating concepts to applications 1000
1 Peter and Christ's Descent to the Dead in Its Early Christian Reception 700
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
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 7734367
求助须知:如何正确求助?哪些是违规求助? 9284753
关于积分的说明 20166698
捐赠科研通 7312240
什么是DOI,文献DOI怎么找? 3304642
关于科研通互助平台的介绍 2457279
邀请新用户注册赠送积分活动 2313831