Artificial intelligence and food flavor: How AI models are shaping the future and revolutionary technologies for flavor food development

风味 计算机科学 产品(数学) 食品工业 生物技术 生化工程 数据科学 食品科学 工程类 化学 数学 生物 几何学
作者
Zhiyong Cui,Chong Qi,Tianxing Zhou,Yanyang Yu,Yueming Wang,Zhiwei Zhang,Yin Zhang,Wenli Wang,Yuan Liu
出处
期刊:Comprehensive Reviews in Food Science and Food Safety [Wiley]
卷期号:24 (1): e70068-e70068 被引量:60
标识
DOI:10.1111/1541-4337.70068
摘要

The food flavor science, traditionally reliant on experimental methods, is now entering a promising era with the help of artificial intelligence (AI). By integrating existing technologies with AI, researchers can explore and develop new flavor substances in a digital environment, saving time and resources. More and more research will use AI and big data to enhance product flavor, improve product quality, meet consumer needs, and drive the industry toward a smarter and more sustainable future. In this review, we elaborate on the mechanisms of flavor recognition and their potential impact on nutritional regulation. With the increase of data accumulation and the development of internet information technology, food flavor databases and food ingredient databases have made great progress. These databases provide detailed information on the nutritional content, flavor molecules, and chemical properties of various food compounds, providing valuable data support for the rapid evaluation of flavor components and the construction of screening technology. With the popularization of AI in various fields, the field of food flavor has also ushered in new development opportunities. This review explores the mechanisms of flavor recognition and the role of AI in enhancing food flavor analysis through high-throughput omics data and screening technologies. AI algorithms offer a pathway to scientifically improve product formulations, thereby enhancing flavor and customized meals. Furthermore, it discusses the safety challenges of integrating AI into the food flavor industry.
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
亲亲应助vivi采纳,获得10
刚刚
冷艳冥茗发布了新的文献求助30
2秒前
2秒前
4秒前
SciGPT应助畅快的书雪采纳,获得10
4秒前
早睡早起发布了新的文献求助10
4秒前
zll发布了新的文献求助10
6秒前
CodeCraft应助独钓寒江雪采纳,获得10
6秒前
sqq完成签到 ,获得积分10
7秒前
7秒前
菜鸟完成签到,获得积分10
7秒前
8秒前
HJJHJH应助美满的访旋采纳,获得30
9秒前
在水一方应助小巧的不评采纳,获得30
9秒前
9秒前
10秒前
月亮河发布了新的文献求助20
11秒前
小居居完成签到,获得积分10
12秒前
悦己发布了新的文献求助10
13秒前
13秒前
14秒前
14秒前
完美世界应助伶俐一曲采纳,获得10
16秒前
16秒前
爆米花应助火星上的新晴采纳,获得10
17秒前
18秒前
orixero应助Lynn采纳,获得10
18秒前
19秒前
19秒前
lulu发布了新的文献求助10
19秒前
20秒前
ding应助张朋朋采纳,获得10
22秒前
ASA发布了新的文献求助10
23秒前
sky发布了新的文献求助10
24秒前
爆米花应助dolor采纳,获得10
24秒前
畅快的书雪完成签到,获得积分10
26秒前
昭昭发布了新的文献求助10
26秒前
乐乐应助渴望者采纳,获得10
27秒前
长安宁完成签到 ,获得积分10
29秒前
伶俐一曲发布了新的文献求助10
32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
APA handbook of comparative psychology: Basic concepts, methods, neural substrate, and behavior 1000
Health Psychology 1000
全员动态考核,锚定高质量发展:读懂同济大学教师人事改革新政的深层价值 900
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
Römisch-Germanische Forschungen 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 7596613
求助须知:如何正确求助?哪些是违规求助? 9173005
关于积分的说明 19637727
捐赠科研通 7173800
什么是DOI,文献DOI怎么找? 3268045
关于科研通互助平台的介绍 2432760
邀请新用户注册赠送积分活动 2261245