Application and prospect of metabolomics-related technologies in food inspection

代谢组学 食品工业 鉴定(生物学) 食品安全 生化工程 食品加工 生物技术 食品科学 计算机科学 数据科学 化学 工程类 色谱法 生物 植物
作者
Jiazong Liu,Haipeng Zhao,Ziyi Yin,Hongyang Dong,Xiaomeng Chu,Xuanlin Meng,Yang Li,Xinhua Ding
出处
期刊:Food Research International [Elsevier BV]
卷期号:171: 113071-113071 被引量:15
标识
DOI:10.1016/j.foodres.2023.113071
摘要

Food inspection covers a broad range of topics, including nutrient analysis, food pollutants, food auxiliary materials, additives, and food sensory identification. The foundation of diverse subjects like food science, nutrition, health research, and the food industry, as well as the desired reference for drafting trade and food legislation, makes food inspection highly significant. Because of their high efficiency, sensitivity, and accuracy, instrumental analysis methods have gradually replaced conventional analytical methods as the primary means of food hygiene inspection. Metabolomics-based analysis technology, such as nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC–MS), liquid chromatography-mass spectrometry (LC-MS), and capillary electrophoresis–mass spectrometry (CE-MS), has become a widely used analytics platform. This research provides a bird's eye view of the application and future of metabolomics-related technologies in food inspection. We have provided a summary of the features and the application range of various metabolomics techniques, the strengths and weaknesses of different metabolomics platforms, and their implementation in specific inspection procedures. These procedures encompass the identification of endogenous metabolites, the detection of exogenous toxins and food additives, analysis of metabolite alterations during processing and storage, as well as the recognition of food adulteration. Despite the widespread utilization and significant contributions of metabolomics-based food inspection technologies, numerous challenges persist as the food industry advances and technology continues to improve. Thus, we anticipate addressing these potential issues in the future.
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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
热心的十二完成签到 ,获得积分10
1秒前
文迪完成签到,获得积分10
2秒前
3秒前
3秒前
5秒前
Ava应助拼搏的二哈采纳,获得10
5秒前
ZJH发布了新的文献求助10
6秒前
郭慧泉完成签到 ,获得积分10
6秒前
8秒前
鳄鱼不做饿梦完成签到,获得积分10
8秒前
kk发布了新的文献求助10
8秒前
胡说八道完成签到 ,获得积分10
10秒前
10秒前
11秒前
zzzzz完成签到,获得积分10
11秒前
情怀应助文静的麦片采纳,获得10
11秒前
12秒前
。。。发布了新的文献求助10
13秒前
逝水完成签到 ,获得积分10
14秒前
微笑子慧发布了新的文献求助10
16秒前
gezianhao完成签到,获得积分10
16秒前
HE发布了新的文献求助10
16秒前
香蕉觅云应助龙哥采纳,获得10
19秒前
朱先生完成签到,获得积分10
20秒前
孙福禄应助cultromics采纳,获得10
21秒前
Lucky完成签到,获得积分10
21秒前
一颗好困芽完成签到 ,获得积分10
24秒前
26秒前
ZJH完成签到,获得积分20
26秒前
Leukocyte完成签到 ,获得积分10
26秒前
wangke完成签到,获得积分10
29秒前
29秒前
29秒前
糟糕的小熊猫关注了科研通微信公众号
29秒前
暖暖完成签到,获得积分10
30秒前
KK发布了新的文献求助10
30秒前
英姑应助反向大笨钟采纳,获得10
31秒前
拼搏的二哈完成签到,获得积分10
33秒前
Youatpome发布了新的文献求助10
33秒前
35秒前
高分求助中
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
A new approach to the extrapolation of accelerated life test data 1000
Problems of point-blast theory 400
Indomethacinのヒトにおける経皮吸収 400
北师大毕业论文 基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 390
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3997687
求助须知:如何正确求助?哪些是违规求助? 3537226
关于积分的说明 11271044
捐赠科研通 3276377
什么是DOI,文献DOI怎么找? 1806965
邀请新用户注册赠送积分活动 883609
科研通“疑难数据库(出版商)”最低求助积分说明 809975