Identification of volatile organic compounds in muscle tissues of different species based on Headspace-Gas-Chromatography Ion-Mobility spectrometry

离子迁移光谱法 气相色谱-质谱法 化学 色谱法 气相色谱法 水煮 动物种类 质谱法 生物 动物 野生动物 生态学
作者
Xue‐bo Li,Chenghao Guo,Yinghua Qi,Wenhui Lu,Guoyan Xu,Ben-you Wang,Dian-bin Zhang,Shushan Zhao,Ming-xia Ding
出处
期刊:Legal Medicine [Elsevier BV]
卷期号:59: 102132-102132 被引量:1
标识
DOI:10.1016/j.legalmed.2022.102132
摘要

Species identification of unknown biological samples is crucial for forensic applications, especially in cases of explosion, disaster accidents, and body mutilation after murdering, as well as poaching, illegal trade in endangered animals, and meat food fraud. In this study, we identified 60 volatile organic compounds (VOCs) in fresh skeletal muscle tissues of seven different animal species (cattle, sheep, pigs, rabbits, rats, chickens and carp) and a human dead body by headspace-gas-chromatography ion-mobility spectrometry (HS-GC-IMS), and compared their differences by retention time, drift time and molecular weight. The results showed that these VOCs formed different gallery plot fingerprints in the skeletal muscle tissues of the human dead body and seven animal species. Principal component analysis (PCA) showed significantly different fingerprints between these species, and these fingerprints maintained good stability between the species and within the same species. Some VOCs have high species specificity, while VOCs of human fresh muscle tissues from different individual sources have little difference, demonstrating that all tested muscle tissue samples could be distinguished based on different VOCs. HS-GC-IMS has proved to be a rapid, high-throughput, highly sensitive and specific species identification method, which can be used for forensic species identification in criminal cases and disaster accidents, as well as detection in the field of food safety, such as meat fraud and adulteration.

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
彭于晏应助lijiuyi采纳,获得10
刚刚
风中访蕊完成签到 ,获得积分10
刚刚
1秒前
忐忑的草丛完成签到,获得积分10
2秒前
3秒前
3秒前
4秒前
4秒前
4秒前
5秒前
5秒前
一行白鹭上青天完成签到 ,获得积分0
5秒前
5秒前
5秒前
5秒前
6秒前
6秒前
Joaquin完成签到,获得积分10
6秒前
6秒前
量子星尘发布了新的文献求助10
6秒前
鲲鹏完成签到 ,获得积分10
6秒前
6秒前
6秒前
7秒前
7秒前
8秒前
8秒前
8秒前
8秒前
8秒前
i2stay完成签到,获得积分0
9秒前
9秒前
djbj2022发布了新的文献求助50
10秒前
czr完成签到,获得积分10
10秒前
niko发布了新的文献求助10
10秒前
niko发布了新的文献求助10
10秒前
niko发布了新的文献求助10
11秒前
niko发布了新的文献求助10
11秒前
niko发布了新的文献求助10
11秒前
niko发布了新的文献求助10
11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
Aerospace Standards Index - 2026 ASIN2026 3000
Polymorphism and polytypism in crystals 1000
Signals, Systems, and Signal Processing 610
Discrete-Time Signals and Systems 610
Research Methods for Business: A Skill Building Approach, 9th Edition 500
Social Work and Social Welfare: An Invitation(7th Edition) 410
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6051347
求助须知:如何正确求助?哪些是违规求助? 7859369
关于积分的说明 16267666
捐赠科研通 5196401
什么是DOI,文献DOI怎么找? 2780606
邀请新用户注册赠送积分活动 1763550
关于科研通互助平台的介绍 1645569