基于智能光谱传感技术的乳制品掺杂快速筛查
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- 英文论文题名：New Insight into Screening of Adulteration in Dairy Products Using Smart Spectroscopy Sensors
- 论文作者：黄志轩 ; 宗婧 ; 谭棕 ; 韩汐 ; 李奇峰 ; 陈达
- 英文论文作者：Zhixuan Huang ; Jing Zong ; Zong Tan ; Xi Han ; Qifeng Li ; Da Chen ; School of Precision Instrument and Opto-Electronics Engineering ; Tianjin University
- 年：2016
- 作者机构：天津大学精密仪器仪器与光电子工程学院;
- 论文关键词：乳制品打假 ; 智能光谱传感 ; 深度学习 ; 化学计量学
- 会议召开时间：2016-07-01
- 会议录名称：中国化学会第30届学术年会摘要集-第二十五分会：化学信息学与化学计量学
- 语种：中文
- 分类号：TS252.7;O657.3
- 学会代码：ZGHY
- 会议名称：中国化学会第30届学术年会-第二十五分会 ; 化学信息学与化学计量学
- 会议地点：中国辽宁大连
- 主办单位：中国化学会
- 学会名称：中国化学会
- 页数：1
- 文件大小：142k
- 原文格式：D
- 会议级别：全国
摘要
乳制品掺杂问题作为我国食品安全的突出矛盾之一,已引起全社会的高度关注。针对乳制品掺杂对象的高度不确定性,高效整合相关光谱传感技术及化学计量学方法,实现乳制品危害因子及重点掺杂对象的快速准确筛查。论文遵循现代检测流程,从样品前处理、无损检测、信息解析等关键点上进行多点突破,并引入深度学习等新算法以促进筛查技术的智能化。在此基础上,引入大数据分析技术及刑侦情报技术,将乳制品造假个案中的线索、证据叠加在一起,串联出一条完整的线索链,实现典型食品掺杂事件的串并案分析,进而精准识别造假源头,从人证、物证自洽的角度为乳制品打假提供有力线索。
The problem of illegal additives in milk represents is one of the prominent contradictions that affect the food safety of China,attracting the great concern of whole society.Our work is centered on the development of smart spectroscopy sensors for efficient screening of hazard factors and typical adulteration objects in dairy products,thus generating an efficient smart spectroscopy system.The system involves groundbreaking innovations ranging from sample preparation,nondestructive testing and signal processing,combining with deep learning algorithm to promote the intelligence of the developed system.We tests and refines the smart spectroscopy system by drawing upon the systematic analysis of different adulterated dairy products to yield challenges representative of those encountered in common situations,and then integrated the clues and evidence presented in the adulterated dairy products into a reasonable clue chain using the criminal investigation methodology.This would provide a promising tool for identification of fraud sources.
The problem of illegal additives in milk represents is one of the prominent contradictions that affect the food safety of China,attracting the great concern of whole society.Our work is centered on the development of smart spectroscopy sensors for efficient screening of hazard factors and typical adulteration objects in dairy products,thus generating an efficient smart spectroscopy system.The system involves groundbreaking innovations ranging from sample preparation,nondestructive testing and signal processing,combining with deep learning algorithm to promote the intelligence of the developed system.We tests and refines the smart spectroscopy system by drawing upon the systematic analysis of different adulterated dairy products to yield challenges representative of those encountered in common situations,and then integrated the clues and evidence presented in the adulterated dairy products into a reasonable clue chain using the criminal investigation methodology.This would provide a promising tool for identification of fraud sources.
引文
[1]Yunker J.;Still T.;Lohr A.Nature,2011,426:787.
[2]Yang Z.;Tian C;Kubota C.Nat.Biotech.,2007,25:77.
[2]Yang Z.;Tian C;Kubota C.Nat.Biotech.,2007,25:77.