Analysis of adulterated milk based on a long short-term memory network

被引：0
|
作者：
Li, Xin [1 ]
Liu, Jiangping [1 ,2 ]
机构：
[1] Inner Mongolia Agr Univ, Coll Comp & Informat Engn, Hohhot, Peoples R China
[2] Inner Mongolia Autonomous Reg Key Lab Big Data Res, Hohhot, Peoples R China
来源：
SPECTROSCOPY LETTERS | 2023年 / 56卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Adulteration; hyperspectral; long short-term memory; milk; principal component analysis;
D O I：
10.1080/00387010.2023.2194950
中图分类号：
O433 [光谱学];
学科分类号：
0703 ; 070302 ;
摘要：
Taking adulterated milk as the research object, the principal component analysis method combined with long short-term memory network was used to study, aiming to find a simple and efficient rapid detection method for adulterated milk. In this paper, qualitative and quantitative analysis of adulterated milk was carried out based on near-infrared hyperspectral data (400-1000 nm). The experimental results verified the feasibility of using near-infrared hyperspectral technology to identify adulterated milk.
引用
收藏
页码：204 / 210
页数：7
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