您好，欢迎访问新疆畜牧科学院 机构知识库！

Rapid detection and quantification of melamine, urea, sucrose, water, and milk powder adulteration in pasteurized milk using Fourier transform infrared (FTIR) spectroscopy coupled with modern statistical machine learning algorithms

文献类型： 外文期刊

作者： Chu, Chu 1 ; Wang, Haitong 1 ; Luo, Xuelu 1 ; Fan, Yikai 1 ; Nan, Liangkang 1 ; Du, Chao 1 ; Gao, Dengying 1 ; Wen, Peipei 1 ; Wang, Dongwei 1 ; Yang, Zhuo 1 ; Yang, Guochang 1 ; Liu, Li 1 ; Li, Yongqing 1 ; Hu, Bo 2 ; Zunongjiang, Abula 2 ; Zhang, Shujun 1 ;

作者机构： 1.Huazhong Agr Univ, Key Lab Agr Anim Genet Breeding & Reprod, Minist Educ, Wuhan 430070, Peoples R China

2.Xinjiang Acad Anim Sci, Qual Stand Institue Anim Husb, Urumqi 830012, Xinjiang, Peoples R China

关键词： Pasteurized milk; Fourier transform infrared (FTIR) spectroscopy; Modern statistical machine learning algorithms; Adulteration

期刊名称：HELIYON （ 影响因子：3.4； 五年影响因子：3.9 ）

ISSN：

年卷期： 2024 年 10 卷 12 期

页码：

收录情况： SCI

摘要： There is an evident requirement for a rapid, efficient, and simple method to screen the authenticity of milk products in the market. Fourier transform infrared (FTIR) spectroscopy stands out as a promising solution. This work employed FTIR spectroscopy and modern statistical machine learning algorithms for the identification and quantification of pasteurized milk adulteration. Comparative results demonstrate modern statistical machine learning algorithms will improve the ability of FTIR spectroscopy to predict milk adulteration compared to partial least square (PLS). To discern the types of substances utilized in milk adulteration, a top-performing multiclassification model was established using multi-layer perceptron (MLP) algorithm, delivering an impressive prediction accuracy of 97.4 %. For quantification purposes, bayesian regularized neural networks (BRNN) provided the best results for the determination of both melamine, urea and milk powder adulteration, while extreme gradient boosting (XGB) and projection pursuit regression (PPR) gave better results in predicting sucrose and water adulteration levels, respectively. The regression models provided suitable predictive accuracy with the ratio of performance to deviation (RPD) values higher than 3. The proposed methodology proved to be a cost-effective and fast tool for screening the authenticity of pasteurized milk in the market.

  • 相关文献
作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：新疆畜牧科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台