Predictive modeling of milk adulteration with urea content using the gray wolf optimization algorithm and long and short-term memory network model-Reference-Cited by-同舟云学术

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Predictive modeling of milk adulteration with urea content using the gray wolf optimization algorithm and long and short-term memory network model

Published:2024-04-08 Issue:4 Volume:57 Page:201-212
ISSN:0038-7010
Container-title:Spectroscopy Letters
language:en
Short-container-title:Spectroscopy Letters

Author:

Zhang Wenjing¹,Fu Kangle¹,Xue Heru¹,Liu Jiangping¹

Affiliation:

1. College of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot, China

Funder

Inner Mongolia Agricultural University Basic Discipline Scientific Research Startup Fund Project

Inner Mongolia University Basic Research Project

Inner Mongolia Natural Science Fund Project

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/00387010.2024.2331616

Reference29 articles.

1. Detection of Adulterants in Milk using Near Infrared Spectroscopy;Jha S.N.;Journal of Food Science and Technology,2004

2. Application of Infrared Spectrometry in the Determination of Melamine and Urea in Milk Powder;Jing B.;Food and Fermentation Industries,2020

3. Study of a Rapid In Situ Method for the Determination of Urea in Milk;Dan S.;Modern Scientific Instruments (in Chinese),2011

4. Inversion of True Protein Content in Milk based on Hyperspectral;Qianqian Z.;Spectroscopy and Spectral Analysis,2015

5. Principles and Applications of Hyperspectral Imaging Technology in Nondestructive Testing of Fruit and Vegetable Quality and Safety;Baohua Z.;Spectroscopy and Spectral Analysis,2014

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