Prediction of Milk Powder Raman Spectra and Ammonium Sulfate Adulteration Concentration Based on Neural Network Model
DOI:
https://doi.org/10.54097/mvv4ng30Keywords:
milk powder, ammonium sulfate, Raman spectroscopy technique, BP neural network model.Abstract
This article aims to explore the changes in Raman spectra of milk powder when different concentrations of ammonium sulfate are adulterated. By conducting neural network tests on milk powder samples with different ammonium sulfate concentrations, we studied the impact of ammonium sulfate adulteration on milk powder. The research results show that moderate concentrations of ammonium sulfate adulteration can improve the solubility and flowability of milk powder, but high concentrations of adulteration may reduce the protein content of milk powder and have negative effects on its sensory quality and safety, causing significant adverse effects on human health. Therefore, the adulteration concentration of ammonium sulfate should be strictly controlled in the production and processing of milk powder to ensure its quality and safety.
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