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Review
. 2025 Jan 9;30(2):239.
doi: 10.3390/molecules30020239.

Technology for the Quantitative Identification of Dairy Products Based on Raman Spectroscopy, Chemometrics, and Machine Learning

Zheng-Yong Zhang  1 , Jian-Sheng Su  1 , Huan-Ming Xiong  2
Affiliations
Review

Technology for the Quantitative Identification of Dairy Products Based on Raman Spectroscopy, Chemometrics, and Machine Learning

Zheng-Yong Zhang et al. Molecules. .

Abstract

The technologies used for the characterization and quantitative analysis of dairy products based on Raman spectroscopy have developed rapidly in recent years. At the level of spectral data, there are not only traditional Raman spectra but also two-dimensional correlation spectra, which can provide rich compositional and characteristic information about the samples. In terms of spectral preprocessing, there are various methods, such as normalization, wavelet denoising, and feature extraction. A combination of these methods with appropriate quantitative techniques is beneficial to reveal the differences between samples or improve predictive performance. Quantitative evaluation can be divided into similarity measurement methods and machine learning algorithms. When evaluating small batch samples, similarity measurements can provide quantitative discrimination results. When the sample data are sufficient and matched with Raman spectroscopy parameters, machine learning algorithms suitable for intelligent discrimination can be trained and optimized. Finally, with the rise of deep learning algorithms and fusion strategies, some challenges in this field are proposed.

Keywords: Raman spectroscopy; chemometrics; dairy products; machine learning; quantitative identification.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Raman spectra of Nestle skim cow milk powder (a), Nestle whole cow milk powder (b), Meisu Jia’er infant milk powder (c), and Jiabeiaite infant goat milk powder (d) [30].
Figure 2
Figure 2
Two-dimensional correlation Raman spectra and three-dimensional images of cow milk (A) and goat milk powder (B) [30].
Figure 3
Figure 3
Original Raman spectra (A) and Raman spectra after mean normalization and wavelet denoising (B) of milk powder under different laser power conditions [39].
Figure 4
Figure 4
Schematic diagram of preprocessing process for Raman spectroscopy.
Figure 5
Figure 5
Discriminant analysis of dairy products based on similarity measurement [54].
Figure 6
Figure 6
Schematic diagram of spectral data fusion research.
See this image and copyright information in PMC

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