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Technology for the Quantitative Identification of Dairy Products Based on Raman Spectroscopy, Chemometrics, and
Zheng-Yong Zhang1, Jian-Sheng Su1, Huan-Ming Xiong2
1School of Management Science and Engineering, Nanjing University of Finance and Economics, Nanjing 210023, China.
Raman spectroscopy rapidly advances dairy product analysis using spectral data and preprocessing techniques. Advanced methods like machine learning and deep learning offer improved quantitative analysis and discrimination of dairy samples.
Area of Science:
- Analytical Chemistry
- Food Science
- Spectroscopy
Background:
- Raman spectroscopy technologies for dairy product characterization and quantitative analysis have seen rapid development.
- Spectral data now include traditional Raman spectra and two-dimensional correlation spectra, offering rich compositional information.
Purpose of the Study:
- To review and summarize recent advancements in Raman spectroscopy for dairy product analysis.
- To discuss various spectral preprocessing and quantitative evaluation methods.
- To highlight emerging trends and challenges in the field.
Main Methods:
- Utilizing traditional and two-dimensional correlation Raman spectra for analysis.
- Applying spectral preprocessing techniques like normalization, wavelet denoising, and feature extraction.
- Employing quantitative evaluation methods including similarity measurements and machine learning algorithms.
Main Results:
- Preprocessing methods combined with quantitative techniques enhance sample differentiation and predictive accuracy.
- Similarity measurements are effective for quantitative discrimination of small sample batches.
- Machine learning algorithms, especially deep learning, show promise for intelligent discrimination with sufficient data.
Conclusions:
- Raman spectroscopy offers powerful tools for dairy product analysis, with ongoing advancements in data processing and algorithms.
- The integration of advanced techniques like deep learning and data fusion presents future opportunities and challenges.
- Further research is needed to fully leverage these technologies for comprehensive dairy analysis.
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