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Brand Identification of Soybean Milk Powder based on Raman Spectroscopy Combined with Random Forest Algorithm

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Abstract

Raman spectroscopy can characterize the rich molecular vibration information of soybean milk powder samples, but difficulties arise in its direct use for sample classification and identification. Therefore, it is urgent to develop an intelligent identification technology based on Raman spectroscopy. For brand identification of soybean milk powder, this work investigates and discusses a variety of spectral processing technologies including wavelet denoising, normalization, principal component analysis, and the results show that appropriate spectral processing can improve the recognition accuracy of the random forest algorithm. Under the optimal conditions (db2 wavelet, normalization, principal component analysis, 30 decision trees), the best recognition effect of soybean milk brand identification can be achieved. The Raman spectral signal acquisition time of each sample is 40 s, and the spectra pretreatment and identification operation time only takes a few minutes. The analytical approach established in this paper has the advantages of convenient and fast Raman spectra acquisition, fast and accurate model identification.

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Funding

This research was financially supported by the Excellent Young Backbone Teachers of “Blue Project” in Jiangsu Universities in 2021, National Natural Science Foundation of China (nos. 61602217, 61806177, 91746202), and the Natural Science Foundation of Zhejiang Province (LQ20C200004).

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Authors and Affiliations

  1. School of Management Science and Engineering, Nanjing University of Finance and Economics, 210023, Nanjing, Jiangsu, The People’s Republic of China

    Zheng-Yong Zhang & Xiao-Jing Shi

  2. School of Management Engineering and Electronic Commerce, Zhejiang Gongshang University, 310018, Hangzhou, Zhejiang, The People’s Republic of China

    Ya-Ju Zhao, Yin-Sheng Zhang & Hai-Yan Wang

Authors
  1. Zheng-Yong Zhang
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  2. Xiao-Jing Shi
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  3. Ya-Ju Zhao
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  4. Yin-Sheng Zhang
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  5. Hai-Yan Wang
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Correspondence to Zheng-Yong Zhang.

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Zhang, ZY., Shi, XJ., Zhao, YJ. et al. Brand Identification of Soybean Milk Powder based on Raman Spectroscopy Combined with Random Forest Algorithm. J Anal Chem 77, 1282–1286 (2022). https://doi.org/10.1134/S1061934822100173

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