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Quantitative analysis of BPO additive in flour via Raman hyperspectral imaging technology

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Abstract

Raman hyperspectral imaging technology not only can acquire the image information of the sample; it also contains the Raman spectra information about each pixel. Due to the abundant information that the method provides, it has been applied to detect food safety. This study adopted line-scan Raman hyperspectral technology to quantify benzoyl peroxide (BPO) additive in flour. By analyzing the Raman spectra of BPO and flour, the 999 cm−1 Raman peak was selected for the detection and identification of BPO in flour. Savitzky–Golay filter and adaptive iteratively reweighted penalized least squares (airPLS) methods were used to de-noise and fluorescence correction of the original Raman signals. Binary image was established by 999 cm−1 single-band correction image and threshold segmentation, and this method was used to detect 11 mixture samples with different BPO additive concentrations. The results show that the BPO additives in the mixture samples can be detected, and the detected BPO pixels had a good linear relationship with the concentration of BPO in the mixture samples, correlation coefficient was 0.9902. The above results indicated that the method established in this paper can be applied to non-destructive quantitative detection of BPO additive in flour.

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Acknowledgements

This work was supported by Young Scientist Fund of National Natural Science Foundation of China (No. 61605009), Beijing Nova program (No. Z161100004916076) and Beijing Municipal Organization Department talents project (No. 2015000021223ZK40).

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Authors and Affiliations

  1. Beijing Research Center of Intelligent Equipment for Agriculture, Beijing, 100097, China

    Xiaobin Wang, Wenqian Huang, Chunjiang Zhao, Qingyan Wang, Chen Liu & Guiyan Yang

  2. National Research Center of Intelligent Equipment for Agriculture, Beijing, 100097, China

    Xiaobin Wang, Wenqian Huang, Chunjiang Zhao, Qingyan Wang, Chen Liu & Guiyan Yang

  3. Key Laboratory of Agri-informatics, Ministry of Agriculture, Beijing, 100097, China

    Xiaobin Wang, Wenqian Huang, Chunjiang Zhao, Qingyan Wang, Chen Liu & Guiyan Yang

  4. Beijing Key Laboratory of Intelligent Equipment Technology for Agriculture, Beijing, 100097, China

    Xiaobin Wang, Wenqian Huang, Chunjiang Zhao, Qingyan Wang, Chen Liu & Guiyan Yang

  5. College of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang, 110866, China

    Xiaobin Wang & Chunjiang Zhao

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  1. Xiaobin Wang
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  2. Wenqian Huang
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  3. Chunjiang Zhao
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  4. Qingyan Wang
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Correspondence to Wenqian Huang.

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Wang, X., Huang, W., Zhao, C. et al. Quantitative analysis of BPO additive in flour via Raman hyperspectral imaging technology. Eur Food Res Technol 243, 2265–2273 (2017). https://doi.org/10.1007/s00217-017-2928-9

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  • DOI: https://doi.org/10.1007/s00217-017-2928-9

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