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<p>The potential adulteration of shiitake powder through the incorporation of low-cost mushroom powder or stipe powder in varying proportions was investigated in this study. The detection of such adulteration was performed using a combination of near-infrared (NIR) spectroscopy and chemometric techniques. Various spectral data types and wavelength bands were meticulously analyzed using chemometric methods. For adulterated samples of shiitake pileus and shiitake powder, linear discriminant analysis (LDA) and partial least squares (PLS) regression were employed to develop models for qualitative identification and quantitative analysis using NIR data. The LDA model demonstrated 100% prediction accuracy in validation sets after removal of overlapping wavelength bands and preprocessing of raw data using multiplicative signal correction (MSC), confirming its efficacy in qualitatively distinguishing shiitake pileus powder from adulterated variants. Furthermore, the PLS quantitative model for adulterated shiitake pileus powder was established utilizing full-wavelength bands and MSC, revealing a strong linear correlation between powder content and NIR spectral absorption. These results indicate that adulterant content in shiitake powder can be quantitatively determined. The proposed method has significant potential for the rapid identification of contaminated shiitake powder, as it does not require expensive equipment or extensive sample processing.</p>

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Detection of Shiitake powder adulteration using near-infrared spectroscopy combined with chemometrics

  • 期刊论文

  • 发表日期：

    2025年12月12日

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  • Xiaowei Tie,
  • Wei Zhang,
  • Zhenxing Wu,
  • Kunxiu Sun,
  • Xiting Hu,
  • Tingna Liang,
  • Ning Lv,
  • Steven Suryoprabowo,
  • Hongwei Zhang,
  • Yahui Guo,
  • Weirong Yao

摘要

The potential adulteration of shiitake powder through the incorporation of low-cost mushroom powder or stipe powder in varying proportions was investigated in this study. The detection of such adulteration was performed using a combination of near-infrared (NIR) spectroscopy and chemometric techniques. Various spectral data types and wavelength bands were meticulously analyzed using chemometric methods. For adulterated samples of shiitake pileus and shiitake powder, linear discriminant analysis (LDA) and partial least squares (PLS) regression were employed to develop models for qualitative identification and quantitative analysis using NIR data. The LDA model demonstrated 100% prediction accuracy in validation sets after removal of overlapping wavelength bands and preprocessing of raw data using multiplicative signal correction (MSC), confirming its efficacy in qualitatively distinguishing shiitake pileus powder from adulterated variants. Furthermore, the PLS quantitative model for adulterated shiitake pileus powder was established utilizing full-wavelength bands and MSC, revealing a strong linear correlation between powder content and NIR spectral absorption. These results indicate that adulterant content in shiitake powder can be quantitatively determined. The proposed method has significant potential for the rapid identification of contaminated shiitake powder, as it does not require expensive equipment or extensive sample processing.