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<p>Timber adulteration, illegal harvesting, and logging of legally protected timber species are a major threat to biodiversity. Identifying and differentiating low-value timber species from high-grade ones is a prerequisite to combat timber-related crimes. Timber adulteration can be detected by techniques such as DNA barcoding. However, these techniques have some drawbacks as they are time-consuming and destructive. To address all these issues, in this study, a quick and non-destructive approach has been used to detect timber adulteration by identifying and discriminating selective timber species using vibrational spectroscopy along chemometric methods such as principal component analysis (PCA), linear discriminant analysis (LDA), and partial least square discriminant analysis (PLS-DA) that successfully differentiated <i>Tectona grandis</i> (teak) from <i>Magnolia champaca</i> (champ) with 96.25% accuracy, <i>Swietenia macrophylla</i> (mahogany) from <i>Magnolia champaca</i> with 97.5% accuracy, and <i>Artocarpus heterophyllus</i> (Jack) from <i>Mangifera indica</i> (mango) with 100% PCA LDA training accuracies. Partial least square discriminant analysis successfully differentiated the timber species with 100% accuracy. ATR-FTIR spectroscopy and chemometric tools proved to be effective in detecting timber adulteration, which will help the investigating agencies combat timber-related crimes.</p>

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A quick and non-destructive approach to combat timber adulteration using attenuated total reflectance Fourier transform infrared spectroscopy and chemometrics

  • 期刊论文

  • 发表日期：

    2025年2月21日

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  • Arti Yadav,
  • Chongtham Nimi,
  • Manish Kapoor,
  • Rajinder Singh

摘要

Timber adulteration, illegal harvesting, and logging of legally protected timber species are a major threat to biodiversity. Identifying and differentiating low-value timber species from high-grade ones is a prerequisite to combat timber-related crimes. Timber adulteration can be detected by techniques such as DNA barcoding. However, these techniques have some drawbacks as they are time-consuming and destructive. To address all these issues, in this study, a quick and non-destructive approach has been used to detect timber adulteration by identifying and discriminating selective timber species using vibrational spectroscopy along chemometric methods such as principal component analysis (PCA), linear discriminant analysis (LDA), and partial least square discriminant analysis (PLS-DA) that successfully differentiated Tectona grandis (teak) from Magnolia champaca (champ) with 96.25% accuracy, Swietenia macrophylla (mahogany) from Magnolia champaca with 97.5% accuracy, and Artocarpus heterophyllus (Jack) from Mangifera indica (mango) with 100% PCA LDA training accuracies. Partial least square discriminant analysis successfully differentiated the timber species with 100% accuracy. ATR-FTIR spectroscopy and chemometric tools proved to be effective in detecting timber adulteration, which will help the investigating agencies combat timber-related crimes.