| Autor: |
Yadav, Arti, Sharma, Sweety, Singh, Vaibhav, Kapoor, Manish, Singh, Rajinder |
| Předmět: |
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| Zdroj: |
Frontiers in Analytical Science; 2024, p1-12, 12p |
| Abstrakt: |
Identifying an unascertained timber species is essential to stop illegal logging of the protected species. Timber forensics involves the identification of an unknown timber species to link to its source or to authenticate the timber and its products. This paper anticipates a quick, robust, non-destructive, and environment-friendly proof-of-concept study using ATR-FTIR spectroscopy and chemometric interpretation to identify and discriminate economically important and legitimately protected timber species. The chemometric methods used included partial least square discriminant analysis (PLS-DA), principal component analysis (PCA), and linear discriminant analysis (LDA). The mid-IR spectral bands indicated the presence of timber constituents such as cellulose, lignin, and hemicellulose. PLS-DA successfully discriminated between hardwoods and softwoods with 100% accuracy. PCA-LDA analysis of softwoods and hardwoods was done separately. LDA for softwoods resulted in a training and validation accuracy of 87.5%. Similarly, LDA analysis of hardwoods showed 82.22% training and 80% validation accuracies. The results of the blind test showed that all the blind samples could be correctly identified using this approach with 100% accuracy. All these approaches delivered significant findings to identify and discriminate timber samples. It is believed that this study will offer great opportunities to withstand illegal logging quickly and non-destructively. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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