Discrimination and evaluation Gentiana rigescens–Camellia sinensis with different planting year using Fourier transform infrared spectroscopy

Mi, Li-Ju; Zhang, Ji; Zhao, Yanli; Zuo, Zhiyan; Wang, Yuanzhong; Li, Fusheng

doi:10.1007/s10457-018-0216-8

Cited by 5 publications

(2 citation statements)

References 47 publications

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“…Thus, FTIR coupled with chemometrics is a valuable method for classifying trees and predicting the wood chemical composition. Through pattern recognition models like PLS-DA, it has been possible to identify timber wood species and wood procedures 17 , 28 , 29 . So, it can be used to address illegal wood traffic problems and to guarantee legal provenance of timber.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, alternative methods are required to speed up the process at a low cost. Fourier transform infrared spectroscopy (FTIR) is an analytical tool that addresses these problems because of its analysis speed, minimal or non-sample preparation, versatility, accuracy, non-destructiveness, and economic cost, and it requires small amounts of the sample [17][18][19] . Furthermore, FTIR enables the composition and structural characterization of molecules by providing information-rich spectra 18 , which allows the prediction of organic compounds (proteins, lipids, carbohydrates, and extractives [20][21][22][23] and classifies wood species [24][25][26] .…”

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confidence: 99%

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Classification of Amazonian fast-growing tree species and wood chemical determination by FTIR and multivariate analysis (PLS-DA, PLS)

Javier-Astete

Melo

Jimenez-Davalos

et al. 2023

Sci Rep

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Fast-growing trees like Capirona, Bolaina, and Pashaco have the potential to reduce forest degradation because of their ecological features, the economic importance in the Amazon Forest, and an industry based on wood-polymer composites. Therefore, a practical method to discriminate specie (to avoid illegal logging) and determine chemical composition (tree breeding programs) is needed. This study aimed to validate a model for the classification of wood species and a universal model for the rapid determination of cellulose, hemicellulose, and lignin using FTIR spectroscopy coupled with chemometrics. Our results showed that PLS-DA models for the classification of wood species (0.84 ≤ R2 ≤ 0.91, 0.12 ≤ RMSEP ≤ 0.20, accuracy, specificity, and sensibility between 95.2 and 100%) were satisfied with the full spectra and the differentiation among these species based on IR peaks related to cellulose, lignin, and hemicellulose. Besides, the full spectra helped build a three-species universal PLS model to quantify the principal wood chemical components. Lignin (RPD = 2.27, $${R}_{c}^{2}$$ R c 2 = 0.84) and hemicellulose (RPD = 2.46, $${R}_{c}^{2}$$ R c 2 = 0.83) models showed a good prediction, while cellulose model (RPD = 3.43, $${R}_{c}^{2}$$ R c 2 = 0.91) classified as efficient. This study showed that FTIR-ATR, together with chemometrics, is a reliable method to discriminate wood species and to determine the wood chemical composition in juvenile trees of Pashaco, Capirona, and Bolaina.

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Section: Introductionmentioning

confidence: 99%