利用傅立叶变换近红外光谱法对亚马逊中部自然倒伏的鹅掌楸科树木的木材进行替代性鉴定

IF 1.5 4区 农林科学 Q2 FORESTRY International Forestry Review Pub Date : 2024-03-01 DOI:10.1505/146554824838457844
C. Eugenio da Silva, C. Nascimento, J.A. Freitas, R. Araújo, F.M. Durgante, C. Zartman, C. Nascimento, N. Higuchi
{"title":"利用傅立叶变换近红外光谱法对亚马逊中部自然倒伏的鹅掌楸科树木的木材进行替代性鉴定","authors":"C. Eugenio da Silva, C. Nascimento, J.A. Freitas, R. Araújo, F.M. Durgante, C. Zartman, C. Nascimento, N. Higuchi","doi":"10.1505/146554824838457844","DOIUrl":null,"url":null,"abstract":"The scientific identification of natural fallen trees in tropical forests is complex due to the lack of fertile material in field collection. The study evaluated the use of near-infrared spectroscopy with Fourier-transform (FT-NIR) in the discrimination of wood from fallen trees of\n the Lecythidaceae family. Seven trees were collected in the Central Amazonian region (Brazil), from which 63 specimens were prepared from the wood, and NIR spectra were obtained on different wood surfaces (total 756 spectra). Chemometric models were developed with a spectral data set, and\n the Mahalanobis algorithm was applied. The discriminant model with 2nd derivative spectra improved the identification capacity, resulting in errors < 5% in the identification of genus Couratari (3 ssp.), Eschweilera (2 ssp.), Holopyxidium (1 sp.) and\n Lecythis (1 sp.). The comparison of the spectral signatures of samples of fallen trees and wood library revealed that even when wood was exposed to environmental weathering, around 50% of the original bands were preserved, favouring discrimination at the genus level. The accuracy\n of the chemometric models developed indicates the applicability of FT-NIR spectroscopy integrative in identifying fallen trees from the Lecythidaceae family in the tropical forests.","PeriodicalId":13868,"journal":{"name":"International Forestry Review","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Alternative identification of wood from natural fallen trees of the Lecythidaceae family in the Central Amazonian using FT-NIR spectroscopy\",\"authors\":\"C. Eugenio da Silva, C. Nascimento, J.A. Freitas, R. Araújo, F.M. Durgante, C. Zartman, C. Nascimento, N. Higuchi\",\"doi\":\"10.1505/146554824838457844\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The scientific identification of natural fallen trees in tropical forests is complex due to the lack of fertile material in field collection. The study evaluated the use of near-infrared spectroscopy with Fourier-transform (FT-NIR) in the discrimination of wood from fallen trees of\\n the Lecythidaceae family. Seven trees were collected in the Central Amazonian region (Brazil), from which 63 specimens were prepared from the wood, and NIR spectra were obtained on different wood surfaces (total 756 spectra). Chemometric models were developed with a spectral data set, and\\n the Mahalanobis algorithm was applied. The discriminant model with 2nd derivative spectra improved the identification capacity, resulting in errors < 5% in the identification of genus Couratari (3 ssp.), Eschweilera (2 ssp.), Holopyxidium (1 sp.) and\\n Lecythis (1 sp.). The comparison of the spectral signatures of samples of fallen trees and wood library revealed that even when wood was exposed to environmental weathering, around 50% of the original bands were preserved, favouring discrimination at the genus level. The accuracy\\n of the chemometric models developed indicates the applicability of FT-NIR spectroscopy integrative in identifying fallen trees from the Lecythidaceae family in the tropical forests.\",\"PeriodicalId\":13868,\"journal\":{\"name\":\"International Forestry Review\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Forestry Review\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.1505/146554824838457844\",\"RegionNum\":4,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"FORESTRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Forestry Review","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1505/146554824838457844","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"FORESTRY","Score":null,"Total":0}
引用次数: 0

摘要

由于缺乏野外采集的可育材料,对热带森林中的天然倒伏树木进行科学鉴定非常复杂。本研究评估了傅立叶变换近红外光谱仪(FT-NIR)在鉴别落叶松科树木木材中的应用。研究人员在亚马逊中部地区(巴西)采集了 7 棵树,从中制备了 63 个木材标本,并在不同的木材表面获得了近红外光谱(共 756 个光谱)。利用光谱数据集开发了化学计量模型,并应用了 Mahalanobis 算法。带有二阶导数光谱的判别模型提高了识别能力,在识别 Couratari 属(3 种)、Eschweilera 属(2 种)、Holopyxidium 属(1 种)和 Lecythis 属(1 种)时误差小于 5%。对倒下的树木样本和木材库的光谱特征进行比较后发现,即使木材暴露在环境风化中,也能保留约 50%的原始条带,有利于在属一级进行鉴别。所建立的化学计量学模型的准确性表明,傅立叶变换近红外光谱综合技术适用于识别热带森林中的落叶松科树木。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Alternative identification of wood from natural fallen trees of the Lecythidaceae family in the Central Amazonian using FT-NIR spectroscopy
The scientific identification of natural fallen trees in tropical forests is complex due to the lack of fertile material in field collection. The study evaluated the use of near-infrared spectroscopy with Fourier-transform (FT-NIR) in the discrimination of wood from fallen trees of the Lecythidaceae family. Seven trees were collected in the Central Amazonian region (Brazil), from which 63 specimens were prepared from the wood, and NIR spectra were obtained on different wood surfaces (total 756 spectra). Chemometric models were developed with a spectral data set, and the Mahalanobis algorithm was applied. The discriminant model with 2nd derivative spectra improved the identification capacity, resulting in errors < 5% in the identification of genus Couratari (3 ssp.), Eschweilera (2 ssp.), Holopyxidium (1 sp.) and Lecythis (1 sp.). The comparison of the spectral signatures of samples of fallen trees and wood library revealed that even when wood was exposed to environmental weathering, around 50% of the original bands were preserved, favouring discrimination at the genus level. The accuracy of the chemometric models developed indicates the applicability of FT-NIR spectroscopy integrative in identifying fallen trees from the Lecythidaceae family in the tropical forests.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
International Forestry Review
International Forestry Review 农林科学-林学
CiteScore
2.50
自引率
6.20%
发文量
29
审稿时长
>36 weeks
期刊介绍: The International Forestry Review is a peer-reviewed scholarly journal that publishes original research and review papers on forest policy and science, with an emphasis on issues of transnational significance. It is published four times per year, in March, June, September and December. Special Issues are a regular feature and attract a wide audience. Click here for subscription details.
期刊最新文献
Improving the role of communities in participatory forest management through artificial intelligence: the case of Nairobi city park community forest association Alternative identification of wood from natural fallen trees of the Lecythidaceae family in the Central Amazonian using FT-NIR spectroscopy Strengthening capacity for forest protection in Myanmar Tree seed supply system in Ethiopia: modeling source and dissemination of priority species Training forestry students for uncertainty and complexity: the development and assessment of a transformative roleplay
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1