近红外光谱技术在林业领域的应用

王珏; 李彦杰; 陈益存; 高暝; 赵耘霄; 吴立文; 黄世清; 张永志; 朱康烁; 汪阳东

doi:10.12302/j.issn.1000-2006.202203001

近红外光谱技术在林业领域的应用

王珏, 李彦杰, 陈益存, 高暝, 赵耘霄, 吴立文, 黄世清, 张永志, 朱康烁, 汪阳东

南京林业大学学报（自然科学版） ›› 2023, Vol. 47 ›› Issue (3) : 237-246.

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南京林业大学学报（自然科学版） ›› 2023, Vol. 47 ›› Issue (3) : 237-246. DOI: 10.12302/j.issn.1000-2006.202203001

综合述评

近红外光谱技术在林业领域的应用

王珏 ¹ ,
李彦杰 ² ,
陈益存 ² ,
高暝 ² ,
赵耘霄 ² ,
吴立文 ² ,
黄世清 ³ ,
张永志 ³ ,
朱康烁 ³ ,
汪阳东 ¹^,²^,^*

作者信息 +

The application of near-infrared spectroscopy in forestry

WANG Jue ¹ ,
LI Yanjie ² ,
CHEN Yicun ² ,
GAO Ming ² ,
ZHAO Yunxiao ² ,
WU Liwen ² ,
HUANG Shiqing ³ ,
ZHANG Yongzhi ³ ,
ZHU Kangshuo ³ ,
WANG Yangdong ¹^,²^,^*

Author information +

文章历史 +

摘要

近红外光谱技术是一种快速、准确、无损、高通量、低成本的分析技术,广泛应用于林业领域。在木材性质检测方面,近红外光谱技术对于木材力学特征及化学成分含量等检测都有较高的准确性;在经济林产品品质分析方面,则主要用于反映林业产品的化学组分及含量、口感及硬度等直接和间接性状,对经济林产品品质及林木遗传育种的研究有较好应用前景;在林木分类鉴别应用方面,近红外光谱能够鉴别不同树种及种源,乃至反映树龄信息,在多物种模型中应用效果更好;近红外光谱还能够有效区分多物种的正常植物体与染病植物体,可在林木病虫害研究及生物检疫方面发挥作用。此外,近红外光谱还能应用于预测森林凋落物分解速率、预测土壤成分含量等。笔者分析了近红外光谱在林业科研和生产实际应用中的影响因素,包括样品状态、样本集特征等内在因素,以及预处理、波长选择、建模方式、硬件条件等外在因素对最终模型稳定性和准确度产生的影响。总结认为,近红外光谱技术引入林业研究后大大提高了林业样品检测效率,实现了绿色无损的高通量检测,对林地现场快速测量及林木遗传育种有极好的适应性,对促进林业产业的发展意义重大。

Abstract

To obtain reliable forestry data, a large number of samples need to be tested at each stage; however, larger sample sizes can result in increased time, costs, and manpower. Therefore, a fast and efficient detection method to reduce costs and increase forestry study efficiency is needed. Near-infrared spectroscopy (NIR) is a fast, accurate, non-destructive, high-throughput and low-cost analytical technique, which is gradually gaining popularity for use in forestry studies and its potential for the development. The application of NIR spectroscopy for wood property detection can detect wood mechanical characteristics and chemical composition contents with high accuracy. For analyses of economic forestry product quality, NIR spectroscopy is primarily used to reflect indirect and direct traits such as texture, hardness, chemical composition, and content of forestry products; thus, NIR spectroscopy shows good prospects for use in studies of economic forestry product quality and even forest/tree genetic breeding. In addition, NIR spectroscopy can be used in forest tree classification to identify different tree species and species origins, including age information, with better results obtained in multi-species models. Moreover, NIR spectroscopy is useful in the study of forest pests and diseases, as it can effectively distinguish between the normal and diseased plant bodies of multiple species, can be used in bio-quarantine and to predict forest foliage decomposition rates of forest foliage and soil composition. Based on the multiple cross-disciplinary applications of this method, this paper analyzed the factors that influence NIR spectroscopy in practical applications. Intrinsic factors such as sample state and sample set characteristics, and external factors such as pre-processing, wavelength selection, modeling methods, and hardware conditions all have an impact on the stability and accuracy of the final model. It is clear that the introduction of NIR spectroscopy into forestry research has greatly improved the efficiency of forestry sample detection, achieved green and non-destructive high-throughput detection, and has excellent adaptability to rapid measurement of forest land sites and forest genetic breeding; thus, NIR spectroscopy plays a significant role in promoting forestry development.

导出引用

王珏, 李彦杰, 陈益存, 等. 近红外光谱技术在林业领域的应用[J]. 南京林业大学学报（自然科学版）. 2023, 47(3): 237-246 https://doi.org/10.12302/j.issn.1000-2006.202203001

WANG Jue, LI Yanjie, CHEN Yicun, et al. The application of near-infrared spectroscopy in forestry[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY. 2023, 47(3): 237-246 https://doi.org/10.12302/j.issn.1000-2006.202203001

中图分类号： S759.3

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