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木材初期腐朽研究综述
引用本文:杨忠,江泽慧,费本华. 木材初期腐朽研究综述[J]. 林业科学, 2006, 42(3): 99-103
作者姓名:杨忠  江泽慧  费本华
作者单位:中国林业科学研究院木材工业研究所,北京,100091;中国林业科学研究院木材工业研究所,北京,100091;中国林业科学研究院木材工业研究所,北京,100091
基金项目:引进国际先进农业科技计划(948计划),中国林科院预研项目
摘    要:木材容易受到各种微生物的侵袭,真菌腐朽是导致木材破坏最严重的一种方式,即使是在木材质量损失率很小的腐朽初期,真菌也可以迅速引起木材结构的破坏,导致木材强度的急剧降低.生物培养和显微镜观察被认为是目前唯一权威的用来检测和评估木材初期腐朽的方法,但这些方法很难对木材的初期腐朽进行快速、准确地评估.因此,寻找一种迅速、准确地检测和评估木材初期腐朽的方法倍受人们的关注.有关初期腐朽及其检测与评估的研究在国外已有大量报道,而在我国却极为少见.本文综述了近几十年国内外有关木材初期腐朽及其检测与评估的研究,旨在增强人们对木材初期腐朽危害的认识,并呼吁有关部门重视相关研究在我国的发展.

关 键 词:木材  初期腐朽  强度损失  检测  综述
文章编号:1001-7488(2006)03-0099-05
收稿时间:2005-06-14
修稿时间:2005-06-14

Review of Literature on Incipient Decay in Wood
Yang Zhong,Jiang Zehui,Fei Benhua. Review of Literature on Incipient Decay in Wood[J]. Scientia Silvae Sinicae, 2006, 42(3): 99-103
Authors:Yang Zhong  Jiang Zehui  Fei Benhua
Affiliation:Research Institute of Wood Industry, CAF Beifing 100091
Abstract:Previous studies have shown that wood is easily subject to biodegradation by a variety of microorganisms, and decay fungi often cause the greatest damage. Fungi can cause dramatic decreases in strength properties during incipient decay in wood, because they can rapidly cause structural failure, even though the weight loss is minimal. Therefore, early detection of wood incipient decay is critical. Culturing and microscopy are currently considered the only definitive methods to detect and assess incipient decay, however, they are time consuming, and less accurate especially for detection of decay at very early stage. Therefore a satisfactory method for detecting the presence of decay during the incipient stage is very necessary. There were a lot of studies on incipient decay in wood and its detection in many countries, a few studies however was investigated in China. Available literature on the effects of incipient decay in wood on strength properties and the methods for detection of incipient decay were reviewed in this paper, for emphasizing the importance of the studies on incipient decay in wood.
Keywords:wood    incipient decay    strength loss    detection   review
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