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Prediction model based on chemical composition change for the mechanical degradation of Korean pine (Pinus koraiensis) after brown-rot fungi (Gloeophyllum trabeum) invasion

Authors: Lipeng Zhang; Qifang Xie; Liujie Yang; Yajie Wu; Xingxia Ma;

Prediction model based on chemical composition change for the mechanical degradation of Korean pine (Pinus koraiensis) after brown-rot fungi (Gloeophyllum trabeum) invasion

Abstract

Abstract In order to predict the mechanical properties of Korean pine after brown-rot decay based on its chemical composition change, 252 samples were prepared and exposed to a 14-week accelerated laboratory decay test using the brown-rot fungus Gloeophyllum trabeum. The mass loss, parallel-to-grain compressive strength, parallel-to-grain tensile strength and bending strengths were tested. Then chemical components and scanning electron micrograph analysis were conducted every two weeks. Results indicated that the mass loss rates of the samples increased with the increasing decay time and were negatively correlated with the sample volume. The strength loss rates were positively correlated with the decay time and mass loss rates. After 14 weeks the average strength loss rates of the parallel-to-grain compressive, tensile and bending samples reached 32%, 41% and 41%, respectively. Strengths degradation was found sensitive to the change of cellulose and hemicellulose contents. Further, mathematical regression models were proposed based on the content changes of the cellulose and hemicellulose to quantitatively predict the degradation of the strengths of Korean pine after brown-rot decay.

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Powered by OpenAIRE graph
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Average