On the Methods to Predict Moisture Content on Wood: A Literature Review

Vítor Magalhães, Giancarlo Lucca, Alessandro Bicho, Eduardo Borges

2022

Abstract

Wood is the raw material for many manufactured goods. Charcoal, cellulose for the paper industry, laminated wood furniture, and even explosive products, such as gunpowder cotton, are possible destinations for the wood. On the other hand, the growing use of wood as a raw material has increased illegal deforestation and, as a direct consequence, it has changed the climate at a global level. The use of wood in production processes must be optimized to mitigate these adverse effects. One of the determining factors for this optimization is moisture content on wood, i.e., the ratio between the mass of water contained in the wood and dry wood mass. This article reviews the scientific literature published from 1959 to 2019 regarding the use of wood due to a better knowledge of its properties, particularly systems to explain or predict the moisture content. It contributes to the continuity of related research with the theme by ensemble the conducted studies into a single analysis.

Paper Citation

in Harvard Style

Magalhães V., Lucca G., Bicho A. and Borges E. (2022). On the Methods to Predict Moisture Content on Wood: A Literature Review. In Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-569-2, pages 521-528. DOI: 10.5220/0011063100003179

in Bibtex Style

@conference{iceis22,
author={Vítor Magalhães and Giancarlo Lucca and Alessandro Bicho and Eduardo Borges},
title={On the Methods to Predict Moisture Content on Wood: A Literature Review},
booktitle={Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2022},
pages={521-528},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011063100003179},
isbn={978-989-758-569-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - On the Methods to Predict Moisture Content on Wood: A Literature Review
SN - 978-989-758-569-2
AU - Magalhães V.
AU - Lucca G.
AU - Bicho A.
AU - Borges E.
PY - 2022
SP - 521
EP - 528
DO - 10.5220/0011063100003179