Back to Search Start Over

Pulpwood green density prediction models and sampling-based calibration

Authors :
Jaakko Repola
Juha Heikkinen
Jari Lindblad
Source :
Silva Fennica, Vol 55, Iss 4 (2021)
Publication Year :
2021
Publisher :
Finnish Society of Forest Science, 2021.

Abstract

Pulpwood arriving at the mills is mainly measured by weighing. In the loading phase of forwarding and trucking, timber is weighed using scales mounted in the grapple loader. The measured weight of timber is converted into volume using a conversion factor defined as green density (kg m). At the mill, the green density factor is determined by sampling measurements, while in connection with weighing with grapple-mounted scales during transportation, fixed green density factors are used. In this study, we developed predictive regression models for the green density of pulpwood. The models were constructed separately by pulpwood assortments: pine (contains mainly L); spruce (mainly (L.) Karst.); decayed spruce; birch (mainly Ehrh. and Roth); and aspen (mainly L.). Study material was composed of the sampling-based measurements at the mills between 2013â2019. The models were specified as linear mixed models with both fixed and random parameters. The fixed effect produced the expected value of green density as a function of delivery week, storage time, and meteorological conditions during storage. The random effects allowed the model calibration by utilizing the previous sampling weight measurements. The model validation showed that the model predictions faithfully reproduced the observed seasonal variation in green density. They were more reliable than those obtained with the current practices. Even the uncalibrated (fixed) predictions had lower relative root mean squared prediction errors than those obtained with the current practices.â3Pinus sylvestrisPicea abiesBetula pubescensBetula pendulaPopulus tremula

Subjects

Subjects :
Forestry
SD1-669.5

Details

Language :
English
ISSN :
22424075
Volume :
55
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Silva Fennica
Publication Type :
Academic Journal
Accession number :
edsdoj.055b7967b4f4625b26ded9e0c68c7fc
Document Type :
article
Full Text :
https://doi.org/10.14214/sf.10539