Abstract
Internal checking and shrinkage are drying defects that strongly degrade timber for structural and appearance uses in many hardwood species. Wood quality assessors and tree breeders often measure checks and shrinkage from disc-derived wood wedges using scale-based methods and callipers, but these methods are subjective and labour intensive. This study developed an R-based open-source system using image thresholding techniques to quantify checks and shrinkage from digital images of wood wedges. The results showed that the automated quantification of checks predicted the subjective and manual assessment for both area and number of checks in Eucalyptus nitens at the wedge level, and provided much more precision than the subjective classification of checking used by breeders for little additional effort. Similarly, the automated image assessment explained a high proportion of the manually measured variation in shrinkage and collapse with little bias. The automated assessment resulted in significant time saving compared with the manual measurements from digital images. The R-based image analysis thus shows promise in replacing traditional assessment when evaluating a large number of samples and quantitative estimates of checks and shrinkage are required, and has the added advantage that the distribution of checks and collapse within the wedges can be obtained to assist diverse studies on drying defects.
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Acknowledgements
The authors would like to acknowledge STT (Sustainable Timber Tasmania) managers Jhon McNamara and David White for providing access to the trials and allowing sample collection from selected trees. The authors would like to thank Meagan Porter (School of Natural Sciences and ARC Industrial Transformation Training Centre, University of Tasmania) for performing manual assessment on digital images, and Dr. Thomas Baker and Hugh Fitzgerald (School of Natural Sciences and ARC Industrial Transformation Training Centre, University of Tasmania) for assisting in the fieldwork activities. Thanks to Dr. Phillip Blacklow (School of Creative Arts and Media, University of Tasmania) for his technical support with the wood sample processing.
Funding
The research was founded by the Australian Research Council Industrial Transformation Training Centre grant ICI150100004 for supporting this project.
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Rocha-Sepúlveda, M.F., Vega, M., Gendvilas, V. et al. R-based image analysis to quantify checking and shrinkage from wood wedges. Eur. J. Wood Prod. 79, 1269–1281 (2021). https://doi.org/10.1007/s00107-021-01715-0
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DOI: https://doi.org/10.1007/s00107-021-01715-0