‘Tracheid effect’ light scattering response of common commercial species of Malaysia using red laser (650 nm) for grain angle detection, and machine learning based performance prediction

Tan, Chiat Oon; Ogata, Shigenobu; Yap, Hwa Jen; Soo, Jin Xue; Usop, Zuriani; Fauthan, Mohd ’Akashah; Liew, Shaer Jin; Ng, Siew Cheok

doi:https://doi.org/10.1007/s00226-025-01653-7

‘Tracheid effect’ light scattering response of common commercial species of Malaysia using red laser (650 nm) for grain angle detection, and machine learning based performance prediction

Tan, Chiat Oon; Ogata, Shigenobu; Yap, Hwa Jen et al.

Wood Science and Technology, 2025, 59, 56

Number of Access:76（2025-11-07 15:23 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/102245

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Title	‘Tracheid effect’ light scattering response of common commercial species of Malaysia using red laser (650 nm) for grain angle detection, and machine learning based performance prediction
Creator	CreatorName Tan, Chiat Oon
	NRID 1000020273584 1000020273584 ORCID 0000-0002-9072-4496 0000-0002-9072-4496 researchmap permalink read0185246 read0185246 Scopus Author ID 7201796489 7201796489 CreatorName Ogata, Shigenobu
	CreatorName Yap, Hwa Jen
	CreatorName Soo, Jin Xue
	CreatorName Usop, Zuriani
	CreatorName Fauthan, Mohd ’Akashah
	CreatorName Liew, Shaer Jin
	CreatorName Ng, Siew Cheok
Description	The version of record of this article, first published in Wood Science and Technology, is available online at Publisher’s website: https://doi.org/10.1007/s00226-025-01653-7.
Abstract	Tracheid effect’, or laser light scattering in wood is an important phenomenon in the study of wood, but not well researched for Malaysian timber species. Sixty (60) common commercial timber species of Malaysia, as defined by the Forest Research Institute Malaysia (FRIM), were tested for ’tracheid effect’ response using 650 nm (red) laser. 5 samples each of 11 heavy hardwood, 15 medium hardwood, 32 light hardwood, and 2 softwood species were tested. Medium density fibreboard (MDF) was used as a reference. The grain angle performance metric, which is the root mean squared error (RMSE) between the observed and actual angles of ellipse generated by the dot laser and imaged by the camera, was determined and tabulated. To predict the grain angle performance for unknown species using colour and density features, two machine learning (ML) classification approaches were tested, namely k-Nearest Neighbour (k-NN), and shallow feed-forward artificial neural network (ANN), as well as one function-fitting ANN. For predicting RMSE <5∘, the function-fitting ANN performed the best at 82.7%, while k-NN scored the highest overall performance of 89.3% when predicting RMSE <10∘. The density of wood did not directly correlate with the grain angle performance, but its inclusion as a feature together with the colour features improved the accuracy of the ML predictions. The colour features related to brightness were dominant features that affected performance. In summary, this study confirmed that wood colour as well as density plays an important role in the ability to determine grain angle by means of the tracheid effect using 650 nm lasers.
Publisher	Springer Science and Business Media Deutschland GmbH
Source Title	Wood Science and Technology
Volume (Issue)	59
Page	56
Date of Issued	2025-05-07
Language	English
Handle URL	https://hdl.handle.net/11094/102245
PISSN	00437719
eISSN	14325225
Relation.isIdenticalTo	DOI (Publisher Version) https://doi.org/10.1007/s00226-025-01653-7
Access Rights	open access
CopyRight	This article is licensed under a Creative Commons Attribution 4.0 International License.
oaire:version	Version of Record
Category	学術雑誌論文 Journal Article

Resource Type	journal article
Local Type	Journal Article
DCMI Type	Text
DCTERMS.bibliographicCitation	Wood Science and Technology. 2025, 59, p. 56
DC.title	‘Tracheid effect’ light scattering response of common commercial species of Malaysia using red laser (650 nm) for grain angle detection, and machine learning based performance prediction
DC.creator	Tan, Chiat Oon
	Ogata, Shigenobu
	Yap, Hwa Jen
	Soo, Jin Xue
	Usop, Zuriani
	Fauthan, Mohd ’Akashah
	Liew, Shaer Jin
	Ng, Siew Cheok
DC.publisher	Springer Science and Business Media Deutschland GmbH
DC.language' scheme='DCTERMS.RFC1766	English
DC.type' scheme='DCTERMS.DCMIType	Text
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2025-05-07
DC.identifier	https://doi.org/10.1007/s00226-025-01653-7
DC.description	The version of record of this article, first published in Wood Science and Technology, is available online at Publisher’s website: https://doi.org/10.1007/s00226-025-01653-7.
DCTERMS.abstract	Tracheid effect’, or laser light scattering in wood is an important phenomenon in the study of wood, but not well researched for Malaysian timber species. Sixty (60) common commercial timber species of Malaysia, as defined by the Forest Research Institute Malaysia (FRIM), were tested for ’tracheid effect’ response using 650 nm (red) laser. 5 samples each of 11 heavy hardwood, 15 medium hardwood, 32 light hardwood, and 2 softwood species were tested. Medium density fibreboard (MDF) was used as a reference. The grain angle performance metric, which is the root mean squared error (RMSE) between the observed and actual angles of ellipse generated by the dot laser and imaged by the camera, was determined and tabulated. To predict the grain angle performance for unknown species using colour and density features, two machine learning (ML) classification approaches were tested, namely k-Nearest Neighbour (k-NN), and shallow feed-forward artificial neural network (ANN), as well as one function-fitting ANN. For predicting RMSE <5∘, the function-fitting ANN performed the best at 82.7%, while k-NN scored the highest overall performance of 89.3% when predicting RMSE <10∘. The density of wood did not directly correlate with the grain angle performance, but its inclusion as a feature together with the colour features improved the accuracy of the ML predictions. The colour features related to brightness were dominant features that affected performance. In summary, this study confirmed that wood colour as well as density plays an important role in the ability to determine grain angle by means of the tracheid effect using 650 nm lasers.
DC.rights	This article is licensed under a Creative Commons Attribution 4.0 International License.
DC.format	102245
citation_title	‘Tracheid effect’ light scattering response of common commercial species of Malaysia using red laser (650 nm) for grain angle detection, and machine learning based performance prediction
citation_author	Tan, Chiat Oon
	Ogata, Shigenobu
	Yap, Hwa Jen
	Soo, Jin Xue
	Usop, Zuriani
	Fauthan, Mohd ’Akashah
	Liew, Shaer Jin
	Ng, Siew Cheok
citation_publisher	Springer Science and Business Media Deutschland GmbH
citation_language	English
citation_date	2025-05-07
citation_journal_title	Wood Science and Technology
citation_volume	59
citation_firstpage	56
citation_doi	https://doi.org/10.1007/s00226-025-01653-7
citation_public_url	https://hdl.handle.net/11094/102245

‘Tracheid effect’ light scattering response of common commercial species of Malaysia using red laser (650 nm) for grain angle detection, and machine learning based performance prediction

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