Comparison of two forensic wood identification technologies for ten Meliaceae woods: computer vision versus mass spectrometry

Detalhes bibliográficos
Autor(a) principal: Ravindran, Prabu
Data de Publicação: 2020
Outros Autores: Wiedenhoeft, Alex C.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1007/s00226-020-01178-1
http://hdl.handle.net/11449/195489
Resumo: A wealth of forensic wood identification technologies has been developed or improved in recent years, with many attempts to compare results between technologies. The utility of such comparisons is greatly reduced when the species tested with each technology are different and when performance metrics are not calculated or presented in the same way. Here, a species-level XyloTron computer vision model is presented along with a side-by-side comparison for species- and genus-level identification of the 10 species of Meliaceae studied by Deklerck et al. using mass spectrometry. The species-level accuracies of the XyloTron model and the mass spectrometry models are comparable, while the genus-level accuracy of the XyloTron model is higher than that of the mass spectrometry model. The paper concludes with a call for better practices to compare disparate forensic wood identification technologies from a performance driven perspective.
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spelling Comparison of two forensic wood identification technologies for ten Meliaceae woods: computer vision versus mass spectrometryA wealth of forensic wood identification technologies has been developed or improved in recent years, with many attempts to compare results between technologies. The utility of such comparisons is greatly reduced when the species tested with each technology are different and when performance metrics are not calculated or presented in the same way. Here, a species-level XyloTron computer vision model is presented along with a side-by-side comparison for species- and genus-level identification of the 10 species of Meliaceae studied by Deklerck et al. using mass spectrometry. The species-level accuracies of the XyloTron model and the mass spectrometry models are comparable, while the genus-level accuracy of the XyloTron model is higher than that of the mass spectrometry model. The paper concludes with a call for better practices to compare disparate forensic wood identification technologies from a performance driven perspective.Univ Wisconsin, Dept Bot, Madison, WI 53706 USAUS Forest Serv, Forest Prod Lab, Ctr Wood Anat Res, USDA, Madison, WI 53726 USAPurdue Univ, Dept Forestry & Nat Resources, W Lafayette, IN 47907 USAUniv Estadual Paulista Botucatu, Ciencias Biol Bot, Sao Paulo, BrazilUniv Estadual Paulista Botucatu, Ciencias Biol Bot, Sao Paulo, BrazilSpringerUniv WisconsinUS Forest ServPurdue UnivUniversidade Estadual Paulista (Unesp)Ravindran, PrabuWiedenhoeft, Alex C.2020-12-10T17:36:22Z2020-12-10T17:36:22Z2020-07-04info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article1139-1150http://dx.doi.org/10.1007/s00226-020-01178-1Wood Science And Technology. New York: Springer, v. 54, n. 5, p. 1139-1150, 2020.0043-7719http://hdl.handle.net/11449/19548910.1007/s00226-020-01178-1WOS:000545289000001Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengWood Science And Technologyinfo:eu-repo/semantics/openAccess2021-10-23T08:59:40Zoai:repositorio.unesp.br:11449/195489Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:02:55.542615Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Comparison of two forensic wood identification technologies for ten Meliaceae woods: computer vision versus mass spectrometry
title Comparison of two forensic wood identification technologies for ten Meliaceae woods: computer vision versus mass spectrometry
spellingShingle Comparison of two forensic wood identification technologies for ten Meliaceae woods: computer vision versus mass spectrometry
Ravindran, Prabu
title_short Comparison of two forensic wood identification technologies for ten Meliaceae woods: computer vision versus mass spectrometry
title_full Comparison of two forensic wood identification technologies for ten Meliaceae woods: computer vision versus mass spectrometry
title_fullStr Comparison of two forensic wood identification technologies for ten Meliaceae woods: computer vision versus mass spectrometry
title_full_unstemmed Comparison of two forensic wood identification technologies for ten Meliaceae woods: computer vision versus mass spectrometry
title_sort Comparison of two forensic wood identification technologies for ten Meliaceae woods: computer vision versus mass spectrometry
author Ravindran, Prabu
author_facet Ravindran, Prabu
Wiedenhoeft, Alex C.
author_role author
author2 Wiedenhoeft, Alex C.
author2_role author
dc.contributor.none.fl_str_mv Univ Wisconsin
US Forest Serv
Purdue Univ
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Ravindran, Prabu
Wiedenhoeft, Alex C.
description A wealth of forensic wood identification technologies has been developed or improved in recent years, with many attempts to compare results between technologies. The utility of such comparisons is greatly reduced when the species tested with each technology are different and when performance metrics are not calculated or presented in the same way. Here, a species-level XyloTron computer vision model is presented along with a side-by-side comparison for species- and genus-level identification of the 10 species of Meliaceae studied by Deklerck et al. using mass spectrometry. The species-level accuracies of the XyloTron model and the mass spectrometry models are comparable, while the genus-level accuracy of the XyloTron model is higher than that of the mass spectrometry model. The paper concludes with a call for better practices to compare disparate forensic wood identification technologies from a performance driven perspective.
publishDate 2020
dc.date.none.fl_str_mv 2020-12-10T17:36:22Z
2020-12-10T17:36:22Z
2020-07-04
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1007/s00226-020-01178-1
Wood Science And Technology. New York: Springer, v. 54, n. 5, p. 1139-1150, 2020.
0043-7719
http://hdl.handle.net/11449/195489
10.1007/s00226-020-01178-1
WOS:000545289000001
url http://dx.doi.org/10.1007/s00226-020-01178-1
http://hdl.handle.net/11449/195489
identifier_str_mv Wood Science And Technology. New York: Springer, v. 54, n. 5, p. 1139-1150, 2020.
0043-7719
10.1007/s00226-020-01178-1
WOS:000545289000001
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Wood Science And Technology
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 1139-1150
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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