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Towards Sustainable North American Wood Product Value Chains, Part I: Computer Vision Identification of Diffuse Porous Hardwoods
Availability of and access to wood identification expertise or technology is a critical component for the design and implementation of practical, enforceable strategies for effective promotion, monitoring and incentivisation of sustainable practices and conservation efforts in the forest products va...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8815006/ https://www.ncbi.nlm.nih.gov/pubmed/35126406 http://dx.doi.org/10.3389/fpls.2021.758455 |
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author | Ravindran, Prabu Owens, Frank C. Wade, Adam C. Shmulsky, Rubin Wiedenhoeft, Alex C. |
author_facet | Ravindran, Prabu Owens, Frank C. Wade, Adam C. Shmulsky, Rubin Wiedenhoeft, Alex C. |
author_sort | Ravindran, Prabu |
collection | PubMed |
description | Availability of and access to wood identification expertise or technology is a critical component for the design and implementation of practical, enforceable strategies for effective promotion, monitoring and incentivisation of sustainable practices and conservation efforts in the forest products value chain. To address this need in the context of the multi-billion-dollar North American wood products industry 22-class, image-based, deep learning models for the macroscopic identification of North American diffuse porous hardwoods were trained for deployment on the open-source, field-deployable XyloTron platform using transverse surface images of specimens from three different xylaria and evaluated on specimens from a fourth xylarium that did not contribute training data. Analysis of the model performance, in the context of the anatomy of the woods considered, demonstrates immediate readiness of the technology developed herein for field testing in a human-in-the-loop monitoring scenario. Also proposed are strategies for training, evaluating, and advancing the state-of-the-art for developing an expansive, continental scale model for all the North American hardwoods. |
format | Online Article Text |
id | pubmed-8815006 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88150062022-02-05 Towards Sustainable North American Wood Product Value Chains, Part I: Computer Vision Identification of Diffuse Porous Hardwoods Ravindran, Prabu Owens, Frank C. Wade, Adam C. Shmulsky, Rubin Wiedenhoeft, Alex C. Front Plant Sci Plant Science Availability of and access to wood identification expertise or technology is a critical component for the design and implementation of practical, enforceable strategies for effective promotion, monitoring and incentivisation of sustainable practices and conservation efforts in the forest products value chain. To address this need in the context of the multi-billion-dollar North American wood products industry 22-class, image-based, deep learning models for the macroscopic identification of North American diffuse porous hardwoods were trained for deployment on the open-source, field-deployable XyloTron platform using transverse surface images of specimens from three different xylaria and evaluated on specimens from a fourth xylarium that did not contribute training data. Analysis of the model performance, in the context of the anatomy of the woods considered, demonstrates immediate readiness of the technology developed herein for field testing in a human-in-the-loop monitoring scenario. Also proposed are strategies for training, evaluating, and advancing the state-of-the-art for developing an expansive, continental scale model for all the North American hardwoods. Frontiers Media S.A. 2022-01-21 /pmc/articles/PMC8815006/ /pubmed/35126406 http://dx.doi.org/10.3389/fpls.2021.758455 Text en Copyright © 2022 Ravindran, Owens, Wade, Shmulsky and Wiedenhoeft. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Ravindran, Prabu Owens, Frank C. Wade, Adam C. Shmulsky, Rubin Wiedenhoeft, Alex C. Towards Sustainable North American Wood Product Value Chains, Part I: Computer Vision Identification of Diffuse Porous Hardwoods |
title | Towards Sustainable North American Wood Product Value Chains, Part I: Computer Vision Identification of Diffuse Porous Hardwoods |
title_full | Towards Sustainable North American Wood Product Value Chains, Part I: Computer Vision Identification of Diffuse Porous Hardwoods |
title_fullStr | Towards Sustainable North American Wood Product Value Chains, Part I: Computer Vision Identification of Diffuse Porous Hardwoods |
title_full_unstemmed | Towards Sustainable North American Wood Product Value Chains, Part I: Computer Vision Identification of Diffuse Porous Hardwoods |
title_short | Towards Sustainable North American Wood Product Value Chains, Part I: Computer Vision Identification of Diffuse Porous Hardwoods |
title_sort | towards sustainable north american wood product value chains, part i: computer vision identification of diffuse porous hardwoods |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8815006/ https://www.ncbi.nlm.nih.gov/pubmed/35126406 http://dx.doi.org/10.3389/fpls.2021.758455 |
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