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Development of Willow Tree Yield-Mapping Technology

With today’s environmental challenges, developing sustainable energy sources is crucial. From this perspective, woody biomass has been, and continues to be, a significant research interest. The goal of this research was to develop new technology for mapping willow tree yield grown in a short-rotatio...

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Autores principales: Leclerc, Maxime, Adamchuk, Viacheslav, Park, Jaesung, Lachapelle-T., Xavier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7249128/
https://www.ncbi.nlm.nih.gov/pubmed/32384703
http://dx.doi.org/10.3390/s20092650
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author Leclerc, Maxime
Adamchuk, Viacheslav
Park, Jaesung
Lachapelle-T., Xavier
author_facet Leclerc, Maxime
Adamchuk, Viacheslav
Park, Jaesung
Lachapelle-T., Xavier
author_sort Leclerc, Maxime
collection PubMed
description With today’s environmental challenges, developing sustainable energy sources is crucial. From this perspective, woody biomass has been, and continues to be, a significant research interest. The goal of this research was to develop new technology for mapping willow tree yield grown in a short-rotation forestry (SRF) system. The system gathered the physical characteristics of willow trees on-the-go, while the trees were being harvested. Features assessed include the number of trees harvested and their diameter. To complete this task, a machine-vision system featuring an RGB-D stereovision camera was built. The system tagged these data with the corresponding geographical coordinates using a Global Navigation Satellite System (GNSS) receiver. The proposed yield-mapping system showed promising detection results considering the complex background and variable light conditions encountered in the outdoors. Of the 40 randomly selected and manually observed trees in a row, 36 were successfully detected, yielding a 90% detection rate. The correctly detected tree rate of all trees within the scenes was actually 71.8% since the system tended to be sensitive to branches, thus, falsely detecting them as trees. Manual validation of the diameter estimation function showed a poor coefficient of determination and a root mean square error (RMSE) of 10.7 mm.
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spelling pubmed-72491282020-06-10 Development of Willow Tree Yield-Mapping Technology Leclerc, Maxime Adamchuk, Viacheslav Park, Jaesung Lachapelle-T., Xavier Sensors (Basel) Article With today’s environmental challenges, developing sustainable energy sources is crucial. From this perspective, woody biomass has been, and continues to be, a significant research interest. The goal of this research was to develop new technology for mapping willow tree yield grown in a short-rotation forestry (SRF) system. The system gathered the physical characteristics of willow trees on-the-go, while the trees were being harvested. Features assessed include the number of trees harvested and their diameter. To complete this task, a machine-vision system featuring an RGB-D stereovision camera was built. The system tagged these data with the corresponding geographical coordinates using a Global Navigation Satellite System (GNSS) receiver. The proposed yield-mapping system showed promising detection results considering the complex background and variable light conditions encountered in the outdoors. Of the 40 randomly selected and manually observed trees in a row, 36 were successfully detected, yielding a 90% detection rate. The correctly detected tree rate of all trees within the scenes was actually 71.8% since the system tended to be sensitive to branches, thus, falsely detecting them as trees. Manual validation of the diameter estimation function showed a poor coefficient of determination and a root mean square error (RMSE) of 10.7 mm. MDPI 2020-05-06 /pmc/articles/PMC7249128/ /pubmed/32384703 http://dx.doi.org/10.3390/s20092650 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Leclerc, Maxime
Adamchuk, Viacheslav
Park, Jaesung
Lachapelle-T., Xavier
Development of Willow Tree Yield-Mapping Technology
title Development of Willow Tree Yield-Mapping Technology
title_full Development of Willow Tree Yield-Mapping Technology
title_fullStr Development of Willow Tree Yield-Mapping Technology
title_full_unstemmed Development of Willow Tree Yield-Mapping Technology
title_short Development of Willow Tree Yield-Mapping Technology
title_sort development of willow tree yield-mapping technology
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7249128/
https://www.ncbi.nlm.nih.gov/pubmed/32384703
http://dx.doi.org/10.3390/s20092650
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