A novel machine-vision-based facility for the automatic evaluation of yield-related traits in rice

The evaluation of yield-related traits is an essential step in rice breeding, genetic research and functional genomics research. A new, automatic, and labor-free facility to automatically thresh rice panicles, evaluate rice yield traits, and subsequently pack filled spikelets is presented in this pa...

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Detalles Bibliográficos
Autores principales: Duan, Lingfeng, Yang, Wanneng, Huang, Chenglong, Liu, Qian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Methodology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3264518/
https://www.ncbi.nlm.nih.gov/pubmed/22152096
http://dx.doi.org/10.1186/1746-4811-7-44
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author Duan, Lingfeng
Yang, Wanneng
Huang, Chenglong
Liu, Qian
author_facet Duan, Lingfeng
Yang, Wanneng
Huang, Chenglong
Liu, Qian
author_sort Duan, Lingfeng
collection PubMed
description The evaluation of yield-related traits is an essential step in rice breeding, genetic research and functional genomics research. A new, automatic, and labor-free facility to automatically thresh rice panicles, evaluate rice yield traits, and subsequently pack filled spikelets is presented in this paper. Tests showed that the facility was capable of evaluating yield-related traits with a mean absolute percentage error of less than 5% and an efficiency of 1440 plants per continuous 24 h workday.
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spelling pubmed-32645182012-01-24 A novel machine-vision-based facility for the automatic evaluation of yield-related traits in rice Duan, Lingfeng Yang, Wanneng Huang, Chenglong Liu, Qian Plant Methods Methodology The evaluation of yield-related traits is an essential step in rice breeding, genetic research and functional genomics research. A new, automatic, and labor-free facility to automatically thresh rice panicles, evaluate rice yield traits, and subsequently pack filled spikelets is presented in this paper. Tests showed that the facility was capable of evaluating yield-related traits with a mean absolute percentage error of less than 5% and an efficiency of 1440 plants per continuous 24 h workday. BioMed Central 2011-12-12 /pmc/articles/PMC3264518/ /pubmed/22152096 http://dx.doi.org/10.1186/1746-4811-7-44 Text en Copyright ©2011 Duan et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology
Duan, Lingfeng
Yang, Wanneng
Huang, Chenglong
Liu, Qian
A novel machine-vision-based facility for the automatic evaluation of yield-related traits in rice
title A novel machine-vision-based facility for the automatic evaluation of yield-related traits in rice
title_full A novel machine-vision-based facility for the automatic evaluation of yield-related traits in rice
title_fullStr A novel machine-vision-based facility for the automatic evaluation of yield-related traits in rice
title_full_unstemmed A novel machine-vision-based facility for the automatic evaluation of yield-related traits in rice
title_short A novel machine-vision-based facility for the automatic evaluation of yield-related traits in rice
title_sort novel machine-vision-based facility for the automatic evaluation of yield-related traits in rice
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3264518/
https://www.ncbi.nlm.nih.gov/pubmed/22152096
http://dx.doi.org/10.1186/1746-4811-7-44
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