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PocketMaize: An Android-Smartphone Application for Maize Plant Phenotyping

A low-cost portable wild phenotyping system is useful for breeders to obtain detailed phenotypic characterization to identify promising wild species. However, compared with the larger, faster, and more advanced in-laboratory phenotyping systems developed in recent years, the progress for smaller phe...

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Detalles Bibliográficos
Autores principales: Liu, Lingbo, Yu, Lejun, Wu, Dan, Ye, Junli, Feng, Hui, Liu, Qian, Yang, Wanneng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8656718/
https://www.ncbi.nlm.nih.gov/pubmed/34899792
http://dx.doi.org/10.3389/fpls.2021.770217
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author Liu, Lingbo
Yu, Lejun
Wu, Dan
Ye, Junli
Feng, Hui
Liu, Qian
Yang, Wanneng
author_facet Liu, Lingbo
Yu, Lejun
Wu, Dan
Ye, Junli
Feng, Hui
Liu, Qian
Yang, Wanneng
author_sort Liu, Lingbo
collection PubMed
description A low-cost portable wild phenotyping system is useful for breeders to obtain detailed phenotypic characterization to identify promising wild species. However, compared with the larger, faster, and more advanced in-laboratory phenotyping systems developed in recent years, the progress for smaller phenotyping systems, which provide fast deployment and potential for wide usage in rural and wild areas, is quite limited. In this study, we developed a portable whole-plant on-device phenotyping smartphone application running on Android that can measure up to 45 traits, including 15 plant traits, 25 leaf traits and 5 stem traits, based on images. To avoid the influence of outdoor environments, we trained a DeepLabV3+ model for segmentation. In addition, an angle calibration algorithm was also designed to reduce the error introduced by the different imaging angles. The average execution time for the analysis of a 20-million-pixel image is within 2,500 ms. The application is a portable on-device fast phenotyping platform providing methods for real-time trait measurement, which will facilitate maize phenotyping in field and benefit crop breeding in future.
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spelling pubmed-86567182021-12-10 PocketMaize: An Android-Smartphone Application for Maize Plant Phenotyping Liu, Lingbo Yu, Lejun Wu, Dan Ye, Junli Feng, Hui Liu, Qian Yang, Wanneng Front Plant Sci Plant Science A low-cost portable wild phenotyping system is useful for breeders to obtain detailed phenotypic characterization to identify promising wild species. However, compared with the larger, faster, and more advanced in-laboratory phenotyping systems developed in recent years, the progress for smaller phenotyping systems, which provide fast deployment and potential for wide usage in rural and wild areas, is quite limited. In this study, we developed a portable whole-plant on-device phenotyping smartphone application running on Android that can measure up to 45 traits, including 15 plant traits, 25 leaf traits and 5 stem traits, based on images. To avoid the influence of outdoor environments, we trained a DeepLabV3+ model for segmentation. In addition, an angle calibration algorithm was also designed to reduce the error introduced by the different imaging angles. The average execution time for the analysis of a 20-million-pixel image is within 2,500 ms. The application is a portable on-device fast phenotyping platform providing methods for real-time trait measurement, which will facilitate maize phenotyping in field and benefit crop breeding in future. Frontiers Media S.A. 2021-11-25 /pmc/articles/PMC8656718/ /pubmed/34899792 http://dx.doi.org/10.3389/fpls.2021.770217 Text en Copyright © 2021 Liu, Yu, Wu, Ye, Feng, Liu and Yang. 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
Liu, Lingbo
Yu, Lejun
Wu, Dan
Ye, Junli
Feng, Hui
Liu, Qian
Yang, Wanneng
PocketMaize: An Android-Smartphone Application for Maize Plant Phenotyping
title PocketMaize: An Android-Smartphone Application for Maize Plant Phenotyping
title_full PocketMaize: An Android-Smartphone Application for Maize Plant Phenotyping
title_fullStr PocketMaize: An Android-Smartphone Application for Maize Plant Phenotyping
title_full_unstemmed PocketMaize: An Android-Smartphone Application for Maize Plant Phenotyping
title_short PocketMaize: An Android-Smartphone Application for Maize Plant Phenotyping
title_sort pocketmaize: an android-smartphone application for maize plant phenotyping
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8656718/
https://www.ncbi.nlm.nih.gov/pubmed/34899792
http://dx.doi.org/10.3389/fpls.2021.770217
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