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A method to calculate the number of wheat seedlings in the 1st to the 3rd leaf growth stages

BACKGROUND: The number of cultivated wheat seedlings per unit area allows calculation of plant density. Wheat seedling density provides emergence data and this is useful for improving crop management. The number of wheat seedlings is typically determined by visual counts but this is time-consuming a...

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Detalles Bibliográficos
Autores principales: Liu, Tao, Yang, Tianle, Li, Chunyan, Li, Rui, Wu, Wei, Zhong, Xiaochun, Sun, Chengming, Guo, Wenshan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6238276/
https://www.ncbi.nlm.nih.gov/pubmed/30473722
http://dx.doi.org/10.1186/s13007-018-0369-5
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author Liu, Tao
Yang, Tianle
Li, Chunyan
Li, Rui
Wu, Wei
Zhong, Xiaochun
Sun, Chengming
Guo, Wenshan
author_facet Liu, Tao
Yang, Tianle
Li, Chunyan
Li, Rui
Wu, Wei
Zhong, Xiaochun
Sun, Chengming
Guo, Wenshan
author_sort Liu, Tao
collection PubMed
description BACKGROUND: The number of cultivated wheat seedlings per unit area allows calculation of plant density. Wheat seedling density provides emergence data and this is useful for improving crop management. The number of wheat seedlings is typically determined by visual counts but this is time-consuming and laborious. RESULTS: We obtained field digital images of 1st to 3rd leaf stage wheat seedlings. The seedlings were extracted using an image analysis technique that calculated the coverage degree of the seedlings and the number of angular points of overlapping leaves. The wheat seedling quantity estimation model was constructed using multivariate regression analysis. The model parameters included coverage degree, number of angular points, variety coefficient, and leaf age. Introduction of the number of angular points increased the accuracy of the single coverage degree model. The R(2) value was consistently > 0.95 when the model was applied to different varieties, indicating that the model was adaptable for different varieties. As the leaf stage or density increased, the accuracy of the model declined, but the minimum R(2) remained > 0.87, indicating good adaptability of the model to seedlings with different leaf ages and densities. CONCLUSIONS: This method is an effective means for counting wheat seedlings in the 1st to the 3rd leaf stages.
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spelling pubmed-62382762018-11-23 A method to calculate the number of wheat seedlings in the 1st to the 3rd leaf growth stages Liu, Tao Yang, Tianle Li, Chunyan Li, Rui Wu, Wei Zhong, Xiaochun Sun, Chengming Guo, Wenshan Plant Methods Research BACKGROUND: The number of cultivated wheat seedlings per unit area allows calculation of plant density. Wheat seedling density provides emergence data and this is useful for improving crop management. The number of wheat seedlings is typically determined by visual counts but this is time-consuming and laborious. RESULTS: We obtained field digital images of 1st to 3rd leaf stage wheat seedlings. The seedlings were extracted using an image analysis technique that calculated the coverage degree of the seedlings and the number of angular points of overlapping leaves. The wheat seedling quantity estimation model was constructed using multivariate regression analysis. The model parameters included coverage degree, number of angular points, variety coefficient, and leaf age. Introduction of the number of angular points increased the accuracy of the single coverage degree model. The R(2) value was consistently > 0.95 when the model was applied to different varieties, indicating that the model was adaptable for different varieties. As the leaf stage or density increased, the accuracy of the model declined, but the minimum R(2) remained > 0.87, indicating good adaptability of the model to seedlings with different leaf ages and densities. CONCLUSIONS: This method is an effective means for counting wheat seedlings in the 1st to the 3rd leaf stages. BioMed Central 2018-11-16 /pmc/articles/PMC6238276/ /pubmed/30473722 http://dx.doi.org/10.1186/s13007-018-0369-5 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Liu, Tao
Yang, Tianle
Li, Chunyan
Li, Rui
Wu, Wei
Zhong, Xiaochun
Sun, Chengming
Guo, Wenshan
A method to calculate the number of wheat seedlings in the 1st to the 3rd leaf growth stages
title A method to calculate the number of wheat seedlings in the 1st to the 3rd leaf growth stages
title_full A method to calculate the number of wheat seedlings in the 1st to the 3rd leaf growth stages
title_fullStr A method to calculate the number of wheat seedlings in the 1st to the 3rd leaf growth stages
title_full_unstemmed A method to calculate the number of wheat seedlings in the 1st to the 3rd leaf growth stages
title_short A method to calculate the number of wheat seedlings in the 1st to the 3rd leaf growth stages
title_sort method to calculate the number of wheat seedlings in the 1st to the 3rd leaf growth stages
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6238276/
https://www.ncbi.nlm.nih.gov/pubmed/30473722
http://dx.doi.org/10.1186/s13007-018-0369-5
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