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Incorporating the field border effect to reduce the predicted uncertainty of pollen dispersal model in Asia
The presence of the field border (FB), such as roadways or unplanted areas, between two fields is common in Asian farming system. This study evaluated the effect of the FB on the cross-pollination (CP) and predicted the CP rate in the field considering and not considering FB. Three experiments inclu...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8589847/ https://www.ncbi.nlm.nih.gov/pubmed/34772995 http://dx.doi.org/10.1038/s41598-021-01583-x |
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author | Su, Yuan-Chih Lee, Cheng-Bin Yiu, Tien-Joung Kuo, Bo-Jein |
author_facet | Su, Yuan-Chih Lee, Cheng-Bin Yiu, Tien-Joung Kuo, Bo-Jein |
author_sort | Su, Yuan-Chih |
collection | PubMed |
description | The presence of the field border (FB), such as roadways or unplanted areas, between two fields is common in Asian farming system. This study evaluated the effect of the FB on the cross-pollination (CP) and predicted the CP rate in the field considering and not considering FB. Three experiments including 0, 6.75, and 7.5 m width of the FB respectively were conducted to investigate the effect of distance and the FB on the CP rate. The dispersal models combined kernel and observation model by calculating the parameter of observation model from the output of kernel. These models were employed to predict the CP rate at different distances. The Bayesian method was used to estimate parameters and provided a good prediction with uncertainty. The highest average CP rates in the field with and without FB were 74.29% and 36.12%, respectively. It was found that two dispersal models with the FB effect displayed a higher ability to predict average CP rates. The correlation coefficients between actual CP rates and CP rates predicted by the dispersal model combined zero-inflated Poisson observation model with compound exponential kernel and modified Cauchy kernel were 0.834 and 0.833, respectively. Furthermore, the predictive uncertainty was reducing using the dispersal models with the FB effect. |
format | Online Article Text |
id | pubmed-8589847 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-85898472021-11-16 Incorporating the field border effect to reduce the predicted uncertainty of pollen dispersal model in Asia Su, Yuan-Chih Lee, Cheng-Bin Yiu, Tien-Joung Kuo, Bo-Jein Sci Rep Article The presence of the field border (FB), such as roadways or unplanted areas, between two fields is common in Asian farming system. This study evaluated the effect of the FB on the cross-pollination (CP) and predicted the CP rate in the field considering and not considering FB. Three experiments including 0, 6.75, and 7.5 m width of the FB respectively were conducted to investigate the effect of distance and the FB on the CP rate. The dispersal models combined kernel and observation model by calculating the parameter of observation model from the output of kernel. These models were employed to predict the CP rate at different distances. The Bayesian method was used to estimate parameters and provided a good prediction with uncertainty. The highest average CP rates in the field with and without FB were 74.29% and 36.12%, respectively. It was found that two dispersal models with the FB effect displayed a higher ability to predict average CP rates. The correlation coefficients between actual CP rates and CP rates predicted by the dispersal model combined zero-inflated Poisson observation model with compound exponential kernel and modified Cauchy kernel were 0.834 and 0.833, respectively. Furthermore, the predictive uncertainty was reducing using the dispersal models with the FB effect. Nature Publishing Group UK 2021-11-12 /pmc/articles/PMC8589847/ /pubmed/34772995 http://dx.doi.org/10.1038/s41598-021-01583-x Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Su, Yuan-Chih Lee, Cheng-Bin Yiu, Tien-Joung Kuo, Bo-Jein Incorporating the field border effect to reduce the predicted uncertainty of pollen dispersal model in Asia |
title | Incorporating the field border effect to reduce the predicted uncertainty of pollen dispersal model in Asia |
title_full | Incorporating the field border effect to reduce the predicted uncertainty of pollen dispersal model in Asia |
title_fullStr | Incorporating the field border effect to reduce the predicted uncertainty of pollen dispersal model in Asia |
title_full_unstemmed | Incorporating the field border effect to reduce the predicted uncertainty of pollen dispersal model in Asia |
title_short | Incorporating the field border effect to reduce the predicted uncertainty of pollen dispersal model in Asia |
title_sort | incorporating the field border effect to reduce the predicted uncertainty of pollen dispersal model in asia |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8589847/ https://www.ncbi.nlm.nih.gov/pubmed/34772995 http://dx.doi.org/10.1038/s41598-021-01583-x |
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