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GIS-Based Analysis for UAV-Supported Field Experiments Reveals Soybean Traits Associated With Rotational Benefit
Recent advances in unmanned aerial vehicle (UAV) remote sensing and image analysis provide large amounts of plant canopy data, but there is no method to integrate the large imagery datasets with the much smaller manually collected datasets. A simple geographic information system (GIS)-based analysis...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201397/ https://www.ncbi.nlm.nih.gov/pubmed/34135918 http://dx.doi.org/10.3389/fpls.2021.637694 |
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author | Fukano, Yuya Guo, Wei Aoki, Naohiro Ootsuka, Shinjiro Noshita, Koji Uchida, Kei Kato, Yoichiro Sasaki, Kazuhiro Kamikawa, Shotaka Kubota, Hirofumi |
author_facet | Fukano, Yuya Guo, Wei Aoki, Naohiro Ootsuka, Shinjiro Noshita, Koji Uchida, Kei Kato, Yoichiro Sasaki, Kazuhiro Kamikawa, Shotaka Kubota, Hirofumi |
author_sort | Fukano, Yuya |
collection | PubMed |
description | Recent advances in unmanned aerial vehicle (UAV) remote sensing and image analysis provide large amounts of plant canopy data, but there is no method to integrate the large imagery datasets with the much smaller manually collected datasets. A simple geographic information system (GIS)-based analysis for a UAV-supported field study (GAUSS) analytical framework was developed to integrate these datasets. It has three steps: developing a model for predicting sample values from UAV imagery, field gridding and trait value prediction, and statistical testing of predicted values. A field cultivation experiment was conducted to examine the effectiveness of the GAUSS framework, using a soybean–wheat crop rotation as the model system Fourteen soybean cultivars and subsequently a single wheat cultivar were grown in the same field. The crop rotation benefits of the soybeans for wheat yield were examined using GAUSS. Combining manually sampled data (n = 143) and pixel-based UAV imagery indices produced a large amount of high-spatial-resolution predicted wheat yields (n = 8,756). Significant differences were detected among soybean cultivars in their effects on wheat yield, and soybean plant traits were associated with the increases. This is the first reported study that links traits of legume plants with rotational benefits to the subsequent crop. Although some limitations and challenges remain, the GAUSS approach can be applied to many types of field-based plant experimentation, and has potential for extensive use in future studies. |
format | Online Article Text |
id | pubmed-8201397 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82013972021-06-15 GIS-Based Analysis for UAV-Supported Field Experiments Reveals Soybean Traits Associated With Rotational Benefit Fukano, Yuya Guo, Wei Aoki, Naohiro Ootsuka, Shinjiro Noshita, Koji Uchida, Kei Kato, Yoichiro Sasaki, Kazuhiro Kamikawa, Shotaka Kubota, Hirofumi Front Plant Sci Plant Science Recent advances in unmanned aerial vehicle (UAV) remote sensing and image analysis provide large amounts of plant canopy data, but there is no method to integrate the large imagery datasets with the much smaller manually collected datasets. A simple geographic information system (GIS)-based analysis for a UAV-supported field study (GAUSS) analytical framework was developed to integrate these datasets. It has three steps: developing a model for predicting sample values from UAV imagery, field gridding and trait value prediction, and statistical testing of predicted values. A field cultivation experiment was conducted to examine the effectiveness of the GAUSS framework, using a soybean–wheat crop rotation as the model system Fourteen soybean cultivars and subsequently a single wheat cultivar were grown in the same field. The crop rotation benefits of the soybeans for wheat yield were examined using GAUSS. Combining manually sampled data (n = 143) and pixel-based UAV imagery indices produced a large amount of high-spatial-resolution predicted wheat yields (n = 8,756). Significant differences were detected among soybean cultivars in their effects on wheat yield, and soybean plant traits were associated with the increases. This is the first reported study that links traits of legume plants with rotational benefits to the subsequent crop. Although some limitations and challenges remain, the GAUSS approach can be applied to many types of field-based plant experimentation, and has potential for extensive use in future studies. Frontiers Media S.A. 2021-05-31 /pmc/articles/PMC8201397/ /pubmed/34135918 http://dx.doi.org/10.3389/fpls.2021.637694 Text en Copyright © 2021 Fukano, Guo, Aoki, Ootsuka, Noshita, Uchida, Kato, Sasaki, Kamikawa and Kubota. 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 Fukano, Yuya Guo, Wei Aoki, Naohiro Ootsuka, Shinjiro Noshita, Koji Uchida, Kei Kato, Yoichiro Sasaki, Kazuhiro Kamikawa, Shotaka Kubota, Hirofumi GIS-Based Analysis for UAV-Supported Field Experiments Reveals Soybean Traits Associated With Rotational Benefit |
title | GIS-Based Analysis for UAV-Supported Field Experiments Reveals Soybean Traits Associated With Rotational Benefit |
title_full | GIS-Based Analysis for UAV-Supported Field Experiments Reveals Soybean Traits Associated With Rotational Benefit |
title_fullStr | GIS-Based Analysis for UAV-Supported Field Experiments Reveals Soybean Traits Associated With Rotational Benefit |
title_full_unstemmed | GIS-Based Analysis for UAV-Supported Field Experiments Reveals Soybean Traits Associated With Rotational Benefit |
title_short | GIS-Based Analysis for UAV-Supported Field Experiments Reveals Soybean Traits Associated With Rotational Benefit |
title_sort | gis-based analysis for uav-supported field experiments reveals soybean traits associated with rotational benefit |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201397/ https://www.ncbi.nlm.nih.gov/pubmed/34135918 http://dx.doi.org/10.3389/fpls.2021.637694 |
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