Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Fukano, Yuya, Guo, Wei, Aoki, Naohiro, Ootsuka, Shinjiro, Noshita, Koji, Uchida, Kei, Kato, Yoichiro, Sasaki, Kazuhiro, Kamikawa, Shotaka, Kubota, Hirofumi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
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
_version_ 1783707809625407488
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
work_keys_str_mv AT fukanoyuya gisbasedanalysisforuavsupportedfieldexperimentsrevealssoybeantraitsassociatedwithrotationalbenefit
AT guowei gisbasedanalysisforuavsupportedfieldexperimentsrevealssoybeantraitsassociatedwithrotationalbenefit
AT aokinaohiro gisbasedanalysisforuavsupportedfieldexperimentsrevealssoybeantraitsassociatedwithrotationalbenefit
AT ootsukashinjiro gisbasedanalysisforuavsupportedfieldexperimentsrevealssoybeantraitsassociatedwithrotationalbenefit
AT noshitakoji gisbasedanalysisforuavsupportedfieldexperimentsrevealssoybeantraitsassociatedwithrotationalbenefit
AT uchidakei gisbasedanalysisforuavsupportedfieldexperimentsrevealssoybeantraitsassociatedwithrotationalbenefit
AT katoyoichiro gisbasedanalysisforuavsupportedfieldexperimentsrevealssoybeantraitsassociatedwithrotationalbenefit
AT sasakikazuhiro gisbasedanalysisforuavsupportedfieldexperimentsrevealssoybeantraitsassociatedwithrotationalbenefit
AT kamikawashotaka gisbasedanalysisforuavsupportedfieldexperimentsrevealssoybeantraitsassociatedwithrotationalbenefit
AT kubotahirofumi gisbasedanalysisforuavsupportedfieldexperimentsrevealssoybeantraitsassociatedwithrotationalbenefit