Cargando…

Prediction of heading date, culm length, and biomass from canopy-height-related parameters derived from time-series UAV observations of rice

Unmanned aerial vehicles (UAVs) are powerful tools for monitoring crops for high-throughput phenotyping. Time-series aerial photography of fields can record the whole process of crop growth. Canopy height (CH), which is vertical plant growth, has been used as an indicator for the evaluation of lodgi...

Descripción completa

Detalles Bibliográficos
Autores principales: Taniguchi, Shoji, Sakamoto, Toshihiro, Imase, Ryoji, Nonoue, Yasunori, Tsunematsu, Hiroshi, Goto, Akitoshi, Matsushita, Kei, Ohmori, Sinnosuke, Maeda, Hideo, Takeuchi, Yoshinobu, Ishii, Takuro, Yonemaru, Jun-ichi, Ogawa, Daisuke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9792801/
https://www.ncbi.nlm.nih.gov/pubmed/36582650
http://dx.doi.org/10.3389/fpls.2022.998803
_version_ 1784859712451248128
author Taniguchi, Shoji
Sakamoto, Toshihiro
Imase, Ryoji
Nonoue, Yasunori
Tsunematsu, Hiroshi
Goto, Akitoshi
Matsushita, Kei
Ohmori, Sinnosuke
Maeda, Hideo
Takeuchi, Yoshinobu
Ishii, Takuro
Yonemaru, Jun-ichi
Ogawa, Daisuke
author_facet Taniguchi, Shoji
Sakamoto, Toshihiro
Imase, Ryoji
Nonoue, Yasunori
Tsunematsu, Hiroshi
Goto, Akitoshi
Matsushita, Kei
Ohmori, Sinnosuke
Maeda, Hideo
Takeuchi, Yoshinobu
Ishii, Takuro
Yonemaru, Jun-ichi
Ogawa, Daisuke
author_sort Taniguchi, Shoji
collection PubMed
description Unmanned aerial vehicles (UAVs) are powerful tools for monitoring crops for high-throughput phenotyping. Time-series aerial photography of fields can record the whole process of crop growth. Canopy height (CH), which is vertical plant growth, has been used as an indicator for the evaluation of lodging tolerance and the prediction of biomass and yield. However, there have been few attempts to use UAV-derived time-series CH data for field testing of crop lines. Here we provide a novel framework for trait prediction using CH data in rice. We generated UAV-based digital surface models of crops to extract CH data of 30 Japanese rice cultivars in 2019, 2020, and 2021. CH-related parameters were calculated in a non-linear time-series model as an S-shaped plant growth curve. The maximum saturation CH value was the most important predictor for culm length. The time point at the maximum CH contributed to the prediction of days to heading, and was able to predict stem and leaf weight and aboveground weight, possibly reflecting the association of biomass with duration of vegetative growth. These results indicate that the CH-related parameters acquired by UAV can be useful as predictors of traits typically measured by hand.
format Online
Article
Text
id pubmed-9792801
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-97928012022-12-28 Prediction of heading date, culm length, and biomass from canopy-height-related parameters derived from time-series UAV observations of rice Taniguchi, Shoji Sakamoto, Toshihiro Imase, Ryoji Nonoue, Yasunori Tsunematsu, Hiroshi Goto, Akitoshi Matsushita, Kei Ohmori, Sinnosuke Maeda, Hideo Takeuchi, Yoshinobu Ishii, Takuro Yonemaru, Jun-ichi Ogawa, Daisuke Front Plant Sci Plant Science Unmanned aerial vehicles (UAVs) are powerful tools for monitoring crops for high-throughput phenotyping. Time-series aerial photography of fields can record the whole process of crop growth. Canopy height (CH), which is vertical plant growth, has been used as an indicator for the evaluation of lodging tolerance and the prediction of biomass and yield. However, there have been few attempts to use UAV-derived time-series CH data for field testing of crop lines. Here we provide a novel framework for trait prediction using CH data in rice. We generated UAV-based digital surface models of crops to extract CH data of 30 Japanese rice cultivars in 2019, 2020, and 2021. CH-related parameters were calculated in a non-linear time-series model as an S-shaped plant growth curve. The maximum saturation CH value was the most important predictor for culm length. The time point at the maximum CH contributed to the prediction of days to heading, and was able to predict stem and leaf weight and aboveground weight, possibly reflecting the association of biomass with duration of vegetative growth. These results indicate that the CH-related parameters acquired by UAV can be useful as predictors of traits typically measured by hand. Frontiers Media S.A. 2022-12-13 /pmc/articles/PMC9792801/ /pubmed/36582650 http://dx.doi.org/10.3389/fpls.2022.998803 Text en Copyright © 2022 Taniguchi, Sakamoto, Imase, Nonoue, Tsunematsu, Goto, Matsushita, Ohmori, Maeda, Takeuchi, Ishii, Yonemaru and Ogawa 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
Taniguchi, Shoji
Sakamoto, Toshihiro
Imase, Ryoji
Nonoue, Yasunori
Tsunematsu, Hiroshi
Goto, Akitoshi
Matsushita, Kei
Ohmori, Sinnosuke
Maeda, Hideo
Takeuchi, Yoshinobu
Ishii, Takuro
Yonemaru, Jun-ichi
Ogawa, Daisuke
Prediction of heading date, culm length, and biomass from canopy-height-related parameters derived from time-series UAV observations of rice
title Prediction of heading date, culm length, and biomass from canopy-height-related parameters derived from time-series UAV observations of rice
title_full Prediction of heading date, culm length, and biomass from canopy-height-related parameters derived from time-series UAV observations of rice
title_fullStr Prediction of heading date, culm length, and biomass from canopy-height-related parameters derived from time-series UAV observations of rice
title_full_unstemmed Prediction of heading date, culm length, and biomass from canopy-height-related parameters derived from time-series UAV observations of rice
title_short Prediction of heading date, culm length, and biomass from canopy-height-related parameters derived from time-series UAV observations of rice
title_sort prediction of heading date, culm length, and biomass from canopy-height-related parameters derived from time-series uav observations of rice
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9792801/
https://www.ncbi.nlm.nih.gov/pubmed/36582650
http://dx.doi.org/10.3389/fpls.2022.998803
work_keys_str_mv AT taniguchishoji predictionofheadingdateculmlengthandbiomassfromcanopyheightrelatedparametersderivedfromtimeseriesuavobservationsofrice
AT sakamototoshihiro predictionofheadingdateculmlengthandbiomassfromcanopyheightrelatedparametersderivedfromtimeseriesuavobservationsofrice
AT imaseryoji predictionofheadingdateculmlengthandbiomassfromcanopyheightrelatedparametersderivedfromtimeseriesuavobservationsofrice
AT nonoueyasunori predictionofheadingdateculmlengthandbiomassfromcanopyheightrelatedparametersderivedfromtimeseriesuavobservationsofrice
AT tsunematsuhiroshi predictionofheadingdateculmlengthandbiomassfromcanopyheightrelatedparametersderivedfromtimeseriesuavobservationsofrice
AT gotoakitoshi predictionofheadingdateculmlengthandbiomassfromcanopyheightrelatedparametersderivedfromtimeseriesuavobservationsofrice
AT matsushitakei predictionofheadingdateculmlengthandbiomassfromcanopyheightrelatedparametersderivedfromtimeseriesuavobservationsofrice
AT ohmorisinnosuke predictionofheadingdateculmlengthandbiomassfromcanopyheightrelatedparametersderivedfromtimeseriesuavobservationsofrice
AT maedahideo predictionofheadingdateculmlengthandbiomassfromcanopyheightrelatedparametersderivedfromtimeseriesuavobservationsofrice
AT takeuchiyoshinobu predictionofheadingdateculmlengthandbiomassfromcanopyheightrelatedparametersderivedfromtimeseriesuavobservationsofrice
AT ishiitakuro predictionofheadingdateculmlengthandbiomassfromcanopyheightrelatedparametersderivedfromtimeseriesuavobservationsofrice
AT yonemarujunichi predictionofheadingdateculmlengthandbiomassfromcanopyheightrelatedparametersderivedfromtimeseriesuavobservationsofrice
AT ogawadaisuke predictionofheadingdateculmlengthandbiomassfromcanopyheightrelatedparametersderivedfromtimeseriesuavobservationsofrice