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Hyperspectral time series datasets of maize during the grain filling period
OBJECTIVES: Remotely sensed hyperspectral data are increasingly being used to assess crop development and growth throughout the growing season. Large datasets capturing key growth stages can be useful to researchers studying many physiological plant responses. A time series analysis of hyperspectral...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9052440/ https://www.ncbi.nlm.nih.gov/pubmed/35488318 http://dx.doi.org/10.1186/s13104-022-06029-9 |
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author | Craig, Valerie Earl, Hugh Sulik, John Lee, Elizabeth A. |
author_facet | Craig, Valerie Earl, Hugh Sulik, John Lee, Elizabeth A. |
author_sort | Craig, Valerie |
collection | PubMed |
description | OBJECTIVES: Remotely sensed hyperspectral data are increasingly being used to assess crop development and growth throughout the growing season. Large datasets capturing key growth stages can be useful to researchers studying many physiological plant responses. A time series analysis of hyperspectral reflectance measurements taken during the grain filling period and published within a publicly accessible database are described herein. These datasets document the spectral reflectance pattern of the canopy within the visible and near-infrared portion of the electromagnetic spectrum during the late stages of the grain filling period as plants approach and reach physiological maturity. DATA DESCRIPTION: Included within the data repository are canopy-level hyperspectral datasets collected in 2017 and 2018. Data is included in its raw form, as well as with several manipulations to smooth and standardize the raw data. Data are released as comma separated value spreadsheets as well as Microsoft Excel open XLSX spreadsheets. These are accompanied by README text files which further describe the data and supplemental files that record hybrids used and plant phenology for each year of data collection. |
format | Online Article Text |
id | pubmed-9052440 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-90524402022-04-30 Hyperspectral time series datasets of maize during the grain filling period Craig, Valerie Earl, Hugh Sulik, John Lee, Elizabeth A. BMC Res Notes Data Note OBJECTIVES: Remotely sensed hyperspectral data are increasingly being used to assess crop development and growth throughout the growing season. Large datasets capturing key growth stages can be useful to researchers studying many physiological plant responses. A time series analysis of hyperspectral reflectance measurements taken during the grain filling period and published within a publicly accessible database are described herein. These datasets document the spectral reflectance pattern of the canopy within the visible and near-infrared portion of the electromagnetic spectrum during the late stages of the grain filling period as plants approach and reach physiological maturity. DATA DESCRIPTION: Included within the data repository are canopy-level hyperspectral datasets collected in 2017 and 2018. Data is included in its raw form, as well as with several manipulations to smooth and standardize the raw data. Data are released as comma separated value spreadsheets as well as Microsoft Excel open XLSX spreadsheets. These are accompanied by README text files which further describe the data and supplemental files that record hybrids used and plant phenology for each year of data collection. BioMed Central 2022-04-29 /pmc/articles/PMC9052440/ /pubmed/35488318 http://dx.doi.org/10.1186/s13104-022-06029-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Data Note Craig, Valerie Earl, Hugh Sulik, John Lee, Elizabeth A. Hyperspectral time series datasets of maize during the grain filling period |
title | Hyperspectral time series datasets of maize during the grain filling period |
title_full | Hyperspectral time series datasets of maize during the grain filling period |
title_fullStr | Hyperspectral time series datasets of maize during the grain filling period |
title_full_unstemmed | Hyperspectral time series datasets of maize during the grain filling period |
title_short | Hyperspectral time series datasets of maize during the grain filling period |
title_sort | hyperspectral time series datasets of maize during the grain filling period |
topic | Data Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9052440/ https://www.ncbi.nlm.nih.gov/pubmed/35488318 http://dx.doi.org/10.1186/s13104-022-06029-9 |
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