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Use of an unmanned aerial vehicle for monitoring and prediction of oilseed rape crop performance

The flowering stage of oilseed rape (Brassica napus L.) is of vital interest in precision agriculture. It has been shown that data describing the flower production of oilseed rape (OSR), at stage 3, in spring can be used to predict seed yield at harvest. Traditional field-based techniques for assess...

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Autores principales: Ahmed, Shara, Nicholson, Catherine E., Rutter, Simon R., Marshall, John R., Perry, Justin J., Dean, John R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10637715/
https://www.ncbi.nlm.nih.gov/pubmed/37948466
http://dx.doi.org/10.1371/journal.pone.0294184
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author Ahmed, Shara
Nicholson, Catherine E.
Rutter, Simon R.
Marshall, John R.
Perry, Justin J.
Dean, John R.
author_facet Ahmed, Shara
Nicholson, Catherine E.
Rutter, Simon R.
Marshall, John R.
Perry, Justin J.
Dean, John R.
author_sort Ahmed, Shara
collection PubMed
description The flowering stage of oilseed rape (Brassica napus L.) is of vital interest in precision agriculture. It has been shown that data describing the flower production of oilseed rape (OSR), at stage 3, in spring can be used to predict seed yield at harvest. Traditional field-based techniques for assessing OSR flowers are based on a visual assessment which is subjective and time consuming. However, a high throughput phenotyping technique, using an unmanned aerial vehicle (UAV) with multispectral image (MSI) camera, was used to investigate the growth stages of OSR (in terms of crop height) and to quantify its flower production. A simplified approach using a normalised difference yellowness index (NDYI) was coupled with an iso-cluster classification method to quantify the number of OSR flower pixels and incorporate the data into an OSR seed yield estimation. The estimated OSR seed yield showed strong correlation with the actual OSR seed yield (R(2) = 0.86), as determined using in-situ sensors mounted on the combine harvester. Also, using our approach allowed the variation in crop height to be assessed across all growing stages; the maximum crop height of 1.35 m OSR was observed at the flowering stage. This methodology is proposed for effectively predicting seed yield 3 months prior to harvesting.
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spelling pubmed-106377152023-11-11 Use of an unmanned aerial vehicle for monitoring and prediction of oilseed rape crop performance Ahmed, Shara Nicholson, Catherine E. Rutter, Simon R. Marshall, John R. Perry, Justin J. Dean, John R. PLoS One Research Article The flowering stage of oilseed rape (Brassica napus L.) is of vital interest in precision agriculture. It has been shown that data describing the flower production of oilseed rape (OSR), at stage 3, in spring can be used to predict seed yield at harvest. Traditional field-based techniques for assessing OSR flowers are based on a visual assessment which is subjective and time consuming. However, a high throughput phenotyping technique, using an unmanned aerial vehicle (UAV) with multispectral image (MSI) camera, was used to investigate the growth stages of OSR (in terms of crop height) and to quantify its flower production. A simplified approach using a normalised difference yellowness index (NDYI) was coupled with an iso-cluster classification method to quantify the number of OSR flower pixels and incorporate the data into an OSR seed yield estimation. The estimated OSR seed yield showed strong correlation with the actual OSR seed yield (R(2) = 0.86), as determined using in-situ sensors mounted on the combine harvester. Also, using our approach allowed the variation in crop height to be assessed across all growing stages; the maximum crop height of 1.35 m OSR was observed at the flowering stage. This methodology is proposed for effectively predicting seed yield 3 months prior to harvesting. Public Library of Science 2023-11-10 /pmc/articles/PMC10637715/ /pubmed/37948466 http://dx.doi.org/10.1371/journal.pone.0294184 Text en © 2023 Ahmed et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ahmed, Shara
Nicholson, Catherine E.
Rutter, Simon R.
Marshall, John R.
Perry, Justin J.
Dean, John R.
Use of an unmanned aerial vehicle for monitoring and prediction of oilseed rape crop performance
title Use of an unmanned aerial vehicle for monitoring and prediction of oilseed rape crop performance
title_full Use of an unmanned aerial vehicle for monitoring and prediction of oilseed rape crop performance
title_fullStr Use of an unmanned aerial vehicle for monitoring and prediction of oilseed rape crop performance
title_full_unstemmed Use of an unmanned aerial vehicle for monitoring and prediction of oilseed rape crop performance
title_short Use of an unmanned aerial vehicle for monitoring and prediction of oilseed rape crop performance
title_sort use of an unmanned aerial vehicle for monitoring and prediction of oilseed rape crop performance
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10637715/
https://www.ncbi.nlm.nih.gov/pubmed/37948466
http://dx.doi.org/10.1371/journal.pone.0294184
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