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Weather Patterns Associated with DON Levels in Norwegian Spring Oat Grain: A Functional Data Approach
Fusarium graminearum is regarded as the main deoxynivalenol (DON) producer in Norwegian oats, and high levels of DON are occasionally recorded in oat grains. Weather conditions in the period around flowering are reported to have a high impact on the development of Fusarium head blight (FHB) and DON...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747184/ https://www.ncbi.nlm.nih.gov/pubmed/35009077 http://dx.doi.org/10.3390/plants11010073 |
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author | Hjelkrem, Anne-Grete Roer Aamot, Heidi Udnes Lillemo, Morten Sørensen, Espen Sannes Brodal, Guro Russenes, Aina Lundon Edwards, Simon G. Hofgaard, Ingerd Skow |
author_facet | Hjelkrem, Anne-Grete Roer Aamot, Heidi Udnes Lillemo, Morten Sørensen, Espen Sannes Brodal, Guro Russenes, Aina Lundon Edwards, Simon G. Hofgaard, Ingerd Skow |
author_sort | Hjelkrem, Anne-Grete Roer |
collection | PubMed |
description | Fusarium graminearum is regarded as the main deoxynivalenol (DON) producer in Norwegian oats, and high levels of DON are occasionally recorded in oat grains. Weather conditions in the period around flowering are reported to have a high impact on the development of Fusarium head blight (FHB) and DON in cereal grains. Thus, it would be advantageous if the risk of DON contamination of oat grains could be predicted based on weather data. We conducted a functional data analysis of weather-based time series data linked to DON content in order to identify weather patterns associated with increased DON levels. Since flowering date was not recorded in our dataset, a mathematical model was developed to predict phenological growth stages in Norwegian spring oats. Through functional data analysis, weather patterns associated with DON content in the harvested grain were revealed mainly from about three weeks pre-flowering onwards. Oat fields with elevated DON levels generally had warmer weather around sowing, and lower temperatures and higher relative humidity or rain prior to flowering onwards, compared to fields with low DON levels. Our results are in line with results from similar studies presented for FHB epidemics in wheat. Functional data analysis was found to be a useful tool to reveal weather patterns of importance for DON development in oats. |
format | Online Article Text |
id | pubmed-8747184 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87471842022-01-11 Weather Patterns Associated with DON Levels in Norwegian Spring Oat Grain: A Functional Data Approach Hjelkrem, Anne-Grete Roer Aamot, Heidi Udnes Lillemo, Morten Sørensen, Espen Sannes Brodal, Guro Russenes, Aina Lundon Edwards, Simon G. Hofgaard, Ingerd Skow Plants (Basel) Article Fusarium graminearum is regarded as the main deoxynivalenol (DON) producer in Norwegian oats, and high levels of DON are occasionally recorded in oat grains. Weather conditions in the period around flowering are reported to have a high impact on the development of Fusarium head blight (FHB) and DON in cereal grains. Thus, it would be advantageous if the risk of DON contamination of oat grains could be predicted based on weather data. We conducted a functional data analysis of weather-based time series data linked to DON content in order to identify weather patterns associated with increased DON levels. Since flowering date was not recorded in our dataset, a mathematical model was developed to predict phenological growth stages in Norwegian spring oats. Through functional data analysis, weather patterns associated with DON content in the harvested grain were revealed mainly from about three weeks pre-flowering onwards. Oat fields with elevated DON levels generally had warmer weather around sowing, and lower temperatures and higher relative humidity or rain prior to flowering onwards, compared to fields with low DON levels. Our results are in line with results from similar studies presented for FHB epidemics in wheat. Functional data analysis was found to be a useful tool to reveal weather patterns of importance for DON development in oats. MDPI 2021-12-27 /pmc/articles/PMC8747184/ /pubmed/35009077 http://dx.doi.org/10.3390/plants11010073 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Hjelkrem, Anne-Grete Roer Aamot, Heidi Udnes Lillemo, Morten Sørensen, Espen Sannes Brodal, Guro Russenes, Aina Lundon Edwards, Simon G. Hofgaard, Ingerd Skow Weather Patterns Associated with DON Levels in Norwegian Spring Oat Grain: A Functional Data Approach |
title | Weather Patterns Associated with DON Levels in Norwegian Spring Oat Grain: A Functional Data Approach |
title_full | Weather Patterns Associated with DON Levels in Norwegian Spring Oat Grain: A Functional Data Approach |
title_fullStr | Weather Patterns Associated with DON Levels in Norwegian Spring Oat Grain: A Functional Data Approach |
title_full_unstemmed | Weather Patterns Associated with DON Levels in Norwegian Spring Oat Grain: A Functional Data Approach |
title_short | Weather Patterns Associated with DON Levels in Norwegian Spring Oat Grain: A Functional Data Approach |
title_sort | weather patterns associated with don levels in norwegian spring oat grain: a functional data approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747184/ https://www.ncbi.nlm.nih.gov/pubmed/35009077 http://dx.doi.org/10.3390/plants11010073 |
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