Assessing the Impact of Ramularia Leaf Spot on Barley: Prospects for Fungicide Protection Strategies and Weather-Based Prediction Models in Argentina

Autores
Erreguerena, Ignacio Antonio; Quiroz, Facundo Jose; Cambareri, Matias; Pereyra, Silvia; Havis, Neil David; Carmona, Marcelo Anibal
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Ramularia leaf spot (RLS), caused by the fungus Ramularia collo-cygni (Rcc), has become a threat to barley production in Argentina and the world, causing grain yield and quality losses. Characteristics of the pathogen such as a long latency period, high evolutionary potential, numerous transposonic regions and the ability to infect alternative hosts facilitate Rcc adaption to environmental changes and/or control measures such as fungicides. RLS is considered a sporadic disease in Argentina and its occurrence is highly dependent on weather conditions. The objectives of this work were to quantify the impact of RLS on grain yield and its commercial quality, to establish an optimal protection period (PP) for barley with fungicides, and to describe the association between environmental variables and levels of RLS with the purpose of designing prediction models and more efficient protection strategies. Based on the results from field trials (n = 8), we estimated grain yield losses up to 16%, and these occurred due to reduced grain weight (8.7%) and size (20%). We also determined that the PP begins from the third detectable node (GS33) to first visible awns (GS49) and concluded that the flag leaf fully emerged stage (GS39) was the most efficient fungicide spraying time. Four possible forecast models were proposed based on the daily average temperature accumulated from early tillering (GS21) to GS39 stage, in combination with the number of days of soil water availability, number of days with water excess and duration of leaf wetness or accumulated rainfall from tillering to GS39 (n = 10).
EEA Manfredi
Fil: Erreguerena, Ignacio Antonio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; Argentina
Fil: Quiroz, Facundo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Cambareri, Matías. Caburė AgTech; Argentina
Fil: Pereyra, Silvia. Instituto Nacional de Investigación Agropecuaria (INIA). INIA La Estanzuela; Uruguay
Fil: Havis, Neil David. Scotland’s Rural College. Crop and Soil Research Group; Reino Unido
Fil: Carmona, Marcelo Anibal. Universidad de Buenos Aires. Facultad de Agronomía. Catedra de Fitopatología; Argentina
Fuente
Plant Pathology 74 (3) : 858-872. (April 2025)
Materia
Cebada
Fungicidas
Pronóstico del Tiempo
Hongos
Barley
Ramularia
Fungicides
Weather Forecasting
Fungi
Argentina
Ramularia collo-cygni
Nivel de accesibilidad
acceso restringido
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/21948
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oai_identifier_str oai:localhost:20.500.12123/21948
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spelling Assessing the Impact of Ramularia Leaf Spot on Barley: Prospects for Fungicide Protection Strategies and Weather-Based Prediction Models in ArgentinaErreguerena, Ignacio AntonioQuiroz, Facundo JoseCambareri, MatiasPereyra, SilviaHavis, Neil DavidCarmona, Marcelo AnibalCebadaFungicidasPronóstico del TiempoHongosBarleyRamulariaFungicidesWeather ForecastingFungiArgentinaRamularia collo-cygniRamularia leaf spot (RLS), caused by the fungus Ramularia collo-cygni (Rcc), has become a threat to barley production in Argentina and the world, causing grain yield and quality losses. Characteristics of the pathogen such as a long latency period, high evolutionary potential, numerous transposonic regions and the ability to infect alternative hosts facilitate Rcc adaption to environmental changes and/or control measures such as fungicides. RLS is considered a sporadic disease in Argentina and its occurrence is highly dependent on weather conditions. The objectives of this work were to quantify the impact of RLS on grain yield and its commercial quality, to establish an optimal protection period (PP) for barley with fungicides, and to describe the association between environmental variables and levels of RLS with the purpose of designing prediction models and more efficient protection strategies. Based on the results from field trials (n = 8), we estimated grain yield losses up to 16%, and these occurred due to reduced grain weight (8.7%) and size (20%). We also determined that the PP begins from the third detectable node (GS33) to first visible awns (GS49) and concluded that the flag leaf fully emerged stage (GS39) was the most efficient fungicide spraying time. Four possible forecast models were proposed based on the daily average temperature accumulated from early tillering (GS21) to GS39 stage, in combination with the number of days of soil water availability, number of days with water excess and duration of leaf wetness or accumulated rainfall from tillering to GS39 (n = 10).EEA ManfrediFil: Erreguerena, Ignacio Antonio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; ArgentinaFil: Quiroz, Facundo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; ArgentinaFil: Cambareri, Matías. Caburė AgTech; ArgentinaFil: Pereyra, Silvia. Instituto Nacional de Investigación Agropecuaria (INIA). INIA La Estanzuela; UruguayFil: Havis, Neil David. Scotland’s Rural College. Crop and Soil Research Group; Reino UnidoFil: Carmona, Marcelo Anibal. Universidad de Buenos Aires. Facultad de Agronomía. Catedra de Fitopatología; ArgentinaWiley2025-04-08T12:24:12Z2025-04-08T12:24:12Z2025-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/21948https://bsppjournals.onlinelibrary.wiley.com/doi/10.1111/ppa.140560032-08621365-3059https://doi.org/10.1111/ppa.14056Plant Pathology 74 (3) : 858-872. (April 2025)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/restrictedAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-09-29T13:47:14Zoai:localhost:20.500.12123/21948instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-29 13:47:14.608INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Assessing the Impact of Ramularia Leaf Spot on Barley: Prospects for Fungicide Protection Strategies and Weather-Based Prediction Models in Argentina
title Assessing the Impact of Ramularia Leaf Spot on Barley: Prospects for Fungicide Protection Strategies and Weather-Based Prediction Models in Argentina
spellingShingle Assessing the Impact of Ramularia Leaf Spot on Barley: Prospects for Fungicide Protection Strategies and Weather-Based Prediction Models in Argentina
Erreguerena, Ignacio Antonio
Cebada
Fungicidas
Pronóstico del Tiempo
Hongos
Barley
Ramularia
Fungicides
Weather Forecasting
Fungi
Argentina
Ramularia collo-cygni
title_short Assessing the Impact of Ramularia Leaf Spot on Barley: Prospects for Fungicide Protection Strategies and Weather-Based Prediction Models in Argentina
title_full Assessing the Impact of Ramularia Leaf Spot on Barley: Prospects for Fungicide Protection Strategies and Weather-Based Prediction Models in Argentina
title_fullStr Assessing the Impact of Ramularia Leaf Spot on Barley: Prospects for Fungicide Protection Strategies and Weather-Based Prediction Models in Argentina
title_full_unstemmed Assessing the Impact of Ramularia Leaf Spot on Barley: Prospects for Fungicide Protection Strategies and Weather-Based Prediction Models in Argentina
title_sort Assessing the Impact of Ramularia Leaf Spot on Barley: Prospects for Fungicide Protection Strategies and Weather-Based Prediction Models in Argentina
dc.creator.none.fl_str_mv Erreguerena, Ignacio Antonio
Quiroz, Facundo Jose
Cambareri, Matias
Pereyra, Silvia
Havis, Neil David
Carmona, Marcelo Anibal
author Erreguerena, Ignacio Antonio
author_facet Erreguerena, Ignacio Antonio
Quiroz, Facundo Jose
Cambareri, Matias
Pereyra, Silvia
Havis, Neil David
Carmona, Marcelo Anibal
author_role author
author2 Quiroz, Facundo Jose
Cambareri, Matias
Pereyra, Silvia
Havis, Neil David
Carmona, Marcelo Anibal
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Cebada
Fungicidas
Pronóstico del Tiempo
Hongos
Barley
Ramularia
Fungicides
Weather Forecasting
Fungi
Argentina
Ramularia collo-cygni
topic Cebada
Fungicidas
Pronóstico del Tiempo
Hongos
Barley
Ramularia
Fungicides
Weather Forecasting
Fungi
Argentina
Ramularia collo-cygni
dc.description.none.fl_txt_mv Ramularia leaf spot (RLS), caused by the fungus Ramularia collo-cygni (Rcc), has become a threat to barley production in Argentina and the world, causing grain yield and quality losses. Characteristics of the pathogen such as a long latency period, high evolutionary potential, numerous transposonic regions and the ability to infect alternative hosts facilitate Rcc adaption to environmental changes and/or control measures such as fungicides. RLS is considered a sporadic disease in Argentina and its occurrence is highly dependent on weather conditions. The objectives of this work were to quantify the impact of RLS on grain yield and its commercial quality, to establish an optimal protection period (PP) for barley with fungicides, and to describe the association between environmental variables and levels of RLS with the purpose of designing prediction models and more efficient protection strategies. Based on the results from field trials (n = 8), we estimated grain yield losses up to 16%, and these occurred due to reduced grain weight (8.7%) and size (20%). We also determined that the PP begins from the third detectable node (GS33) to first visible awns (GS49) and concluded that the flag leaf fully emerged stage (GS39) was the most efficient fungicide spraying time. Four possible forecast models were proposed based on the daily average temperature accumulated from early tillering (GS21) to GS39 stage, in combination with the number of days of soil water availability, number of days with water excess and duration of leaf wetness or accumulated rainfall from tillering to GS39 (n = 10).
EEA Manfredi
Fil: Erreguerena, Ignacio Antonio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; Argentina
Fil: Quiroz, Facundo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Cambareri, Matías. Caburė AgTech; Argentina
Fil: Pereyra, Silvia. Instituto Nacional de Investigación Agropecuaria (INIA). INIA La Estanzuela; Uruguay
Fil: Havis, Neil David. Scotland’s Rural College. Crop and Soil Research Group; Reino Unido
Fil: Carmona, Marcelo Anibal. Universidad de Buenos Aires. Facultad de Agronomía. Catedra de Fitopatología; Argentina
description Ramularia leaf spot (RLS), caused by the fungus Ramularia collo-cygni (Rcc), has become a threat to barley production in Argentina and the world, causing grain yield and quality losses. Characteristics of the pathogen such as a long latency period, high evolutionary potential, numerous transposonic regions and the ability to infect alternative hosts facilitate Rcc adaption to environmental changes and/or control measures such as fungicides. RLS is considered a sporadic disease in Argentina and its occurrence is highly dependent on weather conditions. The objectives of this work were to quantify the impact of RLS on grain yield and its commercial quality, to establish an optimal protection period (PP) for barley with fungicides, and to describe the association between environmental variables and levels of RLS with the purpose of designing prediction models and more efficient protection strategies. Based on the results from field trials (n = 8), we estimated grain yield losses up to 16%, and these occurred due to reduced grain weight (8.7%) and size (20%). We also determined that the PP begins from the third detectable node (GS33) to first visible awns (GS49) and concluded that the flag leaf fully emerged stage (GS39) was the most efficient fungicide spraying time. Four possible forecast models were proposed based on the daily average temperature accumulated from early tillering (GS21) to GS39 stage, in combination with the number of days of soil water availability, number of days with water excess and duration of leaf wetness or accumulated rainfall from tillering to GS39 (n = 10).
publishDate 2025
dc.date.none.fl_str_mv 2025-04-08T12:24:12Z
2025-04-08T12:24:12Z
2025-04
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12123/21948
https://bsppjournals.onlinelibrary.wiley.com/doi/10.1111/ppa.14056
0032-0862
1365-3059
https://doi.org/10.1111/ppa.14056
url http://hdl.handle.net/20.500.12123/21948
https://bsppjournals.onlinelibrary.wiley.com/doi/10.1111/ppa.14056
https://doi.org/10.1111/ppa.14056
identifier_str_mv 0032-0862
1365-3059
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/restrictedAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv restrictedAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
dc.source.none.fl_str_mv Plant Pathology 74 (3) : 858-872. (April 2025)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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