Prediction of Italian ryegrass (Lolium multiflorum L.) emergence using soil thermal time

ABSTRACT Italian ryegrass (Lolium multiflorum L.) is a highly competitive weed widely disseminated worldwide that affects both summer and winter crops. The development of predictive emergence models can contribute to optimizing weed management. The aim of this study was to develop and validate an empirical emergence model of Italian ryegrass based on soil thermal time. For model development, cumulative emergence in two locations was obtained, and the model was validated with data collected in an experiment conducted independently. Three commonly used emergence models were compared (Gompertz, Logistic, and Weibull). The relationship between emergence and soil thermal time was described best by the Gompertz model. The Gompertz model predicted Italian ryegrass emergence start at 300 thermal time (TT), reaching 50% emergence at 444 TT, and 90% at 590 TT. Model validation performed well in predicting Italian ryegrass emergence and proved to be efficient at describing its emergence. This is a potential predictive tool for assisting farmers with Italian ryegrass management.

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Main Authors: Pagnoncelli Junior,Fortunato de Bortoli, Trezzi,Michelangelo Muzell, Salomão,Helis Marina, Hartmann,Katia Cristina, Gonzalez-Andujar,Jose Luis
Format: Digital revista
Language:English
Published: Editora da Universidade Estadual de Maringá - EDUEM 2021
Online Access:http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-86212021000105030
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spelling oai:scielo:S1807-862120210001050302021-09-20Prediction of Italian ryegrass (Lolium multiflorum L.) emergence using soil thermal timePagnoncelli Junior,Fortunato de BortoliTrezzi,Michelangelo MuzellSalomão,Helis MarinaHartmann,Katia CristinaGonzalez-Andujar,Jose Luis Gompertz model logistic model Weibull model soil temperature weed management ABSTRACT Italian ryegrass (Lolium multiflorum L.) is a highly competitive weed widely disseminated worldwide that affects both summer and winter crops. The development of predictive emergence models can contribute to optimizing weed management. The aim of this study was to develop and validate an empirical emergence model of Italian ryegrass based on soil thermal time. For model development, cumulative emergence in two locations was obtained, and the model was validated with data collected in an experiment conducted independently. Three commonly used emergence models were compared (Gompertz, Logistic, and Weibull). The relationship between emergence and soil thermal time was described best by the Gompertz model. The Gompertz model predicted Italian ryegrass emergence start at 300 thermal time (TT), reaching 50% emergence at 444 TT, and 90% at 590 TT. Model validation performed well in predicting Italian ryegrass emergence and proved to be efficient at describing its emergence. This is a potential predictive tool for assisting farmers with Italian ryegrass management.info:eu-repo/semantics/openAccessEditora da Universidade Estadual de Maringá - EDUEMActa Scientiarum. Agronomy v.43 20212021-01-01info:eu-repo/semantics/articletext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-86212021000105030en10.4025/actasciagron.v43i1.52152
institution SCIELO
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country Brasil
countrycode BR
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region America del Sur
libraryname SciELO
language English
format Digital
author Pagnoncelli Junior,Fortunato de Bortoli
Trezzi,Michelangelo Muzell
Salomão,Helis Marina
Hartmann,Katia Cristina
Gonzalez-Andujar,Jose Luis
spellingShingle Pagnoncelli Junior,Fortunato de Bortoli
Trezzi,Michelangelo Muzell
Salomão,Helis Marina
Hartmann,Katia Cristina
Gonzalez-Andujar,Jose Luis
Prediction of Italian ryegrass (Lolium multiflorum L.) emergence using soil thermal time
author_facet Pagnoncelli Junior,Fortunato de Bortoli
Trezzi,Michelangelo Muzell
Salomão,Helis Marina
Hartmann,Katia Cristina
Gonzalez-Andujar,Jose Luis
author_sort Pagnoncelli Junior,Fortunato de Bortoli
title Prediction of Italian ryegrass (Lolium multiflorum L.) emergence using soil thermal time
title_short Prediction of Italian ryegrass (Lolium multiflorum L.) emergence using soil thermal time
title_full Prediction of Italian ryegrass (Lolium multiflorum L.) emergence using soil thermal time
title_fullStr Prediction of Italian ryegrass (Lolium multiflorum L.) emergence using soil thermal time
title_full_unstemmed Prediction of Italian ryegrass (Lolium multiflorum L.) emergence using soil thermal time
title_sort prediction of italian ryegrass (lolium multiflorum l.) emergence using soil thermal time
description ABSTRACT Italian ryegrass (Lolium multiflorum L.) is a highly competitive weed widely disseminated worldwide that affects both summer and winter crops. The development of predictive emergence models can contribute to optimizing weed management. The aim of this study was to develop and validate an empirical emergence model of Italian ryegrass based on soil thermal time. For model development, cumulative emergence in two locations was obtained, and the model was validated with data collected in an experiment conducted independently. Three commonly used emergence models were compared (Gompertz, Logistic, and Weibull). The relationship between emergence and soil thermal time was described best by the Gompertz model. The Gompertz model predicted Italian ryegrass emergence start at 300 thermal time (TT), reaching 50% emergence at 444 TT, and 90% at 590 TT. Model validation performed well in predicting Italian ryegrass emergence and proved to be efficient at describing its emergence. This is a potential predictive tool for assisting farmers with Italian ryegrass management.
publisher Editora da Universidade Estadual de Maringá - EDUEM
publishDate 2021
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-86212021000105030
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