Simulation models on the ecology and management of arable weeds structure, quantitative insights, and applications

Simulation models on the ecology and management of arable weeds structure, quantitative insights, and applications

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In weed science and management, models are important and can be used to better understand what has occurred in management scenarios, to predict what will happen and to evaluate the outcomes of control methods. To-date, perspectives on and the understanding of weed models have been disjointed, especially in terms of how they have been applied to advance weed science and management. This paper presents a general overview of the nature and application of a full range of simulation models on the ecology, biology, and management of arable weeds, and how they have been used to provide insights and directions for decision making when long-term weed population trajectories are impractical to be determined using field experimentation. While research on weed biology and ecology has gained momentum over the past four decades, especially for species with high risk for herbicide resistance evolution, knowledge gaps still exist for several life cycle parameters for many agriculturally important weed species. More research efforts should be invested in filling these knowledge gaps, which will lead to better models and ultimately better inform weed management decision making.

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Main Authors: Bagavathiannan, Muthukumar V., Beckie, Hugh J., Chantre, Guillermo Rubén, González Andújar, José L., León, Ramón G., Neve, Paul, Poggio, Santiago Luis, Schutte, Brian J.
Format: Texto biblioteca
Language:eng
Subjects:WEED SEEDLING EMERGENCE, CROP - WEED COMPETITION, WEED POPULATION DYNAMICS, GENE FLOW, HERBICIDE RESISTANCE, DECISION - SUPPORT TOOLS, PREDICTIVE MODELS, ,
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spelling KOHA-OAI-AGRO:544682023-09-20T10:18:31Zhttp://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=54468http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=AAGSimulation models on the ecology and management of arable weeds structure, quantitative insights, and applicationsBagavathiannan, Muthukumar V.Beckie, Hugh J.Chantre, Guillermo RubénGonzález Andújar, José L.León, Ramón G.Neve, PaulPoggio, Santiago LuisSchutte, Brian J.textengapplication/pdfIn weed science and management, models are important and can be used to better understand what has occurred in management scenarios, to predict what will happen and to evaluate the outcomes of control methods. To-date, perspectives on and the understanding of weed models have been disjointed, especially in terms of how they have been applied to advance weed science and management. This paper presents a general overview of the nature and application of a full range of simulation models on the ecology, biology, and management of arable weeds, and how they have been used to provide insights and directions for decision making when long-term weed population trajectories are impractical to be determined using field experimentation. While research on weed biology and ecology has gained momentum over the past four decades, especially for species with high risk for herbicide resistance evolution, knowledge gaps still exist for several life cycle parameters for many agriculturally important weed species. More research efforts should be invested in filling these knowledge gaps, which will lead to better models and ultimately better inform weed management decision making.In weed science and management, models are important and can be used to better understand what has occurred in management scenarios, to predict what will happen and to evaluate the outcomes of control methods. To-date, perspectives on and the understanding of weed models have been disjointed, especially in terms of how they have been applied to advance weed science and management. This paper presents a general overview of the nature and application of a full range of simulation models on the ecology, biology, and management of arable weeds, and how they have been used to provide insights and directions for decision making when long-term weed population trajectories are impractical to be determined using field experimentation. While research on weed biology and ecology has gained momentum over the past four decades, especially for species with high risk for herbicide resistance evolution, knowledge gaps still exist for several life cycle parameters for many agriculturally important weed species. More research efforts should be invested in filling these knowledge gaps, which will lead to better models and ultimately better inform weed management decision making.WEED SEEDLING EMERGENCECROP - WEED COMPETITIONWEED POPULATION DYNAMICSGENE FLOWHERBICIDE RESISTANCEDECISION - SUPPORT TOOLSPREDICTIVE MODELSAgronomy
institution UBA FA
collection Koha
country Argentina
countrycode AR
component Bibliográfico
access En linea
En linea
databasecode cat-ceiba
tag biblioteca
region America del Sur
libraryname Biblioteca Central FAUBA
language eng
topic WEED SEEDLING EMERGENCE
CROP - WEED COMPETITION
WEED POPULATION DYNAMICS
GENE FLOW
HERBICIDE RESISTANCE
DECISION - SUPPORT TOOLS
PREDICTIVE MODELS

WEED SEEDLING EMERGENCE
CROP - WEED COMPETITION
WEED POPULATION DYNAMICS
GENE FLOW
HERBICIDE RESISTANCE
DECISION - SUPPORT TOOLS
PREDICTIVE MODELS
spellingShingle WEED SEEDLING EMERGENCE
CROP - WEED COMPETITION
WEED POPULATION DYNAMICS
GENE FLOW
HERBICIDE RESISTANCE
DECISION - SUPPORT TOOLS
PREDICTIVE MODELS

WEED SEEDLING EMERGENCE
CROP - WEED COMPETITION
WEED POPULATION DYNAMICS
GENE FLOW
HERBICIDE RESISTANCE
DECISION - SUPPORT TOOLS
PREDICTIVE MODELS
Bagavathiannan, Muthukumar V.
Beckie, Hugh J.
Chantre, Guillermo Rubén
González Andújar, José L.
León, Ramón G.
Neve, Paul
Poggio, Santiago Luis
Schutte, Brian J.
Simulation models on the ecology and management of arable weeds structure, quantitative insights, and applications
description In weed science and management, models are important and can be used to better understand what has occurred in management scenarios, to predict what will happen and to evaluate the outcomes of control methods. To-date, perspectives on and the understanding of weed models have been disjointed, especially in terms of how they have been applied to advance weed science and management. This paper presents a general overview of the nature and application of a full range of simulation models on the ecology, biology, and management of arable weeds, and how they have been used to provide insights and directions for decision making when long-term weed population trajectories are impractical to be determined using field experimentation. While research on weed biology and ecology has gained momentum over the past four decades, especially for species with high risk for herbicide resistance evolution, knowledge gaps still exist for several life cycle parameters for many agriculturally important weed species. More research efforts should be invested in filling these knowledge gaps, which will lead to better models and ultimately better inform weed management decision making.
format Texto
topic_facet
WEED SEEDLING EMERGENCE
CROP - WEED COMPETITION
WEED POPULATION DYNAMICS
GENE FLOW
HERBICIDE RESISTANCE
DECISION - SUPPORT TOOLS
PREDICTIVE MODELS
author Bagavathiannan, Muthukumar V.
Beckie, Hugh J.
Chantre, Guillermo Rubén
González Andújar, José L.
León, Ramón G.
Neve, Paul
Poggio, Santiago Luis
Schutte, Brian J.
author_facet Bagavathiannan, Muthukumar V.
Beckie, Hugh J.
Chantre, Guillermo Rubén
González Andújar, José L.
León, Ramón G.
Neve, Paul
Poggio, Santiago Luis
Schutte, Brian J.
author_sort Bagavathiannan, Muthukumar V.
title Simulation models on the ecology and management of arable weeds structure, quantitative insights, and applications
title_short Simulation models on the ecology and management of arable weeds structure, quantitative insights, and applications
title_full Simulation models on the ecology and management of arable weeds structure, quantitative insights, and applications
title_fullStr Simulation models on the ecology and management of arable weeds structure, quantitative insights, and applications
title_full_unstemmed Simulation models on the ecology and management of arable weeds structure, quantitative insights, and applications
title_sort simulation models on the ecology and management of arable weeds structure, quantitative insights, and applications
url http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=54468
http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=
http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=
http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=
http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=
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