Spatio-temporal distribution of Anthonomus grandis grandis Boh. in tropical cotton fields.

Detalhes bibliográficos
Autor(a) principal: OLIVEIRA, A. A. S.
Data de Publicação: 2022
Outros Autores: ARAÚJO, T. A., SHOWLER, A. T., ARAÚJO, A. C. A., ALMEIDA, I. S., AGUIAR, R. S. A., MIRANDA, J. E., FERNANDES, F. L., BASTOS, C. S.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1146623
Resumo: The boll weevil, Anthonomus grandis grandis Boheman (Coleoptera: Curculionidae), is considered to be the most harmful cotton, Gossypium hirsutum L., pest throughout subtropical, and tropical regions of the western hemisphere.1,2 Boll weevil damages cotton by feeding upon and laying eggs inside its reproductive structures, where hatched larvae feed and pupate,3,4 causing abscission or reduction of fiber quality,3,5,6 and economic losses of up to US$74 million per year.7 Boll weevil chemical control interventions are based on economic thresholds obtained by sampling the plants and for adult boll weevils captured in pheromone-baited traps.3,8,9 In order to develop an accurate monitoring and management program, estimates of population density are essential.10,11 Biotic and abiotic factors affect dynamics and within-field distribution (aggregated, random or uniform patterns) of insect populations.10,12 Knowing a pest's distribution within a field can help to: (1) develop site-specific sampling and control efforts; (2) predict pest movement; (3) improve insecticide-resistance management; (4) conserve biological control agents by precision targeting sprays for the infested areas; and (5) reduce the economic, social and environmental costs associated with pest control.10,11,13 The spatial distribution of boll weevils has been investigated using mean?variance relationships4,14 without considering within-field spatial density distribution, or has been based on pheromone-baited trap captures.15 The most accurate approach is the use of geostatistics because the position of the samples in space is accounted for.16 Recent work reported that geostatistics is of particular interest for pest management because it allows inferences about the minimum inter-sample distance needed to obtain independent estimations and indicates patterns of distribution and colonization of an organism, all of which are crucial for the development of effective sampling programs.11,13 The purpose of this study was to investigate the spatial dynamics of A. grandis grandis on cotton by determining within-field distribution of adults and infested reproductive structures (having feeding and/or oviposition punctures).
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spelling Spatio-temporal distribution of Anthonomus grandis grandis Boh. in tropical cotton fields.HortaliçasBrócolisTomatoSweet potatoSunflowerAlgodãoGossypium HirsutumEntomologiaEstatística AgrícolaPestePraga de PlantaAnthonomus GrandisBicudoClima TropicalRepolhoCenouraMandiocaCouveAlhoTomateGirassolBatata DoceEntomologyCottonGeostatisticsPlant pestsAnthonomus grandis grandisTropical agricultureCabbageCarrotsCassavaGarlicSunflower seed proteinSunflower seed productsVegetablesBroccoliThe boll weevil, Anthonomus grandis grandis Boheman (Coleoptera: Curculionidae), is considered to be the most harmful cotton, Gossypium hirsutum L., pest throughout subtropical, and tropical regions of the western hemisphere.1,2 Boll weevil damages cotton by feeding upon and laying eggs inside its reproductive structures, where hatched larvae feed and pupate,3,4 causing abscission or reduction of fiber quality,3,5,6 and economic losses of up to US$74 million per year.7 Boll weevil chemical control interventions are based on economic thresholds obtained by sampling the plants and for adult boll weevils captured in pheromone-baited traps.3,8,9 In order to develop an accurate monitoring and management program, estimates of population density are essential.10,11 Biotic and abiotic factors affect dynamics and within-field distribution (aggregated, random or uniform patterns) of insect populations.10,12 Knowing a pest's distribution within a field can help to: (1) develop site-specific sampling and control efforts; (2) predict pest movement; (3) improve insecticide-resistance management; (4) conserve biological control agents by precision targeting sprays for the infested areas; and (5) reduce the economic, social and environmental costs associated with pest control.10,11,13 The spatial distribution of boll weevils has been investigated using mean?variance relationships4,14 without considering within-field spatial density distribution, or has been based on pheromone-baited trap captures.15 The most accurate approach is the use of geostatistics because the position of the samples in space is accounted for.16 Recent work reported that geostatistics is of particular interest for pest management because it allows inferences about the minimum inter-sample distance needed to obtain independent estimations and indicates patterns of distribution and colonization of an organism, all of which are crucial for the development of effective sampling programs.11,13 The purpose of this study was to investigate the spatial dynamics of A. grandis grandis on cotton by determining within-field distribution of adults and infested reproductive structures (having feeding and/or oviposition punctures).ANDRÉA A. S. OLIVEIRA, UnB; TAMÍRIS A. ARAÚJO, UFSCar; ALLAN T. SHOWLER, USDA; ANA C. A. ARAÚJO, UnB; IGOR S. ALMEIDA, UnB; RENATA S. A. AGUIAR, UnB; JOSÉ EDNILSON MIRANDA, CNPA; FLÁVIO L. FERNANDES, UFV; CRISTINA S. BASTOS, UnB.OLIVEIRA, A. A. S.ARAÚJO, T. A.SHOWLER, A. T.ARAÚJO, A. C. A.ALMEIDA, I. S.AGUIAR, R. S. A.MIRANDA, J. E.FERNANDES, F. L.BASTOS, C. S.2022-09-20T13:05:20Z2022-09-20T13:05:20Z2022-09-202022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlePest Management Science, v. 78, n. 3, p. 2492-2501, 2022.1526-498xhttp://www.alice.cnptia.embrapa.br/alice/handle/doc/114662310.1002/ps.6880enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2022-09-20T13:05:29Zoai:www.alice.cnptia.embrapa.br:doc/1146623Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542022-09-20T13:05:29falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542022-09-20T13:05:29Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Spatio-temporal distribution of Anthonomus grandis grandis Boh. in tropical cotton fields.
title Spatio-temporal distribution of Anthonomus grandis grandis Boh. in tropical cotton fields.
spellingShingle Spatio-temporal distribution of Anthonomus grandis grandis Boh. in tropical cotton fields.
OLIVEIRA, A. A. S.
Hortaliças
Brócolis
Tomato
Sweet potato
Sunflower
Algodão
Gossypium Hirsutum
Entomologia
Estatística Agrícola
Peste
Praga de Planta
Anthonomus Grandis
Bicudo
Clima Tropical
Repolho
Cenoura
Mandioca
Couve
Alho
Tomate
Girassol
Batata Doce
Entomology
Cotton
Geostatistics
Plant pests
Anthonomus grandis grandis
Tropical agriculture
Cabbage
Carrots
Cassava
Garlic
Sunflower seed protein
Sunflower seed products
Vegetables
Broccoli
title_short Spatio-temporal distribution of Anthonomus grandis grandis Boh. in tropical cotton fields.
title_full Spatio-temporal distribution of Anthonomus grandis grandis Boh. in tropical cotton fields.
title_fullStr Spatio-temporal distribution of Anthonomus grandis grandis Boh. in tropical cotton fields.
title_full_unstemmed Spatio-temporal distribution of Anthonomus grandis grandis Boh. in tropical cotton fields.
title_sort Spatio-temporal distribution of Anthonomus grandis grandis Boh. in tropical cotton fields.
author OLIVEIRA, A. A. S.
author_facet OLIVEIRA, A. A. S.
ARAÚJO, T. A.
SHOWLER, A. T.
ARAÚJO, A. C. A.
ALMEIDA, I. S.
AGUIAR, R. S. A.
MIRANDA, J. E.
FERNANDES, F. L.
BASTOS, C. S.
author_role author
author2 ARAÚJO, T. A.
SHOWLER, A. T.
ARAÚJO, A. C. A.
ALMEIDA, I. S.
AGUIAR, R. S. A.
MIRANDA, J. E.
FERNANDES, F. L.
BASTOS, C. S.
author2_role author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv ANDRÉA A. S. OLIVEIRA, UnB; TAMÍRIS A. ARAÚJO, UFSCar; ALLAN T. SHOWLER, USDA; ANA C. A. ARAÚJO, UnB; IGOR S. ALMEIDA, UnB; RENATA S. A. AGUIAR, UnB; JOSÉ EDNILSON MIRANDA, CNPA; FLÁVIO L. FERNANDES, UFV; CRISTINA S. BASTOS, UnB.
dc.contributor.author.fl_str_mv OLIVEIRA, A. A. S.
ARAÚJO, T. A.
SHOWLER, A. T.
ARAÚJO, A. C. A.
ALMEIDA, I. S.
AGUIAR, R. S. A.
MIRANDA, J. E.
FERNANDES, F. L.
BASTOS, C. S.
dc.subject.por.fl_str_mv Hortaliças
Brócolis
Tomato
Sweet potato
Sunflower
Algodão
Gossypium Hirsutum
Entomologia
Estatística Agrícola
Peste
Praga de Planta
Anthonomus Grandis
Bicudo
Clima Tropical
Repolho
Cenoura
Mandioca
Couve
Alho
Tomate
Girassol
Batata Doce
Entomology
Cotton
Geostatistics
Plant pests
Anthonomus grandis grandis
Tropical agriculture
Cabbage
Carrots
Cassava
Garlic
Sunflower seed protein
Sunflower seed products
Vegetables
Broccoli
topic Hortaliças
Brócolis
Tomato
Sweet potato
Sunflower
Algodão
Gossypium Hirsutum
Entomologia
Estatística Agrícola
Peste
Praga de Planta
Anthonomus Grandis
Bicudo
Clima Tropical
Repolho
Cenoura
Mandioca
Couve
Alho
Tomate
Girassol
Batata Doce
Entomology
Cotton
Geostatistics
Plant pests
Anthonomus grandis grandis
Tropical agriculture
Cabbage
Carrots
Cassava
Garlic
Sunflower seed protein
Sunflower seed products
Vegetables
Broccoli
description The boll weevil, Anthonomus grandis grandis Boheman (Coleoptera: Curculionidae), is considered to be the most harmful cotton, Gossypium hirsutum L., pest throughout subtropical, and tropical regions of the western hemisphere.1,2 Boll weevil damages cotton by feeding upon and laying eggs inside its reproductive structures, where hatched larvae feed and pupate,3,4 causing abscission or reduction of fiber quality,3,5,6 and economic losses of up to US$74 million per year.7 Boll weevil chemical control interventions are based on economic thresholds obtained by sampling the plants and for adult boll weevils captured in pheromone-baited traps.3,8,9 In order to develop an accurate monitoring and management program, estimates of population density are essential.10,11 Biotic and abiotic factors affect dynamics and within-field distribution (aggregated, random or uniform patterns) of insect populations.10,12 Knowing a pest's distribution within a field can help to: (1) develop site-specific sampling and control efforts; (2) predict pest movement; (3) improve insecticide-resistance management; (4) conserve biological control agents by precision targeting sprays for the infested areas; and (5) reduce the economic, social and environmental costs associated with pest control.10,11,13 The spatial distribution of boll weevils has been investigated using mean?variance relationships4,14 without considering within-field spatial density distribution, or has been based on pheromone-baited trap captures.15 The most accurate approach is the use of geostatistics because the position of the samples in space is accounted for.16 Recent work reported that geostatistics is of particular interest for pest management because it allows inferences about the minimum inter-sample distance needed to obtain independent estimations and indicates patterns of distribution and colonization of an organism, all of which are crucial for the development of effective sampling programs.11,13 The purpose of this study was to investigate the spatial dynamics of A. grandis grandis on cotton by determining within-field distribution of adults and infested reproductive structures (having feeding and/or oviposition punctures).
publishDate 2022
dc.date.none.fl_str_mv 2022-09-20T13:05:20Z
2022-09-20T13:05:20Z
2022-09-20
2022
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv Pest Management Science, v. 78, n. 3, p. 2492-2501, 2022.
1526-498x
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1146623
10.1002/ps.6880
identifier_str_mv Pest Management Science, v. 78, n. 3, p. 2492-2501, 2022.
1526-498x
10.1002/ps.6880
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1146623
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
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