Model applicability to predict growth rate of insects throughout storage of corn grain (Zea mays L.)

Detalhes bibliográficos
Autor(a) principal: Faria, Igor Lopes de
Data de Publicação: 2022
Outros Autores: Silva, Luís Cesar da, Zeymer, Juliana Soares, Araujo, Marcos Eduardo Viana de, Oliveira, Gabriel Henrique Horta de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Engenharia na Agricultura
Texto Completo: https://periodicos.ufv.br/reveng/article/view/12656
Resumo: Insect pest infestation in stored grains can cause several losses during storage, in addition to promoting the spread of fungi, changing the temperature of the grain mass, and reducing the value of the final product. Knowing the behavior of these insect pests and how they reproduce in the grain mass is essential to design more efficient control strategies and ensure a quality final product. Thus, this work aimed to accomplish modeling and simulation of the population growth of insects Rhyzopertha dominica, Sitophilus oryzae, Oryzaephilus surinamensis and Tribolium castaneum throughout the storage of corn grain, using data retrieved from digital sensors of temperature installed in three Brazilian storage facilities in different regions. Data were collected through managing system CERES (company Procer Automação e Sistemas) and retrieved from 1st of July to 29th September 2019. In each one of the facilities, a silo equipped with the aforementioned sensors was used. Mean weekly values of temperature of the grain mass and the intergranular relative humidity were used, calculated using the Modified Henderson equation. The silos evaluated in facilities 1, 2, and 3 have a static capacity of 2,100; 6,304, and 93 tones, respectively, considering soybean with a bulk density of 750 kg m-3. Higher growth rates of all assessed species were observed for the storage facility number 2; and lowest values for storage facility number 1. Storage facilities that presented a higher potential for the growth rate of insects are subjected to elevated levels of insect populations throughout time.
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spelling Model applicability to predict growth rate of insects throughout storage of corn grain (Zea mays L.)Model applicability to predict growth rates of insects throughout the storage of corn (Zea mays L.) grain Digital sensorsMathematical modelingPopulation monitoringThermometrymathematical modelingpopulational monitoringdigital sensorsthermometryInsect pest infestation in stored grains can cause several losses during storage, in addition to promoting the spread of fungi, changing the temperature of the grain mass, and reducing the value of the final product. Knowing the behavior of these insect pests and how they reproduce in the grain mass is essential to design more efficient control strategies and ensure a quality final product. Thus, this work aimed to accomplish modeling and simulation of the population growth of insects Rhyzopertha dominica, Sitophilus oryzae, Oryzaephilus surinamensis and Tribolium castaneum throughout the storage of corn grain, using data retrieved from digital sensors of temperature installed in three Brazilian storage facilities in different regions. Data were collected through managing system CERES (company Procer Automação e Sistemas) and retrieved from 1st of July to 29th September 2019. In each one of the facilities, a silo equipped with the aforementioned sensors was used. Mean weekly values of temperature of the grain mass and the intergranular relative humidity were used, calculated using the Modified Henderson equation. The silos evaluated in facilities 1, 2, and 3 have a static capacity of 2,100; 6,304, and 93 tones, respectively, considering soybean with a bulk density of 750 kg m-3. Higher growth rates of all assessed species were observed for the storage facility number 2; and lowest values for storage facility number 1. Storage facilities that presented a higher potential for the growth rate of insects are subjected to elevated levels of insect populations throughout time.Insect pest infestation in stored grains can cause several losses during storage, in addition to promoting the spread of fungi, changing the temperature of the grain mass, and reducing the value of the final product. Knowing the behavior of these insect pests and how they reproduce in the grain mass is essential to design more efficient control strategies and ensure a quality final product. Thus, this work aimed to accomplish modeling and simulation of the population growth of insects Rhyzopertha dominica, Sitophilus oryzae, Oryzaephilus surinamensis and Tribolium castaneum throughout the storage of corn grain, using data retrieved from digital sensors of temperature installed in three Brazilian storage facilities in different regions. Data were collected through managing system CERES (company Procer Automação e Sistemas) and retrieved from 1st of July to 29th September 2019. In each one of the facilities, a silo equipped with the aforementioned sensors was used. Mean weekly values of temperature of the grain mass and the intergranular relative humidity were used, calculated using the Modified Henderson equation. The silos evaluated in facilities 1, 2, and 3 have a static capacity of 2,100; 6,304, and 93 tones, respectively, considering soybean with a bulk density of 750 kg m-3. Higher growth rates of all assessed species were observed for the storage facility number 2; and lowest values for storage facility number 1. Storage facilities that presented a higher potential for the growth rate of insects are subjected to elevated levels of insect populations throughout time.Universidade Federal de Viçosa - UFV2022-04-25info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufv.br/reveng/article/view/1265610.13083/reveng.v30i1.12656Engineering in Agriculture; Vol. 30 No. Contínua (2022); 36-48Revista Engenharia na Agricultura - REVENG; v. 30 n. Contínua (2022); 36-482175-68131414-3984reponame:Engenharia na Agriculturainstname:Universidade Federal de Viçosa (UFV)instacron:UFVenghttps://periodicos.ufv.br/reveng/article/view/12656/7295Copyright (c) 2022 Revista Engenharia na Agricultura - REVENGhttps://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessFaria, Igor Lopes deSilva, Luís Cesar daZeymer, Juliana SoaresAraujo, Marcos Eduardo Viana deOliveira, Gabriel Henrique Horta de2023-01-23T14:06:10Zoai:ojs.periodicos.ufv.br:article/12656Revistahttps://periodicos.ufv.br/revengPUBhttps://periodicos.ufv.br/reveng/oairevistaengenharianagricultura@gmail.com||andrerosa@ufv.br||tramitacao.reveng@gmail.com|| reveng@ufv.br2175-68131414-3984opendoar:2023-01-23T14:06:10Engenharia na Agricultura - Universidade Federal de Viçosa (UFV)false
dc.title.none.fl_str_mv Model applicability to predict growth rate of insects throughout storage of corn grain (Zea mays L.)
Model applicability to predict growth rates of insects throughout the storage of corn (Zea mays L.) grain
title Model applicability to predict growth rate of insects throughout storage of corn grain (Zea mays L.)
spellingShingle Model applicability to predict growth rate of insects throughout storage of corn grain (Zea mays L.)
Faria, Igor Lopes de
Digital sensors
Mathematical modeling
Population monitoring
Thermometry
mathematical modeling
populational monitoring
digital sensors
thermometry
title_short Model applicability to predict growth rate of insects throughout storage of corn grain (Zea mays L.)
title_full Model applicability to predict growth rate of insects throughout storage of corn grain (Zea mays L.)
title_fullStr Model applicability to predict growth rate of insects throughout storage of corn grain (Zea mays L.)
title_full_unstemmed Model applicability to predict growth rate of insects throughout storage of corn grain (Zea mays L.)
title_sort Model applicability to predict growth rate of insects throughout storage of corn grain (Zea mays L.)
author Faria, Igor Lopes de
author_facet Faria, Igor Lopes de
Silva, Luís Cesar da
Zeymer, Juliana Soares
Araujo, Marcos Eduardo Viana de
Oliveira, Gabriel Henrique Horta de
author_role author
author2 Silva, Luís Cesar da
Zeymer, Juliana Soares
Araujo, Marcos Eduardo Viana de
Oliveira, Gabriel Henrique Horta de
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Faria, Igor Lopes de
Silva, Luís Cesar da
Zeymer, Juliana Soares
Araujo, Marcos Eduardo Viana de
Oliveira, Gabriel Henrique Horta de
dc.subject.por.fl_str_mv Digital sensors
Mathematical modeling
Population monitoring
Thermometry
mathematical modeling
populational monitoring
digital sensors
thermometry
topic Digital sensors
Mathematical modeling
Population monitoring
Thermometry
mathematical modeling
populational monitoring
digital sensors
thermometry
description Insect pest infestation in stored grains can cause several losses during storage, in addition to promoting the spread of fungi, changing the temperature of the grain mass, and reducing the value of the final product. Knowing the behavior of these insect pests and how they reproduce in the grain mass is essential to design more efficient control strategies and ensure a quality final product. Thus, this work aimed to accomplish modeling and simulation of the population growth of insects Rhyzopertha dominica, Sitophilus oryzae, Oryzaephilus surinamensis and Tribolium castaneum throughout the storage of corn grain, using data retrieved from digital sensors of temperature installed in three Brazilian storage facilities in different regions. Data were collected through managing system CERES (company Procer Automação e Sistemas) and retrieved from 1st of July to 29th September 2019. In each one of the facilities, a silo equipped with the aforementioned sensors was used. Mean weekly values of temperature of the grain mass and the intergranular relative humidity were used, calculated using the Modified Henderson equation. The silos evaluated in facilities 1, 2, and 3 have a static capacity of 2,100; 6,304, and 93 tones, respectively, considering soybean with a bulk density of 750 kg m-3. Higher growth rates of all assessed species were observed for the storage facility number 2; and lowest values for storage facility number 1. Storage facilities that presented a higher potential for the growth rate of insects are subjected to elevated levels of insect populations throughout time.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-25
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.ufv.br/reveng/article/view/12656
10.13083/reveng.v30i1.12656
url https://periodicos.ufv.br/reveng/article/view/12656
identifier_str_mv 10.13083/reveng.v30i1.12656
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://periodicos.ufv.br/reveng/article/view/12656/7295
dc.rights.driver.fl_str_mv Copyright (c) 2022 Revista Engenharia na Agricultura - REVENG
https://creativecommons.org/licenses/by-nc/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2022 Revista Engenharia na Agricultura - REVENG
https://creativecommons.org/licenses/by-nc/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Viçosa - UFV
publisher.none.fl_str_mv Universidade Federal de Viçosa - UFV
dc.source.none.fl_str_mv Engineering in Agriculture; Vol. 30 No. Contínua (2022); 36-48
Revista Engenharia na Agricultura - REVENG; v. 30 n. Contínua (2022); 36-48
2175-6813
1414-3984
reponame:Engenharia na Agricultura
instname:Universidade Federal de Viçosa (UFV)
instacron:UFV
instname_str Universidade Federal de Viçosa (UFV)
instacron_str UFV
institution UFV
reponame_str Engenharia na Agricultura
collection Engenharia na Agricultura
repository.name.fl_str_mv Engenharia na Agricultura - Universidade Federal de Viçosa (UFV)
repository.mail.fl_str_mv revistaengenharianagricultura@gmail.com||andrerosa@ufv.br||tramitacao.reveng@gmail.com|| reveng@ufv.br
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