Model applicability to predict growth rate of insects throughout storage of corn grain (Zea mays L.)
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Engenharia na Agricultura |
DOI: | 10.13083/reveng.v30i1.12656 |
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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Engenharia na Agricultura |
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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.) 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 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.) 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.) 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 Faria, Igor Lopes de Silva, Luís Cesar da Zeymer, Juliana Soares Araujo, Marcos Eduardo Viana de Oliveira, Gabriel Henrique Horta 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 |
_version_ |
1822179074929328128 |
dc.identifier.doi.none.fl_str_mv |
10.13083/reveng.v30i1.12656 |