The use of time series models for forecast corn production in Mato Grosso state

Detalhes bibliográficos
Autor(a) principal: Silva, Rodolfo Benedito Zattar da
Data de Publicação: 2020
Outros Autores: Silva, Rosângela Natalina Zattar da, Aires, Fábia Fernanda da Costa, Soares, Eduardo José Oenning
Tipo de documento: Artigo
Idioma: por
Título da fonte: Research, Society and Development
Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/1915
Resumo: The Mato Grosso State is the main producer of corn of the Brazil and its production has been increasing every year. In this sense, is very important to gain information about future production to planning and monitoring of the corn crops. In this way, the main aim of this paper is to compare the performance showed by the forecast models of time series and to choose the best model. The historical data of corn crop from 1976/1977 to 2017/2018 was obtained with CONAB (The Brazilian National Supply Company). Then, the time series pattern was analyzed, as well as the descriptive statistics of the data obtained. Subsequently, electronic spreadsheets were developed for application and analysis of the evaluated models. With the results it was verified that the trend exponential smoothing model (Holt's linear model) presented the smallest prediction errors, and then it was selected to predict the next seven crops (from 2018/2019 to 2024/2025). The forecast obtained by this model for the 2024/2025 crop indicates that total corn production in the state of Mato Grosso will increase by approximately 70% compared to the 2017/2018 crop production.
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spelling The use of time series models for forecast corn production in Mato Grosso stateUso de modelos de series temporales para pronósticos de cultivos de maíz en el estado de Mato GrossoUso de modelos de séries temporais para previsões de safras de milho no estado de Mato GrossoSéries temporaisModelos de previsãoProdução de milho.Series de tiempoModelos de pronósticoProducción de maíz.Time seriesForecast modelsCorn production.The Mato Grosso State is the main producer of corn of the Brazil and its production has been increasing every year. In this sense, is very important to gain information about future production to planning and monitoring of the corn crops. In this way, the main aim of this paper is to compare the performance showed by the forecast models of time series and to choose the best model. The historical data of corn crop from 1976/1977 to 2017/2018 was obtained with CONAB (The Brazilian National Supply Company). Then, the time series pattern was analyzed, as well as the descriptive statistics of the data obtained. Subsequently, electronic spreadsheets were developed for application and analysis of the evaluated models. With the results it was verified that the trend exponential smoothing model (Holt's linear model) presented the smallest prediction errors, and then it was selected to predict the next seven crops (from 2018/2019 to 2024/2025). The forecast obtained by this model for the 2024/2025 crop indicates that total corn production in the state of Mato Grosso will increase by approximately 70% compared to the 2017/2018 crop production.El estado de Mato Grosso es el principal productor de maíz en el país y su producción aumenta con cada nuevo ciclo de cultivo. En este sentido, obtener información futura sobre la producción de maíz adquiere una importancia fundamental para la planificación y el monitoreo adecuados de la producción. Por lo tanto, el presente trabajo tuvo como objetivo comparar los rendimientos presentados por los modelos de pronóstico de series de tiempo y seleccionar aquel que muestre el mejor ajuste a los datos históricos para hacer pronósticos futuros de la producción total de maíz en Mato Grosso. Para esto, se obtuvieron datos históricos de las cosechas de la Compañía Nacional de Abastecimiento (CONAB) para el período comprendido entre 1976/1977 y 2017/2018. Luego, se analizó el patrón de la serie temporal, así como las estadísticas descriptivas de los datos obtenidos. Posteriormente, se desarrollaron hojas de cálculo electrónicas para la aplicación y el análisis de los modelos evaluados. Con los resultados obtenidos, se verificó que el modelo de suavizado exponencial de tendencia (modelo lineal de Holt) presentó los menores errores de pronóstico, siendo seleccionado para obtener pronósticos de las próximas 7 (siete) cosechas (2018/2019 a 2024/2025). El pronóstico obtenido por este modelo para el final del horizonte de pronóstico para la cosecha 2024/2025 indica que la producción total de maíz en el estado de Mato Grosso aumentará aproximadamente un 70% en comparación con la producción de cultivo 2017/2018.O estado de Mato Grosso é o principal produtor de milho do país e sua produção vem aumentando a cada nova safra. Neste sentido, obter informações futuras da produção de milho se torna de fundamental importância para o adequado planejamento e acompanhamento das safras. Deste modo, o presente trabalho teve como objetivo realizar a comparação dos desempenhos apresentados pelos modelos de previsões de séries temporais e selecionar aquele que melhor se ajustou aos dados históricos para realizar previsões futuras da produção total de milho em Mato Grosso. Para isto, foram obtidos dados históricos das safras juntamente a Companhia Nacional de Abastecimento (CONAB) compreendendo o período de 1976/1977 a 2017/2018. Em seguida, foi analisado o padrão da série temporal, bem como as estatísticas descritivas dos dados obtidos. Posteriormente, foram desenvolvidas planilhas eletrônicas para aplicação e análise dos modelos avaliados. Com os resultados obtidos, verificou-se que o modelo de suavização exponencial com tendência (modelo linear de Holt) foi o que apresentou os menores erros de previsão, sendo selecionado para obter previsões das próximas 7 (sete) safras (2018/2019 a 2024/2025). A previsão obtida por este modelo para o fim do horizonte de previsão, na safra de 2024/2025, indica que a produção total de milho no estado de Mato Grosso terá um aumento de aproximadamente 70% quando comparada com a produção da safra de 2017/2018.Research, Society and Development2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/191510.33448/rsd-v9i1.1915Research, Society and Development; Vol. 9 No. 1; e184911915Research, Society and Development; Vol. 9 Núm. 1; e184911915Research, Society and Development; v. 9 n. 1; e1849119152525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/1915/1581Copyright (c) 2020 Rodolfo Benedito Zattar da Silva, Rosângela Natalina Zattar da Silva, Fábia Fernanda da Costa Aires, Eduardo José Oenning Soaresinfo:eu-repo/semantics/openAccessSilva, Rodolfo Benedito Zattar daSilva, Rosângela Natalina Zattar daAires, Fábia Fernanda da CostaSoares, Eduardo José Oenning2020-08-19T03:04:08Zoai:ojs.pkp.sfu.ca:article/1915Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:26:46.522709Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false
dc.title.none.fl_str_mv The use of time series models for forecast corn production in Mato Grosso state
Uso de modelos de series temporales para pronósticos de cultivos de maíz en el estado de Mato Grosso
Uso de modelos de séries temporais para previsões de safras de milho no estado de Mato Grosso
title The use of time series models for forecast corn production in Mato Grosso state
spellingShingle The use of time series models for forecast corn production in Mato Grosso state
Silva, Rodolfo Benedito Zattar da
Séries temporais
Modelos de previsão
Produção de milho.
Series de tiempo
Modelos de pronóstico
Producción de maíz.
Time series
Forecast models
Corn production.
title_short The use of time series models for forecast corn production in Mato Grosso state
title_full The use of time series models for forecast corn production in Mato Grosso state
title_fullStr The use of time series models for forecast corn production in Mato Grosso state
title_full_unstemmed The use of time series models for forecast corn production in Mato Grosso state
title_sort The use of time series models for forecast corn production in Mato Grosso state
author Silva, Rodolfo Benedito Zattar da
author_facet Silva, Rodolfo Benedito Zattar da
Silva, Rosângela Natalina Zattar da
Aires, Fábia Fernanda da Costa
Soares, Eduardo José Oenning
author_role author
author2 Silva, Rosângela Natalina Zattar da
Aires, Fábia Fernanda da Costa
Soares, Eduardo José Oenning
author2_role author
author
author
dc.contributor.author.fl_str_mv Silva, Rodolfo Benedito Zattar da
Silva, Rosângela Natalina Zattar da
Aires, Fábia Fernanda da Costa
Soares, Eduardo José Oenning
dc.subject.por.fl_str_mv Séries temporais
Modelos de previsão
Produção de milho.
Series de tiempo
Modelos de pronóstico
Producción de maíz.
Time series
Forecast models
Corn production.
topic Séries temporais
Modelos de previsão
Produção de milho.
Series de tiempo
Modelos de pronóstico
Producción de maíz.
Time series
Forecast models
Corn production.
description The Mato Grosso State is the main producer of corn of the Brazil and its production has been increasing every year. In this sense, is very important to gain information about future production to planning and monitoring of the corn crops. In this way, the main aim of this paper is to compare the performance showed by the forecast models of time series and to choose the best model. The historical data of corn crop from 1976/1977 to 2017/2018 was obtained with CONAB (The Brazilian National Supply Company). Then, the time series pattern was analyzed, as well as the descriptive statistics of the data obtained. Subsequently, electronic spreadsheets were developed for application and analysis of the evaluated models. With the results it was verified that the trend exponential smoothing model (Holt's linear model) presented the smallest prediction errors, and then it was selected to predict the next seven crops (from 2018/2019 to 2024/2025). The forecast obtained by this model for the 2024/2025 crop indicates that total corn production in the state of Mato Grosso will increase by approximately 70% compared to the 2017/2018 crop production.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-01
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://rsdjournal.org/index.php/rsd/article/view/1915
10.33448/rsd-v9i1.1915
url https://rsdjournal.org/index.php/rsd/article/view/1915
identifier_str_mv 10.33448/rsd-v9i1.1915
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/1915/1581
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Research, Society and Development
publisher.none.fl_str_mv Research, Society and Development
dc.source.none.fl_str_mv Research, Society and Development; Vol. 9 No. 1; e184911915
Research, Society and Development; Vol. 9 Núm. 1; e184911915
Research, Society and Development; v. 9 n. 1; e184911915
2525-3409
reponame:Research, Society and Development
instname:Universidade Federal de Itajubá (UNIFEI)
instacron:UNIFEI
instname_str Universidade Federal de Itajubá (UNIFEI)
instacron_str UNIFEI
institution UNIFEI
reponame_str Research, Society and Development
collection Research, Society and Development
repository.name.fl_str_mv Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)
repository.mail.fl_str_mv rsd.articles@gmail.com
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