The use of time series models for forecast corn production in Mato Grosso state
DOI:
https://doi.org/10.33448/rsd-v9i1.1915Keywords:
Time series; Forecast models; Corn production.Abstract
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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