Current challenges and forecasts in maize grain production and consumption in Mexico

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JAVIER MEDINA HERNÁNDEZ https://orcid.org/0000-0001-6990-3740
IGNACIO CAAMAL CAUICH https://orcid.org/0000-0002-3571-0542
VERNA GRICEL PAT FERNÁNDEZ https://orcid.org/0000-0001-7048-6710
JOSÉ ANTONIO ÁVILA DORANTES https://orcid.org/0000-0003-0423-793X

Keywords

yields, imports, exports, time series, deep neural networks.

Resumen

Objective: to analyze production and consumption of maize grain in Mexico, with time series and recurrent neural networks, to describe the present and future situation of maize cultivation.


Design/ Methodology/ Approach: key variables were analyzed in graphs and maps created in Excel® and SCImago Graphica®, respectively. Forecasts for the year 2050 were obtained in Python© with Recurrent Neural Network (RNN) of the Long Short-Term Memory (LSTM) type, and were compared with the years 1980 and 2020.


Results: the largest production of white and yellow maize grain was obtained by the United States and China. Mexico ranks seventh, is not competitive in exports, and relies on imports of yellow maize grain from the United States to supply demand. The Mexican states that implemented technology packages showed higher yields and production. By 2050, maize grain production in Mexico will increase due to the technological advances of Agriculture 5.0 Although it would not be enough to supply the apparent consumption of the growing population, for this reason imports will increase.


Limitations/ Implications of the study: analysis of the possible future, created from time series through RNN-LSTM, helps to guide decision-making in the present.


Findings/ Conclusions: new agricultural public policies are needed to guide, in the long term, the challenges of maize grain production and consumption in Mexico to guarantee food sovereignty.

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