Javier MEDINA HERNÁNDEZ, Ignacio Caamal Cauich, Verna Gricel Pat Fernández, José Antonio Ávila Dorantes
{"title":"Current challenges and forecasts in maize grain production and consumption in Mexico","authors":"Javier MEDINA HERNÁNDEZ, Ignacio Caamal Cauich, Verna Gricel Pat Fernández, José Antonio Ávila Dorantes","doi":"10.32854/agrop.v17i5.2741","DOIUrl":null,"url":null,"abstract":"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.\nDesign/ 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.\nResults: 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.\nLimitations/ Implications of the study: analysis of the possible future, created from time series through RNN-LSTM, helps to guide decision-making in the present.\nFindings/ 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.","PeriodicalId":153856,"journal":{"name":"Agro Productividad","volume":"15 10","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agro Productividad","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32854/agrop.v17i5.2741","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
墨西哥玉米谷物生产和消费目前面临的挑战和预测
设计/方法/途径:通过 Excel® 和 SCImago Graphica® 分别创建的图表和地图对关键变量进行分析。在 Python© 中使用长短期记忆(LSTM)类型的递归神经网络(RNN)对 2050 年进行了预测,并与 1980 年和 2020 年进行了比较。墨西哥排名第七,出口竞争力不强,依赖从美国进口黄玉米谷物来满足需求。实施了成套技术的墨西哥各州的单产和产量都有所提高。到 2050 年,由于农业 5.0 的技术进步,墨西哥的玉米谷物产量将增加,但不足以满足日益增长的人口的表面消费,因此进口量将增加。研究的局限性/意义:通过 RNN-LSTM 对时间序列创建的可能未来进行分析,有助于指导当前的决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。