Statistical Forecasting Model for Maize Yield in the Semiarid Region of Córdoba Based on Areal Rainfall Data

An statistical model for corn yield forecasting is developed to estimate the crop productivity in the semiarid region of the Córdoba province. Monthly precipitation data were used to calculate areal precipitation, which was utilized as an independent variable set. The methodology consisted of a mult...

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Main Author: De la Casa, Antonio
Format: Online
Language:spa
Published: Facultad de Ciencias Agropecuarias 1992
Subjects:
Online Access:https://revistas.unc.edu.ar/index.php/agris/article/view/2377
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author De la Casa, Antonio
author_facet De la Casa, Antonio
author_sort De la Casa, Antonio
collection Portal de Revistas
description An statistical model for corn yield forecasting is developed to estimate the crop productivity in the semiarid region of the Córdoba province. Monthly precipitation data were used to calculate areal precipitation, which was utilized as an independent variable set. The methodology consisted of a multivariate analysis with a stepwise program. The predictor variables were included or eliminated from the model one at a time, considering the F value used to evaluate the significance of the relationships. The model considered pluviometric, technology, and geographic terms. The error tests were 17 and 18% compared with the control data. Significant differences were detected in the Río Cuarto department. October and November precipitation are the variables more related to district corn yield.
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spelling oai:ojs.revistas.unc.edu.ar:article-23772024-09-11T17:43:33Z Statistical Forecasting Model for Maize Yield in the Semiarid Region of Córdoba Based on Areal Rainfall Data Modelo estadístico de pronóstico de rendimiento de maíz para la región semiárida de Córdoba basado en datos pluviométricos areales De la Casa, Antonio statistical model corn yield forecasting stepwise regression modelo estadístico maíz predicción de rendimiento regresión paso a paso An statistical model for corn yield forecasting is developed to estimate the crop productivity in the semiarid region of the Córdoba province. Monthly precipitation data were used to calculate areal precipitation, which was utilized as an independent variable set. The methodology consisted of a multivariate analysis with a stepwise program. The predictor variables were included or eliminated from the model one at a time, considering the F value used to evaluate the significance of the relationships. The model considered pluviometric, technology, and geographic terms. The error tests were 17 and 18% compared with the control data. Significant differences were detected in the Río Cuarto department. October and November precipitation are the variables more related to district corn yield. Se desarrolla un modelo de pronóstico de rendimiento de naturaleza estadística, con el propósito de estimar la productividad del cultivo de maíz en la región semiárida de la provincia de Córdoba. Se emplearon registros de precipitación a nivel mensual, reformulados en términos areales, como parte de un grupo de variables independientes. La metodología de análisis multivariado fue realizada mediante un programa de cálculo "stepwise", que incluye o elimina variables predictoras según la incidencia que esto provoca en el estadístico empleado para valorar la significancia de la relación. El modelo queda conformado por términos pluviométricos, tecnológicos y geográficos, resultando la prueba de evaluación y testeo con un error porcentual medio entre 17 y 18% respecto de los datos testigos. Solo surgen diferencias significativas de sobreestimación en el departamento Río Cuarto. Las precipitaciones de octubre y noviembre son las variables de mayor incidencia sobre el rendimiento departamental. Facultad de Ciencias Agropecuarias 1992-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://revistas.unc.edu.ar/index.php/agris/article/view/2377 10.31047/1668.298x.v9.n2.2377 AgriScientia; Vol. 9 No. 2 (1992); 87-96 AgriScientia; Vol. 9 Núm. 2 (1992); 87-96 1668-298X 10.31047/1668.298x.v9.n2 spa https://revistas.unc.edu.ar/index.php/agris/article/view/2377/1323 Derechos de autor 1992 Antonio De la Casa https://creativecommons.org/licenses/by-sa/4.0
spellingShingle statistical model
corn
yield forecasting
stepwise regression
modelo estadístico
maíz
predicción de rendimiento
regresión paso a paso
De la Casa, Antonio
Statistical Forecasting Model for Maize Yield in the Semiarid Region of Córdoba Based on Areal Rainfall Data
title Statistical Forecasting Model for Maize Yield in the Semiarid Region of Córdoba Based on Areal Rainfall Data
title_alt Modelo estadístico de pronóstico de rendimiento de maíz para la región semiárida de Córdoba basado en datos pluviométricos areales
title_full Statistical Forecasting Model for Maize Yield in the Semiarid Region of Córdoba Based on Areal Rainfall Data
title_fullStr Statistical Forecasting Model for Maize Yield in the Semiarid Region of Córdoba Based on Areal Rainfall Data
title_full_unstemmed Statistical Forecasting Model for Maize Yield in the Semiarid Region of Córdoba Based on Areal Rainfall Data
title_short Statistical Forecasting Model for Maize Yield in the Semiarid Region of Córdoba Based on Areal Rainfall Data
title_sort statistical forecasting model for maize yield in the semiarid region of cordoba based on areal rainfall data
topic statistical model
corn
yield forecasting
stepwise regression
modelo estadístico
maíz
predicción de rendimiento
regresión paso a paso
topic_facet statistical model
corn
yield forecasting
stepwise regression
modelo estadístico
maíz
predicción de rendimiento
regresión paso a paso
url https://revistas.unc.edu.ar/index.php/agris/article/view/2377
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AT delacasaantonio modeloestadisticodepronosticoderendimientodemaizparalaregionsemiaridadecordobabasadoendatospluviometricosareales