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Спутники
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SpaceX
Роскосмос
NASA
СпутникиРНSpaceXРоскосмосNASAUnderstanding the factors affecting crop yield is essential for designing sustainable agricultural management strategies. In Mexico, maize production plays a central role in food security, particularly in production systems transitioning toward agroecological practices. The objective of this study was to determine the factors affecting maize yield in agroecological transition systems in Mexico using a multiple linear regression model and to analyze their implications for agricultural sustainability. Data from maize producers undergoing agroecological transition were analyzed considering variables related to crop management, input use, and soil characteristics. The variables included in the model were hours devoted to crop management (hours/day), total farm area (SupTotalPdva), fertilizer use (Fertilizante), soil salinity (Salinidad), soil acidity (Acidez), eroded areas (Erosionadas), soil depth (ProfSuelo), the use of certified seed (Certificada), and mechanized cultivation (MetMecaniza). Results indicate that both agricultural management practices and soil conditions significantly influence maize yield. The estimated model showed a coefficient of determination of R² = 0.7039 and a root mean squared error of RMSE = 1.982, indicating an adequate capacity to explain yield variability. These findings contribute to understanding the factors determining maize productivity in agroecological transition systems and provide useful insights for improving the sustainability of agricultural production systems.
Understanding the factors affecting crop yield is essential for designing sustainable agricultural management strategies. In Mexico, maize production plays a central role in food security, particularly in production systems transitioning toward agroecological practices. The objective of this study was to determine the factors affecting maize yield in agroecological transition systems in Mexico using a multiple linear regression model and to analyze their implications for agricultural sustainability. Data from maize producers undergoing agroecological transition were analyzed considering variables related to crop management, input use, and soil characteristics. The variables included in the model were hours devoted to crop management (hours/day), total farm area (SupTotalPdva), fertilizer use (Fertilizante), soil salinity (Salinidad), soil acidity (Acidez), eroded areas (Erosionadas), soil depth (ProfSuelo), the use of certified seed (Certificada), and mechanized cultivation (MetMecaniza). Results indicate that both agricultural management practices and soil conditions significantly influence maize yield. The estimated model showed a coefficient of determination of R² = 0.7039 and a root mean squared error of RMSE = 1.982, indicating an adequate capacity to explain yield variability. These findings contribute to understanding the factors determining maize productivity in agroecological transition systems and provide useful insights for improving the sustainability of agricultural production systems.