Analysis of spatial variation in soil fertility for the delimitation of homogeneous management zones in precision agriculture

Descripción del Articulo

This study analyzed spatial soil fertility variability in a 1440 m² plot in Mosquera, Colombia, to create homogeneous management zones for precision agriculture.  480 soil samples were collected using a 3x1 m grid, analyzing pH, electrical conductivity, phosphorus, exchangeable cations, mic...

Descripción completa

Detalles Bibliográficos
Autores: Galindo-Pacheco, Julio, Vargas-Díaz, Ruy, Martínez-Niño, Carlos, Franco-Florez, Clara
Formato: artículo
Fecha de Publicación:2024
Institución:Universidad Nacional Intercultural Fabiola Salazar Leguía de Bagua
Repositorio:Revistas - Universidad Nacional Intercultural Fabiola Salazar Leguía de Bagua
Lenguaje:español
OAI Identifier:oai:revista.unibagua.edu.pe:article/289
Enlace del recurso:https://revista.unibagua.edu.pe/index.php/dekamuagropec/article/view/289
Nivel de acceso:acceso abierto
Materia:Agricultura de precisión
análisis de componentes principales
fertilidad del suelo
kriging
variabilidad espacial
variograma
zonas de manejo homogéneo
Precision agriculture
principal component analysis
soil fertility
spatial variability
variogram
homogeneous management zones
Descripción
Sumario:This study analyzed spatial soil fertility variability in a 1440 m² plot in Mosquera, Colombia, to create homogeneous management zones for precision agriculture.  480 soil samples were collected using a 3x1 m grid, analyzing pH, electrical conductivity, phosphorus, exchangeable cations, microelements, and soil organic matter (SOM).  Principal Component Analysis (PCA) identified SOM, pH, and electrical conductivity as key indicators for zoning. Kriging interpolation mapped these properties, revealing high variability.  The exponential model best represented the semivariograms.  Fuzzy clustering, based on indicator thresholds, divided the plot into two zones, with high overlap between pH and SOM-based divisions.  A QUEFTS model simulated crop yield, showing that optimized N and K fertilization, based on zoning, maximized yields. The study demonstrates the effectiveness of using PCA and Kriging to create management zones.  SOM-based zoning improved P and K fertilization management, while pH-based zoning targeted micronutrient differences.  The results highlight the potential of precision agriculture to improve crop yields and resource efficiency.  Future research should incorporate physical soil properties and climatic variations for more comprehensive zone management.
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).