A nonlinear model to estimate Nitrogen level in agricultural soil using Gaussian Kernels

• Autores: Sanchez-Mora, K, Zuniga-Gutierrez, MA, Mayhua-Lopez, E
• Formato: objeto de conferencia
• Fecha de Publicación: 2016
• Institución: Consejo Nacional de Ciencia Tecnología e Innovación
• Repositorio: CONCYTEC-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.concytec.gob.pe:20.500.12390/1011
• Enlace del recurso: https://hdl.handle.net/20.500.12390/1011; https://doi.org/10.1109/ANDESCON.2016.7836247
• Nivel de acceso: acceso abierto
• Materia: fertilisers; agriculture; electrical conductivity; https://purl.org/pe-repo/ocde/ford#4.01.01

Nitrogen fertilizers are commonly used to improve agricultural productivity. However, its excessive use may cause or lead to environmental problems. Therefore, technologies capable of monitoring and measure levels of nitrogen in agricultural soil in-situ and in real time are required in order to make efficient the use of fertilizers. Nitrogen levels are usually measured by direct and indirect methods. Direct methods can be conducted in-situ or in laboratory, but they are really expensive and/or little resistant to soil conditions.