Near-infrared (nir) diffuse reflectance spectroscopy for the prediction of carbon and nitrogen in an oxisol

The characterization of soil properties through laboratory analysis is an essential part of the diagnosis of the potential use of lands and their fertility. Conventional chemical analyzes are expensive and time consuming, hampering the adoption of crop management technologies, such as precision agriculture. The aim of the present paper was to evaluate the potential of near-infrared (NIR) diffuse reflectance spectroscopy for the prediction of the carbon and nitrogen of Typic Hapludox. In the A and B horizons, 1,240 samples were collected in order to determine the total carbon (TC) and nitrogen (TN) contents, obtain the NIR spectral curve, and build models using partial least squares regression. The use of diffuse reflectance spectroscopy and statistical techniques allowed for the quantification of the TC with adequate models of prediction based on a small number of samples, an residual prediction deviation RP D greater than 2.0, an R2 greater than 0.80 and a low root mean square error RMSE. For TN, models with a good level of prediction were not obtained. The results based on the NIR models were able to be integrated directly into the geostatistical evaluations, obtaining similar digital maps from the observed and predicted TC. The use of pedometric techniques showed promising results for these soils and constitutes a basis for the development of this area of research on soil science in Colombia.

• Autores: Camacho-Tamayo, Jesús H.; Rubiano S., Yolanda; Hurtado S., María del Pilar
• Tipo de recurso: Article of journal
• Fecha de publicación: 2014
• Institución: Universidad Nacional de Colombia
• Repositorio: Universidad Nacional de Colombia
• Idioma: spa
• OAI Identifier: oai:repositorio.unal.edu.co:unal/72754
• Acceso en línea: https://repositorio.unal.edu.co/handle/unal/72754; http://bdigital.unal.edu.co/37229/
• Palabra clave: Oxisol; pedometrics; soil mapping; geostatistics.; Suelos; percepción remota; modelos matemáticos
• Rights: openAccess
• License: Atribución-NoComercial 4.0 Internacional