Sistema georreferenciado de indicadores de calidad de suelos para los llanos orientales de colombia estudio de caso: municipio de puerto lópez, meta

Geosoil permite almacenar, consultar e interpretar información tanto del suelo como de su entorno biofísico a diferentes escalas: parcela, finca, comunidad, municipio, departamento, región, país. Opera a partir de una base de datos relacional elaborada en ACCES 2000, compuesta por una serie de tablas principales estructuradas con información a diferentes niveles jerárquicos que permiten la caracterización de las propiedades del suelo. Los elementos morfológicos y analíticos del suelo se combinan para conformar indicadores de calidad mediante un sistema de calificación que permite visualizar el grado y el número de limitaciones que podría tener un suelo para ser utilizado en agricultura. Además, posee módulos en los cuales el usuario puede: (a) adicionar o consultar características espaciales y de atributos del suelo; (b) visualizar la interpretación de los indicadores de calidad, agrupados en rangos de limitación (c) determinar la aptitud general del suelo para un cultivo específico mediante la comparación entre oferta (suelo) vs. demanda (requerimientos del cultivo); (d) calcular necesidades de fertilización; (e) generar reportes de la variabilidad en profundidad de algunas características, para uno o más suelos; (f) cartografiar los resultados mediante un link con el SIG MapMaker y (g) visualizar mapas de variabilidad espacial y/o temporal (isolíneas) de la variable utilizada como indicador. ABSTRACT The System Georeferenced of soil quality indicators for the savannas of Colombia. Geosoil allows to as much store, to consult and to process data of the soil as of his biophysics surroundings on different scales: parcel, property, community, municipality, department, region, and country. It operates from a relational database elaborated in ACCES 2000, composed by a series of structured main tables with information at different hierarchic levels that they allow the characterization of the properties of the soil. The morphologic and analytical elements of the ground are combined to conform indicators of quality by means of a qualification system that allows visualizing the degree and the number of limitations that could have a soil to be used in agriculture. In addition, it has modules in which the user can: (a) to add or to consult space characteristics and of attributes of the soil; (b) to visualize the interpretation of the quality indicators, grouped in limitation ranks; (c) to determine the general aptitude of the soil for a specific culture by means of the comparison between supply (soil) versus demands (requirements of the culture); (d) to calculate the fertilization necessities (e) to generate reports of the variability in depth of some characteristics, for one or more soil; (f) to map the results by means of a link with the MapMaker GIS (g) to visualize maps of space and/or temporary variability (isolines) of the variable used like indicator. Key words: indicators, soil quality, Geographical Information Systems, soil database, land degradation and land evaluation, savannas

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 RPD 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