Soil quality under two different management schemes in coffee plantations of southern Colombia.
Guardado en:
| Autores: | , , |
|---|---|
| Formato: | artículo original |
| Estado: | Versión publicada |
| Fecha de Publicación: | 2016 |
| Descripción: | The aim of this work was to develop an additive soil quality index (ASQI) in agrofostery managements of coffee (Coffea arabica L.). The study took place under two intense and traditional management schemes, in nine farms (32 lots) in the south of Colombia, during 2013. A separation of means analysis was held through the LSD Fisher test (P<0,05) to each of the physical and chemical variables of the soil. The variables that showed differences between the schemes were submitted to a main components analysis to select the minimum data set (MDS) of the components that explained the most variability and the redundancy was verified within the indicators, based on the correlation. The ASQI was obtained from the total sum of soil quality index (SQI) of all the indicators, taking into account that the higher the score of the ASQI, the higher the quality of the soil within the study system. The selected physical variables were the content of sand and clay; while the chemical variables were: organic carbon (OC), P, CA, Mg, total bases (TB) and Ca/Mg. The best ASQI was obtained from traditional management, because the value of the selected variables matched in a bigger proportion with the quality objective identified for the ASQI quanti cation; in this case the crop yield, based on limit values for coffee plantations. |
| País: | Portal de Revistas UCR |
| Institución: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| Lenguaje: | Español |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/21092 |
| Acceso en línea: | https://revistas.ucr.ac.cr/index.php/agromeso/article/view/21092 |
| Access Level: | acceso abierto |
| Palabra clave: | additive soil quality index minimum data set principal component analysis. índice calidad de suelo aditivo conjunto mínimo de datos análisis de componentes principales. |