Article contents
Spatial variability of soil fertility in an integrated crop livestock forest system
Published online by Cambridge University Press: 01 June 2017
Abstract
Knowledge on spatial variability of soil properties is useful for the rational use of inputs, as in the site specific application of lime and fertilizer. Crop-livestock-forest integrated systems (CLFIS) provide a strategy of sustainable agricultural production which integrates annual crops, trees and livestock activities on a same area and in the same season. Since the lime and fertilizer are key factors for the intensification of agricultural systems in acid-soil in the tropics, precision agriculture (PA) is the tool to improve the efficiency of use of these issues. The objective of this research was to map and evaluate the spatial variability of soil properties, liming and fertilizer need of a CLFIS. The field study was carried out in a 30 ha area at Embrapa Pecuária Sudeste in São Carlos, SP, Brazil. Soil samples were collected at 0–0.2 m depth, and each sample represented a paddock. The spatial variability of soil properties and site-specific liming and fertilizer needs were modeled using semi-variograms, the soil fertility information were modeled. Spatial variability soil properties and site specific liming and fertilizer need were modeled by kriging and inverse distance weighting (IDW) techniques. Another approach used was based on lime and fertilizer recommendation considering the paddocks as the minimum management unit. The results showed that geostatistics and GIS were useful tools for revealing soil spatial variability and supporting management strategies. Soil nutrients were used to classify the soil spatial distribution map and design site-specific lime and fertilizer application zones. Spatial analyses of crop needs and requirement can provide management tools for avoiding potential environmental problems, caused by unbalanced nutrient supplies.
- Type
- Data analysis and Geostatistics
- Information
- Copyright
- © The Animal Consortium 2017
References
- 13
- Cited by