RESEARCH PAPER
Management systems impact on soil spatial variability under semi-arid climates conditions
1
Department of Soil Science and Plant Nutrition, Faculty of Agriculture, Igdir University, Turkey
Final revision date: 2022-10-03
Acceptance date: 2022-10-10
Publication date: 2022-12-05
Corresponding author
Serdar Sari
Department of Soil Science and Plant Nutrition, Faculty of Agriculture, Igdir University, 76000, Iğdır, Turkey
Department of Soil Science and Plant Nutrition, Faculty of Agriculture, Igdir University, 76000, Iğdır, Turkey
Int. Agrophys. 2022, 36(4): 361-373
HIGHLIGHTS
- Plant patterns was effective on soil properties
- SOM, ρb, AS and PR were significantly influenced by plant pattern and tillage.
- Alfalfa led to high PR and SOM
- Tillage caused a decrease in SOM
KEYWORDS
TOPICS
ABSTRACT
Cropping systems are one of the most important living components affecting the surface soil spatial variability. Composite disturbed and undisturbed soils were collected (intersections of the grid system, 50 x 50 m) at 0-20 and 20-40 cm depths under maize (Zea mays), wheat (Triticum aestivum), and alfalfa (Medicago sativa L.) cropping systems from the farmer’s field, in the Igdir Plain, eastern Turkey. Soil spatial variability was based on clay, silt, and sand, calcium carbonate (CaCO3) and organic matter, the pH, electrical conductivity, bulk density, aggregate stability and penetration resistance of the soil were determined. The data was analysed using both statistical and geostatistical approaches and suggested that the spatial distribution model and spatial dependence level varied significantly within the farm soils. Exponential, Gaussian, and spherical semivariogram models were found to be the best models to explain the spatial structure of the soil properties. Clay and sand, electrical conductivity, soil organic matter, bulk density, aggregate stability, and penetration resistance were found to be significantly different between the soil depths. The soil property ranges of the variogram were between 58.5 and 305.9 m and showed a moderate to strong spatial dependence. The development of spatial distribution maps for the soil variables analysed provided for a comparison to be made between the various soil properties and raises the possibility of understanding heterogeneity within the farm in the form of a regional representation. It may be concluded that these maps will assist in determining site-specific soil use and identifying the impact of soil management.
CONFLICT OF INTEREST
The authors declare no conflict of interest
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