2012Journal of Integrative AgricultureOpen access

Geostatistical Assessment of the Spatial Distribution of Some Chemical Properties in Calcareous Soils

Asma Najafian, M. Dayani, Hamidreza Motaghian, Habibolah Nadian

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Abstract

Spatial patterns of soil fertility parameters and other extrinsic factors need to be identified to develop farming practices that match agricultural inputs with local crop needs. Little is known about the spatial structure of nutrition in Iran. The present study was conducted in a 132-ha field located in central Iran. Soil samples were collected at 0–30 cm depth and were then analyzed for total nitrogen (N), available phosphorus (P), available potassium (K), available copper (Cu), available zinc (Zn), available iron (Fe) and available manganese (Mn). The results showed that the contents of soil organic matter, Cu and Zn in Marvdasht's farms were low. The spatial distribution model and spatial dependence level for soil chemical properties varied in the field. N, K, carbonate calcium equivalent (CaCO3) and electrical conductivity (EC) data indicated the existence of moderate spatial dependence. The variograms for other variables revealed stronger spatial structure. The results showed a longer range value for available P (480 m), followed by total N (429 m). The value of other chemical properties values showed a shorter range (128 to 174 m). Clear patchy distribution of N, P, K, Fe, Mn, Cu and Zn were found from their spatial distribution maps. This proved that sampling strategy for estimating variability should be adapted to the different soil chemical properties and field management. Therefore, the spatial variability of soil chemical properties with strong spatial dependence could be readily managed and a site-specific fertilization scheme for precision farming could be easily developed.

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Spatial patterns of soil fertility parameters and other extrinsic factors need to be identified to develop farming practices that match agricultural inputs with local crop needs. Little is known about the spatial structure of nutrition in Iran. The present study was conducted in a 132-ha field located in central Iran. Soil samples were collected at 0–30 cm depth and were then analyzed for total nitrogen (N), available phosphorus (P), available potassium (K), available copper (Cu), available zinc (Zn), available iron (Fe) and available manganese (Mn). The results showed that the contents of soil organic matter, Cu and Zn in Marvdasht's farms were low. The spatial distribution model and spatial dependence level for soil chemical properties varied in the field. N, K, carbonate calcium equivalent (CaCO3) and electrical conductivity (EC) data indicated the existence of moderate spatial dependence. The variograms for other variables revealed stronger spatial structure. The results showed a longer range value for available P (480 m), followed by total N (429 m). The value of other chemical properties values showed a shorter range (128 to 174 m). Clear patchy distribution of N, P, K, Fe, Mn, Cu and Zn were found from their spatial distribution maps. This proved that sampling strategy for estimating variability should be adapted to the different soil chemical properties and field management. Therefore, the spatial variability of soil chemical properties with strong spatial dependence could be readily managed and a site-specific fertilization scheme for precision farming could be easily developed.

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Available abstract

Spatial patterns of soil fertility parameters and other extrinsic factors need to be identified to develop farming practices that match agricultural inputs with local crop needs. Little is known about the spatial structure of nutrition in Iran. The present study was conducted in a 132-ha field located in central Iran. Soil samples were collected at 0–30 cm depth and were then analyzed for total nitrogen (N), available phosphorus (P), available potassium (K), available copper (Cu), available zinc (Zn), available iron (Fe) and available manganese (Mn). The results showed that the contents of soil organic matter, Cu and Zn in Marvdasht's farms were low. The spatial distribution model and spatial dependence level for soil chemical properties varied in the field. N, K, carbonate calcium equivalent (CaCO3) and electrical conductivity (EC) data indicated the existence of moderate spatial dependence. The variograms for other variables revealed stronger spatial structure. The results showed a longer range value for available P (480 m), followed by total N (429 m). The value of other chemical properties values showed a shorter range (128 to 174 m). Clear patchy distribution of N, P, K, Fe, Mn, Cu and Zn were found from their spatial distribution maps. This proved that sampling strategy for estimating variability should be adapted to the different soil chemical properties and field management. Therefore, the spatial variability of soil chemical properties with strong spatial dependence could be readily managed and a site-specific fertilization scheme for precision farming could be easily developed.

Key concepts: Spatial variability, Spatial distribution, Calcareous, Soil fertility, Soil science, Geostatistics, Soil test, Soil water

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