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Characterization of spatial variability of vertisol micronutrients by geostatistical techniques in Deccan Plateau of India

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In vertisols, accounting for the spatial variability of micronutrients is important for sustainable agriculture. In this study, the assessment of spatial variability maps is carried out by the geostatistical technique in SpaceStat 4.0®. A total of 68 random soil samples were collected from small-scale agricultural lands from Kalaburagi, Karnataka, India. The chemical analysis for iron (Fe), manganese (Mn), copper (Cu), and zinc (Zn) was carried out in microwave plasma-atomic emission spectroscopy. The coefficient of variation (CV) showed different micronutrients variability (CV > 35%). The significant correlation is among Cu with Fe and Mn (r = 0.753 and 0.258, respectively). The Box–Cox transformation converted the raw data to normal distribution efficiently. Spherical semivariogram model defined the spatial structure for all micronutrients. The nugget/sill ratio specifies that the Zn showed strong spatial dependence and rest micronutrients moderate. Ordinary kriging is applied for generating maps. The spatial variability maps exhibited different distribution pattern; maps generated are utilized as initial guidance for site-specific management practices and the amount of fertilizer application rate planned in the vertisols. The obtained range and spatial distribution maps act as the baseline in this region for administration planners.

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The authors are thankful for Dr. Pierre Goovaerts, Chief Scientist in BioMedware for providing adequate guidelines in using SpaceStat Software and providing a licensed version for analysis. We thank Dr. M.S. Nagaraja, University of Horticultural Science, Bagalkot for providing laboratory facilities to carry out chemical analysis.

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Correspondence to Vinod Tamburi.

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Tamburi, V., Shetty, A. & Shrihari, S. Characterization of spatial variability of vertisol micronutrients by geostatistical techniques in Deccan Plateau of India. Model. Earth Syst. Environ. 6, 173–182 (2020). https://doi.org/10.1007/s40808-019-00669-w

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  • Vertisols
  • Micronutrients
  • Geostatistics
  • Ordinary kriging
  • Spatial variability