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<p>Understanding the spatial variability of soil properties is fundamental for implementation of precision nutrient management in organic farming systems. The present study was conducted in 2022–2023 at the 56.25&#xa0;ha organic farm in the Trans-Indo-Gangetic Plains of western India, to characterize and map spatial distribution of soil micronutrients. A total of 89 surface soil samples were collected and analyzed for various physico-chemical properties and micronutrient concentrations, including zinc, manganese, iron, copper, lead, cadmium and nickel. Soils exhibited neutral to alkaline reactions with variable salinity, characterized by moderate to high contents of soil organic carbon, available phosphorus and potassium, but comparatively low nitrogen availability. Micronutrient concentrations were generally adequate, except for zinc, which showed localized deficiencies. Geostatistical analysis, employing semivariogram modelling and ordinary kriging, revealed distinct spatial patterns: Gaussian model provided the best fit for zinc, manganese and lead, whereas exponential model more accurately characterized spatial variability of iron, copper, cadmium and nickel. Nugget values varied from 0 to 6.13 while sill values varied from 0.01 to 35.78. Semivariogram ranges varied markedly from 142.64 to 1521.47&#xa0;m. Zinc and manganese exhibited moderate spatial dependence, whereas iron, copper, lead, cadmium and nickel exhibited strong spatial dependence. Principal component analysis extracted four principal components explaining 73.49% of total variance, identifying soil organic carbon as the most influential factor governing nutrient availability. Fuzzy c-means clustering delineated three distinct soil management zones exhibiting significant fertility contrasts. Integrated geostatistical and multivariate approach proved effective for guiding site-specific management and promoting sustainable organic farming in semi-arid regions.</p>

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Geostatistical and Multivariate Characterization of Micronutrient Deficiency and Heavy Metal Contamination in Semi-Arid Soils of Hisar, Haryana, India

  • 期刊论文

  • 发表日期：

    2026年6月15日

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  • Ankit Singh,
  • Narender Yadav,
  • Dinesh Tomar,
  • Krisanu Golui,
  • Jyoti Sheoran,
  • Pardeep Phogat,
  • Shekhar Acharya

摘要

Understanding the spatial variability of soil properties is fundamental for implementation of precision nutrient management in organic farming systems. The present study was conducted in 2022–2023 at the 56.25 ha organic farm in the Trans-Indo-Gangetic Plains of western India, to characterize and map spatial distribution of soil micronutrients. A total of 89 surface soil samples were collected and analyzed for various physico-chemical properties and micronutrient concentrations, including zinc, manganese, iron, copper, lead, cadmium and nickel. Soils exhibited neutral to alkaline reactions with variable salinity, characterized by moderate to high contents of soil organic carbon, available phosphorus and potassium, but comparatively low nitrogen availability. Micronutrient concentrations were generally adequate, except for zinc, which showed localized deficiencies. Geostatistical analysis, employing semivariogram modelling and ordinary kriging, revealed distinct spatial patterns: Gaussian model provided the best fit for zinc, manganese and lead, whereas exponential model more accurately characterized spatial variability of iron, copper, cadmium and nickel. Nugget values varied from 0 to 6.13 while sill values varied from 0.01 to 35.78. Semivariogram ranges varied markedly from 142.64 to 1521.47 m. Zinc and manganese exhibited moderate spatial dependence, whereas iron, copper, lead, cadmium and nickel exhibited strong spatial dependence. Principal component analysis extracted four principal components explaining 73.49% of total variance, identifying soil organic carbon as the most influential factor governing nutrient availability. Fuzzy c-means clustering delineated three distinct soil management zones exhibiting significant fertility contrasts. Integrated geostatistical and multivariate approach proved effective for guiding site-specific management and promoting sustainable organic farming in semi-arid regions.