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Plant Science Today (PST)

Research Articles

Vol. 12 No. sp1 (2025): Recent Advances in Agriculture by Young Minds - II

Soil fertility status and assessment of nutrient soil quality index of Ganasandra micro-watershed using GIS-based geospatial tool

DOI
https://doi.org/10.14719/pst.10186
Submitted
23 June 2025
Published
31-08-2025 — Updated on 29-09-2025
Versions

Abstract

Despite growing concerns about sustainable land management, limited studies have comprehensively evaluated soil fertility and spatial variability of nutrient soil quality at the micro-watershed level using geospatial techniques. The current research (2023-24) aimed to assess nutrient levels, soil health and the spatial variability of soil fertility within the Ganasandra micro-watershed, a component of the Naganahalli sub-watershed in Nagamangala taluk, Mandya district, Karnataka, using geospatial methods. Statistical evaluation of analytical data was performed using parameters such as range, mean and standard deviation. The soil was found to be slightly to strongly alkaline and nonsaline. Organic carbon levels ranged from low to medium; nitrogen and phosphorus availability were moderate; potassium was high and sulfur levels ranged from low to moderate. Diethylene triamine pentaacetic acid (DTPA) extractable micronutrients analysis indicated that half of the samples lacked sufficient zinc and iron, whereas copper and manganese concentrations were adequate. Shortages of N (nitrogen), P (phosphorus), S (sulphur), Zn (zinc) and Fe (iron) were identified as significant limitations to soil fertility. Principal component analysis (PCA) was employed to obtain the minimum data set (MDS) from the assessed soil parameters. Essential factors affecting soil quality include pH, organic carbon content and the availability of nitrogen and zinc. Three principal components with eigenvalues exceeding 1 accounted for 73.00 % of the overall variance. The soil quality index (SQI) ranged from 0.10 to 0.62. The study established that SQI, derived through grid sampling at a 320 m scale, successfully reflected spatial dependence through ordinary kriging and enabled the creation of thematic maps for soil management at the micro-watershed level. The SQI map showed that 46.63 % of the region was classified as low to very low soil quality, 22.79 % as medium and 31.32 % as high-quality categories.

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